pybear-dask
===========
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.. |DaskVersion| replace:: <2025.1.0
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.. |PybearVersion| replace:: >=0.2.0
.. |PytestVersion| replace:: >=7.0.0
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
License
-------
BSD 3-Clause License. See `License File <https://github.com/PylarBear/pybear-dask/blob/main/LICENSE>`__.
=======
Installation
------------
Dependencies
~~~~~~~~~~~~
pybear-dask requires:
- Python (|PythonVersion|)
- dask (|DaskVersion|)
- dask-ml (|DaskMLVersion|)
- distributed (|DistributedVersion|)
- pybear (|PybearVersion|)
User installation
~~~~~~~~~~~~~~~~~
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.
=======
Usage
-----
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:
.. code-block:: console
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)
=======
Major Modules
-------------
AutoGridSearchCVDask
~~~~~~~~~~~~~~~~~~~~
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.
GSTCVDask (GridSearchThresholdCV for Dask)
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.
AutoGSTCVDask (AutoGridSearchThresholdCV for Dask)
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Perform multiple uninterrupted passes of grid search with pybear-dask GSTCVDask
utilizing progressively narrower search grids.
- Access via pybear-dask.model_selection.AutoGSTCVDask.
=======
Changelog
---------
See the `changelog <https://github.com/PylarBear/pybear-dask/blob/main/CHANGELOG.md>`__
for a history of notable changes to pybear-dask.
=======
Development
-----------
Important links
~~~~~~~~~~~~~~~
- 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
Source code
~~~~~~~~~~~
You can clone the latest source code with the command::
git clone https://github.com/PylarBear/pybear-dask.git
Contributing
~~~~~~~~~~~~
pybear-dask is not ready for contributions at this time!
Testing
~~~~~~~
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 (|PytestVersion|)
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 <https://pypi.org/project/pybear-dask/>`_ or cloning the pybear-dask
repo from `GitHub <https://github.com/PylarBear/pybear-dask>`_. 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/
Project History
---------------
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.
Help and Support
----------------
Documentation
~~~~~~~~~~~~~
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/
Communication
~~~~~~~~~~~~~
- GitHub Discussions: https://github.com/PylarBear/pybear-dask/discussions
- Website: https://github.com/PylarBear/pybear-dask
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See `License File <https://github.com/PylarBear/pybear-dask/blob/main/LICENSE>`__.\n\n=======\n\nInstallation\n------------\n\nDependencies\n~~~~~~~~~~~~\n\npybear-dask requires:\n\n- Python (|PythonVersion|)\n- dask (|DaskVersion|)\n- dask-ml (|DaskMLVersion|)\n- distributed (|DistributedVersion|)\n- pybear (|PybearVersion|)\n\nUser installation\n~~~~~~~~~~~~~~~~~\n\nInstall pybear-dask from the online PyPI package repository using ``pip``::\n\n (your-env) $ pip install pybear-dask\n\nConda distributions are expected to be made available sometime after release to\nPyPI.\n\n=======\n\nUsage\n-----\nThe folder structure of pybear-dask is nearly identical to scikit-learn. 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