Awesome

Simple IEX Stock Fetcher

A python lib to get stock prices/dividends/splits from IEX Cloud.

My IEX Referrals: https://iexcloud.io/s/62efba08

Test api

import iex
import key
iex.init(key.test_token, api='sandbox')
aapl = iex.Stock('AAPL')
aapl.chart('5d', chartCloseOnly=True)

<div> <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>change</th> <th>changeOverTime</th> <th>changePercent</th> <th>close</th> <th>volume</th> </tr> <tr> <th>date</th> <th></th> <th></th> <th></th> <th></th> <th></th> </tr> </thead> <tbody> <tr> <th>2019-10-01</th> <td>0.630000</td> <td>0.002846</td> <td>0.2776</td> <td>235.08</td> <td>36626895</td> </tr> <tr> <th>2019-10-02</th> <td>-5.740000</td> <td>-0.023081</td> <td>-2.5109</td> <td>222.51</td> <td>35941685</td> </tr> <tr> <th>2019-10-03</th> <td>1.940000</td> <td>-0.014185</td> <td>0.8914</td> <td>231.78</td> <td>30438546</td> </tr> <tr> <th>2019-10-04</th> <td>6.310000</td> <td>0.013995</td> <td>2.8347</td> <td>230.24</td> <td>34995248</td> </tr> <tr> <th>2019-10-07</th> <td>0.051249</td> <td>0.000000</td> <td>0.0200</td> <td>234.46</td> <td>32130948</td> </tr> </tbody> </table> </div>

aapl.dividends('1y')

<div> <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>amount</th> <th>currency</th> <th>date</th> <th>declaredDate</th> <th>description</th> <th>flag</th> <th>frequency</th> <th>paymentDate</th> <th>recordDate</th> </tr> <tr> <th>exDate</th> <th></th> <th></th> <th></th> <th></th> <th></th> <th></th> <th></th> <th></th> <th></th> </tr> </thead> <tbody> <tr> <th>2018-11-14</th> <td>0.74</td> <td>USD</td> <td>2019-10-08</td> <td>2018-11-10</td> <td>er eD lrpfpl$esAa7reP a udDiv. h3 areSeeydicr ...</td> <td>QhneQoNCao g</td> <td>reayurltQ</td> <td>2018-11-29</td> <td>2018-11-14</td> </tr> </tbody> </table> </div>

Fetcher stocks

symbols = iex.Reference.symbols()
symbols = symbols[(symbols.type == 'ad') | (symbols.type == 'cs') & (symbols.exchange != 'OTC')]
symbols = symbols.symbol.values

from tqdm.notebook import tqdm
for k in tqdm(symbols):
    sys.stdout.write('\r{}   '.format(k))
    filename = "./daily/{}.csv".format(k)
    iex.Stock(k).chart('5y').to_csv(filename)
print('ok')

Code above will consume about 60 million messages