Add Forecast model to ORM layer

- the model handles the caching of demand forecasting results
- include the database migration script

src/urban_meal_delivery/db/__init__.py

@@ -8,6 +8,7 @@ from urban_meal_delivery.db.connection import engine
 from urban_meal_delivery.db.connection import session
 from urban_meal_delivery.db.couriers import Courier
 from urban_meal_delivery.db.customers import Customer
+from urban_meal_delivery.db.forecasts import Forecast
 from urban_meal_delivery.db.grids import Grid
 from urban_meal_delivery.db.meta import Base
 from urban_meal_delivery.db.orders import Order

src/urban_meal_delivery/db/forecasts.py

@@ -0,0 +1,66 @@
+"""Provide the ORM's `Forecast` model."""
+
+import sqlalchemy as sa
+from sqlalchemy import orm
+from sqlalchemy.dialects import postgresql
+
+from urban_meal_delivery.db import meta
+
+
+class Forecast(meta.Base):
+    """A demand forecast for a `.pixel` and `.time_step` pair.
+
+    This table is denormalized on purpose to keep things simple.
+    """
+
+    __tablename__ = 'forecasts'
+
+    # Columns
+    id = sa.Column(sa.Integer, primary_key=True, autoincrement=True)  # noqa:WPS125
+    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)
+    method = sa.Column(sa.Unicode(length=20), nullable=False)  # noqa:WPS432
+    # Raw `.prediction`s are stored as `float`s (possibly negative).
+    # The rounding is then done on the fly if required.
+    prediction = sa.Column(postgresql.DOUBLE_PRECISION, nullable=False)
+
+    # Constraints
+    __table_args__ = (
+        sa.ForeignKeyConstraint(
+            ['pixel_id'], ['pixels.id'], onupdate='RESTRICT', ondelete='RESTRICT',
+        ),
+        sa.CheckConstraint(
+            """
+                NOT (
+                    EXTRACT(HOUR FROM start_at) < 11
+                    OR
+                    EXTRACT(HOUR FROM start_at) > 22
+                )
+            """,
+            name='start_at_must_be_within_operating_hours',
+        ),
+        sa.CheckConstraint(
+            'CAST(EXTRACT(MINUTES FROM start_at) AS INTEGER) % 15 = 0',
+            name='start_at_minutes_must_be_quarters_of_the_hour',
+        ),
+        sa.CheckConstraint(
+            'EXTRACT(SECONDS FROM start_at) = 0', name='start_at_allows_no_seconds',
+        ),
+        sa.CheckConstraint(
+            'CAST(EXTRACT(MICROSECONDS FROM start_at) AS INTEGER) % 1000000 = 0',
+            name='start_at_allows_no_microseconds',
+        ),
+        sa.CheckConstraint('time_step > 0', name='time_step_must_be_positive'),
+        sa.CheckConstraint(
+            'training_horizon > 0', name='training_horizon_must_be_positive',
+        ),
+        # There can be only one prediction per forecasting setting.
+        sa.UniqueConstraint(
+            'pixel_id', 'start_at', 'time_step', 'training_horizon', 'method',
+        ),
+    )
+
+    # Relationships
+    pixel = orm.relationship('Pixel', back_populates='forecasts')

src/urban_meal_delivery/db/pixels.py

@@ -39,6 +39,7 @@ class Pixel(meta.Base):
     # Relationships
     grid = orm.relationship('Grid', back_populates='pixels')
     addresses = orm.relationship('AddressPixelAssociation', back_populates='pixel')
+    forecasts = orm.relationship('Forecast', back_populates='pixel')
 
     def __repr__(self) -> str:
         """Non-literal text representation."""