Pivot: High-Performance Python Pipeline Tool

Change your code. Pivot knows what to run.

Pivot is a Python pipeline tool with automatic code change detection. Define stages with typed Python functions and annotations, and Pivot figures out what needs to re-run — no manual dependency declarations, no stale caches.

• Automatic code change detection using Python introspection
• Per-stage lock files for fast parallel writes
• Warm worker pools with preloaded imports
• Content-addressable caching with S3 remote storage
• DVC compatibility via YAML export

Python: 3.13+ | Platform: Unix (Linux/macOS)

Quick Start

pip install pivot

Define stages as pure, typed functions:

# pipeline.py
from typing import Annotated, TypedDict

import pandas
import pivot


class PreprocessOutputs(TypedDict):
    clean: Annotated[pandas.DataFrame, pivot.Out("processed.csv", pivot.loaders.CSV())]


def preprocess(
    raw: Annotated[pandas.DataFrame, pivot.Dep("data.csv", pivot.loaders.CSV())],
) -> PreprocessOutputs:
    return PreprocessOutputs(clean=raw.dropna())


pipeline = pivot.Pipeline("my_pipeline")
pipeline.register(preprocess)

Then run the pipeline — Pivot resolves the DAG from artifact dependencies:

pivot repro           # Run the entire pipeline
pivot repro           # Instant - nothing changed
pivot repro --watch   # Re-run automatically on file changes

Learn More

• Documentation
• Source code
• Interactive TUI: pip install pivot[tui], then pivot repro --tui