I have a database (Microsoft Access) that i am accessing through my python file, in order for my program to work efficiently i need to have a cached copy of the whole database. I am able to connect to the database no problem. I was hoping to then import this database into a pandas format. I am doing this by:

cached_database = pandas.read_sql('select * from myTable', database_connection)

Problem with this is this line throws an error:

UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2
connection. Other DBAPI2 objects are not tested. Please consider using
SQLAlchemy.
cached_database = pandas.read_sql('select * from myTable', database_connection)
pyodbc.Error: ('HY109', '[HY109] [Microsoft][ODBC Microsoft Access Driver] Record is deleted. (-1017) (SQLGetData)')

Here i thought maybe pandas is just broken so i investigated a bit, and have thought using raw pyodbc commands:

cursor = database_connection.cursor()
cursor.execute('select * from myTable')

print(cursor.fetchone)             # this works and returns the first row
print(cursor.fetchmany(100000))    # this also works and return me 100 thousand row
print(cursor.fetchmany(1000000))   # this does NOT work and throws the error like above
print(cursor.fetchall())           # this does NOT also work and throws the same error above

So this leads me to believe that a row in the database is causing the code to fail, its hard to find though given the sheer number of rows the database have.

Is there any workaround to this? i would like to import my data to pandas so i can do some processing with it.

Thanks so much