Python version of the "Parking" exercise

parkings.py

from flask import Flask, request
import urllib.request
import json
import geopy.distance

app = Flask(__name__)


def parkings_Poitiers():
  """
  Get all parkings of Poiters, as list of dict objects

  Usage:
  curl 'http://127.0.0.1:5000/nearOfPoint?lat=46.58570214260076&lon=0.35044408926683884&limit=1'

  curl 'http://127.0.0.1:5000/all'
  
  """
  webURL = urllib.request.urlopen(
        'https://data.grandpoitiers.fr/api/records/1.0/search/?dataset=mobilites-stationnement-des-parkings-en-temps-reel&facet=nom'
  )
  data = webURL.read()
  encoding = webURL.info().get_content_charset('utf-8')
  JSON_object = json.loads(data.decode(encoding))
  records = JSON_object['records']
  parkings = []
  for d in records:
    parking = {}
    fields = d["fields"]
    parking["name"] = fields["nom"]
    if "geo_point_2d" in fields:
      parking["lat"] = fields["geo_point_2d"][0]
      parking["lon"] = fields["geo_point_2d"][1]
    else:
      continue
    parking["capacity"] = fields["capacite"]
    parking["vacancy"] = fields["places"]
    parkings.append(parking)
  return parkings


@app.route('/all')
def index():
  """
  Return all parkings of the URL request
  """
  return parkings_Poitiers()


@app.route('/nearOfPoint')
def parkings_near_of():
  """
  Return sorted parkings of the URL request, limited to a number of results
  """
  lat = float(request.args.get("lat"))
  lon = float(request.args.get("lon"))
  limit = int(request.args.get("limit"))
  data = sorted(parkings_Poitiers(),
                key=lambda parking: geopy.distance.geodesic(
                    (float(parking["lat"]), float(parking["lon"])),
                    (lat, lon)).km * 1000)
  if limit:
    return data[0:limit]
  else:
    return data


if __name__ == "__main__":
  app.run()