Skip to main content

(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

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

polars_hist_db-0.8.3.tar.gz (40.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

polars_hist_db-0.8.3-py3-none-any.whl (62.9 kB view details)

Uploaded Python 3

File details

Details for the file polars_hist_db-0.8.3.tar.gz.

File metadata

  • Download URL: polars_hist_db-0.8.3.tar.gz
  • Upload date:
  • Size: 40.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/2.1.2 CPython/3.12.3 Linux/6.11.0-1018-azure

File hashes

Hashes for polars_hist_db-0.8.3.tar.gz
Algorithm Hash digest
SHA256 fcae94eedaedef035c3e8c1984b850eff847ff4598e99e7bc1d15d1d26ea45aa
MD5 eee62044351bb5021fe8087f42ba414e
BLAKE2b-256 9d14c161b17964cb48a40bebb032c2a6873bc952df58cbd34b1a4056343a9b34

See more details on using hashes here.

File details

Details for the file polars_hist_db-0.8.3-py3-none-any.whl.

File metadata

  • Download URL: polars_hist_db-0.8.3-py3-none-any.whl
  • Upload date:
  • Size: 62.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/2.1.2 CPython/3.12.3 Linux/6.11.0-1018-azure

File hashes

Hashes for polars_hist_db-0.8.3-py3-none-any.whl
Algorithm Hash digest
SHA256 27eadf9eb49f115873fa05f38256fb7ae34e6153a573ddcbb26026b70928b9cb
MD5 0c5d40047ec4100f6a6c33cf65d911ef
BLAKE2b-256 14af61080142c0d3934c7f27f4868e18687c4d22f26a9857a29c8751978cf2cc

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page