Get bars fixes

[brettelliot]

1. When asked for daily bars, tradier now returns bars with a Timestamp index just like all the other datasources (it was previously returning a date).
2. When asked to get daily bars and given a length of N and a timeshift of none, tradier now returns the last N bars (instead of what it was doing before which was getting the bars for the last N days unlike the other datasources).

The following datasources now are tested for this stuff:
pandas, yahoo, alpaca, polygon, tradier.
(sorry i dont have any ibkr or thetadata accounts to test with)

Description by Korbit AI

What change is being made?

Modify the get_historical_prices function to ensure it fetches the last n bars instead of bars from the past n days, and refactor test cases for clarity and correctness in tradier_data.py.

Why are these changes being made?

The change ensures accurate fetching of historical bars by adjusting the start date to include only the required number of trading days, addressing inaccuracies with the previous method. Additionally, test cases are revised to enhance legibility and ensure that they effectively validate the data sources and the outputs, thus increasing the maintainability of the codebase.

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[korbit-ai]

Review Summary by Korbit AI

Code Execution Comments

• Ensure correct number of bars by modifying start_date calculation for accurate trading days array slicing.

Code Health Comments

• Handle date and datetime objects for consistent timezone-aware index conversion in DataFrame.

Files scanned

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File Path	Reviewed
lumibot/data_sources/tradier_data.py	✅

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[korbit-ai]

Enhance index handling for date and datetime objects.

Tell me more

​

The current implementation only checks if the index is a date object before converting it to a timezone-aware timestamp. However, it's possible that the index could already be a datetime object. To ensure consistent behavior, consider modifying the code to handle both date and datetime objects. You could update the condition as follows:

if isinstance(df.index[0], (date, datetime)) and df.index.tzinfo is None:
    df.index = pd.to_datetime(df.index, utc=True).tz_convert("America/New_York")

This change ensures that the index is always converted to a timezone-aware timestamp, regardless of whether it's originally a date or datetime object.

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[korbit-ai]

Incorrect start_date calculation with timestep 'day' and timeshift None.

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​

The current implementation for calculating the start_date when timestep is 'day' and timeshift is None might not always return the correct number of bars. Consider modifying the code to use the length parameter to slice the trading_days array, ensuring we always get the exact number of bars requested. For example, you could change:

start_date = trading_days.index[-length]

to:

start_date = trading_days.index[-length:][0]

This change ensures that we always get the correct number of bars, even if there are gaps in the trading days.

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[grzesir]

We should not hard code New York. This is a variable in lumibot so people can change it if they're international