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Building an Historical Prices Object With the OpenBB SDK

#tutorial #python #opensource #showdev

The objective is to build an object for historical price data, containing the attributes of multiple resolutions, wrapped as a one-liner function. The purpose of the functionality is to reduce the amount of time required to toggle between various time-intervals, for downstream calculations or charting.

For those interested in both, open source and finance, OpenBB is a great rabbit hole to dive down; and it's free. Clone the repo from GitHub here.

The first code block is for the import statements.

# Import the SDK from typing import Optional from openbb_terminal.sdk import openbb from IPython.utils import io
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The next step is to define the object that will be returned when called by the function.

# Define the object to be returned. class HistoricalPrices: def __init__( self, symbol: str = "", start_date: Optional[str] = "1990-01-01", end_date: Optional[str] = None, prepost: Optional[bool] = False, source: str = "YahooFinance", ) -> None: self.one_min = openbb.stocks.load( symbol=symbol, start_date=start_date, end_date=end_date, interval=1, prepost=prepost, source=source, ) self.five_min = openbb.stocks.load( symbol=symbol, start_date=start_date, end_date=end_date, interval=5, prepost=prepost, source=source, ) self.fifteen_min = openbb.stocks.load( symbol=symbol, start_date=start_date, end_date=end_date, interval=15, prepost=prepost, source=source, ) self.thirty_min = openbb.stocks.load( symbol=symbol, start_date=start_date, end_date=end_date, interval=30, prepost=prepost, source=source, ) self.sixty_min = openbb.stocks.load( symbol=symbol, start_date=start_date, end_date=end_date, interval=60, prepost=prepost, source=source, ) self.daily = openbb.stocks.load( symbol=symbol, start_date=start_date, end_date=end_date, interval=1440, prepost=prepost, source=source, ) self.weekly = openbb.stocks.load( symbol=symbol, start_date=start_date, end_date=end_date, interval=1440, prepost=prepost, weekly=True, source=source, ) self.monthly = openbb.stocks.load( symbol=symbol, start_date=start_date, end_date=end_date, interval=1440, prepost=prepost, monthly=True, source=source, )
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Then, make the function to call the object.

# Create the function to return the data as an object. def historical_prices( symbol: str = "SPY", start_date: Optional[str] = "1990-01-01", end_date: Optional[str] = None, prepost: Optional[bool] = True, source: str = "YahooFinance", ) -> HistoricalPrices: # capture_output() is used to silence the console output. with io.capture_output(): historical = HistoricalPrices(symbol, start_date, end_date, prepost, source) return historical
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Finally, assign the function to a variable.

#Use the variables, [symbol, start_date, end_date, prepost, source], to modify the call. historical = historical_prices()
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The attributes returned are:

historical.one_min historical.five_min historical.fifteen_min historical.thirty_min historical.sixty_min historical.daily historical.weekly historical.monthly
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historical.one_min.tail(5)
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date Open High Low Close Adj Close Volume
2023-03-07 19:55:00 398.15 398.19 398.14 398.18 398.18 0
2023-03-07 19:56:00 398.15 398.19 398.15 398.175 398.175 0
2023-03-07 19:57:00 398.17 398.28 398.17 398.25 398.25 0
2023-03-07 19:58:00 398.25 398.27 398.23 398.24 398.24 0
2023-03-07 19:59:00 398.26 398.27 398.18 398.25 398.25 0 
historical.monthly.head(5)
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date Open High Low Close Adj Close Volume Dividends Stock Splits
1993-02-01 00:00:00 25.2362 25.8998 24.5725 25.4873 25.4873 5.4176e+06 0 0
1993-03-01 00:00:00 25.577 26.3123 25.3797 25.9357 25.9357 3.0192e+06 0.213 0
1993-04-01 00:00:00 26.0942 26.0942 24.9589 25.3914 25.3914 2.6972e+06 0 0
1993-05-01 00:00:00 25.4274 26.3285 25.2833 26.0762 26.0762 1.808e+06 0 0
1993-06-01 00:00:00 26.1663 26.4186 25.4995 25.9861 25.9861 3.438e+06 0.318 0

Download a notebook with this code, here

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