Allow reading beliefs from xlsx files, and from data files with multiple headers

flexmeasures/api/common/utils/api_utils.py

@@ -13,9 +13,7 @@
 from flexmeasures.data import db
 from flexmeasures.data.models.assets import Asset, Power
 from flexmeasures.data.models.markets import Market, Price
-from flexmeasures.data.models.data_sources import DataSource
 from flexmeasures.data.models.weather import WeatherSensor, Weather
-from flexmeasures.data.models.user import User
 from flexmeasures.data.utils import save_to_session
 from flexmeasures.utils.entity_address_utils import parse_entity_address
 from flexmeasures.api.common.responses import (
@@ -284,16 +282,6 @@ def asset_replace_name_with_id(connections_as_name: List[str]) -> List[str]:
     return connections_as_ea
 
 
-def get_or_create_user_data_source(user: User) -> DataSource:
-    data_source = DataSource.query.filter(DataSource.user == user).one_or_none()
-    if not data_source:
-        current_app.logger.info("SETTING UP USER AS NEW DATA SOURCE...")
-        data_source = DataSource(user=user)
-        db.session.add(data_source)
-        db.session.flush()  # flush so that we can reference the new object in the current db session
-    return data_source
-
-
 def get_weather_sensor_by(
     weather_sensor_type_name: str, latitude: float = 0, longitude: float = 0
 ) -> WeatherSensor:

flexmeasures/api/v1/implementations.py

@@ -12,6 +12,7 @@
     EntityAddressException,
 )
 from flexmeasures.data.models.assets import Asset, Power
+from flexmeasures.data.models.data_sources import get_or_create_source
 from flexmeasures.data.services.resources import get_assets
 from flexmeasures.data.services.forecasting import create_forecasting_jobs
 from flexmeasures.api.common.responses import (
@@ -24,7 +25,6 @@
 )
 from flexmeasures.api.common.utils.api_utils import (
     groups_to_dict,
-    get_or_create_user_data_source,
     save_to_db,
 )
 from flexmeasures.api.common.utils.validators import (
@@ -242,7 +242,7 @@ def create_connection_and_value_groups(  # noqa: C901
 
     current_app.logger.info("POSTING POWER DATA")
 
-    data_source = get_or_create_user_data_source(current_user)
+    data_source = get_or_create_source(current_user)
     user_assets = get_assets()
     if not user_assets:
         current_app.logger.info("User doesn't seem to have any assets")

flexmeasures/api/v1_1/implementations.py

@@ -16,7 +16,6 @@
 )
 from flexmeasures.api.common.utils.api_utils import (
     save_to_db,
-    get_or_create_user_data_source,
 )
 from flexmeasures.api.common.utils.validators import (
     type_accepted,
@@ -37,6 +36,7 @@
     create_connection_and_value_groups,
 )
 from flexmeasures.api.common.utils.api_utils import get_weather_sensor_by
+from flexmeasures.data.models.data_sources import get_or_create_source
 from flexmeasures.data.models.markets import Market, Price
 from flexmeasures.data.models.weather import Weather
 from flexmeasures.data.services.resources import get_assets
@@ -79,7 +79,7 @@ def post_price_data_response(
 
     current_app.logger.info("POSTING PRICE DATA")
 
-    data_source = get_or_create_user_data_source(current_user)
+    data_source = get_or_create_source(current_user)
     prices = []
     forecasting_jobs = []
     for market_group, value_group in zip(generic_asset_name_groups, value_groups):
@@ -154,7 +154,7 @@ def post_weather_data_response(  # noqa: C901
 
     current_app.logger.info("POSTING WEATHER DATA")
 
-    data_source = get_or_create_user_data_source(current_user)
+    data_source = get_or_create_source(current_user)
     weather_measurements = []
     forecasting_jobs = []
     for sensor_group, value_group in zip(generic_asset_name_groups, value_groups):

flexmeasures/api/v2_0/implementations/sensors.py

@@ -15,7 +15,6 @@
     ResponseTuple,
 )
 from flexmeasures.api.common.utils.api_utils import (
-    get_or_create_user_data_source,
     get_weather_sensor_by,
     save_to_db,
     determine_belief_timing,
@@ -33,6 +32,7 @@
     values_required,
 )
 from flexmeasures.data.models.assets import Asset, Power
+from flexmeasures.data.models.data_sources import get_or_create_source
 from flexmeasures.data.models.markets import Market, Price
 from flexmeasures.data.models.weather import Weather
 from flexmeasures.data.services.forecasting import create_forecasting_jobs
@@ -69,7 +69,7 @@ def post_price_data_response(  # noqa C901
 
     current_app.logger.info("POSTING PRICE DATA")
 
-    data_source = get_or_create_user_data_source(current_user)
+    data_source = get_or_create_source(current_user)
     prices = []
     forecasting_jobs = []
     for market_group, event_values in zip(generic_asset_name_groups, value_groups):
@@ -152,7 +152,7 @@ def post_weather_data_response(  # noqa: C901
 
     current_app.logger.info("POSTING WEATHER DATA")
 
-    data_source = get_or_create_user_data_source(current_user)
+    data_source = get_or_create_source(current_user)
     weather_measurements = []
     forecasting_jobs = []
     for sensor_group, event_values in zip(generic_asset_name_groups, value_groups):
@@ -301,7 +301,7 @@ def post_power_data(
 
     current_app.logger.info("POSTING POWER DATA")
 
-    data_source = get_or_create_user_data_source(current_user)
+    data_source = get_or_create_source(current_user)
     user_assets = get_assets()
     if not user_assets:
         current_app.logger.info("User doesn't seem to have any assets")

flexmeasures/data/migrations/versions/04f0e2d2924a_add_source_id_as_primary_key_for_timed_beliefs.py

@@ -0,0 +1,39 @@
+"""add source id as primary key for timed beliefs
+
+Revision ID: 04f0e2d2924a
+Revises: e62ac5f519d7
+Create Date: 2021-04-10 13:53:22.561718
+
+"""
+from alembic import op
+
+
+# revision identifiers, used by Alembic.
+revision = "04f0e2d2924a"
+down_revision = "e62ac5f519d7"
+branch_labels = None
+depends_on = None
+
+
+def upgrade():
+    op.drop_constraint("timed_belief_pkey", "timed_belief")
+    op.create_primary_key(
+        "timed_belief_pkey",
+        "timed_belief",
+        [
+            "event_start",
+            "belief_horizon",
+            "cumulative_probability",
+            "sensor_id",
+            "source_id",
+        ],
+    )
+
+
+def downgrade():
+    op.drop_constraint("timed_belief_pkey", "timed_belief")
+    op.create_primary_key(
+        "timed_belief_pkey",
+        "timed_belief",
+        ["event_start", "belief_horizon", "cumulative_probability", "sensor_id"],
+    )

flexmeasures/data/models/data_sources.py

@@ -1,9 +1,10 @@
-from typing import Optional
+from typing import Optional, Union
 
 import timely_beliefs as tb
+from flask import current_app
 
 from flexmeasures.data.config import db
-from flexmeasures.data.models.user import User
+from flexmeasures.data.models.user import User, is_user
 
 
 class DataSource(db.Model, tb.BeliefSourceDBMixin):
@@ -53,3 +54,33 @@ def label(self):
 
     def __repr__(self):
         return "<Data source %r (%s)>" % (self.id, self.label)
+
+
+def get_or_create_source(
+    source: Union[User, str], source_type: str = "user", flush: bool = True
+) -> DataSource:
+    query = DataSource.query.filter(DataSource.type == source_type)
+    if is_user(source):
+        query = query.filter(DataSource.user == source)
+    elif isinstance(source, str):
+        query = query.filter(DataSource.name == source)
+    else:
+        raise TypeError("source should be of type User or str")
+    _source = query.one_or_none()
+    if not _source:
+        current_app.logger.info(f"Setting up '{source}' as new data source...")
+        if is_user(source):
+            _source = DataSource(user=source)
+        else:
+            _source = DataSource(name=source, type=source_type)
+        db.session.add(_source)
+        if flush:
+            # assigns id so that we can reference the new object in the current db session
+            db.session.flush()
+    return _source
+
+
+def get_source_or_none(source: int, source_type: str) -> Optional[DataSource]:
+    query = DataSource.query.filter(DataSource.type == source_type)
+    query = query.filter(DataSource.id == int(source))
+    return query.one_or_none()

flexmeasures/data/models/user.py

@@ -98,3 +98,14 @@ def remember_login(the_app, user):
     if user.login_count is None:
         user.login_count = 0
     user.login_count = user.login_count + 1
+
+
+def is_user(o) -> bool:
+    """True if object is or proxies a User, False otherwise.
+
+    Takes into account that object can be of LocalProxy type, and
+    uses get_current_object to get the underlying (User) object.
+    """
+    return isinstance(o, User) or (
+        hasattr(o, "_get_current_object") and isinstance(o._get_current_object(), User)
+    )

flexmeasures/data/scripts/cli_tasks/data_add.py

@@ -20,7 +20,10 @@
 from flexmeasures.data.models.assets import Asset, AssetSchema
 from flexmeasures.data.models.markets import Market
 from flexmeasures.data.models.weather import WeatherSensor, WeatherSensorSchema
-from flexmeasures.data.models.data_sources import DataSource
+from flexmeasures.data.models.data_sources import (
+    get_or_create_source,
+    get_source_or_none,
+)
 from flexmeasures.utils.time_utils import server_now
 
 
@@ -220,6 +223,12 @@ def add_initial_structure():
     type=click.IntRange(min=1),
     help="Sensor to which the beliefs pertain.",
 )
+@click.option(
+    "--source",
+    required=True,
+    type=str,
+    help="Source of the beliefs (an existing source id or name, or a new name).",
+)
 @click.option(
     "--horizon",
     required=False,
@@ -238,16 +247,55 @@ def add_initial_structure():
     help="Allow overwriting possibly already existing data.\n"
     "Not allowing overwriting can be much more efficient",
 )
+@click.option(
+    "--skiprows",
+    required=False,
+    default=1,
+    type=int,
+    help="Number of rows to skip from the top. Set to >1 to skip additional headers.",
+)
+@click.option(
+    "--nrows",
+    required=False,
+    type=int,
+    help="Number of rows to read (from the top, after possibly skipping rows). Leave out to read all rows.",
+)
+@click.option(
+    "--datecol",
+    required=False,
+    default=0,
+    type=int,
+    help="Column number with datetimes (0 is 1st column, the default)",
+)
+@click.option(
+    "--valuecol",
+    required=False,
+    default=1,
+    type=int,
+    help="Column number with values (1 is 2nd column, the default)",
+)
+@click.option(
+    "--sheet_number",
+    required=False,
+    type=int,
+    help="[For xls or xlsx files] Sheet number with the data (0 is 1st sheet)",
+)
 def add_beliefs(
     file: str,
     sensor_id: int,
+    source: str,
     horizon: Optional[int] = None,
     cp: Optional[float] = None,
     allow_overwrite: bool = False,
+    skiprows: int = 1,
+    nrows: Optional[int] = None,
+    datecol: int = 0,
+    valuecol: int = 1,
+    sheet_number: Optional[int] = None,
 ):
-    """Add sensor data from a csv file.
+    """Add sensor data from a csv file (also accepts xls or xlsx).
 
-    Structure your csv file as follows:
+    To use default settings, structure your csv file as follows:
 
         - One header line (will be ignored!)
         - UTC datetimes in 1st column
@@ -267,30 +315,36 @@ def add_beliefs(
     if sensor is None:
         print(f"Failed to create beliefs: no sensor found with id {sensor_id}.")
         return
-    source = (
-        DataSource.query.filter(DataSource.name == "Seita")
-        .filter(DataSource.type == "CLI script")
-        .one_or_none()
-    )
-    if not source:
-        print("SETTING UP CLI SCRIPT AS NEW DATA SOURCE...")
-        source = DataSource(name="Seita", type="CLI script")
-        db.session.add(source)
-        db.session.flush()  # assigns id
+    if source.isdigit():
+        _source = get_source_or_none(int(source), source_type="CLI script")
+        if not _source:
+            print(f"Failed to find source {source}.")
+            return
+    else:
+        _source = get_or_create_source(source, source_type="CLI script")
+
+    # Set up optional parameters for read_csv
+    kwargs = dict()
+    if file.split(".")[-1].lower() == "csv":
+        kwargs["infer_datetime_format"] = True
+    if sheet_number is not None:
+        kwargs["sheet_name"] = sheet_number
+    if horizon is not None:
+        kwargs["belief_horizon"] = timedelta(minutes=horizon)
+    else:
+        kwargs["belief_time"] = server_now().astimezone(pytz.timezone(sensor.timezone))
+
     bdf = tb.read_csv(
         file,
         sensor,
-        source=source,
+        source=_source,
         cumulative_probability=cp,
+        header=None,
+        skiprows=skiprows,
+        nrows=nrows,
+        usecols=[datecol, valuecol],
         parse_dates=True,
-        infer_datetime_format=True,
-        **(
-            dict(belief_horizon=timedelta(minutes=horizon))
-            if horizon is not None
-            else dict(
-                belief_time=server_now().astimezone(pytz.timezone(sensor.timezone))
-            )
-        ),
+        **kwargs,
     )
     try:
         TimedBelief.add(

requirements/app.in

@@ -32,7 +32,7 @@ netCDF4
 siphon
 tables
 timetomodel>=0.6.8
-timely-beliefs>=1.4.0
+timely-beliefs>=1.4.3
 python-dotenv
 # a backport, not needed in Python3.8
 importlib_metadata

requirements/app.txt

@@ -317,7 +317,7 @@ tables==3.6.1
     # via -r requirements/app.in
 threadpoolctl==2.1.0
     # via scikit-learn
-timely-beliefs==1.4.0
+timely-beliefs==1.4.3
     # via -r requirements/app.in
 timetomodel==0.6.9
     # via -r requirements/app.in