pybear-dask is a Python computing library that supplements the pybear library with analogous modules that have dask capability.
Website: https://github.com/PylarBear/pybear-dask
BSD 3-Clause License. See License File.
pybear-dask requires:
- Python (>=3.10, <3.13)
- dask (<2025.1.0)
- dask-ml (<2025.1.0)
- distributed (<2025.1.0)
- pybear (>=0.2.0)
Install pybear-dask from the online PyPI package repository using pip:
(your-env) $ pip install pybear-dask
Conda distributions are expected to be made available sometime after release to PyPI.
The folder structure of pybear-dask is nearly identical to scikit-learn. This is so those that are familiar with the scikit layout and have experience with writing the associated import statements have an easy transition to pybear-dask. The pybear-dask subfolders are base and model_selection.
You can import pybear-dask's packages in the same way you would with scikit. Here are a few examples of how you could import and use pybear-dask modules:
from pybear-dask.model_selection import GSTCVDask
search = GSTCVDask()
search.fit(X, y)
from pybear-dask import model_selection as ms
search = ms.AutoGridSearchCVDask()
search.fit(X, y)Perform multiple uninterrupted passes of grid search with dask_ml GridSearchCV and dask objects utilizing progressively narrower search grids.
- Access via pybear-dask.model_selection.AutoGridSearchCVDask.
Perform conventional grid search on a classifier with concurrent threshold search using dask objects in parallel and distributed environments. Finds the global optima for the passed parameters and thresholds. Fully compliant with the dask_ml/scikit-learn GridSearchCV API.
- Access via pybear-dask.model_selection.GSTCVDask.
Perform multiple uninterrupted passes of grid search with pybear-dask GSTCVDask utilizing progressively narrower search grids.
- Access via pybear-dask.model_selection.AutoGSTCVDask.
See the changelog for a history of notable changes to pybear-dask.
- Official source code repo: https://github.com/PylarBear/pybear-dask
- Download releases: https://pypi.org/project/pybear-dask/
- Issue tracker: https://github.com/PylarBear/pybear-dask/issues
You can clone the latest source code with the command:
git clone https://github.com/PylarBear/pybear-dask.git
pybear-dask is not ready for contributions at this time!
pybear-dask 0.2 is tested via GitHub Actions to run on Linux, Windows, and MacOS, with Python versions 3.10, 3.11, and 3.12. pybear-dask is not tested on earlier versions, but some features may work.
If you want to test pybear-dask yourself, you will need:
- pytest (>=7.0.0)
The tests are not available in the PyPI pip installation. You can get the tests by downloading the tarball from the pybear-dask project page on pypi.org or cloning the pybear-dask repo from GitHub. Once you have the source files in a local project folder, create a poetry environment for the project and install the test dependencies. After installation, launch the poetry environment shell and you can launch the test suite from the root of your pybear-dask project folder with:
(your-pybear-dask-env) you@your_computer:/path/to/pybear-dask/project$ pytest tests/
This project was spun off the main pybear project just prior to the first public release of both. pybear-dask was spun off to ensure maximum stability for the main pybear project, while keeping these modules available.
Documentation is not expected to be made available via a website for this package. Use the documentation for similar packages in the main pybear package. See the repo for pybear: https://github.com/PylarBear/pybear/
- GitHub Discussions: https://github.com/PylarBear/pybear-dask/discussions
- Website: https://github.com/PylarBear/pybear-dask