_helpers.py

# Copyright 2015 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.

"""Shared helper functions for BigQuery API classes."""

import base64
import datetime
import decimal
import re

from google.cloud._helpers import UTC
from google.cloud._helpers import _date_from_iso8601_date
from google.cloud._helpers import _datetime_from_microseconds
from google.cloud._helpers import _RFC3339_MICROS
from google.cloud._helpers import _RFC3339_NO_FRACTION
from google.cloud._helpers import _to_bytes

_RFC3339_MICROS_NO_ZULU = "%Y-%m-%dT%H:%M:%S.%f"
_TIMEONLY_WO_MICROS = "%H:%M:%S"
_TIMEONLY_W_MICROS = "%H:%M:%S.%f"
_PROJECT_PREFIX_PATTERN = re.compile(
    r"""
    (?P<project_id>\S+\:[^.]+)\.(?P<dataset_id>[^.]+)(?:$|\.(?P<custom_id>[^.]+)$)
""",
    re.VERBOSE,
)


def _not_null(value, field):
    """Check whether 'value' should be coerced to 'field' type."""
    return value is not None or (field is not None and field.mode != "NULLABLE")


def _int_from_json(value, field):
    """Coerce 'value' to an int, if set or not nullable."""
    if _not_null(value, field):
        return int(value)


def _float_from_json(value, field):
    """Coerce 'value' to a float, if set or not nullable."""
    if _not_null(value, field):
        return float(value)


def _decimal_from_json(value, field):
    """Coerce 'value' to a Decimal, if set or not nullable."""
    if _not_null(value, field):
        return decimal.Decimal(value)


def _bool_from_json(value, field):
    """Coerce 'value' to a bool, if set or not nullable."""
    if _not_null(value, field):
        return value.lower() in ["t", "true", "1"]


def _string_from_json(value, _):
    """NOOP string -> string coercion"""
    return value


def _bytes_from_json(value, field):
    """Base64-decode value"""
    if _not_null(value, field):
        return base64.standard_b64decode(_to_bytes(value))


def _timestamp_from_json(value, field):
    """Coerce 'value' to a datetime, if set or not nullable."""
    if _not_null(value, field):
        # value will be a integer in seconds, to microsecond precision, in UTC.
        return _datetime_from_microseconds(int(value))


def _timestamp_query_param_from_json(value, field):
    """Coerce 'value' to a datetime, if set or not nullable.

    Args:
        value (str): The timestamp.

        field (google.cloud.bigquery.schema.SchemaField):
            The field corresponding to the value.

    Returns:
        Optional[datetime.datetime]:
            The parsed datetime object from
            ``value`` if the ``field`` is not null (otherwise it is
            :data:`None`).
    """
    if _not_null(value, field):
        # Canonical formats for timestamps in BigQuery are flexible. See:
        # g.co/cloud/bigquery/docs/reference/standard-sql/data-types#timestamp-type
        # The separator between the date and time can be 'T' or ' '.
        value = value.replace(" ", "T", 1)
        # The UTC timezone may be formatted as Z or +00:00.
        value = value.replace("Z", "")
        value = value.replace("+00:00", "")

        if "." in value:
            # YYYY-MM-DDTHH:MM:SS.ffffff
            return datetime.datetime.strptime(value, _RFC3339_MICROS_NO_ZULU).replace(
                tzinfo=UTC
            )
        else:
            # YYYY-MM-DDTHH:MM:SS
            return datetime.datetime.strptime(value, _RFC3339_NO_FRACTION).replace(
                tzinfo=UTC
            )
    else:
        return None


def _datetime_from_json(value, field):
    """Coerce 'value' to a datetime, if set or not nullable.

    Args:
        value (str): The timestamp.
        field (google.cloud.bigquery.schema.SchemaField):
            The field corresponding to the value.

    Returns:
        Optional[datetime.datetime]:
            The parsed datetime object from
            ``value`` if the ``field`` is not null (otherwise it is
            :data:`None`).
    """
    if _not_null(value, field):
        if "." in value:
            # YYYY-MM-DDTHH:MM:SS.ffffff
            return datetime.datetime.strptime(value, _RFC3339_MICROS_NO_ZULU)
        else:
            # YYYY-MM-DDTHH:MM:SS
            return datetime.datetime.strptime(value, _RFC3339_NO_FRACTION)
    else:
        return None


def _date_from_json(value, field):
    """Coerce 'value' to a datetime date, if set or not nullable"""
    if _not_null(value, field):
        # value will be a string, in YYYY-MM-DD form.
        return _date_from_iso8601_date(value)


def _time_from_json(value, field):
    """Coerce 'value' to a datetime date, if set or not nullable"""
    if _not_null(value, field):
        if len(value) == 8:  # HH:MM:SS
            fmt = _TIMEONLY_WO_MICROS
        elif len(value) == 15:  # HH:MM:SS.micros
            fmt = _TIMEONLY_W_MICROS
        else:
            raise ValueError("Unknown time format: {}".format(value))
        return datetime.datetime.strptime(value, fmt).time()


def _record_from_json(value, field):
    """Coerce 'value' to a mapping, if set or not nullable."""
    if _not_null(value, field):
        record = {}
        record_iter = zip(field.fields, value["f"])
        for subfield, cell in record_iter:
            converter = _CELLDATA_FROM_JSON[subfield.field_type]
            if subfield.mode == "REPEATED":
                value = [converter(item["v"], subfield) for item in cell["v"]]
            else:
                value = converter(cell["v"], subfield)
            record[subfield.name] = value
        return record


_CELLDATA_FROM_JSON = {
    "INTEGER": _int_from_json,
    "INT64": _int_from_json,
    "FLOAT": _float_from_json,
    "FLOAT64": _float_from_json,
    "NUMERIC": _decimal_from_json,
    "BIGNUMERIC": _decimal_from_json,
    "BOOLEAN": _bool_from_json,
    "BOOL": _bool_from_json,
    "STRING": _string_from_json,
    "GEOGRAPHY": _string_from_json,
    "BYTES": _bytes_from_json,
    "TIMESTAMP": _timestamp_from_json,
    "DATETIME": _datetime_from_json,
    "DATE": _date_from_json,
    "TIME": _time_from_json,
    "RECORD": _record_from_json,
}

_QUERY_PARAMS_FROM_JSON = dict(_CELLDATA_FROM_JSON)
_QUERY_PARAMS_FROM_JSON["TIMESTAMP"] = _timestamp_query_param_from_json


def _field_to_index_mapping(schema):
    """Create a mapping from schema field name to index of field."""
    return {f.name: i for i, f in enumerate(schema)}


def _field_from_json(resource, field):
    converter = _CELLDATA_FROM_JSON.get(field.field_type, lambda value, _: value)
    if field.mode == "REPEATED":
        return [converter(item["v"], field) for item in resource]
    else:
        return converter(resource, field)


def _row_tuple_from_json(row, schema):
    """Convert JSON row data to row with appropriate types.

    Note:  ``row['f']`` and ``schema`` are presumed to be of the same length.

    Args:
        row (Dict): A JSON response row to be converted.
        schema (Sequence[Union[ \
                :class:`~google.cloud.bigquery.schema.SchemaField`, \
                Mapping[str, Any] \
        ]]):  Specification of the field types in ``row``.

    Returns:
        Tuple: A tuple of data converted to native types.
    """
    from google.cloud.bigquery.schema import _to_schema_fields

    schema = _to_schema_fields(schema)

    row_data = []
    for field, cell in zip(schema, row["f"]):
        row_data.append(_field_from_json(cell["v"], field))
    return tuple(row_data)


def _rows_from_json(values, schema):
    """Convert JSON row data to rows with appropriate types.

    Args:
        values (Sequence[Dict]): The list of responses (JSON rows) to convert.
        schema (Sequence[Union[ \
                :class:`~google.cloud.bigquery.schema.SchemaField`, \
                Mapping[str, Any] \
        ]]):
            The table's schema. If any item is a mapping, its content must be
            compatible with
            :meth:`~google.cloud.bigquery.schema.SchemaField.from_api_repr`.

    Returns:
        List[:class:`~google.cloud.bigquery.Row`]
    """
    from google.cloud.bigquery import Row
    from google.cloud.bigquery.schema import _to_schema_fields

    schema = _to_schema_fields(schema)
    field_to_index = _field_to_index_mapping(schema)
    return [Row(_row_tuple_from_json(r, schema), field_to_index) for r in values]


def _int_to_json(value):
    """Coerce 'value' to an JSON-compatible representation."""
    if isinstance(value, int):
        value = str(value)
    return value


def _float_to_json(value):
    """Coerce 'value' to an JSON-compatible representation."""
    return value


def _decimal_to_json(value):
    """Coerce 'value' to a JSON-compatible representation."""
    if isinstance(value, decimal.Decimal):
        value = str(value)
    return value


def _bool_to_json(value):
    """Coerce 'value' to an JSON-compatible representation."""
    if isinstance(value, bool):
        value = "true" if value else "false"
    return value


def _bytes_to_json(value):
    """Coerce 'value' to an JSON-compatible representation."""
    if isinstance(value, bytes):
        value = base64.standard_b64encode(value).decode("ascii")
    return value


def _timestamp_to_json_parameter(value):
    """Coerce 'value' to an JSON-compatible representation.

    This version returns the string representation used in query parameters.
    """
    if isinstance(value, datetime.datetime):
        if value.tzinfo not in (None, UTC):
            # Convert to UTC and remove the time zone info.
            value = value.replace(tzinfo=None) - value.utcoffset()
        value = "%s %s+00:00" % (value.date().isoformat(), value.time().isoformat())
    return value


def _timestamp_to_json_row(value):
    """Coerce 'value' to an JSON-compatible representation."""
    if isinstance(value, datetime.datetime):
        # For naive datetime objects UTC timezone is assumed, thus we format
        # those to string directly without conversion.
        if value.tzinfo is not None:
            value = value.astimezone(UTC)
        value = value.strftime(_RFC3339_MICROS)
    return value


def _datetime_to_json(value):
    """Coerce 'value' to an JSON-compatible representation."""
    if isinstance(value, datetime.datetime):
        # For naive datetime objects UTC timezone is assumed, thus we format
        # those to string directly without conversion.
        if value.tzinfo is not None:
            value = value.astimezone(UTC)
        value = value.strftime(_RFC3339_MICROS_NO_ZULU)
    return value


def _date_to_json(value):
    """Coerce 'value' to an JSON-compatible representation."""
    if isinstance(value, datetime.date):
        value = value.isoformat()
    return value


def _time_to_json(value):
    """Coerce 'value' to an JSON-compatible representation."""
    if isinstance(value, datetime.time):
        value = value.isoformat()
    return value


# Converters used for scalar values marshalled as row data.
_SCALAR_VALUE_TO_JSON_ROW = {
    "INTEGER": _int_to_json,
    "INT64": _int_to_json,
    "FLOAT": _float_to_json,
    "FLOAT64": _float_to_json,
    "NUMERIC": _decimal_to_json,
    "BIGNUMERIC": _decimal_to_json,
    "BOOLEAN": _bool_to_json,
    "BOOL": _bool_to_json,
    "BYTES": _bytes_to_json,
    "TIMESTAMP": _timestamp_to_json_row,
    "DATETIME": _datetime_to_json,
    "DATE": _date_to_json,
    "TIME": _time_to_json,
}


# Converters used for scalar values marshalled as query parameters.
_SCALAR_VALUE_TO_JSON_PARAM = _SCALAR_VALUE_TO_JSON_ROW.copy()
_SCALAR_VALUE_TO_JSON_PARAM["TIMESTAMP"] = _timestamp_to_json_parameter


def _scalar_field_to_json(field, row_value):
    """Maps a field and value to a JSON-safe value.

    Args:
        field (google.cloud.bigquery.schema.SchemaField):
            The SchemaField to use for type conversion and field name.
        row_value (Any):
            Value to be converted, based on the field's type.

    Returns:
        Any: A JSON-serializable object.
    """
    converter = _SCALAR_VALUE_TO_JSON_ROW.get(field.field_type)
    if converter is None:  # STRING doesn't need converting
        return row_value
    return converter(row_value)


def _repeated_field_to_json(field, row_value):
    """Convert a repeated/array field to its JSON representation.

    Args:
        field (google.cloud.bigquery.schema.SchemaField):
            The SchemaField to use for type conversion and field name. The
            field mode must equal ``REPEATED``.
        row_value (Sequence[Any]):
            A sequence of values to convert to JSON-serializable values.

    Returns:
        List[Any]: A list of JSON-serializable objects.
    """
    values = []
    for item in row_value:
        values.append(_single_field_to_json(field, item))
    return values


def _record_field_to_json(fields, row_value):
    """Convert a record/struct field to its JSON representation.

    Args:
        fields (Sequence[google.cloud.bigquery.schema.SchemaField]):
            The :class:`~google.cloud.bigquery.schema.SchemaField`s of the
            record's subfields to use for type conversion and field names.
        row_value (Union[Tuple[Any], Mapping[str, Any]):
            A tuple or dictionary to convert to JSON-serializable values.

    Returns:
        Mapping[str, Any]: A JSON-serializable dictionary.
    """
    isdict = isinstance(row_value, dict)

    # If row is passed as a tuple, make the length sanity check to avoid either
    # uninformative index errors a few lines below or silently omitting some of
    # the values from the result (we cannot know exactly which fields are missing
    # or redundant, since we don't have their names).
    if not isdict and len(row_value) != len(fields):
        msg = "The number of row fields ({}) does not match schema length ({}).".format(
            len(row_value), len(fields)
        )
        raise ValueError(msg)

    record = {}

    if isdict:
        processed_fields = set()

    for subindex, subfield in enumerate(fields):
        subname = subfield.name
        subvalue = row_value.get(subname) if isdict else row_value[subindex]

        # None values are unconditionally omitted
        if subvalue is not None:
            record[subname] = _field_to_json(subfield, subvalue)

        if isdict:
            processed_fields.add(subname)

    # Unknown fields should not be silently dropped, include them. Since there
    # is no schema information available for them, include them as strings
    # to make them JSON-serializable.
    if isdict:
        not_processed = set(row_value.keys()) - processed_fields

        for field_name in not_processed:
            value = row_value[field_name]
            if value is not None:
                record[field_name] = str(value)

    return record


def _single_field_to_json(field, row_value):
    """Convert a single field into JSON-serializable values.

    Ignores mode so that this can function for ARRAY / REPEATING fields
    without requiring a deepcopy of the field. See:
    https://github.com/googleapis/python-bigquery/issues/6

    Args:
        field (google.cloud.bigquery.schema.SchemaField):
            The SchemaField to use for type conversion and field name.

        row_value (Any):
            Scalar or Struct to be inserted. The type
            is inferred from the SchemaField's field_type.

    Returns:
        Any: A JSON-serializable object.
    """
    if row_value is None:
        return None

    if field.field_type == "RECORD":
        return _record_field_to_json(field.fields, row_value)

    return _scalar_field_to_json(field, row_value)


def _field_to_json(field, row_value):
    """Convert a field into JSON-serializable values.

    Args:
        field (google.cloud.bigquery.schema.SchemaField):
            The SchemaField to use for type conversion and field name.

        row_value (Union[Sequence[List], Any]):
            Row data to be inserted. If the SchemaField's mode is
            REPEATED, assume this is a list. If not, the type
            is inferred from the SchemaField's field_type.

    Returns:
        Any: A JSON-serializable object.
    """
    if row_value is None:
        return None

    if field.mode == "REPEATED":
        return _repeated_field_to_json(field, row_value)

    return _single_field_to_json(field, row_value)


def _snake_to_camel_case(value):
    """Convert snake case string to camel case."""
    words = value.split("_")
    return words[0] + "".join(map(str.capitalize, words[1:]))


def _get_sub_prop(container, keys, default=None):
    """Get a nested value from a dictionary.

    This method works like ``dict.get(key)``, but for nested values.

    Args:
        container (Dict):
            A dictionary which may contain other dictionaries as values.
        keys (Iterable):
            A sequence of keys to attempt to get the value for. Each item in
            the sequence represents a deeper nesting. The first key is for
            the top level. If there is a dictionary there, the second key
            attempts to get the value within that, and so on.
        default (Optional[object]):
            Value to returned if any of the keys are not found.
            Defaults to ``None``.

    Examples:
        Get a top-level value (equivalent to ``container.get('key')``).

        >>> _get_sub_prop({'key': 'value'}, ['key'])
        'value'

        Get a top-level value, providing a default (equivalent to
        ``container.get('key', default='default')``).

        >>> _get_sub_prop({'nothere': 123}, ['key'], default='not found')
        'not found'

        Get a nested value.

        >>> _get_sub_prop({'key': {'subkey': 'value'}}, ['key', 'subkey'])
        'value'

    Returns:
        object: The value if present or the default.
    """
    sub_val = container
    for key in keys:
        if key not in sub_val:
            return default
        sub_val = sub_val[key]
    return sub_val


def _set_sub_prop(container, keys, value):
    """Set a nested value in a dictionary.

    Args:
        container (Dict):
            A dictionary which may contain other dictionaries as values.
        keys (Iterable):
            A sequence of keys to attempt to set the value for. Each item in
            the sequence represents a deeper nesting. The first key is for
            the top level. If there is a dictionary there, the second key
            attempts to get the value within that, and so on.
        value (object): Value to set within the container.

    Examples:
        Set a top-level value (equivalent to ``container['key'] = 'value'``).

        >>> container = {}
        >>> _set_sub_prop(container, ['key'], 'value')
        >>> container
        {'key': 'value'}

        Set a nested value.

        >>> container = {}
        >>> _set_sub_prop(container, ['key', 'subkey'], 'value')
        >>> container
        {'key': {'subkey': 'value'}}

        Replace a nested value.

        >>> container = {'key': {'subkey': 'prev'}}
        >>> _set_sub_prop(container, ['key', 'subkey'], 'new')
        >>> container
        {'key': {'subkey': 'new'}}
    """
    sub_val = container
    for key in keys[:-1]:
        if key not in sub_val:
            sub_val[key] = {}
        sub_val = sub_val[key]
    sub_val[keys[-1]] = value


def _del_sub_prop(container, keys):
    """Remove a nested key fro a dictionary.

    Args:
        container (Dict):
            A dictionary which may contain other dictionaries as values.
        keys (Iterable):
            A sequence of keys to attempt to clear the value for. Each item in
            the sequence represents a deeper nesting. The first key is for
            the top level. If there is a dictionary there, the second key
            attempts to get the value within that, and so on.

    Examples:
        Remove a top-level value (equivalent to ``del container['key']``).

        >>> container = {'key': 'value'}
        >>> _del_sub_prop(container, ['key'])
        >>> container
        {}

        Remove a nested value.

        >>> container = {'key': {'subkey': 'value'}}
        >>> _del_sub_prop(container, ['key', 'subkey'])
        >>> container
        {'key': {}}
    """
    sub_val = container
    for key in keys[:-1]:
        if key not in sub_val:
            sub_val[key] = {}
        sub_val = sub_val[key]
    if keys[-1] in sub_val:
        del sub_val[keys[-1]]


def _int_or_none(value):
    """Helper: deserialize int value from JSON string."""
    if isinstance(value, int):
        return value
    if value is not None:
        return int(value)


def _str_or_none(value):
    """Helper: serialize value to JSON string."""
    if value is not None:
        return str(value)


def _split_id(full_id):
    """Helper: split full_id into composite parts.

    Args:
        full_id (str): Fully-qualified ID in standard SQL format.

    Returns:
        List[str]: ID's parts separated into components.
    """
    with_prefix = _PROJECT_PREFIX_PATTERN.match(full_id)
    if with_prefix is None:
        parts = full_id.split(".")
    else:
        parts = with_prefix.groups()
        parts = [part for part in parts if part]
    return parts


def _parse_3_part_id(full_id, default_project=None, property_name="table_id"):
    output_project_id = default_project
    output_dataset_id = None
    output_resource_id = None
    parts = _split_id(full_id)

    if len(parts) != 2 and len(parts) != 3:
        raise ValueError(
            "{property_name} must be a fully-qualified ID in "
            'standard SQL format, e.g., "project.dataset.{property_name}", '
            "got {}".format(full_id, property_name=property_name)
        )

    if len(parts) == 2 and not default_project:
        raise ValueError(
            "When default_project is not set, {property_name} must be a "
            "fully-qualified ID in standard SQL format, "
            'e.g., "project.dataset_id.{property_name}", got {}'.format(
                full_id, property_name=property_name
            )
        )

    if len(parts) == 2:
        output_dataset_id, output_resource_id = parts
    else:
        output_project_id, output_dataset_id, output_resource_id = parts

    return output_project_id, output_dataset_id, output_resource_id


def _build_resource_from_properties(obj, filter_fields):
    """Build a resource based on a ``_properties`` dictionary, filtered by
    ``filter_fields``, which follow the name of the Python object.
    """
    partial = {}
    for filter_field in filter_fields:
        api_field = obj._PROPERTY_TO_API_FIELD.get(filter_field)
        if api_field is None and filter_field not in obj._properties:
            raise ValueError("No property %s" % filter_field)
        elif api_field is not None:
            partial[api_field] = obj._properties.get(api_field)
        else:
            # allows properties that are not defined in the library
            # and properties that have the same name as API resource key
            partial[filter_field] = obj._properties[filter_field]

    return partial


def _verify_job_config_type(job_config, expected_type, param_name="job_config"):
    if not isinstance(job_config, expected_type):
        msg = (
            "Expected an instance of {expected_type} class for the {param_name} parameter, "
            "but received {param_name} = {job_config}"
        )
        raise TypeError(
            msg.format(
                expected_type=expected_type.__name__,
                param_name=param_name,
                job_config=job_config,
            )
        )