psycopg2 VS Pandas

You can practice both by using https://www.psycopg.org from your Python code to communicate with your database. When I wanted to practice some SQL, that's what I did (we use psycopg at work, so that's what I practiced with, making a dream journal thingy for myself that was better than just noting stuff in a notepad because I could then look up e.g. what other stuff was correlated with Y, how many times I dreamed of X, etc. etc.)

But seems like it should work with Django 3, which you have specified https://github.com/psycopg/psycopg2/issues/1293

If you're using Postgres for your SQL, look at the "copy' method of the psycopg module (see https://www.psycopg.org/articles/2020/11/15/psycopg3-copy/) . It's much faster than INSERTs in my experience (YMMV).

Back when I used Psycopg2, there was no -binary package, so you'd get libpq set up similarly to pg-native. Docs say:

> The binary package is a practical choice for development and testing but in production it is advised to use the package built from sources.

Relevant GitHub discussion: https://github.com/psycopg/psycopg2/issues/674

I dunno, this seems worse to me.

Just go to the more easily readable docs here. I’m sorry, but the linked article is terrible.

psycopg2-binary. See https://github.com/psycopg/psycopg2/issues/1286.

psycopg2-binary, PostgreSQL Database adapter for python.

... # psycopg2==2.9.3 # https://github.com/psycopg/psycopg2 ...

I sometimes do this in testing. For example, consider the library used to communicate with a Postgres database, psycopg.

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[1]: https://github.com/pandas-dev/pandas/issues/53999

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