[nooorofe]

>pendulum is probably your best bet

It is best until you work with Pandas DataFrame (https://stackoverflow.com/questions/47849342/making-pandas-w...)

[BiteCode_dev]

Numpy and pandas are their own little island. It's not just dates and time, it's everything.

If you use numpy and pandas, you should also not use Python datetime, generators, most stdlib mathematical functions, the itertools module, random, etc.

It's the first thing you learn if you read any good pandas book, and the first thing I teach in my numpy/pandas trainings.

It has pretty much nothing to do with pendulum.

Basically, half the Python ecosystem is "well, except with numpy/pandas of course".

[nooorofe]

    from zoneinfo import ZoneInfo
    import pendulum
    import datetime

    def pendulum_to_datetime(pendulum_dt: pendulum.DateTime) -> datetime.datetime:
        return datetime.datetime.fromtimestamp(pendulum_dt.timestamp(), 
    ZoneInfo(pendulum_dt.timezone_name))
    
    # test 
    
    df = pd.DataFrame([[1, 2], [1, 2]], columns=['a', 'b'])
    df["time_column"] = pendulum_to_datetime(pendulum.now())
    
    print(df)

output

       a  b                      time_column
    0  1  2 2023-11-19 18:14:16.027777-05:00
    1  1  2 2023-11-19 18:14:16.027777-05:00


    >> df.dtypes

    a                                         int64
    b                                         int64
    time_column    datetime64[ns, America/New_York]
    dtype: object