datopy 0.0.1 — datopy is up and running

Datopy is a package for simplifying the early stages of the data analysis workflow (getting data, modeling data, validating data, etc). It is first and foremost a personal use package; however, I prioritize extensibility and clear documentation, and I hope that other developers will find the package useful.

While I make no guarantees in the way of performance or functionality, datopy is now in more-or-less working order (parts of it, at least). Feel free to explore, sample, and extend.

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This release includes some routines for data modeling (see datopy.modeling), ETL (Extract, Transform, Load; datopy.etl), and data inspection (datopy.inspection, datopy.stylesheet). Still to come: the datopy.models subpackage, which will include data models, validation, and processing routines for dealing with media metadata (datopy.models.media), animal data (datopy.models.eco), and global development indicators (datopy.models.global).

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Here's a snapshot of what this release includes:

What's Included

Exciting Features 🙌

• Core data modeling/validation functionality and various workflow-related utilities

Stability and Performance ⚡️

• Extensive type checking and doctesting
• Continual performance and coverage testing via tox and Github actions
• Tested in Python 3.10 and Python 3.11 environments

Key Patches

• Improved type checking and examples (#5)
• Improved doctesting (#6)
• Improved environment management (#7)
• Better orchestration and unittesting suite (#9)
• Data validation schemes for retrieval and processing (#14)
• Generic Pydantic media model (#28)

Full Changelog: https://github.com/bainmatt/datopy/commits/v0.0.1