import urllib2
import json
import os
import datetime
import pandas as pd

with open(os.path.expanduser('~/.velib'), 'r') as f:
    key = f.read()

def geturl(path):
    delim = '&' if '?' in path else '?'  
    return "https://api.jcdecaux.com/vls/v1/{0:s}{1:s}apiKey={2:s}".format(path, delim, key)

def get(path):
    url = geturl(path)
    return json.loads(urllib2.urlopen(url).read())

filter(lambda d: d['name'] == 'Paris', get('contracts'))

stations = get('stations?contract=Paris')

stations_df = pd.DataFrame(stations)

stands = stations_df.bike_stands
print("""There are {0:d} stations with a total of {1:d} bike stands near Paris.
Each station has between {2:d} and {3:d} stands, with a mean of {4:.1f} stands.
""".format(
    stands.count(),
    stands.sum(),
    stands.min(),
    stands.max(),
    stands.mean(),
))

stands.hist();
title("Number of bike stands per station.");

timestamp = stations_df.last_update.max()
date = datetime.datetime.fromtimestamp(timestamp / 1000.).strftime('%Y-%m-%d %H:%M:%S')
print(date)

available_bike_stands = stations_df.available_bike_stands
available_bikes = stations_df.available_bikes
print("""There are {0:d} stations with no bikes out of {1:d} stations on {2:s}.""".format(
    np.sum(available_bikes == 0),
    available_bikes.count(),
    date,))

positions = np.array([(d['position']['lng'], d['position']['lat']) for d in stations])
indices = positions.min(axis=1) != 0.0
positions = positions[indices,:]
x, y = positions.T

sizes = stations_df.bike_stands[indices]
available_stands = stations_df.available_bike_stands[indices]

figure(figsize=(12,8));
scatter(x, y, c=available_stands, s=sizes, edgecolors='none', cmap=get_cmap('RdYlGn'));
xticks([]);
yticks([]);
title("Available bike stands in Paris Velib' stations, {0:s}".format(date));