Rename Forecast.training_horizon into .train_horizon

- we use that shorter name in `urban_meal_delivery.forecasts.*`
  and want to be consistent in the ORM layer as well

migrations/versions/rev_20210202_12_8bfb928a31f8_rename_training_horizon_into_train_horizon.py

@@ -0,0 +1,48 @@
+"""Rename `Forecast.training_horizon` into `.train_horizon`.
+
+Revision: #8bfb928a31f8 at 2021-02-02 12:55:09
+Revises: #c2af85bada01
+"""
+
+import os
+
+from alembic import op
+
+from urban_meal_delivery import configuration
+
+
+revision = '8bfb928a31f8'
+down_revision = 'c2af85bada01'
+branch_labels = None
+depends_on = None
+
+
+config = configuration.make_config('testing' if os.getenv('TESTING') else 'production')
+
+
+def upgrade():
+    """Upgrade to revision 8bfb928a31f8."""
+    op.execute(
+        f"""
+        ALTER TABLE
+            {config.CLEAN_SCHEMA}.forecasts
+        RENAME COLUMN
+            training_horizon
+            TO
+            train_horizon;
+        """,
+    )  # noqa:WPS355
+
+
+def downgrade():
+    """Downgrade to revision c2af85bada01."""
+    op.execute(
+        f"""
+        ALTER TABLE
+            {config.CLEAN_SCHEMA}.forecasts
+        RENAME COLUMN
+            train_horizon
+            TO
+            training_horizon;
+        """,
+    )  # noqa:WPS355

src/urban_meal_delivery/db/forecasts.py

@@ -27,7 +27,7 @@ class Forecast(meta.Base):
     pixel_id = sa.Column(sa.Integer, nullable=False, index=True)
     start_at = sa.Column(sa.DateTime, nullable=False)
     time_step = sa.Column(sa.SmallInteger, nullable=False)
-    training_horizon = sa.Column(sa.SmallInteger, nullable=False)
+    train_horizon = sa.Column(sa.SmallInteger, nullable=False)
     model = sa.Column(sa.Unicode(length=20), nullable=False)
     # We also store the actual order counts for convenient retrieval.
     # A `UniqueConstraint` below ensures that redundant values that
@@ -71,7 +71,7 @@ class Forecast(meta.Base):
         ),
         sa.CheckConstraint('time_step > 0', name='time_step_must_be_positive'),
         sa.CheckConstraint(
-            'training_horizon > 0', name='training_horizon_must_be_positive',
+            'train_horizon > 0', name='training_horizon_must_be_positive',
         ),
         sa.CheckConstraint('actual >= 0', name='actuals_must_be_non_negative'),
         sa.CheckConstraint(
@@ -124,7 +124,7 @@ class Forecast(meta.Base):
         ),
         # There can be only one prediction per forecasting setting.
         sa.UniqueConstraint(
-            'pixel_id', 'start_at', 'time_step', 'training_horizon', 'model',
+            'pixel_id', 'start_at', 'time_step', 'train_horizon', 'model',
         ),
     )
 
@@ -146,7 +146,7 @@ class Forecast(meta.Base):
         cls,
         pixel: db.Pixel,
         time_step: int,
-        training_horizon: int,
+        train_horizon: int,
         model: str,
         data: pd.Dataframe,
     ) -> List[db.Forecast]:
@@ -166,7 +166,7 @@ class Forecast(meta.Base):
         Args:
             pixel: in which the forecast is made
             time_step: length of one time step in minutes
-            training_horizon: length of the training horizon in weeks
+            train_horizon: length of the training horizon in weeks
             model: name of the forecasting model
             data: a `pd.Dataframe` as described above (i.e.,
                 with the six columns holding `float`s)
@@ -214,7 +214,7 @@ class Forecast(meta.Base):
                     pixel=pixel,
                     start_at=start_at,
                     time_step=time_step,
-                    training_horizon=training_horizon,
+                    train_horizon=train_horizon,
                     model=model,
                     actual=actual,
                     prediction=prediction,

src/urban_meal_delivery/forecasts/models/base.py

@@ -79,7 +79,7 @@ class ForecastingModelABC(abc.ABC):
             .filter_by(pixel=pixel)
             .filter_by(start_at=predict_at)
             .filter_by(time_step=self._order_history.time_step)
-            .filter_by(training_horizon=train_horizon)
+            .filter_by(train_horizon=train_horizon)
             .filter_by(model=self.name)
             .first()
         ) :
@@ -94,7 +94,7 @@ class ForecastingModelABC(abc.ABC):
         forecasts = db.Forecast.from_dataframe(
             pixel=pixel,
             time_step=self._order_history.time_step,
-            training_horizon=train_horizon,
+            train_horizon=train_horizon,
             model=self.name,
             data=predictions,
         )

tests/db/test_forecasts.py

@@ -28,7 +28,7 @@ def forecast(pixel):
         pixel=pixel,
         start_at=start_at,
         time_step=test_config.LONG_TIME_STEP,
-        training_horizon=test_config.LONG_TRAIN_HORIZON,
+        train_horizon=test_config.LONG_TRAIN_HORIZON,
         model=MODEL,
         actual=12,
         prediction=12.3,
@@ -143,9 +143,9 @@ class TestConstraints:
             db_session.commit()
 
     @pytest.mark.parametrize('value', [-1, 0])
-    def test_positive_training_horizon(self, db_session, forecast, value):
+    def test_positive_train_horizon(self, db_session, forecast, value):
         """Insert an instance with invalid data."""
-        forecast.training_horizon = value
+        forecast.train_horizon = value
         db_session.add(forecast)
 
         with pytest.raises(
@@ -418,7 +418,7 @@ class TestConstraints:
             pixel=forecast.pixel,
             start_at=forecast.start_at,
             time_step=forecast.time_step,
-            training_horizon=forecast.training_horizon,
+            train_horizon=forecast.train_horizon,
             model=forecast.model,
             actual=forecast.actual,
             prediction=2,
@@ -479,7 +479,7 @@ class TestFromDataFrameConstructor:
         forecasts = db.Forecast.from_dataframe(
             pixel=pixel,
             time_step=test_config.LONG_TIME_STEP,
-            training_horizon=test_config.LONG_TRAIN_HORIZON,
+            train_horizon=test_config.LONG_TRAIN_HORIZON,
             model=MODEL,
             data=prediction_data,
         )
@@ -496,7 +496,7 @@ class TestFromDataFrameConstructor:
         forecasts = db.Forecast.from_dataframe(
             pixel=pixel,
             time_step=test_config.LONG_TIME_STEP,
-            training_horizon=test_config.LONG_TRAIN_HORIZON,
+            train_horizon=test_config.LONG_TRAIN_HORIZON,
             model=MODEL,
             data=prediction_data,
         )

tests/forecasts/test_models.py

@@ -140,7 +140,7 @@ class TestGenericForecastingModelProperties:
         assert isinstance(result, db.Forecast)
         assert result.pixel == pixel
         assert result.start_at == predict_at
-        assert result.training_horizon == test_config.LONG_TRAIN_HORIZON
+        assert result.train_horizon == test_config.LONG_TRAIN_HORIZON
 
     @pytest.mark.db
     @pytest.mark.r