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Prepare release 0.14 (#1262)
* Bump version number and add changelog * Incorporate feedback from Pieter * Fix unit test * Make assert less strict * Update release notes * Fix indent
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‎doc/progress.rst‎

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Changelog
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=========
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0.14.0
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~~~~~~
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**IMPORTANT:** This release paves the way towards a breaking update of OpenML-Python. From version
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0.15, functions that had the option to return a pandas DataFrame will return a pandas DataFrame
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by default. This version (0.14) emits a warning if you still use the old access functionality.
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More concretely:
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* In 0.15 we will drop the ability to return dictionaries in listing calls and only provide
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pandas DataFrames. To disable warnings in 0.14 you have to request a pandas DataFrame
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(using ``output_format="dataframe"``).
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* In 0.15 we will drop the ability to return datasets as numpy arrays and only provide
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pandas DataFrames. To disable warnings in 0.14 you have to request a pandas DataFrame
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(using ``dataset_format="dataframe"``).
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Furthermore, from version 0.15, OpenML-Python will no longer download datasets and dataset metadata
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by default. This version (0.14) emits a warning if you don't explicitly specifiy the desired behavior.
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Please see the pull requests #1258 and #1260 for further information.
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* ADD #1081: New flag that allows disabling downloading dataset features.
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* ADD #1132: New flag that forces a redownload of cached data.
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* FIX #1244: Fixes a rare bug where task listing could fail when the server returned invalid data.
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* DOC #1229: Fixes a comment string for the main example.
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* DOC #1241: Fixes a comment in an example.
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* MAINT #1124: Improve naming of helper functions that govern the cache directories.
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* MAINT #1223, #1250: Update tools used in pre-commit to the latest versions (``black==23.30``, ``mypy==1.3.0``, ``flake8==6.0.0``).
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* MAINT #1253: Update the citation request to the JMLR paper.
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* MAINT #1246: Add a warning that warns the user that checking for duplicate runs on the server cannot be done without an API key.
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0.13.1
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~~~~~~
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* ADD #1081 #1132: Add additional options for (not) downloading datasets ``openml.datasets.get_dataset`` and cache management.
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* ADD #1028: Add functions to delete runs, flows, datasets, and tasks (e.g., ``openml.datasets.delete_dataset``).
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* ADD #1144: Add locally computed results to the ``OpenMLRun`` object's representation if the run was created locally and not downloaded from the server.
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* ADD #1180: Improve the error message when the checksum of a downloaded dataset does not match the checksum provided by the API.
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* ADD #1201: Make ``OpenMLTraceIteration`` a dataclass.
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* DOC #1069: Add argument documentation for the ``OpenMLRun`` class.
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* DOC #1241 #1229 #1231: Minor documentation fixes and resolve documentation examples not working.
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* FIX #1197 #559 #1131: Fix the order of ground truth and predictions in the ``OpenMLRun`` object and in ``format_prediction``.
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* FIX #1198: Support numpy 1.24 and higher.
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* FIX #1216: Allow unknown task types on the server. This is only relevant when new task types are added to the test server.
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* FIX #1223: Fix mypy errors for implicit optional typing.
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* MAINT #1155: Add dependabot github action to automatically update other github actions.
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* MAINT #1199: Obtain pre-commit's flake8 from github.com instead of gitlab.com.
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* MAINT #1215: Support latest numpy version.
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* MAINT #1218: Test Python3.6 on Ubuntu 20.04 instead of the latest Ubuntu (which is 22.04).
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* MAINT #1221 #1212 #1206 #1211: Update github actions to the latest versions.
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* ADD #1081 #1132: Add additional options for (not) downloading datasets ``openml.datasets.get_dataset`` and cache management.
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* ADD #1028: Add functions to delete runs, flows, datasets, and tasks (e.g., ``openml.datasets.delete_dataset``).
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* ADD #1144: Add locally computed results to the ``OpenMLRun`` object's representation if the run was created locally and not downloaded from the server.
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* ADD #1180: Improve the error message when the checksum of a downloaded dataset does not match the checksum provided by the API.
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* ADD #1201: Make ``OpenMLTraceIteration`` a dataclass.
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* DOC #1069: Add argument documentation for the ``OpenMLRun`` class.
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* DOC #1241 #1229 #1231: Minor documentation fixes and resolve documentation examples not working.
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* FIX #1197 #559 #1131: Fix the order of ground truth and predictions in the ``OpenMLRun`` object and in ``format_prediction``.
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* FIX #1198: Support numpy 1.24 and higher.
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* FIX #1216: Allow unknown task types on the server. This is only relevant when new task types are added to the test server.
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* FIX #1223: Fix mypy errors for implicit optional typing.
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* MAINT #1155: Add dependabot github action to automatically update other github actions.
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* MAINT #1199: Obtain pre-commit's flake8 from github.com instead of gitlab.com.
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* MAINT #1215: Support latest numpy version.
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* MAINT #1218: Test Python3.6 on Ubuntu 20.04 instead of the latest Ubuntu (which is 22.04).
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* MAINT #1221 #1212 #1206 #1211: Update github actions to the latest versions.
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0.13.0
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~~~~~~

‎openml/__version__.py‎

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# License: BSD 3-Clause
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# The following line *must* be the last in the module, exactly as formatted:
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__version__ = "0.14.0dev"
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__version__ = "0.14.0"

‎tests/test_utils/test_utils.py‎

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def test_list_all_with_multiple_batches(self):
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res = openml.utils._list_all(
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listing_call=openml.tasks.functions._list_tasks, output_format="dict", batch_size=2000
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listing_call=openml.tasks.functions._list_tasks, output_format="dict", batch_size=1050
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)
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# Verify that test server state is still valid for this test to work as intended
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# -> If the number of results is less than 2000, the test can not test the
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# batching operation.
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assert len(res) > 2000
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# -> If the number of results is less than 1050, the test can not test the
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# batching operation. By having more than 1050 results we know that batching
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# was triggered. 1050 appears to be a number of tasks that is available on a fresh
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# test server.
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assert len(res) > 1050
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openml.utils._list_all(
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listing_call=openml.tasks.functions._list_tasks,
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output_format="dataframe",
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batch_size=2000,
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batch_size=1050,
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)
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# Comparing the number of tasks is not possible as other unit tests running in
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# parallel might be adding or removing tasks!
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# assert len(res) <= len(res2)
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@unittest.mock.patch("openml._api_calls._perform_api_call", side_effect=mocked_perform_api_call)
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def test_list_all_few_results_available(self, _perform_api_call):

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