8000 MNT Update `asv.conf.json` to get rid of last references to Python 2.… · scikit-learn/scikit-learn@734245a · GitHub
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DimitriPapadopoulosDimitriPapadopoulos
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MNT Update asv.conf.json to get rid of last references to Python 2.7 (#31064)
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‎asv_benchmarks/asv.conf.json

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@@ -7,27 +7,21 @@
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"project": "scikit-learn",
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// The project's homepage
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"project_url": "scikit-learn.org/",
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"project_url": "https://scikit-learn.org/",
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// The URL or local path of the source code repository for the
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// project being benchmarked
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"repo": "..",
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// The Python project's subdirectory in your repo. If missing or
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// the empty string, the project is assumed to be located at the root
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// of the repository.
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// "repo_subdir": "",
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// Customizable commands for building, installing, and
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// uninstalling the project. See asv.conf.json documentation.
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"install_command": ["python -mpip install {wheel_file}"],
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"uninstall_command": ["return-code=any python -mpip uninstall -y {project}"],
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"build_command": ["python -m build --wheel -o {build_cache_dir} {build_dir}"],
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// List of branches to benchmark. If not provided, defaults to "master
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// List of branches to benchmark. If not provided, defaults to "main"
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// (for git) or "default" (for mercurial).
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"branches": ["main"],
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// "branches": ["default"], // for mercurial
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// The DVCS being used. If not set, it will be automatically
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// determined from "repo" by looking at the protocol in the URL
@@ -46,19 +40,19 @@
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// defaults to 10 min
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//"install_timeout": 600,
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// timeout in seconds all benchmarks, can be overridden per benchmark
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// defaults to 1 min
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//"default_benchmark_timeout": 60,
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// the base URL to show a commit for the project.
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"show_commit_url": "https://github.com/scikit-learn/scikit-learn/commit/",
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// The Pythons you'd like to test against. If not provided, defaults
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// The Pythons you'd like to test against. If not provided, defaults
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// to the current version of Python used to run `asv`.
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// "pythons": ["3.6"],
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// The list of conda channel names to be searched for benchmark
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// dependency packages in the specified order
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// "conda_channels": ["conda-forge", "defaults"]
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// "pythons": ["3.12"],
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// The matrix of dependencies to test. Each key is the name of a
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// package (in PyPI) and the values are version numbers. An empty
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// The matrix of dependencies to test. Each key is the name of a
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// package (in PyPI) and the values are version numbers. An empty
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// list or empty string indicates to just test against the default
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// (latest) version. null indicates that the package is to not be
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// installed. If the package to be tested is only available from
@@ -107,10 +101,10 @@
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// ],
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//
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// "include": [
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// // additional env for python2.7
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// {"python": "2.7", "numpy": "1.8"},
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// // additional env for python3.12
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// {"python": "3.12", "numpy": "1.26"},
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// // additional env if run on windows+conda
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// {"platform": "win32", "environment_type": "conda", "python": "2.7", "libpython": ""},
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// {"sys_platform": "win32", "environment_type": "conda", "python": "3.12", "libpython": ""},
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// ],
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// The directory (relative to the current directory) that benchmarks are
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// The number of characters to retain in the commit hashes.
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// "hash_length": 8,
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// `asv` will cache results of the recent builds in each
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// `asv` will cache wheels of the recent builds in each
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// environment, making them faster to install next time. This is
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// the number of builds to keep, per environment.
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// "build_cache_size": 2,
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// number of builds to keep, per environment.
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// "build_cache_size": 0
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// The commits after which the regression search in `asv publish`
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// should start looking for regressions. Dictionary whose keys are
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// "regressions_first_commits": {
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// "some_benchmark": "352cdf", // Consider regressions only after this commit
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// "another_benchmark": null, // Skip regression detection altogether
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// },
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// The thresholds for relative change in results, after which `asv
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// publish` starts reporting regressions. Dictionary of the same
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// form as in ``regressions_first_commits``, with values
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// indicating the thresholds. If multiple entries match, the
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// maximum is taken. If no entry matches, the default is 5%.
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//
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// "regressions_thresholds": {
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// "some_benchmark": 0.01, // Threshold of 1%
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// "another_benchmark": 0.5, // Threshold of 50%
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// },
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// }
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}

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