Merge on range between two columns

I have a table of records with a position "stand" and a column timestamp or "datetime". I need to append this table with information on "acreg" and "flight".

The table with records (df_hvd) has the following columns of interest:

datetime	stand	reason
022-08-08 02:55:15	D02	Technical

I have a table with all flights (arriving and departing movements), and the corresponding start and end time of each movement. Based on the movement and stand, I want to retrieve the correct "acreg" and "flight". This source data looks like (df_events):

acreg	flight	movement_type	start_datetime	end_datetime	position
PHTFM	OR1072	AR-PK	2022-08-08 02:24:44	2022-08-08 04:07:00	D02
PHTFM	OR377	PK-DP	2022-08-08 12:15:00	2022-08-08 14:42:22	D07

Note that the timestamp of the first table falls between the start and end times in the second table. I somehow need to find a way to performa a merge that understands that the record of interest corresponds to the first movement in the source data.

I tried to built a loop, but it is far too slow and it has some key errors:

for r in df_hvd.index: 
    for e in df_temp.index: 
        if df_hvd.at[r, "Positie"] == df_temp.at[r, "stand"]:
            if df_hvd.at[r, "datetime"] <= df_temp.at[e, "end_datetime"] and df_hvd.at[r, "datetime"] >= df_temp.at[e, "start_datetime"]: 
                print(df_temp.at[r, "acreg"])

This also didn't work:

for e in df_temp.index: 
    stand = df_temp.at[e, "stand"]
    start = df_temp.at[e, "start_datetime"]
    end = df_temp.at[e, "end_datetime"]
    acreg = df_temp.at[e, "acreg"]
    
    df_hvd.loc[(df_hvd["datetime"] <= end) & (df_hvd["datetime"] >= start) & (df_hvd["Positie"] == stand), 'acreg'] = acreg

source https://stackoverflow.com/questions/75733938/merge-on-range-between-two-columns