kedro-auto-catalog 0.0.0

A rich terminal report for coveragepy.

Kedro Auto Catalog

A configurable version of the built in kedro catalog create cli. Default types can be configured in the projects settings.py, to get these types rather than MemoryDataSets.

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Table of Contents

• Installation
• License

Installation

pip install kedro-auto-catalog

Configuration

Configure the project defaults in src/<project_name>/settings.py with this dict.

AUTO_CATALOG = {
    "directory": "data",
    "subdirs": ["raw", "intermediate", "primary"],
    "default_extension": "parquet",
    "default_type": "pandas.ParquetDataSet",
}

Usage

To auto create catalog entries for the __default__ pipeline, run this from the command line.

kedro auto-catalog -p __default__

If you want a reminder of what to do, use the --help.

❯ kedro auto-catalog --help❯
Usage: kedro auto-catalog [OPTIONS]

  Create Data Catalog YAML configuration with missing datasets.

  Add configurable datasets to Data Catalog YAML configuration file for each
  dataset in a registered pipeline if it is missing from the `DataCatalog`.

  The catalog configuration will be saved to
  `<conf_source>/<env>/catalog/<pipeline_name>.yml` file.

  Configure the project defaults in `src/<project_name>/settings.py` with this
  dict.

Options:
  -e, --env TEXT       Environment to create Data Catalog YAML file in.
                       Defaults to `base`.
  -p, --pipeline TEXT  Name of a pipeline.  [required]
  -h, --help           Show this message and exit.

License

kedro-auto-catalog is distributed under the terms of the MIT license.