egutierrez
dabc945eda
Extrae al registry funciones del proyecto interno footprint_aurgi: - core (6): slugify_ascii, normalize_for_join, cp_provincia_es, infer_provincia_from_cp, safe_read_csv_fallback, csv_to_parquet_duckdb - geo puras (7): haversine_km, point_in_ring, point_in_polygon, point_in_polygons_bbox, polygon_bbox, extent_with_padding, distance_bucket - geo I/O (4): load_geojson_polygons, load_boundary_gdf, add_basemap_osm, add_basemap_with_timeout - valhalla client (4): valhalla_route, valhalla_isochrone, valhalla_isochrones_async, valhalla_matrix_1_to_n - datascience stats (7): trimmed_mean, geometric_mean, detect_distribution_type, best_central_tendency, summary_stats, kde_density_levels, alpha_shape_concave_hull - datascience fuzzy (3): fuzzy_merge_adaptive (rapidfuzz), words_to_dataset, remove_words_from_column - datascience viz (2): plot_kde_2d, plot_heatmap_log - infra (4): compress_pdf_ghostscript, render_table_page_pdfpages, add_header_logo, osm2pgsql_ingest - pipelines (4): setup_geo_stack_docker, compute_centers_reachability, generate_isochrones_by_zone, count_points_per_zone - types geo (4): LonLat, BBox, IsochroneRequest, Centro Incluye: - apps/footprint_geo_stack/ (PostGIS + Martin + Valhalla via docker-compose) - 131/132 tests pasan (1 skip esperado: osm2pgsql en PATH) - Issue tracker dev/issues/0052-footprint-aurgi-extraction.md - Atribucion uniforme: source_repo internal:footprint_aurgi, source_license internal-aurgi - Build con 9 agentes en paralelo (8 wave 1 + 1 wave 2 pipelines) Tambien commitea trabajo previo no commiteado: aggregate_extraction_results, chunk_with_overlap, clean_pdf_text, merge_entity_aliases, extract_graph_gliner2, extract_relations_mrebel, extract_triples_spacy_es, gliner2/mrebel/marianmt/rebel/spacy_es load_model, parse_rebel_output, translate_es_to_en, issue 0050/0051. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2.5 KiB
2.5 KiB
name, kind, lang, domain, version, purity, signature, description, tags, uses_functions, uses_types, returns, returns_optional, error_type, imports, params, output, tested, tests, test_file_path, file_path, source_repo, source_license, source_file
| name | kind | lang | domain | version | purity | signature | description | tags | uses_functions | uses_types | returns | returns_optional | error_type | imports | params | output | tested | tests | test_file_path | file_path | source_repo | source_license | source_file | ||||||||||||||||||||||||||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| valhalla_isochrones_async | function | py | geo | 1.0.0 | impure | async def valhalla_isochrones_async(requests: list[dict], base_url: str = 'http://localhost:8002', costing: str = 'auto', concurrency: int = 6, timeout_s: float = 120.0, denoise: float = 0.6, generalize_m: int = 50) -> list[dict | None] | Calcula isócronas para múltiples puntos en paralelo usando httpx.AsyncClient y asyncio.Semaphore. Order-preserving: la lista retornada es paralela a la de entrada. |
|
true | error_go_core |
|
|
Lista paralela a 'requests' con GeoJSON dict (campo 'features') o None por cada punto. Preserva el orden de entrada. Nunca lanza excepcion — fallos individuales se mapean a None. | true |
|
python/functions/geo/tests/test_valhalla_isochrones_async.py | python/functions/geo/valhalla_isochrones_async.py | internal:footprint_aurgi | internal-aurgi | ponderacion_isochronas/src/generar_isochronas_aurgi.py |
Ejemplo
import asyncio
pts = [
{"lat": 40.4168, "lon": -3.7038, "minutes": 10, "id": "madrid_centro"},
{"lat": 40.4530, "lon": -3.6883, "minutes": 10, "id": "retiro"},
]
results = asyncio.run(valhalla_isochrones_async(pts))
for req, gj in zip(pts, results):
status = "ok" if gj else "error"
print(f"{req['id']}: {status}")
Notas
Adaptada de _run_isochrones y _fetch_isochrone en generar_isochronas_aurgi.py. La versión original acoplaba pandas DataFrames y escritura a disco — esta versión es pandas-free y retorna datos en memoria. Usa asyncio.gather para preservar el orden de resultados.