Core Concepts

These guides explain the model behind Flowfile's Python API: what a FlowFrame is, how expressions and formulas differ, and why every operation is lazy and graph-connected.

Guides

FlowFrame and FlowGraph

The fundamental building blocks. Covers how a FlowFrame differs from a DataFrame, how the FlowGraph tracks each operation as a node, why everything is lazy, and how the code and visual representations connect.

Expressions

Polars-style column operations — the default way to express transformations. Column references, arithmetic, conditional logic with ff.when, filtering, and the .str / .dt / .list namespaces.

Formulas in Python

The FlowFrame methods that accept Flowfile formula strings: with_columns(flowfile_formulas=...), filter(flowfile_formula=...), and filter_split. The formula language itself (syntax, operators, functions) is documented in the Formula Language guide.

The lazy model

A FlowFrame is always lazy: operations build a plan and append a node to the FlowGraph, and nothing runs until .collect(). See FlowFrame and FlowGraph for a worked example.