All 128 Dependencies
Every package Flowfile depends on, ranked by repo health score.
Flowfile is an open-source visual ETL tool that bridges the gap between low-code pipeline design and production-grade Python code. You build data pipelines by dragging nodes onto a canvas, connecting them visually, and watching live data previews update as you work. When you're done, Flowfile exports the entire flow as standalone Polars Python code that runs anywhere with no Flowfile dependency required.
At its core, Flowfile is a monorepo of interconnected services: a FastAPI backend that executes ETL logic using the Polars dataframe library, a separate compute worker that handles heavy data processing tasks, and a Vue 3 + VueFlow frontend that renders the visual canvas. The same pipeline can be built either visually or programmatically through Flowfile's Python API, which mirrors Polars' familiar chained method syntax. Switching between the two is seamless — call `open_graph_in_editor()` on any Python-defined pipeline and it opens immediately in the visual designer.
Beyond the canvas, Flowfile ships an integrated data catalog backed by Delta Lake for time-travel and versioning, a SQL editor with embedded visualization powered by Graphic Walker, a built-in scheduler supporting interval and event-triggered runs, sandboxed Python kernel containers for running custom user code in isolation, and support for reading from and writing to PostgreSQL, MySQL, SQL Server, Oracle, S3, Azure Blob Storage, Google Cloud Storage, and Kafka. The browser-based demo runs entirely via Pyodide — no installation needed to try it.
Flowfile is MIT-licensed and available as a pip package, a desktop app for Windows, macOS, and Linux built with Tauri, or as a Docker Compose stack. An npm package (`flowfile-editor`) lets web developers embed the visual ETL canvas as a standalone Vue component in their own applications.