perfect-postcode/pipeline/transform/test_poi_proximity.py
2026-05-12 22:00:56 +01:00

55 lines
1.6 KiB
Python

import polars as pl
from pipeline.transform.poi_proximity import (
_build_poi_category_groups,
_dynamic_poi_metric_renames,
)
def test_dynamic_poi_groups_include_requested_categories_only() -> None:
pois = pl.DataFrame(
{
"group": (
["Public Transport"] * 2
+ ["Leisure"] * 2
+ ["Groceries"] * 101
+ ["Groceries"] * 100
+ ["Leisure"] * 10
+ ["Education"] * 200
+ ["Health"] * 200
),
"category": (
["Rail station", "Bus stop"]
+ ["Café", "Restaurant"]
+ ["Tesco"] * 101
+ ["Waitrose"] * 100
+ ["Park"] * 10
+ ["School"] * 200
+ ["Pharmacy"] * 200
),
"lat": [51.5] * 615,
"lng": [-0.1] * 615,
}
)
groups, display_names = _build_poi_category_groups(pois)
assert set(display_names.values()) == {
"Bus stop",
"Café",
"Rail station",
"Restaurant",
"Tesco",
}
assert "poi_waitrose" not in groups
assert "poi_park" not in groups
assert "poi_school" not in groups
assert "poi_pharmacy" not in groups
def test_dynamic_poi_metric_renames_support_park_count_options() -> None:
assert _dynamic_poi_metric_renames({"parks": "Park"}) == {
"parks_nearest_km": "Distance to nearest amenity (Park) (km)",
"parks_2km": "Number of amenities (Park) within 2km",
"parks_5km": "Number of amenities (Park) within 5km",
}