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(dsv,jetstream) --> dataframe <--> bitemporal-tables

Project description

polars-hist-db

This library is for scraping data from CSV style files, temporally, into MariaDB.

Main features are:

  • Uploading data from strongly-typed Polars DataFrames.
  • Querying data into Polars DataFrames, with column types inferred from the database schema.
  • A scrape specification that:
    • Defines pipelines for typing, enriching, and normalizing data before uploading.
    • Allows construction of the 'as-of' time from file attributes or as a function of the input columns.
    • Catalogs the history of scrape inputs to prevent duplication.
    • Supports per-file transactional scraping (either the processing for a file succeeds, or the transaction is rolled back).

Development Setup

  1. Install NATS server
brew install nats-server
  1. Create a virtual environment:
python3 -m venv .venv
source .venv/bin/activate
  1. Install development dependencies:
poetry install --with dev
  1. Run tests:
poetry run pytest
  1. Make docs. The documentation will be generated in the docs/_build/html directory:
cd docs && poetry run make html

Code Style

This project follows the following code style guidelines:

  • Use type hints for all function parameters and return values
  • Follow PEP 8 style guide
  • Use Google-style docstrings
  • Keep functions focused and single-purpose
  • Write comprehensive tests for new features

Run make check to check the code style.

Contributing

  1. Fork the repository
  2. Create a feature branch
  3. Commit your changes
  4. Push to the branch
  5. Create a Pull Request

License

This project is licensed under the terms specified in the LICENSE file.

References

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