Epochalyst is the base for Team Epoch competitions.

This package contains many modules and classes necessary to construct the src code for machine learning competitions.

Epochalyst: A fusion of "Epoch" and "Catalyst," this name positions your pipeline as a catalyst in the field of machine learning, sparking significant advancements and transformations.

Installation

Install epochalyst via pip:

pip install epochalyst

Or using Poetry:

poetry add epochalyst

Pytest coverage report

To generate pytest coverage report run

python -m pytest --cov=epochalyst --cov-branch --cov-report=html:coverage_re

Imports

Caching

For caching some imports are only required, these have to be manually installed when needed

• dask >= 2023.12.0 & dask-expr
• pandas >= 1.3.0
• polars
• pyarrow >= 6.0.0 (Read parquet files)
• annotated-types >= 0.6.0

Model

There is support for using timm models. To be able to do so the user must manually install timm.

• timm >= 0.9.16

Augmentation

There is also implementations of augmentations that are not in commonly used packages. Most of these are for time series data but there are implmenetations for CutMix and MixUp for images that can be used in the pipeline. To be able to use these the user must manually install kornia.

• kornia >= 0.7.2

Documentation

Documentation is generated using Sphinx.

To make the documentation, run make html with docs as the working directory. The documentation can then be found in docs/_build/html/index.html.

Here's a short command to make the documentation and open it in the browser:

cd ./docs/;
./make.bat html; start chrome file://$PWD/_build/html/index.html
cd ../