This is a very light wrapper around the PredictIt.org market data api.
market = get_market('DNOM16')
sanders = get_contract(market, 'SANDERS.DNOM16')
clinton = get_contract(market, 'CLINTON.DNOM16')
timestamp = get_timestamp(market)get_market will return a dict which contains data on all contracts in the given market. Then get_contract
will extract the data for a given contract. get_timestamp will get a datetime.datetime of the timestamp
associated with the market data.
You should expect get_market to return a dict which looks like:
{
u'Status': u'Open',
u'Name': u'Who will win the 2016 Democratic presidential nomination?',
u'URL': u'...',
u'TimeStamp': u'2016-04-06T11:52:07.2347221',
u'Image': u'...',
u'Contracts': [ ... ]
}and you should expect get_contract to return a dict which looks like:
{
u'Status': u'Open',
u'Name': u'Hillary Clinton',
u'URL': u'...',
u'Image': u'...',
u'LastTradePrice': 0.83,
u'BestBuyYesCost': 0.84,
u'BestBuyNoCost': 0.17,
u'BestSellYesCost': 0.83,
u'DateEnd': u'2016-09-15T00:00:00',
u'BestSellNoCost': 0.16,
u'LongName': u'Will Hillary Clinton win the 2016 Democratic presidential nomination? ',
u'ShortName': u'Clinton',
u'ID': 435,
u'TickerSymbol': u'CLINTON.DNOM16',
u'LastClosePrice': 0.82
}There is also a class Client which has essentially the same methods but handles caching of data for each
contract and between markets.
pip install predictitpy