I already know how to get market data for 1 hour and 1 min,
but how do I get 30mins time frame data? Anybody could show the python code?
Thanks
@sheep Setting the timeframe depends upon the python SDK you are using
If one uses the alpaca-py SDK then one must create a TimeFrame object and then pass it as a parameter to the get_stock_bars method. The TimeFrame class is documented here.
!pip install alpaca-py
from alpaca.data.historical import StockHistoricalDataClient
from alpaca.data.timeframe import TimeFrame, TimeFrameUnit
from alpaca.data.requests import StockBarsRequest
ALPACA_API_KEY_ID = 'xxxxx'
ALPACA_API_SECRET_KEY = 'xxxxx'
# Create a data client to fetch historical data
data_client = StockHistoricalDataClient(ALPACA_API_KEY_ID, ALPACA_API_SECRET_KEY)
# Set parameters
symbols=['AIU', 'AMD', 'MSFT', 'NVDA', 'TOVX']
start_date = pd.to_datetime("2022-01-03").tz_localize('America/New_York')
end_date = pd.to_datetime("2022-01-04").tz_localize('America/New_York')
timeframe_30_min = TimeFrame(30, TimeFrameUnit.Minute)
request_parameters = StockBarsRequest(
symbol_or_symbols=symbols,
timeframe=timeframe_30_min,
start=start_date,
end=end_date,
)
# Fetch data and convert to dataframe
min_30_bars = data_client.get_stock_bars(request_parameters).df
It’s much more straightforward using the alpaca-trade-api. One can simply use strings like “30Min”, “10Min”, or “2Hour” to specify the bars.
!pip install alpaca-trade-api
import alpaca_trade_api as alpacaapi
ALPACA_API_KEY_ID = 'xxxxx'
ALPACA_API_SECRET_KEY = 'xxxxx'
api_data = alpacaapi.REST(ALPACA_API_KEY_ID, ALPACA_API_SECRET_KEY)
# Set parameters
symbols=['AIU', 'AMD', 'MSFT', 'NVDA', 'TOVX']
start_date = pd.to_datetime("2022-01-03").tz_localize('America/New_York')
end_date = pd.to_datetime("2022-01-04").tz_localize('America/New_York')
min_30_bars = api_data.get_bars(symbols,
'30Min',
start=start_date.isoformat(),
end=end_date.isoformat(),
).df
Hope that helps.
2 Likes
@Dan_Whitnable_Alpaca I found this article to help clarify what I am doing wrong but I am not having any luck.
I am transitioning everything slowly to alpca-py and currently working on get_stock_bars. I am getting this error however:
2024-03-19 10:51:00,559 - ERROR - Error in on_bars: 1 validation error for StockBarsRequest
timeframe
Input should be an instance of TimeFrame [type=is_instance_of, input_value=<alpaca_trade_api.rest.Ti...t at 0x0000025AF8ADA830>, input_type=TimeFrame]
For further information visit https://errors.pydantic.dev/2.6/v/is_instance_of
This is my code setup:
current_time = pd.Timestamp.now(tz="America/New_York").floor("1s")
today_date = current_time.strftime("%Y-%m-%d")
yesterday_date = (current_time - pd.Timedelta(days=3)).strftime("%Y-%m-%d")
timeframe_minute = TimeFrame(1, TimeFrameUnit.Minute)
request_params = StockBarsRequest(
symbol_or_symbols=[self.symbol],
timeframe=timeframe_minute,
start=yesterday_date,
end=today_date,
adjustment=Adjustment.RAW,
feed=DataFeed.SIP
)
self.data_bars = alpaca_py_stockdataclient_api.get_stock_bars(request_params).df
I cannot for the life of me see what is going wrong. I can get it working perfectly with get_bars:
self.data_bars = rest_api.get_bars(self.symbol, TimeFrame(1, TimeFrameUnit.Minute), start=yesterday_date, end=today_date, adjustment='raw').df
@FIRMCEO Not sure why your code doesn’t work? I was able to run very similar code without an error
from alpaca.data import StockHistoricalDataClient
from alpaca.data.requests import StockBarsRequest
from alpaca.data.timeframe import TimeFrame, TimeFrameUnit
from alpaca.data.enums import DataFeed, Adjustment
client = StockHistoricalDataClient(ALPACA_API_KEY, ALPACA_API_SECRET_KEY)
current_time = pd.Timestamp.now(tz="America/New_York").floor("1s")
today_date = current_time.strftime("%Y-%m-%d")
yesterday_date = (current_time - pd.Timedelta(days=3)).strftime("%Y-%m-%d")
timeframe_minute = TimeFrame(1, TimeFrameUnit.Minute)
request_params = StockBarsRequest(
symbol_or_symbols='SPY',
timeframe=timeframe_minute,
start=yesterday_date,
end=today_date,
adjustment=Adjustment.RAW,
feed=DataFeed.SIP
)
client.get_stock_bars(request_params).df
Perhaps look at your version of the alpaca-py SDK and make certain it is the latest.
I did the code standalone and I was able to get a printed set of data_bars. Which is wierd because I didn’t change anything with the timeframe, just applied a symbol directly in the symbol_or_symbols.
What is new now, that is brought to my attention, unlike the restAPI, is that even though my ‘end’ is TODAYS date I am only getting yesterday bars, for the 18th and nothing for today the 19th?
current_time = pd.Timestamp.now(tz="America/New_York").floor("1s")
today_date = current_time.strftime("%Y-%m-%d")
print(today_date)
yesterday_date = (current_time - pd.Timedelta(days=3)).strftime("%Y-%m-%d")
print(yesterday_date)
timeframe_minute = TimeFrame(1, TimeFrameUnit.Hour)
request_params = StockBarsRequest(
symbol_or_symbols=["AAPL"],
timeframe=timeframe_minute,
start=yesterday_date,
end=today_date,
adjustment=Adjustment.RAW,
feed=DataFeed.SIP
)
data_bars = alpaca_py_stockdataclient_api.get_stock_bars(request_params).df
print(data_bars)
2024-03-19
2024-03-16
open high low close volume trade_count vwap
symbol timestamp
AAPL 2024-03-18 08:00:00+00:00 173.400 174.0000 173.2700 173.750 57140.0 1343.0 173.644298
2024-03-18 09:00:00+00:00 173.730 173.9700 173.1500 173.510 27015.0 494.0 173.600521
2024-03-18 10:00:00+00:00 173.270 173.8600 173.0300 173.110 60022.0 1165.0 173.390566
2024-03-18 11:00:00+00:00 173.110 174.8000 172.4100 174.640 335775.0 6256.0 173.558252
2024-03-18 12:00:00+00:00 173.100 175.1900 172.4100 174.680 763990.0 12863.0 174.450807
2024-03-18 13:00:00+00:00 174.530 177.5800 174.2700 176.758 15385991.0 163908.0 176.357032
2024-03-18 14:00:00+00:00 176.770 177.7100 176.5850 177.180 11257483.0 199480.0 177.128022
2024-03-18 15:00:00+00:00 177.180 177.3300 175.6115 175.640 7405847.0 184044.0 176.512867
2024-03-18 16:00:00+00:00 175.640 175.6500 175.0750 175.080 5750690.0 67657.0 175.365402
2024-03-18 17:00:00+00:00 175.080 175.4500 174.7400 175.116 5046812.0 59679.0 175.102547
2024-03-18 18:00:00+00:00 175.120 175.5400 174.8200 174.975 5497583.0 55552.0 175.185205
2024-03-18 19:00:00+00:00 174.975 175.1760 173.5200 173.700 9622001.0 101460.0 174.448655
2024-03-18 20:00:00+00:00 173.790 173.7900 173.0000 173.260 14014712.0 5713.0 173.712317
2024-03-18 21:00:00+00:00 173.231 174.1153 173.2200 173.800 253491.0 2811.0 173.608822
2024-03-18 22:00:00+00:00 173.800 173.9000 173.4000 173.500 67759.0 1219.0 173.611733
2024-03-18 23:00:00+00:00 173.420 173.6900 173.3300 173.590 38300.0 1059.0 173.574086
@FIRMCEO The alpaca-py SDK really expects timezone aware datetime objects and not strings for datetime parameters. When it tries to convert strings, which are not timezone aware, to datetimes it 1) assumes the timezone is UTC and then 2) assumes if no time is given that the time is 00:00. So, if it is passed the string “2024-03-19” it assumes it is 2024-03-19 00:00:00Z which is 2024-03-18 20:00:00-0400. That is why you only get hour bars from 03-18.
It’s best to always pass timezone aware datetimes as parameters. Maybe like this
current_time = pd.Timestamp.now(tz="America/New_York")
yesterday_date = current_time - pd.Timedelta(days=3)
request_params = StockBarsRequest(
symbol_or_symbols=["AAPL"],
timeframe=TimeFrame(1, TimeFrameUnit.Hour),
start=yesterday_date,
end=current_time,
adjustment=Adjustment.RAW,
feed=DataFeed.SIP
)
data_bars = alpaca_py_stockdataclient_api.get_stock_bars(request_params).df