Python API

Build data pipelines programmatically with Flowfile's Polars-compatible API. Pipelines built this way are version-controllable, reproducible, and open unchanged in the visual editor.

Backend required — not in Flowfile Lite

The Python API runs the full Flowfile engine in-process. It is not part of the browser-only Flowfile Lite edition, which is visual-only. Install the Python package to use this API.

If you know Polars, most of this API will look familiar: the FlowFrame mirrors a Polars LazyFrame, and expressions (ff.col, ff.when, the .str/.dt namespaces) work the same way. The additions are the parts that connect your code to the rest of Flowfile — cloud and database connectors, the catalog, and opening a pipeline in the visual editor.

Quick example

This snippet is a repository file executed by CI — it cannot drift from the real API:

import flowfile as ff

SALES = "https://raw.githubusercontent.com/edwardvaneechoud/flowfile/main/data/templates/supermarket_sales.csv"

result = (
    ff.read_csv(SALES)
    .unique()
    .filter(ff.col("quantity") > 7)
    .group_by("city")
    .agg(
        ff.col("gross_income").sum().alias("total_income"),
        ff.col("gross_income").median().alias("median_income"),
    )
)

Build the same chain without the final .collect() and the pipeline object opens on the canvas via ff.open_graph_in_editor(pipeline.flow_graph) — see Visual UI Integration.

Documentation

Quick Start

Install the package and build your first pipeline.

Core Concepts

FlowFrame and FlowGraph — the lazy, graph-connected data model
Expressions — Polars-style column operations
Formulas in Python — methods that accept the Excel-like formula language

API Reference

Tutorials

Building Flows with Code

For contributors

To understand how Flowfile works internally or contribute to the project, see the Developer Documentation.