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-0.8.19.tar.gz (42.3 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-0.8.19-py3-none-any.whl (65.1 kB view details)

Uploaded Python 3

File details

Details for the file polars_hist_db-0.8.19.tar.gz.

File metadata

  • Download URL: polars_hist_db-0.8.19.tar.gz
  • Upload date:
  • Size: 42.3 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-0.8.19.tar.gz
Algorithm Hash digest
SHA256 bee3dd3873a75b0d9f0d621671e033b9a1c335d5189cfffa99fa1d4cbc114061
MD5 4040f62a277f1be3ce84cd5c2ac6085a
BLAKE2b-256 8173308358690ae0cba6795779c9f7f8d2063a38d0e8d37bcc29dcbcf557364d

See more details on using hashes here.

File details

Details for the file polars_hist_db-0.8.19-py3-none-any.whl.

File metadata

  • Download URL: polars_hist_db-0.8.19-py3-none-any.whl
  • Upload date:
  • Size: 65.1 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-0.8.19-py3-none-any.whl
Algorithm Hash digest
SHA256 b462a3fc16444aab0b5ca80eec91be077236fd9a035735a38e68c3bc6f317836
MD5 a9a19e0e154f74df21113e0a92ff263d
BLAKE2b-256 ff7538cf1546e772254b2de0801edf236c9135ed9ca308680ba79ba2e465625b

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