Changelog¶
0.14.0¶
IMPORTANT: This release paves the way towards a breaking update of OpenML-Python. From version 0.15, functions that had the option to return a pandas DataFrame will return a pandas DataFrame by default. This version (0.14) emits a warning if you still use the old access functionality. More concretely:
In 0.15 we will drop the ability to return dictionaries in listing calls and only provide pandas DataFrames. To disable warnings in 0.14 you have to request a pandas DataFrame (using
output_format="dataframe"
).In 0.15 we will drop the ability to return datasets as numpy arrays and only provide pandas DataFrames. To disable warnings in 0.14 you have to request a pandas DataFrame (using
dataset_format="dataframe"
).
Furthermore, from version 0.15, OpenML-Python will no longer download datasets and dataset metadata by default. This version (0.14) emits a warning if you don’t explicitly specifiy the desired behavior.
Please see the pull requests #1258 and #1260 for further information.
ADD #1081: New flag that allows disabling downloading dataset features.
ADD #1132: New flag that forces a redownload of cached data.
FIX #1244: Fixes a rare bug where task listing could fail when the server returned invalid data.
DOC #1229: Fixes a comment string for the main example.
DOC #1241: Fixes a comment in an example.
MAINT #1124: Improve naming of helper functions that govern the cache directories.
MAINT #1223, #1250: Update tools used in pre-commit to the latest versions (
black==23.30
,mypy==1.3.0
,flake8==6.0.0
).MAINT #1253: Update the citation request to the JMLR paper.
MAINT #1246: Add a warning that warns the user that checking for duplicate runs on the server cannot be done without an API key.
0.13.1¶
ADD #1081 #1132: Add additional options for (not) downloading datasets
openml.datasets.get_dataset
and cache management.ADD #1028: Add functions to delete runs, flows, datasets, and tasks (e.g.,
openml.datasets.delete_dataset
).ADD #1144: Add locally computed results to the
OpenMLRun
object’s representation if the run was created locally and not downloaded from the server.ADD #1180: Improve the error message when the checksum of a downloaded dataset does not match the checksum provided by the API.
ADD #1201: Make
OpenMLTraceIteration
a dataclass.DOC #1069: Add argument documentation for the
OpenMLRun
class.DOC #1241 #1229 #1231: Minor documentation fixes and resolve documentation examples not working.
FIX #1197 #559 #1131: Fix the order of ground truth and predictions in the
OpenMLRun
object and informat_prediction
.FIX #1198: Support numpy 1.24 and higher.
FIX #1216: Allow unknown task types on the server. This is only relevant when new task types are added to the test server.
FIX #1223: Fix mypy errors for implicit optional typing.
MAINT #1155: Add dependabot github action to automatically update other github actions.
MAINT #1199: Obtain pre-commit’s flake8 from github.com instead of gitlab.com.
MAINT #1215: Support latest numpy version.
MAINT #1218: Test Python3.6 on Ubuntu 20.04 instead of the latest Ubuntu (which is 22.04).
MAINT #1221 #1212 #1206 #1211: Update github actions to the latest versions.
0.13.0¶
FIX #1030:
pre-commit
hooks now no longer should issue a warning.FIX #1058, #1100: Avoid
NoneType
error when printing task withoutclass_labels
attribute.FIX #1110: Make arguments to
create_study
andcreate_suite
that are defined as optional by the OpenML XSD actually optional.FIX #1147:
openml.flow.flow_exists
no longer requires an API key.FIX #1184: Automatically resolve proxies when downloading from minio. Turn this off by setting environment variable
no_proxy="*"
.MAINT #1088: Do CI for Windows on Github Actions instead of Appveyor.
MAINT #1104: Fix outdated docstring for
list_task
.MAINT #1146: Update the pre-commit dependencies.
ADD #1103: Add a
predictions
property to OpenMLRun for easy accessibility of prediction data.ADD #1188: EXPERIMENTAL. Allow downloading all files from a minio bucket with
download_all_files=True
forget_dataset
.
0.12.2¶
ADD #1065: Add a
retry_policy
configuration option that determines the frequency and number of times to attempt to retry server requests.ADD #1075: A docker image is now automatically built on a push to develop. It can be used to build docs or run tests in an isolated environment.
ADD: You can now avoid downloading ‘qualities’ meta-data when downloading a task with the
download_qualities
parameter ofopenml.tasks.get_task[s]
functions.DOC: Fixes a few broken links in the documentation.
DOC #1061: Improve examples to always show a warning when they switch to the test server.
DOC #1067: Improve documentation on the scikit-learn extension interface.
DOC #1068: Create dedicated extensions page.
FIX #1075: Correctly convert y to a pandas series when downloading sparse data.
MAINT: Rename master brach to ` main` branch.
MAINT/DOC: Automatically check for broken external links when building the documentation.
MAINT/DOC: Fail documentation building on warnings. This will make the documentation building fail if a reference cannot be found (i.e. an internal link is broken).
0.12.1¶
ADD #895/#1038: Measure runtimes of scikit-learn runs also for models which are parallelized via the joblib.
DOC #1050: Refer to the webpage instead of the XML file in the main example.
DOC #1051: Document existing extensions to OpenML-Python besides the shipped scikit-learn extension.
FIX #1035: Render class attributes and methods again.
ADD #1049: Add a command line tool for configuration openml-python.
FIX #1042: Fixes a rare concurrency issue with OpenML-Python and joblib which caused the joblib worker pool to fail.
FIX #1053: Fixes a bug which could prevent importing the package in a docker container.
0.12.0¶
ADD #964: Validate
ignore_attribute
,default_target_attribute
,row_id_attribute
are set to attributes that exist on the dataset when callingcreate_dataset
.ADD #979: Dataset features and qualities are now also cached in pickle format.
ADD #982: Add helper functions for column transformers.
ADD #989:
run_model_on_task
will now warn the user the the model passed has already been fitted.ADD #1009 : Give possibility to not download the dataset qualities. The cached version is used even so download attribute is false.
ADD #1016: Add scikit-learn 0.24 support.
ADD #1020: Add option to parallelize evaluation of tasks with joblib.
ADD #1022: Allow minimum version of dependencies to be listed for a flow, use more accurate minimum versions for scikit-learn dependencies.
ADD #1023: Add admin-only calls for adding topics to datasets.
ADD #1029: Add support for fetching dataset from a minio server in parquet format.
ADD #1031: Generally improve runtime measurements, add them for some previously unsupported flows (e.g. BaseSearchCV derived flows).
DOC #973 : Change the task used in the welcome page example so it no longer fails using numerical dataset.
MAINT #671: Improved the performance of
check_datasets_active
by only querying the given list of datasets in contrast to querying all datasets. Modified the corresponding unit test.MAINT #891: Changed the way that numerical features are stored. Numerical features that range from 0 to 255 are now stored as uint8, which reduces the storage space required as well as storing and loading times.
MAINT #975, #988: Add CI through Github Actions.
MAINT #977: Allow
short
andlong
scenarios for unit tests. Reduce the workload for some unit tests.MAINT #985, #1000: Improve unit test stability and output readability, and adds load balancing.
MAINT #1018: Refactor data loading and storage. Data is now compressed on the first call to get_data.
MAINT #1024: Remove flaky decorator for study unit test.
FIX #883 #884 #906 #972: Various improvements to the caching system.
FIX #980: Speed up
check_datasets_active
.FIX #984: Add a retry mechanism when the server encounters a database issue.
FIX #1004: Fixed an issue that prevented installation on some systems (e.g. Ubuntu).
FIX #1013: Fixes a bug where
OpenMLRun.setup_string
was not uploaded to the server, prepares forrun_details
being sent from the server.FIX #1021: Fixes an issue that could occur when running unit tests and openml-python was not in PATH.
FIX #1037: Fixes a bug where a dataset could not be loaded if a categorical value had listed nan-like as a possible category.
0.11.0¶
ADD #753: Allows uploading custom flows to OpenML via OpenML-Python.
ADD #777: Allows running a flow on pandas dataframes (in addition to numpy arrays).
ADD #888: Allow passing a task_id to run_model_on_task.
ADD #894: Support caching of datasets using feather format as an option.
ADD #929: Add
edit_dataset
andfork_dataset
to allow editing and forking of uploaded datasets.ADD #866, #943: Add support for scikit-learn’s passthrough and drop when uploading flows to OpenML.
ADD #879: Add support for scikit-learn’s MLP hyperparameter layer_sizes.
ADD #894: Support caching of datasets using feather format as an option.
ADD #945: PEP 561 compliance for distributing Type information.
DOC #660: Remove nonexistent argument from docstring.
DOC #901: The API reference now documents the config file and its options.
DOC #912: API reference now shows create_task.
DOC #954: Remove TODO text from documentation.
DOC #960: document how to upload multiple ignore attributes.
FIX #873: Fixes an issue which resulted in incorrect URLs when printing OpenML objects after switching the server.
FIX #885: Logger no longer registered by default. Added utility functions to easily register logging to console and file.
FIX #890: Correct the scaling of data in the SVM example.
MAINT #371:
list_evaluations
defaultsize
changed fromNone
to10_000
.MAINT #767: Source distribution installation is now unit-tested.
MAINT #781: Add pre-commit and automated code formatting with black.
MAINT #804: Rename arguments of list_evaluations to indicate they expect lists of ids.
MAINT #836: OpenML supports only pandas version 1.0.0 or above.
MAINT #865: OpenML no longer bundles test files in the source distribution.
MAINT #881: Improve the error message for too-long URIs.
MAINT #897: Dropping support for Python 3.5.
MAINT #916: Adding support for Python 3.8.
MAINT #920: Improve error messages for dataset upload.
MAINT #921: Improve hangling of the OpenML server URL in the config file.
MAINT #925: Improve error handling and error message when loading datasets.
MAINT #928: Restructures the contributing documentation.
MAINT #936: Adding support for scikit-learn 0.23.X.
MAINT #945: Make OpenML-Python PEP562 compliant.
MAINT #951: Converts TaskType class to a TaskType enum.
0.10.2¶
ADD #857: Adds task type ID to list_runs
DOC #862: Added license BSD 3-Clause to each of the source files.
0.10.1¶
ADD #175: Automatically adds the docstring of scikit-learn objects to flow and its parameters.
ADD #737: New evaluation listing call that includes the hyperparameter settings.
ADD #744: It is now possible to only issue a warning and not raise an exception if the package versions for a flow are not met when deserializing it.
ADD #783: The URL to download the predictions for a run is now stored in the run object.
ADD #790: Adds the uploader name and id as new filtering options for
list_evaluations
.ADD #792: New convenience function
openml.flow.get_flow_id
.ADD #861: Debug-level log information now being written to a file in the cache directory (at most 2 MB).
DOC #778: Introduces instructions on how to publish an extension to support other libraries than scikit-learn.
DOC #785: The examples section is completely restructured into simple simple examples, advanced examples and examples showcasing the use of OpenML-Python to reproduce papers which were done with OpenML-Python.
DOC #788: New example on manually iterating through the split of a task.
DOC #789: Improve the usage of dataframes in the examples.
DOC #791: New example for the paper Efficient and Robust Automated Machine Learning by Feurer et al. (2015).
DOC #803: New example for the paper Don’t Rule Out Simple Models Prematurely: A Large Scale Benchmark Comparing Linear and Non-linear Classifiers in OpenML by Benjamin Strang et al. (2018).
DOC #808: New example demonstrating basic use cases of a dataset.
DOC #810: New example demonstrating the use of benchmarking studies and suites.
DOC #832: New example for the paper Scalable Hyperparameter Transfer Learning by Valerio Perrone et al. (2019)
DOC #834: New example showing how to plot the loss surface for a support vector machine.
FIX #305: Do not require the external version in the flow XML when loading an object.
FIX #734: Better handling of “old” flows.
FIX #736: Attach a StreamHandler to the openml logger instead of the root logger.
FIX #758: Fixes an error which made the client API crash when loading a sparse data with categorical variables.
FIX #779: Do not fail on corrupt pickle
FIX #782: Assign the study id to the correct class attribute.
FIX #819: Automatically convert column names to type string when uploading a dataset.
FIX #820: Make
__repr__
work for datasets which do not have an id.MAINT #796: Rename an argument to make the function
list_evaluations
more consistent.MAINT #811: Print the full error message given by the server.
MAINT #828: Create base class for OpenML entity classes.
MAINT #829: Reduce the number of data conversion warnings.
MAINT #831: Warn if there’s an empty flow description when publishing a flow.
MAINT #837: Also print the flow XML if a flow fails to validate.
FIX #838: Fix list_evaluations_setups to work when evaluations are not a 100 multiple.
FIX #847: Fixes an issue where the client API would crash when trying to download a dataset when there are no qualities available on the server.
MAINT #849: Move logic of most different
publish
functions into the base class.MAINt #850: Remove outdated test code.
0.10.0¶
ADD #737: Add list_evaluations_setups to return hyperparameters along with list of evaluations.
FIX #261: Test server is cleared of all files uploaded during unit testing.
FIX #447: All files created by unit tests no longer persist in local.
FIX #608: Fixing dataset_id referenced before assignment error in get_run function.
FIX #447: All files created by unit tests are deleted after the completion of all unit tests.
FIX #589: Fixing a bug that did not successfully upload the columns to ignore when creating and publishing a dataset.
FIX #608: Fixing dataset_id referenced before assignment error in get_run function.
DOC #639: More descriptive documention for function to convert array format.
DOC #719: Add documentation on uploading tasks.
ADD #687: Adds a function to retrieve the list of evaluation measures available.
ADD #695: A function to retrieve all the data quality measures available.
ADD #412: Add a function to trim flow names for scikit-learn flows.
ADD #715: list_evaluations now has an option to sort evaluations by score (value).
ADD #722: Automatic reinstantiation of flow in run_model_on_task. Clearer errors if that’s not possible.
ADD #412: The scikit-learn extension populates the short name field for flows.
MAINT #726: Update examples to remove deprecation warnings from scikit-learn
MAINT #752: Update OpenML-Python to be compatible with sklearn 0.21
ADD #790: Add user ID and name to list_evaluations
0.9.0¶
ADD #560: OpenML-Python can now handle regression tasks as well.
ADD #620, #628, #632, #649, #682: Full support for studies and distinguishes suites from studies.
ADD #607: Tasks can now be created and uploaded.
ADD #647, #673: Introduced the extension interface. This provides an easy way to create a hook for machine learning packages to perform e.g. automated runs.
ADD #548, #646, #676: Support for Pandas DataFrame and SparseDataFrame
ADD #662: Results of listing functions can now be returned as pandas.DataFrame.
ADD #59: Datasets can now also be retrieved by name.
ADD #672: Add timing measurements for runs, when possible.
ADD #661: Upload time and error messages now displayed with list_runs.
ADD #644: Datasets can now be downloaded ‘lazily’, retrieving only metadata at first, and the full dataset only when necessary.
ADD #659: Lazy loading of task splits.
ADD #516: run_flow_on_task flow uploading is now optional.
ADD #680: Adds openml.config.start_using_configuration_for_example (and resp. stop) to easily connect to the test server.
ADD #75, #653: Adds a pretty print for objects of the top-level classes.
FIX #642: check_datasets_active now correctly also returns active status of deactivated datasets.
FIX #304, #636: Allow serialization of numpy datatypes and list of lists of more types (e.g. bools, ints) for flows.
FIX #651: Fixed a bug that would prevent openml-python from finding the user’s config file.
FIX #693: OpenML-Python uses liac-arff instead of scipy.io for loading task splits now.
DOC #678: Better color scheme for code examples in documentation.
DOC #681: Small improvements and removing list of missing functions.
DOC #684: Add notice to examples that connect to the test server.
DOC #688: Add new example on retrieving evaluations.
DOC #691: Update contributing guidelines to use Github draft feature instead of tags in title.
DOC #692: All functions are documented now.
MAINT #184: Dropping Python2 support.
MAINT #596: Fewer dependencies for regular pip install.
MAINT #652: Numpy and Scipy are no longer required before installation.
MAINT #655: Lazy loading is now preferred in unit tests.
MAINT #667: Different tag functions now share code.
MAINT #666: More descriptive error message for TypeError in list_runs.
MAINT #668: Fix some type hints.
MAINT #677: dataset.get_data now has consistent behavior in its return type.
MAINT #686: Adds ignore directives for several mypy folders.
MAINT #629, #630: Code now adheres to single PEP8 standard.
0.8.0¶
ADD #440: Improved dataset upload.
ADD #545, #583: Allow uploading a dataset from a pandas DataFrame.
ADD #528: New functions to update the status of a dataset.
ADD #523: Support for scikit-learn 0.20’s new ColumnTransformer.
ADD #459: Enhanced support to store runs on disk prior to uploading them to OpenML.
ADD #564: New helpers to access the structure of a flow (and find its subflows).
ADD #618: The software will from now on retry to connect to the server if a connection failed. The number of retries can be configured.
FIX #538: Support loading clustering tasks.
FIX #464: Fixes a bug related to listing functions (returns correct listing size).
FIX #580: Listing function now works properly when there are less results than requested.
FIX #571: Fixes an issue where tasks could not be downloaded in parallel.
FIX #536: Flows can now be printed when the flow name is None.
FIX #504: Better support for hierarchical hyperparameters when uploading scikit-learn’s grid and random search.
FIX #569: Less strict checking of flow dependencies when loading flows.
FIX #431: Pickle of task splits are no longer cached.
DOC #540: More examples for dataset uploading.
DOC #554: Remove the doubled progress entry from the docs.
MAINT #613: Utilize the latest updates in OpenML evaluation listings.
MAINT #482: Cleaner interface for handling search traces.
MAINT #557: Continuous integration works for scikit-learn 0.18-0.20.
MAINT #542: Continuous integration now runs python3.7 as well.
MAINT #535: Continuous integration now enforces PEP8 compliance for new code.
MAINT #527: Replace deprecated nose by pytest.
MAINT #510: Documentation is now built by travis-ci instead of circle-ci.
MAINT: Completely re-designed documentation built on sphinx gallery.
MAINT #462: Appveyor CI support.
MAINT #477: Improve error handling for issue #479: the OpenML connector fails earlier and with a better error message when failing to create a flow from the OpenML description.
MAINT #561: Improve documentation on running specific unit tests.
0.4.-0.7¶
There is no changelog for these versions.
0.3.0¶
Add this changelog
2nd example notebook PyOpenML.ipynb
Pagination support for list datasets and list tasks
Prior¶
There is no changelog for prior versions.