import json
import numpy as np

d = json.loads(open('/tmp/wunderlist-2014015-12-49-55.json').read())

# extract the id of the category "Future Blog Posts"
cat_id = [x['id'] for x in d['lists'] if x['title'].startswith('Future blog posts')][0]

# convert datetimes into epoc milliseconds
from datetime import datetime
to_epoc = lambda x: int(datetime.strptime(x['created_at'], '%Y-%m-%dT%H:%M:%SZ').strftime('%s'))*1000

# list of pairs (time, val) where val is 1 iff the task belongs to the category under analysis 
time_indicator = sorted([[to_epoc(x),  x['list_id'] == cat_id and 1 or 0] for x in d['tasks']])
times, indicator = zip(*time_indicator)

# prepare the JSON for nvd3
data = []
data.append({'key': 'All other lists', 'values' : zip(times, [int(x) for x in np.cumsum([1-x for x in indicator])])})
data.append({'key': 'Future posts', 'values' : zip(times, [int(x) for x in np.cumsum(indicator)])})
f = open('../data/wunderlist.json', 'w')
f.write(json.dumps(data))
f.close()

%%bash
cat ../_includes/bladh/wunderlist_infographic.html