This question feels fiendishly simple but I haven't been able to find an answer.
I have an ORM query object, say
query_obj = session.query(Class1).join(Class2).filter(Class2.attr == 'state')
I can read it into a dataframe like so:
testdf = pd.read_sql(query_obj.statement, query_obj.session.bind)
But what I really want to do is use a traditional SQL query instead of the ORM:
with engine.connect() as connection:
# Execute the query against the database
results = connection.execute(query_obj)
# Fetch all the results of the query
fetchall = results.fetchall()
# Build a DataFrame with the results
dataframe = pd.DataFrame(fetchall)
Where query is a traditional SQL string. Now when I run this I get an error along the lines of "query_obj is not executable" Anyone know how to convert the ORM query to a traditional query? Also how does one get the columns in after getting the dataframe?
Context why I'm doing this: I've set up an ORM layer on top of my database and am using it to query data into a Pandas DataFrame. It works, but it's frequently maxing out my memory. I want to cut my in-memory overhead with some string folding (pass 3 outlined here: http://www.mobify.com/blog/sqlalchemy-memory-magic/). That requires (and correct me if I'm wrong here) not using the read_sql string and instead processing the query's return as raw tuples.
fetchall.keys()