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get_barset() still ignores start and end date

See original GitHub issue

I’ve looked through #66 and the advice doesn’t work.

bars = api.get_barset(['AAPL'], '1D', limit=100, start=pd.Timestamp('2010-01-01', tz='America/New_York').isoformat())
print(bars.df)

                               AAPL                                        
                               open      high       low     close    volume
time                                                                       
2019-03-27 00:00:00-04:00  188.7500  189.7600  186.5500  188.4700  26586290
2019-03-28 00:00:00-04:00  188.9500  189.5590  187.5300  188.7100  19309376
2019-03-29 00:00:00-04:00  189.9900  190.0800  188.5400  189.9400  18489986
2019-04-01 00:00:00-04:00  191.6400  191.6800  188.3800  191.2400  12098014
2019-04-02 00:00:00-04:00  191.0900  194.4600  191.0500  194.0400  19797454
2019-04-03 00:00:00-04:00  193.2500  196.5000  193.1500  195.3500  19793141
2019-04-04 00:00:00-04:00  194.7900  196.3700  193.1400  195.7200  17091108
2019-04-05 00:00:00-04:00  196.4500  197.1000  195.9300  196.9700  15842943
2019-04-08 00:00:00-04:00  196.4200  200.2300  196.3400  200.0800  23231403
2019-04-09 00:00:00-04:00  200.3200  202.8500  199.2300  199.5000  32840959
2019-04-10 00:00:00-04:00  198.6800  200.7400  198.1800  200.6600  19861942
2019-04-11 00:00:00-04:00  200.8500  201.0000  198.4431  198.9500  17931789
2019-04-12 00:00:00-04:00  199.2000  200.1400  196.2100  198.8800  24667735
2019-04-15 00:00:00-04:00  198.5800  199.8500  198.0100  199.2300  14551176
2019-04-16 00:00:00-04:00  199.4600  201.3700  198.5600  199.2500  24002891
2019-04-17 00:00:00-04:00  199.5400  203.3800  198.6100  203.1200  27366117
2019-04-18 00:00:00-04:00  203.1200  204.1500  202.5200  203.8600  21928367
2019-04-22 00:00:00-04:00  202.8300  204.9400  202.3400  204.6400  13720923
2019-04-23 00:00:00-04:00  204.4300  207.7500  203.9000  207.5100  19401417
2019-04-24 00:00:00-04:00  207.3600  208.4800  207.0500  207.1800  14914939
2019-04-25 00:00:00-04:00  206.8300  207.7600  205.1200  205.2400  15908807
2019-04-26 00:00:00-04:00  204.9000  205.0000  202.1200  204.2900  16315669
2019-04-29 00:00:00-04:00  204.4000  205.9700  203.8600  204.6100  19641066
2019-04-30 00:00:00-04:00  203.0600  203.4000  199.1100  200.5700  35362106
2019-05-01 00:00:00-04:00  209.8800  215.3100  209.2300  210.5200  57751414
2019-05-02 00:00:00-04:00  209.8400  212.6500  208.1300  209.1700  29014844
2019-05-03 00:00:00-04:00  210.7400  211.8400  210.2300  211.7800  17987793
2019-05-06 00:00:00-04:00  204.2900  208.8400  203.5000  208.6000  28949691
2019-05-07 00:00:00-04:00  205.8800  207.4175  200.8250  202.8600  34328425
2019-05-08 00:00:00-04:00  201.9000  205.3400  201.7500  202.9000  22729670
...                             ...       ...       ...       ...       ...

Issue Analytics

State:
Created 4 years ago
Reactions:4
Comments:13 (2 by maintainers)

Top GitHub Comments

3reactions

jabowerycommented, Sep 8, 2020

Wasted a day tracking this down till I found jholland1’s nuclear flyswatter. Bad documentation. Fix it.

2reactions

shlomikushchicommented, Sep 9, 2020

Hi guys. this code snippet is an example on how to use the

import pandas as pd
NY = 'America/New_York'
start=pd.Timestamp('2020-08-01', tz=NY).isoformat()
end=pd.Timestamp('2020-08-30', tz=NY).isoformat()
print(api.get_barset(['AAPL', 'GOOG'], 'day', start=start, end=end).df)

also added it to the readme: https://github.com/alpacahq/alpaca-trade-api-python/pull/309

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