Merge pandas dataframes where one value is between two others

I need to merge two pandas dataframes on an identifier and a condition where a date in one dataframe is between two dates in the other dataframe.

Dataframe A has a date ("fdate") and an ID ("cusip"):

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I need to merge this with this dataframe B:

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on A.cusip==B.ncusip and A.fdate is between B.namedt and B.nameenddt.

In SQL this would be trivial, but the only way I can see how to do this in pandas is to first merge unconditionally on the identifier, and then filter on the date condition:

    df = pd.merge(A, B, how='inner', left_on='cusip', right_on='ncusip')
    df = df[(df['fdate']>=df['namedt']) & (df['fdate']<=df['nameenddt'])]

Is this really the best way to do this? It seems that it would be much better if one could filter within the merge so as to avoid having a potentially very large dataframe after the merge but before the filter has completed.

As you say, this is pretty easy in SQL, so why not do it in SQL?

    import pandas as pd
    import sqlite3

    #We'll use firelynx's tables:
    presidents = pd.DataFrame({"name": ["Bush", "Obama", "Trump"],
                               "president_id":[43, 44, 45]})
    terms = pd.DataFrame({'start_date': pd.date_range('2001-01-20', periods=5, freq='48M'),
                          'end_date': pd.date_range('2005-01-21', periods=5, freq='48M'),
                          'president_id': [43, 43, 44, 44, 45]})
    war_declarations = pd.DataFrame({"date": [datetime(2001, 9, 14), datetime(2003, 3, 3)],
                                     "name": ["War in Afghanistan", "Iraq War"]})
    #Make the db in memory
    conn = sqlite3.connect(':memory:')
    #write the tables
    terms.to_sql('terms', conn, index=False)
    presidents.to_sql('presidents', conn, index=False)
    war_declarations.to_sql('wars', conn, index=False)

    qry = '''
            start_date PresTermStart,
            end_date PresTermEnd,
            terms join wars on
            date between start_date and end_date join presidents on
            terms.president_id = presidents.president_id
    df = pd.read_sql_query(qry, conn)


             PresTermStart          PresTermEnd             WarStart  Pres
    0  2001-01-31 00:00:00  2005-01-31 00:00:00  2001-09-14 00:00:00  Bush
    1  2001-01-31 00:00:00  2005-01-31 00:00:00  2003-03-03 00:00:00  Bush