ttools/tests/alpaca_loader.ipynb

In [1]:

from ttools.external_loaders import load_history_bars
from ttools.config import zoneNY
from datetime import datetime, time
from alpaca.data.timeframe import TimeFrame, TimeFrameUnit

symbol = "AAPL"
start_date = zoneNY.localize(datetime(2023, 2, 27, 18, 51, 38))
end_date = zoneNY.localize(datetime(2023, 4, 27, 21, 51, 39))
timeframe = TimeFrame(amount=1,unit=TimeFrameUnit.Minute)

df = load_history_bars(symbol, start_date, end_date, timeframe, True)
df.loc[('AAPL',)]

TTOOLS: Loaded env variables from file /Users/davidbrazda/Documents/Development/python/.env

In [5]:

df.loc[('AAPL',)]

Out[5]:

<style scoped=""> .dataframe tbody tr th:only-of-type { vertical-align: middle; } .dataframe tbody tr th { vertical-align: top; } .dataframe thead th { text-align: right; } </style>

	open	high	low	close	volume	trade_count	vwap
timestamp
2023-02-28 09:30:00-05:00	147.050	147.380	146.830	147.2700	1554100.0	6447.0	146.914560
2023-02-28 09:31:00-05:00	147.250	147.320	147.180	147.2942	159387.0	6855.0	147.252171
2023-02-28 09:32:00-05:00	147.305	147.330	147.090	147.1600	214536.0	7435.0	147.210128
2023-02-28 09:33:00-05:00	147.140	147.230	147.090	147.1500	171487.0	7235.0	147.154832
2023-02-28 09:34:00-05:00	147.160	147.160	146.880	146.9850	235915.0	4965.0	147.001762
...	...	...	...	...	...	...	...
2023-04-27 15:26:00-04:00	168.400	168.415	168.340	168.3601	163973.0	1398.0	168.368809
2023-04-27 15:27:00-04:00	168.360	168.400	168.330	168.3800	130968.0	1420.0	168.364799
2023-04-27 15:28:00-04:00	168.380	168.430	168.320	168.3285	152193.0	1361.0	168.372671
2023-04-27 15:29:00-04:00	168.325	168.330	168.260	168.2850	208426.0	1736.0	168.297379
2023-04-27 15:30:00-04:00	168.280	168.350	168.255	168.3450	218077.0	1694.0	168.308873

15162 rows × 7 columns

In [3]:

df

Out[3]:

<style scoped=""> .dataframe tbody tr th:only-of-type { vertical-align: middle; } .dataframe tbody tr th { vertical-align: top; } .dataframe thead th { text-align: right; } </style>

		open	high	low	close	volume	trade_count	vwap
symbol	timestamp
AAPL	2023-02-27 18:52:00-05:00	148.0200	148.02	148.0200	148.02	112.0	7.0	148.020000
	2023-02-27 18:56:00-05:00	148.0200	148.02	148.0200	148.02	175.0	10.0	148.020000
	2023-02-27 19:00:00-05:00	148.0299	148.03	148.0299	148.03	1957.0	10.0	148.029993
	2023-02-27 19:06:00-05:00	148.0600	148.06	148.0600	148.06	122.0	7.0	148.060000
	2023-02-27 19:09:00-05:00	148.0500	148.10	148.0500	148.10	1604.0	33.0	148.075109
	...	...	...	...	...	...	...	...
	2023-04-27 19:54:00-04:00	167.8000	167.80	167.8000	167.80	534.0	15.0	167.800000
	2023-04-27 19:56:00-04:00	167.8800	167.88	167.8800	167.88	1386.0	28.0	167.880000
	2023-04-27 19:57:00-04:00	167.8000	167.80	167.8000	167.80	912.0	60.0	167.800000
	2023-04-27 19:58:00-04:00	167.8000	167.88	167.8000	167.88	3311.0	22.0	167.877333
	2023-04-27 19:59:00-04:00	167.9000	167.94	167.9000	167.94	1969.0	64.0	167.918150

31217 rows × 7 columns