skself
======

.. py:module:: skself


Submodules
----------

.. toctree::
   :maxdepth: 1

   /autoapi/skself/data/index
   /autoapi/skself/embedding_training /index
   /autoapi/skself/gptano/index
   /autoapi/skself/partial_annotations/index
   /autoapi/skself/test/index
   /autoapi/skself/utils/index


Attributes
----------

.. autoapisummary::

   skself.__version__


Functions
---------

.. autoapisummary::

   skself.enable_hyper_search_progress_bar


Package Contents
----------------

.. py:function:: enable_hyper_search_progress_bar()

   Progress bar for sklearn parallel searches in jupyter notebooks.

   This fixes two issues:

   1. Notebooks unrealiably displas output from subprocesses
   2. Parallel Processing does not have a process bar in sklearn

   WARNING. This sets the default parallelization in sklearn to threading.
   That's okay unless you want to utilize the processing power of multiple machines.


.. py:data:: __version__
   :value: '0.1.0'