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Pydra dataflow engine

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Pydra: Dataflow Engine

A simple dataflow engine with scalable semantics.

Pydra is a rewrite of the Nipype engine with mapping and joining as first-class operations. It forms the core of the Nipype 2.0 ecosystem.

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 attrs

  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, SLURM, and Dask (this is an experimental implementation with limited testing)

API Documentation

Learn more about Pydra

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Installation

pip install pydra

Note that installation fails with older versions of pip on Windows. Upgrade pip before installing:

pip install –upgrade pip
pip install pydra

Developer installation

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

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

In order to run pydra’s test locally:

pytest -vs pydra

If you want to test execution with Dask:

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

It is also useful to install pre-commit:

pip install pre-commit
pre-commit

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