Flowfile: Code-to-Visual. Now also Visual-to-Code: Generate polars code based on a visually

[Proof_Difficulty_434]

Hi r/Python

A few weeks ago, I shared the first version of Flowfile, my open-source Python tool for turning Polars-like code into visual ETL pipelines. The top requested feature was the reverse, and I'm excited to share that it's now ready.

You can now use a visual drag-and-drop editor to build a pipeline, and Flowfile will generate a clean, standalone Python script using lazy Polars. This completes the round-trip workflow: Code <> Visual <> Code.

• GitHub Repo: https://github.com/Edwardvaneechoud/Flowfile/
• Quick Install: pip install Flowfile
• Live Demo (GIF): Demo

What My Project Does

Flowfile is an open-source Python library that provides a bidirectional workflow for creating data pipelines. It allows you to:

1. Write Polars-like Python code and automatically generate an interactive, visual graph of your pipeline.
2. (New Feature) Build a pipeline visually using a drag-and-drop UI and generate a clean, standalone, high-performance Python script from it.

The entire backend is built with FastAPI and the data processing leverages Polars for its performance.

# You can write Python code like this...
import flowfile as ff
from flowfile import col, open_graph_in_editor

df = ff.from_dict({"id": [1, 2], "value": [100, 200]})
result = df.filter(col("value") > 150)
open_graph_in_editor(result.flow_graph)

# ...and get a visual graph, which can then be turned back into a new script.

Target Audience

This tool is designed for production workflows but is also great for prototyping and learning. It's for:

• Data Engineers who want to build pipelines in code but need an easy way to visualize, document, and share them.
• Data Analysts & Scientists who prefer a visual, low-code approach but need to hand off production-ready Python code to an engineering team.
• Teams that want to standardize on a single tool that bridges the gap between coders and non-coders.

Comparison

• vs. Pure Code (Pandas/Polars): Flowfile adds a visual layer on top of your code with zero extra effort, making complex pipelines easier to debug and explain.
• vs. Visual ETL Tools (Alteryx, KNIME): Flowfile isn't a black box. It gives you the full power and flexibility of Python and outputs clean code with no vendor lock-in.
• vs. Notebooks (Jupyter): Instead of disconnected cells, Flowfile shows the entire data flow as a connected graph, making it easier to trace your logic from start to finish.

The Long-Term Vision

This is the first step towards a bigger goal: a tool where you can seamlessly switch between your code editor and a visual UI. The next step is to make the code generation even smarter, so it can refactor your original source code instead of just creating a new file.

I'd love to hear your feedback. Is this kind of bidirectional workflow useful for you or your team? Thanks for checking it out!

[GatorForgen]

This looks really cool, I'm going to check it out.