From a5b590b24c6e78c9f1c07355282a6d88db5854e7 Mon Sep 17 00:00:00 2001
From: Alexander Hess <alexander@webartifex.biz>
Date: Sun, 31 Jan 2021 18:29:53 +0100
Subject: [PATCH] Add `Forecast.actual` column

---
 ...2af85bada01_store_actuals_with_forecast.py | 41 +++++++++++++++++++
 src/urban_meal_delivery/db/forecasts.py       |  5 +++
 tests/db/test_forecasts.py                    | 12 ++++++
 3 files changed, 58 insertions(+)
 create mode 100644 migrations/versions/rev_20210129_11_c2af85bada01_store_actuals_with_forecast.py

diff --git a/migrations/versions/rev_20210129_11_c2af85bada01_store_actuals_with_forecast.py b/migrations/versions/rev_20210129_11_c2af85bada01_store_actuals_with_forecast.py
new file mode 100644
index 0000000..810fbb5
--- /dev/null
+++ b/migrations/versions/rev_20210129_11_c2af85bada01_store_actuals_with_forecast.py
@@ -0,0 +1,41 @@
+"""Store actuals with forecast.
+
+Revision: #c2af85bada01 at 2021-01-29 11:13:15
+Revises: #e86290e7305e
+"""
+
+import os
+
+import sqlalchemy as sa
+from alembic import op
+
+from urban_meal_delivery import configuration
+
+
+revision = 'c2af85bada01'
+down_revision = 'e86290e7305e'
+branch_labels = None
+depends_on = None
+
+
+config = configuration.make_config('testing' if os.getenv('TESTING') else 'production')
+
+
+def upgrade():
+    """Upgrade to revision c2af85bada01."""
+    op.add_column(
+        'forecasts',
+        sa.Column('actual', sa.SmallInteger(), nullable=False),
+        schema=config.CLEAN_SCHEMA,
+    )
+    op.create_check_constraint(
+        op.f('ck_forecasts_on_actuals_must_be_non_negative'),
+        'forecasts',
+        'actual >= 0',
+        schema=config.CLEAN_SCHEMA,
+    )
+
+
+def downgrade():
+    """Downgrade to revision e86290e7305e."""
+    op.drop_column('forecasts', 'actual', schema=config.CLEAN_SCHEMA)
diff --git a/src/urban_meal_delivery/db/forecasts.py b/src/urban_meal_delivery/db/forecasts.py
index 2edb695..f9ebc44 100644
--- a/src/urban_meal_delivery/db/forecasts.py
+++ b/src/urban_meal_delivery/db/forecasts.py
@@ -22,6 +22,10 @@ class Forecast(meta.Base):
     time_step = sa.Column(sa.SmallInteger, nullable=False)
     training_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
+    # are to be expected are consistend across rows.
+    actual = sa.Column(sa.SmallInteger, nullable=False)
     # 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)
@@ -62,6 +66,7 @@ class Forecast(meta.Base):
         sa.CheckConstraint(
             'training_horizon > 0', name='training_horizon_must_be_positive',
         ),
+        sa.CheckConstraint('actual >= 0', name='actuals_must_be_non_negative'),
         sa.CheckConstraint(
             """
                 NOT (
diff --git a/tests/db/test_forecasts.py b/tests/db/test_forecasts.py
index 426de7b..d6780df 100644
--- a/tests/db/test_forecasts.py
+++ b/tests/db/test_forecasts.py
@@ -18,6 +18,7 @@ def forecast(pixel):
         time_step=60,
         training_horizon=8,
         model='hets',
+        actual=12,
         prediction=12.3,
         low80=1.23,
         high80=123.4,
@@ -131,6 +132,16 @@ class TestConstraints:
         ):
             db_session.commit()
 
+    def test_non_negative_actuals(self, db_session, forecast):
+        """Insert an instance with invalid data."""
+        forecast.actual = -1
+        db_session.add(forecast)
+
+        with pytest.raises(
+            sa_exc.IntegrityError, match='actuals_must_be_non_negative',
+        ):
+            db_session.commit()
+
     def test_set_prediction_without_ci(self, db_session, forecast):
         """Sanity check to see that the check constraint ...
 
@@ -388,6 +399,7 @@ class TestConstraints:
             time_step=forecast.time_step,
             training_horizon=forecast.training_horizon,
             model=forecast.model,
+            actual=forecast.actual,
             prediction=2,
             low80=1,
             high80=3,