Metadata-Version: 2.1
Name: benchopt
Version: 1.0.0
Summary: Benchmark toolkit for optimization
Home-page: https://github.com/benchopt/benchopt
Maintainer: T. Moreau
Maintainer-email: thomas.moreau@inria.fr
License: BSD (3-clause)
Description: Benchmark repository for optimization
        =====================================
        
        |Build Status| |Python 3.6+| |codecov|
        
        BenchOpt is a package to simplify, make more transparent and
        more reproducible the comparisons of optimization algorithms.
        
        BenchOpt is written in Python but it is available with
        `many programming languages <https://benchopt.github.io/auto_examples/plot_run_benchmark_python_R_julia.html>`_.
        So far it has been tested with `Python <https://www.python.org/>`_,
        `R <https://www.r-project.org/>`_, `Julia <https://julialang.org/>`_
        and compiled binaries written in C/C++ available via a terminal
        command. If it can be installed via
        `conda <https://docs.conda.io/en/latest/>`_ it should just work!
        
        BenchOpt is used through a command line as described
        in `the API Documentation <https://benchopt.github.io/api.html>`_.
        Ultimately running and replicating an optimization benchmark should
        be **as simple as doing**:
        
        .. code-block::
        
            $ git clone https://github.com/benchopt/benchmark_logreg_l2
            $ benchopt run ./benchmark_logreg_l2
        
        Running this command will give you a benchmark plot on l2-regularized
        logistic regression:
        
        .. figure:: https://benchopt.github.io/_images/sphx_glr_plot_run_benchmark_001.png
           :target: how.html
           :align: center
           :scale: 80%
        
        To discover which benchmarks are presently available look
        for `benchmark_* repositories on GitHub <https://github.com/benchopt/>`_,
        such as for
        `l1-regularized logistic regression <https://github.com/benchopt/benchmark_logreg_l1>`_.
        
        
        Learn how to `write a benchmark on our documentation <https://benchopt.github.io/how.html>`_.
        
        Install
        --------
        
        This package can be installed through `pip` using:
        
        .. code-block::
        
            $ pip install benchopt
        
        This will install the command line tool to run the benchmark. Then, existing
        benchmarks can be retrieved from git or created locally. For instance, the
        benchmark for Lasso can be retrieved with:
        
        .. code-block::
        
            $ git clone https://github.com/benchopt/benchmark_lasso
        
        
        Command line usage
        ------------------
        
        To run the Lasso benchmark on all datasets and with all solvers, run:
        
        .. code-block::
        
            $ benchopt run ./benchmark_lasso
        
        Use
        
        .. code-block::
        
            $ benchopt run -h
        
        for more details about different options or read the
        `API Documentation <https://benchopt.github.io/api.html>`_.
        
        
        List of optimization problems available
        ---------------------------------------
        
        - `ols`_: ordinary least-squares.
        - `nnls`_: non-negative least-squares.
        - `lasso`_: l1-regularized least-squares.
        - `logreg_l2`_: l2-regularized logistic regression.
        - `logreg_l1`_: l1-regularized logistic regression.
        
        
        .. |Build Status| image:: https://dev.azure.com/benchopt/benchopt/_apis/build/status/benchopt.benchOpt?branchName=master
           :target: https://dev.azure.com/benchopt/benchopt/_build/latest?definitionId=1&branchName=master
        .. |Python 3.6+| image:: https://img.shields.io/badge/python-3.6%2B-blue
           :target: https://www.python.org/downloads/release/python-360/
        .. |codecov| image:: https://codecov.io/gh/benchopt/benchOpt/branch/master/graph/badge.svg
           :target: https://codecov.io/gh/benchopt/benchOpt
        
        .. _`ols`: https://github.com/benchopt/benchmark_ols
        .. _`nnls`: https://github.com/benchopt/benchmark_nnls
        .. _`lasso`: https://github.com/benchopt/benchmark_lasso
        .. _`logreg_l1`: https://github.com/benchopt/benchmark_logreg_l1
        .. _`logreg_l2`: https://github.com/benchopt/benchmark_logreg_l2
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Environment :: Console
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: R
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Utilities
Classifier: Topic :: Software Development :: Libraries
Description-Content-Type: text/x-rst
