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        "description": "Experiment Manager (exman)\n==========================\n\nSimple and minimalistic utility to manage many experiments runs and\ncustom analysis of results\n\nWhy another custom solution?\n----------------------------\n\nMy job is to do research in Deep Learning and I have dozens of different\nexperiments. Testing one hypothesis usually required several runs over\nparameter grid. Plotting and visualizing results is often ad-hoc and\nupdating code producing output is a kind of overhead. Instead I decided\nto collect all results in Jupyter notebook and create plots kind of\n``interest ~ parameters``. As I said, plotting that is a separate task\nalmost every time. Such tools as\n`ModelDB <https://github.com/mitdbg/modeldb>`__ provide you with simple\nvisualizations so that they can be easily aggregated for model\ncomparison. Testing a hypothesis is not about model comparison and thus\nrequires special treatment.\n\nVisualizing results became a kind of pain, you had to remember a mapping\n``parameters -> results``, separating results into different folders\nmade even more mess. I had really bad experience in visualizations. I\ngot that all I need was to iterate over folder with results and apply\nthe same function to it.\n\nInstallation\n------------\n\n.. code:: bash\n\n    pip install -U git+https://github.com/ferrine/exman.git#egg=exman\n    # or\n    pip install exman\n\nSimple Start\n------------\n\nSimple drop in replacement of standard ``argparse.ArgumentParser``\n\n.. code:: python\n\n    #file: main.py\n    import exman\n    # you should always use `exman.simpleroot(__file__)` unless you want another dir\n    parser = exman.ExParser(root=exman.simpleroot(__file__))  # `root = ./exman` relative to the main file\n    parser.add_argument(...)\n\nYou then just add arguments as you did before without any change.\n\nBest Practices\n--------------\n\nError Handling in main\n~~~~~~~~~~~~~~~~~~~~~~\n\nSince 0.0.3 you can use the following context manager. If ``main()``\nfunction fails it will be moved to ``exman/fails``\n\n.. code:: python\n\n    import exman\n    # you should always use `exman.simpleroot(__file__)` unless you want another dir\n    parser = exman.ExParser(root=exman.simpleroot(__file__))  # `root = ./exman` relative to the main file\n    parser.add_argument(...)\n    ...\n    if __name__ == '__main__':\n        args = parser.parse_args()\n        with args.safe_experiment:\n            # do your stuff\n            main(args)\n\n\nKeep Your Repository Clean\n~~~~~~~~~~~~~~~~~~~~~~~~~~\nTo avoid non reproducible results you can ensure you have commited all changes. Exman will take care and will log\n``hash`` for the commit and ``diff`` if any. To use these features you should hint the parser with the repo.\n\n.. code:: python\n\n    import exman\n\n    parser = exman.ExParser(root=exman.simpleroot(__file__), git=True)\n    # less fragile solution, but works only locally\n    parser = exman.ExParser(root=exman.simpleroot(__file__), git=\"/abs/path/to/repo\")\n    # an ok solution, if you are sure in the relative path\n    parser = exman.ExParser(root=exman.simpleroot(__file__),\n        git=os.path.join(os.path.dirname(__file__), \"relative\", \"path\", \"goes\", \"here\"),\n        git_assert_clean=True  # run assertion check before each run. False by default.\n    )\n\nIn cli of your favorite experiment you can skip the assertion if you want to:\n\n.. code:: bash\n\n    python train.py --git-dirty --other-args\n\nOptional Parameters\n~~~~~~~~~~~~~~~~~~~\n\nTo avoid issues in `reproducing experiments <#rerunning-experiment>`__\nyou should consider using ``exman.optional(type)`` for optional\narguments\n\n.. code:: python\n\n    import exman\n    # you should always use `exman.simpleroot(__file__)` unless you want another dir\n    parser = exman.ExParser(root=exman.simpleroot(__file__))  # `root = ./exman` relative to the main file\n    parser.add_argument('--myarg', type=exman.optional(int))\n\nValidators\n~~~~~~~~~~\n\nIn simple argparser you cant easily validate multiple arguments, it is\neasy in Exman. You can create an informative error message\n\n.. code:: python\n\n    import exman\n    # you should always use `exman.simpleroot(__file__)` unless you want another dir\n    parser = exman.ExParser(root=exman.simpleroot(__file__))  # `root = ./exman` relative to the main file\n    parser.add_argument(...)\n    # here `p` stands for initial namespace parsed from arguments\n    parser.register_validator(lambda p: p.arg1 != p.arg2 or p.arg3 == p.arg4,\n                              # next line will be autoformatted for you using .format\n                              'You have provided wrong set of arguments: {arg1}, {arg2}, {arg3}, {arg4}')\n\nAdvanced validators can raise `exman.ArgumentError` that contains a better message than the one in validators function\n\nMarry Pandas with Exman\n~~~~~~~~~~~~~~~~~~~~~~~\n\nPandas is a great tool to work with table data. Experiments are the same\ndata and can be loaded in python. So all you need is to run batch of\nexperiments and open a Jupyter notebook.\n\n.. code:: python\n\n    import exman\n    index = exman.Index(exman.simpleroot('/path/to/main.py'))\n    experiments = index.info()\n\nTable has columns ``time (datetime64[ns])`` of experiment and\n``root (pathlib.Path)`` path to results. Moreover this table has all\nother parameters of the experiment. You later can filter/order the\nresults according to them and have easy-breezy access to results folder\nand it's content.\n\n.. code:: python\n\n    for i, ex in experiments.iterrows():\n        # do some actions\n        # use ex.param for parameters\n        # ex.root / 'plot.png' for file paths\n        ...\n\nLocal Configuration\n~~~~~~~~~~~~~~~~~~~\n\nYou can store local configuration files in your experiment folder. You\nshould provide the filename to ExParser as well.\n\n.. code:: python\n\n    import exman\n    # you should always use `exman.simpleroot(__file__)` unless you want another dir\n    parser = exman.ExParser(\n        root=exman.simpleroot(__file__),\n        default_config_files=['local.cfg']\n    )\n\nLocal configuration stores globally defined default values, they\noverride defaults set in main file\n\nAuto Structure\n~~~~~~~~~~~~~~\n\nIf you want argument specific human friendly directory structure you can\ntie specific argument names for that\n\n.. code:: python\n\n    import exman\n    # you should always use `exman.simpleroot(__file__)` unless you want another dir\n    parser = exman.ExParser(\n        root=exman.simpleroot(__file__),\n        automark=['arg1', 'constant']\n    )\n    parser.add_argument('--arg1')\n\nLater you can see your `marked folder <#directory-structure-and-cli>`__\nlooks like this\n\n::\n\n    exman/marked/arg1/<arg1>/constant/<name-of-experiment>/...\n\nThis can be usefull if you work in a team. Write in ``main.py``\n\n.. code:: python\n\n    import exman\n    # you should always use `exman.simpleroot(__file__)` unless you want another dir\n    parser = exman.ExParser(\n        root=exman.simpleroot(__file__),\n        automark=['user'],\n        # store `user: myuser` content in local.cfg\n        default_config_files=['local.cfg']\n    )\n    parser.add_argument('--user')\n\nAfter you've done that, your team runs can be stored in a single exman\ndirectory assuming all access rights are correctly set up.\n\n::\n\n    exman/marked/user/<username>/constant/<name-of-experiment>/...\n\nDirectory Structure and CLI\n---------------------------\n\nIn command line runs will look also the same:\n\n::\n\n    python main.py --param1 foo --param2 bar\n\nThings change if you actually run the program. It dumps all the parsed\nparameters combined with defaults into Yaml style file into location\n``root/runs/<name-of-experiment>/params.yaml``. ``name-of-experiment``\nis generic and autocreated on the fly. For quick look or search there\nare symlinks in the ``index`` folder e.g.\n``root/index/<name-of-experiment>.yaml``. Since a lot of experiments are\ncreated and debugging is sometimes needed, you might want not to create\ndebug experiments in ``runs`` folder. For that case you just add\n``--tmp`` flag and new filed will be written to\n``root/tmp/<name-of-experiment>`` folder. That is convenient as you both\ndo not loose important info about experiment and results and can restore\nthese symlinks in index by hand if needed.\n\n::\n\n    root\n    |-- runs\n    |   `-- xxxxxx-YYYY-mm-dd-HH-MM-SS\n    |       |-- params.yaml\n    |       `-- ...\n    |-- fails\n    |-- index\n    |   `-- xxxxxx-YYYY-mm-dd-HH-MM-SS.yaml (symlink)\n    |-- marked\n    |   `-- <mark>\n    |       `-- xxxxxx-YYYY-mm-dd-HH-MM-SS (symlink)\n    |           |-- params.yaml\n    |           `-- ...\n    `-- tmp\n        `-- xxxxxx-YYYY-mm-dd-HH-MM-SS\n            |-- params.yaml\n            `-- ...\n\nRerunning experiment\n~~~~~~~~~~~~~~~~~~~~\n\nIf you want to reproduce an experiment, you can provide source\nconfiguration file in yaml format. For example:\n\n.. code:: bash\n\n    python main.py --config root/index/<name-of-experiment-to-reproduce>.yaml\n\nAll the values will be restored from the previous run. You can also\nmodify old values in ``--config ...`` using\n\n.. code:: bash\n\n    python main.py --config root/index/<name-of-experiment-to-reproduce>.yaml --override-param=new_value\n\nIn case you do not want to restore some argument from saved config (it\nmay be some dynamic setted variable) you should use ``volatile=True`` in\n``add_argument``:\n\n.. code:: python\n\n    parser.add_argument('--my_dynamic_id', default=os.environ.get('AUTOSETTED_ID'), volatile=True)\n\nMarking experiments\n-------------------\n\nIf you like some experiments you can mark them for easier later access.\n\n::\n\n    cd root_of_exman_dir\n    exman mark <key> <#ex1> [<#ex2> <#ex3> ...]\n\nand later in Jupyter\n\n.. code:: python\n\n    index = exman.Index(exman.simpleroot('/path/to/main.py'))\n    experiments = index.info('<key>')\n    # assuming you work in a team and use best practice advice\n    user_experiments = index.info('user/username')\n\nDeleting experiments\n--------------------\n\n::\n\n    cd root_of_exman_dir\n    # delete only index\n    exman delete <#ex1> [<#ex2> <#ex3> ...]\n    # delete all files\n    exman delete --all <#ex1> [<#ex2> <#ex3> ...]\n\n\n",
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