Standardize use of n_jobs and reporting of computation time (#1038)

* Unit test to test existence of refit time

* Measuring runtime always

* Removing redundant check in unit test

* Updating docs with runtimes

* Adding more utilities to new example

* Removing refit_time + fetching trace runtime in example

* rename example

* Reiterating with changes to example from @mfeurer suggestions

* Including refit time and other minor formatting

* Adding more cases + a concluding summary

* Cosmetic changes

* Adding 5th case with no release of GIL

* Removing debug code

* Runtime measurement example updates (#1052)

* Minor reshuffling

* Update examples/30_extended/fetch_runtimes_tutorial.py

Co-authored-by: Neeratyoy Mallik <[email protected]>

Co-authored-by: Neeratyoy Mallik <[email protected]>

Co-authored-by: Matthias Feurer <[email protected]>

Author: Neeratyoy

doc/usage.rst

@@ -145,13 +145,19 @@ obtained on. Learn how to share your datasets in the following tutorial:
 
 * `Upload a dataset <examples/30_extended/create_upload_tutorial.html>`_
 
-~~~~~~~~~~~~~~~~~~~~~~~
+***********************
 Extending OpenML-Python
-~~~~~~~~~~~~~~~~~~~~~~~
+***********************
 
 OpenML-Python provides an extension interface to connect other machine learning libraries than
 scikit-learn to OpenML. Please check the :ref:`api_extensions` and use the
 scikit-learn extension in :class:`openml.extensions.sklearn.SklearnExtension` as a starting point.
+
+Runtime measurement is incorporated in the OpenML sklearn-extension. Example usage and potential
+usage for Hyperparameter Optimisation can be found in the example tutorial:
+`HPO using OpenML <examples/30_extended/fetch_runtimes.html>`_
+
+
 Here is a list of currently maintained OpenML extensions:
 
 * `openml-keras <https://github.com/openml/openml-keras>`_