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Release 2.8.0 (#495)
Release PR for 2.8.0 * changelog * version bump
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.all-contributorsrc

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"contributions": [
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"doc"
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]
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},
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{
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"login": "sairevanth25",
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"name": "Sai Revanth Gowravajhala",
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"avatar_url": "https://avatars.githubusercontent.com/u/132150745?v=4",
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"profile": "https://github.com/SaiRevanth25",
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"contributions": [
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"code",
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"doc"
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]
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}
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]
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}

CODEOWNERS

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# The file specifies framework level core developers for automated review requests
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#
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# Note: historically, this file has been used to maintain a list of
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# algorithm maintainers as specified in GOVERNANCE.md.
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# This is no longer the case, algorithm maintainers are now
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# specified directly in the estimator,
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# in the "maintainers" tag of the respective scikit-base object.
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#
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# Algorithm maintainers are programmatically queryable
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# via Estimator.get_class_tag("maintainers").
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# Further lookup such as "which algorithms does M maintain"
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# can be carried out using registry.all_estimators
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* @achieveordie @benheid @fkiraly @fnhirwa @geetu040 @pranavvp16 @sairevanth25 @XinyuWuu @yarnabrina

README.md

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<a href="https://skpro.readthedocs.io/en/latest"><img src="https://github.com/sktime/skpro/blob/main/docs/source/images/skpro-banner.png" width="500" align="right" /></a>
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:rocket: **Version 2.7.0 out now!** [Read the release notes here.](https://skpro.readthedocs.io/en/latest/changelog.html).
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:rocket: **Version 2.8.0 out now!** [Read the release notes here.](https://skpro.readthedocs.io/en/latest/changelog.html).
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`skpro` is a library for supervised probabilistic prediction in python.
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It provides `scikit-learn`-like, `scikit-base` compatible interfaces to:

docs/source/_static/switcher.json

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"url": "https://skpro.readthedocs.io/en/latest/"
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},
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{
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"name": "2.7.0 (stable)",
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"name": "2.8.0 (stable)",
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"version": "stable",
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"url": "https://skpro.readthedocs.io/en/v2.8.0/"
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},
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{
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"name": "2.7.0",
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"version": "stable",
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"url": "https://skpro.readthedocs.io/en/v2.7.0/"
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},

docs/source/changelog.rst

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For planned changes and upcoming releases, see roadmap in the
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`issue tracker <https://github.com/sktime/skpro/issues>`_.
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[2.8.0] - 2024-11-17
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====================
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Feature and maintenance release.
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Dependency changes
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~~~~~~~~~~~~~~~~~~
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* ``scikit-base`` bounds have been updated to ``>=0.6.1,<0.13.0``.
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* ``pymc`` is now a soft dependency, for probabilistic regressors.
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* ``polars`` (data container soft dependency) bounds have been updated to ``<1.14.0``.
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Enhancements
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~~~~~~~~~~~~
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* [ENH] Creating a new Bayesian Regressor with ``pymc`` as a backend (:pr:`358`) :user:`meraldoantonio`
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* [ENH] add suite test for docstring and ``get_test_params`` coverage (:pr:`482`) :user:`fkiraly`
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* [ENH] Synchronize dependency checker with ``sktime`` counterpart (:pr:`490`) :user:`meraldoantonio`
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Maintenance
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~~~~~~~~~~~
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* [MNT] fix failing ``code-quality`` CI step (:pr:`483`) :user:`fkiraly`
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* [MNT] [Dependabot](deps): Update ``scikit-base`` requirement from ``<0.12.0,>=0.6.1`` to ``>=0.6.1,<0.13.0`` (:pr:`483`) :user:`dependabot[bot]`
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* [MNT] [Dependabot](deps): Update ``sphinx-gallery`` requirement from ``<0.18.0`` to ``<0.19.0`` (:pr:`481`) :user:`dependabot[bot]`
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* [MNT] [Dependabot](deps): Update ``sphinx-issues`` requirement from ``<5.0.0`` to ``<6.0.0`` (:pr:`484`) :user:`dependabot[bot]`
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* [MNT] [Dependabot](deps): Update ``polars`` requirement from ``<1.10.0`` to ``<1.14.0`` (:pr:`491`) :user:`dependabot[bot]`
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* [MNT] [Dependabot](deps): Bump codecov/codecov-action from ``4`` to ``5`` (:pr:`494`) :user:`dependabot[bot]`
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Documentation
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~~~~~~~~~~~~~
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* [DOC] in docstring, rename ``Example`` to ``Examples`` sections (:pr:`487`) :user:`fkiraly`
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Contributors
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~~~~~~~~~~~~
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:user:`fkiraly`,
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:user:`meraldoantonio`
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[2.7.0] - 2024-10-08
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====================

pyproject.toml

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[project]
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name = "skpro"
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version = "2.7.0"
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version = "2.8.0"
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description = "A unified framework for tabular probabilistic regression, time-to-event prediction, and probability distributions in python"
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authors = [
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{name = "skpro developers", email = "[email protected]"},

skpro/__init__.py

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"""skpro."""
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__version__ = "2.7.0"
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__version__ = "2.8.0"
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__all__ = ["show_versions"]
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skpro/base/_base.py

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def __init__(self):
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super().__init__()
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import sys
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from warnings import warn
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from packaging.specifiers import SpecifierSet
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py39_or_higher = SpecifierSet(">=3.9")
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sys_version = sys.version.split(" ")[0]
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# todo 2.8.0 - check whether python 3.8 eol is reached.
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# If yes, remove this msg.
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if sys_version not in py39_or_higher:
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warn(
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f"From skpro 2.5.0, skpro requires Python version >=3.9, "
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f"but found {sys_version}. "
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"The package can still be installed, until 3.8 end of life "
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"is reached, "
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"but some functionality may not work as test coverage is dropped."
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"Kindly note for context: python 3.8 will reach end of life "
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"in October 2024, and multiple skpro core dependencies, "
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"including scikit-learn, have already dropped support for 3.8. ",
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category=DeprecationWarning,
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stacklevel=2,
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)
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class BaseEstimator(_CommonTags, _BaseEstimator):
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"""Base class for fittable objects."""

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