PipelineX
0.5.0

Contents:

  • PipelineX
  • Introduction
  • Installation
  • Getting Started
    • Getting Started with Kedro 0.17.x
    • Example/Demo Projects tested with Kedro 0.16.x
  • HatchDict: YAML/JSON enhancement for Python developers
    • Import-less Python object (class and function)
    • Anchor-less aliasing (self-lookup)
    • Python expression
  • Kedro as the unified data interface framework
    • Why the unified data interface framework is needed
    • Kedro overview
  • Kedro context to use YAML files more conveniently
    • Options available in parameters.yml
      • Define Kedro pipelines
      • Configure Kedro run config using RUN_CONFIG key
      • HatchDict feature
    • Options available in catalog.yml
      • Enable caching
      • HatchDict feature
  • Integration of Kedro with MLflow as Kedro DataSet and Hooks (callbacks)
    • How to use MLflow from Kedro projects
    • Comparison with kedro-mlflow package
  • Integration of Kedro with the additional Python packages as Kedro DataSets, Hooks (callbacks), and wrappers.
    • Additional Kedro datasets (data interface sets)
    • Additional function decorators for benchmarking
    • Use with PyTorch
    • Use with PyTorch Ignite
    • Use with OpenCV
    • Use with PyTorch Lightning
    • Use with TensorFlow/Keras
  • Build Docker image
  • Why and how PipelineX was born
  • Author
  • Contributors are welcome!
    • How to contribute
    • Contributor list
  • API Docs
    • pipelinex package
      • Subpackages
        • pipelinex.extras package
        • pipelinex.framework package
        • pipelinex.hatch_dict package
        • pipelinex.pipeline package
      • Submodules
      • pipelinex.utils module
PipelineX
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© Copyright 2021, Yusuke Minami. Revision 671d6d30.

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