From 610384c63dab9df04a2f9b9e80817999a420440f Mon Sep 17 00:00:00 2001 From: Owl Bot Date: Fri, 16 Jul 2021 20:49:08 +0000 Subject: [PATCH 1/4] feat: add standard sql table type, update scalar type enums Committer: @shollyman PiperOrigin-RevId: 385164907 Source-Link: https://github.com/googleapis/googleapis/commit/9ae82b82bdb634058af4b2bafe53c37b8566f68d Source-Link: https://github.com/googleapis/googleapis-gen/commit/bc1724b0b544bdcd9b5b2f4e3d8676f75adacfdf --- owl-bot-staging/v2/.coveragerc | 17 + owl-bot-staging/v2/MANIFEST.in | 2 + owl-bot-staging/v2/README.rst | 49 + .../v2/docs/bigquery_v2/model_service.rst | 6 + .../v2/docs/bigquery_v2/services.rst | 6 + owl-bot-staging/v2/docs/bigquery_v2/types.rst | 7 + owl-bot-staging/v2/docs/conf.py | 376 ++++ owl-bot-staging/v2/docs/index.rst | 7 + .../v2/google/cloud/bigquery/__init__.py | 49 + .../v2/google/cloud/bigquery/py.typed | 2 + .../v2/google/cloud/bigquery_v2/__init__.py | 50 + .../cloud/bigquery_v2/gapic_metadata.json | 63 + .../v2/google/cloud/bigquery_v2/py.typed | 2 + .../cloud/bigquery_v2/services/__init__.py | 15 + .../services/model_service/__init__.py | 22 + .../services/model_service/async_client.py | 510 +++++ .../services/model_service/client.py | 688 +++++++ .../model_service/transports/__init__.py | 33 + .../services/model_service/transports/base.py | 215 ++ .../services/model_service/transports/grpc.py | 332 +++ .../model_service/transports/grpc_asyncio.py | 336 +++ .../cloud/bigquery_v2/types/__init__.py | 54 + .../bigquery_v2/types/encryption_config.py | 47 + .../google/cloud/bigquery_v2/types/model.py | 1821 +++++++++++++++++ .../bigquery_v2/types/model_reference.py | 56 + .../cloud/bigquery_v2/types/standard_sql.py | 141 ++ .../bigquery_v2/types/table_reference.py | 58 + owl-bot-staging/v2/mypy.ini | 3 + owl-bot-staging/v2/noxfile.py | 132 ++ .../v2/scripts/fixup_bigquery_v2_keywords.py | 179 ++ owl-bot-staging/v2/setup.py | 53 + owl-bot-staging/v2/tests/__init__.py | 16 + owl-bot-staging/v2/tests/unit/__init__.py | 16 + .../v2/tests/unit/gapic/__init__.py | 16 + .../tests/unit/gapic/bigquery_v2/__init__.py | 16 + .../gapic/bigquery_v2/test_model_service.py | 1712 ++++++++++++++++ 36 files changed, 7107 insertions(+) create mode 100644 owl-bot-staging/v2/.coveragerc create mode 100644 owl-bot-staging/v2/MANIFEST.in create mode 100644 owl-bot-staging/v2/README.rst create mode 100644 owl-bot-staging/v2/docs/bigquery_v2/model_service.rst create mode 100644 owl-bot-staging/v2/docs/bigquery_v2/services.rst create mode 100644 owl-bot-staging/v2/docs/bigquery_v2/types.rst create mode 100644 owl-bot-staging/v2/docs/conf.py create mode 100644 owl-bot-staging/v2/docs/index.rst create mode 100644 owl-bot-staging/v2/google/cloud/bigquery/__init__.py create mode 100644 owl-bot-staging/v2/google/cloud/bigquery/py.typed create mode 100644 owl-bot-staging/v2/google/cloud/bigquery_v2/__init__.py create mode 100644 owl-bot-staging/v2/google/cloud/bigquery_v2/gapic_metadata.json create mode 100644 owl-bot-staging/v2/google/cloud/bigquery_v2/py.typed create mode 100644 owl-bot-staging/v2/google/cloud/bigquery_v2/services/__init__.py create mode 100644 owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/__init__.py create mode 100644 owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/async_client.py create mode 100644 owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/client.py create mode 100644 owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/transports/__init__.py create mode 100644 owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/transports/base.py create mode 100644 owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/transports/grpc.py create mode 100644 owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/transports/grpc_asyncio.py create mode 100644 owl-bot-staging/v2/google/cloud/bigquery_v2/types/__init__.py create mode 100644 owl-bot-staging/v2/google/cloud/bigquery_v2/types/encryption_config.py create mode 100644 owl-bot-staging/v2/google/cloud/bigquery_v2/types/model.py create mode 100644 owl-bot-staging/v2/google/cloud/bigquery_v2/types/model_reference.py create mode 100644 owl-bot-staging/v2/google/cloud/bigquery_v2/types/standard_sql.py create mode 100644 owl-bot-staging/v2/google/cloud/bigquery_v2/types/table_reference.py create mode 100644 owl-bot-staging/v2/mypy.ini create mode 100644 owl-bot-staging/v2/noxfile.py create mode 100644 owl-bot-staging/v2/scripts/fixup_bigquery_v2_keywords.py create mode 100644 owl-bot-staging/v2/setup.py create mode 100644 owl-bot-staging/v2/tests/__init__.py create mode 100644 owl-bot-staging/v2/tests/unit/__init__.py create mode 100644 owl-bot-staging/v2/tests/unit/gapic/__init__.py create mode 100644 owl-bot-staging/v2/tests/unit/gapic/bigquery_v2/__init__.py create mode 100644 owl-bot-staging/v2/tests/unit/gapic/bigquery_v2/test_model_service.py diff --git a/owl-bot-staging/v2/.coveragerc b/owl-bot-staging/v2/.coveragerc new file mode 100644 index 000000000..33ea00ba9 --- /dev/null +++ b/owl-bot-staging/v2/.coveragerc @@ -0,0 +1,17 @@ +[run] +branch = True + +[report] +show_missing = True +omit = + google/cloud/bigquery/__init__.py +exclude_lines = + # Re-enable the standard pragma + pragma: NO COVER + # Ignore debug-only repr + def __repr__ + # Ignore pkg_resources exceptions. + # This is added at the module level as a safeguard for if someone + # generates the code and tries to run it without pip installing. This + # makes it virtually impossible to test properly. + except pkg_resources.DistributionNotFound diff --git a/owl-bot-staging/v2/MANIFEST.in b/owl-bot-staging/v2/MANIFEST.in new file mode 100644 index 000000000..df96b1d74 --- /dev/null +++ b/owl-bot-staging/v2/MANIFEST.in @@ -0,0 +1,2 @@ +recursive-include google/cloud/bigquery *.py +recursive-include google/cloud/bigquery_v2 *.py diff --git a/owl-bot-staging/v2/README.rst b/owl-bot-staging/v2/README.rst new file mode 100644 index 000000000..402efe90f --- /dev/null +++ b/owl-bot-staging/v2/README.rst @@ -0,0 +1,49 @@ +Python Client for Google Cloud Bigquery API +================================================= + +Quick Start +----------- + +In order to use this library, you first need to go through the following steps: + +1. `Select or create a Cloud Platform project.`_ +2. `Enable billing for your project.`_ +3. Enable the Google Cloud Bigquery API. +4. `Setup Authentication.`_ + +.. _Select or create a Cloud Platform project.: https://console.cloud.google.com/project +.. _Enable billing for your project.: https://cloud.google.com/billing/docs/how-to/modify-project#enable_billing_for_a_project +.. _Setup Authentication.: https://googleapis.dev/python/google-api-core/latest/auth.html + +Installation +~~~~~~~~~~~~ + +Install this library in a `virtualenv`_ using pip. `virtualenv`_ is a tool to +create isolated Python environments. The basic problem it addresses is one of +dependencies and versions, and indirectly permissions. + +With `virtualenv`_, it's possible to install this library without needing system +install permissions, and without clashing with the installed system +dependencies. + +.. _`virtualenv`: https://virtualenv.pypa.io/en/latest/ + + +Mac/Linux +^^^^^^^^^ + +.. code-block:: console + + python3 -m venv + source /bin/activate + /bin/pip install /path/to/library + + +Windows +^^^^^^^ + +.. code-block:: console + + python3 -m venv + \Scripts\activate + \Scripts\pip.exe install \path\to\library diff --git a/owl-bot-staging/v2/docs/bigquery_v2/model_service.rst b/owl-bot-staging/v2/docs/bigquery_v2/model_service.rst new file mode 100644 index 000000000..65b1e5e5f --- /dev/null +++ b/owl-bot-staging/v2/docs/bigquery_v2/model_service.rst @@ -0,0 +1,6 @@ +ModelService +------------------------------ + +.. automodule:: google.cloud.bigquery_v2.services.model_service + :members: + :inherited-members: diff --git a/owl-bot-staging/v2/docs/bigquery_v2/services.rst b/owl-bot-staging/v2/docs/bigquery_v2/services.rst new file mode 100644 index 000000000..f8159a448 --- /dev/null +++ b/owl-bot-staging/v2/docs/bigquery_v2/services.rst @@ -0,0 +1,6 @@ +Services for Google Cloud Bigquery v2 API +========================================= +.. toctree:: + :maxdepth: 2 + + model_service diff --git a/owl-bot-staging/v2/docs/bigquery_v2/types.rst b/owl-bot-staging/v2/docs/bigquery_v2/types.rst new file mode 100644 index 000000000..c36a83e0b --- /dev/null +++ b/owl-bot-staging/v2/docs/bigquery_v2/types.rst @@ -0,0 +1,7 @@ +Types for Google Cloud Bigquery v2 API +====================================== + +.. automodule:: google.cloud.bigquery_v2.types + :members: + :undoc-members: + :show-inheritance: diff --git a/owl-bot-staging/v2/docs/conf.py b/owl-bot-staging/v2/docs/conf.py new file mode 100644 index 000000000..73ab15fdc --- /dev/null +++ b/owl-bot-staging/v2/docs/conf.py @@ -0,0 +1,376 @@ +# -*- coding: utf-8 -*- +# Copyright 2020 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# +# +# google-cloud-bigquery documentation build configuration file +# +# This file is execfile()d with the current directory set to its +# containing dir. +# +# Note that not all possible configuration values are present in this +# autogenerated file. +# +# All configuration values have a default; values that are commented out +# serve to show the default. + +import sys +import os +import shlex + +# If extensions (or modules to document with autodoc) are in another directory, +# add these directories to sys.path here. If the directory is relative to the +# documentation root, use os.path.abspath to make it absolute, like shown here. +sys.path.insert(0, os.path.abspath("..")) + +__version__ = "0.1.0" + +# -- General configuration ------------------------------------------------ + +# If your documentation needs a minimal Sphinx version, state it here. +needs_sphinx = "1.6.3" + +# Add any Sphinx extension module names here, as strings. They can be +# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom +# ones. +extensions = [ + "sphinx.ext.autodoc", + "sphinx.ext.autosummary", + "sphinx.ext.intersphinx", + "sphinx.ext.coverage", + "sphinx.ext.napoleon", + "sphinx.ext.todo", + "sphinx.ext.viewcode", +] + +# autodoc/autosummary flags +autoclass_content = "both" +autodoc_default_flags = ["members"] +autosummary_generate = True + + +# Add any paths that contain templates here, relative to this directory. +templates_path = ["_templates"] + +# Allow markdown includes (so releases.md can include CHANGLEOG.md) +# http://www.sphinx-doc.org/en/master/markdown.html +source_parsers = {".md": "recommonmark.parser.CommonMarkParser"} + +# The suffix(es) of source filenames. +# You can specify multiple suffix as a list of string: +source_suffix = [".rst", ".md"] + +# The encoding of source files. +# source_encoding = 'utf-8-sig' + +# The master toctree document. +master_doc = "index" + +# General information about the project. +project = u"google-cloud-bigquery" +copyright = u"2020, Google, LLC" +author = u"Google APIs" # TODO: autogenerate this bit + +# The version info for the project you're documenting, acts as replacement for +# |version| and |release|, also used in various other places throughout the +# built documents. +# +# The full version, including alpha/beta/rc tags. +release = __version__ +# The short X.Y version. +version = ".".join(release.split(".")[0:2]) + +# The language for content autogenerated by Sphinx. Refer to documentation +# for a list of supported languages. +# +# This is also used if you do content translation via gettext catalogs. +# Usually you set "language" from the command line for these cases. +language = None + +# There are two options for replacing |today|: either, you set today to some +# non-false value, then it is used: +# today = '' +# Else, today_fmt is used as the format for a strftime call. +# today_fmt = '%B %d, %Y' + +# List of patterns, relative to source directory, that match files and +# directories to ignore when looking for source files. +exclude_patterns = ["_build"] + +# The reST default role (used for this markup: `text`) to use for all +# documents. +# default_role = None + +# If true, '()' will be appended to :func: etc. cross-reference text. +# add_function_parentheses = True + +# If true, the current module name will be prepended to all description +# unit titles (such as .. function::). +# add_module_names = True + +# If true, sectionauthor and moduleauthor directives will be shown in the +# output. They are ignored by default. +# show_authors = False + +# The name of the Pygments (syntax highlighting) style to use. +pygments_style = "sphinx" + +# A list of ignored prefixes for module index sorting. +# modindex_common_prefix = [] + +# If true, keep warnings as "system message" paragraphs in the built documents. +# keep_warnings = False + +# If true, `todo` and `todoList` produce output, else they produce nothing. +todo_include_todos = True + + +# -- Options for HTML output ---------------------------------------------- + +# The theme to use for HTML and HTML Help pages. See the documentation for +# a list of builtin themes. +html_theme = "alabaster" + +# Theme options are theme-specific and customize the look and feel of a theme +# further. For a list of options available for each theme, see the +# documentation. +html_theme_options = { + "description": "Google Cloud Client Libraries for Python", + "github_user": "googleapis", + "github_repo": "google-cloud-python", + "github_banner": True, + "font_family": "'Roboto', Georgia, sans", + "head_font_family": "'Roboto', Georgia, serif", + "code_font_family": "'Roboto Mono', 'Consolas', monospace", +} + +# Add any paths that contain custom themes here, relative to this directory. +# html_theme_path = [] + +# The name for this set of Sphinx documents. If None, it defaults to +# " v documentation". +# html_title = None + +# A shorter title for the navigation bar. Default is the same as html_title. +# html_short_title = None + +# The name of an image file (relative to this directory) to place at the top +# of the sidebar. +# html_logo = None + +# The name of an image file (within the static path) to use as favicon of the +# docs. This file should be a Windows icon file (.ico) being 16x16 or 32x32 +# pixels large. +# html_favicon = None + +# Add any paths that contain custom static files (such as style sheets) here, +# relative to this directory. They are copied after the builtin static files, +# so a file named "default.css" will overwrite the builtin "default.css". +html_static_path = ["_static"] + +# Add any extra paths that contain custom files (such as robots.txt or +# .htaccess) here, relative to this directory. These files are copied +# directly to the root of the documentation. +# html_extra_path = [] + +# If not '', a 'Last updated on:' timestamp is inserted at every page bottom, +# using the given strftime format. +# html_last_updated_fmt = '%b %d, %Y' + +# If true, SmartyPants will be used to convert quotes and dashes to +# typographically correct entities. +# html_use_smartypants = True + +# Custom sidebar templates, maps document names to template names. +# html_sidebars = {} + +# Additional templates that should be rendered to pages, maps page names to +# template names. +# html_additional_pages = {} + +# If false, no module index is generated. +# html_domain_indices = True + +# If false, no index is generated. +# html_use_index = True + +# If true, the index is split into individual pages for each letter. +# html_split_index = False + +# If true, links to the reST sources are added to the pages. +# html_show_sourcelink = True + +# If true, "Created using Sphinx" is shown in the HTML footer. Default is True. +# html_show_sphinx = True + +# If true, "(C) Copyright ..." is shown in the HTML footer. Default is True. +# html_show_copyright = True + +# If true, an OpenSearch description file will be output, and all pages will +# contain a tag referring to it. The value of this option must be the +# base URL from which the finished HTML is served. +# html_use_opensearch = '' + +# This is the file name suffix for HTML files (e.g. ".xhtml"). +# html_file_suffix = None + +# Language to be used for generating the HTML full-text search index. +# Sphinx supports the following languages: +# 'da', 'de', 'en', 'es', 'fi', 'fr', 'hu', 'it', 'ja' +# 'nl', 'no', 'pt', 'ro', 'ru', 'sv', 'tr' +# html_search_language = 'en' + +# A dictionary with options for the search language support, empty by default. +# Now only 'ja' uses this config value +# html_search_options = {'type': 'default'} + +# The name of a javascript file (relative to the configuration directory) that +# implements a search results scorer. If empty, the default will be used. +# html_search_scorer = 'scorer.js' + +# Output file base name for HTML help builder. +htmlhelp_basename = "google-cloud-bigquery-doc" + +# -- Options for warnings ------------------------------------------------------ + + +suppress_warnings = [ + # Temporarily suppress this to avoid "more than one target found for + # cross-reference" warning, which are intractable for us to avoid while in + # a mono-repo. + # See https://github.com/sphinx-doc/sphinx/blob + # /2a65ffeef5c107c19084fabdd706cdff3f52d93c/sphinx/domains/python.py#L843 + "ref.python" +] + +# -- Options for LaTeX output --------------------------------------------- + +latex_elements = { + # The paper size ('letterpaper' or 'a4paper'). + # 'papersize': 'letterpaper', + # The font size ('10pt', '11pt' or '12pt'). + # 'pointsize': '10pt', + # Additional stuff for the LaTeX preamble. + # 'preamble': '', + # Latex figure (float) alignment + # 'figure_align': 'htbp', +} + +# Grouping the document tree into LaTeX files. List of tuples +# (source start file, target name, title, +# author, documentclass [howto, manual, or own class]). +latex_documents = [ + ( + master_doc, + "google-cloud-bigquery.tex", + u"google-cloud-bigquery Documentation", + author, + "manual", + ) +] + +# The name of an image file (relative to this directory) to place at the top of +# the title page. +# latex_logo = None + +# For "manual" documents, if this is true, then toplevel headings are parts, +# not chapters. +# latex_use_parts = False + +# If true, show page references after internal links. +# latex_show_pagerefs = False + +# If true, show URL addresses after external links. +# latex_show_urls = False + +# Documents to append as an appendix to all manuals. +# latex_appendices = [] + +# If false, no module index is generated. +# latex_domain_indices = True + + +# -- Options for manual page output --------------------------------------- + +# One entry per manual page. List of tuples +# (source start file, name, description, authors, manual section). +man_pages = [ + ( + master_doc, + "google-cloud-bigquery", + u"Google Cloud Bigquery Documentation", + [author], + 1, + ) +] + +# If true, show URL addresses after external links. +# man_show_urls = False + + +# -- Options for Texinfo output ------------------------------------------- + +# Grouping the document tree into Texinfo files. List of tuples +# (source start file, target name, title, author, +# dir menu entry, description, category) +texinfo_documents = [ + ( + master_doc, + "google-cloud-bigquery", + u"google-cloud-bigquery Documentation", + author, + "google-cloud-bigquery", + "GAPIC library for Google Cloud Bigquery API", + "APIs", + ) +] + +# Documents to append as an appendix to all manuals. +# texinfo_appendices = [] + +# If false, no module index is generated. +# texinfo_domain_indices = True + +# How to display URL addresses: 'footnote', 'no', or 'inline'. +# texinfo_show_urls = 'footnote' + +# If true, do not generate a @detailmenu in the "Top" node's menu. +# texinfo_no_detailmenu = False + + +# Example configuration for intersphinx: refer to the Python standard library. +intersphinx_mapping = { + "python": ("http://python.readthedocs.org/en/latest/", None), + "gax": ("https://gax-python.readthedocs.org/en/latest/", None), + "google-auth": ("https://google-auth.readthedocs.io/en/stable", None), + "google-gax": ("https://gax-python.readthedocs.io/en/latest/", None), + "google.api_core": ("https://googleapis.dev/python/google-api-core/latest/", None), + "grpc": ("https://grpc.io/grpc/python/", None), + "requests": ("http://requests.kennethreitz.org/en/stable/", None), + "proto": ("https://proto-plus-python.readthedocs.io/en/stable", None), + "protobuf": ("https://googleapis.dev/python/protobuf/latest/", None), +} + + +# Napoleon settings +napoleon_google_docstring = True +napoleon_numpy_docstring = True +napoleon_include_private_with_doc = False +napoleon_include_special_with_doc = True +napoleon_use_admonition_for_examples = False +napoleon_use_admonition_for_notes = False +napoleon_use_admonition_for_references = False +napoleon_use_ivar = False +napoleon_use_param = True +napoleon_use_rtype = True diff --git a/owl-bot-staging/v2/docs/index.rst b/owl-bot-staging/v2/docs/index.rst new file mode 100644 index 000000000..ef9072101 --- /dev/null +++ b/owl-bot-staging/v2/docs/index.rst @@ -0,0 +1,7 @@ +API Reference +------------- +.. toctree:: + :maxdepth: 2 + + bigquery_v2/services + bigquery_v2/types diff --git a/owl-bot-staging/v2/google/cloud/bigquery/__init__.py b/owl-bot-staging/v2/google/cloud/bigquery/__init__.py new file mode 100644 index 000000000..a2b0edcd8 --- /dev/null +++ b/owl-bot-staging/v2/google/cloud/bigquery/__init__.py @@ -0,0 +1,49 @@ +# -*- coding: utf-8 -*- +# Copyright 2020 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + +from google.cloud.bigquery_v2.services.model_service.client import ModelServiceClient +from google.cloud.bigquery_v2.services.model_service.async_client import ModelServiceAsyncClient + +from google.cloud.bigquery_v2.types.encryption_config import EncryptionConfiguration +from google.cloud.bigquery_v2.types.model import DeleteModelRequest +from google.cloud.bigquery_v2.types.model import GetModelRequest +from google.cloud.bigquery_v2.types.model import ListModelsRequest +from google.cloud.bigquery_v2.types.model import ListModelsResponse +from google.cloud.bigquery_v2.types.model import Model +from google.cloud.bigquery_v2.types.model import PatchModelRequest +from google.cloud.bigquery_v2.types.model_reference import ModelReference +from google.cloud.bigquery_v2.types.standard_sql import StandardSqlDataType +from google.cloud.bigquery_v2.types.standard_sql import StandardSqlField +from google.cloud.bigquery_v2.types.standard_sql import StandardSqlStructType +from google.cloud.bigquery_v2.types.standard_sql import StandardSqlTableType +from google.cloud.bigquery_v2.types.table_reference import TableReference + +__all__ = ('ModelServiceClient', + 'ModelServiceAsyncClient', + 'EncryptionConfiguration', + 'DeleteModelRequest', + 'GetModelRequest', + 'ListModelsRequest', + 'ListModelsResponse', + 'Model', + 'PatchModelRequest', + 'ModelReference', + 'StandardSqlDataType', + 'StandardSqlField', + 'StandardSqlStructType', + 'StandardSqlTableType', + 'TableReference', +) diff --git a/owl-bot-staging/v2/google/cloud/bigquery/py.typed b/owl-bot-staging/v2/google/cloud/bigquery/py.typed new file mode 100644 index 000000000..e73777993 --- /dev/null +++ b/owl-bot-staging/v2/google/cloud/bigquery/py.typed @@ -0,0 +1,2 @@ +# Marker file for PEP 561. +# The google-cloud-bigquery package uses inline types. diff --git a/owl-bot-staging/v2/google/cloud/bigquery_v2/__init__.py b/owl-bot-staging/v2/google/cloud/bigquery_v2/__init__.py new file mode 100644 index 000000000..f7aa4a849 --- /dev/null +++ b/owl-bot-staging/v2/google/cloud/bigquery_v2/__init__.py @@ -0,0 +1,50 @@ +# -*- coding: utf-8 -*- +# Copyright 2020 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + +from .services.model_service import ModelServiceClient +from .services.model_service import ModelServiceAsyncClient + +from .types.encryption_config import EncryptionConfiguration +from .types.model import DeleteModelRequest +from .types.model import GetModelRequest +from .types.model import ListModelsRequest +from .types.model import ListModelsResponse +from .types.model import Model +from .types.model import PatchModelRequest +from .types.model_reference import ModelReference +from .types.standard_sql import StandardSqlDataType +from .types.standard_sql import StandardSqlField +from .types.standard_sql import StandardSqlStructType +from .types.standard_sql import StandardSqlTableType +from .types.table_reference import TableReference + +__all__ = ( + 'ModelServiceAsyncClient', +'DeleteModelRequest', +'EncryptionConfiguration', +'GetModelRequest', +'ListModelsRequest', +'ListModelsResponse', +'Model', +'ModelReference', +'ModelServiceClient', +'PatchModelRequest', +'StandardSqlDataType', +'StandardSqlField', +'StandardSqlStructType', +'StandardSqlTableType', +'TableReference', +) diff --git a/owl-bot-staging/v2/google/cloud/bigquery_v2/gapic_metadata.json b/owl-bot-staging/v2/google/cloud/bigquery_v2/gapic_metadata.json new file mode 100644 index 000000000..3251a2630 --- /dev/null +++ b/owl-bot-staging/v2/google/cloud/bigquery_v2/gapic_metadata.json @@ -0,0 +1,63 @@ + { + "comment": "This file maps proto services/RPCs to the corresponding library clients/methods", + "language": "python", + "libraryPackage": "google.cloud.bigquery_v2", + "protoPackage": "google.cloud.bigquery.v2", + "schema": "1.0", + "services": { + "ModelService": { + "clients": { + "grpc": { + "libraryClient": "ModelServiceClient", + "rpcs": { + "DeleteModel": { + "methods": [ + "delete_model" + ] + }, + "GetModel": { + "methods": [ + "get_model" + ] + }, + "ListModels": { + "methods": [ + "list_models" + ] + }, + "PatchModel": { + "methods": [ + "patch_model" + ] + } + } + }, + "grpc-async": { + "libraryClient": "ModelServiceAsyncClient", + "rpcs": { + "DeleteModel": { + "methods": [ + "delete_model" + ] + }, + "GetModel": { + "methods": [ + "get_model" + ] + }, + "ListModels": { + "methods": [ + "list_models" + ] + }, + "PatchModel": { + "methods": [ + "patch_model" + ] + } + } + } + } + } + } +} diff --git a/owl-bot-staging/v2/google/cloud/bigquery_v2/py.typed b/owl-bot-staging/v2/google/cloud/bigquery_v2/py.typed new file mode 100644 index 000000000..e73777993 --- /dev/null +++ b/owl-bot-staging/v2/google/cloud/bigquery_v2/py.typed @@ -0,0 +1,2 @@ +# Marker file for PEP 561. +# The google-cloud-bigquery package uses inline types. diff --git a/owl-bot-staging/v2/google/cloud/bigquery_v2/services/__init__.py b/owl-bot-staging/v2/google/cloud/bigquery_v2/services/__init__.py new file mode 100644 index 000000000..4de65971c --- /dev/null +++ b/owl-bot-staging/v2/google/cloud/bigquery_v2/services/__init__.py @@ -0,0 +1,15 @@ +# -*- coding: utf-8 -*- +# Copyright 2020 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# diff --git a/owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/__init__.py b/owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/__init__.py new file mode 100644 index 000000000..5c4d570d1 --- /dev/null +++ b/owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/__init__.py @@ -0,0 +1,22 @@ +# -*- coding: utf-8 -*- +# Copyright 2020 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# +from .client import ModelServiceClient +from .async_client import ModelServiceAsyncClient + +__all__ = ( + 'ModelServiceClient', + 'ModelServiceAsyncClient', +) diff --git a/owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/async_client.py b/owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/async_client.py new file mode 100644 index 000000000..f663b4845 --- /dev/null +++ b/owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/async_client.py @@ -0,0 +1,510 @@ +# -*- coding: utf-8 -*- +# Copyright 2020 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# +from collections import OrderedDict +import functools +import re +from typing import Dict, Sequence, Tuple, Type, Union +import pkg_resources + +import google.api_core.client_options as ClientOptions # type: ignore +from google.api_core import exceptions as core_exceptions # type: ignore +from google.api_core import gapic_v1 # type: ignore +from google.api_core import retry as retries # type: ignore +from google.auth import credentials as ga_credentials # type: ignore +from google.oauth2 import service_account # type: ignore + +from google.cloud.bigquery_v2.types import encryption_config +from google.cloud.bigquery_v2.types import model +from google.cloud.bigquery_v2.types import model as gcb_model +from google.cloud.bigquery_v2.types import model_reference +from google.cloud.bigquery_v2.types import standard_sql +from google.protobuf import wrappers_pb2 # type: ignore +from .transports.base import ModelServiceTransport, DEFAULT_CLIENT_INFO +from .transports.grpc_asyncio import ModelServiceGrpcAsyncIOTransport +from .client import ModelServiceClient + + +class ModelServiceAsyncClient: + """""" + + _client: ModelServiceClient + + DEFAULT_ENDPOINT = ModelServiceClient.DEFAULT_ENDPOINT + DEFAULT_MTLS_ENDPOINT = ModelServiceClient.DEFAULT_MTLS_ENDPOINT + + common_billing_account_path = staticmethod(ModelServiceClient.common_billing_account_path) + parse_common_billing_account_path = staticmethod(ModelServiceClient.parse_common_billing_account_path) + common_folder_path = staticmethod(ModelServiceClient.common_folder_path) + parse_common_folder_path = staticmethod(ModelServiceClient.parse_common_folder_path) + common_organization_path = staticmethod(ModelServiceClient.common_organization_path) + parse_common_organization_path = staticmethod(ModelServiceClient.parse_common_organization_path) + common_project_path = staticmethod(ModelServiceClient.common_project_path) + parse_common_project_path = staticmethod(ModelServiceClient.parse_common_project_path) + common_location_path = staticmethod(ModelServiceClient.common_location_path) + parse_common_location_path = staticmethod(ModelServiceClient.parse_common_location_path) + + @classmethod + def from_service_account_info(cls, info: dict, *args, **kwargs): + """Creates an instance of this client using the provided credentials + info. + + Args: + info (dict): The service account private key info. + args: Additional arguments to pass to the constructor. + kwargs: Additional arguments to pass to the constructor. + + Returns: + ModelServiceAsyncClient: The constructed client. + """ + return ModelServiceClient.from_service_account_info.__func__(ModelServiceAsyncClient, info, *args, **kwargs) # type: ignore + + @classmethod + def from_service_account_file(cls, filename: str, *args, **kwargs): + """Creates an instance of this client using the provided credentials + file. + + Args: + filename (str): The path to the service account private key json + file. + args: Additional arguments to pass to the constructor. + kwargs: Additional arguments to pass to the constructor. + + Returns: + ModelServiceAsyncClient: The constructed client. + """ + return ModelServiceClient.from_service_account_file.__func__(ModelServiceAsyncClient, filename, *args, **kwargs) # type: ignore + + from_service_account_json = from_service_account_file + + @property + def transport(self) -> ModelServiceTransport: + """Returns the transport used by the client instance. + + Returns: + ModelServiceTransport: The transport used by the client instance. + """ + return self._client.transport + + get_transport_class = functools.partial(type(ModelServiceClient).get_transport_class, type(ModelServiceClient)) + + def __init__(self, *, + credentials: ga_credentials.Credentials = None, + transport: Union[str, ModelServiceTransport] = "grpc_asyncio", + client_options: ClientOptions = None, + client_info: gapic_v1.client_info.ClientInfo = DEFAULT_CLIENT_INFO, + ) -> None: + """Instantiates the model service client. + + Args: + credentials (Optional[google.auth.credentials.Credentials]): The + authorization credentials to attach to requests. These + credentials identify the application to the service; if none + are specified, the client will attempt to ascertain the + credentials from the environment. + transport (Union[str, ~.ModelServiceTransport]): The + transport to use. If set to None, a transport is chosen + automatically. + client_options (ClientOptions): Custom options for the client. It + won't take effect if a ``transport`` instance is provided. + (1) The ``api_endpoint`` property can be used to override the + default endpoint provided by the client. GOOGLE_API_USE_MTLS_ENDPOINT + environment variable can also be used to override the endpoint: + "always" (always use the default mTLS endpoint), "never" (always + use the default regular endpoint) and "auto" (auto switch to the + default mTLS endpoint if client certificate is present, this is + the default value). However, the ``api_endpoint`` property takes + precedence if provided. + (2) If GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable + is "true", then the ``client_cert_source`` property can be used + to provide client certificate for mutual TLS transport. If + not provided, the default SSL client certificate will be used if + present. If GOOGLE_API_USE_CLIENT_CERTIFICATE is "false" or not + set, no client certificate will be used. + + Raises: + google.auth.exceptions.MutualTlsChannelError: If mutual TLS transport + creation failed for any reason. + """ + self._client = ModelServiceClient( + credentials=credentials, + transport=transport, + client_options=client_options, + client_info=client_info, + + ) + + async def get_model(self, + request: model.GetModelRequest = None, + *, + project_id: str = None, + dataset_id: str = None, + model_id: str = None, + retry: retries.Retry = gapic_v1.method.DEFAULT, + timeout: float = None, + metadata: Sequence[Tuple[str, str]] = (), + ) -> model.Model: + r"""Gets the specified model resource by model ID. + + Args: + request (:class:`google.cloud.bigquery_v2.types.GetModelRequest`): + The request object. + project_id (:class:`str`): + Required. Project ID of the requested + model. + + This corresponds to the ``project_id`` field + on the ``request`` instance; if ``request`` is provided, this + should not be set. + dataset_id (:class:`str`): + Required. Dataset ID of the requested + model. + + This corresponds to the ``dataset_id`` field + on the ``request`` instance; if ``request`` is provided, this + should not be set. + model_id (:class:`str`): + Required. Model ID of the requested + model. + + This corresponds to the ``model_id`` field + on the ``request`` instance; if ``request`` is provided, this + should not be set. + retry (google.api_core.retry.Retry): Designation of what errors, if any, + should be retried. + timeout (float): The timeout for this request. + metadata (Sequence[Tuple[str, str]]): Strings which should be + sent along with the request as metadata. + + Returns: + google.cloud.bigquery_v2.types.Model: + + """ + # Create or coerce a protobuf request object. + # Sanity check: If we got a request object, we should *not* have + # gotten any keyword arguments that map to the request. + has_flattened_params = any([project_id, dataset_id, model_id]) + if request is not None and has_flattened_params: + raise ValueError("If the `request` argument is set, then none of " + "the individual field arguments should be set.") + + request = model.GetModelRequest(request) + + # If we have keyword arguments corresponding to fields on the + # request, apply these. + if project_id is not None: + request.project_id = project_id + if dataset_id is not None: + request.dataset_id = dataset_id + if model_id is not None: + request.model_id = model_id + + # Wrap the RPC method; this adds retry and timeout information, + # and friendly error handling. + rpc = gapic_v1.method_async.wrap_method( + self._client._transport.get_model, + default_timeout=600.0, + client_info=DEFAULT_CLIENT_INFO, + ) + + # Send the request. + response = await rpc( + request, + retry=retry, + timeout=timeout, + metadata=metadata, + ) + + # Done; return the response. + return response + + async def list_models(self, + request: model.ListModelsRequest = None, + *, + project_id: str = None, + dataset_id: str = None, + max_results: wrappers_pb2.UInt32Value = None, + retry: retries.Retry = gapic_v1.method.DEFAULT, + timeout: float = None, + metadata: Sequence[Tuple[str, str]] = (), + ) -> model.ListModelsResponse: + r"""Lists all models in the specified dataset. Requires + the READER dataset role. + + Args: + request (:class:`google.cloud.bigquery_v2.types.ListModelsRequest`): + The request object. + project_id (:class:`str`): + Required. Project ID of the models to + list. + + This corresponds to the ``project_id`` field + on the ``request`` instance; if ``request`` is provided, this + should not be set. + dataset_id (:class:`str`): + Required. Dataset ID of the models to + list. + + This corresponds to the ``dataset_id`` field + on the ``request`` instance; if ``request`` is provided, this + should not be set. + max_results (:class:`google.protobuf.wrappers_pb2.UInt32Value`): + The maximum number of results to + return in a single response page. + Leverage the page tokens to iterate + through the entire collection. + + This corresponds to the ``max_results`` field + on the ``request`` instance; if ``request`` is provided, this + should not be set. + retry (google.api_core.retry.Retry): Designation of what errors, if any, + should be retried. + timeout (float): The timeout for this request. + metadata (Sequence[Tuple[str, str]]): Strings which should be + sent along with the request as metadata. + + Returns: + google.cloud.bigquery_v2.types.ListModelsResponse: + + """ + # Create or coerce a protobuf request object. + # Sanity check: If we got a request object, we should *not* have + # gotten any keyword arguments that map to the request. + has_flattened_params = any([project_id, dataset_id, max_results]) + if request is not None and has_flattened_params: + raise ValueError("If the `request` argument is set, then none of " + "the individual field arguments should be set.") + + request = model.ListModelsRequest(request) + + # If we have keyword arguments corresponding to fields on the + # request, apply these. + if project_id is not None: + request.project_id = project_id + if dataset_id is not None: + request.dataset_id = dataset_id + if max_results is not None: + request.max_results = max_results + + # Wrap the RPC method; this adds retry and timeout information, + # and friendly error handling. + rpc = gapic_v1.method_async.wrap_method( + self._client._transport.list_models, + default_timeout=600.0, + client_info=DEFAULT_CLIENT_INFO, + ) + + # Send the request. + response = await rpc( + request, + retry=retry, + timeout=timeout, + metadata=metadata, + ) + + # Done; return the response. + return response + + async def patch_model(self, + request: gcb_model.PatchModelRequest = None, + *, + project_id: str = None, + dataset_id: str = None, + model_id: str = None, + model: gcb_model.Model = None, + retry: retries.Retry = gapic_v1.method.DEFAULT, + timeout: float = None, + metadata: Sequence[Tuple[str, str]] = (), + ) -> gcb_model.Model: + r"""Patch specific fields in the specified model. + + Args: + request (:class:`google.cloud.bigquery_v2.types.PatchModelRequest`): + The request object. + project_id (:class:`str`): + Required. Project ID of the model to + patch. + + This corresponds to the ``project_id`` field + on the ``request`` instance; if ``request`` is provided, this + should not be set. + dataset_id (:class:`str`): + Required. Dataset ID of the model to + patch. + + This corresponds to the ``dataset_id`` field + on the ``request`` instance; if ``request`` is provided, this + should not be set. + model_id (:class:`str`): + Required. Model ID of the model to + patch. + + This corresponds to the ``model_id`` field + on the ``request`` instance; if ``request`` is provided, this + should not be set. + model (:class:`google.cloud.bigquery_v2.types.Model`): + Required. Patched model. + Follows RFC5789 patch semantics. Missing + fields are not updated. To clear a + field, explicitly set to default value. + + This corresponds to the ``model`` field + on the ``request`` instance; if ``request`` is provided, this + should not be set. + retry (google.api_core.retry.Retry): Designation of what errors, if any, + should be retried. + timeout (float): The timeout for this request. + metadata (Sequence[Tuple[str, str]]): Strings which should be + sent along with the request as metadata. + + Returns: + google.cloud.bigquery_v2.types.Model: + + """ + # Create or coerce a protobuf request object. + # Sanity check: If we got a request object, we should *not* have + # gotten any keyword arguments that map to the request. + has_flattened_params = any([project_id, dataset_id, model_id, model]) + if request is not None and has_flattened_params: + raise ValueError("If the `request` argument is set, then none of " + "the individual field arguments should be set.") + + request = gcb_model.PatchModelRequest(request) + + # If we have keyword arguments corresponding to fields on the + # request, apply these. + if project_id is not None: + request.project_id = project_id + if dataset_id is not None: + request.dataset_id = dataset_id + if model_id is not None: + request.model_id = model_id + if model is not None: + request.model = model + + # Wrap the RPC method; this adds retry and timeout information, + # and friendly error handling. + rpc = gapic_v1.method_async.wrap_method( + self._client._transport.patch_model, + default_timeout=600.0, + client_info=DEFAULT_CLIENT_INFO, + ) + + # Send the request. + response = await rpc( + request, + retry=retry, + timeout=timeout, + metadata=metadata, + ) + + # Done; return the response. + return response + + async def delete_model(self, + request: model.DeleteModelRequest = None, + *, + project_id: str = None, + dataset_id: str = None, + model_id: str = None, + retry: retries.Retry = gapic_v1.method.DEFAULT, + timeout: float = None, + metadata: Sequence[Tuple[str, str]] = (), + ) -> None: + r"""Deletes the model specified by modelId from the + dataset. + + Args: + request (:class:`google.cloud.bigquery_v2.types.DeleteModelRequest`): + The request object. + project_id (:class:`str`): + Required. Project ID of the model to + delete. + + This corresponds to the ``project_id`` field + on the ``request`` instance; if ``request`` is provided, this + should not be set. + dataset_id (:class:`str`): + Required. Dataset ID of the model to + delete. + + This corresponds to the ``dataset_id`` field + on the ``request`` instance; if ``request`` is provided, this + should not be set. + model_id (:class:`str`): + Required. Model ID of the model to + delete. + + This corresponds to the ``model_id`` field + on the ``request`` instance; if ``request`` is provided, this + should not be set. + retry (google.api_core.retry.Retry): Designation of what errors, if any, + should be retried. + timeout (float): The timeout for this request. + metadata (Sequence[Tuple[str, str]]): Strings which should be + sent along with the request as metadata. + """ + # Create or coerce a protobuf request object. + # Sanity check: If we got a request object, we should *not* have + # gotten any keyword arguments that map to the request. + has_flattened_params = any([project_id, dataset_id, model_id]) + if request is not None and has_flattened_params: + raise ValueError("If the `request` argument is set, then none of " + "the individual field arguments should be set.") + + request = model.DeleteModelRequest(request) + + # If we have keyword arguments corresponding to fields on the + # request, apply these. + if project_id is not None: + request.project_id = project_id + if dataset_id is not None: + request.dataset_id = dataset_id + if model_id is not None: + request.model_id = model_id + + # Wrap the RPC method; this adds retry and timeout information, + # and friendly error handling. + rpc = gapic_v1.method_async.wrap_method( + self._client._transport.delete_model, + default_timeout=600.0, + client_info=DEFAULT_CLIENT_INFO, + ) + + # Send the request. + await rpc( + request, + retry=retry, + timeout=timeout, + metadata=metadata, + ) + + + + + +try: + DEFAULT_CLIENT_INFO = gapic_v1.client_info.ClientInfo( + gapic_version=pkg_resources.get_distribution( + "google-cloud-bigquery", + ).version, + ) +except pkg_resources.DistributionNotFound: + DEFAULT_CLIENT_INFO = gapic_v1.client_info.ClientInfo() + + +__all__ = ( + "ModelServiceAsyncClient", +) diff --git a/owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/client.py b/owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/client.py new file mode 100644 index 000000000..856416def --- /dev/null +++ b/owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/client.py @@ -0,0 +1,688 @@ +# -*- coding: utf-8 -*- +# Copyright 2020 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# +from collections import OrderedDict +from distutils import util +import os +import re +from typing import Callable, Dict, Optional, Sequence, Tuple, Type, Union +import pkg_resources + +from google.api_core import client_options as client_options_lib # type: ignore +from google.api_core import exceptions as core_exceptions # type: ignore +from google.api_core import gapic_v1 # type: ignore +from google.api_core import retry as retries # type: ignore +from google.auth import credentials as ga_credentials # type: ignore +from google.auth.transport import mtls # type: ignore +from google.auth.transport.grpc import SslCredentials # type: ignore +from google.auth.exceptions import MutualTLSChannelError # type: ignore +from google.oauth2 import service_account # type: ignore + +from google.cloud.bigquery_v2.types import encryption_config +from google.cloud.bigquery_v2.types import model +from google.cloud.bigquery_v2.types import model as gcb_model +from google.cloud.bigquery_v2.types import model_reference +from google.cloud.bigquery_v2.types import standard_sql +from google.protobuf import wrappers_pb2 # type: ignore +from .transports.base import ModelServiceTransport, DEFAULT_CLIENT_INFO +from .transports.grpc import ModelServiceGrpcTransport +from .transports.grpc_asyncio import ModelServiceGrpcAsyncIOTransport + + +class ModelServiceClientMeta(type): + """Metaclass for the ModelService client. + + This provides class-level methods for building and retrieving + support objects (e.g. transport) without polluting the client instance + objects. + """ + _transport_registry = OrderedDict() # type: Dict[str, Type[ModelServiceTransport]] + _transport_registry["grpc"] = ModelServiceGrpcTransport + _transport_registry["grpc_asyncio"] = ModelServiceGrpcAsyncIOTransport + + def get_transport_class(cls, + label: str = None, + ) -> Type[ModelServiceTransport]: + """Returns an appropriate transport class. + + Args: + label: The name of the desired transport. If none is + provided, then the first transport in the registry is used. + + Returns: + The transport class to use. + """ + # If a specific transport is requested, return that one. + if label: + return cls._transport_registry[label] + + # No transport is requested; return the default (that is, the first one + # in the dictionary). + return next(iter(cls._transport_registry.values())) + + +class ModelServiceClient(metaclass=ModelServiceClientMeta): + """""" + + @staticmethod + def _get_default_mtls_endpoint(api_endpoint): + """Converts api endpoint to mTLS endpoint. + + Convert "*.sandbox.googleapis.com" and "*.googleapis.com" to + "*.mtls.sandbox.googleapis.com" and "*.mtls.googleapis.com" respectively. + Args: + api_endpoint (Optional[str]): the api endpoint to convert. + Returns: + str: converted mTLS api endpoint. + """ + if not api_endpoint: + return api_endpoint + + mtls_endpoint_re = re.compile( + r"(?P[^.]+)(?P\.mtls)?(?P\.sandbox)?(?P\.googleapis\.com)?" + ) + + m = mtls_endpoint_re.match(api_endpoint) + name, mtls, sandbox, googledomain = m.groups() + if mtls or not googledomain: + return api_endpoint + + if sandbox: + return api_endpoint.replace( + "sandbox.googleapis.com", "mtls.sandbox.googleapis.com" + ) + + return api_endpoint.replace(".googleapis.com", ".mtls.googleapis.com") + + DEFAULT_ENDPOINT = "bigquery.googleapis.com" + DEFAULT_MTLS_ENDPOINT = _get_default_mtls_endpoint.__func__( # type: ignore + DEFAULT_ENDPOINT + ) + + @classmethod + def from_service_account_info(cls, info: dict, *args, **kwargs): + """Creates an instance of this client using the provided credentials + info. + + Args: + info (dict): The service account private key info. + args: Additional arguments to pass to the constructor. + kwargs: Additional arguments to pass to the constructor. + + Returns: + ModelServiceClient: The constructed client. + """ + credentials = service_account.Credentials.from_service_account_info(info) + kwargs["credentials"] = credentials + return cls(*args, **kwargs) + + @classmethod + def from_service_account_file(cls, filename: str, *args, **kwargs): + """Creates an instance of this client using the provided credentials + file. + + Args: + filename (str): The path to the service account private key json + file. + args: Additional arguments to pass to the constructor. + kwargs: Additional arguments to pass to the constructor. + + Returns: + ModelServiceClient: The constructed client. + """ + credentials = service_account.Credentials.from_service_account_file( + filename) + kwargs["credentials"] = credentials + return cls(*args, **kwargs) + + from_service_account_json = from_service_account_file + + @property + def transport(self) -> ModelServiceTransport: + """Returns the transport used by the client instance. + + Returns: + ModelServiceTransport: The transport used by the client + instance. + """ + return self._transport + + @staticmethod + def common_billing_account_path(billing_account: str, ) -> str: + """Returns a fully-qualified billing_account string.""" + return "billingAccounts/{billing_account}".format(billing_account=billing_account, ) + + @staticmethod + def parse_common_billing_account_path(path: str) -> Dict[str,str]: + """Parse a billing_account path into its component segments.""" + m = re.match(r"^billingAccounts/(?P.+?)$", path) + return m.groupdict() if m else {} + + @staticmethod + def common_folder_path(folder: str, ) -> str: + """Returns a fully-qualified folder string.""" + return "folders/{folder}".format(folder=folder, ) + + @staticmethod + def parse_common_folder_path(path: str) -> Dict[str,str]: + """Parse a folder path into its component segments.""" + m = re.match(r"^folders/(?P.+?)$", path) + return m.groupdict() if m else {} + + @staticmethod + def common_organization_path(organization: str, ) -> str: + """Returns a fully-qualified organization string.""" + return "organizations/{organization}".format(organization=organization, ) + + @staticmethod + def parse_common_organization_path(path: str) -> Dict[str,str]: + """Parse a organization path into its component segments.""" + m = re.match(r"^organizations/(?P.+?)$", path) + return m.groupdict() if m else {} + + @staticmethod + def common_project_path(project: str, ) -> str: + """Returns a fully-qualified project string.""" + return "projects/{project}".format(project=project, ) + + @staticmethod + def parse_common_project_path(path: str) -> Dict[str,str]: + """Parse a project path into its component segments.""" + m = re.match(r"^projects/(?P.+?)$", path) + return m.groupdict() if m else {} + + @staticmethod + def common_location_path(project: str, location: str, ) -> str: + """Returns a fully-qualified location string.""" + return "projects/{project}/locations/{location}".format(project=project, location=location, ) + + @staticmethod + def parse_common_location_path(path: str) -> Dict[str,str]: + """Parse a location path into its component segments.""" + m = re.match(r"^projects/(?P.+?)/locations/(?P.+?)$", path) + return m.groupdict() if m else {} + + def __init__(self, *, + credentials: Optional[ga_credentials.Credentials] = None, + transport: Union[str, ModelServiceTransport, None] = None, + client_options: Optional[client_options_lib.ClientOptions] = None, + client_info: gapic_v1.client_info.ClientInfo = DEFAULT_CLIENT_INFO, + ) -> None: + """Instantiates the model service client. + + Args: + credentials (Optional[google.auth.credentials.Credentials]): The + authorization credentials to attach to requests. These + credentials identify the application to the service; if none + are specified, the client will attempt to ascertain the + credentials from the environment. + transport (Union[str, ModelServiceTransport]): The + transport to use. If set to None, a transport is chosen + automatically. + client_options (google.api_core.client_options.ClientOptions): Custom options for the + client. It won't take effect if a ``transport`` instance is provided. + (1) The ``api_endpoint`` property can be used to override the + default endpoint provided by the client. GOOGLE_API_USE_MTLS_ENDPOINT + environment variable can also be used to override the endpoint: + "always" (always use the default mTLS endpoint), "never" (always + use the default regular endpoint) and "auto" (auto switch to the + default mTLS endpoint if client certificate is present, this is + the default value). However, the ``api_endpoint`` property takes + precedence if provided. + (2) If GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable + is "true", then the ``client_cert_source`` property can be used + to provide client certificate for mutual TLS transport. If + not provided, the default SSL client certificate will be used if + present. If GOOGLE_API_USE_CLIENT_CERTIFICATE is "false" or not + set, no client certificate will be used. + client_info (google.api_core.gapic_v1.client_info.ClientInfo): + The client info used to send a user-agent string along with + API requests. If ``None``, then default info will be used. + Generally, you only need to set this if you're developing + your own client library. + + Raises: + google.auth.exceptions.MutualTLSChannelError: If mutual TLS transport + creation failed for any reason. + """ + if isinstance(client_options, dict): + client_options = client_options_lib.from_dict(client_options) + if client_options is None: + client_options = client_options_lib.ClientOptions() + + # Create SSL credentials for mutual TLS if needed. + use_client_cert = bool(util.strtobool(os.getenv("GOOGLE_API_USE_CLIENT_CERTIFICATE", "false"))) + + client_cert_source_func = None + is_mtls = False + if use_client_cert: + if client_options.client_cert_source: + is_mtls = True + client_cert_source_func = client_options.client_cert_source + else: + is_mtls = mtls.has_default_client_cert_source() + if is_mtls: + client_cert_source_func = mtls.default_client_cert_source() + else: + client_cert_source_func = None + + # Figure out which api endpoint to use. + if client_options.api_endpoint is not None: + api_endpoint = client_options.api_endpoint + else: + use_mtls_env = os.getenv("GOOGLE_API_USE_MTLS_ENDPOINT", "auto") + if use_mtls_env == "never": + api_endpoint = self.DEFAULT_ENDPOINT + elif use_mtls_env == "always": + api_endpoint = self.DEFAULT_MTLS_ENDPOINT + elif use_mtls_env == "auto": + if is_mtls: + api_endpoint = self.DEFAULT_MTLS_ENDPOINT + else: + api_endpoint = self.DEFAULT_ENDPOINT + else: + raise MutualTLSChannelError( + "Unsupported GOOGLE_API_USE_MTLS_ENDPOINT value. Accepted " + "values: never, auto, always" + ) + + # Save or instantiate the transport. + # Ordinarily, we provide the transport, but allowing a custom transport + # instance provides an extensibility point for unusual situations. + if isinstance(transport, ModelServiceTransport): + # transport is a ModelServiceTransport instance. + if credentials or client_options.credentials_file: + raise ValueError("When providing a transport instance, " + "provide its credentials directly.") + if client_options.scopes: + raise ValueError( + "When providing a transport instance, provide its scopes " + "directly." + ) + self._transport = transport + else: + Transport = type(self).get_transport_class(transport) + self._transport = Transport( + credentials=credentials, + credentials_file=client_options.credentials_file, + host=api_endpoint, + scopes=client_options.scopes, + client_cert_source_for_mtls=client_cert_source_func, + quota_project_id=client_options.quota_project_id, + client_info=client_info, + ) + + def get_model(self, + request: model.GetModelRequest = None, + *, + project_id: str = None, + dataset_id: str = None, + model_id: str = None, + retry: retries.Retry = gapic_v1.method.DEFAULT, + timeout: float = None, + metadata: Sequence[Tuple[str, str]] = (), + ) -> model.Model: + r"""Gets the specified model resource by model ID. + + Args: + request (google.cloud.bigquery_v2.types.GetModelRequest): + The request object. + project_id (str): + Required. Project ID of the requested + model. + + This corresponds to the ``project_id`` field + on the ``request`` instance; if ``request`` is provided, this + should not be set. + dataset_id (str): + Required. Dataset ID of the requested + model. + + This corresponds to the ``dataset_id`` field + on the ``request`` instance; if ``request`` is provided, this + should not be set. + model_id (str): + Required. Model ID of the requested + model. + + This corresponds to the ``model_id`` field + on the ``request`` instance; if ``request`` is provided, this + should not be set. + retry (google.api_core.retry.Retry): Designation of what errors, if any, + should be retried. + timeout (float): The timeout for this request. + metadata (Sequence[Tuple[str, str]]): Strings which should be + sent along with the request as metadata. + + Returns: + google.cloud.bigquery_v2.types.Model: + + """ + # Create or coerce a protobuf request object. + # Sanity check: If we got a request object, we should *not* have + # gotten any keyword arguments that map to the request. + has_flattened_params = any([project_id, dataset_id, model_id]) + if request is not None and has_flattened_params: + raise ValueError('If the `request` argument is set, then none of ' + 'the individual field arguments should be set.') + + # Minor optimization to avoid making a copy if the user passes + # in a model.GetModelRequest. + # There's no risk of modifying the input as we've already verified + # there are no flattened fields. + if not isinstance(request, model.GetModelRequest): + request = model.GetModelRequest(request) + # If we have keyword arguments corresponding to fields on the + # request, apply these. + if project_id is not None: + request.project_id = project_id + if dataset_id is not None: + request.dataset_id = dataset_id + if model_id is not None: + request.model_id = model_id + + # Wrap the RPC method; this adds retry and timeout information, + # and friendly error handling. + rpc = self._transport._wrapped_methods[self._transport.get_model] + + # Send the request. + response = rpc( + request, + retry=retry, + timeout=timeout, + metadata=metadata, + ) + + # Done; return the response. + return response + + def list_models(self, + request: model.ListModelsRequest = None, + *, + project_id: str = None, + dataset_id: str = None, + max_results: wrappers_pb2.UInt32Value = None, + retry: retries.Retry = gapic_v1.method.DEFAULT, + timeout: float = None, + metadata: Sequence[Tuple[str, str]] = (), + ) -> model.ListModelsResponse: + r"""Lists all models in the specified dataset. Requires + the READER dataset role. + + Args: + request (google.cloud.bigquery_v2.types.ListModelsRequest): + The request object. + project_id (str): + Required. Project ID of the models to + list. + + This corresponds to the ``project_id`` field + on the ``request`` instance; if ``request`` is provided, this + should not be set. + dataset_id (str): + Required. Dataset ID of the models to + list. + + This corresponds to the ``dataset_id`` field + on the ``request`` instance; if ``request`` is provided, this + should not be set. + max_results (google.protobuf.wrappers_pb2.UInt32Value): + The maximum number of results to + return in a single response page. + Leverage the page tokens to iterate + through the entire collection. + + This corresponds to the ``max_results`` field + on the ``request`` instance; if ``request`` is provided, this + should not be set. + retry (google.api_core.retry.Retry): Designation of what errors, if any, + should be retried. + timeout (float): The timeout for this request. + metadata (Sequence[Tuple[str, str]]): Strings which should be + sent along with the request as metadata. + + Returns: + google.cloud.bigquery_v2.types.ListModelsResponse: + + """ + # Create or coerce a protobuf request object. + # Sanity check: If we got a request object, we should *not* have + # gotten any keyword arguments that map to the request. + has_flattened_params = any([project_id, dataset_id, max_results]) + if request is not None and has_flattened_params: + raise ValueError('If the `request` argument is set, then none of ' + 'the individual field arguments should be set.') + + # Minor optimization to avoid making a copy if the user passes + # in a model.ListModelsRequest. + # There's no risk of modifying the input as we've already verified + # there are no flattened fields. + if not isinstance(request, model.ListModelsRequest): + request = model.ListModelsRequest(request) + # If we have keyword arguments corresponding to fields on the + # request, apply these. + if project_id is not None: + request.project_id = project_id + if dataset_id is not None: + request.dataset_id = dataset_id + if max_results is not None: + request.max_results = max_results + + # Wrap the RPC method; this adds retry and timeout information, + # and friendly error handling. + rpc = self._transport._wrapped_methods[self._transport.list_models] + + # Send the request. + response = rpc( + request, + retry=retry, + timeout=timeout, + metadata=metadata, + ) + + # Done; return the response. + return response + + def patch_model(self, + request: gcb_model.PatchModelRequest = None, + *, + project_id: str = None, + dataset_id: str = None, + model_id: str = None, + model: gcb_model.Model = None, + retry: retries.Retry = gapic_v1.method.DEFAULT, + timeout: float = None, + metadata: Sequence[Tuple[str, str]] = (), + ) -> gcb_model.Model: + r"""Patch specific fields in the specified model. + + Args: + request (google.cloud.bigquery_v2.types.PatchModelRequest): + The request object. + project_id (str): + Required. Project ID of the model to + patch. + + This corresponds to the ``project_id`` field + on the ``request`` instance; if ``request`` is provided, this + should not be set. + dataset_id (str): + Required. Dataset ID of the model to + patch. + + This corresponds to the ``dataset_id`` field + on the ``request`` instance; if ``request`` is provided, this + should not be set. + model_id (str): + Required. Model ID of the model to + patch. + + This corresponds to the ``model_id`` field + on the ``request`` instance; if ``request`` is provided, this + should not be set. + model (google.cloud.bigquery_v2.types.Model): + Required. Patched model. + Follows RFC5789 patch semantics. Missing + fields are not updated. To clear a + field, explicitly set to default value. + + This corresponds to the ``model`` field + on the ``request`` instance; if ``request`` is provided, this + should not be set. + retry (google.api_core.retry.Retry): Designation of what errors, if any, + should be retried. + timeout (float): The timeout for this request. + metadata (Sequence[Tuple[str, str]]): Strings which should be + sent along with the request as metadata. + + Returns: + google.cloud.bigquery_v2.types.Model: + + """ + # Create or coerce a protobuf request object. + # Sanity check: If we got a request object, we should *not* have + # gotten any keyword arguments that map to the request. + has_flattened_params = any([project_id, dataset_id, model_id, model]) + if request is not None and has_flattened_params: + raise ValueError('If the `request` argument is set, then none of ' + 'the individual field arguments should be set.') + + # Minor optimization to avoid making a copy if the user passes + # in a gcb_model.PatchModelRequest. + # There's no risk of modifying the input as we've already verified + # there are no flattened fields. + if not isinstance(request, gcb_model.PatchModelRequest): + request = gcb_model.PatchModelRequest(request) + # If we have keyword arguments corresponding to fields on the + # request, apply these. + if project_id is not None: + request.project_id = project_id + if dataset_id is not None: + request.dataset_id = dataset_id + if model_id is not None: + request.model_id = model_id + if model is not None: + request.model = model + + # Wrap the RPC method; this adds retry and timeout information, + # and friendly error handling. + rpc = self._transport._wrapped_methods[self._transport.patch_model] + + # Send the request. + response = rpc( + request, + retry=retry, + timeout=timeout, + metadata=metadata, + ) + + # Done; return the response. + return response + + def delete_model(self, + request: model.DeleteModelRequest = None, + *, + project_id: str = None, + dataset_id: str = None, + model_id: str = None, + retry: retries.Retry = gapic_v1.method.DEFAULT, + timeout: float = None, + metadata: Sequence[Tuple[str, str]] = (), + ) -> None: + r"""Deletes the model specified by modelId from the + dataset. + + Args: + request (google.cloud.bigquery_v2.types.DeleteModelRequest): + The request object. + project_id (str): + Required. Project ID of the model to + delete. + + This corresponds to the ``project_id`` field + on the ``request`` instance; if ``request`` is provided, this + should not be set. + dataset_id (str): + Required. Dataset ID of the model to + delete. + + This corresponds to the ``dataset_id`` field + on the ``request`` instance; if ``request`` is provided, this + should not be set. + model_id (str): + Required. Model ID of the model to + delete. + + This corresponds to the ``model_id`` field + on the ``request`` instance; if ``request`` is provided, this + should not be set. + retry (google.api_core.retry.Retry): Designation of what errors, if any, + should be retried. + timeout (float): The timeout for this request. + metadata (Sequence[Tuple[str, str]]): Strings which should be + sent along with the request as metadata. + """ + # Create or coerce a protobuf request object. + # Sanity check: If we got a request object, we should *not* have + # gotten any keyword arguments that map to the request. + has_flattened_params = any([project_id, dataset_id, model_id]) + if request is not None and has_flattened_params: + raise ValueError('If the `request` argument is set, then none of ' + 'the individual field arguments should be set.') + + # Minor optimization to avoid making a copy if the user passes + # in a model.DeleteModelRequest. + # There's no risk of modifying the input as we've already verified + # there are no flattened fields. + if not isinstance(request, model.DeleteModelRequest): + request = model.DeleteModelRequest(request) + # If we have keyword arguments corresponding to fields on the + # request, apply these. + if project_id is not None: + request.project_id = project_id + if dataset_id is not None: + request.dataset_id = dataset_id + if model_id is not None: + request.model_id = model_id + + # Wrap the RPC method; this adds retry and timeout information, + # and friendly error handling. + rpc = self._transport._wrapped_methods[self._transport.delete_model] + + # Send the request. + rpc( + request, + retry=retry, + timeout=timeout, + metadata=metadata, + ) + + + + + +try: + DEFAULT_CLIENT_INFO = gapic_v1.client_info.ClientInfo( + gapic_version=pkg_resources.get_distribution( + "google-cloud-bigquery", + ).version, + ) +except pkg_resources.DistributionNotFound: + DEFAULT_CLIENT_INFO = gapic_v1.client_info.ClientInfo() + + +__all__ = ( + "ModelServiceClient", +) diff --git a/owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/transports/__init__.py b/owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/transports/__init__.py new file mode 100644 index 000000000..0f09224d3 --- /dev/null +++ b/owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/transports/__init__.py @@ -0,0 +1,33 @@ +# -*- coding: utf-8 -*- +# Copyright 2020 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# +from collections import OrderedDict +from typing import Dict, Type + +from .base import ModelServiceTransport +from .grpc import ModelServiceGrpcTransport +from .grpc_asyncio import ModelServiceGrpcAsyncIOTransport + + +# Compile a registry of transports. +_transport_registry = OrderedDict() # type: Dict[str, Type[ModelServiceTransport]] +_transport_registry['grpc'] = ModelServiceGrpcTransport +_transport_registry['grpc_asyncio'] = ModelServiceGrpcAsyncIOTransport + +__all__ = ( + 'ModelServiceTransport', + 'ModelServiceGrpcTransport', + 'ModelServiceGrpcAsyncIOTransport', +) diff --git a/owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/transports/base.py b/owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/transports/base.py new file mode 100644 index 000000000..3b3c4ae99 --- /dev/null +++ b/owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/transports/base.py @@ -0,0 +1,215 @@ +# -*- coding: utf-8 -*- +# Copyright 2020 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# +import abc +from typing import Awaitable, Callable, Dict, Optional, Sequence, Union +import packaging.version +import pkg_resources + +import google.auth # type: ignore +import google.api_core # type: ignore +from google.api_core import exceptions as core_exceptions # type: ignore +from google.api_core import gapic_v1 # type: ignore +from google.api_core import retry as retries # type: ignore +from google.auth import credentials as ga_credentials # type: ignore +from google.oauth2 import service_account # type: ignore + +from google.cloud.bigquery_v2.types import model +from google.cloud.bigquery_v2.types import model as gcb_model +from google.protobuf import empty_pb2 # type: ignore + +try: + DEFAULT_CLIENT_INFO = gapic_v1.client_info.ClientInfo( + gapic_version=pkg_resources.get_distribution( + 'google-cloud-bigquery', + ).version, + ) +except pkg_resources.DistributionNotFound: + DEFAULT_CLIENT_INFO = gapic_v1.client_info.ClientInfo() + +try: + # google.auth.__version__ was added in 1.26.0 + _GOOGLE_AUTH_VERSION = google.auth.__version__ +except AttributeError: + try: # try pkg_resources if it is available + _GOOGLE_AUTH_VERSION = pkg_resources.get_distribution("google-auth").version + except pkg_resources.DistributionNotFound: # pragma: NO COVER + _GOOGLE_AUTH_VERSION = None + + +class ModelServiceTransport(abc.ABC): + """Abstract transport class for ModelService.""" + + AUTH_SCOPES = ( + 'https://www.googleapis.com/auth/bigquery', + 'https://www.googleapis.com/auth/bigquery.readonly', + 'https://www.googleapis.com/auth/cloud-platform', + 'https://www.googleapis.com/auth/cloud-platform.read-only', + ) + + DEFAULT_HOST: str = 'bigquery.googleapis.com' + def __init__( + self, *, + host: str = DEFAULT_HOST, + credentials: ga_credentials.Credentials = None, + credentials_file: Optional[str] = None, + scopes: Optional[Sequence[str]] = None, + quota_project_id: Optional[str] = None, + client_info: gapic_v1.client_info.ClientInfo = DEFAULT_CLIENT_INFO, + always_use_jwt_access: Optional[bool] = False, + **kwargs, + ) -> None: + """Instantiate the transport. + + Args: + host (Optional[str]): + The hostname to connect to. + credentials (Optional[google.auth.credentials.Credentials]): The + authorization credentials to attach to requests. These + credentials identify the application to the service; if none + are specified, the client will attempt to ascertain the + credentials from the environment. + credentials_file (Optional[str]): A file with credentials that can + be loaded with :func:`google.auth.load_credentials_from_file`. + This argument is mutually exclusive with credentials. + scopes (Optional[Sequence[str]]): A list of scopes. + quota_project_id (Optional[str]): An optional project to use for billing + and quota. + client_info (google.api_core.gapic_v1.client_info.ClientInfo): + The client info used to send a user-agent string along with + API requests. If ``None``, then default info will be used. + Generally, you only need to set this if you're developing + your own client library. + always_use_jwt_access (Optional[bool]): Whether self signed JWT should + be used for service account credentials. + """ + # Save the hostname. Default to port 443 (HTTPS) if none is specified. + if ':' not in host: + host += ':443' + self._host = host + + scopes_kwargs = self._get_scopes_kwargs(self._host, scopes) + + # Save the scopes. + self._scopes = scopes + + # If no credentials are provided, then determine the appropriate + # defaults. + if credentials and credentials_file: + raise core_exceptions.DuplicateCredentialArgs("'credentials_file' and 'credentials' are mutually exclusive") + + if credentials_file is not None: + credentials, _ = google.auth.load_credentials_from_file( + credentials_file, + **scopes_kwargs, + quota_project_id=quota_project_id + ) + + elif credentials is None: + credentials, _ = google.auth.default(**scopes_kwargs, quota_project_id=quota_project_id) + + # If the credentials is service account credentials, then always try to use self signed JWT. + if always_use_jwt_access and isinstance(credentials, service_account.Credentials) and hasattr(service_account.Credentials, "with_always_use_jwt_access"): + credentials = credentials.with_always_use_jwt_access(True) + + # Save the credentials. + self._credentials = credentials + + # TODO(busunkim): This method is in the base transport + # to avoid duplicating code across the transport classes. These functions + # should be deleted once the minimum required versions of google-auth is increased. + + # TODO: Remove this function once google-auth >= 1.25.0 is required + @classmethod + def _get_scopes_kwargs(cls, host: str, scopes: Optional[Sequence[str]]) -> Dict[str, Optional[Sequence[str]]]: + """Returns scopes kwargs to pass to google-auth methods depending on the google-auth version""" + + scopes_kwargs = {} + + if _GOOGLE_AUTH_VERSION and ( + packaging.version.parse(_GOOGLE_AUTH_VERSION) + >= packaging.version.parse("1.25.0") + ): + scopes_kwargs = {"scopes": scopes, "default_scopes": cls.AUTH_SCOPES} + else: + scopes_kwargs = {"scopes": scopes or cls.AUTH_SCOPES} + + return scopes_kwargs + + def _prep_wrapped_messages(self, client_info): + # Precompute the wrapped methods. + self._wrapped_methods = { + self.get_model: gapic_v1.method.wrap_method( + self.get_model, + default_timeout=600.0, + client_info=client_info, + ), + self.list_models: gapic_v1.method.wrap_method( + self.list_models, + default_timeout=600.0, + client_info=client_info, + ), + self.patch_model: gapic_v1.method.wrap_method( + self.patch_model, + default_timeout=600.0, + client_info=client_info, + ), + self.delete_model: gapic_v1.method.wrap_method( + self.delete_model, + default_timeout=600.0, + client_info=client_info, + ), + } + + @property + def get_model(self) -> Callable[ + [model.GetModelRequest], + Union[ + model.Model, + Awaitable[model.Model] + ]]: + raise NotImplementedError() + + @property + def list_models(self) -> Callable[ + [model.ListModelsRequest], + Union[ + model.ListModelsResponse, + Awaitable[model.ListModelsResponse] + ]]: + raise NotImplementedError() + + @property + def patch_model(self) -> Callable[ + [gcb_model.PatchModelRequest], + Union[ + gcb_model.Model, + Awaitable[gcb_model.Model] + ]]: + raise NotImplementedError() + + @property + def delete_model(self) -> Callable[ + [model.DeleteModelRequest], + Union[ + empty_pb2.Empty, + Awaitable[empty_pb2.Empty] + ]]: + raise NotImplementedError() + + +__all__ = ( + 'ModelServiceTransport', +) diff --git a/owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/transports/grpc.py b/owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/transports/grpc.py new file mode 100644 index 000000000..a873fde46 --- /dev/null +++ b/owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/transports/grpc.py @@ -0,0 +1,332 @@ +# -*- coding: utf-8 -*- +# Copyright 2020 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# +import warnings +from typing import Callable, Dict, Optional, Sequence, Tuple, Union + +from google.api_core import grpc_helpers # type: ignore +from google.api_core import gapic_v1 # type: ignore +import google.auth # type: ignore +from google.auth import credentials as ga_credentials # type: ignore +from google.auth.transport.grpc import SslCredentials # type: ignore + +import grpc # type: ignore + +from google.cloud.bigquery_v2.types import model +from google.cloud.bigquery_v2.types import model as gcb_model +from google.protobuf import empty_pb2 # type: ignore +from .base import ModelServiceTransport, DEFAULT_CLIENT_INFO + + +class ModelServiceGrpcTransport(ModelServiceTransport): + """gRPC backend transport for ModelService. + + This class defines the same methods as the primary client, so the + primary client can load the underlying transport implementation + and call it. + + It sends protocol buffers over the wire using gRPC (which is built on + top of HTTP/2); the ``grpcio`` package must be installed. + """ + _stubs: Dict[str, Callable] + + def __init__(self, *, + host: str = 'bigquery.googleapis.com', + credentials: ga_credentials.Credentials = None, + credentials_file: str = None, + scopes: Sequence[str] = None, + channel: grpc.Channel = None, + api_mtls_endpoint: str = None, + client_cert_source: Callable[[], Tuple[bytes, bytes]] = None, + ssl_channel_credentials: grpc.ChannelCredentials = None, + client_cert_source_for_mtls: Callable[[], Tuple[bytes, bytes]] = None, + quota_project_id: Optional[str] = None, + client_info: gapic_v1.client_info.ClientInfo = DEFAULT_CLIENT_INFO, + always_use_jwt_access: Optional[bool] = False, + ) -> None: + """Instantiate the transport. + + Args: + host (Optional[str]): + The hostname to connect to. + credentials (Optional[google.auth.credentials.Credentials]): The + authorization credentials to attach to requests. These + credentials identify the application to the service; if none + are specified, the client will attempt to ascertain the + credentials from the environment. + This argument is ignored if ``channel`` is provided. + credentials_file (Optional[str]): A file with credentials that can + be loaded with :func:`google.auth.load_credentials_from_file`. + This argument is ignored if ``channel`` is provided. + scopes (Optional(Sequence[str])): A list of scopes. This argument is + ignored if ``channel`` is provided. + channel (Optional[grpc.Channel]): A ``Channel`` instance through + which to make calls. + api_mtls_endpoint (Optional[str]): Deprecated. The mutual TLS endpoint. + If provided, it overrides the ``host`` argument and tries to create + a mutual TLS channel with client SSL credentials from + ``client_cert_source`` or applicatin default SSL credentials. + client_cert_source (Optional[Callable[[], Tuple[bytes, bytes]]]): + Deprecated. A callback to provide client SSL certificate bytes and + private key bytes, both in PEM format. It is ignored if + ``api_mtls_endpoint`` is None. + ssl_channel_credentials (grpc.ChannelCredentials): SSL credentials + for grpc channel. It is ignored if ``channel`` is provided. + client_cert_source_for_mtls (Optional[Callable[[], Tuple[bytes, bytes]]]): + A callback to provide client certificate bytes and private key bytes, + both in PEM format. It is used to configure mutual TLS channel. It is + ignored if ``channel`` or ``ssl_channel_credentials`` is provided. + quota_project_id (Optional[str]): An optional project to use for billing + and quota. + client_info (google.api_core.gapic_v1.client_info.ClientInfo): + The client info used to send a user-agent string along with + API requests. If ``None``, then default info will be used. + Generally, you only need to set this if you're developing + your own client library. + always_use_jwt_access (Optional[bool]): Whether self signed JWT should + be used for service account credentials. + + Raises: + google.auth.exceptions.MutualTLSChannelError: If mutual TLS transport + creation failed for any reason. + google.api_core.exceptions.DuplicateCredentialArgs: If both ``credentials`` + and ``credentials_file`` are passed. + """ + self._grpc_channel = None + self._ssl_channel_credentials = ssl_channel_credentials + self._stubs: Dict[str, Callable] = {} + + if api_mtls_endpoint: + warnings.warn("api_mtls_endpoint is deprecated", DeprecationWarning) + if client_cert_source: + warnings.warn("client_cert_source is deprecated", DeprecationWarning) + + if channel: + # Ignore credentials if a channel was passed. + credentials = False + # If a channel was explicitly provided, set it. + self._grpc_channel = channel + self._ssl_channel_credentials = None + + else: + if api_mtls_endpoint: + host = api_mtls_endpoint + + # Create SSL credentials with client_cert_source or application + # default SSL credentials. + if client_cert_source: + cert, key = client_cert_source() + self._ssl_channel_credentials = grpc.ssl_channel_credentials( + certificate_chain=cert, private_key=key + ) + else: + self._ssl_channel_credentials = SslCredentials().ssl_credentials + + else: + if client_cert_source_for_mtls and not ssl_channel_credentials: + cert, key = client_cert_source_for_mtls() + self._ssl_channel_credentials = grpc.ssl_channel_credentials( + certificate_chain=cert, private_key=key + ) + + # The base transport sets the host, credentials and scopes + super().__init__( + host=host, + credentials=credentials, + credentials_file=credentials_file, + scopes=scopes, + quota_project_id=quota_project_id, + client_info=client_info, + always_use_jwt_access=always_use_jwt_access, + ) + + if not self._grpc_channel: + self._grpc_channel = type(self).create_channel( + self._host, + credentials=self._credentials, + credentials_file=credentials_file, + scopes=self._scopes, + ssl_credentials=self._ssl_channel_credentials, + quota_project_id=quota_project_id, + options=[ + ("grpc.max_send_message_length", -1), + ("grpc.max_receive_message_length", -1), + ], + ) + + # Wrap messages. This must be done after self._grpc_channel exists + self._prep_wrapped_messages(client_info) + + @classmethod + def create_channel(cls, + host: str = 'bigquery.googleapis.com', + credentials: ga_credentials.Credentials = None, + credentials_file: str = None, + scopes: Optional[Sequence[str]] = None, + quota_project_id: Optional[str] = None, + **kwargs) -> grpc.Channel: + """Create and return a gRPC channel object. + Args: + host (Optional[str]): The host for the channel to use. + credentials (Optional[~.Credentials]): The + authorization credentials to attach to requests. These + credentials identify this application to the service. If + none are specified, the client will attempt to ascertain + the credentials from the environment. + credentials_file (Optional[str]): A file with credentials that can + be loaded with :func:`google.auth.load_credentials_from_file`. + This argument is mutually exclusive with credentials. + scopes (Optional[Sequence[str]]): A optional list of scopes needed for this + service. These are only used when credentials are not specified and + are passed to :func:`google.auth.default`. + quota_project_id (Optional[str]): An optional project to use for billing + and quota. + kwargs (Optional[dict]): Keyword arguments, which are passed to the + channel creation. + Returns: + grpc.Channel: A gRPC channel object. + + Raises: + google.api_core.exceptions.DuplicateCredentialArgs: If both ``credentials`` + and ``credentials_file`` are passed. + """ + + return grpc_helpers.create_channel( + host, + credentials=credentials, + credentials_file=credentials_file, + quota_project_id=quota_project_id, + default_scopes=cls.AUTH_SCOPES, + scopes=scopes, + default_host=cls.DEFAULT_HOST, + **kwargs + ) + + @property + def grpc_channel(self) -> grpc.Channel: + """Return the channel designed to connect to this service. + """ + return self._grpc_channel + + @property + def get_model(self) -> Callable[ + [model.GetModelRequest], + model.Model]: + r"""Return a callable for the get model method over gRPC. + + Gets the specified model resource by model ID. + + Returns: + Callable[[~.GetModelRequest], + ~.Model]: + A function that, when called, will call the underlying RPC + on the server. + """ + # Generate a "stub function" on-the-fly which will actually make + # the request. + # gRPC handles serialization and deserialization, so we just need + # to pass in the functions for each. + if 'get_model' not in self._stubs: + self._stubs['get_model'] = self.grpc_channel.unary_unary( + '/google.cloud.bigquery.v2.ModelService/GetModel', + request_serializer=model.GetModelRequest.serialize, + response_deserializer=model.Model.deserialize, + ) + return self._stubs['get_model'] + + @property + def list_models(self) -> Callable[ + [model.ListModelsRequest], + model.ListModelsResponse]: + r"""Return a callable for the list models method over gRPC. + + Lists all models in the specified dataset. Requires + the READER dataset role. + + Returns: + Callable[[~.ListModelsRequest], + ~.ListModelsResponse]: + A function that, when called, will call the underlying RPC + on the server. + """ + # Generate a "stub function" on-the-fly which will actually make + # the request. + # gRPC handles serialization and deserialization, so we just need + # to pass in the functions for each. + if 'list_models' not in self._stubs: + self._stubs['list_models'] = self.grpc_channel.unary_unary( + '/google.cloud.bigquery.v2.ModelService/ListModels', + request_serializer=model.ListModelsRequest.serialize, + response_deserializer=model.ListModelsResponse.deserialize, + ) + return self._stubs['list_models'] + + @property + def patch_model(self) -> Callable[ + [gcb_model.PatchModelRequest], + gcb_model.Model]: + r"""Return a callable for the patch model method over gRPC. + + Patch specific fields in the specified model. + + Returns: + Callable[[~.PatchModelRequest], + ~.Model]: + A function that, when called, will call the underlying RPC + on the server. + """ + # Generate a "stub function" on-the-fly which will actually make + # the request. + # gRPC handles serialization and deserialization, so we just need + # to pass in the functions for each. + if 'patch_model' not in self._stubs: + self._stubs['patch_model'] = self.grpc_channel.unary_unary( + '/google.cloud.bigquery.v2.ModelService/PatchModel', + request_serializer=gcb_model.PatchModelRequest.serialize, + response_deserializer=gcb_model.Model.deserialize, + ) + return self._stubs['patch_model'] + + @property + def delete_model(self) -> Callable[ + [model.DeleteModelRequest], + empty_pb2.Empty]: + r"""Return a callable for the delete model method over gRPC. + + Deletes the model specified by modelId from the + dataset. + + Returns: + Callable[[~.DeleteModelRequest], + ~.Empty]: + A function that, when called, will call the underlying RPC + on the server. + """ + # Generate a "stub function" on-the-fly which will actually make + # the request. + # gRPC handles serialization and deserialization, so we just need + # to pass in the functions for each. + if 'delete_model' not in self._stubs: + self._stubs['delete_model'] = self.grpc_channel.unary_unary( + '/google.cloud.bigquery.v2.ModelService/DeleteModel', + request_serializer=model.DeleteModelRequest.serialize, + response_deserializer=empty_pb2.Empty.FromString, + ) + return self._stubs['delete_model'] + + +__all__ = ( + 'ModelServiceGrpcTransport', +) diff --git a/owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/transports/grpc_asyncio.py b/owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/transports/grpc_asyncio.py new file mode 100644 index 000000000..b6adab8ad --- /dev/null +++ b/owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/transports/grpc_asyncio.py @@ -0,0 +1,336 @@ +# -*- coding: utf-8 -*- +# Copyright 2020 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# +import warnings +from typing import Awaitable, Callable, Dict, Optional, Sequence, Tuple, Union + +from google.api_core import gapic_v1 # type: ignore +from google.api_core import grpc_helpers_async # type: ignore +from google.auth import credentials as ga_credentials # type: ignore +from google.auth.transport.grpc import SslCredentials # type: ignore +import packaging.version + +import grpc # type: ignore +from grpc.experimental import aio # type: ignore + +from google.cloud.bigquery_v2.types import model +from google.cloud.bigquery_v2.types import model as gcb_model +from google.protobuf import empty_pb2 # type: ignore +from .base import ModelServiceTransport, DEFAULT_CLIENT_INFO +from .grpc import ModelServiceGrpcTransport + + +class ModelServiceGrpcAsyncIOTransport(ModelServiceTransport): + """gRPC AsyncIO backend transport for ModelService. + + This class defines the same methods as the primary client, so the + primary client can load the underlying transport implementation + and call it. + + It sends protocol buffers over the wire using gRPC (which is built on + top of HTTP/2); the ``grpcio`` package must be installed. + """ + + _grpc_channel: aio.Channel + _stubs: Dict[str, Callable] = {} + + @classmethod + def create_channel(cls, + host: str = 'bigquery.googleapis.com', + credentials: ga_credentials.Credentials = None, + credentials_file: Optional[str] = None, + scopes: Optional[Sequence[str]] = None, + quota_project_id: Optional[str] = None, + **kwargs) -> aio.Channel: + """Create and return a gRPC AsyncIO channel object. + Args: + host (Optional[str]): The host for the channel to use. + credentials (Optional[~.Credentials]): The + authorization credentials to attach to requests. These + credentials identify this application to the service. If + none are specified, the client will attempt to ascertain + the credentials from the environment. + credentials_file (Optional[str]): A file with credentials that can + be loaded with :func:`google.auth.load_credentials_from_file`. + This argument is ignored if ``channel`` is provided. + scopes (Optional[Sequence[str]]): A optional list of scopes needed for this + service. These are only used when credentials are not specified and + are passed to :func:`google.auth.default`. + quota_project_id (Optional[str]): An optional project to use for billing + and quota. + kwargs (Optional[dict]): Keyword arguments, which are passed to the + channel creation. + Returns: + aio.Channel: A gRPC AsyncIO channel object. + """ + + return grpc_helpers_async.create_channel( + host, + credentials=credentials, + credentials_file=credentials_file, + quota_project_id=quota_project_id, + default_scopes=cls.AUTH_SCOPES, + scopes=scopes, + default_host=cls.DEFAULT_HOST, + **kwargs + ) + + def __init__(self, *, + host: str = 'bigquery.googleapis.com', + credentials: ga_credentials.Credentials = None, + credentials_file: Optional[str] = None, + scopes: Optional[Sequence[str]] = None, + channel: aio.Channel = None, + api_mtls_endpoint: str = None, + client_cert_source: Callable[[], Tuple[bytes, bytes]] = None, + ssl_channel_credentials: grpc.ChannelCredentials = None, + client_cert_source_for_mtls: Callable[[], Tuple[bytes, bytes]] = None, + quota_project_id=None, + client_info: gapic_v1.client_info.ClientInfo = DEFAULT_CLIENT_INFO, + always_use_jwt_access: Optional[bool] = False, + ) -> None: + """Instantiate the transport. + + Args: + host (Optional[str]): + The hostname to connect to. + credentials (Optional[google.auth.credentials.Credentials]): The + authorization credentials to attach to requests. These + credentials identify the application to the service; if none + are specified, the client will attempt to ascertain the + credentials from the environment. + This argument is ignored if ``channel`` is provided. + credentials_file (Optional[str]): A file with credentials that can + be loaded with :func:`google.auth.load_credentials_from_file`. + This argument is ignored if ``channel`` is provided. + scopes (Optional[Sequence[str]]): A optional list of scopes needed for this + service. These are only used when credentials are not specified and + are passed to :func:`google.auth.default`. + channel (Optional[aio.Channel]): A ``Channel`` instance through + which to make calls. + api_mtls_endpoint (Optional[str]): Deprecated. The mutual TLS endpoint. + If provided, it overrides the ``host`` argument and tries to create + a mutual TLS channel with client SSL credentials from + ``client_cert_source`` or applicatin default SSL credentials. + client_cert_source (Optional[Callable[[], Tuple[bytes, bytes]]]): + Deprecated. A callback to provide client SSL certificate bytes and + private key bytes, both in PEM format. It is ignored if + ``api_mtls_endpoint`` is None. + ssl_channel_credentials (grpc.ChannelCredentials): SSL credentials + for grpc channel. It is ignored if ``channel`` is provided. + client_cert_source_for_mtls (Optional[Callable[[], Tuple[bytes, bytes]]]): + A callback to provide client certificate bytes and private key bytes, + both in PEM format. It is used to configure mutual TLS channel. It is + ignored if ``channel`` or ``ssl_channel_credentials`` is provided. + quota_project_id (Optional[str]): An optional project to use for billing + and quota. + client_info (google.api_core.gapic_v1.client_info.ClientInfo): + The client info used to send a user-agent string along with + API requests. If ``None``, then default info will be used. + Generally, you only need to set this if you're developing + your own client library. + always_use_jwt_access (Optional[bool]): Whether self signed JWT should + be used for service account credentials. + + Raises: + google.auth.exceptions.MutualTlsChannelError: If mutual TLS transport + creation failed for any reason. + google.api_core.exceptions.DuplicateCredentialArgs: If both ``credentials`` + and ``credentials_file`` are passed. + """ + self._grpc_channel = None + self._ssl_channel_credentials = ssl_channel_credentials + self._stubs: Dict[str, Callable] = {} + + if api_mtls_endpoint: + warnings.warn("api_mtls_endpoint is deprecated", DeprecationWarning) + if client_cert_source: + warnings.warn("client_cert_source is deprecated", DeprecationWarning) + + if channel: + # Ignore credentials if a channel was passed. + credentials = False + # If a channel was explicitly provided, set it. + self._grpc_channel = channel + self._ssl_channel_credentials = None + else: + if api_mtls_endpoint: + host = api_mtls_endpoint + + # Create SSL credentials with client_cert_source or application + # default SSL credentials. + if client_cert_source: + cert, key = client_cert_source() + self._ssl_channel_credentials = grpc.ssl_channel_credentials( + certificate_chain=cert, private_key=key + ) + else: + self._ssl_channel_credentials = SslCredentials().ssl_credentials + + else: + if client_cert_source_for_mtls and not ssl_channel_credentials: + cert, key = client_cert_source_for_mtls() + self._ssl_channel_credentials = grpc.ssl_channel_credentials( + certificate_chain=cert, private_key=key + ) + + # The base transport sets the host, credentials and scopes + super().__init__( + host=host, + credentials=credentials, + credentials_file=credentials_file, + scopes=scopes, + quota_project_id=quota_project_id, + client_info=client_info, + always_use_jwt_access=always_use_jwt_access, + ) + + if not self._grpc_channel: + self._grpc_channel = type(self).create_channel( + self._host, + credentials=self._credentials, + credentials_file=credentials_file, + scopes=self._scopes, + ssl_credentials=self._ssl_channel_credentials, + quota_project_id=quota_project_id, + options=[ + ("grpc.max_send_message_length", -1), + ("grpc.max_receive_message_length", -1), + ], + ) + + # Wrap messages. This must be done after self._grpc_channel exists + self._prep_wrapped_messages(client_info) + + @property + def grpc_channel(self) -> aio.Channel: + """Create the channel designed to connect to this service. + + This property caches on the instance; repeated calls return + the same channel. + """ + # Return the channel from cache. + return self._grpc_channel + + @property + def get_model(self) -> Callable[ + [model.GetModelRequest], + Awaitable[model.Model]]: + r"""Return a callable for the get model method over gRPC. + + Gets the specified model resource by model ID. + + Returns: + Callable[[~.GetModelRequest], + Awaitable[~.Model]]: + A function that, when called, will call the underlying RPC + on the server. + """ + # Generate a "stub function" on-the-fly which will actually make + # the request. + # gRPC handles serialization and deserialization, so we just need + # to pass in the functions for each. + if 'get_model' not in self._stubs: + self._stubs['get_model'] = self.grpc_channel.unary_unary( + '/google.cloud.bigquery.v2.ModelService/GetModel', + request_serializer=model.GetModelRequest.serialize, + response_deserializer=model.Model.deserialize, + ) + return self._stubs['get_model'] + + @property + def list_models(self) -> Callable[ + [model.ListModelsRequest], + Awaitable[model.ListModelsResponse]]: + r"""Return a callable for the list models method over gRPC. + + Lists all models in the specified dataset. Requires + the READER dataset role. + + Returns: + Callable[[~.ListModelsRequest], + Awaitable[~.ListModelsResponse]]: + A function that, when called, will call the underlying RPC + on the server. + """ + # Generate a "stub function" on-the-fly which will actually make + # the request. + # gRPC handles serialization and deserialization, so we just need + # to pass in the functions for each. + if 'list_models' not in self._stubs: + self._stubs['list_models'] = self.grpc_channel.unary_unary( + '/google.cloud.bigquery.v2.ModelService/ListModels', + request_serializer=model.ListModelsRequest.serialize, + response_deserializer=model.ListModelsResponse.deserialize, + ) + return self._stubs['list_models'] + + @property + def patch_model(self) -> Callable[ + [gcb_model.PatchModelRequest], + Awaitable[gcb_model.Model]]: + r"""Return a callable for the patch model method over gRPC. + + Patch specific fields in the specified model. + + Returns: + Callable[[~.PatchModelRequest], + Awaitable[~.Model]]: + A function that, when called, will call the underlying RPC + on the server. + """ + # Generate a "stub function" on-the-fly which will actually make + # the request. + # gRPC handles serialization and deserialization, so we just need + # to pass in the functions for each. + if 'patch_model' not in self._stubs: + self._stubs['patch_model'] = self.grpc_channel.unary_unary( + '/google.cloud.bigquery.v2.ModelService/PatchModel', + request_serializer=gcb_model.PatchModelRequest.serialize, + response_deserializer=gcb_model.Model.deserialize, + ) + return self._stubs['patch_model'] + + @property + def delete_model(self) -> Callable[ + [model.DeleteModelRequest], + Awaitable[empty_pb2.Empty]]: + r"""Return a callable for the delete model method over gRPC. + + Deletes the model specified by modelId from the + dataset. + + Returns: + Callable[[~.DeleteModelRequest], + Awaitable[~.Empty]]: + A function that, when called, will call the underlying RPC + on the server. + """ + # Generate a "stub function" on-the-fly which will actually make + # the request. + # gRPC handles serialization and deserialization, so we just need + # to pass in the functions for each. + if 'delete_model' not in self._stubs: + self._stubs['delete_model'] = self.grpc_channel.unary_unary( + '/google.cloud.bigquery.v2.ModelService/DeleteModel', + request_serializer=model.DeleteModelRequest.serialize, + response_deserializer=empty_pb2.Empty.FromString, + ) + return self._stubs['delete_model'] + + +__all__ = ( + 'ModelServiceGrpcAsyncIOTransport', +) diff --git a/owl-bot-staging/v2/google/cloud/bigquery_v2/types/__init__.py b/owl-bot-staging/v2/google/cloud/bigquery_v2/types/__init__.py new file mode 100644 index 000000000..36a5ff64d --- /dev/null +++ b/owl-bot-staging/v2/google/cloud/bigquery_v2/types/__init__.py @@ -0,0 +1,54 @@ +# -*- coding: utf-8 -*- +# Copyright 2020 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# +from .encryption_config import ( + EncryptionConfiguration, +) +from .model import ( + DeleteModelRequest, + GetModelRequest, + ListModelsRequest, + ListModelsResponse, + Model, + PatchModelRequest, +) +from .model_reference import ( + ModelReference, +) +from .standard_sql import ( + StandardSqlDataType, + StandardSqlField, + StandardSqlStructType, + StandardSqlTableType, +) +from .table_reference import ( + TableReference, +) + +__all__ = ( + 'EncryptionConfiguration', + 'DeleteModelRequest', + 'GetModelRequest', + 'ListModelsRequest', + 'ListModelsResponse', + 'Model', + 'PatchModelRequest', + 'ModelReference', + 'StandardSqlDataType', + 'StandardSqlField', + 'StandardSqlStructType', + 'StandardSqlTableType', + 'TableReference', +) diff --git a/owl-bot-staging/v2/google/cloud/bigquery_v2/types/encryption_config.py b/owl-bot-staging/v2/google/cloud/bigquery_v2/types/encryption_config.py new file mode 100644 index 000000000..a1f60c1b9 --- /dev/null +++ b/owl-bot-staging/v2/google/cloud/bigquery_v2/types/encryption_config.py @@ -0,0 +1,47 @@ +# -*- coding: utf-8 -*- +# Copyright 2020 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# +import proto # type: ignore + +from google.protobuf import wrappers_pb2 # type: ignore + + +__protobuf__ = proto.module( + package='google.cloud.bigquery.v2', + manifest={ + 'EncryptionConfiguration', + }, +) + + +class EncryptionConfiguration(proto.Message): + r""" + Attributes: + kms_key_name (google.protobuf.wrappers_pb2.StringValue): + Optional. Describes the Cloud KMS encryption + key that will be used to protect destination + BigQuery table. The BigQuery Service Account + associated with your project requires access to + this encryption key. + """ + + kms_key_name = proto.Field( + proto.MESSAGE, + number=1, + message=wrappers_pb2.StringValue, + ) + + +__all__ = tuple(sorted(__protobuf__.manifest)) diff --git a/owl-bot-staging/v2/google/cloud/bigquery_v2/types/model.py b/owl-bot-staging/v2/google/cloud/bigquery_v2/types/model.py new file mode 100644 index 000000000..70d8684b1 --- /dev/null +++ b/owl-bot-staging/v2/google/cloud/bigquery_v2/types/model.py @@ -0,0 +1,1821 @@ +# -*- coding: utf-8 -*- +# Copyright 2020 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# +import proto # type: ignore + +from google.cloud.bigquery_v2.types import encryption_config +from google.cloud.bigquery_v2.types import model_reference as gcb_model_reference +from google.cloud.bigquery_v2.types import standard_sql +from google.cloud.bigquery_v2.types import table_reference +from google.protobuf import timestamp_pb2 # type: ignore +from google.protobuf import wrappers_pb2 # type: ignore + + +__protobuf__ = proto.module( + package='google.cloud.bigquery.v2', + manifest={ + 'Model', + 'GetModelRequest', + 'PatchModelRequest', + 'DeleteModelRequest', + 'ListModelsRequest', + 'ListModelsResponse', + }, +) + + +class Model(proto.Message): + r""" + Attributes: + etag (str): + Output only. A hash of this resource. + model_reference (google.cloud.bigquery_v2.types.ModelReference): + Required. Unique identifier for this model. + creation_time (int): + Output only. The time when this model was + created, in millisecs since the epoch. + last_modified_time (int): + Output only. The time when this model was + last modified, in millisecs since the epoch. + description (str): + Optional. A user-friendly description of this + model. + friendly_name (str): + Optional. A descriptive name for this model. + labels (Sequence[google.cloud.bigquery_v2.types.Model.LabelsEntry]): + The labels associated with this model. You + can use these to organize and group your models. + Label keys and values can be no longer than 63 + characters, can only contain lowercase letters, + numeric characters, underscores and dashes. + International characters are allowed. Label + values are optional. Label keys must start with + a letter and each label in the list must have a + different key. + expiration_time (int): + Optional. The time when this model expires, + in milliseconds since the epoch. If not present, + the model will persist indefinitely. Expired + models will be deleted and their storage + reclaimed. The defaultTableExpirationMs + property of the encapsulating dataset can be + used to set a default expirationTime on newly + created models. + location (str): + Output only. The geographic location where + the model resides. This value is inherited from + the dataset. + encryption_configuration (google.cloud.bigquery_v2.types.EncryptionConfiguration): + Custom encryption configuration (e.g., Cloud + KMS keys). This shows the encryption + configuration of the model data while stored in + BigQuery storage. This field can be used with + PatchModel to update encryption key for an + already encrypted model. + model_type (google.cloud.bigquery_v2.types.Model.ModelType): + Output only. Type of the model resource. + training_runs (Sequence[google.cloud.bigquery_v2.types.Model.TrainingRun]): + Output only. Information for all training runs in increasing + order of start_time. + feature_columns (Sequence[google.cloud.bigquery_v2.types.StandardSqlField]): + Output only. Input feature columns that were + used to train this model. + label_columns (Sequence[google.cloud.bigquery_v2.types.StandardSqlField]): + Output only. Label columns that were used to train this + model. The output of the model will have a "predicted_" + prefix to these columns. + """ + class ModelType(proto.Enum): + r"""Indicates the type of the Model.""" + MODEL_TYPE_UNSPECIFIED = 0 + LINEAR_REGRESSION = 1 + LOGISTIC_REGRESSION = 2 + KMEANS = 3 + MATRIX_FACTORIZATION = 4 + DNN_CLASSIFIER = 5 + TENSORFLOW = 6 + DNN_REGRESSOR = 7 + BOOSTED_TREE_REGRESSOR = 9 + BOOSTED_TREE_CLASSIFIER = 10 + ARIMA = 11 + AUTOML_REGRESSOR = 12 + AUTOML_CLASSIFIER = 13 + + class LossType(proto.Enum): + r"""Loss metric to evaluate model training performance.""" + LOSS_TYPE_UNSPECIFIED = 0 + MEAN_SQUARED_LOSS = 1 + MEAN_LOG_LOSS = 2 + + class DistanceType(proto.Enum): + r"""Distance metric used to compute the distance between two + points. + """ + DISTANCE_TYPE_UNSPECIFIED = 0 + EUCLIDEAN = 1 + COSINE = 2 + + class DataSplitMethod(proto.Enum): + r"""Indicates the method to split input data into multiple + tables. + """ + DATA_SPLIT_METHOD_UNSPECIFIED = 0 + RANDOM = 1 + CUSTOM = 2 + SEQUENTIAL = 3 + NO_SPLIT = 4 + AUTO_SPLIT = 5 + + class DataFrequency(proto.Enum): + r"""Type of supported data frequency for time series forecasting + models. + """ + DATA_FREQUENCY_UNSPECIFIED = 0 + AUTO_FREQUENCY = 1 + YEARLY = 2 + QUARTERLY = 3 + MONTHLY = 4 + WEEKLY = 5 + DAILY = 6 + HOURLY = 7 + + class HolidayRegion(proto.Enum): + r"""Type of supported holiday regions for time series forecasting + models. + """ + HOLIDAY_REGION_UNSPECIFIED = 0 + GLOBAL = 1 + NA = 2 + JAPAC = 3 + EMEA = 4 + LAC = 5 + AE = 6 + AR = 7 + AT = 8 + AU = 9 + BE = 10 + BR = 11 + CA = 12 + CH = 13 + CL = 14 + CN = 15 + CO = 16 + CS = 17 + CZ = 18 + DE = 19 + DK = 20 + DZ = 21 + EC = 22 + EE = 23 + EG = 24 + ES = 25 + FI = 26 + FR = 27 + GB = 28 + GR = 29 + HK = 30 + HU = 31 + ID = 32 + IE = 33 + IL = 34 + IN = 35 + IR = 36 + IT = 37 + JP = 38 + KR = 39 + LV = 40 + MA = 41 + MX = 42 + MY = 43 + NG = 44 + NL = 45 + NO = 46 + NZ = 47 + PE = 48 + PH = 49 + PK = 50 + PL = 51 + PT = 52 + RO = 53 + RS = 54 + RU = 55 + SA = 56 + SE = 57 + SG = 58 + SI = 59 + SK = 60 + TH = 61 + TR = 62 + TW = 63 + UA = 64 + US = 65 + VE = 66 + VN = 67 + ZA = 68 + + class LearnRateStrategy(proto.Enum): + r"""Indicates the learning rate optimization strategy to use.""" + LEARN_RATE_STRATEGY_UNSPECIFIED = 0 + LINE_SEARCH = 1 + CONSTANT = 2 + + class OptimizationStrategy(proto.Enum): + r"""Indicates the optimization strategy used for training.""" + OPTIMIZATION_STRATEGY_UNSPECIFIED = 0 + BATCH_GRADIENT_DESCENT = 1 + NORMAL_EQUATION = 2 + + class FeedbackType(proto.Enum): + r"""Indicates the training algorithm to use for matrix + factorization models. + """ + FEEDBACK_TYPE_UNSPECIFIED = 0 + IMPLICIT = 1 + EXPLICIT = 2 + + class SeasonalPeriod(proto.Message): + r""" """ + class SeasonalPeriodType(proto.Enum): + r"""""" + SEASONAL_PERIOD_TYPE_UNSPECIFIED = 0 + NO_SEASONALITY = 1 + DAILY = 2 + WEEKLY = 3 + MONTHLY = 4 + QUARTERLY = 5 + YEARLY = 6 + + class KmeansEnums(proto.Message): + r""" """ + class KmeansInitializationMethod(proto.Enum): + r"""Indicates the method used to initialize the centroids for + KMeans clustering algorithm. + """ + KMEANS_INITIALIZATION_METHOD_UNSPECIFIED = 0 + RANDOM = 1 + CUSTOM = 2 + KMEANS_PLUS_PLUS = 3 + + class RegressionMetrics(proto.Message): + r"""Evaluation metrics for regression and explicit feedback type + matrix factorization models. + + Attributes: + mean_absolute_error (google.protobuf.wrappers_pb2.DoubleValue): + Mean absolute error. + mean_squared_error (google.protobuf.wrappers_pb2.DoubleValue): + Mean squared error. + mean_squared_log_error (google.protobuf.wrappers_pb2.DoubleValue): + Mean squared log error. + median_absolute_error (google.protobuf.wrappers_pb2.DoubleValue): + Median absolute error. + r_squared (google.protobuf.wrappers_pb2.DoubleValue): + R^2 score. + """ + + mean_absolute_error = proto.Field( + proto.MESSAGE, + number=1, + message=wrappers_pb2.DoubleValue, + ) + mean_squared_error = proto.Field( + proto.MESSAGE, + number=2, + message=wrappers_pb2.DoubleValue, + ) + mean_squared_log_error = proto.Field( + proto.MESSAGE, + number=3, + message=wrappers_pb2.DoubleValue, + ) + median_absolute_error = proto.Field( + proto.MESSAGE, + number=4, + message=wrappers_pb2.DoubleValue, + ) + r_squared = proto.Field( + proto.MESSAGE, + number=5, + message=wrappers_pb2.DoubleValue, + ) + + class AggregateClassificationMetrics(proto.Message): + r"""Aggregate metrics for classification/classifier models. For + multi-class models, the metrics are either macro-averaged or + micro-averaged. When macro-averaged, the metrics are calculated + for each label and then an unweighted average is taken of those + values. When micro-averaged, the metric is calculated globally + by counting the total number of correctly predicted rows. + + Attributes: + precision (google.protobuf.wrappers_pb2.DoubleValue): + Precision is the fraction of actual positive + predictions that had positive actual labels. For + multiclass this is a macro-averaged metric + treating each class as a binary classifier. + recall (google.protobuf.wrappers_pb2.DoubleValue): + Recall is the fraction of actual positive + labels that were given a positive prediction. + For multiclass this is a macro-averaged metric. + accuracy (google.protobuf.wrappers_pb2.DoubleValue): + Accuracy is the fraction of predictions given + the correct label. For multiclass this is a + micro-averaged metric. + threshold (google.protobuf.wrappers_pb2.DoubleValue): + Threshold at which the metrics are computed. + For binary classification models this is the + positive class threshold. For multi-class + classfication models this is the confidence + threshold. + f1_score (google.protobuf.wrappers_pb2.DoubleValue): + The F1 score is an average of recall and + precision. For multiclass this is a macro- + averaged metric. + log_loss (google.protobuf.wrappers_pb2.DoubleValue): + Logarithmic Loss. For multiclass this is a + macro-averaged metric. + roc_auc (google.protobuf.wrappers_pb2.DoubleValue): + Area Under a ROC Curve. For multiclass this + is a macro-averaged metric. + """ + + precision = proto.Field( + proto.MESSAGE, + number=1, + message=wrappers_pb2.DoubleValue, + ) + recall = proto.Field( + proto.MESSAGE, + number=2, + message=wrappers_pb2.DoubleValue, + ) + accuracy = proto.Field( + proto.MESSAGE, + number=3, + message=wrappers_pb2.DoubleValue, + ) + threshold = proto.Field( + proto.MESSAGE, + number=4, + message=wrappers_pb2.DoubleValue, + ) + f1_score = proto.Field( + proto.MESSAGE, + number=5, + message=wrappers_pb2.DoubleValue, + ) + log_loss = proto.Field( + proto.MESSAGE, + number=6, + message=wrappers_pb2.DoubleValue, + ) + roc_auc = proto.Field( + proto.MESSAGE, + number=7, + message=wrappers_pb2.DoubleValue, + ) + + class BinaryClassificationMetrics(proto.Message): + r"""Evaluation metrics for binary classification/classifier + models. + + Attributes: + aggregate_classification_metrics (google.cloud.bigquery_v2.types.Model.AggregateClassificationMetrics): + Aggregate classification metrics. + binary_confusion_matrix_list (Sequence[google.cloud.bigquery_v2.types.Model.BinaryClassificationMetrics.BinaryConfusionMatrix]): + Binary confusion matrix at multiple + thresholds. + positive_label (str): + Label representing the positive class. + negative_label (str): + Label representing the negative class. + """ + + class BinaryConfusionMatrix(proto.Message): + r"""Confusion matrix for binary classification models. + Attributes: + positive_class_threshold (google.protobuf.wrappers_pb2.DoubleValue): + Threshold value used when computing each of + the following metric. + true_positives (google.protobuf.wrappers_pb2.Int64Value): + Number of true samples predicted as true. + false_positives (google.protobuf.wrappers_pb2.Int64Value): + Number of false samples predicted as true. + true_negatives (google.protobuf.wrappers_pb2.Int64Value): + Number of true samples predicted as false. + false_negatives (google.protobuf.wrappers_pb2.Int64Value): + Number of false samples predicted as false. + precision (google.protobuf.wrappers_pb2.DoubleValue): + The fraction of actual positive predictions + that had positive actual labels. + recall (google.protobuf.wrappers_pb2.DoubleValue): + The fraction of actual positive labels that + were given a positive prediction. + f1_score (google.protobuf.wrappers_pb2.DoubleValue): + The equally weighted average of recall and + precision. + accuracy (google.protobuf.wrappers_pb2.DoubleValue): + The fraction of predictions given the correct + label. + """ + + positive_class_threshold = proto.Field( + proto.MESSAGE, + number=1, + message=wrappers_pb2.DoubleValue, + ) + true_positives = proto.Field( + proto.MESSAGE, + number=2, + message=wrappers_pb2.Int64Value, + ) + false_positives = proto.Field( + proto.MESSAGE, + number=3, + message=wrappers_pb2.Int64Value, + ) + true_negatives = proto.Field( + proto.MESSAGE, + number=4, + message=wrappers_pb2.Int64Value, + ) + false_negatives = proto.Field( + proto.MESSAGE, + number=5, + message=wrappers_pb2.Int64Value, + ) + precision = proto.Field( + proto.MESSAGE, + number=6, + message=wrappers_pb2.DoubleValue, + ) + recall = proto.Field( + proto.MESSAGE, + number=7, + message=wrappers_pb2.DoubleValue, + ) + f1_score = proto.Field( + proto.MESSAGE, + number=8, + message=wrappers_pb2.DoubleValue, + ) + accuracy = proto.Field( + proto.MESSAGE, + number=9, + message=wrappers_pb2.DoubleValue, + ) + + aggregate_classification_metrics = proto.Field( + proto.MESSAGE, + number=1, + message='Model.AggregateClassificationMetrics', + ) + binary_confusion_matrix_list = proto.RepeatedField( + proto.MESSAGE, + number=2, + message='Model.BinaryClassificationMetrics.BinaryConfusionMatrix', + ) + positive_label = proto.Field( + proto.STRING, + number=3, + ) + negative_label = proto.Field( + proto.STRING, + number=4, + ) + + class MultiClassClassificationMetrics(proto.Message): + r"""Evaluation metrics for multi-class classification/classifier + models. + + Attributes: + aggregate_classification_metrics (google.cloud.bigquery_v2.types.Model.AggregateClassificationMetrics): + Aggregate classification metrics. + confusion_matrix_list (Sequence[google.cloud.bigquery_v2.types.Model.MultiClassClassificationMetrics.ConfusionMatrix]): + Confusion matrix at different thresholds. + """ + + class ConfusionMatrix(proto.Message): + r"""Confusion matrix for multi-class classification models. + Attributes: + confidence_threshold (google.protobuf.wrappers_pb2.DoubleValue): + Confidence threshold used when computing the + entries of the confusion matrix. + rows (Sequence[google.cloud.bigquery_v2.types.Model.MultiClassClassificationMetrics.ConfusionMatrix.Row]): + One row per actual label. + """ + + class Entry(proto.Message): + r"""A single entry in the confusion matrix. + Attributes: + predicted_label (str): + The predicted label. For confidence_threshold > 0, we will + also add an entry indicating the number of items under the + confidence threshold. + item_count (google.protobuf.wrappers_pb2.Int64Value): + Number of items being predicted as this + label. + """ + + predicted_label = proto.Field( + proto.STRING, + number=1, + ) + item_count = proto.Field( + proto.MESSAGE, + number=2, + message=wrappers_pb2.Int64Value, + ) + + class Row(proto.Message): + r"""A single row in the confusion matrix. + Attributes: + actual_label (str): + The original label of this row. + entries (Sequence[google.cloud.bigquery_v2.types.Model.MultiClassClassificationMetrics.ConfusionMatrix.Entry]): + Info describing predicted label distribution. + """ + + actual_label = proto.Field( + proto.STRING, + number=1, + ) + entries = proto.RepeatedField( + proto.MESSAGE, + number=2, + message='Model.MultiClassClassificationMetrics.ConfusionMatrix.Entry', + ) + + confidence_threshold = proto.Field( + proto.MESSAGE, + number=1, + message=wrappers_pb2.DoubleValue, + ) + rows = proto.RepeatedField( + proto.MESSAGE, + number=2, + message='Model.MultiClassClassificationMetrics.ConfusionMatrix.Row', + ) + + aggregate_classification_metrics = proto.Field( + proto.MESSAGE, + number=1, + message='Model.AggregateClassificationMetrics', + ) + confusion_matrix_list = proto.RepeatedField( + proto.MESSAGE, + number=2, + message='Model.MultiClassClassificationMetrics.ConfusionMatrix', + ) + + class ClusteringMetrics(proto.Message): + r"""Evaluation metrics for clustering models. + Attributes: + davies_bouldin_index (google.protobuf.wrappers_pb2.DoubleValue): + Davies-Bouldin index. + mean_squared_distance (google.protobuf.wrappers_pb2.DoubleValue): + Mean of squared distances between each sample + to its cluster centroid. + clusters (Sequence[google.cloud.bigquery_v2.types.Model.ClusteringMetrics.Cluster]): + [Beta] Information for all clusters. + """ + + class Cluster(proto.Message): + r"""Message containing the information about one cluster. + Attributes: + centroid_id (int): + Centroid id. + feature_values (Sequence[google.cloud.bigquery_v2.types.Model.ClusteringMetrics.Cluster.FeatureValue]): + Values of highly variant features for this + cluster. + count (google.protobuf.wrappers_pb2.Int64Value): + Count of training data rows that were + assigned to this cluster. + """ + + class FeatureValue(proto.Message): + r"""Representative value of a single feature within the cluster. + Attributes: + feature_column (str): + The feature column name. + numerical_value (google.protobuf.wrappers_pb2.DoubleValue): + The numerical feature value. This is the + centroid value for this feature. + categorical_value (google.cloud.bigquery_v2.types.Model.ClusteringMetrics.Cluster.FeatureValue.CategoricalValue): + The categorical feature value. + """ + + class CategoricalValue(proto.Message): + r"""Representative value of a categorical feature. + Attributes: + category_counts (Sequence[google.cloud.bigquery_v2.types.Model.ClusteringMetrics.Cluster.FeatureValue.CategoricalValue.CategoryCount]): + Counts of all categories for the categorical feature. If + there are more than ten categories, we return top ten (by + count) and return one more CategoryCount with category + "*OTHER*" and count as aggregate counts of remaining + categories. + """ + + class CategoryCount(proto.Message): + r"""Represents the count of a single category within the cluster. + Attributes: + category (str): + The name of category. + count (google.protobuf.wrappers_pb2.Int64Value): + The count of training samples matching the + category within the cluster. + """ + + category = proto.Field( + proto.STRING, + number=1, + ) + count = proto.Field( + proto.MESSAGE, + number=2, + message=wrappers_pb2.Int64Value, + ) + + category_counts = proto.RepeatedField( + proto.MESSAGE, + number=1, + message='Model.ClusteringMetrics.Cluster.FeatureValue.CategoricalValue.CategoryCount', + ) + + feature_column = proto.Field( + proto.STRING, + number=1, + ) + numerical_value = proto.Field( + proto.MESSAGE, + number=2, + oneof='value', + message=wrappers_pb2.DoubleValue, + ) + categorical_value = proto.Field( + proto.MESSAGE, + number=3, + oneof='value', + message='Model.ClusteringMetrics.Cluster.FeatureValue.CategoricalValue', + ) + + centroid_id = proto.Field( + proto.INT64, + number=1, + ) + feature_values = proto.RepeatedField( + proto.MESSAGE, + number=2, + message='Model.ClusteringMetrics.Cluster.FeatureValue', + ) + count = proto.Field( + proto.MESSAGE, + number=3, + message=wrappers_pb2.Int64Value, + ) + + davies_bouldin_index = proto.Field( + proto.MESSAGE, + number=1, + message=wrappers_pb2.DoubleValue, + ) + mean_squared_distance = proto.Field( + proto.MESSAGE, + number=2, + message=wrappers_pb2.DoubleValue, + ) + clusters = proto.RepeatedField( + proto.MESSAGE, + number=3, + message='Model.ClusteringMetrics.Cluster', + ) + + class RankingMetrics(proto.Message): + r"""Evaluation metrics used by weighted-ALS models specified by + feedback_type=implicit. + + Attributes: + mean_average_precision (google.protobuf.wrappers_pb2.DoubleValue): + Calculates a precision per user for all the + items by ranking them and then averages all the + precisions across all the users. + mean_squared_error (google.protobuf.wrappers_pb2.DoubleValue): + Similar to the mean squared error computed in + regression and explicit recommendation models + except instead of computing the rating directly, + the output from evaluate is computed against a + preference which is 1 or 0 depending on if the + rating exists or not. + normalized_discounted_cumulative_gain (google.protobuf.wrappers_pb2.DoubleValue): + A metric to determine the goodness of a + ranking calculated from the predicted confidence + by comparing it to an ideal rank measured by the + original ratings. + average_rank (google.protobuf.wrappers_pb2.DoubleValue): + Determines the goodness of a ranking by + computing the percentile rank from the predicted + confidence and dividing it by the original rank. + """ + + mean_average_precision = proto.Field( + proto.MESSAGE, + number=1, + message=wrappers_pb2.DoubleValue, + ) + mean_squared_error = proto.Field( + proto.MESSAGE, + number=2, + message=wrappers_pb2.DoubleValue, + ) + normalized_discounted_cumulative_gain = proto.Field( + proto.MESSAGE, + number=3, + message=wrappers_pb2.DoubleValue, + ) + average_rank = proto.Field( + proto.MESSAGE, + number=4, + message=wrappers_pb2.DoubleValue, + ) + + class ArimaForecastingMetrics(proto.Message): + r"""Model evaluation metrics for ARIMA forecasting models. + Attributes: + non_seasonal_order (Sequence[google.cloud.bigquery_v2.types.Model.ArimaOrder]): + Non-seasonal order. + arima_fitting_metrics (Sequence[google.cloud.bigquery_v2.types.Model.ArimaFittingMetrics]): + Arima model fitting metrics. + seasonal_periods (Sequence[google.cloud.bigquery_v2.types.Model.SeasonalPeriod.SeasonalPeriodType]): + Seasonal periods. Repeated because multiple + periods are supported for one time series. + has_drift (Sequence[bool]): + Whether Arima model fitted with drift or not. + It is always false when d is not 1. + time_series_id (Sequence[str]): + Id to differentiate different time series for + the large-scale case. + arima_single_model_forecasting_metrics (Sequence[google.cloud.bigquery_v2.types.Model.ArimaForecastingMetrics.ArimaSingleModelForecastingMetrics]): + Repeated as there can be many metric sets + (one for each model) in auto-arima and the + large-scale case. + """ + + class ArimaSingleModelForecastingMetrics(proto.Message): + r"""Model evaluation metrics for a single ARIMA forecasting + model. + + Attributes: + non_seasonal_order (google.cloud.bigquery_v2.types.Model.ArimaOrder): + Non-seasonal order. + arima_fitting_metrics (google.cloud.bigquery_v2.types.Model.ArimaFittingMetrics): + Arima fitting metrics. + has_drift (bool): + Is arima model fitted with drift or not. It + is always false when d is not 1. + time_series_id (str): + The id to indicate different time series. + seasonal_periods (Sequence[google.cloud.bigquery_v2.types.Model.SeasonalPeriod.SeasonalPeriodType]): + Seasonal periods. Repeated because multiple + periods are supported for one time series. + """ + + non_seasonal_order = proto.Field( + proto.MESSAGE, + number=1, + message='Model.ArimaOrder', + ) + arima_fitting_metrics = proto.Field( + proto.MESSAGE, + number=2, + message='Model.ArimaFittingMetrics', + ) + has_drift = proto.Field( + proto.BOOL, + number=3, + ) + time_series_id = proto.Field( + proto.STRING, + number=4, + ) + seasonal_periods = proto.RepeatedField( + proto.ENUM, + number=5, + enum='Model.SeasonalPeriod.SeasonalPeriodType', + ) + + non_seasonal_order = proto.RepeatedField( + proto.MESSAGE, + number=1, + message='Model.ArimaOrder', + ) + arima_fitting_metrics = proto.RepeatedField( + proto.MESSAGE, + number=2, + message='Model.ArimaFittingMetrics', + ) + seasonal_periods = proto.RepeatedField( + proto.ENUM, + number=3, + enum='Model.SeasonalPeriod.SeasonalPeriodType', + ) + has_drift = proto.RepeatedField( + proto.BOOL, + number=4, + ) + time_series_id = proto.RepeatedField( + proto.STRING, + number=5, + ) + arima_single_model_forecasting_metrics = proto.RepeatedField( + proto.MESSAGE, + number=6, + message='Model.ArimaForecastingMetrics.ArimaSingleModelForecastingMetrics', + ) + + class EvaluationMetrics(proto.Message): + r"""Evaluation metrics of a model. These are either computed on + all training data or just the eval data based on whether eval + data was used during training. These are not present for + imported models. + + Attributes: + regression_metrics (google.cloud.bigquery_v2.types.Model.RegressionMetrics): + Populated for regression models and explicit + feedback type matrix factorization models. + binary_classification_metrics (google.cloud.bigquery_v2.types.Model.BinaryClassificationMetrics): + Populated for binary + classification/classifier models. + multi_class_classification_metrics (google.cloud.bigquery_v2.types.Model.MultiClassClassificationMetrics): + Populated for multi-class + classification/classifier models. + clustering_metrics (google.cloud.bigquery_v2.types.Model.ClusteringMetrics): + Populated for clustering models. + ranking_metrics (google.cloud.bigquery_v2.types.Model.RankingMetrics): + Populated for implicit feedback type matrix + factorization models. + arima_forecasting_metrics (google.cloud.bigquery_v2.types.Model.ArimaForecastingMetrics): + Populated for ARIMA models. + """ + + regression_metrics = proto.Field( + proto.MESSAGE, + number=1, + oneof='metrics', + message='Model.RegressionMetrics', + ) + binary_classification_metrics = proto.Field( + proto.MESSAGE, + number=2, + oneof='metrics', + message='Model.BinaryClassificationMetrics', + ) + multi_class_classification_metrics = proto.Field( + proto.MESSAGE, + number=3, + oneof='metrics', + message='Model.MultiClassClassificationMetrics', + ) + clustering_metrics = proto.Field( + proto.MESSAGE, + number=4, + oneof='metrics', + message='Model.ClusteringMetrics', + ) + ranking_metrics = proto.Field( + proto.MESSAGE, + number=5, + oneof='metrics', + message='Model.RankingMetrics', + ) + arima_forecasting_metrics = proto.Field( + proto.MESSAGE, + number=6, + oneof='metrics', + message='Model.ArimaForecastingMetrics', + ) + + class DataSplitResult(proto.Message): + r"""Data split result. This contains references to the training + and evaluation data tables that were used to train the model. + + Attributes: + training_table (google.cloud.bigquery_v2.types.TableReference): + Table reference of the training data after + split. + evaluation_table (google.cloud.bigquery_v2.types.TableReference): + Table reference of the evaluation data after + split. + """ + + training_table = proto.Field( + proto.MESSAGE, + number=1, + message=table_reference.TableReference, + ) + evaluation_table = proto.Field( + proto.MESSAGE, + number=2, + message=table_reference.TableReference, + ) + + class ArimaOrder(proto.Message): + r"""Arima order, can be used for both non-seasonal and seasonal + parts. + + Attributes: + p (int): + Order of the autoregressive part. + d (int): + Order of the differencing part. + q (int): + Order of the moving-average part. + """ + + p = proto.Field( + proto.INT64, + number=1, + ) + d = proto.Field( + proto.INT64, + number=2, + ) + q = proto.Field( + proto.INT64, + number=3, + ) + + class ArimaFittingMetrics(proto.Message): + r"""ARIMA model fitting metrics. + Attributes: + log_likelihood (float): + Log-likelihood. + aic (float): + AIC. + variance (float): + Variance. + """ + + log_likelihood = proto.Field( + proto.DOUBLE, + number=1, + ) + aic = proto.Field( + proto.DOUBLE, + number=2, + ) + variance = proto.Field( + proto.DOUBLE, + number=3, + ) + + class GlobalExplanation(proto.Message): + r"""Global explanations containing the top most important + features after training. + + Attributes: + explanations (Sequence[google.cloud.bigquery_v2.types.Model.GlobalExplanation.Explanation]): + A list of the top global explanations. Sorted + by absolute value of attribution in descending + order. + class_label (str): + Class label for this set of global + explanations. Will be empty/null for binary + logistic and linear regression models. Sorted + alphabetically in descending order. + """ + + class Explanation(proto.Message): + r"""Explanation for a single feature. + Attributes: + feature_name (str): + Full name of the feature. For non-numerical features, will + be formatted like .. + Overall size of feature name will always be truncated to + first 120 characters. + attribution (google.protobuf.wrappers_pb2.DoubleValue): + Attribution of feature. + """ + + feature_name = proto.Field( + proto.STRING, + number=1, + ) + attribution = proto.Field( + proto.MESSAGE, + number=2, + message=wrappers_pb2.DoubleValue, + ) + + explanations = proto.RepeatedField( + proto.MESSAGE, + number=1, + message='Model.GlobalExplanation.Explanation', + ) + class_label = proto.Field( + proto.STRING, + number=2, + ) + + class TrainingRun(proto.Message): + r"""Information about a single training query run for the model. + Attributes: + training_options (google.cloud.bigquery_v2.types.Model.TrainingRun.TrainingOptions): + Options that were used for this training run, + includes user specified and default options that + were used. + start_time (google.protobuf.timestamp_pb2.Timestamp): + The start time of this training run. + results (Sequence[google.cloud.bigquery_v2.types.Model.TrainingRun.IterationResult]): + Output of each iteration run, results.size() <= + max_iterations. + evaluation_metrics (google.cloud.bigquery_v2.types.Model.EvaluationMetrics): + The evaluation metrics over training/eval + data that were computed at the end of training. + data_split_result (google.cloud.bigquery_v2.types.Model.DataSplitResult): + Data split result of the training run. Only + set when the input data is actually split. + global_explanations (Sequence[google.cloud.bigquery_v2.types.Model.GlobalExplanation]): + Global explanations for important features of + the model. For multi-class models, there is one + entry for each label class. For other models, + there is only one entry in the list. + """ + + class TrainingOptions(proto.Message): + r""" + Attributes: + max_iterations (int): + The maximum number of iterations in training. + Used only for iterative training algorithms. + loss_type (google.cloud.bigquery_v2.types.Model.LossType): + Type of loss function used during training + run. + learn_rate (float): + Learning rate in training. Used only for + iterative training algorithms. + l1_regularization (google.protobuf.wrappers_pb2.DoubleValue): + L1 regularization coefficient. + l2_regularization (google.protobuf.wrappers_pb2.DoubleValue): + L2 regularization coefficient. + min_relative_progress (google.protobuf.wrappers_pb2.DoubleValue): + When early_stop is true, stops training when accuracy + improvement is less than 'min_relative_progress'. Used only + for iterative training algorithms. + warm_start (google.protobuf.wrappers_pb2.BoolValue): + Whether to train a model from the last + checkpoint. + early_stop (google.protobuf.wrappers_pb2.BoolValue): + Whether to stop early when the loss doesn't improve + significantly any more (compared to min_relative_progress). + Used only for iterative training algorithms. + input_label_columns (Sequence[str]): + Name of input label columns in training data. + data_split_method (google.cloud.bigquery_v2.types.Model.DataSplitMethod): + The data split type for training and + evaluation, e.g. RANDOM. + data_split_eval_fraction (float): + The fraction of evaluation data over the + whole input data. The rest of data will be used + as training data. The format should be double. + Accurate to two decimal places. + Default value is 0.2. + data_split_column (str): + The column to split data with. This column won't be used as + a feature. + + 1. When data_split_method is CUSTOM, the corresponding + column should be boolean. The rows with true value tag + are eval data, and the false are training data. + 2. When data_split_method is SEQ, the first + DATA_SPLIT_EVAL_FRACTION rows (from smallest to largest) + in the corresponding column are used as training data, + and the rest are eval data. It respects the order in + Orderable data types: + https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types#data-type-properties + learn_rate_strategy (google.cloud.bigquery_v2.types.Model.LearnRateStrategy): + The strategy to determine learn rate for the + current iteration. + initial_learn_rate (float): + Specifies the initial learning rate for the + line search learn rate strategy. + label_class_weights (Sequence[google.cloud.bigquery_v2.types.Model.TrainingRun.TrainingOptions.LabelClassWeightsEntry]): + Weights associated with each label class, for + rebalancing the training data. Only applicable + for classification models. + user_column (str): + User column specified for matrix + factorization models. + item_column (str): + Item column specified for matrix + factorization models. + distance_type (google.cloud.bigquery_v2.types.Model.DistanceType): + Distance type for clustering models. + num_clusters (int): + Number of clusters for clustering models. + model_uri (str): + [Beta] Google Cloud Storage URI from which the model was + imported. Only applicable for imported models. + optimization_strategy (google.cloud.bigquery_v2.types.Model.OptimizationStrategy): + Optimization strategy for training linear + regression models. + hidden_units (Sequence[int]): + Hidden units for dnn models. + batch_size (int): + Batch size for dnn models. + dropout (google.protobuf.wrappers_pb2.DoubleValue): + Dropout probability for dnn models. + max_tree_depth (int): + Maximum depth of a tree for boosted tree + models. + subsample (float): + Subsample fraction of the training data to + grow tree to prevent overfitting for boosted + tree models. + min_split_loss (google.protobuf.wrappers_pb2.DoubleValue): + Minimum split loss for boosted tree models. + num_factors (int): + Num factors specified for matrix + factorization models. + feedback_type (google.cloud.bigquery_v2.types.Model.FeedbackType): + Feedback type that specifies which algorithm + to run for matrix factorization. + wals_alpha (google.protobuf.wrappers_pb2.DoubleValue): + Hyperparameter for matrix factoration when + implicit feedback type is specified. + kmeans_initialization_method (google.cloud.bigquery_v2.types.Model.KmeansEnums.KmeansInitializationMethod): + The method used to initialize the centroids + for kmeans algorithm. + kmeans_initialization_column (str): + The column used to provide the initial centroids for kmeans + algorithm when kmeans_initialization_method is CUSTOM. + time_series_timestamp_column (str): + Column to be designated as time series + timestamp for ARIMA model. + time_series_data_column (str): + Column to be designated as time series data + for ARIMA model. + auto_arima (bool): + Whether to enable auto ARIMA or not. + non_seasonal_order (google.cloud.bigquery_v2.types.Model.ArimaOrder): + A specification of the non-seasonal part of + the ARIMA model: the three components (p, d, q) + are the AR order, the degree of differencing, + and the MA order. + data_frequency (google.cloud.bigquery_v2.types.Model.DataFrequency): + The data frequency of a time series. + include_drift (bool): + Include drift when fitting an ARIMA model. + holiday_region (google.cloud.bigquery_v2.types.Model.HolidayRegion): + The geographical region based on which the + holidays are considered in time series modeling. + If a valid value is specified, then holiday + effects modeling is enabled. + time_series_id_column (str): + The id column that will be used to indicate + different time series to forecast in parallel. + horizon (int): + The number of periods ahead that need to be + forecasted. + preserve_input_structs (bool): + Whether to preserve the input structs in output feature + names. Suppose there is a struct A with field b. When false + (default), the output feature name is A_b. When true, the + output feature name is A.b. + auto_arima_max_order (int): + The max value of non-seasonal p and q. + """ + + max_iterations = proto.Field( + proto.INT64, + number=1, + ) + loss_type = proto.Field( + proto.ENUM, + number=2, + enum='Model.LossType', + ) + learn_rate = proto.Field( + proto.DOUBLE, + number=3, + ) + l1_regularization = proto.Field( + proto.MESSAGE, + number=4, + message=wrappers_pb2.DoubleValue, + ) + l2_regularization = proto.Field( + proto.MESSAGE, + number=5, + message=wrappers_pb2.DoubleValue, + ) + min_relative_progress = proto.Field( + proto.MESSAGE, + number=6, + message=wrappers_pb2.DoubleValue, + ) + warm_start = proto.Field( + proto.MESSAGE, + number=7, + message=wrappers_pb2.BoolValue, + ) + early_stop = proto.Field( + proto.MESSAGE, + number=8, + message=wrappers_pb2.BoolValue, + ) + input_label_columns = proto.RepeatedField( + proto.STRING, + number=9, + ) + data_split_method = proto.Field( + proto.ENUM, + number=10, + enum='Model.DataSplitMethod', + ) + data_split_eval_fraction = proto.Field( + proto.DOUBLE, + number=11, + ) + data_split_column = proto.Field( + proto.STRING, + number=12, + ) + learn_rate_strategy = proto.Field( + proto.ENUM, + number=13, + enum='Model.LearnRateStrategy', + ) + initial_learn_rate = proto.Field( + proto.DOUBLE, + number=16, + ) + label_class_weights = proto.MapField( + proto.STRING, + proto.DOUBLE, + number=17, + ) + user_column = proto.Field( + proto.STRING, + number=18, + ) + item_column = proto.Field( + proto.STRING, + number=19, + ) + distance_type = proto.Field( + proto.ENUM, + number=20, + enum='Model.DistanceType', + ) + num_clusters = proto.Field( + proto.INT64, + number=21, + ) + model_uri = proto.Field( + proto.STRING, + number=22, + ) + optimization_strategy = proto.Field( + proto.ENUM, + number=23, + enum='Model.OptimizationStrategy', + ) + hidden_units = proto.RepeatedField( + proto.INT64, + number=24, + ) + batch_size = proto.Field( + proto.INT64, + number=25, + ) + dropout = proto.Field( + proto.MESSAGE, + number=26, + message=wrappers_pb2.DoubleValue, + ) + max_tree_depth = proto.Field( + proto.INT64, + number=27, + ) + subsample = proto.Field( + proto.DOUBLE, + number=28, + ) + min_split_loss = proto.Field( + proto.MESSAGE, + number=29, + message=wrappers_pb2.DoubleValue, + ) + num_factors = proto.Field( + proto.INT64, + number=30, + ) + feedback_type = proto.Field( + proto.ENUM, + number=31, + enum='Model.FeedbackType', + ) + wals_alpha = proto.Field( + proto.MESSAGE, + number=32, + message=wrappers_pb2.DoubleValue, + ) + kmeans_initialization_method = proto.Field( + proto.ENUM, + number=33, + enum='Model.KmeansEnums.KmeansInitializationMethod', + ) + kmeans_initialization_column = proto.Field( + proto.STRING, + number=34, + ) + time_series_timestamp_column = proto.Field( + proto.STRING, + number=35, + ) + time_series_data_column = proto.Field( + proto.STRING, + number=36, + ) + auto_arima = proto.Field( + proto.BOOL, + number=37, + ) + non_seasonal_order = proto.Field( + proto.MESSAGE, + number=38, + message='Model.ArimaOrder', + ) + data_frequency = proto.Field( + proto.ENUM, + number=39, + enum='Model.DataFrequency', + ) + include_drift = proto.Field( + proto.BOOL, + number=41, + ) + holiday_region = proto.Field( + proto.ENUM, + number=42, + enum='Model.HolidayRegion', + ) + time_series_id_column = proto.Field( + proto.STRING, + number=43, + ) + horizon = proto.Field( + proto.INT64, + number=44, + ) + preserve_input_structs = proto.Field( + proto.BOOL, + number=45, + ) + auto_arima_max_order = proto.Field( + proto.INT64, + number=46, + ) + + class IterationResult(proto.Message): + r"""Information about a single iteration of the training run. + Attributes: + index (google.protobuf.wrappers_pb2.Int32Value): + Index of the iteration, 0 based. + duration_ms (google.protobuf.wrappers_pb2.Int64Value): + Time taken to run the iteration in + milliseconds. + training_loss (google.protobuf.wrappers_pb2.DoubleValue): + Loss computed on the training data at the end + of iteration. + eval_loss (google.protobuf.wrappers_pb2.DoubleValue): + Loss computed on the eval data at the end of + iteration. + learn_rate (float): + Learn rate used for this iteration. + cluster_infos (Sequence[google.cloud.bigquery_v2.types.Model.TrainingRun.IterationResult.ClusterInfo]): + Information about top clusters for clustering + models. + arima_result (google.cloud.bigquery_v2.types.Model.TrainingRun.IterationResult.ArimaResult): + + """ + + class ClusterInfo(proto.Message): + r"""Information about a single cluster for clustering model. + Attributes: + centroid_id (int): + Centroid id. + cluster_radius (google.protobuf.wrappers_pb2.DoubleValue): + Cluster radius, the average distance from + centroid to each point assigned to the cluster. + cluster_size (google.protobuf.wrappers_pb2.Int64Value): + Cluster size, the total number of points + assigned to the cluster. + """ + + centroid_id = proto.Field( + proto.INT64, + number=1, + ) + cluster_radius = proto.Field( + proto.MESSAGE, + number=2, + message=wrappers_pb2.DoubleValue, + ) + cluster_size = proto.Field( + proto.MESSAGE, + number=3, + message=wrappers_pb2.Int64Value, + ) + + class ArimaResult(proto.Message): + r"""(Auto-)arima fitting result. Wrap everything in ArimaResult + for easier refactoring if we want to use model-specific + iteration results. + + Attributes: + arima_model_info (Sequence[google.cloud.bigquery_v2.types.Model.TrainingRun.IterationResult.ArimaResult.ArimaModelInfo]): + This message is repeated because there are + multiple arima models fitted in auto-arima. For + non-auto-arima model, its size is one. + seasonal_periods (Sequence[google.cloud.bigquery_v2.types.Model.SeasonalPeriod.SeasonalPeriodType]): + Seasonal periods. Repeated because multiple + periods are supported for one time series. + """ + + class ArimaCoefficients(proto.Message): + r"""Arima coefficients. + Attributes: + auto_regressive_coefficients (Sequence[float]): + Auto-regressive coefficients, an array of + double. + moving_average_coefficients (Sequence[float]): + Moving-average coefficients, an array of + double. + intercept_coefficient (float): + Intercept coefficient, just a double not an + array. + """ + + auto_regressive_coefficients = proto.RepeatedField( + proto.DOUBLE, + number=1, + ) + moving_average_coefficients = proto.RepeatedField( + proto.DOUBLE, + number=2, + ) + intercept_coefficient = proto.Field( + proto.DOUBLE, + number=3, + ) + + class ArimaModelInfo(proto.Message): + r"""Arima model information. + Attributes: + non_seasonal_order (google.cloud.bigquery_v2.types.Model.ArimaOrder): + Non-seasonal order. + arima_coefficients (google.cloud.bigquery_v2.types.Model.TrainingRun.IterationResult.ArimaResult.ArimaCoefficients): + Arima coefficients. + arima_fitting_metrics (google.cloud.bigquery_v2.types.Model.ArimaFittingMetrics): + Arima fitting metrics. + has_drift (bool): + Whether Arima model fitted with drift or not. + It is always false when d is not 1. + time_series_id (str): + The id to indicate different time series. + seasonal_periods (Sequence[google.cloud.bigquery_v2.types.Model.SeasonalPeriod.SeasonalPeriodType]): + Seasonal periods. Repeated because multiple + periods are supported for one time series. + """ + + non_seasonal_order = proto.Field( + proto.MESSAGE, + number=1, + message='Model.ArimaOrder', + ) + arima_coefficients = proto.Field( + proto.MESSAGE, + number=2, + message='Model.TrainingRun.IterationResult.ArimaResult.ArimaCoefficients', + ) + arima_fitting_metrics = proto.Field( + proto.MESSAGE, + number=3, + message='Model.ArimaFittingMetrics', + ) + has_drift = proto.Field( + proto.BOOL, + number=4, + ) + time_series_id = proto.Field( + proto.STRING, + number=5, + ) + seasonal_periods = proto.RepeatedField( + proto.ENUM, + number=6, + enum='Model.SeasonalPeriod.SeasonalPeriodType', + ) + + arima_model_info = proto.RepeatedField( + proto.MESSAGE, + number=1, + message='Model.TrainingRun.IterationResult.ArimaResult.ArimaModelInfo', + ) + seasonal_periods = proto.RepeatedField( + proto.ENUM, + number=2, + enum='Model.SeasonalPeriod.SeasonalPeriodType', + ) + + index = proto.Field( + proto.MESSAGE, + number=1, + message=wrappers_pb2.Int32Value, + ) + duration_ms = proto.Field( + proto.MESSAGE, + number=4, + message=wrappers_pb2.Int64Value, + ) + training_loss = proto.Field( + proto.MESSAGE, + number=5, + message=wrappers_pb2.DoubleValue, + ) + eval_loss = proto.Field( + proto.MESSAGE, + number=6, + message=wrappers_pb2.DoubleValue, + ) + learn_rate = proto.Field( + proto.DOUBLE, + number=7, + ) + cluster_infos = proto.RepeatedField( + proto.MESSAGE, + number=8, + message='Model.TrainingRun.IterationResult.ClusterInfo', + ) + arima_result = proto.Field( + proto.MESSAGE, + number=9, + message='Model.TrainingRun.IterationResult.ArimaResult', + ) + + training_options = proto.Field( + proto.MESSAGE, + number=1, + message='Model.TrainingRun.TrainingOptions', + ) + start_time = proto.Field( + proto.MESSAGE, + number=8, + message=timestamp_pb2.Timestamp, + ) + results = proto.RepeatedField( + proto.MESSAGE, + number=6, + message='Model.TrainingRun.IterationResult', + ) + evaluation_metrics = proto.Field( + proto.MESSAGE, + number=7, + message='Model.EvaluationMetrics', + ) + data_split_result = proto.Field( + proto.MESSAGE, + number=9, + message='Model.DataSplitResult', + ) + global_explanations = proto.RepeatedField( + proto.MESSAGE, + number=10, + message='Model.GlobalExplanation', + ) + + etag = proto.Field( + proto.STRING, + number=1, + ) + model_reference = proto.Field( + proto.MESSAGE, + number=2, + message=gcb_model_reference.ModelReference, + ) + creation_time = proto.Field( + proto.INT64, + number=5, + ) + last_modified_time = proto.Field( + proto.INT64, + number=6, + ) + description = proto.Field( + proto.STRING, + number=12, + ) + friendly_name = proto.Field( + proto.STRING, + number=14, + ) + labels = proto.MapField( + proto.STRING, + proto.STRING, + number=15, + ) + expiration_time = proto.Field( + proto.INT64, + number=16, + ) + location = proto.Field( + proto.STRING, + number=13, + ) + encryption_configuration = proto.Field( + proto.MESSAGE, + number=17, + message=encryption_config.EncryptionConfiguration, + ) + model_type = proto.Field( + proto.ENUM, + number=7, + enum=ModelType, + ) + training_runs = proto.RepeatedField( + proto.MESSAGE, + number=9, + message=TrainingRun, + ) + feature_columns = proto.RepeatedField( + proto.MESSAGE, + number=10, + message=standard_sql.StandardSqlField, + ) + label_columns = proto.RepeatedField( + proto.MESSAGE, + number=11, + message=standard_sql.StandardSqlField, + ) + + +class GetModelRequest(proto.Message): + r""" + Attributes: + project_id (str): + Required. Project ID of the requested model. + dataset_id (str): + Required. Dataset ID of the requested model. + model_id (str): + Required. Model ID of the requested model. + """ + + project_id = proto.Field( + proto.STRING, + number=1, + ) + dataset_id = proto.Field( + proto.STRING, + number=2, + ) + model_id = proto.Field( + proto.STRING, + number=3, + ) + + +class PatchModelRequest(proto.Message): + r""" + Attributes: + project_id (str): + Required. Project ID of the model to patch. + dataset_id (str): + Required. Dataset ID of the model to patch. + model_id (str): + Required. Model ID of the model to patch. + model (google.cloud.bigquery_v2.types.Model): + Required. Patched model. + Follows RFC5789 patch semantics. Missing fields + are not updated. To clear a field, explicitly + set to default value. + """ + + project_id = proto.Field( + proto.STRING, + number=1, + ) + dataset_id = proto.Field( + proto.STRING, + number=2, + ) + model_id = proto.Field( + proto.STRING, + number=3, + ) + model = proto.Field( + proto.MESSAGE, + number=4, + message='Model', + ) + + +class DeleteModelRequest(proto.Message): + r""" + Attributes: + project_id (str): + Required. Project ID of the model to delete. + dataset_id (str): + Required. Dataset ID of the model to delete. + model_id (str): + Required. Model ID of the model to delete. + """ + + project_id = proto.Field( + proto.STRING, + number=1, + ) + dataset_id = proto.Field( + proto.STRING, + number=2, + ) + model_id = proto.Field( + proto.STRING, + number=3, + ) + + +class ListModelsRequest(proto.Message): + r""" + Attributes: + project_id (str): + Required. Project ID of the models to list. + dataset_id (str): + Required. Dataset ID of the models to list. + max_results (google.protobuf.wrappers_pb2.UInt32Value): + The maximum number of results to return in a + single response page. Leverage the page tokens + to iterate through the entire collection. + page_token (str): + Page token, returned by a previous call to + request the next page of results + """ + + project_id = proto.Field( + proto.STRING, + number=1, + ) + dataset_id = proto.Field( + proto.STRING, + number=2, + ) + max_results = proto.Field( + proto.MESSAGE, + number=3, + message=wrappers_pb2.UInt32Value, + ) + page_token = proto.Field( + proto.STRING, + number=4, + ) + + +class ListModelsResponse(proto.Message): + r""" + Attributes: + models (Sequence[google.cloud.bigquery_v2.types.Model]): + Models in the requested dataset. Only the following fields + are populated: model_reference, model_type, creation_time, + last_modified_time and labels. + next_page_token (str): + A token to request the next page of results. + """ + + @property + def raw_page(self): + return self + + models = proto.RepeatedField( + proto.MESSAGE, + number=1, + message='Model', + ) + next_page_token = proto.Field( + proto.STRING, + number=2, + ) + + +__all__ = tuple(sorted(__protobuf__.manifest)) diff --git a/owl-bot-staging/v2/google/cloud/bigquery_v2/types/model_reference.py b/owl-bot-staging/v2/google/cloud/bigquery_v2/types/model_reference.py new file mode 100644 index 000000000..7dfe7b30f --- /dev/null +++ b/owl-bot-staging/v2/google/cloud/bigquery_v2/types/model_reference.py @@ -0,0 +1,56 @@ +# -*- coding: utf-8 -*- +# Copyright 2020 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# +import proto # type: ignore + + +__protobuf__ = proto.module( + package='google.cloud.bigquery.v2', + manifest={ + 'ModelReference', + }, +) + + +class ModelReference(proto.Message): + r"""Id path of a model. + Attributes: + project_id (str): + Required. The ID of the project containing + this model. + dataset_id (str): + Required. The ID of the dataset containing + this model. + model_id (str): + Required. The ID of the model. The ID must contain only + letters (a-z, A-Z), numbers (0-9), or underscores (_). The + maximum length is 1,024 characters. + """ + + project_id = proto.Field( + proto.STRING, + number=1, + ) + dataset_id = proto.Field( + proto.STRING, + number=2, + ) + model_id = proto.Field( + proto.STRING, + number=3, + ) + + +__all__ = tuple(sorted(__protobuf__.manifest)) diff --git a/owl-bot-staging/v2/google/cloud/bigquery_v2/types/standard_sql.py b/owl-bot-staging/v2/google/cloud/bigquery_v2/types/standard_sql.py new file mode 100644 index 000000000..dfe315e35 --- /dev/null +++ b/owl-bot-staging/v2/google/cloud/bigquery_v2/types/standard_sql.py @@ -0,0 +1,141 @@ +# -*- coding: utf-8 -*- +# Copyright 2020 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# +import proto # type: ignore + + +__protobuf__ = proto.module( + package='google.cloud.bigquery.v2', + manifest={ + 'StandardSqlDataType', + 'StandardSqlField', + 'StandardSqlStructType', + 'StandardSqlTableType', + }, +) + + +class StandardSqlDataType(proto.Message): + r"""The type of a variable, e.g., a function argument. Examples: INT64: + {type_kind="INT64"} ARRAY: {type_kind="ARRAY", + array_element_type="STRING"} STRUCT: + {type_kind="STRUCT", struct_type={fields=[ {name="x", + type={type_kind="STRING"}}, {name="y", type={type_kind="ARRAY", + array_element_type="DATE"}} ]}} + + Attributes: + type_kind (google.cloud.bigquery_v2.types.StandardSqlDataType.TypeKind): + Required. The top level type of this field. + Can be any standard SQL data type (e.g., + "INT64", "DATE", "ARRAY"). + array_element_type (google.cloud.bigquery_v2.types.StandardSqlDataType): + The type of the array's elements, if type_kind = "ARRAY". + struct_type (google.cloud.bigquery_v2.types.StandardSqlStructType): + The fields of this struct, in order, if type_kind = + "STRUCT". + """ + class TypeKind(proto.Enum): + r"""""" + TYPE_KIND_UNSPECIFIED = 0 + INT64 = 2 + BOOL = 5 + FLOAT64 = 7 + STRING = 8 + BYTES = 9 + TIMESTAMP = 19 + DATE = 10 + TIME = 20 + DATETIME = 21 + INTERVAL = 26 + GEOGRAPHY = 22 + NUMERIC = 23 + BIGNUMERIC = 24 + JSON = 25 + ARRAY = 16 + STRUCT = 17 + + type_kind = proto.Field( + proto.ENUM, + number=1, + enum=TypeKind, + ) + array_element_type = proto.Field( + proto.MESSAGE, + number=2, + oneof='sub_type', + message='StandardSqlDataType', + ) + struct_type = proto.Field( + proto.MESSAGE, + number=3, + oneof='sub_type', + message='StandardSqlStructType', + ) + + +class StandardSqlField(proto.Message): + r"""A field or a column. + Attributes: + name (str): + Optional. The name of this field. Can be + absent for struct fields. + type_ (google.cloud.bigquery_v2.types.StandardSqlDataType): + Optional. The type of this parameter. Absent + if not explicitly specified (e.g., CREATE + FUNCTION statement can omit the return type; in + this case the output parameter does not have + this "type" field). + """ + + name = proto.Field( + proto.STRING, + number=1, + ) + type_ = proto.Field( + proto.MESSAGE, + number=2, + message='StandardSqlDataType', + ) + + +class StandardSqlStructType(proto.Message): + r""" + Attributes: + fields (Sequence[google.cloud.bigquery_v2.types.StandardSqlField]): + + """ + + fields = proto.RepeatedField( + proto.MESSAGE, + number=1, + message='StandardSqlField', + ) + + +class StandardSqlTableType(proto.Message): + r"""A table type + Attributes: + columns (Sequence[google.cloud.bigquery_v2.types.StandardSqlField]): + The columns in this table type + """ + + columns = proto.RepeatedField( + proto.MESSAGE, + number=1, + message='StandardSqlField', + ) + + +__all__ = tuple(sorted(__protobuf__.manifest)) diff --git a/owl-bot-staging/v2/google/cloud/bigquery_v2/types/table_reference.py b/owl-bot-staging/v2/google/cloud/bigquery_v2/types/table_reference.py new file mode 100644 index 000000000..2e6a37202 --- /dev/null +++ b/owl-bot-staging/v2/google/cloud/bigquery_v2/types/table_reference.py @@ -0,0 +1,58 @@ +# -*- coding: utf-8 -*- +# Copyright 2020 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# +import proto # type: ignore + + +__protobuf__ = proto.module( + package='google.cloud.bigquery.v2', + manifest={ + 'TableReference', + }, +) + + +class TableReference(proto.Message): + r""" + Attributes: + project_id (str): + Required. The ID of the project containing + this table. + dataset_id (str): + Required. The ID of the dataset containing + this table. + table_id (str): + Required. The ID of the table. The ID must contain only + letters (a-z, A-Z), numbers (0-9), or underscores (_). The + maximum length is 1,024 characters. Certain operations allow + suffixing of the table ID with a partition decorator, such + as ``sample_table$20190123``. + """ + + project_id = proto.Field( + proto.STRING, + number=1, + ) + dataset_id = proto.Field( + proto.STRING, + number=2, + ) + table_id = proto.Field( + proto.STRING, + number=3, + ) + + +__all__ = tuple(sorted(__protobuf__.manifest)) diff --git a/owl-bot-staging/v2/mypy.ini b/owl-bot-staging/v2/mypy.ini new file mode 100644 index 000000000..4505b4854 --- /dev/null +++ b/owl-bot-staging/v2/mypy.ini @@ -0,0 +1,3 @@ +[mypy] +python_version = 3.6 +namespace_packages = True diff --git a/owl-bot-staging/v2/noxfile.py b/owl-bot-staging/v2/noxfile.py new file mode 100644 index 000000000..fa6a0142d --- /dev/null +++ b/owl-bot-staging/v2/noxfile.py @@ -0,0 +1,132 @@ +# -*- coding: utf-8 -*- +# Copyright 2020 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# +import os +import pathlib +import shutil +import subprocess +import sys + + +import nox # type: ignore + +CURRENT_DIRECTORY = pathlib.Path(__file__).parent.absolute() + +LOWER_BOUND_CONSTRAINTS_FILE = CURRENT_DIRECTORY / "constraints.txt" +PACKAGE_NAME = subprocess.check_output([sys.executable, "setup.py", "--name"], encoding="utf-8") + + +nox.sessions = [ + "unit", + "cover", + "mypy", + "check_lower_bounds" + # exclude update_lower_bounds from default + "docs", +] + +@nox.session(python=['3.6', '3.7', '3.8', '3.9']) +def unit(session): + """Run the unit test suite.""" + + session.install('coverage', 'pytest', 'pytest-cov', 'asyncmock', 'pytest-asyncio') + session.install('-e', '.') + + session.run( + 'py.test', + '--quiet', + '--cov=google/cloud/bigquery_v2/', + '--cov-config=.coveragerc', + '--cov-report=term', + '--cov-report=html', + os.path.join('tests', 'unit', ''.join(session.posargs)) + ) + + +@nox.session(python='3.7') +def cover(session): + """Run the final coverage report. + This outputs the coverage report aggregating coverage from the unit + test runs (not system test runs), and then erases coverage data. + """ + session.install("coverage", "pytest-cov") + session.run("coverage", "report", "--show-missing", "--fail-under=100") + + session.run("coverage", "erase") + + +@nox.session(python=['3.6', '3.7']) +def mypy(session): + """Run the type checker.""" + session.install('mypy', 'types-pkg_resources') + session.install('.') + session.run( + 'mypy', + '--explicit-package-bases', + 'google', + ) + + +@nox.session +def update_lower_bounds(session): + """Update lower bounds in constraints.txt to match setup.py""" + session.install('google-cloud-testutils') + session.install('.') + + session.run( + 'lower-bound-checker', + 'update', + '--package-name', + PACKAGE_NAME, + '--constraints-file', + str(LOWER_BOUND_CONSTRAINTS_FILE), + ) + + +@nox.session +def check_lower_bounds(session): + """Check lower bounds in setup.py are reflected in constraints file""" + session.install('google-cloud-testutils') + session.install('.') + + session.run( + 'lower-bound-checker', + 'check', + '--package-name', + PACKAGE_NAME, + '--constraints-file', + str(LOWER_BOUND_CONSTRAINTS_FILE), + ) + +@nox.session(python='3.6') +def docs(session): + """Build the docs for this library.""" + + session.install("-e", ".") + session.install("sphinx<3.0.0", "alabaster", "recommonmark") + + shutil.rmtree(os.path.join("docs", "_build"), ignore_errors=True) + session.run( + "sphinx-build", + "-W", # warnings as errors + "-T", # show full traceback on exception + "-N", # no colors + "-b", + "html", + "-d", + os.path.join("docs", "_build", "doctrees", ""), + os.path.join("docs", ""), + os.path.join("docs", "_build", "html", ""), + ) diff --git a/owl-bot-staging/v2/scripts/fixup_bigquery_v2_keywords.py b/owl-bot-staging/v2/scripts/fixup_bigquery_v2_keywords.py new file mode 100644 index 000000000..b1bdb7647 --- /dev/null +++ b/owl-bot-staging/v2/scripts/fixup_bigquery_v2_keywords.py @@ -0,0 +1,179 @@ +#! /usr/bin/env python3 +# -*- coding: utf-8 -*- +# Copyright 2020 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# +import argparse +import os +import libcst as cst +import pathlib +import sys +from typing import (Any, Callable, Dict, List, Sequence, Tuple) + + +def partition( + predicate: Callable[[Any], bool], + iterator: Sequence[Any] +) -> Tuple[List[Any], List[Any]]: + """A stable, out-of-place partition.""" + results = ([], []) + + for i in iterator: + results[int(predicate(i))].append(i) + + # Returns trueList, falseList + return results[1], results[0] + + +class bigqueryCallTransformer(cst.CSTTransformer): + CTRL_PARAMS: Tuple[str] = ('retry', 'timeout', 'metadata') + METHOD_TO_PARAMS: Dict[str, Tuple[str]] = { + 'delete_model': ('project_id', 'dataset_id', 'model_id', ), + 'get_model': ('project_id', 'dataset_id', 'model_id', ), + 'list_models': ('project_id', 'dataset_id', 'max_results', 'page_token', ), + 'patch_model': ('project_id', 'dataset_id', 'model_id', 'model', ), + } + + def leave_Call(self, original: cst.Call, updated: cst.Call) -> cst.CSTNode: + try: + key = original.func.attr.value + kword_params = self.METHOD_TO_PARAMS[key] + except (AttributeError, KeyError): + # Either not a method from the API or too convoluted to be sure. + return updated + + # If the existing code is valid, keyword args come after positional args. + # Therefore, all positional args must map to the first parameters. + args, kwargs = partition(lambda a: not bool(a.keyword), updated.args) + if any(k.keyword.value == "request" for k in kwargs): + # We've already fixed this file, don't fix it again. + return updated + + kwargs, ctrl_kwargs = partition( + lambda a: not a.keyword.value in self.CTRL_PARAMS, + kwargs + ) + + args, ctrl_args = args[:len(kword_params)], args[len(kword_params):] + ctrl_kwargs.extend(cst.Arg(value=a.value, keyword=cst.Name(value=ctrl)) + for a, ctrl in zip(ctrl_args, self.CTRL_PARAMS)) + + request_arg = cst.Arg( + value=cst.Dict([ + cst.DictElement( + cst.SimpleString("'{}'".format(name)), +cst.Element(value=arg.value) + ) + # Note: the args + kwargs looks silly, but keep in mind that + # the control parameters had to be stripped out, and that + # those could have been passed positionally or by keyword. + for name, arg in zip(kword_params, args + kwargs)]), + keyword=cst.Name("request") + ) + + return updated.with_changes( + args=[request_arg] + ctrl_kwargs + ) + + +def fix_files( + in_dir: pathlib.Path, + out_dir: pathlib.Path, + *, + transformer=bigqueryCallTransformer(), +): + """Duplicate the input dir to the output dir, fixing file method calls. + + Preconditions: + * in_dir is a real directory + * out_dir is a real, empty directory + """ + pyfile_gen = ( + pathlib.Path(os.path.join(root, f)) + for root, _, files in os.walk(in_dir) + for f in files if os.path.splitext(f)[1] == ".py" + ) + + for fpath in pyfile_gen: + with open(fpath, 'r') as f: + src = f.read() + + # Parse the code and insert method call fixes. + tree = cst.parse_module(src) + updated = tree.visit(transformer) + + # Create the path and directory structure for the new file. + updated_path = out_dir.joinpath(fpath.relative_to(in_dir)) + updated_path.parent.mkdir(parents=True, exist_ok=True) + + # Generate the updated source file at the corresponding path. + with open(updated_path, 'w') as f: + f.write(updated.code) + + +if __name__ == '__main__': + parser = argparse.ArgumentParser( + description="""Fix up source that uses the bigquery client library. + +The existing sources are NOT overwritten but are copied to output_dir with changes made. + +Note: This tool operates at a best-effort level at converting positional + parameters in client method calls to keyword based parameters. + Cases where it WILL FAIL include + A) * or ** expansion in a method call. + B) Calls via function or method alias (includes free function calls) + C) Indirect or dispatched calls (e.g. the method is looked up dynamically) + + These all constitute false negatives. The tool will also detect false + positives when an API method shares a name with another method. +""") + parser.add_argument( + '-d', + '--input-directory', + required=True, + dest='input_dir', + help='the input directory to walk for python files to fix up', + ) + parser.add_argument( + '-o', + '--output-directory', + required=True, + dest='output_dir', + help='the directory to output files fixed via un-flattening', + ) + args = parser.parse_args() + input_dir = pathlib.Path(args.input_dir) + output_dir = pathlib.Path(args.output_dir) + if not input_dir.is_dir(): + print( + f"input directory '{input_dir}' does not exist or is not a directory", + file=sys.stderr, + ) + sys.exit(-1) + + if not output_dir.is_dir(): + print( + f"output directory '{output_dir}' does not exist or is not a directory", + file=sys.stderr, + ) + sys.exit(-1) + + if os.listdir(output_dir): + print( + f"output directory '{output_dir}' is not empty", + file=sys.stderr, + ) + sys.exit(-1) + + fix_files(input_dir, output_dir) diff --git a/owl-bot-staging/v2/setup.py b/owl-bot-staging/v2/setup.py new file mode 100644 index 000000000..e26921308 --- /dev/null +++ b/owl-bot-staging/v2/setup.py @@ -0,0 +1,53 @@ +# -*- coding: utf-8 -*- +# Copyright 2020 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# +import io +import os +import setuptools # type: ignore + +version = '0.1.0' + +package_root = os.path.abspath(os.path.dirname(__file__)) + +readme_filename = os.path.join(package_root, 'README.rst') +with io.open(readme_filename, encoding='utf-8') as readme_file: + readme = readme_file.read() + +setuptools.setup( + name='google-cloud-bigquery', + version=version, + long_description=readme, + packages=setuptools.PEP420PackageFinder.find(), + namespace_packages=('google', 'google.cloud'), + platforms='Posix; MacOS X; Windows', + include_package_data=True, + install_requires=( + 'google-api-core[grpc] >= 1.27.0, < 2.0.0dev', + 'libcst >= 0.2.5', + 'proto-plus >= 1.15.0', + 'packaging >= 14.3', ), + python_requires='>=3.6', + classifiers=[ + 'Development Status :: 3 - Alpha', + 'Intended Audience :: Developers', + 'Operating System :: OS Independent', + 'Programming Language :: Python :: 3.6', + 'Programming Language :: Python :: 3.7', + 'Programming Language :: Python :: 3.8', + 'Topic :: Internet', + 'Topic :: Software Development :: Libraries :: Python Modules', + ], + zip_safe=False, +) diff --git a/owl-bot-staging/v2/tests/__init__.py b/owl-bot-staging/v2/tests/__init__.py new file mode 100644 index 000000000..b54a5fcc4 --- /dev/null +++ b/owl-bot-staging/v2/tests/__init__.py @@ -0,0 +1,16 @@ + +# -*- coding: utf-8 -*- +# Copyright 2020 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# diff --git a/owl-bot-staging/v2/tests/unit/__init__.py b/owl-bot-staging/v2/tests/unit/__init__.py new file mode 100644 index 000000000..b54a5fcc4 --- /dev/null +++ b/owl-bot-staging/v2/tests/unit/__init__.py @@ -0,0 +1,16 @@ + +# -*- coding: utf-8 -*- +# Copyright 2020 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# diff --git a/owl-bot-staging/v2/tests/unit/gapic/__init__.py b/owl-bot-staging/v2/tests/unit/gapic/__init__.py new file mode 100644 index 000000000..b54a5fcc4 --- /dev/null +++ b/owl-bot-staging/v2/tests/unit/gapic/__init__.py @@ -0,0 +1,16 @@ + +# -*- coding: utf-8 -*- +# Copyright 2020 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# diff --git a/owl-bot-staging/v2/tests/unit/gapic/bigquery_v2/__init__.py b/owl-bot-staging/v2/tests/unit/gapic/bigquery_v2/__init__.py new file mode 100644 index 000000000..b54a5fcc4 --- /dev/null +++ b/owl-bot-staging/v2/tests/unit/gapic/bigquery_v2/__init__.py @@ -0,0 +1,16 @@ + +# -*- coding: utf-8 -*- +# Copyright 2020 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# diff --git a/owl-bot-staging/v2/tests/unit/gapic/bigquery_v2/test_model_service.py b/owl-bot-staging/v2/tests/unit/gapic/bigquery_v2/test_model_service.py new file mode 100644 index 000000000..32ebcc9a4 --- /dev/null +++ b/owl-bot-staging/v2/tests/unit/gapic/bigquery_v2/test_model_service.py @@ -0,0 +1,1712 @@ +# -*- coding: utf-8 -*- +# Copyright 2020 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# +import os +import mock +import packaging.version + +import grpc +from grpc.experimental import aio +import math +import pytest +from proto.marshal.rules.dates import DurationRule, TimestampRule + + +from google.api_core import client_options +from google.api_core import exceptions as core_exceptions +from google.api_core import gapic_v1 +from google.api_core import grpc_helpers +from google.api_core import grpc_helpers_async +from google.auth import credentials as ga_credentials +from google.auth.exceptions import MutualTLSChannelError +from google.cloud.bigquery_v2.services.model_service import ModelServiceAsyncClient +from google.cloud.bigquery_v2.services.model_service import ModelServiceClient +from google.cloud.bigquery_v2.services.model_service import transports +from google.cloud.bigquery_v2.services.model_service.transports.base import _GOOGLE_AUTH_VERSION +from google.cloud.bigquery_v2.types import encryption_config +from google.cloud.bigquery_v2.types import model +from google.cloud.bigquery_v2.types import model as gcb_model +from google.cloud.bigquery_v2.types import model_reference +from google.cloud.bigquery_v2.types import standard_sql +from google.cloud.bigquery_v2.types import table_reference +from google.oauth2 import service_account +from google.protobuf import timestamp_pb2 # type: ignore +from google.protobuf import wrappers_pb2 # type: ignore +import google.auth + + +# TODO(busunkim): Once google-auth >= 1.25.0 is required transitively +# through google-api-core: +# - Delete the auth "less than" test cases +# - Delete these pytest markers (Make the "greater than or equal to" tests the default). +requires_google_auth_lt_1_25_0 = pytest.mark.skipif( + packaging.version.parse(_GOOGLE_AUTH_VERSION) >= packaging.version.parse("1.25.0"), + reason="This test requires google-auth < 1.25.0", +) +requires_google_auth_gte_1_25_0 = pytest.mark.skipif( + packaging.version.parse(_GOOGLE_AUTH_VERSION) < packaging.version.parse("1.25.0"), + reason="This test requires google-auth >= 1.25.0", +) + +def client_cert_source_callback(): + return b"cert bytes", b"key bytes" + + +# If default endpoint is localhost, then default mtls endpoint will be the same. +# This method modifies the default endpoint so the client can produce a different +# mtls endpoint for endpoint testing purposes. +def modify_default_endpoint(client): + return "foo.googleapis.com" if ("localhost" in client.DEFAULT_ENDPOINT) else client.DEFAULT_ENDPOINT + + +def test__get_default_mtls_endpoint(): + api_endpoint = "example.googleapis.com" + api_mtls_endpoint = "example.mtls.googleapis.com" + sandbox_endpoint = "example.sandbox.googleapis.com" + sandbox_mtls_endpoint = "example.mtls.sandbox.googleapis.com" + non_googleapi = "api.example.com" + + assert ModelServiceClient._get_default_mtls_endpoint(None) is None + assert ModelServiceClient._get_default_mtls_endpoint(api_endpoint) == api_mtls_endpoint + assert ModelServiceClient._get_default_mtls_endpoint(api_mtls_endpoint) == api_mtls_endpoint + assert ModelServiceClient._get_default_mtls_endpoint(sandbox_endpoint) == sandbox_mtls_endpoint + assert ModelServiceClient._get_default_mtls_endpoint(sandbox_mtls_endpoint) == sandbox_mtls_endpoint + assert ModelServiceClient._get_default_mtls_endpoint(non_googleapi) == non_googleapi + + +@pytest.mark.parametrize("client_class", [ + ModelServiceClient, + ModelServiceAsyncClient, +]) +def test_model_service_client_from_service_account_info(client_class): + creds = ga_credentials.AnonymousCredentials() + with mock.patch.object(service_account.Credentials, 'from_service_account_info') as factory: + factory.return_value = creds + info = {"valid": True} + client = client_class.from_service_account_info(info) + assert client.transport._credentials == creds + assert isinstance(client, client_class) + + assert client.transport._host == 'bigquery.googleapis.com:443' + + +@pytest.mark.parametrize("client_class", [ + ModelServiceClient, + ModelServiceAsyncClient, +]) +def test_model_service_client_service_account_always_use_jwt(client_class): + with mock.patch.object(service_account.Credentials, 'with_always_use_jwt_access', create=True) as use_jwt: + creds = service_account.Credentials(None, None, None) + client = client_class(credentials=creds) + use_jwt.assert_not_called() + + +@pytest.mark.parametrize("transport_class,transport_name", [ + (transports.ModelServiceGrpcTransport, "grpc"), + (transports.ModelServiceGrpcAsyncIOTransport, "grpc_asyncio"), +]) +def test_model_service_client_service_account_always_use_jwt_true(transport_class, transport_name): + with mock.patch.object(service_account.Credentials, 'with_always_use_jwt_access', create=True) as use_jwt: + creds = service_account.Credentials(None, None, None) + transport = transport_class(credentials=creds, always_use_jwt_access=True) + use_jwt.assert_called_once_with(True) + + +@pytest.mark.parametrize("client_class", [ + ModelServiceClient, + ModelServiceAsyncClient, +]) +def test_model_service_client_from_service_account_file(client_class): + creds = ga_credentials.AnonymousCredentials() + with mock.patch.object(service_account.Credentials, 'from_service_account_file') as factory: + factory.return_value = creds + client = client_class.from_service_account_file("dummy/file/path.json") + assert client.transport._credentials == creds + assert isinstance(client, client_class) + + client = client_class.from_service_account_json("dummy/file/path.json") + assert client.transport._credentials == creds + assert isinstance(client, client_class) + + assert client.transport._host == 'bigquery.googleapis.com:443' + + +def test_model_service_client_get_transport_class(): + transport = ModelServiceClient.get_transport_class() + available_transports = [ + transports.ModelServiceGrpcTransport, + ] + assert transport in available_transports + + transport = ModelServiceClient.get_transport_class("grpc") + assert transport == transports.ModelServiceGrpcTransport + + +@pytest.mark.parametrize("client_class,transport_class,transport_name", [ + (ModelServiceClient, transports.ModelServiceGrpcTransport, "grpc"), + (ModelServiceAsyncClient, transports.ModelServiceGrpcAsyncIOTransport, "grpc_asyncio"), +]) +@mock.patch.object(ModelServiceClient, "DEFAULT_ENDPOINT", modify_default_endpoint(ModelServiceClient)) +@mock.patch.object(ModelServiceAsyncClient, "DEFAULT_ENDPOINT", modify_default_endpoint(ModelServiceAsyncClient)) +def test_model_service_client_client_options(client_class, transport_class, transport_name): + # Check that if channel is provided we won't create a new one. + with mock.patch.object(ModelServiceClient, 'get_transport_class') as gtc: + transport = transport_class( + credentials=ga_credentials.AnonymousCredentials() + ) + client = client_class(transport=transport) + gtc.assert_not_called() + + # Check that if channel is provided via str we will create a new one. + with mock.patch.object(ModelServiceClient, 'get_transport_class') as gtc: + client = client_class(transport=transport_name) + gtc.assert_called() + + # Check the case api_endpoint is provided. + options = client_options.ClientOptions(api_endpoint="squid.clam.whelk") + with mock.patch.object(transport_class, '__init__') as patched: + patched.return_value = None + client = client_class(client_options=options) + patched.assert_called_once_with( + credentials=None, + credentials_file=None, + host="squid.clam.whelk", + scopes=None, + client_cert_source_for_mtls=None, + quota_project_id=None, + client_info=transports.base.DEFAULT_CLIENT_INFO, + ) + + # Check the case api_endpoint is not provided and GOOGLE_API_USE_MTLS_ENDPOINT is + # "never". + with mock.patch.dict(os.environ, {"GOOGLE_API_USE_MTLS_ENDPOINT": "never"}): + with mock.patch.object(transport_class, '__init__') as patched: + patched.return_value = None + client = client_class() + patched.assert_called_once_with( + credentials=None, + credentials_file=None, + host=client.DEFAULT_ENDPOINT, + scopes=None, + client_cert_source_for_mtls=None, + quota_project_id=None, + client_info=transports.base.DEFAULT_CLIENT_INFO, + ) + + # Check the case api_endpoint is not provided and GOOGLE_API_USE_MTLS_ENDPOINT is + # "always". + with mock.patch.dict(os.environ, {"GOOGLE_API_USE_MTLS_ENDPOINT": "always"}): + with mock.patch.object(transport_class, '__init__') as patched: + patched.return_value = None + client = client_class() + patched.assert_called_once_with( + credentials=None, + credentials_file=None, + host=client.DEFAULT_MTLS_ENDPOINT, + scopes=None, + client_cert_source_for_mtls=None, + quota_project_id=None, + client_info=transports.base.DEFAULT_CLIENT_INFO, + ) + + # Check the case api_endpoint is not provided and GOOGLE_API_USE_MTLS_ENDPOINT has + # unsupported value. + with mock.patch.dict(os.environ, {"GOOGLE_API_USE_MTLS_ENDPOINT": "Unsupported"}): + with pytest.raises(MutualTLSChannelError): + client = client_class() + + # Check the case GOOGLE_API_USE_CLIENT_CERTIFICATE has unsupported value. + with mock.patch.dict(os.environ, {"GOOGLE_API_USE_CLIENT_CERTIFICATE": "Unsupported"}): + with pytest.raises(ValueError): + client = client_class() + + # Check the case quota_project_id is provided + options = client_options.ClientOptions(quota_project_id="octopus") + with mock.patch.object(transport_class, '__init__') as patched: + patched.return_value = None + client = client_class(client_options=options) + patched.assert_called_once_with( + credentials=None, + credentials_file=None, + host=client.DEFAULT_ENDPOINT, + scopes=None, + client_cert_source_for_mtls=None, + quota_project_id="octopus", + client_info=transports.base.DEFAULT_CLIENT_INFO, + ) + +@pytest.mark.parametrize("client_class,transport_class,transport_name,use_client_cert_env", [ + (ModelServiceClient, transports.ModelServiceGrpcTransport, "grpc", "true"), + (ModelServiceAsyncClient, transports.ModelServiceGrpcAsyncIOTransport, "grpc_asyncio", "true"), + (ModelServiceClient, transports.ModelServiceGrpcTransport, "grpc", "false"), + (ModelServiceAsyncClient, transports.ModelServiceGrpcAsyncIOTransport, "grpc_asyncio", "false"), +]) +@mock.patch.object(ModelServiceClient, "DEFAULT_ENDPOINT", modify_default_endpoint(ModelServiceClient)) +@mock.patch.object(ModelServiceAsyncClient, "DEFAULT_ENDPOINT", modify_default_endpoint(ModelServiceAsyncClient)) +@mock.patch.dict(os.environ, {"GOOGLE_API_USE_MTLS_ENDPOINT": "auto"}) +def test_model_service_client_mtls_env_auto(client_class, transport_class, transport_name, use_client_cert_env): + # This tests the endpoint autoswitch behavior. Endpoint is autoswitched to the default + # mtls endpoint, if GOOGLE_API_USE_CLIENT_CERTIFICATE is "true" and client cert exists. + + # Check the case client_cert_source is provided. Whether client cert is used depends on + # GOOGLE_API_USE_CLIENT_CERTIFICATE value. + with mock.patch.dict(os.environ, {"GOOGLE_API_USE_CLIENT_CERTIFICATE": use_client_cert_env}): + options = client_options.ClientOptions(client_cert_source=client_cert_source_callback) + with mock.patch.object(transport_class, '__init__') as patched: + patched.return_value = None + client = client_class(client_options=options) + + if use_client_cert_env == "false": + expected_client_cert_source = None + expected_host = client.DEFAULT_ENDPOINT + else: + expected_client_cert_source = client_cert_source_callback + expected_host = client.DEFAULT_MTLS_ENDPOINT + + patched.assert_called_once_with( + credentials=None, + credentials_file=None, + host=expected_host, + scopes=None, + client_cert_source_for_mtls=expected_client_cert_source, + quota_project_id=None, + client_info=transports.base.DEFAULT_CLIENT_INFO, + ) + + # Check the case ADC client cert is provided. Whether client cert is used depends on + # GOOGLE_API_USE_CLIENT_CERTIFICATE value. + with mock.patch.dict(os.environ, {"GOOGLE_API_USE_CLIENT_CERTIFICATE": use_client_cert_env}): + with mock.patch.object(transport_class, '__init__') as patched: + with mock.patch('google.auth.transport.mtls.has_default_client_cert_source', return_value=True): + with mock.patch('google.auth.transport.mtls.default_client_cert_source', return_value=client_cert_source_callback): + if use_client_cert_env == "false": + expected_host = client.DEFAULT_ENDPOINT + expected_client_cert_source = None + else: + expected_host = client.DEFAULT_MTLS_ENDPOINT + expected_client_cert_source = client_cert_source_callback + + patched.return_value = None + client = client_class() + patched.assert_called_once_with( + credentials=None, + credentials_file=None, + host=expected_host, + scopes=None, + client_cert_source_for_mtls=expected_client_cert_source, + quota_project_id=None, + client_info=transports.base.DEFAULT_CLIENT_INFO, + ) + + # Check the case client_cert_source and ADC client cert are not provided. + with mock.patch.dict(os.environ, {"GOOGLE_API_USE_CLIENT_CERTIFICATE": use_client_cert_env}): + with mock.patch.object(transport_class, '__init__') as patched: + with mock.patch("google.auth.transport.mtls.has_default_client_cert_source", return_value=False): + patched.return_value = None + client = client_class() + patched.assert_called_once_with( + credentials=None, + credentials_file=None, + host=client.DEFAULT_ENDPOINT, + scopes=None, + client_cert_source_for_mtls=None, + quota_project_id=None, + client_info=transports.base.DEFAULT_CLIENT_INFO, + ) + + +@pytest.mark.parametrize("client_class,transport_class,transport_name", [ + (ModelServiceClient, transports.ModelServiceGrpcTransport, "grpc"), + (ModelServiceAsyncClient, transports.ModelServiceGrpcAsyncIOTransport, "grpc_asyncio"), +]) +def test_model_service_client_client_options_scopes(client_class, transport_class, transport_name): + # Check the case scopes are provided. + options = client_options.ClientOptions( + scopes=["1", "2"], + ) + with mock.patch.object(transport_class, '__init__') as patched: + patched.return_value = None + client = client_class(client_options=options) + patched.assert_called_once_with( + credentials=None, + credentials_file=None, + host=client.DEFAULT_ENDPOINT, + scopes=["1", "2"], + client_cert_source_for_mtls=None, + quota_project_id=None, + client_info=transports.base.DEFAULT_CLIENT_INFO, + ) + +@pytest.mark.parametrize("client_class,transport_class,transport_name", [ + (ModelServiceClient, transports.ModelServiceGrpcTransport, "grpc"), + (ModelServiceAsyncClient, transports.ModelServiceGrpcAsyncIOTransport, "grpc_asyncio"), +]) +def test_model_service_client_client_options_credentials_file(client_class, transport_class, transport_name): + # Check the case credentials file is provided. + options = client_options.ClientOptions( + credentials_file="credentials.json" + ) + with mock.patch.object(transport_class, '__init__') as patched: + patched.return_value = None + client = client_class(client_options=options) + patched.assert_called_once_with( + credentials=None, + credentials_file="credentials.json", + host=client.DEFAULT_ENDPOINT, + scopes=None, + client_cert_source_for_mtls=None, + quota_project_id=None, + client_info=transports.base.DEFAULT_CLIENT_INFO, + ) + + +def test_model_service_client_client_options_from_dict(): + with mock.patch('google.cloud.bigquery_v2.services.model_service.transports.ModelServiceGrpcTransport.__init__') as grpc_transport: + grpc_transport.return_value = None + client = ModelServiceClient( + client_options={'api_endpoint': 'squid.clam.whelk'} + ) + grpc_transport.assert_called_once_with( + credentials=None, + credentials_file=None, + host="squid.clam.whelk", + scopes=None, + client_cert_source_for_mtls=None, + quota_project_id=None, + client_info=transports.base.DEFAULT_CLIENT_INFO, + ) + + +def test_get_model(transport: str = 'grpc', request_type=model.GetModelRequest): + client = ModelServiceClient( + credentials=ga_credentials.AnonymousCredentials(), + transport=transport, + ) + + # Everything is optional in proto3 as far as the runtime is concerned, + # and we are mocking out the actual API, so just send an empty request. + request = request_type() + + # Mock the actual call within the gRPC stub, and fake the request. + with mock.patch.object( + type(client.transport.get_model), + '__call__') as call: + # Designate an appropriate return value for the call. + call.return_value = model.Model( + etag='etag_value', + creation_time=1379, + last_modified_time=1890, + description='description_value', + friendly_name='friendly_name_value', + expiration_time=1617, + location='location_value', + model_type=model.Model.ModelType.LINEAR_REGRESSION, + ) + response = client.get_model(request) + + # Establish that the underlying gRPC stub method was called. + assert len(call.mock_calls) == 1 + _, args, _ = call.mock_calls[0] + assert args[0] == model.GetModelRequest() + + # Establish that the response is the type that we expect. + assert isinstance(response, model.Model) + assert response.etag == 'etag_value' + assert response.creation_time == 1379 + assert response.last_modified_time == 1890 + assert response.description == 'description_value' + assert response.friendly_name == 'friendly_name_value' + assert response.expiration_time == 1617 + assert response.location == 'location_value' + assert response.model_type == model.Model.ModelType.LINEAR_REGRESSION + + +def test_get_model_from_dict(): + test_get_model(request_type=dict) + + +def test_get_model_empty_call(): + # This test is a coverage failsafe to make sure that totally empty calls, + # i.e. request == None and no flattened fields passed, work. + client = ModelServiceClient( + credentials=ga_credentials.AnonymousCredentials(), + transport='grpc', + ) + + # Mock the actual call within the gRPC stub, and fake the request. + with mock.patch.object( + type(client.transport.get_model), + '__call__') as call: + client.get_model() + call.assert_called() + _, args, _ = call.mock_calls[0] + assert args[0] == model.GetModelRequest() + + +@pytest.mark.asyncio +async def test_get_model_async(transport: str = 'grpc_asyncio', request_type=model.GetModelRequest): + client = ModelServiceAsyncClient( + credentials=ga_credentials.AnonymousCredentials(), + transport=transport, + ) + + # Everything is optional in proto3 as far as the runtime is concerned, + # and we are mocking out the actual API, so just send an empty request. + request = request_type() + + # Mock the actual call within the gRPC stub, and fake the request. + with mock.patch.object( + type(client.transport.get_model), + '__call__') as call: + # Designate an appropriate return value for the call. + call.return_value =grpc_helpers_async.FakeUnaryUnaryCall(model.Model( + etag='etag_value', + creation_time=1379, + last_modified_time=1890, + description='description_value', + friendly_name='friendly_name_value', + expiration_time=1617, + location='location_value', + model_type=model.Model.ModelType.LINEAR_REGRESSION, + )) + response = await client.get_model(request) + + # Establish that the underlying gRPC stub method was called. + assert len(call.mock_calls) + _, args, _ = call.mock_calls[0] + assert args[0] == model.GetModelRequest() + + # Establish that the response is the type that we expect. + assert isinstance(response, model.Model) + assert response.etag == 'etag_value' + assert response.creation_time == 1379 + assert response.last_modified_time == 1890 + assert response.description == 'description_value' + assert response.friendly_name == 'friendly_name_value' + assert response.expiration_time == 1617 + assert response.location == 'location_value' + assert response.model_type == model.Model.ModelType.LINEAR_REGRESSION + + +@pytest.mark.asyncio +async def test_get_model_async_from_dict(): + await test_get_model_async(request_type=dict) + + +def test_get_model_flattened(): + client = ModelServiceClient( + credentials=ga_credentials.AnonymousCredentials(), + ) + + # Mock the actual call within the gRPC stub, and fake the request. + with mock.patch.object( + type(client.transport.get_model), + '__call__') as call: + # Designate an appropriate return value for the call. + call.return_value = model.Model() + # Call the method with a truthy value for each flattened field, + # using the keyword arguments to the method. + client.get_model( + project_id='project_id_value', + dataset_id='dataset_id_value', + model_id='model_id_value', + ) + + # Establish that the underlying call was made with the expected + # request object values. + assert len(call.mock_calls) == 1 + _, args, _ = call.mock_calls[0] + assert args[0].project_id == 'project_id_value' + assert args[0].dataset_id == 'dataset_id_value' + assert args[0].model_id == 'model_id_value' + + +def test_get_model_flattened_error(): + client = ModelServiceClient( + credentials=ga_credentials.AnonymousCredentials(), + ) + + # Attempting to call a method with both a request object and flattened + # fields is an error. + with pytest.raises(ValueError): + client.get_model( + model.GetModelRequest(), + project_id='project_id_value', + dataset_id='dataset_id_value', + model_id='model_id_value', + ) + + +@pytest.mark.asyncio +async def test_get_model_flattened_async(): + client = ModelServiceAsyncClient( + credentials=ga_credentials.AnonymousCredentials(), + ) + + # Mock the actual call within the gRPC stub, and fake the request. + with mock.patch.object( + type(client.transport.get_model), + '__call__') as call: + # Designate an appropriate return value for the call. + call.return_value = model.Model() + + call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(model.Model()) + # Call the method with a truthy value for each flattened field, + # using the keyword arguments to the method. + response = await client.get_model( + project_id='project_id_value', + dataset_id='dataset_id_value', + model_id='model_id_value', + ) + + # Establish that the underlying call was made with the expected + # request object values. + assert len(call.mock_calls) + _, args, _ = call.mock_calls[0] + assert args[0].project_id == 'project_id_value' + assert args[0].dataset_id == 'dataset_id_value' + assert args[0].model_id == 'model_id_value' + + +@pytest.mark.asyncio +async def test_get_model_flattened_error_async(): + client = ModelServiceAsyncClient( + credentials=ga_credentials.AnonymousCredentials(), + ) + + # Attempting to call a method with both a request object and flattened + # fields is an error. + with pytest.raises(ValueError): + await client.get_model( + model.GetModelRequest(), + project_id='project_id_value', + dataset_id='dataset_id_value', + model_id='model_id_value', + ) + + +def test_list_models(transport: str = 'grpc', request_type=model.ListModelsRequest): + client = ModelServiceClient( + credentials=ga_credentials.AnonymousCredentials(), + transport=transport, + ) + + # Everything is optional in proto3 as far as the runtime is concerned, + # and we are mocking out the actual API, so just send an empty request. + request = request_type() + + # Mock the actual call within the gRPC stub, and fake the request. + with mock.patch.object( + type(client.transport.list_models), + '__call__') as call: + # Designate an appropriate return value for the call. + call.return_value = model.ListModelsResponse( + next_page_token='next_page_token_value', + ) + response = client.list_models(request) + + # Establish that the underlying gRPC stub method was called. + assert len(call.mock_calls) == 1 + _, args, _ = call.mock_calls[0] + assert args[0] == model.ListModelsRequest() + + # Establish that the response is the type that we expect. + assert response.raw_page is response + assert isinstance(response, model.ListModelsResponse) + assert response.next_page_token == 'next_page_token_value' + + +def test_list_models_from_dict(): + test_list_models(request_type=dict) + + +def test_list_models_empty_call(): + # This test is a coverage failsafe to make sure that totally empty calls, + # i.e. request == None and no flattened fields passed, work. + client = ModelServiceClient( + credentials=ga_credentials.AnonymousCredentials(), + transport='grpc', + ) + + # Mock the actual call within the gRPC stub, and fake the request. + with mock.patch.object( + type(client.transport.list_models), + '__call__') as call: + client.list_models() + call.assert_called() + _, args, _ = call.mock_calls[0] + assert args[0] == model.ListModelsRequest() + + +@pytest.mark.asyncio +async def test_list_models_async(transport: str = 'grpc_asyncio', request_type=model.ListModelsRequest): + client = ModelServiceAsyncClient( + credentials=ga_credentials.AnonymousCredentials(), + transport=transport, + ) + + # Everything is optional in proto3 as far as the runtime is concerned, + # and we are mocking out the actual API, so just send an empty request. + request = request_type() + + # Mock the actual call within the gRPC stub, and fake the request. + with mock.patch.object( + type(client.transport.list_models), + '__call__') as call: + # Designate an appropriate return value for the call. + call.return_value =grpc_helpers_async.FakeUnaryUnaryCall(model.ListModelsResponse( + next_page_token='next_page_token_value', + )) + response = await client.list_models(request) + + # Establish that the underlying gRPC stub method was called. + assert len(call.mock_calls) + _, args, _ = call.mock_calls[0] + assert args[0] == model.ListModelsRequest() + + # Establish that the response is the type that we expect. + assert isinstance(response, model.ListModelsResponse) + assert response.next_page_token == 'next_page_token_value' + + +@pytest.mark.asyncio +async def test_list_models_async_from_dict(): + await test_list_models_async(request_type=dict) + + +def test_list_models_flattened(): + client = ModelServiceClient( + credentials=ga_credentials.AnonymousCredentials(), + ) + + # Mock the actual call within the gRPC stub, and fake the request. + with mock.patch.object( + type(client.transport.list_models), + '__call__') as call: + # Designate an appropriate return value for the call. + call.return_value = model.ListModelsResponse() + # Call the method with a truthy value for each flattened field, + # using the keyword arguments to the method. + client.list_models( + project_id='project_id_value', + dataset_id='dataset_id_value', + max_results=wrappers_pb2.UInt32Value(value=541), + ) + + # Establish that the underlying call was made with the expected + # request object values. + assert len(call.mock_calls) == 1 + _, args, _ = call.mock_calls[0] + assert args[0].project_id == 'project_id_value' + assert args[0].dataset_id == 'dataset_id_value' + assert args[0].max_results == wrappers_pb2.UInt32Value(value=541) + + +def test_list_models_flattened_error(): + client = ModelServiceClient( + credentials=ga_credentials.AnonymousCredentials(), + ) + + # Attempting to call a method with both a request object and flattened + # fields is an error. + with pytest.raises(ValueError): + client.list_models( + model.ListModelsRequest(), + project_id='project_id_value', + dataset_id='dataset_id_value', + max_results=wrappers_pb2.UInt32Value(value=541), + ) + + +@pytest.mark.asyncio +async def test_list_models_flattened_async(): + client = ModelServiceAsyncClient( + credentials=ga_credentials.AnonymousCredentials(), + ) + + # Mock the actual call within the gRPC stub, and fake the request. + with mock.patch.object( + type(client.transport.list_models), + '__call__') as call: + # Designate an appropriate return value for the call. + call.return_value = model.ListModelsResponse() + + call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(model.ListModelsResponse()) + # Call the method with a truthy value for each flattened field, + # using the keyword arguments to the method. + response = await client.list_models( + project_id='project_id_value', + dataset_id='dataset_id_value', + max_results=wrappers_pb2.UInt32Value(value=541), + ) + + # Establish that the underlying call was made with the expected + # request object values. + assert len(call.mock_calls) + _, args, _ = call.mock_calls[0] + assert args[0].project_id == 'project_id_value' + assert args[0].dataset_id == 'dataset_id_value' + assert args[0].max_results == wrappers_pb2.UInt32Value(value=541) + + +@pytest.mark.asyncio +async def test_list_models_flattened_error_async(): + client = ModelServiceAsyncClient( + credentials=ga_credentials.AnonymousCredentials(), + ) + + # Attempting to call a method with both a request object and flattened + # fields is an error. + with pytest.raises(ValueError): + await client.list_models( + model.ListModelsRequest(), + project_id='project_id_value', + dataset_id='dataset_id_value', + max_results=wrappers_pb2.UInt32Value(value=541), + ) + + +def test_patch_model(transport: str = 'grpc', request_type=gcb_model.PatchModelRequest): + client = ModelServiceClient( + credentials=ga_credentials.AnonymousCredentials(), + transport=transport, + ) + + # Everything is optional in proto3 as far as the runtime is concerned, + # and we are mocking out the actual API, so just send an empty request. + request = request_type() + + # Mock the actual call within the gRPC stub, and fake the request. + with mock.patch.object( + type(client.transport.patch_model), + '__call__') as call: + # Designate an appropriate return value for the call. + call.return_value = gcb_model.Model( + etag='etag_value', + creation_time=1379, + last_modified_time=1890, + description='description_value', + friendly_name='friendly_name_value', + expiration_time=1617, + location='location_value', + model_type=gcb_model.Model.ModelType.LINEAR_REGRESSION, + ) + response = client.patch_model(request) + + # Establish that the underlying gRPC stub method was called. + assert len(call.mock_calls) == 1 + _, args, _ = call.mock_calls[0] + assert args[0] == gcb_model.PatchModelRequest() + + # Establish that the response is the type that we expect. + assert isinstance(response, gcb_model.Model) + assert response.etag == 'etag_value' + assert response.creation_time == 1379 + assert response.last_modified_time == 1890 + assert response.description == 'description_value' + assert response.friendly_name == 'friendly_name_value' + assert response.expiration_time == 1617 + assert response.location == 'location_value' + assert response.model_type == gcb_model.Model.ModelType.LINEAR_REGRESSION + + +def test_patch_model_from_dict(): + test_patch_model(request_type=dict) + + +def test_patch_model_empty_call(): + # This test is a coverage failsafe to make sure that totally empty calls, + # i.e. request == None and no flattened fields passed, work. + client = ModelServiceClient( + credentials=ga_credentials.AnonymousCredentials(), + transport='grpc', + ) + + # Mock the actual call within the gRPC stub, and fake the request. + with mock.patch.object( + type(client.transport.patch_model), + '__call__') as call: + client.patch_model() + call.assert_called() + _, args, _ = call.mock_calls[0] + assert args[0] == gcb_model.PatchModelRequest() + + +@pytest.mark.asyncio +async def test_patch_model_async(transport: str = 'grpc_asyncio', request_type=gcb_model.PatchModelRequest): + client = ModelServiceAsyncClient( + credentials=ga_credentials.AnonymousCredentials(), + transport=transport, + ) + + # Everything is optional in proto3 as far as the runtime is concerned, + # and we are mocking out the actual API, so just send an empty request. + request = request_type() + + # Mock the actual call within the gRPC stub, and fake the request. + with mock.patch.object( + type(client.transport.patch_model), + '__call__') as call: + # Designate an appropriate return value for the call. + call.return_value =grpc_helpers_async.FakeUnaryUnaryCall(gcb_model.Model( + etag='etag_value', + creation_time=1379, + last_modified_time=1890, + description='description_value', + friendly_name='friendly_name_value', + expiration_time=1617, + location='location_value', + model_type=gcb_model.Model.ModelType.LINEAR_REGRESSION, + )) + response = await client.patch_model(request) + + # Establish that the underlying gRPC stub method was called. + assert len(call.mock_calls) + _, args, _ = call.mock_calls[0] + assert args[0] == gcb_model.PatchModelRequest() + + # Establish that the response is the type that we expect. + assert isinstance(response, gcb_model.Model) + assert response.etag == 'etag_value' + assert response.creation_time == 1379 + assert response.last_modified_time == 1890 + assert response.description == 'description_value' + assert response.friendly_name == 'friendly_name_value' + assert response.expiration_time == 1617 + assert response.location == 'location_value' + assert response.model_type == gcb_model.Model.ModelType.LINEAR_REGRESSION + + +@pytest.mark.asyncio +async def test_patch_model_async_from_dict(): + await test_patch_model_async(request_type=dict) + + +def test_patch_model_flattened(): + client = ModelServiceClient( + credentials=ga_credentials.AnonymousCredentials(), + ) + + # Mock the actual call within the gRPC stub, and fake the request. + with mock.patch.object( + type(client.transport.patch_model), + '__call__') as call: + # Designate an appropriate return value for the call. + call.return_value = gcb_model.Model() + # Call the method with a truthy value for each flattened field, + # using the keyword arguments to the method. + client.patch_model( + project_id='project_id_value', + dataset_id='dataset_id_value', + model_id='model_id_value', + model=gcb_model.Model(etag='etag_value'), + ) + + # Establish that the underlying call was made with the expected + # request object values. + assert len(call.mock_calls) == 1 + _, args, _ = call.mock_calls[0] + assert args[0].project_id == 'project_id_value' + assert args[0].dataset_id == 'dataset_id_value' + assert args[0].model_id == 'model_id_value' + assert args[0].model == gcb_model.Model(etag='etag_value') + + +def test_patch_model_flattened_error(): + client = ModelServiceClient( + credentials=ga_credentials.AnonymousCredentials(), + ) + + # Attempting to call a method with both a request object and flattened + # fields is an error. + with pytest.raises(ValueError): + client.patch_model( + gcb_model.PatchModelRequest(), + project_id='project_id_value', + dataset_id='dataset_id_value', + model_id='model_id_value', + model=gcb_model.Model(etag='etag_value'), + ) + + +@pytest.mark.asyncio +async def test_patch_model_flattened_async(): + client = ModelServiceAsyncClient( + credentials=ga_credentials.AnonymousCredentials(), + ) + + # Mock the actual call within the gRPC stub, and fake the request. + with mock.patch.object( + type(client.transport.patch_model), + '__call__') as call: + # Designate an appropriate return value for the call. + call.return_value = gcb_model.Model() + + call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(gcb_model.Model()) + # Call the method with a truthy value for each flattened field, + # using the keyword arguments to the method. + response = await client.patch_model( + project_id='project_id_value', + dataset_id='dataset_id_value', + model_id='model_id_value', + model=gcb_model.Model(etag='etag_value'), + ) + + # Establish that the underlying call was made with the expected + # request object values. + assert len(call.mock_calls) + _, args, _ = call.mock_calls[0] + assert args[0].project_id == 'project_id_value' + assert args[0].dataset_id == 'dataset_id_value' + assert args[0].model_id == 'model_id_value' + assert args[0].model == gcb_model.Model(etag='etag_value') + + +@pytest.mark.asyncio +async def test_patch_model_flattened_error_async(): + client = ModelServiceAsyncClient( + credentials=ga_credentials.AnonymousCredentials(), + ) + + # Attempting to call a method with both a request object and flattened + # fields is an error. + with pytest.raises(ValueError): + await client.patch_model( + gcb_model.PatchModelRequest(), + project_id='project_id_value', + dataset_id='dataset_id_value', + model_id='model_id_value', + model=gcb_model.Model(etag='etag_value'), + ) + + +def test_delete_model(transport: str = 'grpc', request_type=model.DeleteModelRequest): + client = ModelServiceClient( + credentials=ga_credentials.AnonymousCredentials(), + transport=transport, + ) + + # Everything is optional in proto3 as far as the runtime is concerned, + # and we are mocking out the actual API, so just send an empty request. + request = request_type() + + # Mock the actual call within the gRPC stub, and fake the request. + with mock.patch.object( + type(client.transport.delete_model), + '__call__') as call: + # Designate an appropriate return value for the call. + call.return_value = None + response = client.delete_model(request) + + # Establish that the underlying gRPC stub method was called. + assert len(call.mock_calls) == 1 + _, args, _ = call.mock_calls[0] + assert args[0] == model.DeleteModelRequest() + + # Establish that the response is the type that we expect. + assert response is None + + +def test_delete_model_from_dict(): + test_delete_model(request_type=dict) + + +def test_delete_model_empty_call(): + # This test is a coverage failsafe to make sure that totally empty calls, + # i.e. request == None and no flattened fields passed, work. + client = ModelServiceClient( + credentials=ga_credentials.AnonymousCredentials(), + transport='grpc', + ) + + # Mock the actual call within the gRPC stub, and fake the request. + with mock.patch.object( + type(client.transport.delete_model), + '__call__') as call: + client.delete_model() + call.assert_called() + _, args, _ = call.mock_calls[0] + assert args[0] == model.DeleteModelRequest() + + +@pytest.mark.asyncio +async def test_delete_model_async(transport: str = 'grpc_asyncio', request_type=model.DeleteModelRequest): + client = ModelServiceAsyncClient( + credentials=ga_credentials.AnonymousCredentials(), + transport=transport, + ) + + # Everything is optional in proto3 as far as the runtime is concerned, + # and we are mocking out the actual API, so just send an empty request. + request = request_type() + + # Mock the actual call within the gRPC stub, and fake the request. + with mock.patch.object( + type(client.transport.delete_model), + '__call__') as call: + # Designate an appropriate return value for the call. + call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(None) + response = await client.delete_model(request) + + # Establish that the underlying gRPC stub method was called. + assert len(call.mock_calls) + _, args, _ = call.mock_calls[0] + assert args[0] == model.DeleteModelRequest() + + # Establish that the response is the type that we expect. + assert response is None + + +@pytest.mark.asyncio +async def test_delete_model_async_from_dict(): + await test_delete_model_async(request_type=dict) + + +def test_delete_model_flattened(): + client = ModelServiceClient( + credentials=ga_credentials.AnonymousCredentials(), + ) + + # Mock the actual call within the gRPC stub, and fake the request. + with mock.patch.object( + type(client.transport.delete_model), + '__call__') as call: + # Designate an appropriate return value for the call. + call.return_value = None + # Call the method with a truthy value for each flattened field, + # using the keyword arguments to the method. + client.delete_model( + project_id='project_id_value', + dataset_id='dataset_id_value', + model_id='model_id_value', + ) + + # Establish that the underlying call was made with the expected + # request object values. + assert len(call.mock_calls) == 1 + _, args, _ = call.mock_calls[0] + assert args[0].project_id == 'project_id_value' + assert args[0].dataset_id == 'dataset_id_value' + assert args[0].model_id == 'model_id_value' + + +def test_delete_model_flattened_error(): + client = ModelServiceClient( + credentials=ga_credentials.AnonymousCredentials(), + ) + + # Attempting to call a method with both a request object and flattened + # fields is an error. + with pytest.raises(ValueError): + client.delete_model( + model.DeleteModelRequest(), + project_id='project_id_value', + dataset_id='dataset_id_value', + model_id='model_id_value', + ) + + +@pytest.mark.asyncio +async def test_delete_model_flattened_async(): + client = ModelServiceAsyncClient( + credentials=ga_credentials.AnonymousCredentials(), + ) + + # Mock the actual call within the gRPC stub, and fake the request. + with mock.patch.object( + type(client.transport.delete_model), + '__call__') as call: + # Designate an appropriate return value for the call. + call.return_value = None + + call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(None) + # Call the method with a truthy value for each flattened field, + # using the keyword arguments to the method. + response = await client.delete_model( + project_id='project_id_value', + dataset_id='dataset_id_value', + model_id='model_id_value', + ) + + # Establish that the underlying call was made with the expected + # request object values. + assert len(call.mock_calls) + _, args, _ = call.mock_calls[0] + assert args[0].project_id == 'project_id_value' + assert args[0].dataset_id == 'dataset_id_value' + assert args[0].model_id == 'model_id_value' + + +@pytest.mark.asyncio +async def test_delete_model_flattened_error_async(): + client = ModelServiceAsyncClient( + credentials=ga_credentials.AnonymousCredentials(), + ) + + # Attempting to call a method with both a request object and flattened + # fields is an error. + with pytest.raises(ValueError): + await client.delete_model( + model.DeleteModelRequest(), + project_id='project_id_value', + dataset_id='dataset_id_value', + model_id='model_id_value', + ) + + +def test_credentials_transport_error(): + # It is an error to provide credentials and a transport instance. + transport = transports.ModelServiceGrpcTransport( + credentials=ga_credentials.AnonymousCredentials(), + ) + with pytest.raises(ValueError): + client = ModelServiceClient( + credentials=ga_credentials.AnonymousCredentials(), + transport=transport, + ) + + # It is an error to provide a credentials file and a transport instance. + transport = transports.ModelServiceGrpcTransport( + credentials=ga_credentials.AnonymousCredentials(), + ) + with pytest.raises(ValueError): + client = ModelServiceClient( + client_options={"credentials_file": "credentials.json"}, + transport=transport, + ) + + # It is an error to provide scopes and a transport instance. + transport = transports.ModelServiceGrpcTransport( + credentials=ga_credentials.AnonymousCredentials(), + ) + with pytest.raises(ValueError): + client = ModelServiceClient( + client_options={"scopes": ["1", "2"]}, + transport=transport, + ) + + +def test_transport_instance(): + # A client may be instantiated with a custom transport instance. + transport = transports.ModelServiceGrpcTransport( + credentials=ga_credentials.AnonymousCredentials(), + ) + client = ModelServiceClient(transport=transport) + assert client.transport is transport + +def test_transport_get_channel(): + # A client may be instantiated with a custom transport instance. + transport = transports.ModelServiceGrpcTransport( + credentials=ga_credentials.AnonymousCredentials(), + ) + channel = transport.grpc_channel + assert channel + + transport = transports.ModelServiceGrpcAsyncIOTransport( + credentials=ga_credentials.AnonymousCredentials(), + ) + channel = transport.grpc_channel + assert channel + +@pytest.mark.parametrize("transport_class", [ + transports.ModelServiceGrpcTransport, + transports.ModelServiceGrpcAsyncIOTransport, +]) +def test_transport_adc(transport_class): + # Test default credentials are used if not provided. + with mock.patch.object(google.auth, 'default') as adc: + adc.return_value = (ga_credentials.AnonymousCredentials(), None) + transport_class() + adc.assert_called_once() + +def test_transport_grpc_default(): + # A client should use the gRPC transport by default. + client = ModelServiceClient( + credentials=ga_credentials.AnonymousCredentials(), + ) + assert isinstance( + client.transport, + transports.ModelServiceGrpcTransport, + ) + +def test_model_service_base_transport_error(): + # Passing both a credentials object and credentials_file should raise an error + with pytest.raises(core_exceptions.DuplicateCredentialArgs): + transport = transports.ModelServiceTransport( + credentials=ga_credentials.AnonymousCredentials(), + credentials_file="credentials.json" + ) + + +def test_model_service_base_transport(): + # Instantiate the base transport. + with mock.patch('google.cloud.bigquery_v2.services.model_service.transports.ModelServiceTransport.__init__') as Transport: + Transport.return_value = None + transport = transports.ModelServiceTransport( + credentials=ga_credentials.AnonymousCredentials(), + ) + + # Every method on the transport should just blindly + # raise NotImplementedError. + methods = ( + 'get_model', + 'list_models', + 'patch_model', + 'delete_model', + ) + for method in methods: + with pytest.raises(NotImplementedError): + getattr(transport, method)(request=object()) + + +@requires_google_auth_gte_1_25_0 +def test_model_service_base_transport_with_credentials_file(): + # Instantiate the base transport with a credentials file + with mock.patch.object(google.auth, 'load_credentials_from_file', autospec=True) as load_creds, mock.patch('google.cloud.bigquery_v2.services.model_service.transports.ModelServiceTransport._prep_wrapped_messages') as Transport: + Transport.return_value = None + load_creds.return_value = (ga_credentials.AnonymousCredentials(), None) + transport = transports.ModelServiceTransport( + credentials_file="credentials.json", + quota_project_id="octopus", + ) + load_creds.assert_called_once_with("credentials.json", + scopes=None, + default_scopes=( + 'https://www.googleapis.com/auth/bigquery', + 'https://www.googleapis.com/auth/bigquery.readonly', + 'https://www.googleapis.com/auth/cloud-platform', + 'https://www.googleapis.com/auth/cloud-platform.read-only', +), + quota_project_id="octopus", + ) + + +@requires_google_auth_lt_1_25_0 +def test_model_service_base_transport_with_credentials_file_old_google_auth(): + # Instantiate the base transport with a credentials file + with mock.patch.object(google.auth, 'load_credentials_from_file', autospec=True) as load_creds, mock.patch('google.cloud.bigquery_v2.services.model_service.transports.ModelServiceTransport._prep_wrapped_messages') as Transport: + Transport.return_value = None + load_creds.return_value = (ga_credentials.AnonymousCredentials(), None) + transport = transports.ModelServiceTransport( + credentials_file="credentials.json", + quota_project_id="octopus", + ) + load_creds.assert_called_once_with("credentials.json", scopes=( + 'https://www.googleapis.com/auth/bigquery', + 'https://www.googleapis.com/auth/bigquery.readonly', + 'https://www.googleapis.com/auth/cloud-platform', + 'https://www.googleapis.com/auth/cloud-platform.read-only', + ), + quota_project_id="octopus", + ) + + +def test_model_service_base_transport_with_adc(): + # Test the default credentials are used if credentials and credentials_file are None. + with mock.patch.object(google.auth, 'default', autospec=True) as adc, mock.patch('google.cloud.bigquery_v2.services.model_service.transports.ModelServiceTransport._prep_wrapped_messages') as Transport: + Transport.return_value = None + adc.return_value = (ga_credentials.AnonymousCredentials(), None) + transport = transports.ModelServiceTransport() + adc.assert_called_once() + + +@requires_google_auth_gte_1_25_0 +def test_model_service_auth_adc(): + # If no credentials are provided, we should use ADC credentials. + with mock.patch.object(google.auth, 'default', autospec=True) as adc: + adc.return_value = (ga_credentials.AnonymousCredentials(), None) + ModelServiceClient() + adc.assert_called_once_with( + scopes=None, + default_scopes=( + 'https://www.googleapis.com/auth/bigquery', + 'https://www.googleapis.com/auth/bigquery.readonly', + 'https://www.googleapis.com/auth/cloud-platform', + 'https://www.googleapis.com/auth/cloud-platform.read-only', +), + quota_project_id=None, + ) + + +@requires_google_auth_lt_1_25_0 +def test_model_service_auth_adc_old_google_auth(): + # If no credentials are provided, we should use ADC credentials. + with mock.patch.object(google.auth, 'default', autospec=True) as adc: + adc.return_value = (ga_credentials.AnonymousCredentials(), None) + ModelServiceClient() + adc.assert_called_once_with( + scopes=( 'https://www.googleapis.com/auth/bigquery', 'https://www.googleapis.com/auth/bigquery.readonly', 'https://www.googleapis.com/auth/cloud-platform', 'https://www.googleapis.com/auth/cloud-platform.read-only',), + quota_project_id=None, + ) + + +@pytest.mark.parametrize( + "transport_class", + [ + transports.ModelServiceGrpcTransport, + transports.ModelServiceGrpcAsyncIOTransport, + ], +) +@requires_google_auth_gte_1_25_0 +def test_model_service_transport_auth_adc(transport_class): + # If credentials and host are not provided, the transport class should use + # ADC credentials. + with mock.patch.object(google.auth, 'default', autospec=True) as adc: + adc.return_value = (ga_credentials.AnonymousCredentials(), None) + transport_class(quota_project_id="octopus", scopes=["1", "2"]) + adc.assert_called_once_with( + scopes=["1", "2"], + default_scopes=( 'https://www.googleapis.com/auth/bigquery', 'https://www.googleapis.com/auth/bigquery.readonly', 'https://www.googleapis.com/auth/cloud-platform', 'https://www.googleapis.com/auth/cloud-platform.read-only',), + quota_project_id="octopus", + ) + + +@pytest.mark.parametrize( + "transport_class", + [ + transports.ModelServiceGrpcTransport, + transports.ModelServiceGrpcAsyncIOTransport, + ], +) +@requires_google_auth_lt_1_25_0 +def test_model_service_transport_auth_adc_old_google_auth(transport_class): + # If credentials and host are not provided, the transport class should use + # ADC credentials. + with mock.patch.object(google.auth, "default", autospec=True) as adc: + adc.return_value = (ga_credentials.AnonymousCredentials(), None) + transport_class(quota_project_id="octopus") + adc.assert_called_once_with(scopes=( + 'https://www.googleapis.com/auth/bigquery', + 'https://www.googleapis.com/auth/bigquery.readonly', + 'https://www.googleapis.com/auth/cloud-platform', + 'https://www.googleapis.com/auth/cloud-platform.read-only', +), + quota_project_id="octopus", + ) + + +@pytest.mark.parametrize( + "transport_class,grpc_helpers", + [ + (transports.ModelServiceGrpcTransport, grpc_helpers), + (transports.ModelServiceGrpcAsyncIOTransport, grpc_helpers_async) + ], +) +def test_model_service_transport_create_channel(transport_class, grpc_helpers): + # If credentials and host are not provided, the transport class should use + # ADC credentials. + with mock.patch.object(google.auth, "default", autospec=True) as adc, mock.patch.object( + grpc_helpers, "create_channel", autospec=True + ) as create_channel: + creds = ga_credentials.AnonymousCredentials() + adc.return_value = (creds, None) + transport_class( + quota_project_id="octopus", + scopes=["1", "2"] + ) + + create_channel.assert_called_with( + "bigquery.googleapis.com:443", + credentials=creds, + credentials_file=None, + quota_project_id="octopus", + default_scopes=( + 'https://www.googleapis.com/auth/bigquery', + 'https://www.googleapis.com/auth/bigquery.readonly', + 'https://www.googleapis.com/auth/cloud-platform', + 'https://www.googleapis.com/auth/cloud-platform.read-only', +), + scopes=["1", "2"], + default_host="bigquery.googleapis.com", + ssl_credentials=None, + options=[ + ("grpc.max_send_message_length", -1), + ("grpc.max_receive_message_length", -1), + ], + ) + + +@pytest.mark.parametrize("transport_class", [transports.ModelServiceGrpcTransport, transports.ModelServiceGrpcAsyncIOTransport]) +def test_model_service_grpc_transport_client_cert_source_for_mtls( + transport_class +): + cred = ga_credentials.AnonymousCredentials() + + # Check ssl_channel_credentials is used if provided. + with mock.patch.object(transport_class, "create_channel") as mock_create_channel: + mock_ssl_channel_creds = mock.Mock() + transport_class( + host="squid.clam.whelk", + credentials=cred, + ssl_channel_credentials=mock_ssl_channel_creds + ) + mock_create_channel.assert_called_once_with( + "squid.clam.whelk:443", + credentials=cred, + credentials_file=None, + scopes=None, + ssl_credentials=mock_ssl_channel_creds, + quota_project_id=None, + options=[ + ("grpc.max_send_message_length", -1), + ("grpc.max_receive_message_length", -1), + ], + ) + + # Check if ssl_channel_credentials is not provided, then client_cert_source_for_mtls + # is used. + with mock.patch.object(transport_class, "create_channel", return_value=mock.Mock()): + with mock.patch("grpc.ssl_channel_credentials") as mock_ssl_cred: + transport_class( + credentials=cred, + client_cert_source_for_mtls=client_cert_source_callback + ) + expected_cert, expected_key = client_cert_source_callback() + mock_ssl_cred.assert_called_once_with( + certificate_chain=expected_cert, + private_key=expected_key + ) + + +def test_model_service_host_no_port(): + client = ModelServiceClient( + credentials=ga_credentials.AnonymousCredentials(), + client_options=client_options.ClientOptions(api_endpoint='bigquery.googleapis.com'), + ) + assert client.transport._host == 'bigquery.googleapis.com:443' + + +def test_model_service_host_with_port(): + client = ModelServiceClient( + credentials=ga_credentials.AnonymousCredentials(), + client_options=client_options.ClientOptions(api_endpoint='bigquery.googleapis.com:8000'), + ) + assert client.transport._host == 'bigquery.googleapis.com:8000' + +def test_model_service_grpc_transport_channel(): + channel = grpc.secure_channel('http://localhost/', grpc.local_channel_credentials()) + + # Check that channel is used if provided. + transport = transports.ModelServiceGrpcTransport( + host="squid.clam.whelk", + channel=channel, + ) + assert transport.grpc_channel == channel + assert transport._host == "squid.clam.whelk:443" + assert transport._ssl_channel_credentials == None + + +def test_model_service_grpc_asyncio_transport_channel(): + channel = aio.secure_channel('http://localhost/', grpc.local_channel_credentials()) + + # Check that channel is used if provided. + transport = transports.ModelServiceGrpcAsyncIOTransport( + host="squid.clam.whelk", + channel=channel, + ) + assert transport.grpc_channel == channel + assert transport._host == "squid.clam.whelk:443" + assert transport._ssl_channel_credentials == None + + +# Remove this test when deprecated arguments (api_mtls_endpoint, client_cert_source) are +# removed from grpc/grpc_asyncio transport constructor. +@pytest.mark.parametrize("transport_class", [transports.ModelServiceGrpcTransport, transports.ModelServiceGrpcAsyncIOTransport]) +def test_model_service_transport_channel_mtls_with_client_cert_source( + transport_class +): + with mock.patch("grpc.ssl_channel_credentials", autospec=True) as grpc_ssl_channel_cred: + with mock.patch.object(transport_class, "create_channel") as grpc_create_channel: + mock_ssl_cred = mock.Mock() + grpc_ssl_channel_cred.return_value = mock_ssl_cred + + mock_grpc_channel = mock.Mock() + grpc_create_channel.return_value = mock_grpc_channel + + cred = ga_credentials.AnonymousCredentials() + with pytest.warns(DeprecationWarning): + with mock.patch.object(google.auth, 'default') as adc: + adc.return_value = (cred, None) + transport = transport_class( + host="squid.clam.whelk", + api_mtls_endpoint="mtls.squid.clam.whelk", + client_cert_source=client_cert_source_callback, + ) + adc.assert_called_once() + + grpc_ssl_channel_cred.assert_called_once_with( + certificate_chain=b"cert bytes", private_key=b"key bytes" + ) + grpc_create_channel.assert_called_once_with( + "mtls.squid.clam.whelk:443", + credentials=cred, + credentials_file=None, + scopes=None, + ssl_credentials=mock_ssl_cred, + quota_project_id=None, + options=[ + ("grpc.max_send_message_length", -1), + ("grpc.max_receive_message_length", -1), + ], + ) + assert transport.grpc_channel == mock_grpc_channel + assert transport._ssl_channel_credentials == mock_ssl_cred + + +# Remove this test when deprecated arguments (api_mtls_endpoint, client_cert_source) are +# removed from grpc/grpc_asyncio transport constructor. +@pytest.mark.parametrize("transport_class", [transports.ModelServiceGrpcTransport, transports.ModelServiceGrpcAsyncIOTransport]) +def test_model_service_transport_channel_mtls_with_adc( + transport_class +): + mock_ssl_cred = mock.Mock() + with mock.patch.multiple( + "google.auth.transport.grpc.SslCredentials", + __init__=mock.Mock(return_value=None), + ssl_credentials=mock.PropertyMock(return_value=mock_ssl_cred), + ): + with mock.patch.object(transport_class, "create_channel") as grpc_create_channel: + mock_grpc_channel = mock.Mock() + grpc_create_channel.return_value = mock_grpc_channel + mock_cred = mock.Mock() + + with pytest.warns(DeprecationWarning): + transport = transport_class( + host="squid.clam.whelk", + credentials=mock_cred, + api_mtls_endpoint="mtls.squid.clam.whelk", + client_cert_source=None, + ) + + grpc_create_channel.assert_called_once_with( + "mtls.squid.clam.whelk:443", + credentials=mock_cred, + credentials_file=None, + scopes=None, + ssl_credentials=mock_ssl_cred, + quota_project_id=None, + options=[ + ("grpc.max_send_message_length", -1), + ("grpc.max_receive_message_length", -1), + ], + ) + assert transport.grpc_channel == mock_grpc_channel + + +def test_common_billing_account_path(): + billing_account = "squid" + expected = "billingAccounts/{billing_account}".format(billing_account=billing_account, ) + actual = ModelServiceClient.common_billing_account_path(billing_account) + assert expected == actual + + +def test_parse_common_billing_account_path(): + expected = { + "billing_account": "clam", + } + path = ModelServiceClient.common_billing_account_path(**expected) + + # Check that the path construction is reversible. + actual = ModelServiceClient.parse_common_billing_account_path(path) + assert expected == actual + +def test_common_folder_path(): + folder = "whelk" + expected = "folders/{folder}".format(folder=folder, ) + actual = ModelServiceClient.common_folder_path(folder) + assert expected == actual + + +def test_parse_common_folder_path(): + expected = { + "folder": "octopus", + } + path = ModelServiceClient.common_folder_path(**expected) + + # Check that the path construction is reversible. + actual = ModelServiceClient.parse_common_folder_path(path) + assert expected == actual + +def test_common_organization_path(): + organization = "oyster" + expected = "organizations/{organization}".format(organization=organization, ) + actual = ModelServiceClient.common_organization_path(organization) + assert expected == actual + + +def test_parse_common_organization_path(): + expected = { + "organization": "nudibranch", + } + path = ModelServiceClient.common_organization_path(**expected) + + # Check that the path construction is reversible. + actual = ModelServiceClient.parse_common_organization_path(path) + assert expected == actual + +def test_common_project_path(): + project = "cuttlefish" + expected = "projects/{project}".format(project=project, ) + actual = ModelServiceClient.common_project_path(project) + assert expected == actual + + +def test_parse_common_project_path(): + expected = { + "project": "mussel", + } + path = ModelServiceClient.common_project_path(**expected) + + # Check that the path construction is reversible. + actual = ModelServiceClient.parse_common_project_path(path) + assert expected == actual + +def test_common_location_path(): + project = "winkle" + location = "nautilus" + expected = "projects/{project}/locations/{location}".format(project=project, location=location, ) + actual = ModelServiceClient.common_location_path(project, location) + assert expected == actual + + +def test_parse_common_location_path(): + expected = { + "project": "scallop", + "location": "abalone", + } + path = ModelServiceClient.common_location_path(**expected) + + # Check that the path construction is reversible. + actual = ModelServiceClient.parse_common_location_path(path) + assert expected == actual + + +def test_client_withDEFAULT_CLIENT_INFO(): + client_info = gapic_v1.client_info.ClientInfo() + + with mock.patch.object(transports.ModelServiceTransport, '_prep_wrapped_messages') as prep: + client = ModelServiceClient( + credentials=ga_credentials.AnonymousCredentials(), + client_info=client_info, + ) + prep.assert_called_once_with(client_info) + + with mock.patch.object(transports.ModelServiceTransport, '_prep_wrapped_messages') as prep: + transport_class = ModelServiceClient.get_transport_class() + transport = transport_class( + credentials=ga_credentials.AnonymousCredentials(), + client_info=client_info, + ) + prep.assert_called_once_with(client_info) From 88fb113e628056e4700f5f4fa026a0cb93672311 Mon Sep 17 00:00:00 2001 From: Owl Bot Date: Fri, 16 Jul 2021 20:50:28 +0000 Subject: [PATCH 2/4] =?UTF-8?q?=F0=9F=A6=89=20Updates=20from=20OwlBot?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit See https://github.com/googleapis/repo-automation-bots/blob/master/packages/owl-bot/README.md --- .coveragerc | 1 - google/cloud/bigquery_v2/__init__.py | 2 + google/cloud/bigquery_v2/types/__init__.py | 2 + .../cloud/bigquery_v2/types/standard_sql.py | 19 +- owl-bot-staging/v2/.coveragerc | 17 - owl-bot-staging/v2/MANIFEST.in | 2 - owl-bot-staging/v2/README.rst | 49 - .../v2/docs/bigquery_v2/model_service.rst | 6 - .../v2/docs/bigquery_v2/services.rst | 6 - owl-bot-staging/v2/docs/bigquery_v2/types.rst | 7 - owl-bot-staging/v2/docs/conf.py | 376 ---- owl-bot-staging/v2/docs/index.rst | 7 - .../v2/google/cloud/bigquery/__init__.py | 49 - .../v2/google/cloud/bigquery/py.typed | 2 - .../v2/google/cloud/bigquery_v2/__init__.py | 50 - .../cloud/bigquery_v2/gapic_metadata.json | 63 - .../v2/google/cloud/bigquery_v2/py.typed | 2 - .../cloud/bigquery_v2/services/__init__.py | 15 - .../services/model_service/__init__.py | 22 - .../services/model_service/async_client.py | 510 ----- .../services/model_service/client.py | 688 ------- .../model_service/transports/__init__.py | 33 - .../services/model_service/transports/base.py | 215 -- .../services/model_service/transports/grpc.py | 332 --- .../model_service/transports/grpc_asyncio.py | 336 --- .../cloud/bigquery_v2/types/__init__.py | 54 - .../bigquery_v2/types/encryption_config.py | 47 - .../google/cloud/bigquery_v2/types/model.py | 1821 ----------------- .../bigquery_v2/types/model_reference.py | 56 - .../cloud/bigquery_v2/types/standard_sql.py | 141 -- .../bigquery_v2/types/table_reference.py | 58 - owl-bot-staging/v2/mypy.ini | 3 - owl-bot-staging/v2/noxfile.py | 132 -- .../v2/scripts/fixup_bigquery_v2_keywords.py | 179 -- owl-bot-staging/v2/setup.py | 53 - owl-bot-staging/v2/tests/__init__.py | 16 - owl-bot-staging/v2/tests/unit/__init__.py | 16 - .../v2/tests/unit/gapic/__init__.py | 16 - .../tests/unit/gapic/bigquery_v2/__init__.py | 16 - .../gapic/bigquery_v2/test_model_service.py | 1712 ---------------- 40 files changed, 22 insertions(+), 7109 deletions(-) delete mode 100644 owl-bot-staging/v2/.coveragerc delete mode 100644 owl-bot-staging/v2/MANIFEST.in delete mode 100644 owl-bot-staging/v2/README.rst delete mode 100644 owl-bot-staging/v2/docs/bigquery_v2/model_service.rst delete mode 100644 owl-bot-staging/v2/docs/bigquery_v2/services.rst delete mode 100644 owl-bot-staging/v2/docs/bigquery_v2/types.rst delete mode 100644 owl-bot-staging/v2/docs/conf.py delete mode 100644 owl-bot-staging/v2/docs/index.rst delete mode 100644 owl-bot-staging/v2/google/cloud/bigquery/__init__.py delete mode 100644 owl-bot-staging/v2/google/cloud/bigquery/py.typed delete mode 100644 owl-bot-staging/v2/google/cloud/bigquery_v2/__init__.py delete mode 100644 owl-bot-staging/v2/google/cloud/bigquery_v2/gapic_metadata.json delete mode 100644 owl-bot-staging/v2/google/cloud/bigquery_v2/py.typed delete mode 100644 owl-bot-staging/v2/google/cloud/bigquery_v2/services/__init__.py delete mode 100644 owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/__init__.py delete mode 100644 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owl-bot-staging/v2/google/cloud/bigquery_v2/types/standard_sql.py delete mode 100644 owl-bot-staging/v2/google/cloud/bigquery_v2/types/table_reference.py delete mode 100644 owl-bot-staging/v2/mypy.ini delete mode 100644 owl-bot-staging/v2/noxfile.py delete mode 100644 owl-bot-staging/v2/scripts/fixup_bigquery_v2_keywords.py delete mode 100644 owl-bot-staging/v2/setup.py delete mode 100644 owl-bot-staging/v2/tests/__init__.py delete mode 100644 owl-bot-staging/v2/tests/unit/__init__.py delete mode 100644 owl-bot-staging/v2/tests/unit/gapic/__init__.py delete mode 100644 owl-bot-staging/v2/tests/unit/gapic/bigquery_v2/__init__.py delete mode 100644 owl-bot-staging/v2/tests/unit/gapic/bigquery_v2/test_model_service.py diff --git a/.coveragerc b/.coveragerc index 23861a8eb..33ea00ba9 100644 --- a/.coveragerc +++ b/.coveragerc @@ -2,7 +2,6 @@ branch = True [report] -fail_under = 100 show_missing = True omit = google/cloud/bigquery/__init__.py diff --git a/google/cloud/bigquery_v2/__init__.py b/google/cloud/bigquery_v2/__init__.py index 476bd5747..f9957efa9 100644 --- a/google/cloud/bigquery_v2/__init__.py +++ b/google/cloud/bigquery_v2/__init__.py @@ -26,6 +26,7 @@ from .types.standard_sql import StandardSqlDataType from .types.standard_sql import StandardSqlField from .types.standard_sql import StandardSqlStructType +from .types.standard_sql import StandardSqlTableType from .types.table_reference import TableReference __all__ = ( @@ -40,5 +41,6 @@ "StandardSqlDataType", "StandardSqlField", "StandardSqlStructType", + "StandardSqlTableType", "TableReference", ) diff --git a/google/cloud/bigquery_v2/types/__init__.py b/google/cloud/bigquery_v2/types/__init__.py index 9c850dca1..83bbb3a54 100644 --- a/google/cloud/bigquery_v2/types/__init__.py +++ b/google/cloud/bigquery_v2/types/__init__.py @@ -27,6 +27,7 @@ StandardSqlDataType, StandardSqlField, StandardSqlStructType, + StandardSqlTableType, ) from .table_reference import TableReference @@ -42,5 +43,6 @@ "StandardSqlDataType", "StandardSqlField", "StandardSqlStructType", + "StandardSqlTableType", "TableReference", ) diff --git a/google/cloud/bigquery_v2/types/standard_sql.py b/google/cloud/bigquery_v2/types/standard_sql.py index b2191a417..7a845fc48 100644 --- a/google/cloud/bigquery_v2/types/standard_sql.py +++ b/google/cloud/bigquery_v2/types/standard_sql.py @@ -18,7 +18,12 @@ __protobuf__ = proto.module( package="google.cloud.bigquery.v2", - manifest={"StandardSqlDataType", "StandardSqlField", "StandardSqlStructType",}, + manifest={ + "StandardSqlDataType", + "StandardSqlField", + "StandardSqlStructType", + "StandardSqlTableType", + }, ) @@ -54,9 +59,11 @@ class TypeKind(proto.Enum): DATE = 10 TIME = 20 DATETIME = 21 + INTERVAL = 26 GEOGRAPHY = 22 NUMERIC = 23 BIGNUMERIC = 24 + JSON = 25 ARRAY = 16 STRUCT = 17 @@ -97,4 +104,14 @@ class StandardSqlStructType(proto.Message): fields = proto.RepeatedField(proto.MESSAGE, number=1, message="StandardSqlField",) +class StandardSqlTableType(proto.Message): + r"""A table type + Attributes: + columns (Sequence[google.cloud.bigquery_v2.types.StandardSqlField]): + The columns in this table type + """ + + columns = proto.RepeatedField(proto.MESSAGE, number=1, message="StandardSqlField",) + + __all__ = tuple(sorted(__protobuf__.manifest)) diff --git a/owl-bot-staging/v2/.coveragerc b/owl-bot-staging/v2/.coveragerc deleted file mode 100644 index 33ea00ba9..000000000 --- a/owl-bot-staging/v2/.coveragerc +++ /dev/null @@ -1,17 +0,0 @@ -[run] -branch = True - -[report] -show_missing = True -omit = - google/cloud/bigquery/__init__.py -exclude_lines = - # Re-enable the standard pragma - pragma: NO COVER - # Ignore debug-only repr - def __repr__ - # Ignore pkg_resources exceptions. - # This is added at the module level as a safeguard for if someone - # generates the code and tries to run it without pip installing. This - # makes it virtually impossible to test properly. - except pkg_resources.DistributionNotFound diff --git a/owl-bot-staging/v2/MANIFEST.in b/owl-bot-staging/v2/MANIFEST.in deleted file mode 100644 index df96b1d74..000000000 --- a/owl-bot-staging/v2/MANIFEST.in +++ /dev/null @@ -1,2 +0,0 @@ -recursive-include google/cloud/bigquery *.py -recursive-include google/cloud/bigquery_v2 *.py diff --git a/owl-bot-staging/v2/README.rst b/owl-bot-staging/v2/README.rst deleted file mode 100644 index 402efe90f..000000000 --- a/owl-bot-staging/v2/README.rst +++ /dev/null @@ -1,49 +0,0 @@ -Python Client for Google Cloud Bigquery API -================================================= - -Quick Start ------------ - -In order to use this library, you first need to go through the following steps: - -1. `Select or create a Cloud Platform project.`_ -2. `Enable billing for your project.`_ -3. Enable the Google Cloud Bigquery API. -4. `Setup Authentication.`_ - -.. _Select or create a Cloud Platform project.: https://console.cloud.google.com/project -.. _Enable billing for your project.: https://cloud.google.com/billing/docs/how-to/modify-project#enable_billing_for_a_project -.. _Setup Authentication.: https://googleapis.dev/python/google-api-core/latest/auth.html - -Installation -~~~~~~~~~~~~ - -Install this library in a `virtualenv`_ using pip. `virtualenv`_ is a tool to -create isolated Python environments. The basic problem it addresses is one of -dependencies and versions, and indirectly permissions. - -With `virtualenv`_, it's possible to install this library without needing system -install permissions, and without clashing with the installed system -dependencies. - -.. _`virtualenv`: https://virtualenv.pypa.io/en/latest/ - - -Mac/Linux -^^^^^^^^^ - -.. code-block:: console - - python3 -m venv - source /bin/activate - /bin/pip install /path/to/library - - -Windows -^^^^^^^ - -.. code-block:: console - - python3 -m venv - \Scripts\activate - \Scripts\pip.exe install \path\to\library diff --git a/owl-bot-staging/v2/docs/bigquery_v2/model_service.rst b/owl-bot-staging/v2/docs/bigquery_v2/model_service.rst deleted file mode 100644 index 65b1e5e5f..000000000 --- a/owl-bot-staging/v2/docs/bigquery_v2/model_service.rst +++ /dev/null @@ -1,6 +0,0 @@ -ModelService ------------------------------- - -.. automodule:: google.cloud.bigquery_v2.services.model_service - :members: - :inherited-members: diff --git a/owl-bot-staging/v2/docs/bigquery_v2/services.rst b/owl-bot-staging/v2/docs/bigquery_v2/services.rst deleted file mode 100644 index f8159a448..000000000 --- a/owl-bot-staging/v2/docs/bigquery_v2/services.rst +++ /dev/null @@ -1,6 +0,0 @@ -Services for Google Cloud Bigquery v2 API -========================================= -.. toctree:: - :maxdepth: 2 - - model_service diff --git a/owl-bot-staging/v2/docs/bigquery_v2/types.rst b/owl-bot-staging/v2/docs/bigquery_v2/types.rst deleted file mode 100644 index c36a83e0b..000000000 --- a/owl-bot-staging/v2/docs/bigquery_v2/types.rst +++ /dev/null @@ -1,7 +0,0 @@ -Types for Google Cloud Bigquery v2 API -====================================== - -.. automodule:: google.cloud.bigquery_v2.types - :members: - :undoc-members: - :show-inheritance: diff --git a/owl-bot-staging/v2/docs/conf.py b/owl-bot-staging/v2/docs/conf.py deleted file mode 100644 index 73ab15fdc..000000000 --- a/owl-bot-staging/v2/docs/conf.py +++ /dev/null @@ -1,376 +0,0 @@ -# -*- coding: utf-8 -*- -# Copyright 2020 Google LLC -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -# -# -# google-cloud-bigquery documentation build configuration file -# -# This file is execfile()d with the current directory set to its -# containing dir. -# -# Note that not all possible configuration values are present in this -# autogenerated file. -# -# All configuration values have a default; values that are commented out -# serve to show the default. - -import sys -import os -import shlex - -# If extensions (or modules to document with autodoc) are in another directory, -# add these directories to sys.path here. If the directory is relative to the -# documentation root, use os.path.abspath to make it absolute, like shown here. -sys.path.insert(0, os.path.abspath("..")) - -__version__ = "0.1.0" - -# -- General configuration ------------------------------------------------ - -# If your documentation needs a minimal Sphinx version, state it here. -needs_sphinx = "1.6.3" - -# Add any Sphinx extension module names here, as strings. They can be -# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom -# ones. -extensions = [ - "sphinx.ext.autodoc", - "sphinx.ext.autosummary", - "sphinx.ext.intersphinx", - "sphinx.ext.coverage", - "sphinx.ext.napoleon", - "sphinx.ext.todo", - "sphinx.ext.viewcode", -] - -# autodoc/autosummary flags -autoclass_content = "both" -autodoc_default_flags = ["members"] -autosummary_generate = True - - -# Add any paths that contain templates here, relative to this directory. -templates_path = ["_templates"] - -# Allow markdown includes (so releases.md can include CHANGLEOG.md) -# http://www.sphinx-doc.org/en/master/markdown.html -source_parsers = {".md": "recommonmark.parser.CommonMarkParser"} - -# The suffix(es) of source filenames. -# You can specify multiple suffix as a list of string: -source_suffix = [".rst", ".md"] - -# The encoding of source files. -# source_encoding = 'utf-8-sig' - -# The master toctree document. -master_doc = "index" - -# General information about the project. -project = u"google-cloud-bigquery" -copyright = u"2020, Google, LLC" -author = u"Google APIs" # TODO: autogenerate this bit - -# The version info for the project you're documenting, acts as replacement for -# |version| and |release|, also used in various other places throughout the -# built documents. -# -# The full version, including alpha/beta/rc tags. -release = __version__ -# The short X.Y version. -version = ".".join(release.split(".")[0:2]) - -# The language for content autogenerated by Sphinx. Refer to documentation -# for a list of supported languages. -# -# This is also used if you do content translation via gettext catalogs. -# Usually you set "language" from the command line for these cases. -language = None - -# There are two options for replacing |today|: either, you set today to some -# non-false value, then it is used: -# today = '' -# Else, today_fmt is used as the format for a strftime call. -# today_fmt = '%B %d, %Y' - -# List of patterns, relative to source directory, that match files and -# directories to ignore when looking for source files. -exclude_patterns = ["_build"] - -# The reST default role (used for this markup: `text`) to use for all -# documents. -# default_role = None - -# If true, '()' will be appended to :func: etc. cross-reference text. -# add_function_parentheses = True - -# If true, the current module name will be prepended to all description -# unit titles (such as .. function::). -# add_module_names = True - -# If true, sectionauthor and moduleauthor directives will be shown in the -# output. They are ignored by default. -# show_authors = False - -# The name of the Pygments (syntax highlighting) style to use. -pygments_style = "sphinx" - -# A list of ignored prefixes for module index sorting. -# modindex_common_prefix = [] - -# If true, keep warnings as "system message" paragraphs in the built documents. -# keep_warnings = False - -# If true, `todo` and `todoList` produce output, else they produce nothing. -todo_include_todos = True - - -# -- Options for HTML output ---------------------------------------------- - -# The theme to use for HTML and HTML Help pages. See the documentation for -# a list of builtin themes. -html_theme = "alabaster" - -# Theme options are theme-specific and customize the look and feel of a theme -# further. For a list of options available for each theme, see the -# documentation. -html_theme_options = { - "description": "Google Cloud Client Libraries for Python", - "github_user": "googleapis", - "github_repo": "google-cloud-python", - "github_banner": True, - "font_family": "'Roboto', Georgia, sans", - "head_font_family": "'Roboto', Georgia, serif", - "code_font_family": "'Roboto Mono', 'Consolas', monospace", -} - -# Add any paths that contain custom themes here, relative to this directory. -# html_theme_path = [] - -# The name for this set of Sphinx documents. If None, it defaults to -# " v documentation". -# html_title = None - -# A shorter title for the navigation bar. Default is the same as html_title. -# html_short_title = None - -# The name of an image file (relative to this directory) to place at the top -# of the sidebar. -# html_logo = None - -# The name of an image file (within the static path) to use as favicon of the -# docs. This file should be a Windows icon file (.ico) being 16x16 or 32x32 -# pixels large. -# html_favicon = None - -# Add any paths that contain custom static files (such as style sheets) here, -# relative to this directory. They are copied after the builtin static files, -# so a file named "default.css" will overwrite the builtin "default.css". -html_static_path = ["_static"] - -# Add any extra paths that contain custom files (such as robots.txt or -# .htaccess) here, relative to this directory. These files are copied -# directly to the root of the documentation. -# html_extra_path = [] - -# If not '', a 'Last updated on:' timestamp is inserted at every page bottom, -# using the given strftime format. -# html_last_updated_fmt = '%b %d, %Y' - -# If true, SmartyPants will be used to convert quotes and dashes to -# typographically correct entities. -# html_use_smartypants = True - -# Custom sidebar templates, maps document names to template names. -# html_sidebars = {} - -# Additional templates that should be rendered to pages, maps page names to -# template names. -# html_additional_pages = {} - -# If false, no module index is generated. -# html_domain_indices = True - -# If false, no index is generated. -# html_use_index = True - -# If true, the index is split into individual pages for each letter. -# html_split_index = False - -# If true, links to the reST sources are added to the pages. -# html_show_sourcelink = True - -# If true, "Created using Sphinx" is shown in the HTML footer. Default is True. -# html_show_sphinx = True - -# If true, "(C) Copyright ..." is shown in the HTML footer. Default is True. -# html_show_copyright = True - -# If true, an OpenSearch description file will be output, and all pages will -# contain a tag referring to it. The value of this option must be the -# base URL from which the finished HTML is served. -# html_use_opensearch = '' - -# This is the file name suffix for HTML files (e.g. ".xhtml"). -# html_file_suffix = None - -# Language to be used for generating the HTML full-text search index. -# Sphinx supports the following languages: -# 'da', 'de', 'en', 'es', 'fi', 'fr', 'hu', 'it', 'ja' -# 'nl', 'no', 'pt', 'ro', 'ru', 'sv', 'tr' -# html_search_language = 'en' - -# A dictionary with options for the search language support, empty by default. -# Now only 'ja' uses this config value -# html_search_options = {'type': 'default'} - -# The name of a javascript file (relative to the configuration directory) that -# implements a search results scorer. If empty, the default will be used. -# html_search_scorer = 'scorer.js' - -# Output file base name for HTML help builder. -htmlhelp_basename = "google-cloud-bigquery-doc" - -# -- Options for warnings ------------------------------------------------------ - - -suppress_warnings = [ - # Temporarily suppress this to avoid "more than one target found for - # cross-reference" warning, which are intractable for us to avoid while in - # a mono-repo. - # See https://github.com/sphinx-doc/sphinx/blob - # /2a65ffeef5c107c19084fabdd706cdff3f52d93c/sphinx/domains/python.py#L843 - "ref.python" -] - -# -- Options for LaTeX output --------------------------------------------- - -latex_elements = { - # The paper size ('letterpaper' or 'a4paper'). - # 'papersize': 'letterpaper', - # The font size ('10pt', '11pt' or '12pt'). - # 'pointsize': '10pt', - # Additional stuff for the LaTeX preamble. - # 'preamble': '', - # Latex figure (float) alignment - # 'figure_align': 'htbp', -} - -# Grouping the document tree into LaTeX files. List of tuples -# (source start file, target name, title, -# author, documentclass [howto, manual, or own class]). -latex_documents = [ - ( - master_doc, - "google-cloud-bigquery.tex", - u"google-cloud-bigquery Documentation", - author, - "manual", - ) -] - -# The name of an image file (relative to this directory) to place at the top of -# the title page. -# latex_logo = None - -# For "manual" documents, if this is true, then toplevel headings are parts, -# not chapters. -# latex_use_parts = False - -# If true, show page references after internal links. -# latex_show_pagerefs = False - -# If true, show URL addresses after external links. -# latex_show_urls = False - -# Documents to append as an appendix to all manuals. -# latex_appendices = [] - -# If false, no module index is generated. -# latex_domain_indices = True - - -# -- Options for manual page output --------------------------------------- - -# One entry per manual page. List of tuples -# (source start file, name, description, authors, manual section). -man_pages = [ - ( - master_doc, - "google-cloud-bigquery", - u"Google Cloud Bigquery Documentation", - [author], - 1, - ) -] - -# If true, show URL addresses after external links. -# man_show_urls = False - - -# -- Options for Texinfo output ------------------------------------------- - -# Grouping the document tree into Texinfo files. List of tuples -# (source start file, target name, title, author, -# dir menu entry, description, category) -texinfo_documents = [ - ( - master_doc, - "google-cloud-bigquery", - u"google-cloud-bigquery Documentation", - author, - "google-cloud-bigquery", - "GAPIC library for Google Cloud Bigquery API", - "APIs", - ) -] - -# Documents to append as an appendix to all manuals. -# texinfo_appendices = [] - -# If false, no module index is generated. -# texinfo_domain_indices = True - -# How to display URL addresses: 'footnote', 'no', or 'inline'. -# texinfo_show_urls = 'footnote' - -# If true, do not generate a @detailmenu in the "Top" node's menu. -# texinfo_no_detailmenu = False - - -# Example configuration for intersphinx: refer to the Python standard library. -intersphinx_mapping = { - "python": ("http://python.readthedocs.org/en/latest/", None), - "gax": ("https://gax-python.readthedocs.org/en/latest/", None), - "google-auth": ("https://google-auth.readthedocs.io/en/stable", None), - "google-gax": ("https://gax-python.readthedocs.io/en/latest/", None), - "google.api_core": ("https://googleapis.dev/python/google-api-core/latest/", None), - "grpc": ("https://grpc.io/grpc/python/", None), - "requests": ("http://requests.kennethreitz.org/en/stable/", None), - "proto": ("https://proto-plus-python.readthedocs.io/en/stable", None), - "protobuf": ("https://googleapis.dev/python/protobuf/latest/", None), -} - - -# Napoleon settings -napoleon_google_docstring = True -napoleon_numpy_docstring = True -napoleon_include_private_with_doc = False -napoleon_include_special_with_doc = True -napoleon_use_admonition_for_examples = False -napoleon_use_admonition_for_notes = False -napoleon_use_admonition_for_references = False -napoleon_use_ivar = False -napoleon_use_param = True -napoleon_use_rtype = True diff --git a/owl-bot-staging/v2/docs/index.rst b/owl-bot-staging/v2/docs/index.rst deleted file mode 100644 index ef9072101..000000000 --- a/owl-bot-staging/v2/docs/index.rst +++ /dev/null @@ -1,7 +0,0 @@ -API Reference -------------- -.. toctree:: - :maxdepth: 2 - - bigquery_v2/services - bigquery_v2/types diff --git a/owl-bot-staging/v2/google/cloud/bigquery/__init__.py b/owl-bot-staging/v2/google/cloud/bigquery/__init__.py deleted file mode 100644 index a2b0edcd8..000000000 --- a/owl-bot-staging/v2/google/cloud/bigquery/__init__.py +++ /dev/null @@ -1,49 +0,0 @@ -# -*- coding: utf-8 -*- -# Copyright 2020 Google LLC -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -# - -from google.cloud.bigquery_v2.services.model_service.client import ModelServiceClient -from google.cloud.bigquery_v2.services.model_service.async_client import ModelServiceAsyncClient - -from google.cloud.bigquery_v2.types.encryption_config import EncryptionConfiguration -from google.cloud.bigquery_v2.types.model import DeleteModelRequest -from google.cloud.bigquery_v2.types.model import GetModelRequest -from google.cloud.bigquery_v2.types.model import ListModelsRequest -from google.cloud.bigquery_v2.types.model import ListModelsResponse -from google.cloud.bigquery_v2.types.model import Model -from google.cloud.bigquery_v2.types.model import PatchModelRequest -from google.cloud.bigquery_v2.types.model_reference import ModelReference -from google.cloud.bigquery_v2.types.standard_sql import StandardSqlDataType -from google.cloud.bigquery_v2.types.standard_sql import StandardSqlField -from google.cloud.bigquery_v2.types.standard_sql import StandardSqlStructType -from google.cloud.bigquery_v2.types.standard_sql import StandardSqlTableType -from google.cloud.bigquery_v2.types.table_reference import TableReference - -__all__ = ('ModelServiceClient', - 'ModelServiceAsyncClient', - 'EncryptionConfiguration', - 'DeleteModelRequest', - 'GetModelRequest', - 'ListModelsRequest', - 'ListModelsResponse', - 'Model', - 'PatchModelRequest', - 'ModelReference', - 'StandardSqlDataType', - 'StandardSqlField', - 'StandardSqlStructType', - 'StandardSqlTableType', - 'TableReference', -) diff --git a/owl-bot-staging/v2/google/cloud/bigquery/py.typed b/owl-bot-staging/v2/google/cloud/bigquery/py.typed deleted file mode 100644 index e73777993..000000000 --- a/owl-bot-staging/v2/google/cloud/bigquery/py.typed +++ /dev/null @@ -1,2 +0,0 @@ -# Marker file for PEP 561. -# The google-cloud-bigquery package uses inline types. diff --git a/owl-bot-staging/v2/google/cloud/bigquery_v2/__init__.py b/owl-bot-staging/v2/google/cloud/bigquery_v2/__init__.py deleted file mode 100644 index f7aa4a849..000000000 --- a/owl-bot-staging/v2/google/cloud/bigquery_v2/__init__.py +++ /dev/null @@ -1,50 +0,0 @@ -# -*- coding: utf-8 -*- -# Copyright 2020 Google LLC -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -# - -from .services.model_service import ModelServiceClient -from .services.model_service import ModelServiceAsyncClient - -from .types.encryption_config import EncryptionConfiguration -from .types.model import DeleteModelRequest -from .types.model import GetModelRequest -from .types.model import ListModelsRequest -from .types.model import ListModelsResponse -from .types.model import Model -from .types.model import PatchModelRequest -from .types.model_reference import ModelReference -from .types.standard_sql import StandardSqlDataType -from .types.standard_sql import StandardSqlField -from .types.standard_sql import StandardSqlStructType -from .types.standard_sql import StandardSqlTableType -from .types.table_reference import TableReference - -__all__ = ( - 'ModelServiceAsyncClient', -'DeleteModelRequest', -'EncryptionConfiguration', -'GetModelRequest', -'ListModelsRequest', -'ListModelsResponse', -'Model', -'ModelReference', -'ModelServiceClient', -'PatchModelRequest', -'StandardSqlDataType', -'StandardSqlField', -'StandardSqlStructType', -'StandardSqlTableType', -'TableReference', -) diff --git a/owl-bot-staging/v2/google/cloud/bigquery_v2/gapic_metadata.json b/owl-bot-staging/v2/google/cloud/bigquery_v2/gapic_metadata.json deleted file mode 100644 index 3251a2630..000000000 --- a/owl-bot-staging/v2/google/cloud/bigquery_v2/gapic_metadata.json +++ /dev/null @@ -1,63 +0,0 @@ - { - "comment": "This file maps proto services/RPCs to the corresponding library clients/methods", - "language": "python", - "libraryPackage": "google.cloud.bigquery_v2", - "protoPackage": "google.cloud.bigquery.v2", - "schema": "1.0", - "services": { - "ModelService": { - "clients": { - "grpc": { - "libraryClient": "ModelServiceClient", - "rpcs": { - "DeleteModel": { - "methods": [ - "delete_model" - ] - }, - "GetModel": { - "methods": [ - "get_model" - ] - }, - "ListModels": { - "methods": [ - "list_models" - ] - }, - "PatchModel": { - "methods": [ - "patch_model" - ] - } - } - }, - "grpc-async": { - "libraryClient": "ModelServiceAsyncClient", - "rpcs": { - "DeleteModel": { - "methods": [ - "delete_model" - ] - }, - "GetModel": { - "methods": [ - "get_model" - ] - }, - "ListModels": { - "methods": [ - "list_models" - ] - }, - "PatchModel": { - "methods": [ - "patch_model" - ] - } - } - } - } - } - } -} diff --git a/owl-bot-staging/v2/google/cloud/bigquery_v2/py.typed b/owl-bot-staging/v2/google/cloud/bigquery_v2/py.typed deleted file mode 100644 index e73777993..000000000 --- a/owl-bot-staging/v2/google/cloud/bigquery_v2/py.typed +++ /dev/null @@ -1,2 +0,0 @@ -# Marker file for PEP 561. -# The google-cloud-bigquery package uses inline types. diff --git a/owl-bot-staging/v2/google/cloud/bigquery_v2/services/__init__.py b/owl-bot-staging/v2/google/cloud/bigquery_v2/services/__init__.py deleted file mode 100644 index 4de65971c..000000000 --- a/owl-bot-staging/v2/google/cloud/bigquery_v2/services/__init__.py +++ /dev/null @@ -1,15 +0,0 @@ -# -*- coding: utf-8 -*- -# Copyright 2020 Google LLC -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -# diff --git a/owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/__init__.py b/owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/__init__.py deleted file mode 100644 index 5c4d570d1..000000000 --- a/owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/__init__.py +++ /dev/null @@ -1,22 +0,0 @@ -# -*- coding: utf-8 -*- -# Copyright 2020 Google LLC -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -# -from .client import ModelServiceClient -from .async_client import ModelServiceAsyncClient - -__all__ = ( - 'ModelServiceClient', - 'ModelServiceAsyncClient', -) diff --git a/owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/async_client.py b/owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/async_client.py deleted file mode 100644 index f663b4845..000000000 --- a/owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/async_client.py +++ /dev/null @@ -1,510 +0,0 @@ -# -*- coding: utf-8 -*- -# Copyright 2020 Google LLC -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -# -from collections import OrderedDict -import functools -import re -from typing import Dict, Sequence, Tuple, Type, Union -import pkg_resources - -import google.api_core.client_options as ClientOptions # type: ignore -from google.api_core import exceptions as core_exceptions # type: ignore -from google.api_core import gapic_v1 # type: ignore -from google.api_core import retry as retries # type: ignore -from google.auth import credentials as ga_credentials # type: ignore -from google.oauth2 import service_account # type: ignore - -from google.cloud.bigquery_v2.types import encryption_config -from google.cloud.bigquery_v2.types import model -from google.cloud.bigquery_v2.types import model as gcb_model -from google.cloud.bigquery_v2.types import model_reference -from google.cloud.bigquery_v2.types import standard_sql -from google.protobuf import wrappers_pb2 # type: ignore -from .transports.base import ModelServiceTransport, DEFAULT_CLIENT_INFO -from .transports.grpc_asyncio import ModelServiceGrpcAsyncIOTransport -from .client import ModelServiceClient - - -class ModelServiceAsyncClient: - """""" - - _client: ModelServiceClient - - DEFAULT_ENDPOINT = ModelServiceClient.DEFAULT_ENDPOINT - DEFAULT_MTLS_ENDPOINT = ModelServiceClient.DEFAULT_MTLS_ENDPOINT - - common_billing_account_path = staticmethod(ModelServiceClient.common_billing_account_path) - parse_common_billing_account_path = staticmethod(ModelServiceClient.parse_common_billing_account_path) - common_folder_path = staticmethod(ModelServiceClient.common_folder_path) - parse_common_folder_path = staticmethod(ModelServiceClient.parse_common_folder_path) - common_organization_path = staticmethod(ModelServiceClient.common_organization_path) - parse_common_organization_path = staticmethod(ModelServiceClient.parse_common_organization_path) - common_project_path = staticmethod(ModelServiceClient.common_project_path) - parse_common_project_path = staticmethod(ModelServiceClient.parse_common_project_path) - common_location_path = staticmethod(ModelServiceClient.common_location_path) - parse_common_location_path = staticmethod(ModelServiceClient.parse_common_location_path) - - @classmethod - def from_service_account_info(cls, info: dict, *args, **kwargs): - """Creates an instance of this client using the provided credentials - info. - - Args: - info (dict): The service account private key info. - args: Additional arguments to pass to the constructor. - kwargs: Additional arguments to pass to the constructor. - - Returns: - ModelServiceAsyncClient: The constructed client. - """ - return ModelServiceClient.from_service_account_info.__func__(ModelServiceAsyncClient, info, *args, **kwargs) # type: ignore - - @classmethod - def from_service_account_file(cls, filename: str, *args, **kwargs): - """Creates an instance of this client using the provided credentials - file. - - Args: - filename (str): The path to the service account private key json - file. - args: Additional arguments to pass to the constructor. - kwargs: Additional arguments to pass to the constructor. - - Returns: - ModelServiceAsyncClient: The constructed client. - """ - return ModelServiceClient.from_service_account_file.__func__(ModelServiceAsyncClient, filename, *args, **kwargs) # type: ignore - - from_service_account_json = from_service_account_file - - @property - def transport(self) -> ModelServiceTransport: - """Returns the transport used by the client instance. - - Returns: - ModelServiceTransport: The transport used by the client instance. - """ - return self._client.transport - - get_transport_class = functools.partial(type(ModelServiceClient).get_transport_class, type(ModelServiceClient)) - - def __init__(self, *, - credentials: ga_credentials.Credentials = None, - transport: Union[str, ModelServiceTransport] = "grpc_asyncio", - client_options: ClientOptions = None, - client_info: gapic_v1.client_info.ClientInfo = DEFAULT_CLIENT_INFO, - ) -> None: - """Instantiates the model service client. - - Args: - credentials (Optional[google.auth.credentials.Credentials]): The - authorization credentials to attach to requests. These - credentials identify the application to the service; if none - are specified, the client will attempt to ascertain the - credentials from the environment. - transport (Union[str, ~.ModelServiceTransport]): The - transport to use. If set to None, a transport is chosen - automatically. - client_options (ClientOptions): Custom options for the client. It - won't take effect if a ``transport`` instance is provided. - (1) The ``api_endpoint`` property can be used to override the - default endpoint provided by the client. GOOGLE_API_USE_MTLS_ENDPOINT - environment variable can also be used to override the endpoint: - "always" (always use the default mTLS endpoint), "never" (always - use the default regular endpoint) and "auto" (auto switch to the - default mTLS endpoint if client certificate is present, this is - the default value). However, the ``api_endpoint`` property takes - precedence if provided. - (2) If GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable - is "true", then the ``client_cert_source`` property can be used - to provide client certificate for mutual TLS transport. If - not provided, the default SSL client certificate will be used if - present. If GOOGLE_API_USE_CLIENT_CERTIFICATE is "false" or not - set, no client certificate will be used. - - Raises: - google.auth.exceptions.MutualTlsChannelError: If mutual TLS transport - creation failed for any reason. - """ - self._client = ModelServiceClient( - credentials=credentials, - transport=transport, - client_options=client_options, - client_info=client_info, - - ) - - async def get_model(self, - request: model.GetModelRequest = None, - *, - project_id: str = None, - dataset_id: str = None, - model_id: str = None, - retry: retries.Retry = gapic_v1.method.DEFAULT, - timeout: float = None, - metadata: Sequence[Tuple[str, str]] = (), - ) -> model.Model: - r"""Gets the specified model resource by model ID. - - Args: - request (:class:`google.cloud.bigquery_v2.types.GetModelRequest`): - The request object. - project_id (:class:`str`): - Required. Project ID of the requested - model. - - This corresponds to the ``project_id`` field - on the ``request`` instance; if ``request`` is provided, this - should not be set. - dataset_id (:class:`str`): - Required. Dataset ID of the requested - model. - - This corresponds to the ``dataset_id`` field - on the ``request`` instance; if ``request`` is provided, this - should not be set. - model_id (:class:`str`): - Required. Model ID of the requested - model. - - This corresponds to the ``model_id`` field - on the ``request`` instance; if ``request`` is provided, this - should not be set. - retry (google.api_core.retry.Retry): Designation of what errors, if any, - should be retried. - timeout (float): The timeout for this request. - metadata (Sequence[Tuple[str, str]]): Strings which should be - sent along with the request as metadata. - - Returns: - google.cloud.bigquery_v2.types.Model: - - """ - # Create or coerce a protobuf request object. - # Sanity check: If we got a request object, we should *not* have - # gotten any keyword arguments that map to the request. - has_flattened_params = any([project_id, dataset_id, model_id]) - if request is not None and has_flattened_params: - raise ValueError("If the `request` argument is set, then none of " - "the individual field arguments should be set.") - - request = model.GetModelRequest(request) - - # If we have keyword arguments corresponding to fields on the - # request, apply these. - if project_id is not None: - request.project_id = project_id - if dataset_id is not None: - request.dataset_id = dataset_id - if model_id is not None: - request.model_id = model_id - - # Wrap the RPC method; this adds retry and timeout information, - # and friendly error handling. - rpc = gapic_v1.method_async.wrap_method( - self._client._transport.get_model, - default_timeout=600.0, - client_info=DEFAULT_CLIENT_INFO, - ) - - # Send the request. - response = await rpc( - request, - retry=retry, - timeout=timeout, - metadata=metadata, - ) - - # Done; return the response. - return response - - async def list_models(self, - request: model.ListModelsRequest = None, - *, - project_id: str = None, - dataset_id: str = None, - max_results: wrappers_pb2.UInt32Value = None, - retry: retries.Retry = gapic_v1.method.DEFAULT, - timeout: float = None, - metadata: Sequence[Tuple[str, str]] = (), - ) -> model.ListModelsResponse: - r"""Lists all models in the specified dataset. Requires - the READER dataset role. - - Args: - request (:class:`google.cloud.bigquery_v2.types.ListModelsRequest`): - The request object. - project_id (:class:`str`): - Required. Project ID of the models to - list. - - This corresponds to the ``project_id`` field - on the ``request`` instance; if ``request`` is provided, this - should not be set. - dataset_id (:class:`str`): - Required. Dataset ID of the models to - list. - - This corresponds to the ``dataset_id`` field - on the ``request`` instance; if ``request`` is provided, this - should not be set. - max_results (:class:`google.protobuf.wrappers_pb2.UInt32Value`): - The maximum number of results to - return in a single response page. - Leverage the page tokens to iterate - through the entire collection. - - This corresponds to the ``max_results`` field - on the ``request`` instance; if ``request`` is provided, this - should not be set. - retry (google.api_core.retry.Retry): Designation of what errors, if any, - should be retried. - timeout (float): The timeout for this request. - metadata (Sequence[Tuple[str, str]]): Strings which should be - sent along with the request as metadata. - - Returns: - google.cloud.bigquery_v2.types.ListModelsResponse: - - """ - # Create or coerce a protobuf request object. - # Sanity check: If we got a request object, we should *not* have - # gotten any keyword arguments that map to the request. - has_flattened_params = any([project_id, dataset_id, max_results]) - if request is not None and has_flattened_params: - raise ValueError("If the `request` argument is set, then none of " - "the individual field arguments should be set.") - - request = model.ListModelsRequest(request) - - # If we have keyword arguments corresponding to fields on the - # request, apply these. - if project_id is not None: - request.project_id = project_id - if dataset_id is not None: - request.dataset_id = dataset_id - if max_results is not None: - request.max_results = max_results - - # Wrap the RPC method; this adds retry and timeout information, - # and friendly error handling. - rpc = gapic_v1.method_async.wrap_method( - self._client._transport.list_models, - default_timeout=600.0, - client_info=DEFAULT_CLIENT_INFO, - ) - - # Send the request. - response = await rpc( - request, - retry=retry, - timeout=timeout, - metadata=metadata, - ) - - # Done; return the response. - return response - - async def patch_model(self, - request: gcb_model.PatchModelRequest = None, - *, - project_id: str = None, - dataset_id: str = None, - model_id: str = None, - model: gcb_model.Model = None, - retry: retries.Retry = gapic_v1.method.DEFAULT, - timeout: float = None, - metadata: Sequence[Tuple[str, str]] = (), - ) -> gcb_model.Model: - r"""Patch specific fields in the specified model. - - Args: - request (:class:`google.cloud.bigquery_v2.types.PatchModelRequest`): - The request object. - project_id (:class:`str`): - Required. Project ID of the model to - patch. - - This corresponds to the ``project_id`` field - on the ``request`` instance; if ``request`` is provided, this - should not be set. - dataset_id (:class:`str`): - Required. Dataset ID of the model to - patch. - - This corresponds to the ``dataset_id`` field - on the ``request`` instance; if ``request`` is provided, this - should not be set. - model_id (:class:`str`): - Required. Model ID of the model to - patch. - - This corresponds to the ``model_id`` field - on the ``request`` instance; if ``request`` is provided, this - should not be set. - model (:class:`google.cloud.bigquery_v2.types.Model`): - Required. Patched model. - Follows RFC5789 patch semantics. Missing - fields are not updated. To clear a - field, explicitly set to default value. - - This corresponds to the ``model`` field - on the ``request`` instance; if ``request`` is provided, this - should not be set. - retry (google.api_core.retry.Retry): Designation of what errors, if any, - should be retried. - timeout (float): The timeout for this request. - metadata (Sequence[Tuple[str, str]]): Strings which should be - sent along with the request as metadata. - - Returns: - google.cloud.bigquery_v2.types.Model: - - """ - # Create or coerce a protobuf request object. - # Sanity check: If we got a request object, we should *not* have - # gotten any keyword arguments that map to the request. - has_flattened_params = any([project_id, dataset_id, model_id, model]) - if request is not None and has_flattened_params: - raise ValueError("If the `request` argument is set, then none of " - "the individual field arguments should be set.") - - request = gcb_model.PatchModelRequest(request) - - # If we have keyword arguments corresponding to fields on the - # request, apply these. - if project_id is not None: - request.project_id = project_id - if dataset_id is not None: - request.dataset_id = dataset_id - if model_id is not None: - request.model_id = model_id - if model is not None: - request.model = model - - # Wrap the RPC method; this adds retry and timeout information, - # and friendly error handling. - rpc = gapic_v1.method_async.wrap_method( - self._client._transport.patch_model, - default_timeout=600.0, - client_info=DEFAULT_CLIENT_INFO, - ) - - # Send the request. - response = await rpc( - request, - retry=retry, - timeout=timeout, - metadata=metadata, - ) - - # Done; return the response. - return response - - async def delete_model(self, - request: model.DeleteModelRequest = None, - *, - project_id: str = None, - dataset_id: str = None, - model_id: str = None, - retry: retries.Retry = gapic_v1.method.DEFAULT, - timeout: float = None, - metadata: Sequence[Tuple[str, str]] = (), - ) -> None: - r"""Deletes the model specified by modelId from the - dataset. - - Args: - request (:class:`google.cloud.bigquery_v2.types.DeleteModelRequest`): - The request object. - project_id (:class:`str`): - Required. Project ID of the model to - delete. - - This corresponds to the ``project_id`` field - on the ``request`` instance; if ``request`` is provided, this - should not be set. - dataset_id (:class:`str`): - Required. Dataset ID of the model to - delete. - - This corresponds to the ``dataset_id`` field - on the ``request`` instance; if ``request`` is provided, this - should not be set. - model_id (:class:`str`): - Required. Model ID of the model to - delete. - - This corresponds to the ``model_id`` field - on the ``request`` instance; if ``request`` is provided, this - should not be set. - retry (google.api_core.retry.Retry): Designation of what errors, if any, - should be retried. - timeout (float): The timeout for this request. - metadata (Sequence[Tuple[str, str]]): Strings which should be - sent along with the request as metadata. - """ - # Create or coerce a protobuf request object. - # Sanity check: If we got a request object, we should *not* have - # gotten any keyword arguments that map to the request. - has_flattened_params = any([project_id, dataset_id, model_id]) - if request is not None and has_flattened_params: - raise ValueError("If the `request` argument is set, then none of " - "the individual field arguments should be set.") - - request = model.DeleteModelRequest(request) - - # If we have keyword arguments corresponding to fields on the - # request, apply these. - if project_id is not None: - request.project_id = project_id - if dataset_id is not None: - request.dataset_id = dataset_id - if model_id is not None: - request.model_id = model_id - - # Wrap the RPC method; this adds retry and timeout information, - # and friendly error handling. - rpc = gapic_v1.method_async.wrap_method( - self._client._transport.delete_model, - default_timeout=600.0, - client_info=DEFAULT_CLIENT_INFO, - ) - - # Send the request. - await rpc( - request, - retry=retry, - timeout=timeout, - metadata=metadata, - ) - - - - - -try: - DEFAULT_CLIENT_INFO = gapic_v1.client_info.ClientInfo( - gapic_version=pkg_resources.get_distribution( - "google-cloud-bigquery", - ).version, - ) -except pkg_resources.DistributionNotFound: - DEFAULT_CLIENT_INFO = gapic_v1.client_info.ClientInfo() - - -__all__ = ( - "ModelServiceAsyncClient", -) diff --git a/owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/client.py b/owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/client.py deleted file mode 100644 index 856416def..000000000 --- a/owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/client.py +++ /dev/null @@ -1,688 +0,0 @@ -# -*- coding: utf-8 -*- -# Copyright 2020 Google LLC -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -# -from collections import OrderedDict -from distutils import util -import os -import re -from typing import Callable, Dict, Optional, Sequence, Tuple, Type, Union -import pkg_resources - -from google.api_core import client_options as client_options_lib # type: ignore -from google.api_core import exceptions as core_exceptions # type: ignore -from google.api_core import gapic_v1 # type: ignore -from google.api_core import retry as retries # type: ignore -from google.auth import credentials as ga_credentials # type: ignore -from google.auth.transport import mtls # type: ignore -from google.auth.transport.grpc import SslCredentials # type: ignore -from google.auth.exceptions import MutualTLSChannelError # type: ignore -from google.oauth2 import service_account # type: ignore - -from google.cloud.bigquery_v2.types import encryption_config -from google.cloud.bigquery_v2.types import model -from google.cloud.bigquery_v2.types import model as gcb_model -from google.cloud.bigquery_v2.types import model_reference -from google.cloud.bigquery_v2.types import standard_sql -from google.protobuf import wrappers_pb2 # type: ignore -from .transports.base import ModelServiceTransport, DEFAULT_CLIENT_INFO -from .transports.grpc import ModelServiceGrpcTransport -from .transports.grpc_asyncio import ModelServiceGrpcAsyncIOTransport - - -class ModelServiceClientMeta(type): - """Metaclass for the ModelService client. - - This provides class-level methods for building and retrieving - support objects (e.g. transport) without polluting the client instance - objects. - """ - _transport_registry = OrderedDict() # type: Dict[str, Type[ModelServiceTransport]] - _transport_registry["grpc"] = ModelServiceGrpcTransport - _transport_registry["grpc_asyncio"] = ModelServiceGrpcAsyncIOTransport - - def get_transport_class(cls, - label: str = None, - ) -> Type[ModelServiceTransport]: - """Returns an appropriate transport class. - - Args: - label: The name of the desired transport. If none is - provided, then the first transport in the registry is used. - - Returns: - The transport class to use. - """ - # If a specific transport is requested, return that one. - if label: - return cls._transport_registry[label] - - # No transport is requested; return the default (that is, the first one - # in the dictionary). - return next(iter(cls._transport_registry.values())) - - -class ModelServiceClient(metaclass=ModelServiceClientMeta): - """""" - - @staticmethod - def _get_default_mtls_endpoint(api_endpoint): - """Converts api endpoint to mTLS endpoint. - - Convert "*.sandbox.googleapis.com" and "*.googleapis.com" to - "*.mtls.sandbox.googleapis.com" and "*.mtls.googleapis.com" respectively. - Args: - api_endpoint (Optional[str]): the api endpoint to convert. - Returns: - str: converted mTLS api endpoint. - """ - if not api_endpoint: - return api_endpoint - - mtls_endpoint_re = re.compile( - r"(?P[^.]+)(?P\.mtls)?(?P\.sandbox)?(?P\.googleapis\.com)?" - ) - - m = mtls_endpoint_re.match(api_endpoint) - name, mtls, sandbox, googledomain = m.groups() - if mtls or not googledomain: - return api_endpoint - - if sandbox: - return api_endpoint.replace( - "sandbox.googleapis.com", "mtls.sandbox.googleapis.com" - ) - - return api_endpoint.replace(".googleapis.com", ".mtls.googleapis.com") - - DEFAULT_ENDPOINT = "bigquery.googleapis.com" - DEFAULT_MTLS_ENDPOINT = _get_default_mtls_endpoint.__func__( # type: ignore - DEFAULT_ENDPOINT - ) - - @classmethod - def from_service_account_info(cls, info: dict, *args, **kwargs): - """Creates an instance of this client using the provided credentials - info. - - Args: - info (dict): The service account private key info. - args: Additional arguments to pass to the constructor. - kwargs: Additional arguments to pass to the constructor. - - Returns: - ModelServiceClient: The constructed client. - """ - credentials = service_account.Credentials.from_service_account_info(info) - kwargs["credentials"] = credentials - return cls(*args, **kwargs) - - @classmethod - def from_service_account_file(cls, filename: str, *args, **kwargs): - """Creates an instance of this client using the provided credentials - file. - - Args: - filename (str): The path to the service account private key json - file. - args: Additional arguments to pass to the constructor. - kwargs: Additional arguments to pass to the constructor. - - Returns: - ModelServiceClient: The constructed client. - """ - credentials = service_account.Credentials.from_service_account_file( - filename) - kwargs["credentials"] = credentials - return cls(*args, **kwargs) - - from_service_account_json = from_service_account_file - - @property - def transport(self) -> ModelServiceTransport: - """Returns the transport used by the client instance. - - Returns: - ModelServiceTransport: The transport used by the client - instance. - """ - return self._transport - - @staticmethod - def common_billing_account_path(billing_account: str, ) -> str: - """Returns a fully-qualified billing_account string.""" - return "billingAccounts/{billing_account}".format(billing_account=billing_account, ) - - @staticmethod - def parse_common_billing_account_path(path: str) -> Dict[str,str]: - """Parse a billing_account path into its component segments.""" - m = re.match(r"^billingAccounts/(?P.+?)$", path) - return m.groupdict() if m else {} - - @staticmethod - def common_folder_path(folder: str, ) -> str: - """Returns a fully-qualified folder string.""" - return "folders/{folder}".format(folder=folder, ) - - @staticmethod - def parse_common_folder_path(path: str) -> Dict[str,str]: - """Parse a folder path into its component segments.""" - m = re.match(r"^folders/(?P.+?)$", path) - return m.groupdict() if m else {} - - @staticmethod - def common_organization_path(organization: str, ) -> str: - """Returns a fully-qualified organization string.""" - return "organizations/{organization}".format(organization=organization, ) - - @staticmethod - def parse_common_organization_path(path: str) -> Dict[str,str]: - """Parse a organization path into its component segments.""" - m = re.match(r"^organizations/(?P.+?)$", path) - return m.groupdict() if m else {} - - @staticmethod - def common_project_path(project: str, ) -> str: - """Returns a fully-qualified project string.""" - return "projects/{project}".format(project=project, ) - - @staticmethod - def parse_common_project_path(path: str) -> Dict[str,str]: - """Parse a project path into its component segments.""" - m = re.match(r"^projects/(?P.+?)$", path) - return m.groupdict() if m else {} - - @staticmethod - def common_location_path(project: str, location: str, ) -> str: - """Returns a fully-qualified location string.""" - return "projects/{project}/locations/{location}".format(project=project, location=location, ) - - @staticmethod - def parse_common_location_path(path: str) -> Dict[str,str]: - """Parse a location path into its component segments.""" - m = re.match(r"^projects/(?P.+?)/locations/(?P.+?)$", path) - return m.groupdict() if m else {} - - def __init__(self, *, - credentials: Optional[ga_credentials.Credentials] = None, - transport: Union[str, ModelServiceTransport, None] = None, - client_options: Optional[client_options_lib.ClientOptions] = None, - client_info: gapic_v1.client_info.ClientInfo = DEFAULT_CLIENT_INFO, - ) -> None: - """Instantiates the model service client. - - Args: - credentials (Optional[google.auth.credentials.Credentials]): The - authorization credentials to attach to requests. These - credentials identify the application to the service; if none - are specified, the client will attempt to ascertain the - credentials from the environment. - transport (Union[str, ModelServiceTransport]): The - transport to use. If set to None, a transport is chosen - automatically. - client_options (google.api_core.client_options.ClientOptions): Custom options for the - client. It won't take effect if a ``transport`` instance is provided. - (1) The ``api_endpoint`` property can be used to override the - default endpoint provided by the client. GOOGLE_API_USE_MTLS_ENDPOINT - environment variable can also be used to override the endpoint: - "always" (always use the default mTLS endpoint), "never" (always - use the default regular endpoint) and "auto" (auto switch to the - default mTLS endpoint if client certificate is present, this is - the default value). However, the ``api_endpoint`` property takes - precedence if provided. - (2) If GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable - is "true", then the ``client_cert_source`` property can be used - to provide client certificate for mutual TLS transport. If - not provided, the default SSL client certificate will be used if - present. If GOOGLE_API_USE_CLIENT_CERTIFICATE is "false" or not - set, no client certificate will be used. - client_info (google.api_core.gapic_v1.client_info.ClientInfo): - The client info used to send a user-agent string along with - API requests. If ``None``, then default info will be used. - Generally, you only need to set this if you're developing - your own client library. - - Raises: - google.auth.exceptions.MutualTLSChannelError: If mutual TLS transport - creation failed for any reason. - """ - if isinstance(client_options, dict): - client_options = client_options_lib.from_dict(client_options) - if client_options is None: - client_options = client_options_lib.ClientOptions() - - # Create SSL credentials for mutual TLS if needed. - use_client_cert = bool(util.strtobool(os.getenv("GOOGLE_API_USE_CLIENT_CERTIFICATE", "false"))) - - client_cert_source_func = None - is_mtls = False - if use_client_cert: - if client_options.client_cert_source: - is_mtls = True - client_cert_source_func = client_options.client_cert_source - else: - is_mtls = mtls.has_default_client_cert_source() - if is_mtls: - client_cert_source_func = mtls.default_client_cert_source() - else: - client_cert_source_func = None - - # Figure out which api endpoint to use. - if client_options.api_endpoint is not None: - api_endpoint = client_options.api_endpoint - else: - use_mtls_env = os.getenv("GOOGLE_API_USE_MTLS_ENDPOINT", "auto") - if use_mtls_env == "never": - api_endpoint = self.DEFAULT_ENDPOINT - elif use_mtls_env == "always": - api_endpoint = self.DEFAULT_MTLS_ENDPOINT - elif use_mtls_env == "auto": - if is_mtls: - api_endpoint = self.DEFAULT_MTLS_ENDPOINT - else: - api_endpoint = self.DEFAULT_ENDPOINT - else: - raise MutualTLSChannelError( - "Unsupported GOOGLE_API_USE_MTLS_ENDPOINT value. Accepted " - "values: never, auto, always" - ) - - # Save or instantiate the transport. - # Ordinarily, we provide the transport, but allowing a custom transport - # instance provides an extensibility point for unusual situations. - if isinstance(transport, ModelServiceTransport): - # transport is a ModelServiceTransport instance. - if credentials or client_options.credentials_file: - raise ValueError("When providing a transport instance, " - "provide its credentials directly.") - if client_options.scopes: - raise ValueError( - "When providing a transport instance, provide its scopes " - "directly." - ) - self._transport = transport - else: - Transport = type(self).get_transport_class(transport) - self._transport = Transport( - credentials=credentials, - credentials_file=client_options.credentials_file, - host=api_endpoint, - scopes=client_options.scopes, - client_cert_source_for_mtls=client_cert_source_func, - quota_project_id=client_options.quota_project_id, - client_info=client_info, - ) - - def get_model(self, - request: model.GetModelRequest = None, - *, - project_id: str = None, - dataset_id: str = None, - model_id: str = None, - retry: retries.Retry = gapic_v1.method.DEFAULT, - timeout: float = None, - metadata: Sequence[Tuple[str, str]] = (), - ) -> model.Model: - r"""Gets the specified model resource by model ID. - - Args: - request (google.cloud.bigquery_v2.types.GetModelRequest): - The request object. - project_id (str): - Required. Project ID of the requested - model. - - This corresponds to the ``project_id`` field - on the ``request`` instance; if ``request`` is provided, this - should not be set. - dataset_id (str): - Required. Dataset ID of the requested - model. - - This corresponds to the ``dataset_id`` field - on the ``request`` instance; if ``request`` is provided, this - should not be set. - model_id (str): - Required. Model ID of the requested - model. - - This corresponds to the ``model_id`` field - on the ``request`` instance; if ``request`` is provided, this - should not be set. - retry (google.api_core.retry.Retry): Designation of what errors, if any, - should be retried. - timeout (float): The timeout for this request. - metadata (Sequence[Tuple[str, str]]): Strings which should be - sent along with the request as metadata. - - Returns: - google.cloud.bigquery_v2.types.Model: - - """ - # Create or coerce a protobuf request object. - # Sanity check: If we got a request object, we should *not* have - # gotten any keyword arguments that map to the request. - has_flattened_params = any([project_id, dataset_id, model_id]) - if request is not None and has_flattened_params: - raise ValueError('If the `request` argument is set, then none of ' - 'the individual field arguments should be set.') - - # Minor optimization to avoid making a copy if the user passes - # in a model.GetModelRequest. - # There's no risk of modifying the input as we've already verified - # there are no flattened fields. - if not isinstance(request, model.GetModelRequest): - request = model.GetModelRequest(request) - # If we have keyword arguments corresponding to fields on the - # request, apply these. - if project_id is not None: - request.project_id = project_id - if dataset_id is not None: - request.dataset_id = dataset_id - if model_id is not None: - request.model_id = model_id - - # Wrap the RPC method; this adds retry and timeout information, - # and friendly error handling. - rpc = self._transport._wrapped_methods[self._transport.get_model] - - # Send the request. - response = rpc( - request, - retry=retry, - timeout=timeout, - metadata=metadata, - ) - - # Done; return the response. - return response - - def list_models(self, - request: model.ListModelsRequest = None, - *, - project_id: str = None, - dataset_id: str = None, - max_results: wrappers_pb2.UInt32Value = None, - retry: retries.Retry = gapic_v1.method.DEFAULT, - timeout: float = None, - metadata: Sequence[Tuple[str, str]] = (), - ) -> model.ListModelsResponse: - r"""Lists all models in the specified dataset. Requires - the READER dataset role. - - Args: - request (google.cloud.bigquery_v2.types.ListModelsRequest): - The request object. - project_id (str): - Required. Project ID of the models to - list. - - This corresponds to the ``project_id`` field - on the ``request`` instance; if ``request`` is provided, this - should not be set. - dataset_id (str): - Required. Dataset ID of the models to - list. - - This corresponds to the ``dataset_id`` field - on the ``request`` instance; if ``request`` is provided, this - should not be set. - max_results (google.protobuf.wrappers_pb2.UInt32Value): - The maximum number of results to - return in a single response page. - Leverage the page tokens to iterate - through the entire collection. - - This corresponds to the ``max_results`` field - on the ``request`` instance; if ``request`` is provided, this - should not be set. - retry (google.api_core.retry.Retry): Designation of what errors, if any, - should be retried. - timeout (float): The timeout for this request. - metadata (Sequence[Tuple[str, str]]): Strings which should be - sent along with the request as metadata. - - Returns: - google.cloud.bigquery_v2.types.ListModelsResponse: - - """ - # Create or coerce a protobuf request object. - # Sanity check: If we got a request object, we should *not* have - # gotten any keyword arguments that map to the request. - has_flattened_params = any([project_id, dataset_id, max_results]) - if request is not None and has_flattened_params: - raise ValueError('If the `request` argument is set, then none of ' - 'the individual field arguments should be set.') - - # Minor optimization to avoid making a copy if the user passes - # in a model.ListModelsRequest. - # There's no risk of modifying the input as we've already verified - # there are no flattened fields. - if not isinstance(request, model.ListModelsRequest): - request = model.ListModelsRequest(request) - # If we have keyword arguments corresponding to fields on the - # request, apply these. - if project_id is not None: - request.project_id = project_id - if dataset_id is not None: - request.dataset_id = dataset_id - if max_results is not None: - request.max_results = max_results - - # Wrap the RPC method; this adds retry and timeout information, - # and friendly error handling. - rpc = self._transport._wrapped_methods[self._transport.list_models] - - # Send the request. - response = rpc( - request, - retry=retry, - timeout=timeout, - metadata=metadata, - ) - - # Done; return the response. - return response - - def patch_model(self, - request: gcb_model.PatchModelRequest = None, - *, - project_id: str = None, - dataset_id: str = None, - model_id: str = None, - model: gcb_model.Model = None, - retry: retries.Retry = gapic_v1.method.DEFAULT, - timeout: float = None, - metadata: Sequence[Tuple[str, str]] = (), - ) -> gcb_model.Model: - r"""Patch specific fields in the specified model. - - Args: - request (google.cloud.bigquery_v2.types.PatchModelRequest): - The request object. - project_id (str): - Required. Project ID of the model to - patch. - - This corresponds to the ``project_id`` field - on the ``request`` instance; if ``request`` is provided, this - should not be set. - dataset_id (str): - Required. Dataset ID of the model to - patch. - - This corresponds to the ``dataset_id`` field - on the ``request`` instance; if ``request`` is provided, this - should not be set. - model_id (str): - Required. Model ID of the model to - patch. - - This corresponds to the ``model_id`` field - on the ``request`` instance; if ``request`` is provided, this - should not be set. - model (google.cloud.bigquery_v2.types.Model): - Required. Patched model. - Follows RFC5789 patch semantics. Missing - fields are not updated. To clear a - field, explicitly set to default value. - - This corresponds to the ``model`` field - on the ``request`` instance; if ``request`` is provided, this - should not be set. - retry (google.api_core.retry.Retry): Designation of what errors, if any, - should be retried. - timeout (float): The timeout for this request. - metadata (Sequence[Tuple[str, str]]): Strings which should be - sent along with the request as metadata. - - Returns: - google.cloud.bigquery_v2.types.Model: - - """ - # Create or coerce a protobuf request object. - # Sanity check: If we got a request object, we should *not* have - # gotten any keyword arguments that map to the request. - has_flattened_params = any([project_id, dataset_id, model_id, model]) - if request is not None and has_flattened_params: - raise ValueError('If the `request` argument is set, then none of ' - 'the individual field arguments should be set.') - - # Minor optimization to avoid making a copy if the user passes - # in a gcb_model.PatchModelRequest. - # There's no risk of modifying the input as we've already verified - # there are no flattened fields. - if not isinstance(request, gcb_model.PatchModelRequest): - request = gcb_model.PatchModelRequest(request) - # If we have keyword arguments corresponding to fields on the - # request, apply these. - if project_id is not None: - request.project_id = project_id - if dataset_id is not None: - request.dataset_id = dataset_id - if model_id is not None: - request.model_id = model_id - if model is not None: - request.model = model - - # Wrap the RPC method; this adds retry and timeout information, - # and friendly error handling. - rpc = self._transport._wrapped_methods[self._transport.patch_model] - - # Send the request. - response = rpc( - request, - retry=retry, - timeout=timeout, - metadata=metadata, - ) - - # Done; return the response. - return response - - def delete_model(self, - request: model.DeleteModelRequest = None, - *, - project_id: str = None, - dataset_id: str = None, - model_id: str = None, - retry: retries.Retry = gapic_v1.method.DEFAULT, - timeout: float = None, - metadata: Sequence[Tuple[str, str]] = (), - ) -> None: - r"""Deletes the model specified by modelId from the - dataset. - - Args: - request (google.cloud.bigquery_v2.types.DeleteModelRequest): - The request object. - project_id (str): - Required. Project ID of the model to - delete. - - This corresponds to the ``project_id`` field - on the ``request`` instance; if ``request`` is provided, this - should not be set. - dataset_id (str): - Required. Dataset ID of the model to - delete. - - This corresponds to the ``dataset_id`` field - on the ``request`` instance; if ``request`` is provided, this - should not be set. - model_id (str): - Required. Model ID of the model to - delete. - - This corresponds to the ``model_id`` field - on the ``request`` instance; if ``request`` is provided, this - should not be set. - retry (google.api_core.retry.Retry): Designation of what errors, if any, - should be retried. - timeout (float): The timeout for this request. - metadata (Sequence[Tuple[str, str]]): Strings which should be - sent along with the request as metadata. - """ - # Create or coerce a protobuf request object. - # Sanity check: If we got a request object, we should *not* have - # gotten any keyword arguments that map to the request. - has_flattened_params = any([project_id, dataset_id, model_id]) - if request is not None and has_flattened_params: - raise ValueError('If the `request` argument is set, then none of ' - 'the individual field arguments should be set.') - - # Minor optimization to avoid making a copy if the user passes - # in a model.DeleteModelRequest. - # There's no risk of modifying the input as we've already verified - # there are no flattened fields. - if not isinstance(request, model.DeleteModelRequest): - request = model.DeleteModelRequest(request) - # If we have keyword arguments corresponding to fields on the - # request, apply these. - if project_id is not None: - request.project_id = project_id - if dataset_id is not None: - request.dataset_id = dataset_id - if model_id is not None: - request.model_id = model_id - - # Wrap the RPC method; this adds retry and timeout information, - # and friendly error handling. - rpc = self._transport._wrapped_methods[self._transport.delete_model] - - # Send the request. - rpc( - request, - retry=retry, - timeout=timeout, - metadata=metadata, - ) - - - - - -try: - DEFAULT_CLIENT_INFO = gapic_v1.client_info.ClientInfo( - gapic_version=pkg_resources.get_distribution( - "google-cloud-bigquery", - ).version, - ) -except pkg_resources.DistributionNotFound: - DEFAULT_CLIENT_INFO = gapic_v1.client_info.ClientInfo() - - -__all__ = ( - "ModelServiceClient", -) diff --git a/owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/transports/__init__.py b/owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/transports/__init__.py deleted file mode 100644 index 0f09224d3..000000000 --- a/owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/transports/__init__.py +++ /dev/null @@ -1,33 +0,0 @@ -# -*- coding: utf-8 -*- -# Copyright 2020 Google LLC -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -# -from collections import OrderedDict -from typing import Dict, Type - -from .base import ModelServiceTransport -from .grpc import ModelServiceGrpcTransport -from .grpc_asyncio import ModelServiceGrpcAsyncIOTransport - - -# Compile a registry of transports. -_transport_registry = OrderedDict() # type: Dict[str, Type[ModelServiceTransport]] -_transport_registry['grpc'] = ModelServiceGrpcTransport -_transport_registry['grpc_asyncio'] = ModelServiceGrpcAsyncIOTransport - -__all__ = ( - 'ModelServiceTransport', - 'ModelServiceGrpcTransport', - 'ModelServiceGrpcAsyncIOTransport', -) diff --git a/owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/transports/base.py b/owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/transports/base.py deleted file mode 100644 index 3b3c4ae99..000000000 --- a/owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/transports/base.py +++ /dev/null @@ -1,215 +0,0 @@ -# -*- coding: utf-8 -*- -# Copyright 2020 Google LLC -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -# -import abc -from typing import Awaitable, Callable, Dict, Optional, Sequence, Union -import packaging.version -import pkg_resources - -import google.auth # type: ignore -import google.api_core # type: ignore -from google.api_core import exceptions as core_exceptions # type: ignore -from google.api_core import gapic_v1 # type: ignore -from google.api_core import retry as retries # type: ignore -from google.auth import credentials as ga_credentials # type: ignore -from google.oauth2 import service_account # type: ignore - -from google.cloud.bigquery_v2.types import model -from google.cloud.bigquery_v2.types import model as gcb_model -from google.protobuf import empty_pb2 # type: ignore - -try: - DEFAULT_CLIENT_INFO = gapic_v1.client_info.ClientInfo( - gapic_version=pkg_resources.get_distribution( - 'google-cloud-bigquery', - ).version, - ) -except pkg_resources.DistributionNotFound: - DEFAULT_CLIENT_INFO = gapic_v1.client_info.ClientInfo() - -try: - # google.auth.__version__ was added in 1.26.0 - _GOOGLE_AUTH_VERSION = google.auth.__version__ -except AttributeError: - try: # try pkg_resources if it is available - _GOOGLE_AUTH_VERSION = pkg_resources.get_distribution("google-auth").version - except pkg_resources.DistributionNotFound: # pragma: NO COVER - _GOOGLE_AUTH_VERSION = None - - -class ModelServiceTransport(abc.ABC): - """Abstract transport class for ModelService.""" - - AUTH_SCOPES = ( - 'https://www.googleapis.com/auth/bigquery', - 'https://www.googleapis.com/auth/bigquery.readonly', - 'https://www.googleapis.com/auth/cloud-platform', - 'https://www.googleapis.com/auth/cloud-platform.read-only', - ) - - DEFAULT_HOST: str = 'bigquery.googleapis.com' - def __init__( - self, *, - host: str = DEFAULT_HOST, - credentials: ga_credentials.Credentials = None, - credentials_file: Optional[str] = None, - scopes: Optional[Sequence[str]] = None, - quota_project_id: Optional[str] = None, - client_info: gapic_v1.client_info.ClientInfo = DEFAULT_CLIENT_INFO, - always_use_jwt_access: Optional[bool] = False, - **kwargs, - ) -> None: - """Instantiate the transport. - - Args: - host (Optional[str]): - The hostname to connect to. - credentials (Optional[google.auth.credentials.Credentials]): The - authorization credentials to attach to requests. These - credentials identify the application to the service; if none - are specified, the client will attempt to ascertain the - credentials from the environment. - credentials_file (Optional[str]): A file with credentials that can - be loaded with :func:`google.auth.load_credentials_from_file`. - This argument is mutually exclusive with credentials. - scopes (Optional[Sequence[str]]): A list of scopes. - quota_project_id (Optional[str]): An optional project to use for billing - and quota. - client_info (google.api_core.gapic_v1.client_info.ClientInfo): - The client info used to send a user-agent string along with - API requests. If ``None``, then default info will be used. - Generally, you only need to set this if you're developing - your own client library. - always_use_jwt_access (Optional[bool]): Whether self signed JWT should - be used for service account credentials. - """ - # Save the hostname. Default to port 443 (HTTPS) if none is specified. - if ':' not in host: - host += ':443' - self._host = host - - scopes_kwargs = self._get_scopes_kwargs(self._host, scopes) - - # Save the scopes. - self._scopes = scopes - - # If no credentials are provided, then determine the appropriate - # defaults. - if credentials and credentials_file: - raise core_exceptions.DuplicateCredentialArgs("'credentials_file' and 'credentials' are mutually exclusive") - - if credentials_file is not None: - credentials, _ = google.auth.load_credentials_from_file( - credentials_file, - **scopes_kwargs, - quota_project_id=quota_project_id - ) - - elif credentials is None: - credentials, _ = google.auth.default(**scopes_kwargs, quota_project_id=quota_project_id) - - # If the credentials is service account credentials, then always try to use self signed JWT. - if always_use_jwt_access and isinstance(credentials, service_account.Credentials) and hasattr(service_account.Credentials, "with_always_use_jwt_access"): - credentials = credentials.with_always_use_jwt_access(True) - - # Save the credentials. - self._credentials = credentials - - # TODO(busunkim): This method is in the base transport - # to avoid duplicating code across the transport classes. These functions - # should be deleted once the minimum required versions of google-auth is increased. - - # TODO: Remove this function once google-auth >= 1.25.0 is required - @classmethod - def _get_scopes_kwargs(cls, host: str, scopes: Optional[Sequence[str]]) -> Dict[str, Optional[Sequence[str]]]: - """Returns scopes kwargs to pass to google-auth methods depending on the google-auth version""" - - scopes_kwargs = {} - - if _GOOGLE_AUTH_VERSION and ( - packaging.version.parse(_GOOGLE_AUTH_VERSION) - >= packaging.version.parse("1.25.0") - ): - scopes_kwargs = {"scopes": scopes, "default_scopes": cls.AUTH_SCOPES} - else: - scopes_kwargs = {"scopes": scopes or cls.AUTH_SCOPES} - - return scopes_kwargs - - def _prep_wrapped_messages(self, client_info): - # Precompute the wrapped methods. - self._wrapped_methods = { - self.get_model: gapic_v1.method.wrap_method( - self.get_model, - default_timeout=600.0, - client_info=client_info, - ), - self.list_models: gapic_v1.method.wrap_method( - self.list_models, - default_timeout=600.0, - client_info=client_info, - ), - self.patch_model: gapic_v1.method.wrap_method( - self.patch_model, - default_timeout=600.0, - client_info=client_info, - ), - self.delete_model: gapic_v1.method.wrap_method( - self.delete_model, - default_timeout=600.0, - client_info=client_info, - ), - } - - @property - def get_model(self) -> Callable[ - [model.GetModelRequest], - Union[ - model.Model, - Awaitable[model.Model] - ]]: - raise NotImplementedError() - - @property - def list_models(self) -> Callable[ - [model.ListModelsRequest], - Union[ - model.ListModelsResponse, - Awaitable[model.ListModelsResponse] - ]]: - raise NotImplementedError() - - @property - def patch_model(self) -> Callable[ - [gcb_model.PatchModelRequest], - Union[ - gcb_model.Model, - Awaitable[gcb_model.Model] - ]]: - raise NotImplementedError() - - @property - def delete_model(self) -> Callable[ - [model.DeleteModelRequest], - Union[ - empty_pb2.Empty, - Awaitable[empty_pb2.Empty] - ]]: - raise NotImplementedError() - - -__all__ = ( - 'ModelServiceTransport', -) diff --git a/owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/transports/grpc.py b/owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/transports/grpc.py deleted file mode 100644 index a873fde46..000000000 --- a/owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/transports/grpc.py +++ /dev/null @@ -1,332 +0,0 @@ -# -*- coding: utf-8 -*- -# Copyright 2020 Google LLC -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -# -import warnings -from typing import Callable, Dict, Optional, Sequence, Tuple, Union - -from google.api_core import grpc_helpers # type: ignore -from google.api_core import gapic_v1 # type: ignore -import google.auth # type: ignore -from google.auth import credentials as ga_credentials # type: ignore -from google.auth.transport.grpc import SslCredentials # type: ignore - -import grpc # type: ignore - -from google.cloud.bigquery_v2.types import model -from google.cloud.bigquery_v2.types import model as gcb_model -from google.protobuf import empty_pb2 # type: ignore -from .base import ModelServiceTransport, DEFAULT_CLIENT_INFO - - -class ModelServiceGrpcTransport(ModelServiceTransport): - """gRPC backend transport for ModelService. - - This class defines the same methods as the primary client, so the - primary client can load the underlying transport implementation - and call it. - - It sends protocol buffers over the wire using gRPC (which is built on - top of HTTP/2); the ``grpcio`` package must be installed. - """ - _stubs: Dict[str, Callable] - - def __init__(self, *, - host: str = 'bigquery.googleapis.com', - credentials: ga_credentials.Credentials = None, - credentials_file: str = None, - scopes: Sequence[str] = None, - channel: grpc.Channel = None, - api_mtls_endpoint: str = None, - client_cert_source: Callable[[], Tuple[bytes, bytes]] = None, - ssl_channel_credentials: grpc.ChannelCredentials = None, - client_cert_source_for_mtls: Callable[[], Tuple[bytes, bytes]] = None, - quota_project_id: Optional[str] = None, - client_info: gapic_v1.client_info.ClientInfo = DEFAULT_CLIENT_INFO, - always_use_jwt_access: Optional[bool] = False, - ) -> None: - """Instantiate the transport. - - Args: - host (Optional[str]): - The hostname to connect to. - credentials (Optional[google.auth.credentials.Credentials]): The - authorization credentials to attach to requests. These - credentials identify the application to the service; if none - are specified, the client will attempt to ascertain the - credentials from the environment. - This argument is ignored if ``channel`` is provided. - credentials_file (Optional[str]): A file with credentials that can - be loaded with :func:`google.auth.load_credentials_from_file`. - This argument is ignored if ``channel`` is provided. - scopes (Optional(Sequence[str])): A list of scopes. This argument is - ignored if ``channel`` is provided. - channel (Optional[grpc.Channel]): A ``Channel`` instance through - which to make calls. - api_mtls_endpoint (Optional[str]): Deprecated. The mutual TLS endpoint. - If provided, it overrides the ``host`` argument and tries to create - a mutual TLS channel with client SSL credentials from - ``client_cert_source`` or applicatin default SSL credentials. - client_cert_source (Optional[Callable[[], Tuple[bytes, bytes]]]): - Deprecated. A callback to provide client SSL certificate bytes and - private key bytes, both in PEM format. It is ignored if - ``api_mtls_endpoint`` is None. - ssl_channel_credentials (grpc.ChannelCredentials): SSL credentials - for grpc channel. It is ignored if ``channel`` is provided. - client_cert_source_for_mtls (Optional[Callable[[], Tuple[bytes, bytes]]]): - A callback to provide client certificate bytes and private key bytes, - both in PEM format. It is used to configure mutual TLS channel. It is - ignored if ``channel`` or ``ssl_channel_credentials`` is provided. - quota_project_id (Optional[str]): An optional project to use for billing - and quota. - client_info (google.api_core.gapic_v1.client_info.ClientInfo): - The client info used to send a user-agent string along with - API requests. If ``None``, then default info will be used. - Generally, you only need to set this if you're developing - your own client library. - always_use_jwt_access (Optional[bool]): Whether self signed JWT should - be used for service account credentials. - - Raises: - google.auth.exceptions.MutualTLSChannelError: If mutual TLS transport - creation failed for any reason. - google.api_core.exceptions.DuplicateCredentialArgs: If both ``credentials`` - and ``credentials_file`` are passed. - """ - self._grpc_channel = None - self._ssl_channel_credentials = ssl_channel_credentials - self._stubs: Dict[str, Callable] = {} - - if api_mtls_endpoint: - warnings.warn("api_mtls_endpoint is deprecated", DeprecationWarning) - if client_cert_source: - warnings.warn("client_cert_source is deprecated", DeprecationWarning) - - if channel: - # Ignore credentials if a channel was passed. - credentials = False - # If a channel was explicitly provided, set it. - self._grpc_channel = channel - self._ssl_channel_credentials = None - - else: - if api_mtls_endpoint: - host = api_mtls_endpoint - - # Create SSL credentials with client_cert_source or application - # default SSL credentials. - if client_cert_source: - cert, key = client_cert_source() - self._ssl_channel_credentials = grpc.ssl_channel_credentials( - certificate_chain=cert, private_key=key - ) - else: - self._ssl_channel_credentials = SslCredentials().ssl_credentials - - else: - if client_cert_source_for_mtls and not ssl_channel_credentials: - cert, key = client_cert_source_for_mtls() - self._ssl_channel_credentials = grpc.ssl_channel_credentials( - certificate_chain=cert, private_key=key - ) - - # The base transport sets the host, credentials and scopes - super().__init__( - host=host, - credentials=credentials, - credentials_file=credentials_file, - scopes=scopes, - quota_project_id=quota_project_id, - client_info=client_info, - always_use_jwt_access=always_use_jwt_access, - ) - - if not self._grpc_channel: - self._grpc_channel = type(self).create_channel( - self._host, - credentials=self._credentials, - credentials_file=credentials_file, - scopes=self._scopes, - ssl_credentials=self._ssl_channel_credentials, - quota_project_id=quota_project_id, - options=[ - ("grpc.max_send_message_length", -1), - ("grpc.max_receive_message_length", -1), - ], - ) - - # Wrap messages. This must be done after self._grpc_channel exists - self._prep_wrapped_messages(client_info) - - @classmethod - def create_channel(cls, - host: str = 'bigquery.googleapis.com', - credentials: ga_credentials.Credentials = None, - credentials_file: str = None, - scopes: Optional[Sequence[str]] = None, - quota_project_id: Optional[str] = None, - **kwargs) -> grpc.Channel: - """Create and return a gRPC channel object. - Args: - host (Optional[str]): The host for the channel to use. - credentials (Optional[~.Credentials]): The - authorization credentials to attach to requests. These - credentials identify this application to the service. If - none are specified, the client will attempt to ascertain - the credentials from the environment. - credentials_file (Optional[str]): A file with credentials that can - be loaded with :func:`google.auth.load_credentials_from_file`. - This argument is mutually exclusive with credentials. - scopes (Optional[Sequence[str]]): A optional list of scopes needed for this - service. These are only used when credentials are not specified and - are passed to :func:`google.auth.default`. - quota_project_id (Optional[str]): An optional project to use for billing - and quota. - kwargs (Optional[dict]): Keyword arguments, which are passed to the - channel creation. - Returns: - grpc.Channel: A gRPC channel object. - - Raises: - google.api_core.exceptions.DuplicateCredentialArgs: If both ``credentials`` - and ``credentials_file`` are passed. - """ - - return grpc_helpers.create_channel( - host, - credentials=credentials, - credentials_file=credentials_file, - quota_project_id=quota_project_id, - default_scopes=cls.AUTH_SCOPES, - scopes=scopes, - default_host=cls.DEFAULT_HOST, - **kwargs - ) - - @property - def grpc_channel(self) -> grpc.Channel: - """Return the channel designed to connect to this service. - """ - return self._grpc_channel - - @property - def get_model(self) -> Callable[ - [model.GetModelRequest], - model.Model]: - r"""Return a callable for the get model method over gRPC. - - Gets the specified model resource by model ID. - - Returns: - Callable[[~.GetModelRequest], - ~.Model]: - A function that, when called, will call the underlying RPC - on the server. - """ - # Generate a "stub function" on-the-fly which will actually make - # the request. - # gRPC handles serialization and deserialization, so we just need - # to pass in the functions for each. - if 'get_model' not in self._stubs: - self._stubs['get_model'] = self.grpc_channel.unary_unary( - '/google.cloud.bigquery.v2.ModelService/GetModel', - request_serializer=model.GetModelRequest.serialize, - response_deserializer=model.Model.deserialize, - ) - return self._stubs['get_model'] - - @property - def list_models(self) -> Callable[ - [model.ListModelsRequest], - model.ListModelsResponse]: - r"""Return a callable for the list models method over gRPC. - - Lists all models in the specified dataset. Requires - the READER dataset role. - - Returns: - Callable[[~.ListModelsRequest], - ~.ListModelsResponse]: - A function that, when called, will call the underlying RPC - on the server. - """ - # Generate a "stub function" on-the-fly which will actually make - # the request. - # gRPC handles serialization and deserialization, so we just need - # to pass in the functions for each. - if 'list_models' not in self._stubs: - self._stubs['list_models'] = self.grpc_channel.unary_unary( - '/google.cloud.bigquery.v2.ModelService/ListModels', - request_serializer=model.ListModelsRequest.serialize, - response_deserializer=model.ListModelsResponse.deserialize, - ) - return self._stubs['list_models'] - - @property - def patch_model(self) -> Callable[ - [gcb_model.PatchModelRequest], - gcb_model.Model]: - r"""Return a callable for the patch model method over gRPC. - - Patch specific fields in the specified model. - - Returns: - Callable[[~.PatchModelRequest], - ~.Model]: - A function that, when called, will call the underlying RPC - on the server. - """ - # Generate a "stub function" on-the-fly which will actually make - # the request. - # gRPC handles serialization and deserialization, so we just need - # to pass in the functions for each. - if 'patch_model' not in self._stubs: - self._stubs['patch_model'] = self.grpc_channel.unary_unary( - '/google.cloud.bigquery.v2.ModelService/PatchModel', - request_serializer=gcb_model.PatchModelRequest.serialize, - response_deserializer=gcb_model.Model.deserialize, - ) - return self._stubs['patch_model'] - - @property - def delete_model(self) -> Callable[ - [model.DeleteModelRequest], - empty_pb2.Empty]: - r"""Return a callable for the delete model method over gRPC. - - Deletes the model specified by modelId from the - dataset. - - Returns: - Callable[[~.DeleteModelRequest], - ~.Empty]: - A function that, when called, will call the underlying RPC - on the server. - """ - # Generate a "stub function" on-the-fly which will actually make - # the request. - # gRPC handles serialization and deserialization, so we just need - # to pass in the functions for each. - if 'delete_model' not in self._stubs: - self._stubs['delete_model'] = self.grpc_channel.unary_unary( - '/google.cloud.bigquery.v2.ModelService/DeleteModel', - request_serializer=model.DeleteModelRequest.serialize, - response_deserializer=empty_pb2.Empty.FromString, - ) - return self._stubs['delete_model'] - - -__all__ = ( - 'ModelServiceGrpcTransport', -) diff --git a/owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/transports/grpc_asyncio.py b/owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/transports/grpc_asyncio.py deleted file mode 100644 index b6adab8ad..000000000 --- a/owl-bot-staging/v2/google/cloud/bigquery_v2/services/model_service/transports/grpc_asyncio.py +++ /dev/null @@ -1,336 +0,0 @@ -# -*- coding: utf-8 -*- -# Copyright 2020 Google LLC -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -# -import warnings -from typing import Awaitable, Callable, Dict, Optional, Sequence, Tuple, Union - -from google.api_core import gapic_v1 # type: ignore -from google.api_core import grpc_helpers_async # type: ignore -from google.auth import credentials as ga_credentials # type: ignore -from google.auth.transport.grpc import SslCredentials # type: ignore -import packaging.version - -import grpc # type: ignore -from grpc.experimental import aio # type: ignore - -from google.cloud.bigquery_v2.types import model -from google.cloud.bigquery_v2.types import model as gcb_model -from google.protobuf import empty_pb2 # type: ignore -from .base import ModelServiceTransport, DEFAULT_CLIENT_INFO -from .grpc import ModelServiceGrpcTransport - - -class ModelServiceGrpcAsyncIOTransport(ModelServiceTransport): - """gRPC AsyncIO backend transport for ModelService. - - This class defines the same methods as the primary client, so the - primary client can load the underlying transport implementation - and call it. - - It sends protocol buffers over the wire using gRPC (which is built on - top of HTTP/2); the ``grpcio`` package must be installed. - """ - - _grpc_channel: aio.Channel - _stubs: Dict[str, Callable] = {} - - @classmethod - def create_channel(cls, - host: str = 'bigquery.googleapis.com', - credentials: ga_credentials.Credentials = None, - credentials_file: Optional[str] = None, - scopes: Optional[Sequence[str]] = None, - quota_project_id: Optional[str] = None, - **kwargs) -> aio.Channel: - """Create and return a gRPC AsyncIO channel object. - Args: - host (Optional[str]): The host for the channel to use. - credentials (Optional[~.Credentials]): The - authorization credentials to attach to requests. These - credentials identify this application to the service. If - none are specified, the client will attempt to ascertain - the credentials from the environment. - credentials_file (Optional[str]): A file with credentials that can - be loaded with :func:`google.auth.load_credentials_from_file`. - This argument is ignored if ``channel`` is provided. - scopes (Optional[Sequence[str]]): A optional list of scopes needed for this - service. These are only used when credentials are not specified and - are passed to :func:`google.auth.default`. - quota_project_id (Optional[str]): An optional project to use for billing - and quota. - kwargs (Optional[dict]): Keyword arguments, which are passed to the - channel creation. - Returns: - aio.Channel: A gRPC AsyncIO channel object. - """ - - return grpc_helpers_async.create_channel( - host, - credentials=credentials, - credentials_file=credentials_file, - quota_project_id=quota_project_id, - default_scopes=cls.AUTH_SCOPES, - scopes=scopes, - default_host=cls.DEFAULT_HOST, - **kwargs - ) - - def __init__(self, *, - host: str = 'bigquery.googleapis.com', - credentials: ga_credentials.Credentials = None, - credentials_file: Optional[str] = None, - scopes: Optional[Sequence[str]] = None, - channel: aio.Channel = None, - api_mtls_endpoint: str = None, - client_cert_source: Callable[[], Tuple[bytes, bytes]] = None, - ssl_channel_credentials: grpc.ChannelCredentials = None, - client_cert_source_for_mtls: Callable[[], Tuple[bytes, bytes]] = None, - quota_project_id=None, - client_info: gapic_v1.client_info.ClientInfo = DEFAULT_CLIENT_INFO, - always_use_jwt_access: Optional[bool] = False, - ) -> None: - """Instantiate the transport. - - Args: - host (Optional[str]): - The hostname to connect to. - credentials (Optional[google.auth.credentials.Credentials]): The - authorization credentials to attach to requests. These - credentials identify the application to the service; if none - are specified, the client will attempt to ascertain the - credentials from the environment. - This argument is ignored if ``channel`` is provided. - credentials_file (Optional[str]): A file with credentials that can - be loaded with :func:`google.auth.load_credentials_from_file`. - This argument is ignored if ``channel`` is provided. - scopes (Optional[Sequence[str]]): A optional list of scopes needed for this - service. These are only used when credentials are not specified and - are passed to :func:`google.auth.default`. - channel (Optional[aio.Channel]): A ``Channel`` instance through - which to make calls. - api_mtls_endpoint (Optional[str]): Deprecated. The mutual TLS endpoint. - If provided, it overrides the ``host`` argument and tries to create - a mutual TLS channel with client SSL credentials from - ``client_cert_source`` or applicatin default SSL credentials. - client_cert_source (Optional[Callable[[], Tuple[bytes, bytes]]]): - Deprecated. A callback to provide client SSL certificate bytes and - private key bytes, both in PEM format. It is ignored if - ``api_mtls_endpoint`` is None. - ssl_channel_credentials (grpc.ChannelCredentials): SSL credentials - for grpc channel. It is ignored if ``channel`` is provided. - client_cert_source_for_mtls (Optional[Callable[[], Tuple[bytes, bytes]]]): - A callback to provide client certificate bytes and private key bytes, - both in PEM format. It is used to configure mutual TLS channel. It is - ignored if ``channel`` or ``ssl_channel_credentials`` is provided. - quota_project_id (Optional[str]): An optional project to use for billing - and quota. - client_info (google.api_core.gapic_v1.client_info.ClientInfo): - The client info used to send a user-agent string along with - API requests. If ``None``, then default info will be used. - Generally, you only need to set this if you're developing - your own client library. - always_use_jwt_access (Optional[bool]): Whether self signed JWT should - be used for service account credentials. - - Raises: - google.auth.exceptions.MutualTlsChannelError: If mutual TLS transport - creation failed for any reason. - google.api_core.exceptions.DuplicateCredentialArgs: If both ``credentials`` - and ``credentials_file`` are passed. - """ - self._grpc_channel = None - self._ssl_channel_credentials = ssl_channel_credentials - self._stubs: Dict[str, Callable] = {} - - if api_mtls_endpoint: - warnings.warn("api_mtls_endpoint is deprecated", DeprecationWarning) - if client_cert_source: - warnings.warn("client_cert_source is deprecated", DeprecationWarning) - - if channel: - # Ignore credentials if a channel was passed. - credentials = False - # If a channel was explicitly provided, set it. - self._grpc_channel = channel - self._ssl_channel_credentials = None - else: - if api_mtls_endpoint: - host = api_mtls_endpoint - - # Create SSL credentials with client_cert_source or application - # default SSL credentials. - if client_cert_source: - cert, key = client_cert_source() - self._ssl_channel_credentials = grpc.ssl_channel_credentials( - certificate_chain=cert, private_key=key - ) - else: - self._ssl_channel_credentials = SslCredentials().ssl_credentials - - else: - if client_cert_source_for_mtls and not ssl_channel_credentials: - cert, key = client_cert_source_for_mtls() - self._ssl_channel_credentials = grpc.ssl_channel_credentials( - certificate_chain=cert, private_key=key - ) - - # The base transport sets the host, credentials and scopes - super().__init__( - host=host, - credentials=credentials, - credentials_file=credentials_file, - scopes=scopes, - quota_project_id=quota_project_id, - client_info=client_info, - always_use_jwt_access=always_use_jwt_access, - ) - - if not self._grpc_channel: - self._grpc_channel = type(self).create_channel( - self._host, - credentials=self._credentials, - credentials_file=credentials_file, - scopes=self._scopes, - ssl_credentials=self._ssl_channel_credentials, - quota_project_id=quota_project_id, - options=[ - ("grpc.max_send_message_length", -1), - ("grpc.max_receive_message_length", -1), - ], - ) - - # Wrap messages. This must be done after self._grpc_channel exists - self._prep_wrapped_messages(client_info) - - @property - def grpc_channel(self) -> aio.Channel: - """Create the channel designed to connect to this service. - - This property caches on the instance; repeated calls return - the same channel. - """ - # Return the channel from cache. - return self._grpc_channel - - @property - def get_model(self) -> Callable[ - [model.GetModelRequest], - Awaitable[model.Model]]: - r"""Return a callable for the get model method over gRPC. - - Gets the specified model resource by model ID. - - Returns: - Callable[[~.GetModelRequest], - Awaitable[~.Model]]: - A function that, when called, will call the underlying RPC - on the server. - """ - # Generate a "stub function" on-the-fly which will actually make - # the request. - # gRPC handles serialization and deserialization, so we just need - # to pass in the functions for each. - if 'get_model' not in self._stubs: - self._stubs['get_model'] = self.grpc_channel.unary_unary( - '/google.cloud.bigquery.v2.ModelService/GetModel', - request_serializer=model.GetModelRequest.serialize, - response_deserializer=model.Model.deserialize, - ) - return self._stubs['get_model'] - - @property - def list_models(self) -> Callable[ - [model.ListModelsRequest], - Awaitable[model.ListModelsResponse]]: - r"""Return a callable for the list models method over gRPC. - - Lists all models in the specified dataset. Requires - the READER dataset role. - - Returns: - Callable[[~.ListModelsRequest], - Awaitable[~.ListModelsResponse]]: - A function that, when called, will call the underlying RPC - on the server. - """ - # Generate a "stub function" on-the-fly which will actually make - # the request. - # gRPC handles serialization and deserialization, so we just need - # to pass in the functions for each. - if 'list_models' not in self._stubs: - self._stubs['list_models'] = self.grpc_channel.unary_unary( - '/google.cloud.bigquery.v2.ModelService/ListModels', - request_serializer=model.ListModelsRequest.serialize, - response_deserializer=model.ListModelsResponse.deserialize, - ) - return self._stubs['list_models'] - - @property - def patch_model(self) -> Callable[ - [gcb_model.PatchModelRequest], - Awaitable[gcb_model.Model]]: - r"""Return a callable for the patch model method over gRPC. - - Patch specific fields in the specified model. - - Returns: - Callable[[~.PatchModelRequest], - Awaitable[~.Model]]: - A function that, when called, will call the underlying RPC - on the server. - """ - # Generate a "stub function" on-the-fly which will actually make - # the request. - # gRPC handles serialization and deserialization, so we just need - # to pass in the functions for each. - if 'patch_model' not in self._stubs: - self._stubs['patch_model'] = self.grpc_channel.unary_unary( - '/google.cloud.bigquery.v2.ModelService/PatchModel', - request_serializer=gcb_model.PatchModelRequest.serialize, - response_deserializer=gcb_model.Model.deserialize, - ) - return self._stubs['patch_model'] - - @property - def delete_model(self) -> Callable[ - [model.DeleteModelRequest], - Awaitable[empty_pb2.Empty]]: - r"""Return a callable for the delete model method over gRPC. - - Deletes the model specified by modelId from the - dataset. - - Returns: - Callable[[~.DeleteModelRequest], - Awaitable[~.Empty]]: - A function that, when called, will call the underlying RPC - on the server. - """ - # Generate a "stub function" on-the-fly which will actually make - # the request. - # gRPC handles serialization and deserialization, so we just need - # to pass in the functions for each. - if 'delete_model' not in self._stubs: - self._stubs['delete_model'] = self.grpc_channel.unary_unary( - '/google.cloud.bigquery.v2.ModelService/DeleteModel', - request_serializer=model.DeleteModelRequest.serialize, - response_deserializer=empty_pb2.Empty.FromString, - ) - return self._stubs['delete_model'] - - -__all__ = ( - 'ModelServiceGrpcAsyncIOTransport', -) diff --git a/owl-bot-staging/v2/google/cloud/bigquery_v2/types/__init__.py b/owl-bot-staging/v2/google/cloud/bigquery_v2/types/__init__.py deleted file mode 100644 index 36a5ff64d..000000000 --- a/owl-bot-staging/v2/google/cloud/bigquery_v2/types/__init__.py +++ /dev/null @@ -1,54 +0,0 @@ -# -*- coding: utf-8 -*- -# Copyright 2020 Google LLC -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -# -from .encryption_config import ( - EncryptionConfiguration, -) -from .model import ( - DeleteModelRequest, - GetModelRequest, - ListModelsRequest, - ListModelsResponse, - Model, - PatchModelRequest, -) -from .model_reference import ( - ModelReference, -) -from .standard_sql import ( - StandardSqlDataType, - StandardSqlField, - StandardSqlStructType, - StandardSqlTableType, -) -from .table_reference import ( - TableReference, -) - -__all__ = ( - 'EncryptionConfiguration', - 'DeleteModelRequest', - 'GetModelRequest', - 'ListModelsRequest', - 'ListModelsResponse', - 'Model', - 'PatchModelRequest', - 'ModelReference', - 'StandardSqlDataType', - 'StandardSqlField', - 'StandardSqlStructType', - 'StandardSqlTableType', - 'TableReference', -) diff --git a/owl-bot-staging/v2/google/cloud/bigquery_v2/types/encryption_config.py b/owl-bot-staging/v2/google/cloud/bigquery_v2/types/encryption_config.py deleted file mode 100644 index a1f60c1b9..000000000 --- a/owl-bot-staging/v2/google/cloud/bigquery_v2/types/encryption_config.py +++ /dev/null @@ -1,47 +0,0 @@ -# -*- coding: utf-8 -*- -# Copyright 2020 Google LLC -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -# -import proto # type: ignore - -from google.protobuf import wrappers_pb2 # type: ignore - - -__protobuf__ = proto.module( - package='google.cloud.bigquery.v2', - manifest={ - 'EncryptionConfiguration', - }, -) - - -class EncryptionConfiguration(proto.Message): - r""" - Attributes: - kms_key_name (google.protobuf.wrappers_pb2.StringValue): - Optional. Describes the Cloud KMS encryption - key that will be used to protect destination - BigQuery table. The BigQuery Service Account - associated with your project requires access to - this encryption key. - """ - - kms_key_name = proto.Field( - proto.MESSAGE, - number=1, - message=wrappers_pb2.StringValue, - ) - - -__all__ = tuple(sorted(__protobuf__.manifest)) diff --git a/owl-bot-staging/v2/google/cloud/bigquery_v2/types/model.py b/owl-bot-staging/v2/google/cloud/bigquery_v2/types/model.py deleted file mode 100644 index 70d8684b1..000000000 --- a/owl-bot-staging/v2/google/cloud/bigquery_v2/types/model.py +++ /dev/null @@ -1,1821 +0,0 @@ -# -*- coding: utf-8 -*- -# Copyright 2020 Google LLC -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -# -import proto # type: ignore - -from google.cloud.bigquery_v2.types import encryption_config -from google.cloud.bigquery_v2.types import model_reference as gcb_model_reference -from google.cloud.bigquery_v2.types import standard_sql -from google.cloud.bigquery_v2.types import table_reference -from google.protobuf import timestamp_pb2 # type: ignore -from google.protobuf import wrappers_pb2 # type: ignore - - -__protobuf__ = proto.module( - package='google.cloud.bigquery.v2', - manifest={ - 'Model', - 'GetModelRequest', - 'PatchModelRequest', - 'DeleteModelRequest', - 'ListModelsRequest', - 'ListModelsResponse', - }, -) - - -class Model(proto.Message): - r""" - Attributes: - etag (str): - Output only. A hash of this resource. - model_reference (google.cloud.bigquery_v2.types.ModelReference): - Required. Unique identifier for this model. - creation_time (int): - Output only. The time when this model was - created, in millisecs since the epoch. - last_modified_time (int): - Output only. The time when this model was - last modified, in millisecs since the epoch. - description (str): - Optional. A user-friendly description of this - model. - friendly_name (str): - Optional. A descriptive name for this model. - labels (Sequence[google.cloud.bigquery_v2.types.Model.LabelsEntry]): - The labels associated with this model. You - can use these to organize and group your models. - Label keys and values can be no longer than 63 - characters, can only contain lowercase letters, - numeric characters, underscores and dashes. - International characters are allowed. Label - values are optional. Label keys must start with - a letter and each label in the list must have a - different key. - expiration_time (int): - Optional. The time when this model expires, - in milliseconds since the epoch. If not present, - the model will persist indefinitely. Expired - models will be deleted and their storage - reclaimed. The defaultTableExpirationMs - property of the encapsulating dataset can be - used to set a default expirationTime on newly - created models. - location (str): - Output only. The geographic location where - the model resides. This value is inherited from - the dataset. - encryption_configuration (google.cloud.bigquery_v2.types.EncryptionConfiguration): - Custom encryption configuration (e.g., Cloud - KMS keys). This shows the encryption - configuration of the model data while stored in - BigQuery storage. This field can be used with - PatchModel to update encryption key for an - already encrypted model. - model_type (google.cloud.bigquery_v2.types.Model.ModelType): - Output only. Type of the model resource. - training_runs (Sequence[google.cloud.bigquery_v2.types.Model.TrainingRun]): - Output only. Information for all training runs in increasing - order of start_time. - feature_columns (Sequence[google.cloud.bigquery_v2.types.StandardSqlField]): - Output only. Input feature columns that were - used to train this model. - label_columns (Sequence[google.cloud.bigquery_v2.types.StandardSqlField]): - Output only. Label columns that were used to train this - model. The output of the model will have a "predicted_" - prefix to these columns. - """ - class ModelType(proto.Enum): - r"""Indicates the type of the Model.""" - MODEL_TYPE_UNSPECIFIED = 0 - LINEAR_REGRESSION = 1 - LOGISTIC_REGRESSION = 2 - KMEANS = 3 - MATRIX_FACTORIZATION = 4 - DNN_CLASSIFIER = 5 - TENSORFLOW = 6 - DNN_REGRESSOR = 7 - BOOSTED_TREE_REGRESSOR = 9 - BOOSTED_TREE_CLASSIFIER = 10 - ARIMA = 11 - AUTOML_REGRESSOR = 12 - AUTOML_CLASSIFIER = 13 - - class LossType(proto.Enum): - r"""Loss metric to evaluate model training performance.""" - LOSS_TYPE_UNSPECIFIED = 0 - MEAN_SQUARED_LOSS = 1 - MEAN_LOG_LOSS = 2 - - class DistanceType(proto.Enum): - r"""Distance metric used to compute the distance between two - points. - """ - DISTANCE_TYPE_UNSPECIFIED = 0 - EUCLIDEAN = 1 - COSINE = 2 - - class DataSplitMethod(proto.Enum): - r"""Indicates the method to split input data into multiple - tables. - """ - DATA_SPLIT_METHOD_UNSPECIFIED = 0 - RANDOM = 1 - CUSTOM = 2 - SEQUENTIAL = 3 - NO_SPLIT = 4 - AUTO_SPLIT = 5 - - class DataFrequency(proto.Enum): - r"""Type of supported data frequency for time series forecasting - models. - """ - DATA_FREQUENCY_UNSPECIFIED = 0 - AUTO_FREQUENCY = 1 - YEARLY = 2 - QUARTERLY = 3 - MONTHLY = 4 - WEEKLY = 5 - DAILY = 6 - HOURLY = 7 - - class HolidayRegion(proto.Enum): - r"""Type of supported holiday regions for time series forecasting - models. - """ - HOLIDAY_REGION_UNSPECIFIED = 0 - GLOBAL = 1 - NA = 2 - JAPAC = 3 - EMEA = 4 - LAC = 5 - AE = 6 - AR = 7 - AT = 8 - AU = 9 - BE = 10 - BR = 11 - CA = 12 - CH = 13 - CL = 14 - CN = 15 - CO = 16 - CS = 17 - CZ = 18 - DE = 19 - DK = 20 - DZ = 21 - EC = 22 - EE = 23 - EG = 24 - ES = 25 - FI = 26 - FR = 27 - GB = 28 - GR = 29 - HK = 30 - HU = 31 - ID = 32 - IE = 33 - IL = 34 - IN = 35 - IR = 36 - IT = 37 - JP = 38 - KR = 39 - LV = 40 - MA = 41 - MX = 42 - MY = 43 - NG = 44 - NL = 45 - NO = 46 - NZ = 47 - PE = 48 - PH = 49 - PK = 50 - PL = 51 - PT = 52 - RO = 53 - RS = 54 - RU = 55 - SA = 56 - SE = 57 - SG = 58 - SI = 59 - SK = 60 - TH = 61 - TR = 62 - TW = 63 - UA = 64 - US = 65 - VE = 66 - VN = 67 - ZA = 68 - - class LearnRateStrategy(proto.Enum): - r"""Indicates the learning rate optimization strategy to use.""" - LEARN_RATE_STRATEGY_UNSPECIFIED = 0 - LINE_SEARCH = 1 - CONSTANT = 2 - - class OptimizationStrategy(proto.Enum): - r"""Indicates the optimization strategy used for training.""" - OPTIMIZATION_STRATEGY_UNSPECIFIED = 0 - BATCH_GRADIENT_DESCENT = 1 - NORMAL_EQUATION = 2 - - class FeedbackType(proto.Enum): - r"""Indicates the training algorithm to use for matrix - factorization models. - """ - FEEDBACK_TYPE_UNSPECIFIED = 0 - IMPLICIT = 1 - EXPLICIT = 2 - - class SeasonalPeriod(proto.Message): - r""" """ - class SeasonalPeriodType(proto.Enum): - r"""""" - SEASONAL_PERIOD_TYPE_UNSPECIFIED = 0 - NO_SEASONALITY = 1 - DAILY = 2 - WEEKLY = 3 - MONTHLY = 4 - QUARTERLY = 5 - YEARLY = 6 - - class KmeansEnums(proto.Message): - r""" """ - class KmeansInitializationMethod(proto.Enum): - r"""Indicates the method used to initialize the centroids for - KMeans clustering algorithm. - """ - KMEANS_INITIALIZATION_METHOD_UNSPECIFIED = 0 - RANDOM = 1 - CUSTOM = 2 - KMEANS_PLUS_PLUS = 3 - - class RegressionMetrics(proto.Message): - r"""Evaluation metrics for regression and explicit feedback type - matrix factorization models. - - Attributes: - mean_absolute_error (google.protobuf.wrappers_pb2.DoubleValue): - Mean absolute error. - mean_squared_error (google.protobuf.wrappers_pb2.DoubleValue): - Mean squared error. - mean_squared_log_error (google.protobuf.wrappers_pb2.DoubleValue): - Mean squared log error. - median_absolute_error (google.protobuf.wrappers_pb2.DoubleValue): - Median absolute error. - r_squared (google.protobuf.wrappers_pb2.DoubleValue): - R^2 score. - """ - - mean_absolute_error = proto.Field( - proto.MESSAGE, - number=1, - message=wrappers_pb2.DoubleValue, - ) - mean_squared_error = proto.Field( - proto.MESSAGE, - number=2, - message=wrappers_pb2.DoubleValue, - ) - mean_squared_log_error = proto.Field( - proto.MESSAGE, - number=3, - message=wrappers_pb2.DoubleValue, - ) - median_absolute_error = proto.Field( - proto.MESSAGE, - number=4, - message=wrappers_pb2.DoubleValue, - ) - r_squared = proto.Field( - proto.MESSAGE, - number=5, - message=wrappers_pb2.DoubleValue, - ) - - class AggregateClassificationMetrics(proto.Message): - r"""Aggregate metrics for classification/classifier models. For - multi-class models, the metrics are either macro-averaged or - micro-averaged. When macro-averaged, the metrics are calculated - for each label and then an unweighted average is taken of those - values. When micro-averaged, the metric is calculated globally - by counting the total number of correctly predicted rows. - - Attributes: - precision (google.protobuf.wrappers_pb2.DoubleValue): - Precision is the fraction of actual positive - predictions that had positive actual labels. For - multiclass this is a macro-averaged metric - treating each class as a binary classifier. - recall (google.protobuf.wrappers_pb2.DoubleValue): - Recall is the fraction of actual positive - labels that were given a positive prediction. - For multiclass this is a macro-averaged metric. - accuracy (google.protobuf.wrappers_pb2.DoubleValue): - Accuracy is the fraction of predictions given - the correct label. For multiclass this is a - micro-averaged metric. - threshold (google.protobuf.wrappers_pb2.DoubleValue): - Threshold at which the metrics are computed. - For binary classification models this is the - positive class threshold. For multi-class - classfication models this is the confidence - threshold. - f1_score (google.protobuf.wrappers_pb2.DoubleValue): - The F1 score is an average of recall and - precision. For multiclass this is a macro- - averaged metric. - log_loss (google.protobuf.wrappers_pb2.DoubleValue): - Logarithmic Loss. For multiclass this is a - macro-averaged metric. - roc_auc (google.protobuf.wrappers_pb2.DoubleValue): - Area Under a ROC Curve. For multiclass this - is a macro-averaged metric. - """ - - precision = proto.Field( - proto.MESSAGE, - number=1, - message=wrappers_pb2.DoubleValue, - ) - recall = proto.Field( - proto.MESSAGE, - number=2, - message=wrappers_pb2.DoubleValue, - ) - accuracy = proto.Field( - proto.MESSAGE, - number=3, - message=wrappers_pb2.DoubleValue, - ) - threshold = proto.Field( - proto.MESSAGE, - number=4, - message=wrappers_pb2.DoubleValue, - ) - f1_score = proto.Field( - proto.MESSAGE, - number=5, - message=wrappers_pb2.DoubleValue, - ) - log_loss = proto.Field( - proto.MESSAGE, - number=6, - message=wrappers_pb2.DoubleValue, - ) - roc_auc = proto.Field( - proto.MESSAGE, - number=7, - message=wrappers_pb2.DoubleValue, - ) - - class BinaryClassificationMetrics(proto.Message): - r"""Evaluation metrics for binary classification/classifier - models. - - Attributes: - aggregate_classification_metrics (google.cloud.bigquery_v2.types.Model.AggregateClassificationMetrics): - Aggregate classification metrics. - binary_confusion_matrix_list (Sequence[google.cloud.bigquery_v2.types.Model.BinaryClassificationMetrics.BinaryConfusionMatrix]): - Binary confusion matrix at multiple - thresholds. - positive_label (str): - Label representing the positive class. - negative_label (str): - Label representing the negative class. - """ - - class BinaryConfusionMatrix(proto.Message): - r"""Confusion matrix for binary classification models. - Attributes: - positive_class_threshold (google.protobuf.wrappers_pb2.DoubleValue): - Threshold value used when computing each of - the following metric. - true_positives (google.protobuf.wrappers_pb2.Int64Value): - Number of true samples predicted as true. - false_positives (google.protobuf.wrappers_pb2.Int64Value): - Number of false samples predicted as true. - true_negatives (google.protobuf.wrappers_pb2.Int64Value): - Number of true samples predicted as false. - false_negatives (google.protobuf.wrappers_pb2.Int64Value): - Number of false samples predicted as false. - precision (google.protobuf.wrappers_pb2.DoubleValue): - The fraction of actual positive predictions - that had positive actual labels. - recall (google.protobuf.wrappers_pb2.DoubleValue): - The fraction of actual positive labels that - were given a positive prediction. - f1_score (google.protobuf.wrappers_pb2.DoubleValue): - The equally weighted average of recall and - precision. - accuracy (google.protobuf.wrappers_pb2.DoubleValue): - The fraction of predictions given the correct - label. - """ - - positive_class_threshold = proto.Field( - proto.MESSAGE, - number=1, - message=wrappers_pb2.DoubleValue, - ) - true_positives = proto.Field( - proto.MESSAGE, - number=2, - message=wrappers_pb2.Int64Value, - ) - false_positives = proto.Field( - proto.MESSAGE, - number=3, - message=wrappers_pb2.Int64Value, - ) - true_negatives = proto.Field( - proto.MESSAGE, - number=4, - message=wrappers_pb2.Int64Value, - ) - false_negatives = proto.Field( - proto.MESSAGE, - number=5, - message=wrappers_pb2.Int64Value, - ) - precision = proto.Field( - proto.MESSAGE, - number=6, - message=wrappers_pb2.DoubleValue, - ) - recall = proto.Field( - proto.MESSAGE, - number=7, - message=wrappers_pb2.DoubleValue, - ) - f1_score = proto.Field( - proto.MESSAGE, - number=8, - message=wrappers_pb2.DoubleValue, - ) - accuracy = proto.Field( - proto.MESSAGE, - number=9, - message=wrappers_pb2.DoubleValue, - ) - - aggregate_classification_metrics = proto.Field( - proto.MESSAGE, - number=1, - message='Model.AggregateClassificationMetrics', - ) - binary_confusion_matrix_list = proto.RepeatedField( - proto.MESSAGE, - number=2, - message='Model.BinaryClassificationMetrics.BinaryConfusionMatrix', - ) - positive_label = proto.Field( - proto.STRING, - number=3, - ) - negative_label = proto.Field( - proto.STRING, - number=4, - ) - - class MultiClassClassificationMetrics(proto.Message): - r"""Evaluation metrics for multi-class classification/classifier - models. - - Attributes: - aggregate_classification_metrics (google.cloud.bigquery_v2.types.Model.AggregateClassificationMetrics): - Aggregate classification metrics. - confusion_matrix_list (Sequence[google.cloud.bigquery_v2.types.Model.MultiClassClassificationMetrics.ConfusionMatrix]): - Confusion matrix at different thresholds. - """ - - class ConfusionMatrix(proto.Message): - r"""Confusion matrix for multi-class classification models. - Attributes: - confidence_threshold (google.protobuf.wrappers_pb2.DoubleValue): - Confidence threshold used when computing the - entries of the confusion matrix. - rows (Sequence[google.cloud.bigquery_v2.types.Model.MultiClassClassificationMetrics.ConfusionMatrix.Row]): - One row per actual label. - """ - - class Entry(proto.Message): - r"""A single entry in the confusion matrix. - Attributes: - predicted_label (str): - The predicted label. For confidence_threshold > 0, we will - also add an entry indicating the number of items under the - confidence threshold. - item_count (google.protobuf.wrappers_pb2.Int64Value): - Number of items being predicted as this - label. - """ - - predicted_label = proto.Field( - proto.STRING, - number=1, - ) - item_count = proto.Field( - proto.MESSAGE, - number=2, - message=wrappers_pb2.Int64Value, - ) - - class Row(proto.Message): - r"""A single row in the confusion matrix. - Attributes: - actual_label (str): - The original label of this row. - entries (Sequence[google.cloud.bigquery_v2.types.Model.MultiClassClassificationMetrics.ConfusionMatrix.Entry]): - Info describing predicted label distribution. - """ - - actual_label = proto.Field( - proto.STRING, - number=1, - ) - entries = proto.RepeatedField( - proto.MESSAGE, - number=2, - message='Model.MultiClassClassificationMetrics.ConfusionMatrix.Entry', - ) - - confidence_threshold = proto.Field( - proto.MESSAGE, - number=1, - message=wrappers_pb2.DoubleValue, - ) - rows = proto.RepeatedField( - proto.MESSAGE, - number=2, - message='Model.MultiClassClassificationMetrics.ConfusionMatrix.Row', - ) - - aggregate_classification_metrics = proto.Field( - proto.MESSAGE, - number=1, - message='Model.AggregateClassificationMetrics', - ) - confusion_matrix_list = proto.RepeatedField( - proto.MESSAGE, - number=2, - message='Model.MultiClassClassificationMetrics.ConfusionMatrix', - ) - - class ClusteringMetrics(proto.Message): - r"""Evaluation metrics for clustering models. - Attributes: - davies_bouldin_index (google.protobuf.wrappers_pb2.DoubleValue): - Davies-Bouldin index. - mean_squared_distance (google.protobuf.wrappers_pb2.DoubleValue): - Mean of squared distances between each sample - to its cluster centroid. - clusters (Sequence[google.cloud.bigquery_v2.types.Model.ClusteringMetrics.Cluster]): - [Beta] Information for all clusters. - """ - - class Cluster(proto.Message): - r"""Message containing the information about one cluster. - Attributes: - centroid_id (int): - Centroid id. - feature_values (Sequence[google.cloud.bigquery_v2.types.Model.ClusteringMetrics.Cluster.FeatureValue]): - Values of highly variant features for this - cluster. - count (google.protobuf.wrappers_pb2.Int64Value): - Count of training data rows that were - assigned to this cluster. - """ - - class FeatureValue(proto.Message): - r"""Representative value of a single feature within the cluster. - Attributes: - feature_column (str): - The feature column name. - numerical_value (google.protobuf.wrappers_pb2.DoubleValue): - The numerical feature value. This is the - centroid value for this feature. - categorical_value (google.cloud.bigquery_v2.types.Model.ClusteringMetrics.Cluster.FeatureValue.CategoricalValue): - The categorical feature value. - """ - - class CategoricalValue(proto.Message): - r"""Representative value of a categorical feature. - Attributes: - category_counts (Sequence[google.cloud.bigquery_v2.types.Model.ClusteringMetrics.Cluster.FeatureValue.CategoricalValue.CategoryCount]): - Counts of all categories for the categorical feature. If - there are more than ten categories, we return top ten (by - count) and return one more CategoryCount with category - "*OTHER*" and count as aggregate counts of remaining - categories. - """ - - class CategoryCount(proto.Message): - r"""Represents the count of a single category within the cluster. - Attributes: - category (str): - The name of category. - count (google.protobuf.wrappers_pb2.Int64Value): - The count of training samples matching the - category within the cluster. - """ - - category = proto.Field( - proto.STRING, - number=1, - ) - count = proto.Field( - proto.MESSAGE, - number=2, - message=wrappers_pb2.Int64Value, - ) - - category_counts = proto.RepeatedField( - proto.MESSAGE, - number=1, - message='Model.ClusteringMetrics.Cluster.FeatureValue.CategoricalValue.CategoryCount', - ) - - feature_column = proto.Field( - proto.STRING, - number=1, - ) - numerical_value = proto.Field( - proto.MESSAGE, - number=2, - oneof='value', - message=wrappers_pb2.DoubleValue, - ) - categorical_value = proto.Field( - proto.MESSAGE, - number=3, - oneof='value', - message='Model.ClusteringMetrics.Cluster.FeatureValue.CategoricalValue', - ) - - centroid_id = proto.Field( - proto.INT64, - number=1, - ) - feature_values = proto.RepeatedField( - proto.MESSAGE, - number=2, - message='Model.ClusteringMetrics.Cluster.FeatureValue', - ) - count = proto.Field( - proto.MESSAGE, - number=3, - message=wrappers_pb2.Int64Value, - ) - - davies_bouldin_index = proto.Field( - proto.MESSAGE, - number=1, - message=wrappers_pb2.DoubleValue, - ) - mean_squared_distance = proto.Field( - proto.MESSAGE, - number=2, - message=wrappers_pb2.DoubleValue, - ) - clusters = proto.RepeatedField( - proto.MESSAGE, - number=3, - message='Model.ClusteringMetrics.Cluster', - ) - - class RankingMetrics(proto.Message): - r"""Evaluation metrics used by weighted-ALS models specified by - feedback_type=implicit. - - Attributes: - mean_average_precision (google.protobuf.wrappers_pb2.DoubleValue): - Calculates a precision per user for all the - items by ranking them and then averages all the - precisions across all the users. - mean_squared_error (google.protobuf.wrappers_pb2.DoubleValue): - Similar to the mean squared error computed in - regression and explicit recommendation models - except instead of computing the rating directly, - the output from evaluate is computed against a - preference which is 1 or 0 depending on if the - rating exists or not. - normalized_discounted_cumulative_gain (google.protobuf.wrappers_pb2.DoubleValue): - A metric to determine the goodness of a - ranking calculated from the predicted confidence - by comparing it to an ideal rank measured by the - original ratings. - average_rank (google.protobuf.wrappers_pb2.DoubleValue): - Determines the goodness of a ranking by - computing the percentile rank from the predicted - confidence and dividing it by the original rank. - """ - - mean_average_precision = proto.Field( - proto.MESSAGE, - number=1, - message=wrappers_pb2.DoubleValue, - ) - mean_squared_error = proto.Field( - proto.MESSAGE, - number=2, - message=wrappers_pb2.DoubleValue, - ) - normalized_discounted_cumulative_gain = proto.Field( - proto.MESSAGE, - number=3, - message=wrappers_pb2.DoubleValue, - ) - average_rank = proto.Field( - proto.MESSAGE, - number=4, - message=wrappers_pb2.DoubleValue, - ) - - class ArimaForecastingMetrics(proto.Message): - r"""Model evaluation metrics for ARIMA forecasting models. - Attributes: - non_seasonal_order (Sequence[google.cloud.bigquery_v2.types.Model.ArimaOrder]): - Non-seasonal order. - arima_fitting_metrics (Sequence[google.cloud.bigquery_v2.types.Model.ArimaFittingMetrics]): - Arima model fitting metrics. - seasonal_periods (Sequence[google.cloud.bigquery_v2.types.Model.SeasonalPeriod.SeasonalPeriodType]): - Seasonal periods. Repeated because multiple - periods are supported for one time series. - has_drift (Sequence[bool]): - Whether Arima model fitted with drift or not. - It is always false when d is not 1. - time_series_id (Sequence[str]): - Id to differentiate different time series for - the large-scale case. - arima_single_model_forecasting_metrics (Sequence[google.cloud.bigquery_v2.types.Model.ArimaForecastingMetrics.ArimaSingleModelForecastingMetrics]): - Repeated as there can be many metric sets - (one for each model) in auto-arima and the - large-scale case. - """ - - class ArimaSingleModelForecastingMetrics(proto.Message): - r"""Model evaluation metrics for a single ARIMA forecasting - model. - - Attributes: - non_seasonal_order (google.cloud.bigquery_v2.types.Model.ArimaOrder): - Non-seasonal order. - arima_fitting_metrics (google.cloud.bigquery_v2.types.Model.ArimaFittingMetrics): - Arima fitting metrics. - has_drift (bool): - Is arima model fitted with drift or not. It - is always false when d is not 1. - time_series_id (str): - The id to indicate different time series. - seasonal_periods (Sequence[google.cloud.bigquery_v2.types.Model.SeasonalPeriod.SeasonalPeriodType]): - Seasonal periods. Repeated because multiple - periods are supported for one time series. - """ - - non_seasonal_order = proto.Field( - proto.MESSAGE, - number=1, - message='Model.ArimaOrder', - ) - arima_fitting_metrics = proto.Field( - proto.MESSAGE, - number=2, - message='Model.ArimaFittingMetrics', - ) - has_drift = proto.Field( - proto.BOOL, - number=3, - ) - time_series_id = proto.Field( - proto.STRING, - number=4, - ) - seasonal_periods = proto.RepeatedField( - proto.ENUM, - number=5, - enum='Model.SeasonalPeriod.SeasonalPeriodType', - ) - - non_seasonal_order = proto.RepeatedField( - proto.MESSAGE, - number=1, - message='Model.ArimaOrder', - ) - arima_fitting_metrics = proto.RepeatedField( - proto.MESSAGE, - number=2, - message='Model.ArimaFittingMetrics', - ) - seasonal_periods = proto.RepeatedField( - proto.ENUM, - number=3, - enum='Model.SeasonalPeriod.SeasonalPeriodType', - ) - has_drift = proto.RepeatedField( - proto.BOOL, - number=4, - ) - time_series_id = proto.RepeatedField( - proto.STRING, - number=5, - ) - arima_single_model_forecasting_metrics = proto.RepeatedField( - proto.MESSAGE, - number=6, - message='Model.ArimaForecastingMetrics.ArimaSingleModelForecastingMetrics', - ) - - class EvaluationMetrics(proto.Message): - r"""Evaluation metrics of a model. These are either computed on - all training data or just the eval data based on whether eval - data was used during training. These are not present for - imported models. - - Attributes: - regression_metrics (google.cloud.bigquery_v2.types.Model.RegressionMetrics): - Populated for regression models and explicit - feedback type matrix factorization models. - binary_classification_metrics (google.cloud.bigquery_v2.types.Model.BinaryClassificationMetrics): - Populated for binary - classification/classifier models. - multi_class_classification_metrics (google.cloud.bigquery_v2.types.Model.MultiClassClassificationMetrics): - Populated for multi-class - classification/classifier models. - clustering_metrics (google.cloud.bigquery_v2.types.Model.ClusteringMetrics): - Populated for clustering models. - ranking_metrics (google.cloud.bigquery_v2.types.Model.RankingMetrics): - Populated for implicit feedback type matrix - factorization models. - arima_forecasting_metrics (google.cloud.bigquery_v2.types.Model.ArimaForecastingMetrics): - Populated for ARIMA models. - """ - - regression_metrics = proto.Field( - proto.MESSAGE, - number=1, - oneof='metrics', - message='Model.RegressionMetrics', - ) - binary_classification_metrics = proto.Field( - proto.MESSAGE, - number=2, - oneof='metrics', - message='Model.BinaryClassificationMetrics', - ) - multi_class_classification_metrics = proto.Field( - proto.MESSAGE, - number=3, - oneof='metrics', - message='Model.MultiClassClassificationMetrics', - ) - clustering_metrics = proto.Field( - proto.MESSAGE, - number=4, - oneof='metrics', - message='Model.ClusteringMetrics', - ) - ranking_metrics = proto.Field( - proto.MESSAGE, - number=5, - oneof='metrics', - message='Model.RankingMetrics', - ) - arima_forecasting_metrics = proto.Field( - proto.MESSAGE, - number=6, - oneof='metrics', - message='Model.ArimaForecastingMetrics', - ) - - class DataSplitResult(proto.Message): - r"""Data split result. This contains references to the training - and evaluation data tables that were used to train the model. - - Attributes: - training_table (google.cloud.bigquery_v2.types.TableReference): - Table reference of the training data after - split. - evaluation_table (google.cloud.bigquery_v2.types.TableReference): - Table reference of the evaluation data after - split. - """ - - training_table = proto.Field( - proto.MESSAGE, - number=1, - message=table_reference.TableReference, - ) - evaluation_table = proto.Field( - proto.MESSAGE, - number=2, - message=table_reference.TableReference, - ) - - class ArimaOrder(proto.Message): - r"""Arima order, can be used for both non-seasonal and seasonal - parts. - - Attributes: - p (int): - Order of the autoregressive part. - d (int): - Order of the differencing part. - q (int): - Order of the moving-average part. - """ - - p = proto.Field( - proto.INT64, - number=1, - ) - d = proto.Field( - proto.INT64, - number=2, - ) - q = proto.Field( - proto.INT64, - number=3, - ) - - class ArimaFittingMetrics(proto.Message): - r"""ARIMA model fitting metrics. - Attributes: - log_likelihood (float): - Log-likelihood. - aic (float): - AIC. - variance (float): - Variance. - """ - - log_likelihood = proto.Field( - proto.DOUBLE, - number=1, - ) - aic = proto.Field( - proto.DOUBLE, - number=2, - ) - variance = proto.Field( - proto.DOUBLE, - number=3, - ) - - class GlobalExplanation(proto.Message): - r"""Global explanations containing the top most important - features after training. - - Attributes: - explanations (Sequence[google.cloud.bigquery_v2.types.Model.GlobalExplanation.Explanation]): - A list of the top global explanations. Sorted - by absolute value of attribution in descending - order. - class_label (str): - Class label for this set of global - explanations. Will be empty/null for binary - logistic and linear regression models. Sorted - alphabetically in descending order. - """ - - class Explanation(proto.Message): - r"""Explanation for a single feature. - Attributes: - feature_name (str): - Full name of the feature. For non-numerical features, will - be formatted like .. - Overall size of feature name will always be truncated to - first 120 characters. - attribution (google.protobuf.wrappers_pb2.DoubleValue): - Attribution of feature. - """ - - feature_name = proto.Field( - proto.STRING, - number=1, - ) - attribution = proto.Field( - proto.MESSAGE, - number=2, - message=wrappers_pb2.DoubleValue, - ) - - explanations = proto.RepeatedField( - proto.MESSAGE, - number=1, - message='Model.GlobalExplanation.Explanation', - ) - class_label = proto.Field( - proto.STRING, - number=2, - ) - - class TrainingRun(proto.Message): - r"""Information about a single training query run for the model. - Attributes: - training_options (google.cloud.bigquery_v2.types.Model.TrainingRun.TrainingOptions): - Options that were used for this training run, - includes user specified and default options that - were used. - start_time (google.protobuf.timestamp_pb2.Timestamp): - The start time of this training run. - results (Sequence[google.cloud.bigquery_v2.types.Model.TrainingRun.IterationResult]): - Output of each iteration run, results.size() <= - max_iterations. - evaluation_metrics (google.cloud.bigquery_v2.types.Model.EvaluationMetrics): - The evaluation metrics over training/eval - data that were computed at the end of training. - data_split_result (google.cloud.bigquery_v2.types.Model.DataSplitResult): - Data split result of the training run. Only - set when the input data is actually split. - global_explanations (Sequence[google.cloud.bigquery_v2.types.Model.GlobalExplanation]): - Global explanations for important features of - the model. For multi-class models, there is one - entry for each label class. For other models, - there is only one entry in the list. - """ - - class TrainingOptions(proto.Message): - r""" - Attributes: - max_iterations (int): - The maximum number of iterations in training. - Used only for iterative training algorithms. - loss_type (google.cloud.bigquery_v2.types.Model.LossType): - Type of loss function used during training - run. - learn_rate (float): - Learning rate in training. Used only for - iterative training algorithms. - l1_regularization (google.protobuf.wrappers_pb2.DoubleValue): - L1 regularization coefficient. - l2_regularization (google.protobuf.wrappers_pb2.DoubleValue): - L2 regularization coefficient. - min_relative_progress (google.protobuf.wrappers_pb2.DoubleValue): - When early_stop is true, stops training when accuracy - improvement is less than 'min_relative_progress'. Used only - for iterative training algorithms. - warm_start (google.protobuf.wrappers_pb2.BoolValue): - Whether to train a model from the last - checkpoint. - early_stop (google.protobuf.wrappers_pb2.BoolValue): - Whether to stop early when the loss doesn't improve - significantly any more (compared to min_relative_progress). - Used only for iterative training algorithms. - input_label_columns (Sequence[str]): - Name of input label columns in training data. - data_split_method (google.cloud.bigquery_v2.types.Model.DataSplitMethod): - The data split type for training and - evaluation, e.g. RANDOM. - data_split_eval_fraction (float): - The fraction of evaluation data over the - whole input data. The rest of data will be used - as training data. The format should be double. - Accurate to two decimal places. - Default value is 0.2. - data_split_column (str): - The column to split data with. This column won't be used as - a feature. - - 1. When data_split_method is CUSTOM, the corresponding - column should be boolean. The rows with true value tag - are eval data, and the false are training data. - 2. When data_split_method is SEQ, the first - DATA_SPLIT_EVAL_FRACTION rows (from smallest to largest) - in the corresponding column are used as training data, - and the rest are eval data. It respects the order in - Orderable data types: - https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types#data-type-properties - learn_rate_strategy (google.cloud.bigquery_v2.types.Model.LearnRateStrategy): - The strategy to determine learn rate for the - current iteration. - initial_learn_rate (float): - Specifies the initial learning rate for the - line search learn rate strategy. - label_class_weights (Sequence[google.cloud.bigquery_v2.types.Model.TrainingRun.TrainingOptions.LabelClassWeightsEntry]): - Weights associated with each label class, for - rebalancing the training data. Only applicable - for classification models. - user_column (str): - User column specified for matrix - factorization models. - item_column (str): - Item column specified for matrix - factorization models. - distance_type (google.cloud.bigquery_v2.types.Model.DistanceType): - Distance type for clustering models. - num_clusters (int): - Number of clusters for clustering models. - model_uri (str): - [Beta] Google Cloud Storage URI from which the model was - imported. Only applicable for imported models. - optimization_strategy (google.cloud.bigquery_v2.types.Model.OptimizationStrategy): - Optimization strategy for training linear - regression models. - hidden_units (Sequence[int]): - Hidden units for dnn models. - batch_size (int): - Batch size for dnn models. - dropout (google.protobuf.wrappers_pb2.DoubleValue): - Dropout probability for dnn models. - max_tree_depth (int): - Maximum depth of a tree for boosted tree - models. - subsample (float): - Subsample fraction of the training data to - grow tree to prevent overfitting for boosted - tree models. - min_split_loss (google.protobuf.wrappers_pb2.DoubleValue): - Minimum split loss for boosted tree models. - num_factors (int): - Num factors specified for matrix - factorization models. - feedback_type (google.cloud.bigquery_v2.types.Model.FeedbackType): - Feedback type that specifies which algorithm - to run for matrix factorization. - wals_alpha (google.protobuf.wrappers_pb2.DoubleValue): - Hyperparameter for matrix factoration when - implicit feedback type is specified. - kmeans_initialization_method (google.cloud.bigquery_v2.types.Model.KmeansEnums.KmeansInitializationMethod): - The method used to initialize the centroids - for kmeans algorithm. - kmeans_initialization_column (str): - The column used to provide the initial centroids for kmeans - algorithm when kmeans_initialization_method is CUSTOM. - time_series_timestamp_column (str): - Column to be designated as time series - timestamp for ARIMA model. - time_series_data_column (str): - Column to be designated as time series data - for ARIMA model. - auto_arima (bool): - Whether to enable auto ARIMA or not. - non_seasonal_order (google.cloud.bigquery_v2.types.Model.ArimaOrder): - A specification of the non-seasonal part of - the ARIMA model: the three components (p, d, q) - are the AR order, the degree of differencing, - and the MA order. - data_frequency (google.cloud.bigquery_v2.types.Model.DataFrequency): - The data frequency of a time series. - include_drift (bool): - Include drift when fitting an ARIMA model. - holiday_region (google.cloud.bigquery_v2.types.Model.HolidayRegion): - The geographical region based on which the - holidays are considered in time series modeling. - If a valid value is specified, then holiday - effects modeling is enabled. - time_series_id_column (str): - The id column that will be used to indicate - different time series to forecast in parallel. - horizon (int): - The number of periods ahead that need to be - forecasted. - preserve_input_structs (bool): - Whether to preserve the input structs in output feature - names. Suppose there is a struct A with field b. When false - (default), the output feature name is A_b. When true, the - output feature name is A.b. - auto_arima_max_order (int): - The max value of non-seasonal p and q. - """ - - max_iterations = proto.Field( - proto.INT64, - number=1, - ) - loss_type = proto.Field( - proto.ENUM, - number=2, - enum='Model.LossType', - ) - learn_rate = proto.Field( - proto.DOUBLE, - number=3, - ) - l1_regularization = proto.Field( - proto.MESSAGE, - number=4, - message=wrappers_pb2.DoubleValue, - ) - l2_regularization = proto.Field( - proto.MESSAGE, - number=5, - message=wrappers_pb2.DoubleValue, - ) - min_relative_progress = proto.Field( - proto.MESSAGE, - number=6, - message=wrappers_pb2.DoubleValue, - ) - warm_start = proto.Field( - proto.MESSAGE, - number=7, - message=wrappers_pb2.BoolValue, - ) - early_stop = proto.Field( - proto.MESSAGE, - number=8, - message=wrappers_pb2.BoolValue, - ) - input_label_columns = proto.RepeatedField( - proto.STRING, - number=9, - ) - data_split_method = proto.Field( - proto.ENUM, - number=10, - enum='Model.DataSplitMethod', - ) - data_split_eval_fraction = proto.Field( - proto.DOUBLE, - number=11, - ) - data_split_column = proto.Field( - proto.STRING, - number=12, - ) - learn_rate_strategy = proto.Field( - proto.ENUM, - number=13, - enum='Model.LearnRateStrategy', - ) - initial_learn_rate = proto.Field( - proto.DOUBLE, - number=16, - ) - label_class_weights = proto.MapField( - proto.STRING, - proto.DOUBLE, - number=17, - ) - user_column = proto.Field( - proto.STRING, - number=18, - ) - item_column = proto.Field( - proto.STRING, - number=19, - ) - distance_type = proto.Field( - proto.ENUM, - number=20, - enum='Model.DistanceType', - ) - num_clusters = proto.Field( - proto.INT64, - number=21, - ) - model_uri = proto.Field( - proto.STRING, - number=22, - ) - optimization_strategy = proto.Field( - proto.ENUM, - number=23, - enum='Model.OptimizationStrategy', - ) - hidden_units = proto.RepeatedField( - proto.INT64, - number=24, - ) - batch_size = proto.Field( - proto.INT64, - number=25, - ) - dropout = proto.Field( - proto.MESSAGE, - number=26, - message=wrappers_pb2.DoubleValue, - ) - max_tree_depth = proto.Field( - proto.INT64, - number=27, - ) - subsample = proto.Field( - proto.DOUBLE, - number=28, - ) - min_split_loss = proto.Field( - proto.MESSAGE, - number=29, - message=wrappers_pb2.DoubleValue, - ) - num_factors = proto.Field( - proto.INT64, - number=30, - ) - feedback_type = proto.Field( - proto.ENUM, - number=31, - enum='Model.FeedbackType', - ) - wals_alpha = proto.Field( - proto.MESSAGE, - number=32, - message=wrappers_pb2.DoubleValue, - ) - kmeans_initialization_method = proto.Field( - proto.ENUM, - number=33, - enum='Model.KmeansEnums.KmeansInitializationMethod', - ) - kmeans_initialization_column = proto.Field( - proto.STRING, - number=34, - ) - time_series_timestamp_column = proto.Field( - proto.STRING, - number=35, - ) - time_series_data_column = proto.Field( - proto.STRING, - number=36, - ) - auto_arima = proto.Field( - proto.BOOL, - number=37, - ) - non_seasonal_order = proto.Field( - proto.MESSAGE, - number=38, - message='Model.ArimaOrder', - ) - data_frequency = proto.Field( - proto.ENUM, - number=39, - enum='Model.DataFrequency', - ) - include_drift = proto.Field( - proto.BOOL, - number=41, - ) - holiday_region = proto.Field( - proto.ENUM, - number=42, - enum='Model.HolidayRegion', - ) - time_series_id_column = proto.Field( - proto.STRING, - number=43, - ) - horizon = proto.Field( - proto.INT64, - number=44, - ) - preserve_input_structs = proto.Field( - proto.BOOL, - number=45, - ) - auto_arima_max_order = proto.Field( - proto.INT64, - number=46, - ) - - class IterationResult(proto.Message): - r"""Information about a single iteration of the training run. - Attributes: - index (google.protobuf.wrappers_pb2.Int32Value): - Index of the iteration, 0 based. - duration_ms (google.protobuf.wrappers_pb2.Int64Value): - Time taken to run the iteration in - milliseconds. - training_loss (google.protobuf.wrappers_pb2.DoubleValue): - Loss computed on the training data at the end - of iteration. - eval_loss (google.protobuf.wrappers_pb2.DoubleValue): - Loss computed on the eval data at the end of - iteration. - learn_rate (float): - Learn rate used for this iteration. - cluster_infos (Sequence[google.cloud.bigquery_v2.types.Model.TrainingRun.IterationResult.ClusterInfo]): - Information about top clusters for clustering - models. - arima_result (google.cloud.bigquery_v2.types.Model.TrainingRun.IterationResult.ArimaResult): - - """ - - class ClusterInfo(proto.Message): - r"""Information about a single cluster for clustering model. - Attributes: - centroid_id (int): - Centroid id. - cluster_radius (google.protobuf.wrappers_pb2.DoubleValue): - Cluster radius, the average distance from - centroid to each point assigned to the cluster. - cluster_size (google.protobuf.wrappers_pb2.Int64Value): - Cluster size, the total number of points - assigned to the cluster. - """ - - centroid_id = proto.Field( - proto.INT64, - number=1, - ) - cluster_radius = proto.Field( - proto.MESSAGE, - number=2, - message=wrappers_pb2.DoubleValue, - ) - cluster_size = proto.Field( - proto.MESSAGE, - number=3, - message=wrappers_pb2.Int64Value, - ) - - class ArimaResult(proto.Message): - r"""(Auto-)arima fitting result. Wrap everything in ArimaResult - for easier refactoring if we want to use model-specific - iteration results. - - Attributes: - arima_model_info (Sequence[google.cloud.bigquery_v2.types.Model.TrainingRun.IterationResult.ArimaResult.ArimaModelInfo]): - This message is repeated because there are - multiple arima models fitted in auto-arima. For - non-auto-arima model, its size is one. - seasonal_periods (Sequence[google.cloud.bigquery_v2.types.Model.SeasonalPeriod.SeasonalPeriodType]): - Seasonal periods. Repeated because multiple - periods are supported for one time series. - """ - - class ArimaCoefficients(proto.Message): - r"""Arima coefficients. - Attributes: - auto_regressive_coefficients (Sequence[float]): - Auto-regressive coefficients, an array of - double. - moving_average_coefficients (Sequence[float]): - Moving-average coefficients, an array of - double. - intercept_coefficient (float): - Intercept coefficient, just a double not an - array. - """ - - auto_regressive_coefficients = proto.RepeatedField( - proto.DOUBLE, - number=1, - ) - moving_average_coefficients = proto.RepeatedField( - proto.DOUBLE, - number=2, - ) - intercept_coefficient = proto.Field( - proto.DOUBLE, - number=3, - ) - - class ArimaModelInfo(proto.Message): - r"""Arima model information. - Attributes: - non_seasonal_order (google.cloud.bigquery_v2.types.Model.ArimaOrder): - Non-seasonal order. - arima_coefficients (google.cloud.bigquery_v2.types.Model.TrainingRun.IterationResult.ArimaResult.ArimaCoefficients): - Arima coefficients. - arima_fitting_metrics (google.cloud.bigquery_v2.types.Model.ArimaFittingMetrics): - Arima fitting metrics. - has_drift (bool): - Whether Arima model fitted with drift or not. - It is always false when d is not 1. - time_series_id (str): - The id to indicate different time series. - seasonal_periods (Sequence[google.cloud.bigquery_v2.types.Model.SeasonalPeriod.SeasonalPeriodType]): - Seasonal periods. Repeated because multiple - periods are supported for one time series. - """ - - non_seasonal_order = proto.Field( - proto.MESSAGE, - number=1, - message='Model.ArimaOrder', - ) - arima_coefficients = proto.Field( - proto.MESSAGE, - number=2, - message='Model.TrainingRun.IterationResult.ArimaResult.ArimaCoefficients', - ) - arima_fitting_metrics = proto.Field( - proto.MESSAGE, - number=3, - message='Model.ArimaFittingMetrics', - ) - has_drift = proto.Field( - proto.BOOL, - number=4, - ) - time_series_id = proto.Field( - proto.STRING, - number=5, - ) - seasonal_periods = proto.RepeatedField( - proto.ENUM, - number=6, - enum='Model.SeasonalPeriod.SeasonalPeriodType', - ) - - arima_model_info = proto.RepeatedField( - proto.MESSAGE, - number=1, - message='Model.TrainingRun.IterationResult.ArimaResult.ArimaModelInfo', - ) - seasonal_periods = proto.RepeatedField( - proto.ENUM, - number=2, - enum='Model.SeasonalPeriod.SeasonalPeriodType', - ) - - index = proto.Field( - proto.MESSAGE, - number=1, - message=wrappers_pb2.Int32Value, - ) - duration_ms = proto.Field( - proto.MESSAGE, - number=4, - message=wrappers_pb2.Int64Value, - ) - training_loss = proto.Field( - proto.MESSAGE, - number=5, - message=wrappers_pb2.DoubleValue, - ) - eval_loss = proto.Field( - proto.MESSAGE, - number=6, - message=wrappers_pb2.DoubleValue, - ) - learn_rate = proto.Field( - proto.DOUBLE, - number=7, - ) - cluster_infos = proto.RepeatedField( - proto.MESSAGE, - number=8, - message='Model.TrainingRun.IterationResult.ClusterInfo', - ) - arima_result = proto.Field( - proto.MESSAGE, - number=9, - message='Model.TrainingRun.IterationResult.ArimaResult', - ) - - training_options = proto.Field( - proto.MESSAGE, - number=1, - message='Model.TrainingRun.TrainingOptions', - ) - start_time = proto.Field( - proto.MESSAGE, - number=8, - message=timestamp_pb2.Timestamp, - ) - results = proto.RepeatedField( - proto.MESSAGE, - number=6, - message='Model.TrainingRun.IterationResult', - ) - evaluation_metrics = proto.Field( - proto.MESSAGE, - number=7, - message='Model.EvaluationMetrics', - ) - data_split_result = proto.Field( - proto.MESSAGE, - number=9, - message='Model.DataSplitResult', - ) - global_explanations = proto.RepeatedField( - proto.MESSAGE, - number=10, - message='Model.GlobalExplanation', - ) - - etag = proto.Field( - proto.STRING, - number=1, - ) - model_reference = proto.Field( - proto.MESSAGE, - number=2, - message=gcb_model_reference.ModelReference, - ) - creation_time = proto.Field( - proto.INT64, - number=5, - ) - last_modified_time = proto.Field( - proto.INT64, - number=6, - ) - description = proto.Field( - proto.STRING, - number=12, - ) - friendly_name = proto.Field( - proto.STRING, - number=14, - ) - labels = proto.MapField( - proto.STRING, - proto.STRING, - number=15, - ) - expiration_time = proto.Field( - proto.INT64, - number=16, - ) - location = proto.Field( - proto.STRING, - number=13, - ) - encryption_configuration = proto.Field( - proto.MESSAGE, - number=17, - message=encryption_config.EncryptionConfiguration, - ) - model_type = proto.Field( - proto.ENUM, - number=7, - enum=ModelType, - ) - training_runs = proto.RepeatedField( - proto.MESSAGE, - number=9, - message=TrainingRun, - ) - feature_columns = proto.RepeatedField( - proto.MESSAGE, - number=10, - message=standard_sql.StandardSqlField, - ) - label_columns = proto.RepeatedField( - proto.MESSAGE, - number=11, - message=standard_sql.StandardSqlField, - ) - - -class GetModelRequest(proto.Message): - r""" - Attributes: - project_id (str): - Required. Project ID of the requested model. - dataset_id (str): - Required. Dataset ID of the requested model. - model_id (str): - Required. Model ID of the requested model. - """ - - project_id = proto.Field( - proto.STRING, - number=1, - ) - dataset_id = proto.Field( - proto.STRING, - number=2, - ) - model_id = proto.Field( - proto.STRING, - number=3, - ) - - -class PatchModelRequest(proto.Message): - r""" - Attributes: - project_id (str): - Required. Project ID of the model to patch. - dataset_id (str): - Required. Dataset ID of the model to patch. - model_id (str): - Required. Model ID of the model to patch. - model (google.cloud.bigquery_v2.types.Model): - Required. Patched model. - Follows RFC5789 patch semantics. Missing fields - are not updated. To clear a field, explicitly - set to default value. - """ - - project_id = proto.Field( - proto.STRING, - number=1, - ) - dataset_id = proto.Field( - proto.STRING, - number=2, - ) - model_id = proto.Field( - proto.STRING, - number=3, - ) - model = proto.Field( - proto.MESSAGE, - number=4, - message='Model', - ) - - -class DeleteModelRequest(proto.Message): - r""" - Attributes: - project_id (str): - Required. Project ID of the model to delete. - dataset_id (str): - Required. Dataset ID of the model to delete. - model_id (str): - Required. Model ID of the model to delete. - """ - - project_id = proto.Field( - proto.STRING, - number=1, - ) - dataset_id = proto.Field( - proto.STRING, - number=2, - ) - model_id = proto.Field( - proto.STRING, - number=3, - ) - - -class ListModelsRequest(proto.Message): - r""" - Attributes: - project_id (str): - Required. Project ID of the models to list. - dataset_id (str): - Required. Dataset ID of the models to list. - max_results (google.protobuf.wrappers_pb2.UInt32Value): - The maximum number of results to return in a - single response page. Leverage the page tokens - to iterate through the entire collection. - page_token (str): - Page token, returned by a previous call to - request the next page of results - """ - - project_id = proto.Field( - proto.STRING, - number=1, - ) - dataset_id = proto.Field( - proto.STRING, - number=2, - ) - max_results = proto.Field( - proto.MESSAGE, - number=3, - message=wrappers_pb2.UInt32Value, - ) - page_token = proto.Field( - proto.STRING, - number=4, - ) - - -class ListModelsResponse(proto.Message): - r""" - Attributes: - models (Sequence[google.cloud.bigquery_v2.types.Model]): - Models in the requested dataset. Only the following fields - are populated: model_reference, model_type, creation_time, - last_modified_time and labels. - next_page_token (str): - A token to request the next page of results. - """ - - @property - def raw_page(self): - return self - - models = proto.RepeatedField( - proto.MESSAGE, - number=1, - message='Model', - ) - next_page_token = proto.Field( - proto.STRING, - number=2, - ) - - -__all__ = tuple(sorted(__protobuf__.manifest)) diff --git a/owl-bot-staging/v2/google/cloud/bigquery_v2/types/model_reference.py b/owl-bot-staging/v2/google/cloud/bigquery_v2/types/model_reference.py deleted file mode 100644 index 7dfe7b30f..000000000 --- a/owl-bot-staging/v2/google/cloud/bigquery_v2/types/model_reference.py +++ /dev/null @@ -1,56 +0,0 @@ -# -*- coding: utf-8 -*- -# Copyright 2020 Google LLC -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -# -import proto # type: ignore - - -__protobuf__ = proto.module( - package='google.cloud.bigquery.v2', - manifest={ - 'ModelReference', - }, -) - - -class ModelReference(proto.Message): - r"""Id path of a model. - Attributes: - project_id (str): - Required. The ID of the project containing - this model. - dataset_id (str): - Required. The ID of the dataset containing - this model. - model_id (str): - Required. The ID of the model. The ID must contain only - letters (a-z, A-Z), numbers (0-9), or underscores (_). The - maximum length is 1,024 characters. - """ - - project_id = proto.Field( - proto.STRING, - number=1, - ) - dataset_id = proto.Field( - proto.STRING, - number=2, - ) - model_id = proto.Field( - proto.STRING, - number=3, - ) - - -__all__ = tuple(sorted(__protobuf__.manifest)) diff --git a/owl-bot-staging/v2/google/cloud/bigquery_v2/types/standard_sql.py b/owl-bot-staging/v2/google/cloud/bigquery_v2/types/standard_sql.py deleted file mode 100644 index dfe315e35..000000000 --- a/owl-bot-staging/v2/google/cloud/bigquery_v2/types/standard_sql.py +++ /dev/null @@ -1,141 +0,0 @@ -# -*- coding: utf-8 -*- -# Copyright 2020 Google LLC -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -# -import proto # type: ignore - - -__protobuf__ = proto.module( - package='google.cloud.bigquery.v2', - manifest={ - 'StandardSqlDataType', - 'StandardSqlField', - 'StandardSqlStructType', - 'StandardSqlTableType', - }, -) - - -class StandardSqlDataType(proto.Message): - r"""The type of a variable, e.g., a function argument. Examples: INT64: - {type_kind="INT64"} ARRAY: {type_kind="ARRAY", - array_element_type="STRING"} STRUCT: - {type_kind="STRUCT", struct_type={fields=[ {name="x", - type={type_kind="STRING"}}, {name="y", type={type_kind="ARRAY", - array_element_type="DATE"}} ]}} - - Attributes: - type_kind (google.cloud.bigquery_v2.types.StandardSqlDataType.TypeKind): - Required. The top level type of this field. - Can be any standard SQL data type (e.g., - "INT64", "DATE", "ARRAY"). - array_element_type (google.cloud.bigquery_v2.types.StandardSqlDataType): - The type of the array's elements, if type_kind = "ARRAY". - struct_type (google.cloud.bigquery_v2.types.StandardSqlStructType): - The fields of this struct, in order, if type_kind = - "STRUCT". - """ - class TypeKind(proto.Enum): - r"""""" - TYPE_KIND_UNSPECIFIED = 0 - INT64 = 2 - BOOL = 5 - FLOAT64 = 7 - STRING = 8 - BYTES = 9 - TIMESTAMP = 19 - DATE = 10 - TIME = 20 - DATETIME = 21 - INTERVAL = 26 - GEOGRAPHY = 22 - NUMERIC = 23 - BIGNUMERIC = 24 - JSON = 25 - ARRAY = 16 - STRUCT = 17 - - type_kind = proto.Field( - proto.ENUM, - number=1, - enum=TypeKind, - ) - array_element_type = proto.Field( - proto.MESSAGE, - number=2, - oneof='sub_type', - message='StandardSqlDataType', - ) - struct_type = proto.Field( - proto.MESSAGE, - number=3, - oneof='sub_type', - message='StandardSqlStructType', - ) - - -class StandardSqlField(proto.Message): - r"""A field or a column. - Attributes: - name (str): - Optional. The name of this field. Can be - absent for struct fields. - type_ (google.cloud.bigquery_v2.types.StandardSqlDataType): - Optional. The type of this parameter. Absent - if not explicitly specified (e.g., CREATE - FUNCTION statement can omit the return type; in - this case the output parameter does not have - this "type" field). - """ - - name = proto.Field( - proto.STRING, - number=1, - ) - type_ = proto.Field( - proto.MESSAGE, - number=2, - message='StandardSqlDataType', - ) - - -class StandardSqlStructType(proto.Message): - r""" - Attributes: - fields (Sequence[google.cloud.bigquery_v2.types.StandardSqlField]): - - """ - - fields = proto.RepeatedField( - proto.MESSAGE, - number=1, - message='StandardSqlField', - ) - - -class StandardSqlTableType(proto.Message): - r"""A table type - Attributes: - columns (Sequence[google.cloud.bigquery_v2.types.StandardSqlField]): - The columns in this table type - """ - - columns = proto.RepeatedField( - proto.MESSAGE, - number=1, - message='StandardSqlField', - ) - - -__all__ = tuple(sorted(__protobuf__.manifest)) diff --git a/owl-bot-staging/v2/google/cloud/bigquery_v2/types/table_reference.py b/owl-bot-staging/v2/google/cloud/bigquery_v2/types/table_reference.py deleted file mode 100644 index 2e6a37202..000000000 --- a/owl-bot-staging/v2/google/cloud/bigquery_v2/types/table_reference.py +++ /dev/null @@ -1,58 +0,0 @@ -# -*- coding: utf-8 -*- -# Copyright 2020 Google LLC -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -# -import proto # type: ignore - - -__protobuf__ = proto.module( - package='google.cloud.bigquery.v2', - manifest={ - 'TableReference', - }, -) - - -class TableReference(proto.Message): - r""" - Attributes: - project_id (str): - Required. The ID of the project containing - this table. - dataset_id (str): - Required. The ID of the dataset containing - this table. - table_id (str): - Required. The ID of the table. The ID must contain only - letters (a-z, A-Z), numbers (0-9), or underscores (_). The - maximum length is 1,024 characters. Certain operations allow - suffixing of the table ID with a partition decorator, such - as ``sample_table$20190123``. - """ - - project_id = proto.Field( - proto.STRING, - number=1, - ) - dataset_id = proto.Field( - proto.STRING, - number=2, - ) - table_id = proto.Field( - proto.STRING, - number=3, - ) - - -__all__ = tuple(sorted(__protobuf__.manifest)) diff --git a/owl-bot-staging/v2/mypy.ini b/owl-bot-staging/v2/mypy.ini deleted file mode 100644 index 4505b4854..000000000 --- a/owl-bot-staging/v2/mypy.ini +++ /dev/null @@ -1,3 +0,0 @@ -[mypy] -python_version = 3.6 -namespace_packages = True diff --git a/owl-bot-staging/v2/noxfile.py b/owl-bot-staging/v2/noxfile.py deleted file mode 100644 index fa6a0142d..000000000 --- a/owl-bot-staging/v2/noxfile.py +++ /dev/null @@ -1,132 +0,0 @@ -# -*- coding: utf-8 -*- -# Copyright 2020 Google LLC -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -# -import os -import pathlib -import shutil -import subprocess -import sys - - -import nox # type: ignore - -CURRENT_DIRECTORY = pathlib.Path(__file__).parent.absolute() - -LOWER_BOUND_CONSTRAINTS_FILE = CURRENT_DIRECTORY / "constraints.txt" -PACKAGE_NAME = subprocess.check_output([sys.executable, "setup.py", "--name"], encoding="utf-8") - - -nox.sessions = [ - "unit", - "cover", - "mypy", - "check_lower_bounds" - # exclude update_lower_bounds from default - "docs", -] - -@nox.session(python=['3.6', '3.7', '3.8', '3.9']) -def unit(session): - """Run the unit test suite.""" - - session.install('coverage', 'pytest', 'pytest-cov', 'asyncmock', 'pytest-asyncio') - session.install('-e', '.') - - session.run( - 'py.test', - '--quiet', - '--cov=google/cloud/bigquery_v2/', - '--cov-config=.coveragerc', - '--cov-report=term', - '--cov-report=html', - os.path.join('tests', 'unit', ''.join(session.posargs)) - ) - - -@nox.session(python='3.7') -def cover(session): - """Run the final coverage report. - This outputs the coverage report aggregating coverage from the unit - test runs (not system test runs), and then erases coverage data. - """ - session.install("coverage", "pytest-cov") - session.run("coverage", "report", "--show-missing", "--fail-under=100") - - session.run("coverage", "erase") - - -@nox.session(python=['3.6', '3.7']) -def mypy(session): - """Run the type checker.""" - session.install('mypy', 'types-pkg_resources') - session.install('.') - session.run( - 'mypy', - '--explicit-package-bases', - 'google', - ) - - -@nox.session -def update_lower_bounds(session): - """Update lower bounds in constraints.txt to match setup.py""" - session.install('google-cloud-testutils') - session.install('.') - - session.run( - 'lower-bound-checker', - 'update', - '--package-name', - PACKAGE_NAME, - '--constraints-file', - str(LOWER_BOUND_CONSTRAINTS_FILE), - ) - - -@nox.session -def check_lower_bounds(session): - """Check lower bounds in setup.py are reflected in constraints file""" - session.install('google-cloud-testutils') - session.install('.') - - session.run( - 'lower-bound-checker', - 'check', - '--package-name', - PACKAGE_NAME, - '--constraints-file', - str(LOWER_BOUND_CONSTRAINTS_FILE), - ) - -@nox.session(python='3.6') -def docs(session): - """Build the docs for this library.""" - - session.install("-e", ".") - session.install("sphinx<3.0.0", "alabaster", "recommonmark") - - shutil.rmtree(os.path.join("docs", "_build"), ignore_errors=True) - session.run( - "sphinx-build", - "-W", # warnings as errors - "-T", # show full traceback on exception - "-N", # no colors - "-b", - "html", - "-d", - os.path.join("docs", "_build", "doctrees", ""), - os.path.join("docs", ""), - os.path.join("docs", "_build", "html", ""), - ) diff --git a/owl-bot-staging/v2/scripts/fixup_bigquery_v2_keywords.py b/owl-bot-staging/v2/scripts/fixup_bigquery_v2_keywords.py deleted file mode 100644 index b1bdb7647..000000000 --- a/owl-bot-staging/v2/scripts/fixup_bigquery_v2_keywords.py +++ /dev/null @@ -1,179 +0,0 @@ -#! /usr/bin/env python3 -# -*- coding: utf-8 -*- -# Copyright 2020 Google LLC -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -# -import argparse -import os -import libcst as cst -import pathlib -import sys -from typing import (Any, Callable, Dict, List, Sequence, Tuple) - - -def partition( - predicate: Callable[[Any], bool], - iterator: Sequence[Any] -) -> Tuple[List[Any], List[Any]]: - """A stable, out-of-place partition.""" - results = ([], []) - - for i in iterator: - results[int(predicate(i))].append(i) - - # Returns trueList, falseList - return results[1], results[0] - - -class bigqueryCallTransformer(cst.CSTTransformer): - CTRL_PARAMS: Tuple[str] = ('retry', 'timeout', 'metadata') - METHOD_TO_PARAMS: Dict[str, Tuple[str]] = { - 'delete_model': ('project_id', 'dataset_id', 'model_id', ), - 'get_model': ('project_id', 'dataset_id', 'model_id', ), - 'list_models': ('project_id', 'dataset_id', 'max_results', 'page_token', ), - 'patch_model': ('project_id', 'dataset_id', 'model_id', 'model', ), - } - - def leave_Call(self, original: cst.Call, updated: cst.Call) -> cst.CSTNode: - try: - key = original.func.attr.value - kword_params = self.METHOD_TO_PARAMS[key] - except (AttributeError, KeyError): - # Either not a method from the API or too convoluted to be sure. - return updated - - # If the existing code is valid, keyword args come after positional args. - # Therefore, all positional args must map to the first parameters. - args, kwargs = partition(lambda a: not bool(a.keyword), updated.args) - if any(k.keyword.value == "request" for k in kwargs): - # We've already fixed this file, don't fix it again. - return updated - - kwargs, ctrl_kwargs = partition( - lambda a: not a.keyword.value in self.CTRL_PARAMS, - kwargs - ) - - args, ctrl_args = args[:len(kword_params)], args[len(kword_params):] - ctrl_kwargs.extend(cst.Arg(value=a.value, keyword=cst.Name(value=ctrl)) - for a, ctrl in zip(ctrl_args, self.CTRL_PARAMS)) - - request_arg = cst.Arg( - value=cst.Dict([ - cst.DictElement( - cst.SimpleString("'{}'".format(name)), -cst.Element(value=arg.value) - ) - # Note: the args + kwargs looks silly, but keep in mind that - # the control parameters had to be stripped out, and that - # those could have been passed positionally or by keyword. - for name, arg in zip(kword_params, args + kwargs)]), - keyword=cst.Name("request") - ) - - return updated.with_changes( - args=[request_arg] + ctrl_kwargs - ) - - -def fix_files( - in_dir: pathlib.Path, - out_dir: pathlib.Path, - *, - transformer=bigqueryCallTransformer(), -): - """Duplicate the input dir to the output dir, fixing file method calls. - - Preconditions: - * in_dir is a real directory - * out_dir is a real, empty directory - """ - pyfile_gen = ( - pathlib.Path(os.path.join(root, f)) - for root, _, files in os.walk(in_dir) - for f in files if os.path.splitext(f)[1] == ".py" - ) - - for fpath in pyfile_gen: - with open(fpath, 'r') as f: - src = f.read() - - # Parse the code and insert method call fixes. - tree = cst.parse_module(src) - updated = tree.visit(transformer) - - # Create the path and directory structure for the new file. - updated_path = out_dir.joinpath(fpath.relative_to(in_dir)) - updated_path.parent.mkdir(parents=True, exist_ok=True) - - # Generate the updated source file at the corresponding path. - with open(updated_path, 'w') as f: - f.write(updated.code) - - -if __name__ == '__main__': - parser = argparse.ArgumentParser( - description="""Fix up source that uses the bigquery client library. - -The existing sources are NOT overwritten but are copied to output_dir with changes made. - -Note: This tool operates at a best-effort level at converting positional - parameters in client method calls to keyword based parameters. - Cases where it WILL FAIL include - A) * or ** expansion in a method call. - B) Calls via function or method alias (includes free function calls) - C) Indirect or dispatched calls (e.g. the method is looked up dynamically) - - These all constitute false negatives. The tool will also detect false - positives when an API method shares a name with another method. -""") - parser.add_argument( - '-d', - '--input-directory', - required=True, - dest='input_dir', - help='the input directory to walk for python files to fix up', - ) - parser.add_argument( - '-o', - '--output-directory', - required=True, - dest='output_dir', - help='the directory to output files fixed via un-flattening', - ) - args = parser.parse_args() - input_dir = pathlib.Path(args.input_dir) - output_dir = pathlib.Path(args.output_dir) - if not input_dir.is_dir(): - print( - f"input directory '{input_dir}' does not exist or is not a directory", - file=sys.stderr, - ) - sys.exit(-1) - - if not output_dir.is_dir(): - print( - f"output directory '{output_dir}' does not exist or is not a directory", - file=sys.stderr, - ) - sys.exit(-1) - - if os.listdir(output_dir): - print( - f"output directory '{output_dir}' is not empty", - file=sys.stderr, - ) - sys.exit(-1) - - fix_files(input_dir, output_dir) diff --git a/owl-bot-staging/v2/setup.py b/owl-bot-staging/v2/setup.py deleted file mode 100644 index e26921308..000000000 --- a/owl-bot-staging/v2/setup.py +++ /dev/null @@ -1,53 +0,0 @@ -# -*- coding: utf-8 -*- -# Copyright 2020 Google LLC -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -# -import io -import os -import setuptools # type: ignore - -version = '0.1.0' - -package_root = os.path.abspath(os.path.dirname(__file__)) - -readme_filename = os.path.join(package_root, 'README.rst') -with io.open(readme_filename, encoding='utf-8') as readme_file: - readme = readme_file.read() - -setuptools.setup( - name='google-cloud-bigquery', - version=version, - long_description=readme, - packages=setuptools.PEP420PackageFinder.find(), - namespace_packages=('google', 'google.cloud'), - platforms='Posix; MacOS X; Windows', - include_package_data=True, - install_requires=( - 'google-api-core[grpc] >= 1.27.0, < 2.0.0dev', - 'libcst >= 0.2.5', - 'proto-plus >= 1.15.0', - 'packaging >= 14.3', ), - python_requires='>=3.6', - classifiers=[ - 'Development Status :: 3 - Alpha', - 'Intended Audience :: Developers', - 'Operating System :: OS Independent', - 'Programming Language :: Python :: 3.6', - 'Programming Language :: Python :: 3.7', - 'Programming Language :: Python :: 3.8', - 'Topic :: Internet', - 'Topic :: Software Development :: Libraries :: Python Modules', - ], - zip_safe=False, -) diff --git a/owl-bot-staging/v2/tests/__init__.py b/owl-bot-staging/v2/tests/__init__.py deleted file mode 100644 index b54a5fcc4..000000000 --- a/owl-bot-staging/v2/tests/__init__.py +++ /dev/null @@ -1,16 +0,0 @@ - -# -*- coding: utf-8 -*- -# Copyright 2020 Google LLC -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -# diff --git a/owl-bot-staging/v2/tests/unit/__init__.py b/owl-bot-staging/v2/tests/unit/__init__.py deleted file mode 100644 index b54a5fcc4..000000000 --- a/owl-bot-staging/v2/tests/unit/__init__.py +++ /dev/null @@ -1,16 +0,0 @@ - -# -*- coding: utf-8 -*- -# Copyright 2020 Google LLC -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -# diff --git a/owl-bot-staging/v2/tests/unit/gapic/__init__.py b/owl-bot-staging/v2/tests/unit/gapic/__init__.py deleted file mode 100644 index b54a5fcc4..000000000 --- a/owl-bot-staging/v2/tests/unit/gapic/__init__.py +++ /dev/null @@ -1,16 +0,0 @@ - -# -*- coding: utf-8 -*- -# Copyright 2020 Google LLC -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -# diff --git a/owl-bot-staging/v2/tests/unit/gapic/bigquery_v2/__init__.py b/owl-bot-staging/v2/tests/unit/gapic/bigquery_v2/__init__.py deleted file mode 100644 index b54a5fcc4..000000000 --- a/owl-bot-staging/v2/tests/unit/gapic/bigquery_v2/__init__.py +++ /dev/null @@ -1,16 +0,0 @@ - -# -*- coding: utf-8 -*- -# Copyright 2020 Google LLC -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -# diff --git a/owl-bot-staging/v2/tests/unit/gapic/bigquery_v2/test_model_service.py b/owl-bot-staging/v2/tests/unit/gapic/bigquery_v2/test_model_service.py deleted file mode 100644 index 32ebcc9a4..000000000 --- a/owl-bot-staging/v2/tests/unit/gapic/bigquery_v2/test_model_service.py +++ /dev/null @@ -1,1712 +0,0 @@ -# -*- coding: utf-8 -*- -# Copyright 2020 Google LLC -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -# -import os -import mock -import packaging.version - -import grpc -from grpc.experimental import aio -import math -import pytest -from proto.marshal.rules.dates import DurationRule, TimestampRule - - -from google.api_core import client_options -from google.api_core import exceptions as core_exceptions -from google.api_core import gapic_v1 -from google.api_core import grpc_helpers -from google.api_core import grpc_helpers_async -from google.auth import credentials as ga_credentials -from google.auth.exceptions import MutualTLSChannelError -from google.cloud.bigquery_v2.services.model_service import ModelServiceAsyncClient -from google.cloud.bigquery_v2.services.model_service import ModelServiceClient -from google.cloud.bigquery_v2.services.model_service import transports -from google.cloud.bigquery_v2.services.model_service.transports.base import _GOOGLE_AUTH_VERSION -from google.cloud.bigquery_v2.types import encryption_config -from google.cloud.bigquery_v2.types import model -from google.cloud.bigquery_v2.types import model as gcb_model -from google.cloud.bigquery_v2.types import model_reference -from google.cloud.bigquery_v2.types import standard_sql -from google.cloud.bigquery_v2.types import table_reference -from google.oauth2 import service_account -from google.protobuf import timestamp_pb2 # type: ignore -from google.protobuf import wrappers_pb2 # type: ignore -import google.auth - - -# TODO(busunkim): Once google-auth >= 1.25.0 is required transitively -# through google-api-core: -# - Delete the auth "less than" test cases -# - Delete these pytest markers (Make the "greater than or equal to" tests the default). -requires_google_auth_lt_1_25_0 = pytest.mark.skipif( - packaging.version.parse(_GOOGLE_AUTH_VERSION) >= packaging.version.parse("1.25.0"), - reason="This test requires google-auth < 1.25.0", -) -requires_google_auth_gte_1_25_0 = pytest.mark.skipif( - packaging.version.parse(_GOOGLE_AUTH_VERSION) < packaging.version.parse("1.25.0"), - reason="This test requires google-auth >= 1.25.0", -) - -def client_cert_source_callback(): - return b"cert bytes", b"key bytes" - - -# If default endpoint is localhost, then default mtls endpoint will be the same. -# This method modifies the default endpoint so the client can produce a different -# mtls endpoint for endpoint testing purposes. -def modify_default_endpoint(client): - return "foo.googleapis.com" if ("localhost" in client.DEFAULT_ENDPOINT) else client.DEFAULT_ENDPOINT - - -def test__get_default_mtls_endpoint(): - api_endpoint = "example.googleapis.com" - api_mtls_endpoint = "example.mtls.googleapis.com" - sandbox_endpoint = "example.sandbox.googleapis.com" - sandbox_mtls_endpoint = "example.mtls.sandbox.googleapis.com" - non_googleapi = "api.example.com" - - assert ModelServiceClient._get_default_mtls_endpoint(None) is None - assert ModelServiceClient._get_default_mtls_endpoint(api_endpoint) == api_mtls_endpoint - assert ModelServiceClient._get_default_mtls_endpoint(api_mtls_endpoint) == api_mtls_endpoint - assert ModelServiceClient._get_default_mtls_endpoint(sandbox_endpoint) == sandbox_mtls_endpoint - assert ModelServiceClient._get_default_mtls_endpoint(sandbox_mtls_endpoint) == sandbox_mtls_endpoint - assert ModelServiceClient._get_default_mtls_endpoint(non_googleapi) == non_googleapi - - -@pytest.mark.parametrize("client_class", [ - ModelServiceClient, - ModelServiceAsyncClient, -]) -def test_model_service_client_from_service_account_info(client_class): - creds = ga_credentials.AnonymousCredentials() - with mock.patch.object(service_account.Credentials, 'from_service_account_info') as factory: - factory.return_value = creds - info = {"valid": True} - client = client_class.from_service_account_info(info) - assert client.transport._credentials == creds - assert isinstance(client, client_class) - - assert client.transport._host == 'bigquery.googleapis.com:443' - - -@pytest.mark.parametrize("client_class", [ - ModelServiceClient, - ModelServiceAsyncClient, -]) -def test_model_service_client_service_account_always_use_jwt(client_class): - with mock.patch.object(service_account.Credentials, 'with_always_use_jwt_access', create=True) as use_jwt: - creds = service_account.Credentials(None, None, None) - client = client_class(credentials=creds) - use_jwt.assert_not_called() - - -@pytest.mark.parametrize("transport_class,transport_name", [ - (transports.ModelServiceGrpcTransport, "grpc"), - (transports.ModelServiceGrpcAsyncIOTransport, "grpc_asyncio"), -]) -def test_model_service_client_service_account_always_use_jwt_true(transport_class, transport_name): - with mock.patch.object(service_account.Credentials, 'with_always_use_jwt_access', create=True) as use_jwt: - creds = service_account.Credentials(None, None, None) - transport = transport_class(credentials=creds, always_use_jwt_access=True) - use_jwt.assert_called_once_with(True) - - -@pytest.mark.parametrize("client_class", [ - ModelServiceClient, - ModelServiceAsyncClient, -]) -def test_model_service_client_from_service_account_file(client_class): - creds = ga_credentials.AnonymousCredentials() - with mock.patch.object(service_account.Credentials, 'from_service_account_file') as factory: - factory.return_value = creds - client = client_class.from_service_account_file("dummy/file/path.json") - assert client.transport._credentials == creds - assert isinstance(client, client_class) - - client = client_class.from_service_account_json("dummy/file/path.json") - assert client.transport._credentials == creds - assert isinstance(client, client_class) - - assert client.transport._host == 'bigquery.googleapis.com:443' - - -def test_model_service_client_get_transport_class(): - transport = ModelServiceClient.get_transport_class() - available_transports = [ - transports.ModelServiceGrpcTransport, - ] - assert transport in available_transports - - transport = ModelServiceClient.get_transport_class("grpc") - assert transport == transports.ModelServiceGrpcTransport - - -@pytest.mark.parametrize("client_class,transport_class,transport_name", [ - (ModelServiceClient, transports.ModelServiceGrpcTransport, "grpc"), - (ModelServiceAsyncClient, transports.ModelServiceGrpcAsyncIOTransport, "grpc_asyncio"), -]) -@mock.patch.object(ModelServiceClient, "DEFAULT_ENDPOINT", modify_default_endpoint(ModelServiceClient)) -@mock.patch.object(ModelServiceAsyncClient, "DEFAULT_ENDPOINT", modify_default_endpoint(ModelServiceAsyncClient)) -def test_model_service_client_client_options(client_class, transport_class, transport_name): - # Check that if channel is provided we won't create a new one. - with mock.patch.object(ModelServiceClient, 'get_transport_class') as gtc: - transport = transport_class( - credentials=ga_credentials.AnonymousCredentials() - ) - client = client_class(transport=transport) - gtc.assert_not_called() - - # Check that if channel is provided via str we will create a new one. - with mock.patch.object(ModelServiceClient, 'get_transport_class') as gtc: - client = client_class(transport=transport_name) - gtc.assert_called() - - # Check the case api_endpoint is provided. - options = client_options.ClientOptions(api_endpoint="squid.clam.whelk") - with mock.patch.object(transport_class, '__init__') as patched: - patched.return_value = None - client = client_class(client_options=options) - patched.assert_called_once_with( - credentials=None, - credentials_file=None, - host="squid.clam.whelk", - scopes=None, - client_cert_source_for_mtls=None, - quota_project_id=None, - client_info=transports.base.DEFAULT_CLIENT_INFO, - ) - - # Check the case api_endpoint is not provided and GOOGLE_API_USE_MTLS_ENDPOINT is - # "never". - with mock.patch.dict(os.environ, {"GOOGLE_API_USE_MTLS_ENDPOINT": "never"}): - with mock.patch.object(transport_class, '__init__') as patched: - patched.return_value = None - client = client_class() - patched.assert_called_once_with( - credentials=None, - credentials_file=None, - host=client.DEFAULT_ENDPOINT, - scopes=None, - client_cert_source_for_mtls=None, - quota_project_id=None, - client_info=transports.base.DEFAULT_CLIENT_INFO, - ) - - # Check the case api_endpoint is not provided and GOOGLE_API_USE_MTLS_ENDPOINT is - # "always". - with mock.patch.dict(os.environ, {"GOOGLE_API_USE_MTLS_ENDPOINT": "always"}): - with mock.patch.object(transport_class, '__init__') as patched: - patched.return_value = None - client = client_class() - patched.assert_called_once_with( - credentials=None, - credentials_file=None, - host=client.DEFAULT_MTLS_ENDPOINT, - scopes=None, - client_cert_source_for_mtls=None, - quota_project_id=None, - client_info=transports.base.DEFAULT_CLIENT_INFO, - ) - - # Check the case api_endpoint is not provided and GOOGLE_API_USE_MTLS_ENDPOINT has - # unsupported value. - with mock.patch.dict(os.environ, {"GOOGLE_API_USE_MTLS_ENDPOINT": "Unsupported"}): - with pytest.raises(MutualTLSChannelError): - client = client_class() - - # Check the case GOOGLE_API_USE_CLIENT_CERTIFICATE has unsupported value. - with mock.patch.dict(os.environ, {"GOOGLE_API_USE_CLIENT_CERTIFICATE": "Unsupported"}): - with pytest.raises(ValueError): - client = client_class() - - # Check the case quota_project_id is provided - options = client_options.ClientOptions(quota_project_id="octopus") - with mock.patch.object(transport_class, '__init__') as patched: - patched.return_value = None - client = client_class(client_options=options) - patched.assert_called_once_with( - credentials=None, - credentials_file=None, - host=client.DEFAULT_ENDPOINT, - scopes=None, - client_cert_source_for_mtls=None, - quota_project_id="octopus", - client_info=transports.base.DEFAULT_CLIENT_INFO, - ) - -@pytest.mark.parametrize("client_class,transport_class,transport_name,use_client_cert_env", [ - (ModelServiceClient, transports.ModelServiceGrpcTransport, "grpc", "true"), - (ModelServiceAsyncClient, transports.ModelServiceGrpcAsyncIOTransport, "grpc_asyncio", "true"), - (ModelServiceClient, transports.ModelServiceGrpcTransport, "grpc", "false"), - (ModelServiceAsyncClient, transports.ModelServiceGrpcAsyncIOTransport, "grpc_asyncio", "false"), -]) -@mock.patch.object(ModelServiceClient, "DEFAULT_ENDPOINT", modify_default_endpoint(ModelServiceClient)) -@mock.patch.object(ModelServiceAsyncClient, "DEFAULT_ENDPOINT", modify_default_endpoint(ModelServiceAsyncClient)) -@mock.patch.dict(os.environ, {"GOOGLE_API_USE_MTLS_ENDPOINT": "auto"}) -def test_model_service_client_mtls_env_auto(client_class, transport_class, transport_name, use_client_cert_env): - # This tests the endpoint autoswitch behavior. Endpoint is autoswitched to the default - # mtls endpoint, if GOOGLE_API_USE_CLIENT_CERTIFICATE is "true" and client cert exists. - - # Check the case client_cert_source is provided. Whether client cert is used depends on - # GOOGLE_API_USE_CLIENT_CERTIFICATE value. - with mock.patch.dict(os.environ, {"GOOGLE_API_USE_CLIENT_CERTIFICATE": use_client_cert_env}): - options = client_options.ClientOptions(client_cert_source=client_cert_source_callback) - with mock.patch.object(transport_class, '__init__') as patched: - patched.return_value = None - client = client_class(client_options=options) - - if use_client_cert_env == "false": - expected_client_cert_source = None - expected_host = client.DEFAULT_ENDPOINT - else: - expected_client_cert_source = client_cert_source_callback - expected_host = client.DEFAULT_MTLS_ENDPOINT - - patched.assert_called_once_with( - credentials=None, - credentials_file=None, - host=expected_host, - scopes=None, - client_cert_source_for_mtls=expected_client_cert_source, - quota_project_id=None, - client_info=transports.base.DEFAULT_CLIENT_INFO, - ) - - # Check the case ADC client cert is provided. Whether client cert is used depends on - # GOOGLE_API_USE_CLIENT_CERTIFICATE value. - with mock.patch.dict(os.environ, {"GOOGLE_API_USE_CLIENT_CERTIFICATE": use_client_cert_env}): - with mock.patch.object(transport_class, '__init__') as patched: - with mock.patch('google.auth.transport.mtls.has_default_client_cert_source', return_value=True): - with mock.patch('google.auth.transport.mtls.default_client_cert_source', return_value=client_cert_source_callback): - if use_client_cert_env == "false": - expected_host = client.DEFAULT_ENDPOINT - expected_client_cert_source = None - else: - expected_host = client.DEFAULT_MTLS_ENDPOINT - expected_client_cert_source = client_cert_source_callback - - patched.return_value = None - client = client_class() - patched.assert_called_once_with( - credentials=None, - credentials_file=None, - host=expected_host, - scopes=None, - client_cert_source_for_mtls=expected_client_cert_source, - quota_project_id=None, - client_info=transports.base.DEFAULT_CLIENT_INFO, - ) - - # Check the case client_cert_source and ADC client cert are not provided. - with mock.patch.dict(os.environ, {"GOOGLE_API_USE_CLIENT_CERTIFICATE": use_client_cert_env}): - with mock.patch.object(transport_class, '__init__') as patched: - with mock.patch("google.auth.transport.mtls.has_default_client_cert_source", return_value=False): - patched.return_value = None - client = client_class() - patched.assert_called_once_with( - credentials=None, - credentials_file=None, - host=client.DEFAULT_ENDPOINT, - scopes=None, - client_cert_source_for_mtls=None, - quota_project_id=None, - client_info=transports.base.DEFAULT_CLIENT_INFO, - ) - - -@pytest.mark.parametrize("client_class,transport_class,transport_name", [ - (ModelServiceClient, transports.ModelServiceGrpcTransport, "grpc"), - (ModelServiceAsyncClient, transports.ModelServiceGrpcAsyncIOTransport, "grpc_asyncio"), -]) -def test_model_service_client_client_options_scopes(client_class, transport_class, transport_name): - # Check the case scopes are provided. - options = client_options.ClientOptions( - scopes=["1", "2"], - ) - with mock.patch.object(transport_class, '__init__') as patched: - patched.return_value = None - client = client_class(client_options=options) - patched.assert_called_once_with( - credentials=None, - credentials_file=None, - host=client.DEFAULT_ENDPOINT, - scopes=["1", "2"], - client_cert_source_for_mtls=None, - quota_project_id=None, - client_info=transports.base.DEFAULT_CLIENT_INFO, - ) - -@pytest.mark.parametrize("client_class,transport_class,transport_name", [ - (ModelServiceClient, transports.ModelServiceGrpcTransport, "grpc"), - (ModelServiceAsyncClient, transports.ModelServiceGrpcAsyncIOTransport, "grpc_asyncio"), -]) -def test_model_service_client_client_options_credentials_file(client_class, transport_class, transport_name): - # Check the case credentials file is provided. - options = client_options.ClientOptions( - credentials_file="credentials.json" - ) - with mock.patch.object(transport_class, '__init__') as patched: - patched.return_value = None - client = client_class(client_options=options) - patched.assert_called_once_with( - credentials=None, - credentials_file="credentials.json", - host=client.DEFAULT_ENDPOINT, - scopes=None, - client_cert_source_for_mtls=None, - quota_project_id=None, - client_info=transports.base.DEFAULT_CLIENT_INFO, - ) - - -def test_model_service_client_client_options_from_dict(): - with mock.patch('google.cloud.bigquery_v2.services.model_service.transports.ModelServiceGrpcTransport.__init__') as grpc_transport: - grpc_transport.return_value = None - client = ModelServiceClient( - client_options={'api_endpoint': 'squid.clam.whelk'} - ) - grpc_transport.assert_called_once_with( - credentials=None, - credentials_file=None, - host="squid.clam.whelk", - scopes=None, - client_cert_source_for_mtls=None, - quota_project_id=None, - client_info=transports.base.DEFAULT_CLIENT_INFO, - ) - - -def test_get_model(transport: str = 'grpc', request_type=model.GetModelRequest): - client = ModelServiceClient( - credentials=ga_credentials.AnonymousCredentials(), - transport=transport, - ) - - # Everything is optional in proto3 as far as the runtime is concerned, - # and we are mocking out the actual API, so just send an empty request. - request = request_type() - - # Mock the actual call within the gRPC stub, and fake the request. - with mock.patch.object( - type(client.transport.get_model), - '__call__') as call: - # Designate an appropriate return value for the call. - call.return_value = model.Model( - etag='etag_value', - creation_time=1379, - last_modified_time=1890, - description='description_value', - friendly_name='friendly_name_value', - expiration_time=1617, - location='location_value', - model_type=model.Model.ModelType.LINEAR_REGRESSION, - ) - response = client.get_model(request) - - # Establish that the underlying gRPC stub method was called. - assert len(call.mock_calls) == 1 - _, args, _ = call.mock_calls[0] - assert args[0] == model.GetModelRequest() - - # Establish that the response is the type that we expect. - assert isinstance(response, model.Model) - assert response.etag == 'etag_value' - assert response.creation_time == 1379 - assert response.last_modified_time == 1890 - assert response.description == 'description_value' - assert response.friendly_name == 'friendly_name_value' - assert response.expiration_time == 1617 - assert response.location == 'location_value' - assert response.model_type == model.Model.ModelType.LINEAR_REGRESSION - - -def test_get_model_from_dict(): - test_get_model(request_type=dict) - - -def test_get_model_empty_call(): - # This test is a coverage failsafe to make sure that totally empty calls, - # i.e. request == None and no flattened fields passed, work. - client = ModelServiceClient( - credentials=ga_credentials.AnonymousCredentials(), - transport='grpc', - ) - - # Mock the actual call within the gRPC stub, and fake the request. - with mock.patch.object( - type(client.transport.get_model), - '__call__') as call: - client.get_model() - call.assert_called() - _, args, _ = call.mock_calls[0] - assert args[0] == model.GetModelRequest() - - -@pytest.mark.asyncio -async def test_get_model_async(transport: str = 'grpc_asyncio', request_type=model.GetModelRequest): - client = ModelServiceAsyncClient( - credentials=ga_credentials.AnonymousCredentials(), - transport=transport, - ) - - # Everything is optional in proto3 as far as the runtime is concerned, - # and we are mocking out the actual API, so just send an empty request. - request = request_type() - - # Mock the actual call within the gRPC stub, and fake the request. - with mock.patch.object( - type(client.transport.get_model), - '__call__') as call: - # Designate an appropriate return value for the call. - call.return_value =grpc_helpers_async.FakeUnaryUnaryCall(model.Model( - etag='etag_value', - creation_time=1379, - last_modified_time=1890, - description='description_value', - friendly_name='friendly_name_value', - expiration_time=1617, - location='location_value', - model_type=model.Model.ModelType.LINEAR_REGRESSION, - )) - response = await client.get_model(request) - - # Establish that the underlying gRPC stub method was called. - assert len(call.mock_calls) - _, args, _ = call.mock_calls[0] - assert args[0] == model.GetModelRequest() - - # Establish that the response is the type that we expect. - assert isinstance(response, model.Model) - assert response.etag == 'etag_value' - assert response.creation_time == 1379 - assert response.last_modified_time == 1890 - assert response.description == 'description_value' - assert response.friendly_name == 'friendly_name_value' - assert response.expiration_time == 1617 - assert response.location == 'location_value' - assert response.model_type == model.Model.ModelType.LINEAR_REGRESSION - - -@pytest.mark.asyncio -async def test_get_model_async_from_dict(): - await test_get_model_async(request_type=dict) - - -def test_get_model_flattened(): - client = ModelServiceClient( - credentials=ga_credentials.AnonymousCredentials(), - ) - - # Mock the actual call within the gRPC stub, and fake the request. - with mock.patch.object( - type(client.transport.get_model), - '__call__') as call: - # Designate an appropriate return value for the call. - call.return_value = model.Model() - # Call the method with a truthy value for each flattened field, - # using the keyword arguments to the method. - client.get_model( - project_id='project_id_value', - dataset_id='dataset_id_value', - model_id='model_id_value', - ) - - # Establish that the underlying call was made with the expected - # request object values. - assert len(call.mock_calls) == 1 - _, args, _ = call.mock_calls[0] - assert args[0].project_id == 'project_id_value' - assert args[0].dataset_id == 'dataset_id_value' - assert args[0].model_id == 'model_id_value' - - -def test_get_model_flattened_error(): - client = ModelServiceClient( - credentials=ga_credentials.AnonymousCredentials(), - ) - - # Attempting to call a method with both a request object and flattened - # fields is an error. - with pytest.raises(ValueError): - client.get_model( - model.GetModelRequest(), - project_id='project_id_value', - dataset_id='dataset_id_value', - model_id='model_id_value', - ) - - -@pytest.mark.asyncio -async def test_get_model_flattened_async(): - client = ModelServiceAsyncClient( - credentials=ga_credentials.AnonymousCredentials(), - ) - - # Mock the actual call within the gRPC stub, and fake the request. - with mock.patch.object( - type(client.transport.get_model), - '__call__') as call: - # Designate an appropriate return value for the call. - call.return_value = model.Model() - - call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(model.Model()) - # Call the method with a truthy value for each flattened field, - # using the keyword arguments to the method. - response = await client.get_model( - project_id='project_id_value', - dataset_id='dataset_id_value', - model_id='model_id_value', - ) - - # Establish that the underlying call was made with the expected - # request object values. - assert len(call.mock_calls) - _, args, _ = call.mock_calls[0] - assert args[0].project_id == 'project_id_value' - assert args[0].dataset_id == 'dataset_id_value' - assert args[0].model_id == 'model_id_value' - - -@pytest.mark.asyncio -async def test_get_model_flattened_error_async(): - client = ModelServiceAsyncClient( - credentials=ga_credentials.AnonymousCredentials(), - ) - - # Attempting to call a method with both a request object and flattened - # fields is an error. - with pytest.raises(ValueError): - await client.get_model( - model.GetModelRequest(), - project_id='project_id_value', - dataset_id='dataset_id_value', - model_id='model_id_value', - ) - - -def test_list_models(transport: str = 'grpc', request_type=model.ListModelsRequest): - client = ModelServiceClient( - credentials=ga_credentials.AnonymousCredentials(), - transport=transport, - ) - - # Everything is optional in proto3 as far as the runtime is concerned, - # and we are mocking out the actual API, so just send an empty request. - request = request_type() - - # Mock the actual call within the gRPC stub, and fake the request. - with mock.patch.object( - type(client.transport.list_models), - '__call__') as call: - # Designate an appropriate return value for the call. - call.return_value = model.ListModelsResponse( - next_page_token='next_page_token_value', - ) - response = client.list_models(request) - - # Establish that the underlying gRPC stub method was called. - assert len(call.mock_calls) == 1 - _, args, _ = call.mock_calls[0] - assert args[0] == model.ListModelsRequest() - - # Establish that the response is the type that we expect. - assert response.raw_page is response - assert isinstance(response, model.ListModelsResponse) - assert response.next_page_token == 'next_page_token_value' - - -def test_list_models_from_dict(): - test_list_models(request_type=dict) - - -def test_list_models_empty_call(): - # This test is a coverage failsafe to make sure that totally empty calls, - # i.e. request == None and no flattened fields passed, work. - client = ModelServiceClient( - credentials=ga_credentials.AnonymousCredentials(), - transport='grpc', - ) - - # Mock the actual call within the gRPC stub, and fake the request. - with mock.patch.object( - type(client.transport.list_models), - '__call__') as call: - client.list_models() - call.assert_called() - _, args, _ = call.mock_calls[0] - assert args[0] == model.ListModelsRequest() - - -@pytest.mark.asyncio -async def test_list_models_async(transport: str = 'grpc_asyncio', request_type=model.ListModelsRequest): - client = ModelServiceAsyncClient( - credentials=ga_credentials.AnonymousCredentials(), - transport=transport, - ) - - # Everything is optional in proto3 as far as the runtime is concerned, - # and we are mocking out the actual API, so just send an empty request. - request = request_type() - - # Mock the actual call within the gRPC stub, and fake the request. - with mock.patch.object( - type(client.transport.list_models), - '__call__') as call: - # Designate an appropriate return value for the call. - call.return_value =grpc_helpers_async.FakeUnaryUnaryCall(model.ListModelsResponse( - next_page_token='next_page_token_value', - )) - response = await client.list_models(request) - - # Establish that the underlying gRPC stub method was called. - assert len(call.mock_calls) - _, args, _ = call.mock_calls[0] - assert args[0] == model.ListModelsRequest() - - # Establish that the response is the type that we expect. - assert isinstance(response, model.ListModelsResponse) - assert response.next_page_token == 'next_page_token_value' - - -@pytest.mark.asyncio -async def test_list_models_async_from_dict(): - await test_list_models_async(request_type=dict) - - -def test_list_models_flattened(): - client = ModelServiceClient( - credentials=ga_credentials.AnonymousCredentials(), - ) - - # Mock the actual call within the gRPC stub, and fake the request. - with mock.patch.object( - type(client.transport.list_models), - '__call__') as call: - # Designate an appropriate return value for the call. - call.return_value = model.ListModelsResponse() - # Call the method with a truthy value for each flattened field, - # using the keyword arguments to the method. - client.list_models( - project_id='project_id_value', - dataset_id='dataset_id_value', - max_results=wrappers_pb2.UInt32Value(value=541), - ) - - # Establish that the underlying call was made with the expected - # request object values. - assert len(call.mock_calls) == 1 - _, args, _ = call.mock_calls[0] - assert args[0].project_id == 'project_id_value' - assert args[0].dataset_id == 'dataset_id_value' - assert args[0].max_results == wrappers_pb2.UInt32Value(value=541) - - -def test_list_models_flattened_error(): - client = ModelServiceClient( - credentials=ga_credentials.AnonymousCredentials(), - ) - - # Attempting to call a method with both a request object and flattened - # fields is an error. - with pytest.raises(ValueError): - client.list_models( - model.ListModelsRequest(), - project_id='project_id_value', - dataset_id='dataset_id_value', - max_results=wrappers_pb2.UInt32Value(value=541), - ) - - -@pytest.mark.asyncio -async def test_list_models_flattened_async(): - client = ModelServiceAsyncClient( - credentials=ga_credentials.AnonymousCredentials(), - ) - - # Mock the actual call within the gRPC stub, and fake the request. - with mock.patch.object( - type(client.transport.list_models), - '__call__') as call: - # Designate an appropriate return value for the call. - call.return_value = model.ListModelsResponse() - - call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(model.ListModelsResponse()) - # Call the method with a truthy value for each flattened field, - # using the keyword arguments to the method. - response = await client.list_models( - project_id='project_id_value', - dataset_id='dataset_id_value', - max_results=wrappers_pb2.UInt32Value(value=541), - ) - - # Establish that the underlying call was made with the expected - # request object values. - assert len(call.mock_calls) - _, args, _ = call.mock_calls[0] - assert args[0].project_id == 'project_id_value' - assert args[0].dataset_id == 'dataset_id_value' - assert args[0].max_results == wrappers_pb2.UInt32Value(value=541) - - -@pytest.mark.asyncio -async def test_list_models_flattened_error_async(): - client = ModelServiceAsyncClient( - credentials=ga_credentials.AnonymousCredentials(), - ) - - # Attempting to call a method with both a request object and flattened - # fields is an error. - with pytest.raises(ValueError): - await client.list_models( - model.ListModelsRequest(), - project_id='project_id_value', - dataset_id='dataset_id_value', - max_results=wrappers_pb2.UInt32Value(value=541), - ) - - -def test_patch_model(transport: str = 'grpc', request_type=gcb_model.PatchModelRequest): - client = ModelServiceClient( - credentials=ga_credentials.AnonymousCredentials(), - transport=transport, - ) - - # Everything is optional in proto3 as far as the runtime is concerned, - # and we are mocking out the actual API, so just send an empty request. - request = request_type() - - # Mock the actual call within the gRPC stub, and fake the request. - with mock.patch.object( - type(client.transport.patch_model), - '__call__') as call: - # Designate an appropriate return value for the call. - call.return_value = gcb_model.Model( - etag='etag_value', - creation_time=1379, - last_modified_time=1890, - description='description_value', - friendly_name='friendly_name_value', - expiration_time=1617, - location='location_value', - model_type=gcb_model.Model.ModelType.LINEAR_REGRESSION, - ) - response = client.patch_model(request) - - # Establish that the underlying gRPC stub method was called. - assert len(call.mock_calls) == 1 - _, args, _ = call.mock_calls[0] - assert args[0] == gcb_model.PatchModelRequest() - - # Establish that the response is the type that we expect. - assert isinstance(response, gcb_model.Model) - assert response.etag == 'etag_value' - assert response.creation_time == 1379 - assert response.last_modified_time == 1890 - assert response.description == 'description_value' - assert response.friendly_name == 'friendly_name_value' - assert response.expiration_time == 1617 - assert response.location == 'location_value' - assert response.model_type == gcb_model.Model.ModelType.LINEAR_REGRESSION - - -def test_patch_model_from_dict(): - test_patch_model(request_type=dict) - - -def test_patch_model_empty_call(): - # This test is a coverage failsafe to make sure that totally empty calls, - # i.e. request == None and no flattened fields passed, work. - client = ModelServiceClient( - credentials=ga_credentials.AnonymousCredentials(), - transport='grpc', - ) - - # Mock the actual call within the gRPC stub, and fake the request. - with mock.patch.object( - type(client.transport.patch_model), - '__call__') as call: - client.patch_model() - call.assert_called() - _, args, _ = call.mock_calls[0] - assert args[0] == gcb_model.PatchModelRequest() - - -@pytest.mark.asyncio -async def test_patch_model_async(transport: str = 'grpc_asyncio', request_type=gcb_model.PatchModelRequest): - client = ModelServiceAsyncClient( - credentials=ga_credentials.AnonymousCredentials(), - transport=transport, - ) - - # Everything is optional in proto3 as far as the runtime is concerned, - # and we are mocking out the actual API, so just send an empty request. - request = request_type() - - # Mock the actual call within the gRPC stub, and fake the request. - with mock.patch.object( - type(client.transport.patch_model), - '__call__') as call: - # Designate an appropriate return value for the call. - call.return_value =grpc_helpers_async.FakeUnaryUnaryCall(gcb_model.Model( - etag='etag_value', - creation_time=1379, - last_modified_time=1890, - description='description_value', - friendly_name='friendly_name_value', - expiration_time=1617, - location='location_value', - model_type=gcb_model.Model.ModelType.LINEAR_REGRESSION, - )) - response = await client.patch_model(request) - - # Establish that the underlying gRPC stub method was called. - assert len(call.mock_calls) - _, args, _ = call.mock_calls[0] - assert args[0] == gcb_model.PatchModelRequest() - - # Establish that the response is the type that we expect. - assert isinstance(response, gcb_model.Model) - assert response.etag == 'etag_value' - assert response.creation_time == 1379 - assert response.last_modified_time == 1890 - assert response.description == 'description_value' - assert response.friendly_name == 'friendly_name_value' - assert response.expiration_time == 1617 - assert response.location == 'location_value' - assert response.model_type == gcb_model.Model.ModelType.LINEAR_REGRESSION - - -@pytest.mark.asyncio -async def test_patch_model_async_from_dict(): - await test_patch_model_async(request_type=dict) - - -def test_patch_model_flattened(): - client = ModelServiceClient( - credentials=ga_credentials.AnonymousCredentials(), - ) - - # Mock the actual call within the gRPC stub, and fake the request. - with mock.patch.object( - type(client.transport.patch_model), - '__call__') as call: - # Designate an appropriate return value for the call. - call.return_value = gcb_model.Model() - # Call the method with a truthy value for each flattened field, - # using the keyword arguments to the method. - client.patch_model( - project_id='project_id_value', - dataset_id='dataset_id_value', - model_id='model_id_value', - model=gcb_model.Model(etag='etag_value'), - ) - - # Establish that the underlying call was made with the expected - # request object values. - assert len(call.mock_calls) == 1 - _, args, _ = call.mock_calls[0] - assert args[0].project_id == 'project_id_value' - assert args[0].dataset_id == 'dataset_id_value' - assert args[0].model_id == 'model_id_value' - assert args[0].model == gcb_model.Model(etag='etag_value') - - -def test_patch_model_flattened_error(): - client = ModelServiceClient( - credentials=ga_credentials.AnonymousCredentials(), - ) - - # Attempting to call a method with both a request object and flattened - # fields is an error. - with pytest.raises(ValueError): - client.patch_model( - gcb_model.PatchModelRequest(), - project_id='project_id_value', - dataset_id='dataset_id_value', - model_id='model_id_value', - model=gcb_model.Model(etag='etag_value'), - ) - - -@pytest.mark.asyncio -async def test_patch_model_flattened_async(): - client = ModelServiceAsyncClient( - credentials=ga_credentials.AnonymousCredentials(), - ) - - # Mock the actual call within the gRPC stub, and fake the request. - with mock.patch.object( - type(client.transport.patch_model), - '__call__') as call: - # Designate an appropriate return value for the call. - call.return_value = gcb_model.Model() - - call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(gcb_model.Model()) - # Call the method with a truthy value for each flattened field, - # using the keyword arguments to the method. - response = await client.patch_model( - project_id='project_id_value', - dataset_id='dataset_id_value', - model_id='model_id_value', - model=gcb_model.Model(etag='etag_value'), - ) - - # Establish that the underlying call was made with the expected - # request object values. - assert len(call.mock_calls) - _, args, _ = call.mock_calls[0] - assert args[0].project_id == 'project_id_value' - assert args[0].dataset_id == 'dataset_id_value' - assert args[0].model_id == 'model_id_value' - assert args[0].model == gcb_model.Model(etag='etag_value') - - -@pytest.mark.asyncio -async def test_patch_model_flattened_error_async(): - client = ModelServiceAsyncClient( - credentials=ga_credentials.AnonymousCredentials(), - ) - - # Attempting to call a method with both a request object and flattened - # fields is an error. - with pytest.raises(ValueError): - await client.patch_model( - gcb_model.PatchModelRequest(), - project_id='project_id_value', - dataset_id='dataset_id_value', - model_id='model_id_value', - model=gcb_model.Model(etag='etag_value'), - ) - - -def test_delete_model(transport: str = 'grpc', request_type=model.DeleteModelRequest): - client = ModelServiceClient( - credentials=ga_credentials.AnonymousCredentials(), - transport=transport, - ) - - # Everything is optional in proto3 as far as the runtime is concerned, - # and we are mocking out the actual API, so just send an empty request. - request = request_type() - - # Mock the actual call within the gRPC stub, and fake the request. - with mock.patch.object( - type(client.transport.delete_model), - '__call__') as call: - # Designate an appropriate return value for the call. - call.return_value = None - response = client.delete_model(request) - - # Establish that the underlying gRPC stub method was called. - assert len(call.mock_calls) == 1 - _, args, _ = call.mock_calls[0] - assert args[0] == model.DeleteModelRequest() - - # Establish that the response is the type that we expect. - assert response is None - - -def test_delete_model_from_dict(): - test_delete_model(request_type=dict) - - -def test_delete_model_empty_call(): - # This test is a coverage failsafe to make sure that totally empty calls, - # i.e. request == None and no flattened fields passed, work. - client = ModelServiceClient( - credentials=ga_credentials.AnonymousCredentials(), - transport='grpc', - ) - - # Mock the actual call within the gRPC stub, and fake the request. - with mock.patch.object( - type(client.transport.delete_model), - '__call__') as call: - client.delete_model() - call.assert_called() - _, args, _ = call.mock_calls[0] - assert args[0] == model.DeleteModelRequest() - - -@pytest.mark.asyncio -async def test_delete_model_async(transport: str = 'grpc_asyncio', request_type=model.DeleteModelRequest): - client = ModelServiceAsyncClient( - credentials=ga_credentials.AnonymousCredentials(), - transport=transport, - ) - - # Everything is optional in proto3 as far as the runtime is concerned, - # and we are mocking out the actual API, so just send an empty request. - request = request_type() - - # Mock the actual call within the gRPC stub, and fake the request. - with mock.patch.object( - type(client.transport.delete_model), - '__call__') as call: - # Designate an appropriate return value for the call. - call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(None) - response = await client.delete_model(request) - - # Establish that the underlying gRPC stub method was called. - assert len(call.mock_calls) - _, args, _ = call.mock_calls[0] - assert args[0] == model.DeleteModelRequest() - - # Establish that the response is the type that we expect. - assert response is None - - -@pytest.mark.asyncio -async def test_delete_model_async_from_dict(): - await test_delete_model_async(request_type=dict) - - -def test_delete_model_flattened(): - client = ModelServiceClient( - credentials=ga_credentials.AnonymousCredentials(), - ) - - # Mock the actual call within the gRPC stub, and fake the request. - with mock.patch.object( - type(client.transport.delete_model), - '__call__') as call: - # Designate an appropriate return value for the call. - call.return_value = None - # Call the method with a truthy value for each flattened field, - # using the keyword arguments to the method. - client.delete_model( - project_id='project_id_value', - dataset_id='dataset_id_value', - model_id='model_id_value', - ) - - # Establish that the underlying call was made with the expected - # request object values. - assert len(call.mock_calls) == 1 - _, args, _ = call.mock_calls[0] - assert args[0].project_id == 'project_id_value' - assert args[0].dataset_id == 'dataset_id_value' - assert args[0].model_id == 'model_id_value' - - -def test_delete_model_flattened_error(): - client = ModelServiceClient( - credentials=ga_credentials.AnonymousCredentials(), - ) - - # Attempting to call a method with both a request object and flattened - # fields is an error. - with pytest.raises(ValueError): - client.delete_model( - model.DeleteModelRequest(), - project_id='project_id_value', - dataset_id='dataset_id_value', - model_id='model_id_value', - ) - - -@pytest.mark.asyncio -async def test_delete_model_flattened_async(): - client = ModelServiceAsyncClient( - credentials=ga_credentials.AnonymousCredentials(), - ) - - # Mock the actual call within the gRPC stub, and fake the request. - with mock.patch.object( - type(client.transport.delete_model), - '__call__') as call: - # Designate an appropriate return value for the call. - call.return_value = None - - call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(None) - # Call the method with a truthy value for each flattened field, - # using the keyword arguments to the method. - response = await client.delete_model( - project_id='project_id_value', - dataset_id='dataset_id_value', - model_id='model_id_value', - ) - - # Establish that the underlying call was made with the expected - # request object values. - assert len(call.mock_calls) - _, args, _ = call.mock_calls[0] - assert args[0].project_id == 'project_id_value' - assert args[0].dataset_id == 'dataset_id_value' - assert args[0].model_id == 'model_id_value' - - -@pytest.mark.asyncio -async def test_delete_model_flattened_error_async(): - client = ModelServiceAsyncClient( - credentials=ga_credentials.AnonymousCredentials(), - ) - - # Attempting to call a method with both a request object and flattened - # fields is an error. - with pytest.raises(ValueError): - await client.delete_model( - model.DeleteModelRequest(), - project_id='project_id_value', - dataset_id='dataset_id_value', - model_id='model_id_value', - ) - - -def test_credentials_transport_error(): - # It is an error to provide credentials and a transport instance. - transport = transports.ModelServiceGrpcTransport( - credentials=ga_credentials.AnonymousCredentials(), - ) - with pytest.raises(ValueError): - client = ModelServiceClient( - credentials=ga_credentials.AnonymousCredentials(), - transport=transport, - ) - - # It is an error to provide a credentials file and a transport instance. - transport = transports.ModelServiceGrpcTransport( - credentials=ga_credentials.AnonymousCredentials(), - ) - with pytest.raises(ValueError): - client = ModelServiceClient( - client_options={"credentials_file": "credentials.json"}, - transport=transport, - ) - - # It is an error to provide scopes and a transport instance. - transport = transports.ModelServiceGrpcTransport( - credentials=ga_credentials.AnonymousCredentials(), - ) - with pytest.raises(ValueError): - client = ModelServiceClient( - client_options={"scopes": ["1", "2"]}, - transport=transport, - ) - - -def test_transport_instance(): - # A client may be instantiated with a custom transport instance. - transport = transports.ModelServiceGrpcTransport( - credentials=ga_credentials.AnonymousCredentials(), - ) - client = ModelServiceClient(transport=transport) - assert client.transport is transport - -def test_transport_get_channel(): - # A client may be instantiated with a custom transport instance. - transport = transports.ModelServiceGrpcTransport( - credentials=ga_credentials.AnonymousCredentials(), - ) - channel = transport.grpc_channel - assert channel - - transport = transports.ModelServiceGrpcAsyncIOTransport( - credentials=ga_credentials.AnonymousCredentials(), - ) - channel = transport.grpc_channel - assert channel - -@pytest.mark.parametrize("transport_class", [ - transports.ModelServiceGrpcTransport, - transports.ModelServiceGrpcAsyncIOTransport, -]) -def test_transport_adc(transport_class): - # Test default credentials are used if not provided. - with mock.patch.object(google.auth, 'default') as adc: - adc.return_value = (ga_credentials.AnonymousCredentials(), None) - transport_class() - adc.assert_called_once() - -def test_transport_grpc_default(): - # A client should use the gRPC transport by default. - client = ModelServiceClient( - credentials=ga_credentials.AnonymousCredentials(), - ) - assert isinstance( - client.transport, - transports.ModelServiceGrpcTransport, - ) - -def test_model_service_base_transport_error(): - # Passing both a credentials object and credentials_file should raise an error - with pytest.raises(core_exceptions.DuplicateCredentialArgs): - transport = transports.ModelServiceTransport( - credentials=ga_credentials.AnonymousCredentials(), - credentials_file="credentials.json" - ) - - -def test_model_service_base_transport(): - # Instantiate the base transport. - with mock.patch('google.cloud.bigquery_v2.services.model_service.transports.ModelServiceTransport.__init__') as Transport: - Transport.return_value = None - transport = transports.ModelServiceTransport( - credentials=ga_credentials.AnonymousCredentials(), - ) - - # Every method on the transport should just blindly - # raise NotImplementedError. - methods = ( - 'get_model', - 'list_models', - 'patch_model', - 'delete_model', - ) - for method in methods: - with pytest.raises(NotImplementedError): - getattr(transport, method)(request=object()) - - -@requires_google_auth_gte_1_25_0 -def test_model_service_base_transport_with_credentials_file(): - # Instantiate the base transport with a credentials file - with mock.patch.object(google.auth, 'load_credentials_from_file', autospec=True) as load_creds, mock.patch('google.cloud.bigquery_v2.services.model_service.transports.ModelServiceTransport._prep_wrapped_messages') as Transport: - Transport.return_value = None - load_creds.return_value = (ga_credentials.AnonymousCredentials(), None) - transport = transports.ModelServiceTransport( - credentials_file="credentials.json", - quota_project_id="octopus", - ) - load_creds.assert_called_once_with("credentials.json", - scopes=None, - default_scopes=( - 'https://www.googleapis.com/auth/bigquery', - 'https://www.googleapis.com/auth/bigquery.readonly', - 'https://www.googleapis.com/auth/cloud-platform', - 'https://www.googleapis.com/auth/cloud-platform.read-only', -), - quota_project_id="octopus", - ) - - -@requires_google_auth_lt_1_25_0 -def test_model_service_base_transport_with_credentials_file_old_google_auth(): - # Instantiate the base transport with a credentials file - with mock.patch.object(google.auth, 'load_credentials_from_file', autospec=True) as load_creds, mock.patch('google.cloud.bigquery_v2.services.model_service.transports.ModelServiceTransport._prep_wrapped_messages') as Transport: - Transport.return_value = None - load_creds.return_value = (ga_credentials.AnonymousCredentials(), None) - transport = transports.ModelServiceTransport( - credentials_file="credentials.json", - quota_project_id="octopus", - ) - load_creds.assert_called_once_with("credentials.json", scopes=( - 'https://www.googleapis.com/auth/bigquery', - 'https://www.googleapis.com/auth/bigquery.readonly', - 'https://www.googleapis.com/auth/cloud-platform', - 'https://www.googleapis.com/auth/cloud-platform.read-only', - ), - quota_project_id="octopus", - ) - - -def test_model_service_base_transport_with_adc(): - # Test the default credentials are used if credentials and credentials_file are None. - with mock.patch.object(google.auth, 'default', autospec=True) as adc, mock.patch('google.cloud.bigquery_v2.services.model_service.transports.ModelServiceTransport._prep_wrapped_messages') as Transport: - Transport.return_value = None - adc.return_value = (ga_credentials.AnonymousCredentials(), None) - transport = transports.ModelServiceTransport() - adc.assert_called_once() - - -@requires_google_auth_gte_1_25_0 -def test_model_service_auth_adc(): - # If no credentials are provided, we should use ADC credentials. - with mock.patch.object(google.auth, 'default', autospec=True) as adc: - adc.return_value = (ga_credentials.AnonymousCredentials(), None) - ModelServiceClient() - adc.assert_called_once_with( - scopes=None, - default_scopes=( - 'https://www.googleapis.com/auth/bigquery', - 'https://www.googleapis.com/auth/bigquery.readonly', - 'https://www.googleapis.com/auth/cloud-platform', - 'https://www.googleapis.com/auth/cloud-platform.read-only', -), - quota_project_id=None, - ) - - -@requires_google_auth_lt_1_25_0 -def test_model_service_auth_adc_old_google_auth(): - # If no credentials are provided, we should use ADC credentials. - with mock.patch.object(google.auth, 'default', autospec=True) as adc: - adc.return_value = (ga_credentials.AnonymousCredentials(), None) - ModelServiceClient() - adc.assert_called_once_with( - scopes=( 'https://www.googleapis.com/auth/bigquery', 'https://www.googleapis.com/auth/bigquery.readonly', 'https://www.googleapis.com/auth/cloud-platform', 'https://www.googleapis.com/auth/cloud-platform.read-only',), - quota_project_id=None, - ) - - -@pytest.mark.parametrize( - "transport_class", - [ - transports.ModelServiceGrpcTransport, - transports.ModelServiceGrpcAsyncIOTransport, - ], -) -@requires_google_auth_gte_1_25_0 -def test_model_service_transport_auth_adc(transport_class): - # If credentials and host are not provided, the transport class should use - # ADC credentials. - with mock.patch.object(google.auth, 'default', autospec=True) as adc: - adc.return_value = (ga_credentials.AnonymousCredentials(), None) - transport_class(quota_project_id="octopus", scopes=["1", "2"]) - adc.assert_called_once_with( - scopes=["1", "2"], - default_scopes=( 'https://www.googleapis.com/auth/bigquery', 'https://www.googleapis.com/auth/bigquery.readonly', 'https://www.googleapis.com/auth/cloud-platform', 'https://www.googleapis.com/auth/cloud-platform.read-only',), - quota_project_id="octopus", - ) - - -@pytest.mark.parametrize( - "transport_class", - [ - transports.ModelServiceGrpcTransport, - transports.ModelServiceGrpcAsyncIOTransport, - ], -) -@requires_google_auth_lt_1_25_0 -def test_model_service_transport_auth_adc_old_google_auth(transport_class): - # If credentials and host are not provided, the transport class should use - # ADC credentials. - with mock.patch.object(google.auth, "default", autospec=True) as adc: - adc.return_value = (ga_credentials.AnonymousCredentials(), None) - transport_class(quota_project_id="octopus") - adc.assert_called_once_with(scopes=( - 'https://www.googleapis.com/auth/bigquery', - 'https://www.googleapis.com/auth/bigquery.readonly', - 'https://www.googleapis.com/auth/cloud-platform', - 'https://www.googleapis.com/auth/cloud-platform.read-only', -), - quota_project_id="octopus", - ) - - -@pytest.mark.parametrize( - "transport_class,grpc_helpers", - [ - (transports.ModelServiceGrpcTransport, grpc_helpers), - (transports.ModelServiceGrpcAsyncIOTransport, grpc_helpers_async) - ], -) -def test_model_service_transport_create_channel(transport_class, grpc_helpers): - # If credentials and host are not provided, the transport class should use - # ADC credentials. - with mock.patch.object(google.auth, "default", autospec=True) as adc, mock.patch.object( - grpc_helpers, "create_channel", autospec=True - ) as create_channel: - creds = ga_credentials.AnonymousCredentials() - adc.return_value = (creds, None) - transport_class( - quota_project_id="octopus", - scopes=["1", "2"] - ) - - create_channel.assert_called_with( - "bigquery.googleapis.com:443", - credentials=creds, - credentials_file=None, - quota_project_id="octopus", - default_scopes=( - 'https://www.googleapis.com/auth/bigquery', - 'https://www.googleapis.com/auth/bigquery.readonly', - 'https://www.googleapis.com/auth/cloud-platform', - 'https://www.googleapis.com/auth/cloud-platform.read-only', -), - scopes=["1", "2"], - default_host="bigquery.googleapis.com", - ssl_credentials=None, - options=[ - ("grpc.max_send_message_length", -1), - ("grpc.max_receive_message_length", -1), - ], - ) - - -@pytest.mark.parametrize("transport_class", [transports.ModelServiceGrpcTransport, transports.ModelServiceGrpcAsyncIOTransport]) -def test_model_service_grpc_transport_client_cert_source_for_mtls( - transport_class -): - cred = ga_credentials.AnonymousCredentials() - - # Check ssl_channel_credentials is used if provided. - with mock.patch.object(transport_class, "create_channel") as mock_create_channel: - mock_ssl_channel_creds = mock.Mock() - transport_class( - host="squid.clam.whelk", - credentials=cred, - ssl_channel_credentials=mock_ssl_channel_creds - ) - mock_create_channel.assert_called_once_with( - "squid.clam.whelk:443", - credentials=cred, - credentials_file=None, - scopes=None, - ssl_credentials=mock_ssl_channel_creds, - quota_project_id=None, - options=[ - ("grpc.max_send_message_length", -1), - ("grpc.max_receive_message_length", -1), - ], - ) - - # Check if ssl_channel_credentials is not provided, then client_cert_source_for_mtls - # is used. - with mock.patch.object(transport_class, "create_channel", return_value=mock.Mock()): - with mock.patch("grpc.ssl_channel_credentials") as mock_ssl_cred: - transport_class( - credentials=cred, - client_cert_source_for_mtls=client_cert_source_callback - ) - expected_cert, expected_key = client_cert_source_callback() - mock_ssl_cred.assert_called_once_with( - certificate_chain=expected_cert, - private_key=expected_key - ) - - -def test_model_service_host_no_port(): - client = ModelServiceClient( - credentials=ga_credentials.AnonymousCredentials(), - client_options=client_options.ClientOptions(api_endpoint='bigquery.googleapis.com'), - ) - assert client.transport._host == 'bigquery.googleapis.com:443' - - -def test_model_service_host_with_port(): - client = ModelServiceClient( - credentials=ga_credentials.AnonymousCredentials(), - client_options=client_options.ClientOptions(api_endpoint='bigquery.googleapis.com:8000'), - ) - assert client.transport._host == 'bigquery.googleapis.com:8000' - -def test_model_service_grpc_transport_channel(): - channel = grpc.secure_channel('http://localhost/', grpc.local_channel_credentials()) - - # Check that channel is used if provided. - transport = transports.ModelServiceGrpcTransport( - host="squid.clam.whelk", - channel=channel, - ) - assert transport.grpc_channel == channel - assert transport._host == "squid.clam.whelk:443" - assert transport._ssl_channel_credentials == None - - -def test_model_service_grpc_asyncio_transport_channel(): - channel = aio.secure_channel('http://localhost/', grpc.local_channel_credentials()) - - # Check that channel is used if provided. - transport = transports.ModelServiceGrpcAsyncIOTransport( - host="squid.clam.whelk", - channel=channel, - ) - assert transport.grpc_channel == channel - assert transport._host == "squid.clam.whelk:443" - assert transport._ssl_channel_credentials == None - - -# Remove this test when deprecated arguments (api_mtls_endpoint, client_cert_source) are -# removed from grpc/grpc_asyncio transport constructor. -@pytest.mark.parametrize("transport_class", [transports.ModelServiceGrpcTransport, transports.ModelServiceGrpcAsyncIOTransport]) -def test_model_service_transport_channel_mtls_with_client_cert_source( - transport_class -): - with mock.patch("grpc.ssl_channel_credentials", autospec=True) as grpc_ssl_channel_cred: - with mock.patch.object(transport_class, "create_channel") as grpc_create_channel: - mock_ssl_cred = mock.Mock() - grpc_ssl_channel_cred.return_value = mock_ssl_cred - - mock_grpc_channel = mock.Mock() - grpc_create_channel.return_value = mock_grpc_channel - - cred = ga_credentials.AnonymousCredentials() - with pytest.warns(DeprecationWarning): - with mock.patch.object(google.auth, 'default') as adc: - adc.return_value = (cred, None) - transport = transport_class( - host="squid.clam.whelk", - api_mtls_endpoint="mtls.squid.clam.whelk", - client_cert_source=client_cert_source_callback, - ) - adc.assert_called_once() - - grpc_ssl_channel_cred.assert_called_once_with( - certificate_chain=b"cert bytes", private_key=b"key bytes" - ) - grpc_create_channel.assert_called_once_with( - "mtls.squid.clam.whelk:443", - credentials=cred, - credentials_file=None, - scopes=None, - ssl_credentials=mock_ssl_cred, - quota_project_id=None, - options=[ - ("grpc.max_send_message_length", -1), - ("grpc.max_receive_message_length", -1), - ], - ) - assert transport.grpc_channel == mock_grpc_channel - assert transport._ssl_channel_credentials == mock_ssl_cred - - -# Remove this test when deprecated arguments (api_mtls_endpoint, client_cert_source) are -# removed from grpc/grpc_asyncio transport constructor. -@pytest.mark.parametrize("transport_class", [transports.ModelServiceGrpcTransport, transports.ModelServiceGrpcAsyncIOTransport]) -def test_model_service_transport_channel_mtls_with_adc( - transport_class -): - mock_ssl_cred = mock.Mock() - with mock.patch.multiple( - "google.auth.transport.grpc.SslCredentials", - __init__=mock.Mock(return_value=None), - ssl_credentials=mock.PropertyMock(return_value=mock_ssl_cred), - ): - with mock.patch.object(transport_class, "create_channel") as grpc_create_channel: - mock_grpc_channel = mock.Mock() - grpc_create_channel.return_value = mock_grpc_channel - mock_cred = mock.Mock() - - with pytest.warns(DeprecationWarning): - transport = transport_class( - host="squid.clam.whelk", - credentials=mock_cred, - api_mtls_endpoint="mtls.squid.clam.whelk", - client_cert_source=None, - ) - - grpc_create_channel.assert_called_once_with( - "mtls.squid.clam.whelk:443", - credentials=mock_cred, - credentials_file=None, - scopes=None, - ssl_credentials=mock_ssl_cred, - quota_project_id=None, - options=[ - ("grpc.max_send_message_length", -1), - ("grpc.max_receive_message_length", -1), - ], - ) - assert transport.grpc_channel == mock_grpc_channel - - -def test_common_billing_account_path(): - billing_account = "squid" - expected = "billingAccounts/{billing_account}".format(billing_account=billing_account, ) - actual = ModelServiceClient.common_billing_account_path(billing_account) - assert expected == actual - - -def test_parse_common_billing_account_path(): - expected = { - "billing_account": "clam", - } - path = ModelServiceClient.common_billing_account_path(**expected) - - # Check that the path construction is reversible. - actual = ModelServiceClient.parse_common_billing_account_path(path) - assert expected == actual - -def test_common_folder_path(): - folder = "whelk" - expected = "folders/{folder}".format(folder=folder, ) - actual = ModelServiceClient.common_folder_path(folder) - assert expected == actual - - -def test_parse_common_folder_path(): - expected = { - "folder": "octopus", - } - path = ModelServiceClient.common_folder_path(**expected) - - # Check that the path construction is reversible. - actual = ModelServiceClient.parse_common_folder_path(path) - assert expected == actual - -def test_common_organization_path(): - organization = "oyster" - expected = "organizations/{organization}".format(organization=organization, ) - actual = ModelServiceClient.common_organization_path(organization) - assert expected == actual - - -def test_parse_common_organization_path(): - expected = { - "organization": "nudibranch", - } - path = ModelServiceClient.common_organization_path(**expected) - - # Check that the path construction is reversible. - actual = ModelServiceClient.parse_common_organization_path(path) - assert expected == actual - -def test_common_project_path(): - project = "cuttlefish" - expected = "projects/{project}".format(project=project, ) - actual = ModelServiceClient.common_project_path(project) - assert expected == actual - - -def test_parse_common_project_path(): - expected = { - "project": "mussel", - } - path = ModelServiceClient.common_project_path(**expected) - - # Check that the path construction is reversible. - actual = ModelServiceClient.parse_common_project_path(path) - assert expected == actual - -def test_common_location_path(): - project = "winkle" - location = "nautilus" - expected = "projects/{project}/locations/{location}".format(project=project, location=location, ) - actual = ModelServiceClient.common_location_path(project, location) - assert expected == actual - - -def test_parse_common_location_path(): - expected = { - "project": "scallop", - "location": "abalone", - } - path = ModelServiceClient.common_location_path(**expected) - - # Check that the path construction is reversible. - actual = ModelServiceClient.parse_common_location_path(path) - assert expected == actual - - -def test_client_withDEFAULT_CLIENT_INFO(): - client_info = gapic_v1.client_info.ClientInfo() - - with mock.patch.object(transports.ModelServiceTransport, '_prep_wrapped_messages') as prep: - client = ModelServiceClient( - credentials=ga_credentials.AnonymousCredentials(), - client_info=client_info, - ) - prep.assert_called_once_with(client_info) - - with mock.patch.object(transports.ModelServiceTransport, '_prep_wrapped_messages') as prep: - transport_class = ModelServiceClient.get_transport_class() - transport = transport_class( - credentials=ga_credentials.AnonymousCredentials(), - client_info=client_info, - ) - prep.assert_called_once_with(client_info) From 6812f47d34fcfde3174a052b720b3fb50ff3986d Mon Sep 17 00:00:00 2001 From: Tres Seaver Date: Fri, 16 Jul 2021 17:00:41 -0400 Subject: [PATCH 3/4] fix: exclude copying microgenerated '.coveragrc' --- .coveragerc | 1 + owlbot.py | 1 + 2 files changed, 2 insertions(+) diff --git a/.coveragerc b/.coveragerc index 33ea00ba9..23861a8eb 100644 --- a/.coveragerc +++ b/.coveragerc @@ -2,6 +2,7 @@ branch = True [report] +fail_under = 100 show_missing = True omit = google/cloud/bigquery/__init__.py diff --git a/owlbot.py b/owlbot.py index 476c5ee5d..09845480a 100644 --- a/owlbot.py +++ b/owlbot.py @@ -70,6 +70,7 @@ library, excludes=[ "*.tar.gz", + ".coveragerc", "docs/index.rst", f"docs/bigquery_{library.name}/*_service.rst", f"docs/bigquery_{library.name}/services.rst", From ec603868fbc0481cc62242b8c60164b592a43c0b Mon Sep 17 00:00:00 2001 From: Tres Seaver Date: Fri, 16 Jul 2021 17:18:33 -0400 Subject: [PATCH 4/4] fix: add 'INTERVAL'/'JSON' to _SQL_SCALAR_TYPES --- google/cloud/bigquery/enums.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/google/cloud/bigquery/enums.py b/google/cloud/bigquery/enums.py index ef35dffe0..0da01d665 100644 --- a/google/cloud/bigquery/enums.py +++ b/google/cloud/bigquery/enums.py @@ -191,9 +191,11 @@ class KeyResultStatementKind: "DATE", "TIME", "DATETIME", + "INTERVAL", "GEOGRAPHY", "NUMERIC", "BIGNUMERIC", + "JSON", ) )