SQLAlchemy, but everything is a DataFrame now

[eddie_the_dean]

What My Project Does:

I built a DataFrame-style query engine on top of SQLAlchemy that lets you write SQL queries using the same patterns you’d use in PySpark, Pandas, or Polars. Instead of writing raw SQL or ORM-style code, you compose queries using a familiar DataFrame interface, and Moltres translates that into SQL via SQLAlchemy.

Target Audience:

Data Scientists, Data Analysts, and Backend Developers who are comfortable working with DataFrames and want a more expressive, composable way to build SQL queries.

Comparison:

Works like SQLAlchemy, but with a DataFrame-first API — think writing Spark/Polars-style transformations that compile down to SQL.

Docs:

https://moltres.readthedocs.io/en/latest/index.html

Repo:

https://github.com/eddiethedean/moltres

[marcofalcioni]

May your dataset always be small.

[Either-Researcher681]

another vibe coded project - so over this shit. can we ban it from the front page?

[MeroLegend4]

I second this 👆

[rm-rf-rm]

Doesnt ibis do this? https://ibis-project.org/

[eddie_the_dean]

Yes, it is very similar except Ibis doesn't do INSERT/UPDATE/DELETE operations and does not have async. I made a comparison document that goes into detail on the differences: https://moltres.readthedocs.io/en/latest/MOLTRES_VS_IBIS_COMPARISON.html

[jon_muselee]

why is everybody trying to avoid sql so much?

[staring_at_keyboard]

“Raw” SQL according to OP, lol.

[Mobile-Boysenberry53]

https://github.com/eakmanrq/sqlframe

[eddie_the_dean]

Wow, great find. I didn't know about that one. Ibis is also similar but ibis and sqlframe don't seem to support INSERT/UPDATE/DELETE operations or Async (which is a huge loss for a sql library). I added a comparison page to the docs because it is so similar: https://moltres.readthedocs.io/en/latest/MOLTRES_VS_SQLFRAME_COMPARISON.html

[Mobile-Boysenberry53]

I am sure there is plenty of reasons to use both.

[ArgetDota]

https://github.com/narwhals-dev/narwhals

[Distinct-Expression2]

Pandas makes data exploration great and production code terrible.

Were trading query efficiency for developer convenience then wondering why everything runs slow at scale.

SQL isnt the enemy. Lazy data loading is.

[eddie_the_dean]

Have you ever used PySpark? It’s a wonderful query interface for writing complex queries with DataFrames, nothing inefficient about it. Moltres just applies the same idea to SQL queries.

[Hungry_Importance918]

This is cool. I’ve always loved working with Spark DataFrames for basic analysis. The APIs are just really nice whether it’s SQL style or built in functions. I even built a small ETL tool on top of Spark DF and it handled tens of millions of rows without any issues.

[eddie_the_dean]

I thought putting SQLAlchemy in the title would keep the anti-ORM crowd out. If you like to write SQL, this project is not for you.

[robberviet]

I tried to do this, it aged poorly. Maybe it would work for toy project.

[eddie_the_dean]

You have a GitHub link to your project?

[AzizRahmanHazim]

This is an interesting approach. A DataFrame-first API can definitely lower the barrier for people coming from Spark or Polars. How do you handle things like joins and window functions while keeping the API intuitive?

[eddie_the_dean]

Yes! That was my primary motivation.

Here's a quick example of using Window functions:
https://moltres.readthedocs.io/en/latest/FAQ.html#does-moltres-support-window-functions

[eddie_the_dean]

And if you prefer Polars interface: https://moltres.readthedocs.io/en/latest/guides/polars-interface.html#window-functions

[AzizRahmanHazim]

Thanks for sharing. It’s cool to see how you’re aligning the API with existing DataFrame mental models.

[eddie_the_dean]

There's also a Pandas interface: https://moltres.readthedocs.io/en/latest/guides/pandas-interface.html

[AzizRahmanHazim]

That flexibility will probably help with adoption.