#!/usr/bin/env python3 # inspiration : # https://towardsdatascience.com/loading-data-from-openstreetmap-with-python-and-the-overpass-api-513882a27fd0 # https://geo.api.gouv.fr/adresse # https://wiki.cartocite.fr/doku.php?id=umap:10_-_je_valorise_les_donnees_openstreetmap_avec_umap # https://sites-formations.univ-rennes2.fr/mastersigat/Cours/Intro_Overpass.pdf # usage des tags : https://taginfo.openstreetmap.org/tags/?key=amenity&value=bicycle_parking#combinations # exemple URL données pour umap : https://www.velocite63.fr/velocite63/OSM/stationnements_velos_publics.json # penser à cocher "proxy" dans la rubrique "données distantes" du calque # export ODS : # https://pythonhosted.org/pyexcel-ods/ # pip3 install pyexcel-ods3 import requests import json import time from pyexcel_ods3 import save_data from collections import OrderedDict import os from osm_vc63 import errors from osm_vc63 import requetes from osm_vc63.save import Save overpass_url="http://overpass-api.de/api/interpreter" geo_api_url = "https://api-adresse.data.gouv.fr" dossier_sauvegarde = "resultats/" # nombre maxi de retries quand echec API max_retry = 4 # delai en secondes entre les tentatives retry_delay = 120 # id du département "Puy de Dôme" : 7406 # id Riom : 1693144 # id Clermont : 110866 # id Romagnat : 138269 # l'id de l'area se calcule en ajoutant 3600000000 au numéro de l'objet OSM aire_de_recherche = str(3600000000+110866) # ---------------------------------------------- trad_bicycle_parking = { "stands": "Arceaux", "wall_loops": "Pince roues", "rack": "Râteliers", "anchors": "Ancrage", "shed": "Abri collectif", "bollard": "Potelet", "lockers": "Abris individuels", "wide_stands": "Arceaux espacés", "ground_slots": "Fente dans le sol", "building": "Bâtiment", "informal": "Informel", "wave": "Râteliers", "streetpod": "Arceaux", "tree": "Arbre à bicyclettes", "crossbar": "Barre", "rope": "Câble", "two-tier": "Deux étages", "floor": "Sol", "handlebar_holder": "Accroche-guidons"} def run_overpass_query(critere, aire_de_recherche) : """Envoie la requête Overpass et retourne la réponse JSON.""" overpass_query = """[out:json]; ( """+critere+""" ); out center; """ overpass_query = overpass_query.replace("aire_de_recherche", aire_de_recherche) print("Execution requete overpass : \n" + overpass_query) response = requests.get(overpass_url, params={'data': overpass_query}) if (response.status_code != 200) : raise errors.Overpass_error(response.status_code) return (response.json()) def run_reverse_geocoding(lat, lon) : """Retourne une adresse JSON à partir d'une position GPS.""" url = geo_api_url + "/reverse/" response = requests.get(url, params={'lon' : str(lon), 'lat' : str(lat)}) if (response.status_code != 200) : raise errors.Geo_api_error(response.status_code) return (response.json()) def executer_requete_et_exporter_resultats(nom_req, critere, aire_de_recherche, overpass_query_fields) : data = run_overpass_query(critere, aire_de_recherche) nb_elements = len(data["elements"]) print("Nombre d'elements : "+str(nb_elements)) """ print("Géocodage inversé : ", end="", flush=True) # @TODO : optimiser en faisant un appel au service /reverse/csv/ plutot que le service unitaire /reverse/ for element in data["elements"]: if (element["type"] == "node") : rev_geocode = run_reverse_geocoding(element["lat"], element["lon"]) else : rev_geocode = run_reverse_geocoding(element["center"]["lat"], element["center"]["lon"]) api_adresse = rev_geocode["features"][0] element["tags"]["api_adresse:geometry:coordinates:lon"] = api_adresse["geometry"]["coordinates"][0] element["tags"]["api_adresse:geometry:coordinates:lat"] = api_adresse["geometry"]["coordinates"][1] element["tags"]["api_adresse:properties:label"] = api_adresse["properties"]["label"] element["tags"]["api_adresse:properties:score"] = api_adresse["properties"]["score"] if ("housenumber" in api_adresse["properties"]) : element["tags"]["api_adresse:properties:housenumber"] = api_adresse["properties"]["housenumber"] element["tags"]["api_adresse:properties:type"] = api_adresse["properties"]["type"] element["tags"]["api_adresse:properties:name"] = api_adresse["properties"]["name"] element["tags"]["api_adresse:properties:postcode"] = api_adresse["properties"]["postcode"] element["tags"]["api_adresse:properties:citycode"] = api_adresse["properties"]["citycode"] element["tags"]["api_adresse:properties:city"] = api_adresse["properties"]["city"] if ("street" in api_adresse["properties"]) : element["tags"]["api_adresse:properties:street"] = api_adresse["properties"]["street"] element["tags"]["api_adresse:properties:attribution"] = rev_geocode["attribution"] element["tags"]["api_adresse:properties:licence"] = rev_geocode["licence"] # traduction if "bicycle_parking" in element["tags"]: element["tags"]["bicycle_parking"] = trad_bicycle_parking[element["tags"]["bicycle_parking"]] print("X", end="", flush=True) #else : # print("-", end="", flush=True) print() """ export_json = Save().nettoyage_json_pour_umap(data, overpass_query_fields) # Sauvegarde os.makedirs(dossier_sauvegarde, exist_ok = True) Save().as_json(export_json, dossier_sauvegarde, nom_req) Save().as_ods(overpass_query_fields, data, dossier_sauvegarde, nom_req) def main(): for req in requetes.reqs: for nb_essai in range(max_retry): # on tente max_retry fois try: executer_requete_et_exporter_resultats( req.nom, req.critere, aire_de_recherche, req.champs ) break except errors.Api_error: if nb_essai == max_retry: print("trop d'erreurs d'API - abandon") exit() print("erreur API - on retente dans " + str(retry_delay) + "s") time.sleep(retry_delay) print("Fini") if __name__ == "__main__": main()