A simple dataflow engine with scalable semantics.

The goal of pydra is to provide a lightweight Python dataflow engine for DAG construction, manipulation, and distributed execution.

Feature list:

1. Python 3.7+ using type annotation and dataclasses
2. Composable dataflows with simple node semantics. A dataflow can be a node of another dataflow.
3. splitter and combiner provides many ways of compressing complex loop semantics
4. Cached execution with support for a global cache across dataflows and users
5. Distributed execution (presently via ConcurrentFutures and SLURM, more on their way)

[API Documentation]

This tutorial will walk you through the main concepts of Pydra!

Please note that mybinder times out after an hour.

pip install pydra

Pydra requires Python 3.7+. To install in developer mode:

git clone git@github.com:nipype/pydra.git
cd pydra
pip install -e .[dev]

It is also useful to install pre-commit:

pip install pre-commit
pre-commit