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[Python-announce] [ANN] pipefunc 0.32.1: Simplified function composition and pipeline creation for scientific workflows

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Dear Python community,

I am pleased to announce the release of pipefunc, a new open-source Python library
designed to simplify function composition and pipeline creation for scientific computing,
data processing, and machine learning workflows.

BACKGROUND:
In scientific computing and data science, we often deal with complex workflows
involving multiple interdependent functions and large parameter spaces. pipefunc addresses
these challenges by automatically generating Directed Acyclic Graphs (DAGs) from Python
functions and efficiently handling N-dimensional parameter sweeps.

KEY FEATURES:
1. Automatic DAG generation from Python functions
2. Efficient handling of N-dimensional parameter sweeps
3. Seamless scaling from local execution to HPC environments (including SLURM clusters)
4. Built-in pipeline visualization
5. Integrated resource usage profiling
6. N-dimensional map-reduce support
7. Automatic type checking through annotations
8. Minimal boilerplate code required

VERSION: 0.32.1
PYTHON REQUIRED: 3.10+
LICENSE: MIT

INSTALLATION:
pip install pipefunc
or
conda install pipefunc

For more information, please visit:
Documentation: https://pipefunc.readthedocs.io/
Source Code: https://github.com/pipefunc/pipefunc
PyPI: https://pypi.org/project/pipefunc/

We welcome feedback, contributions, and feature requests from the community. Please visit
our GitHub repository for more information on how to get involved.

Best regards,
Bas Nijholt
bas@nijho.lt

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[Python-announce] [ANN] pipefunc 0.32.1: Simplified function composition and pipeline creation for scientific workflows "Bas Nijholt" <basnijholt@gmail.com> - 2024-09-19 19:42 +0000

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