Question: I want to load an entire database table into a Pandas DataFrame using SqlAlchemy ORM. I have successfully queried the number of rows in the table like this: from local_modules import RemoteConnector from sqlalchemy import Integer, Column from sqlalchemy.orm import sessionmaker from sqlalchemy.ext.automap import automap_base import pandas as pd Base = automap_base() class Calculations(Base): __tablename__ = "calculations" id = Column("ID", Integer, primary_key=True) Base.prepare() connection = RemoteConnector('server', 'calculations_database') connection.connect() Session = sessionmaker(bind=connection.engine) session = Session() result = session.query(Calculations).count() print('Record count:', result)  Output: Record count: 13915 Process finished with exit code 0  If possible and, it seems it can be done, I want to define the table using automap_base from sqlalchemy.ext.automap and not have to manually state each column. I did so with 'id' because I had an error that asked me to set a primary key (is there a better way to do this?). In order to get any results I've been able to do the following: results = session.query(Calculations).all()  Output: [<__main__.Calculations object at 0x000001AF2324F510>, <__main__.Calculations object at 0x000001AF2324F6D0>, <__main__.Calculations object at 0x000001AF2324F810>, <__main__.Calculations object at 0x000001AF2324F910>, <__main__.Calculations object at 0x000001AF2324FA50>, <__main__.Calculations object at 0x000001AF2324FB90>, <__main__.Calculations object at 0x000001AF2324FCD0>, <__main__.Calculations object at 0x000001AF2324FE10>, <__main__.Calculations object at 0x000001AF2324FF50>, <__main__.Calculations object at 0x000001AF22CD40D0>, <__main__.Calculations object at 0x000001AF22CD4210>, <__main__.Calculations object at 0x000001AF22CD4350>, <__main__.Calculations object at 0x000001AF22CD4490>, <__main__.Calculations object at 0x000001AF22CD45D0>, <__main__.Calculations object at 0x000001AF22CD4710>, <__main__.Calculations object at 0x000001AF22CD4850>, <__main__.Calculations object at 0x000001AF22CD4990>, <__main__.Calculations object at 0x000001AF22CD4AD0>, <__main__.Calculations object at 0x000001AF22CD4C10>, <__main__.Calculations object at 0x000001AF22CD4D50>, <__main__.Calculations object at 0x000001AF22CD4E90>, <__main__.Calculations object at 0x000001AF22CD4FD0>, <__main__.Calculations object at 0x000001AF22CD5110>, <__main__.Calculations object at 0x000001AF22CD5250>, <__main__.Calculations object at 0x000001AF22CD53D0>, <__main__.Calculations object at 0x000001AF22CD5510>, <__main__.Calculations object at 0x000001AF22CD5650>, <__main__.Calculations object at 0x000001AF22CD5790>, <__main__.Calculations object at 0x000001AF22CD58D0>, <__main__.Calculations object at 0x000001AF22CD5A10>, <__main__.Calculations object at 0x000001AF22CD5B50>, <__main__.Calculations object at 0x000001AF22CD5C90>, <__main__.Calculations object at 0x000001AF22CD5DD0>, <__main__.Calculations object at 0x000001AF22CD5F10>, <__main__.Calculations object at 0x000001AF22CD6050>, <__main__.Calculations object at 0x000001AF22CD6190>, <__main__.Calculations object at 0x000001AF22CD62D0>, <__main__.Calculations object at 0x000001AF22CD6410>, <__main__.Calculations object at 0x000001AF22CD6550>, <__main__.Calculations object at 0x000001AF22CD6690>, <__main__.Calculations object at 0x000001AF22CD67D0>, <__main__.Calculations object at 0x000001AF22CD6910>, <__main__.Calculations object at 0x000001AF22CD6A50>, <__main__.Calculations object at 0x000001AF22CD6B90>, <__main__.Calculations object at 0x000001AF22CD6CD0>, <__main__.Calculations object at 0x000001AF22CD6E10>, <__main__.Calculations object at 0x000001AF22CD6F50>, <__main__.Calculations object at 0x000001AF22CD7090>]  This shows all the columns in the table as an object. My best attempt to extract the values has been: for result in results: print(result.__dict__)  Output: {'_sa_instance_state': <sqlalchemy.orm.state.InstanceState object at 0x00000232E0A91730>, 'id': 1.0} {'_sa_instance_state': <sqlalchemy.orm.state.InstanceState object at 0x00000232E0A90E90>, 'id': 2.0} ... and so on  Not only I do not get the values but it does not print the columns, only the ID I defined in the class. I thought that when I did the automap_base it would transfer automatically. When I do define them they do appear, like this: class Calculations(Base): __tablename__ = "Calculations" id = Column("Trade ID", Integer, primary_key=True) Amount = Column("Amount", Integer) Yield = Column("Yield", Integer)  Output: {'_sa_instance_state': <sqlalchemy.orm.state.InstanceState object at 0x000001BFD2092090>, 'Amount': 34303.0, 'Yield': 0.01141, 'id': 1.0} {'_sa_instance_state': <sqlalchemy.orm.state.InstanceState object at 0x000001BFD2091010>, 'Amount': 10000.0, 'Yield': 0.01214, 'id': 2.0} {'_sa_instance_state': <sqlalchemy.orm.state.InstanceState object at 0x000001BFD2090FB0>, 'Amount': 43515.0, 'Yield': 0.01206, 'id': 3.0} ... and so on  What I would like to ultimately do is something like this as suggested in SQLAlchemy ORM conversion to pandas DataFrame: df = pd.read_sql_query(sql=session.query(Calculation).all(), con=connection.engine)  But I get the following error:  raise exc.ObjectNotExecutableError(statement) from err sqlalchemy.exc.ObjectNotExecutableError: Not an executable object: [<__main__.CALC_TFSB_INVESTMENTS object at 0x000001FF42966E50>, ... an so on  I have also tried: df = pd.read_sql_query(sql=select(Calculations), con=connection.engine) print(df.head())  How can I load the DataFrame? How can I automate the schema detection, I suppose using automap_base? How can I improve my code, are there other things I can add, perhaps dunder fields to make things better?

Answer: The answer is df = pd.read_sql_query(sql=select(Calculations), con=connection.engine) print(df.head())  This does the trick Corralien's answer is much more detailed.