Caltrain MCP Server

import pandas as pd from caltrain_mcp import gtfs def _make_data(): stations = pd.DataFrame( [ {"stop_id": "100", "stop_name": "San Francisco Caltrain", "location_type": 1}, { "stop_id": "110", "stop_name": "South San Francisco Caltrain", "location_type": 1, }, ] ) # Add normalized_name the same way as the loader does stations["normalized_name"] = ( stations["stop_name"] .str.lower() .str.replace(" station", "", regex=False) .str.replace(" caltrain", "", regex=False) ) # Minimal placeholders for unused GTFS tables all_stops = stations.copy() trips = pd.DataFrame(columns=["trip_id"]) # unused here stop_times = pd.DataFrame(columns=["trip_id"]) # unused here calendar = pd.DataFrame(columns=[ "service_id", "monday", "tuesday", "wednesday", "thursday", "friday", "saturday", "sunday", "start_date", "end_date", ]) return gtfs.GTFSData( all_stops=all_stops, stations=stations, trips=trips, stop_times=stop_times, calendar=calendar, station_to_platform_stops={}, ) def test_exact_match_beats_substring(): data = _make_data() # Should resolve to San Francisco, not South San Francisco assert gtfs.find_station("San Francisco", data) == "100" def test_prefix_match_preferred_over_substring(): data = _make_data() # "San" prefixes "San Francisco" but not "South San Francisco" assert gtfs.find_station("San", data) == "100" def test_prefix_south_san_resolves_south_sf(): data = _make_data() assert gtfs.find_station("South San", data) == "110" def test_abbreviation_ssf_points_to_south_sf(): data = _make_data() assert gtfs.find_station("ssf", data) == "110"