Python API

Build data pipelines programmatically with Flowfile's Polars-compatible API.

If You Know Polars, You Know Flowfile

Our API is designed to be a seamless extension of Polars. The majority of the methods are identical, so you can leverage your existing knowledge to be productive from day one. The main additions are features that connect your code to the broader Flowfile ecosystem, like cloud integrations and UI visualization.

Who This Is For

Python developers who prefer code over drag-and-drop
Data scientists familiar with Polars or Pandas
Engineers building automated data pipelines
Anyone who needs version control and programmatic pipeline generation

Quick Example

import flowfile as ff

df = ff.read_csv("sales.csv")
result = df.filter(ff.col("amount") > 100).group_by("region").agg(
    ff.col("amount").sum()
)

# Visualize your pipeline
ff.open_graph_in_editor(result.flow_graph)

Documentation

Quick Start

Get up and running in 5 minutes with your first pipeline.

Core Concepts

FlowFrame and FlowGraph - Fundamental building blocks
Formula Syntax - Flowfile's Excel-like expressions

API Reference

Tutorials

Building Flows with Code

For Contributors

Want to understand how Flowfile works internally or contribute to the project? See the Developer Documentation for architecture details and internal API reference.

Prefer visual workflows? Check out the Visual Editor Guide.