My personal little ML engineering library.
Project description
RiCS: my personal little ML engineering library.
What is it?
An assorted collection of reusable functions that used to live in a Dropbox folder. RiCS, pronounced "rix", is short for Richard's Code Stash. I started this project with the purpose of learning more about Python best practices, typing and the Python ecosystem.
It has grown organically since then, and now provides a wide variety of small utility functions. Large submodules are typically converted to stand-alone PyPI packages once they begin to mature.
Highlighted Features
- Multivariate performance testing and plotting.
- get_by_full_name(): Import functions, objects and classes by name.
- rics.collections.dicts: Extended functionality for the built-in
dict
type. - basic_config(): Configure logging for development.
- And much more; click here for the full API.
Related libraries
The following packages started life as RiCS submodules.
-
Turn meaningless IDs into human-readable labels.
-
Time-based k-fold validation splits for heterogeneous data.
Installation
The package is published through the Python Package Index (PyPI). Source code is available on GitHub: https://github.com/rsundqvist/rics
pip install -U rics
This is the preferred method to install rics
, as it will always install the
most recent stable release.
If you don't have pip installed, this Python installation guide can guide you through the process.
License
Documentation
Hosted on Read the Docs: https://rics.readthedocs.io
Contributing
All contributions, bug reports, bug fixes, documentation improvements, enhancements, and ideas are welcome. To get started, see the Contributing Guide and Code of Conduct.
Project details
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