iexfinance 0.3.4

Stock Endpoints

from iexfinance import Stock
tsla = Stock('TSLA')
tsla.get_open()
tsla.get_price()

It’s also possible to obtain historical data from the get_historical_data top-level function. This will return a daily time-series of the ticker requested over the desired date range (start and end passed as datetime.datetime objects).

Pandas DataFrame and JSON (dict) output formatting are selected with the output_format parameter.

Historical Data

from iexfinance import get_historical_data
from datetime import datetime

start = datetime(2017, 2, 9)
end = datetime(2017, 5, 24)

df = get_historical_data("AAPL", start=start, end=end, output_format='pandas')
df.head()

The resulting DataFrame will indexed by date, with a column for each OHLC datapoint:

It’s really simple to plot this data, using matplotlib:

import matplotlib.pyplot as plt

df.plot()
plt.show()

IEX Reference Data

Support for the IEX Reference Data endpoints is available through the top level functions get_available_symbols, get_corporate_actions, get_dividends, get_next_day_ex_date, and get_listed_symbol_dir. As with all endpoints, request parameters such as retry_count and output format selection (through output_format) can be passed to the call.

from iexfinance import get_available_symbols

get_available_symbols(output_format='pandas')[:2]

IEX Market Data

The IEX Market Data endpoints are supported through various top-level functions, including get_market_tops and get_market_deep.

from iexfinance import get_market_tops

get_market_tops()

IEX Stats

The IEX Stats endpoints are supported through various top-level functions, including get_stats_intraday and get_stats_recent. These endpoints provide IEX’s trading statistics for a given ticker.

from iexfinance import get_stats_intraday

get_stats_intraday()