Python request of parking availability of the city of Lille (from MEL opendata platform)

lille_view_park.py

#!/usr/bin/env python3
# -*- coding: utf-8 -*-

import dateutil.parser
import requests
import pandas as pd
import datetime

# some consts
NAN = float('nan')
URL = 'https://opendata.lillemetropole.fr/api/records/1.0/search/'
PARK_REQ = '?dataset=disponibilite-parkings&rows=50'

# set global options
pd.set_option('display.width', 120)

# some vars
park_df = pd.DataFrame(columns=['name', 'state', 'display', 'available', 'capacity', 'update', 'occupied'])
park_df.index.name = 'id'

# request Lille parking dataset
try:
    park_raw_d = requests.get(URL + PARK_REQ).json()
except requests.exceptions.RequestException:
    park_raw_d = None

# process data
try:
    for record in list(park_raw_d['records']):
        # decode 'fields' part
        fields = dict(record['fields'])
        try:
            park_id = str(fields['id'])
            park_name = str(fields['libelle'])
            park_state = str(fields['etat'])
            park_display = str(fields.get('aff', ''))
            try:
                park_update = dateutil.parser.parse(fields.get('datemaj', ''))
            except (KeyError, ValueError):
                park_update = datetime.datetime(1970, 1, 1, tzinfo=datetime.timezone.utc)
            park_available = float(fields.get('dispo', NAN))
            park_capacity = float(fields.get('max', NAN))
        except KeyError:
            # ignore this one, go next
            continue
        # process park data
        park_df.loc[park_id, 'name'] = park_name
        park_df.loc[park_id, 'state'] = park_state
        park_df.loc[park_id, 'display'] = park_display
        park_df.loc[park_id, 'available'] = park_available
        park_df.loc[park_id, 'capacity'] = park_capacity
        park_df.loc[park_id, 'update'] = park_update
except (TypeError, KeyError):
    # global json fmt mismatch
    print('json not available or not valid')
    exit()

# add "occupied" ratio
park_df['occupied'] = 100 - 100 * park_df['available']/park_df['capacity']

# echo parking selection
print(park_df.loc[['LIL0005', 'LIL0006', 'LIL0007', 'LIL0008']].sort_values(by='occupied', ascending=False))