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asv.conf.json
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asv.conf.json
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{
// The version of the config file format. Do not change, unless
// you know what you are doing.
"version": 1,
// The name of the project being benchmarked
"project": "dgl",
// The project's homepage
"project_url": "https://github.com/dmlc/dgl",
// The URL or local path of the source code repository for the
// project being benchmarked
"repo": ".",
// The Python project's subdirectory in your repo. If missing or
// the empty string, the project is assumed to be located at the root
// of the repository.
// "repo_subdir": "python",
// Customizable commands for building, installing, and
// uninstalling the project. See asv.conf.json documentation.
//
"install_command": [
"/bin/bash {build_dir}/tests/regression/install_dgl_asv.sh"
],
"build_command": [
"/bin/bash {build_dir}/tests/regression/build_dgl_asv.sh"
],
"uninstall_command": [
"return-code=any python -mpip uninstall -y dgl"
],
// "build_command": [
// "python setup.py build",
// "PIP_NO_BUILD_ISOLATION=false python -mpip wheel --no-deps --no-index -w {build_cache_dir} {build_dir}"
// ],
// List of branches to benchmark. If not provided, defaults to "master"
// (for git) or "default" (for mercurial).
"branches": ["master"], // for git
// "branches": ["default"], // for mercurial
// The DVCS being used. If not set, it will be automatically
// determined from "repo" by looking at the protocol in the URL
// (if remote), or by looking for special directories, such as
// ".git" (if local).
// "dvcs": "git",
// The tool to use to create environments. May be "conda",
// "virtualenv" or other value depending on the plugins in use.
// If missing or the empty string, the tool will be automatically
// determined by looking for tools on the PATH environment
// variable.
// "environment_type": "conda",
// timeout in seconds for installing any dependencies in environment
// defaults to 10 min
"install_timeout": 600,
// the base URL to show a commit for the project.
// "show_commit_url": "http://github.com/owner/project/commit/",
// The Pythons you'd like to test against. If not provided, defaults
// to the current version of Python used to run `asv`.
// "pythons": ["2.7", "3.6"],
// The list of conda channel names to be searched for benchmark
// dependency packages in the specified order
// "conda_channels": ["conda-forge", "defaults"],
// The matrix of dependencies to test. Each key is the name of a
// package (in PyPI) and the values are version numbers. An empty
// list or empty string indicates to just test against the default
// (latest) version. null indicates that the package is to not be
// installed. If the package to be tested is only available from
// PyPi, and the 'environment_type' is conda, then you can preface
// the package name by 'pip+', and the package will be installed via
// pip (with all the conda available packages installed first,
// followed by the pip installed packages).
//
// "matrix": {
// "numpy": ["1.6", "1.7"],
// "six": ["", null], // test with and without six installed
// "pip+emcee": [""], // emcee is only available for install with pip.
// },
// Combinations of libraries/python versions can be excluded/included
// from the set to test. Each entry is a dictionary containing additional
// key-value pairs to include/exclude.
//
// An exclude entry excludes entries where all values match. The
// values are regexps that should match the whole string.
//
// An include entry adds an environment. Only the packages listed
// are installed. The 'python' key is required. The exclude rules
// do not apply to includes.
//
// In addition to package names, the following keys are available:
//
// - python
// Python version, as in the *pythons* variable above.
// - environment_type
// Environment type, as above.
// - sys_platform
// Platform, as in sys.platform. Possible values for the common
// cases: 'linux2', 'win32', 'cygwin', 'darwin'.
//
// "exclude": [
// {"python": "3.2", "sys_platform": "win32"}, // skip py3.2 on windows
// {"environment_type": "conda", "six": null}, // don't run without six on conda
// ],
//
// "include": [
// // additional env for python2.7
// {"python": "2.7", "numpy": "1.8"},
// // additional env if run on windows+conda
// {"platform": "win32", "environment_type": "conda", "python": "2.7", "libpython": ""},
// ],
// The directory (relative to the current directory) that benchmarks are
// stored in. If not provided, defaults to "benchmarks"
"benchmark_dir": "tests/regression",
// The directory (relative to the current directory) to cache the Python
// environments in. If not provided, defaults to "env"
"env_dir": ".asv/env",
// The directory (relative to the current directory) that raw benchmark
// results are stored in. If not provided, defaults to "results".
"results_dir": "asv/results",
// The directory (relative to the current directory) that the html tree
// should be written to. If not provided, defaults to "html".
"html_dir": "asv/html",
// The number of characters to retain in the commit hashes.
// "hash_length": 8,
// `asv` will cache results of the recent builds in each
// environment, making them faster to install next time. This is
// the number of builds to keep, per environment.
// "build_cache_size": 2,
// The commits after which the regression search in `asv publish`
// should start looking for regressions. Dictionary whose keys are
// regexps matching to benchmark names, and values corresponding to
// the commit (exclusive) after which to start looking for
// regressions. The default is to start from the first commit
// with results. If the commit is `null`, regression detection is
// skipped for the matching benchmark.
//
// "regressions_first_commits": {
// "some_benchmark": "352cdf", // Consider regressions only after this commit
// "another_benchmark": null, // Skip regression detection altogether
// },
// The thresholds for relative change in results, after which `asv
// publish` starts reporting regressions. Dictionary of the same
// form as in ``regressions_first_commits``, with values
// indicating the thresholds. If multiple entries match, the
// maximum is taken. If no entry matches, the default is 5%.
//
// "regressions_thresholds": {
// "some_benchmark": 0.01, // Threshold of 1%
// "another_benchmark": 0.5, // Threshold of 50%
// },
}