This is the release note of v3.4.0.

Highlights

Optuna 3.4 newly supports the following new features. See our release blog for more detailed information.

• Preferential Optimization (Optuna Dashboard)
• Optuna Artifact
• Jupyter Lab Extension
• VS Code Extension
• User-defined Distance for Categorical Parameters in TPE
• Constrained Optimization Support for Visualization Functions
• User-Defined Plotly’s Figure Support (Optuna Dashboard)
• 3D Model Viewer Support (Optuna Dashboard)

Breaking Changes

• Remove deprecated arguments with regard to LightGBM>=4.0 (#4844)
• Deprecate SkoptSampler (#4913)

New Features

• Support constraints for intermediate values plot (#4851, thanks @adjeiv!)
• Display all objectives on hyperparameter importances plot (#4871)
• Implement get_all_study_names() (#4898)
• Support constraints plot_rank (#4899, thanks @ryota717!)
• Support Study Artifacts (#4905)
• Support specifying distance between categorical choices in TPESampler (#4926)
• Add metric_names getter to study (#4930)
• Add artifact middleware for exponential backoff retries (#4956)
• Add GCSArtifactStore (#4967, thanks @semiexp!)
• Add BestValueStagnationEvaluator (#4974, thanks @smygw72!)
• Allow user-defined objective names in hyperparameter importance plots (#4986)

Enhancements

• CHG constrained param displayed in #cccccc (#4877, thanks @louis-she!)
• Faster implementation of fANOVA (#4897)
• Support constraint in plot slice (#4906, thanks @hrntsm!)
• Add mimetype input (#4910, thanks @hrntsm!)
• Show all ticks in _parallel_coordinate.py when log scale (#4911)
• Speed up multi-objective TPE (#5017)

Bug Fixes

• Fix numpy indexing bugs and named tuple comparing (#4874, thanks @ryota717!)
• Fix fail_stale_trials with race condition (#4886)
• Fix alias handler (#4887)
• Add lazy random state and use it in RandomSampler (#4970, thanks @shu65!)
• Fix TensorBoard error on categorical choices of mixed types (#4973, thanks @ciffelia!)
• Use lazy random state in samplers (#4976, thanks @shu65!)
• Fix an error that does not consider min_child_samples (#5007)
• Fix BruteForceSampler in parallel optimization (#5022)

Documentation

• Fix typo in _filesystem.py (#4909)
• Mention a pruner instance is not stored in a storage in resuming tutorial (#4927)
• Add introduction of optuna-fast-fanova in documents (#4943)
• Add artifact tutorial (#4954)
• Fix an example code in Boto3ArtifactStore's docstring (#4957)
• Add tutorial for JournalStorage (#4980, thanks @semiexp!)
• Fix document regarding ArtifactNotFound (#4982, thanks @smygw72!)
• Add the workaround for duplicated samples to FAQ (#5006)

Examples

• Add huggingface's link to external projects (optuna/optuna-examples#201)
• Fix samplers CI (optuna/optuna-examples#202)
• Set version constraint on aim (optuna/optuna-examples#206)
• Add an example of Optuna Terminator for LightGBM (optuna/optuna-examples#210, thanks @hamster-86!)

Tests

• Reduce n_trials in test_combination_of_different_distributions_objective (#4950)
• Replaces California housing dataset with iris dataset (#4953)
• Fix numpy duplication warning (#4978, thanks @torotoki!)
• Make test order deterministic for pytest-xdist (#4999)

Code Fixes

• Move shap (optuna/optuna-integration#32)
• Remove shap (#4791)
• Use isinstance instead of if type() is ... (#4896)
• Make cmaes dependency optional (#4901)
• Call internal sampler's before_trial (#4914)
• Refactor _grid.py (#4918)
• Fix the checks-integration errors on LightGBMTuner (#4923)
• Replace deprecated botorch method to remove warning (#4940)
• Fix type annotation (#4941)
• Add _split_trials instead of _get_observation_pairs and _split_observation_pairs (#4947)
• Use __future__.annotations in optuna/visualization/_optimization_history.py (#4964, thanks @YuigaWada!)
• Fix #4508 for optuna/visualization/_hypervolume_history.py (#4965, thanks @RuTiO2le!)
• Use future annotation in optuna/_convert_positional_args.py (#4966, thanks @hamster-86!)
• Fix type annotation of SQLAlchemy (#4968)
• Use collections.abc in optuna/visualization/_edf.py (#4969, thanks @g-tamaki!)
• Use collections.abc in plot pareto front (#4971)
• Remove experimental_func from metric_names property (#4983, thanks @semiexp!)
• Add __future__.annotations to progress_bar.py (#4992)
• Fix annotations in optuna/optuna/visualization/matplotlib/_optimization_history.py (#5015, thanks @sousu4!)

Continuous Integration

• Fix checks integration (#4869)
• Remove fakeredis version constraint (#4873)
• Support asv 0.6.0 (#4882)
• Fix speed-benchmarks CI (#4903)
• Fix Tests (MPI) CI (#4904)
• Fix xgboost pruning callback (#4921)
• Enhance speed benchmark (#4981, thanks @g-tamaki!)
• Drop Python 3.7 on tests-mpi (#4998)
• Remove Python 3.7 from the development docker image build (#5009)
• Use CPU version of PyTorch in Docker image (#5019)

Other

• Bump up version number to v3.4.0.dev (optuna/optuna-integration#37)
• Update python shield in README.md (optuna/optuna-integration#39)
• Replace deprecated mypy option (optuna/optuna-integration#40)
• Bump up version to v3.4.0 (optuna/optuna-integration#42)
• Bump the version up to v3.4.0.dev (#4861)
• Use OIDC (#4867)
• Add FUNDING.yml (#4912)
• Update optional-dependencies and document deselecting integration tests in CONTRIBUTING.md (#4962)
• Bump the version up to v3.4.0 (#5031)

Thanks to All the Contributors!

This release was made possible by the authors and the people who participated in the reviews and discussions.

@Alnusjaponica, @HideakiImamura, @RuTiO2le, @YuigaWada, @adjeiv, @c-bata, @ciffelia, @contramundum53, @cross32768, @eukaryo, @g-tamaki, @g-votte, @gen740, @hamster-86, @hrntsm, @hvy, @keisuke-umezawa, @knshnb, @lucasmrdt, @louis-she, @moririn2528, @nabenabe0928, @not522, @nzw0301, @ryota717, @semiexp, @shu65, @smygw72, @sousu4, @torotoki, @toshihikoyanase, @xadrianzetx