Add aggregate_orders() function
- the function queries the database and aggregates the ad-hoc orders by pixel and time steps into a demand time series - implement "heavy" integration tests for `aggregate_orders()` - make `pandas` a package dependency - streamline the `Config`
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1
tests/forecasts/__init__.py
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tests/forecasts/__init__.py
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"""Test the forecasting-related functionality."""
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305
tests/forecasts/test_timify.py
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tests/forecasts/test_timify.py
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"""Test the time series related code."""
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# pylint:disable=no-self-use,unused-argument
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import datetime
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import pytest
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from urban_meal_delivery import db
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from urban_meal_delivery.forecasts import timify
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YEAR, MONTH, DAY = 2020, 1, 1
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@pytest.mark.db
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class TestAggregateOrders:
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"""Test the `aggregate_orders()` function.
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The test cases are all integration tests that model realistic scenarios.
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"""
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@pytest.fixture
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def one_pixel_grid(self, db_session, city, restaurant):
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"""A persisted `Grid` with one `Pixel`.
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`restaurant` must be a dependency as otherwise
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its `.address` is not put into the database.
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"""
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# `+1` as otherwise there would be a second pixel in one direction.
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side_length = max(city.total_x, city.total_y) + 1
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grid = db.Grid.gridify(city=city, side_length=side_length)
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db_session.add(grid)
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assert len(grid.pixels) == 1 # sanity check
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return grid
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def test_no_orders(self, db_session, one_pixel_grid, restaurant):
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"""Edge case that does not occur for real-life data."""
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db_session.commit()
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assert len(restaurant.orders) == 0 # noqa:WPS507 sanity check
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result = timify.aggregate_orders(grid=one_pixel_grid, time_step=60)
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assert len(result) == 0 # noqa:WPS507
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def test_evenly_distributed_ad_hoc_orders(
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self, db_session, one_pixel_grid, restaurant, make_order,
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):
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"""12 ad-hoc orders, one per operating hour."""
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# Create one order per hour and 12 orders in total.
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for hour in range(11, 23):
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order = make_order(
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scheduled=False,
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restaurant=restaurant,
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placed_at=datetime.datetime(YEAR, MONTH, DAY, hour, 11),
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)
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db_session.add(order)
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db_session.commit()
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assert len(restaurant.orders) == 12 # sanity check
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result = timify.aggregate_orders(grid=one_pixel_grid, time_step=60)
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# The resulting `DataFrame` has 12 rows holding `1`s.
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assert len(result) == 12
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assert result['total_orders'].min() == 1
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assert result['total_orders'].max() == 1
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assert result['total_orders'].sum() == 12
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def test_evenly_distributed_ad_hoc_orders_with_no_demand_late( # noqa:WPS218
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self, db_session, one_pixel_grid, restaurant, make_order,
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):
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"""10 ad-hoc orders, one per hour, no orders after 21."""
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# Create one order per hour and 10 orders in total.
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for hour in range(11, 21):
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order = make_order(
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scheduled=False,
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restaurant=restaurant,
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placed_at=datetime.datetime(YEAR, MONTH, DAY, hour, 11),
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)
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db_session.add(order)
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db_session.commit()
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assert len(restaurant.orders) == 10 # sanity check
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result = timify.aggregate_orders(grid=one_pixel_grid, time_step=60)
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# Even though there are only 10 orders, there are 12 rows in the `DataFrame`.
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# That is so as `0`s are filled in for hours without any demand at the end.
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assert len(result) == 12
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assert result['total_orders'].min() == 0
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assert result['total_orders'].max() == 1
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assert result.iloc[:10]['total_orders'].sum() == 10
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assert result.iloc[10:]['total_orders'].sum() == 0
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def test_one_ad_hoc_order_every_other_hour(
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self, db_session, one_pixel_grid, restaurant, make_order,
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):
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"""6 ad-hoc orders, one every other hour."""
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# Create one order every other hour.
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for hour in range(11, 23, 2):
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order = make_order(
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scheduled=False,
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restaurant=restaurant,
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placed_at=datetime.datetime(YEAR, MONTH, DAY, hour, 11),
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)
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db_session.add(order)
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db_session.commit()
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assert len(restaurant.orders) == 6 # sanity check
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result = timify.aggregate_orders(grid=one_pixel_grid, time_step=60)
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# The resulting `DataFrame` has 12 rows, 6 holding `0`s, and 6 holding `1`s.
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assert len(result) == 12
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assert result['total_orders'].min() == 0
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assert result['total_orders'].max() == 1
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assert result['total_orders'].sum() == 6
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def test_one_ad_hoc_and_one_pre_order(
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self, db_session, one_pixel_grid, restaurant, make_order,
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):
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"""1 ad-hoc and 1 scheduled order.
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The scheduled order is discarded.
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"""
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ad_hoc_order = make_order(
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scheduled=False,
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restaurant=restaurant,
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placed_at=datetime.datetime(YEAR, MONTH, DAY, 11, 11),
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)
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db_session.add(ad_hoc_order)
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pre_order = make_order(
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scheduled=True,
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restaurant=restaurant,
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placed_at=datetime.datetime(YEAR, MONTH, DAY, 9, 0),
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scheduled_delivery_at=datetime.datetime(YEAR, MONTH, DAY, 12, 0),
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)
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db_session.add(pre_order)
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db_session.commit()
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assert len(restaurant.orders) == 2 # sanity check
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result = timify.aggregate_orders(grid=one_pixel_grid, time_step=60)
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# The resulting `DataFrame` has 12 rows, 11 holding `0`s, and one holding a `1`.
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assert len(result) == 12
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assert result['total_orders'].min() == 0
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assert result['total_orders'].max() == 1
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assert result['total_orders'].sum() == 1
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def test_evenly_distributed_ad_hoc_orders_with_half_hour_time_steps( # noqa:WPS218
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self, db_session, one_pixel_grid, restaurant, make_order,
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):
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"""12 ad-hoc orders, one per hour, with 30 minute time windows.
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In half the time steps, there is no demand.
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"""
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# Create one order per hour and 10 orders in total.
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for hour in range(11, 23):
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order = make_order(
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scheduled=False,
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restaurant=restaurant,
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placed_at=datetime.datetime(YEAR, MONTH, DAY, hour, 11),
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)
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db_session.add(order)
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db_session.commit()
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assert len(restaurant.orders) == 12 # sanity check
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result = timify.aggregate_orders(grid=one_pixel_grid, time_step=30)
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# The resulting `DataFrame` has 24 rows for the 24 30-minute time steps.
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# The rows' values are `0` and `1` alternating.
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assert len(result) == 24
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assert result['total_orders'].min() == 0
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assert result['total_orders'].max() == 1
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assert result.iloc[::2]['total_orders'].sum() == 12
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assert result.iloc[1::2]['total_orders'].sum() == 0
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def test_ad_hoc_orders_over_two_days(
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self, db_session, one_pixel_grid, restaurant, make_order,
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):
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"""First day 12 ad-hoc orders, one per operating hour ...
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... and 6 orders, one every other hour on the second day.
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In total, there are 18 orders.
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"""
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# Create one order per hour and 12 orders in total.
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for hour in range(11, 23):
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order = make_order(
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scheduled=False,
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restaurant=restaurant,
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placed_at=datetime.datetime(YEAR, MONTH, DAY, hour, 11),
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)
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db_session.add(order)
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# Create one order every other hour and 6 orders in total.
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for hour in range(11, 23, 2): # noqa:WPS440
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order = make_order(
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scheduled=False,
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restaurant=restaurant,
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placed_at=datetime.datetime(
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YEAR, MONTH, DAY + 1, hour, 11, # noqa:WPS441
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),
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)
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db_session.add(order)
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db_session.commit()
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assert len(restaurant.orders) == 18 # sanity check
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result = timify.aggregate_orders(grid=one_pixel_grid, time_step=60)
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# The resulting `DataFrame` has 24 rows, 12 for each day.
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assert len(result) == 24
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assert result['total_orders'].min() == 0
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assert result['total_orders'].max() == 1
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assert result['total_orders'].sum() == 18
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@pytest.fixture
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def two_pixel_grid(self, db_session, city, make_address, make_restaurant):
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"""A persisted `Grid` with two `Pixel` objects.
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`restaurant` must be a dependency as otherwise
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its `.address` is not put into the database.
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"""
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# One `Address` in the lower-left `Pixel`, ...
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address1 = make_address(latitude=48.8357377, longitude=2.2517412)
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# ... and another one in the upper-right one.
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address2 = make_address(latitude=48.8898312, longitude=2.4357622)
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# Create `Restaurant`s at the two addresses.
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make_restaurant(address=address1)
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make_restaurant(address=address2)
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# This creates four `Pixel`s, two of which have no `pickup_address`.
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side_length = max(city.total_x // 2, city.total_y // 2) + 1
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grid = db.Grid.gridify(city=city, side_length=side_length)
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db_session.add(grid)
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assert len(grid.pixels) == 2 # sanity check
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return grid
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def test_two_pixels_with_shifted_orders( # noqa:WPS218
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self, db_session, two_pixel_grid, make_order,
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):
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"""One restaurant with one order every other hour ...
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... and another restaurant with two orders per hour.
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In total, there are 30 orders.
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"""
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address1, address2 = two_pixel_grid.city.addresses
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restaurant1, restaurant2 = address1.restaurant, address2.restaurant
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# Create one order every other hour for `restaurant1`.
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for hour in range(11, 23, 2):
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order = make_order(
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scheduled=False,
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restaurant=restaurant1,
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placed_at=datetime.datetime(YEAR, MONTH, DAY, hour, 11),
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)
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db_session.add(order)
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# Create two orders per hour for `restaurant2`.
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for hour in range(11, 23): # noqa:WPS440
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order = make_order(
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scheduled=False,
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restaurant=restaurant2,
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placed_at=datetime.datetime(YEAR, MONTH, DAY, hour, 13), # noqa:WPS441
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)
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db_session.add(order)
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order = make_order(
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scheduled=False,
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restaurant=restaurant2,
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placed_at=datetime.datetime(YEAR, MONTH, DAY, hour, 14), # noqa:WPS441
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)
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db_session.add(order)
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db_session.commit()
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# sanity checks
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assert len(restaurant1.orders) == 6
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assert len(restaurant2.orders) == 24
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result = timify.aggregate_orders(grid=two_pixel_grid, time_step=60)
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# The resulting `DataFrame` has 24 rows, 12 for each pixel.
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assert len(result) == 24
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assert result['total_orders'].min() == 0
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assert result['total_orders'].max() == 2
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assert result['total_orders'].sum() == 30
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