Flowfile User Guides
Welcome to Flowfile! Whether you prefer visual drag-and-drop or writing code, we've got you covered.
Choose Your Path
🎨 Visual Editor
Perfect for analysts and business users who want to build data pipelines visually.
You'll learn:
- Drag and drop nodes to build flows
- Configure transformations with forms
- Connect to databases and cloud storage
- Export your flows as Python code
🐍 Python API
Perfect for developers and data scientists who prefer code.
You'll learn:
- Build pipelines with Polars-compatible API
- Seamlessly integrate with existing code
- Visualize your code as flow graphs
- Use advanced features and optimizations
The Best of Both Worlds
The beauty of Flowfile is that you don't have to choose. You can:
- Write code and visualize it instantly with
open_graph_in_editor() - Build visually and export as Python code
- Switch between visual and code at any time
- Collaborate across technical and non-technical teams
Quick Examples
Visual Approach
- Drag a "Read Data" node onto canvas
- Add a "Filter" node and connect them
- Configure filter conditions in the form
- Run and see results instantly
Code Approach
import flowfile as ff
df = ff.read_csv("data.csv")
result = df.filter(ff.col("amount") > 100)
ff.open_graph_in_editor(result.flow_graph) # See it visually!
Where to Start?
- New to Flowfile? Start with our Quick Start Guide
- Coming from Excel/Tableau? Try the Visual Editor
- Know Python/Pandas/Polars? Jump into the Python API
- Want to see real examples? Check out our tutorials in either section
Remember: Every visual flow can become code, and every code pipeline can be visualized. Choose what feels natural and switch whenever you want!