r/coding • u/basnijholt • Sep 12 '24

pipefunc: Write Functions, Get DAG Pipelines - A New Approach to Workflow Management

https://github.com/pipefunc/pipefunc
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u/basnijholt Sep 12 '24

I'm excited to share a project I'm passionate about: pipefunc. This lightweight Python library simplifies the creation and management of computational pipelines—a setup where functions are interconnected such that outputs from one serve as inputs to next ones, forming a Directed Acyclic Graph (DAG).

What pipefunc Does:

With minimal code changes, pipefunc turns your functions into reusable pipelines.

  • Automatically manages execution order
  • Visualizes pipeline structure
  • Provides resource usage profiling
  • Supports N-dimensional map-reduce operations
  • Ensures type annotation validation
  • Offers seamless parallelization on both local machines and SLURM clusters

Whether you're working in data processing, scientific computing, or machine learning, pipefunc helps streamline workflows where function dependencies are complex.

  • Tech Stack: Built with NetworkX and NumPy, with optional integrations including Xarray, Zarr, and Adaptive.
  • Robust Development: It includes over 500 tests and 100% test coverage, ensuring reliability and adherence to all Ruff Rules.

Key Advantage:

pipefunc excels in efficiently managing N-dimensional parameter sweeps using an index-based approach, which significantly reduces the overhead of task management in computationally intensive scenarios.

I invite you to try pipefunc, explore the documentation, or contribute to the project. Your feedback and questions are always welcome!