{
    "info": {
        "author": "Oregon Health & Sciences University",
        "author_email": "loneyf@ohsu.edu",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 5 - Production/Stable",
            "Environment :: Console",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: MIT License",
            "Operating System :: OS Independent",
            "Programming Language :: Python",
            "Programming Language :: Python :: 3",
            "Topic :: Scientific/Engineering :: Bio-Informatics"
        ],
        "description": "# Immpload - Immport upload preparation\n\n[immpload](https://github.com/biodev/immpload)\nconverts input data files into files formatted from\n[Immport](http://www.immport.org/home) upload templates.\n\n## Prerequisites\n\n* Python3 with the [pip](https://pypi.org/project/pip/) package installer\n\n## Installation\n\n1. Install the `immpload` Python package and executable:\n\n       pip install immpload\n\n## Usage\n\nThe simplest case copies input columns whose name matches\nthe corresponding output\n[Immport template](https://www.immport.org/resources/dataTemplates)\ncolumn:\n```\n$ immpload subjectAnimals /path/to/input/subjects.txt\n```\nwhich will create the Immport upload file `subjectAnimals.txt`\nin the current directory.\n\nTo place the output in a different directory, use the `-o` or\n`--outDir` option:\n```\n$ immpload -o /path/to/output subjectAnimals /path/to/input/subjects.xslx\n```\nNote that the input can be either a `.xslx` Excel spreadsheet\nor a tab-delimited text file.\n\nThe command:\n```\n$ immpload --help\n```\nshows all `immpload` arguments and options.\n\n## Mapping Configuration\n\nIt is often useful to specify the conversion mapping in a\n[YAML](https://en.wikipedia.org/wiki/YAML) configuration file.\nFor example, the following configuration:\n```\ncolumns:\n    Subject ID: ID\n    Arm Or Cohort ID: Cohort\n```\nconverts the `ID` and `Cohort` input values to `Subject ID` and\n`Arm Or Cohort ID` output values, resp. The command is invoked\nwith the `-c` or `--config` option, e.g:\n```\n$ immpload -o /path/to/output --config /path/to/conf/subjects.yaml \\\n           subjectAnimals /path/to/input/subjects.xslx\n```\n\nThe configuration can include value mappings, e.g.:\n```\nvalues:\n    Species: Mus musculus\n```\nsets the output `Species` to `Mus musculus` for all rows.\n\nThe configuration:\n```\ncolumns:\n    Gender: Sex\nvalues:\n    Gender:\n        n/a: Not Specified\n```\ntransforms the input `Sex` value `n/a` to the output `Gender` value\n`Not Specified`. Other input values are copied without change.\n\n`immpload` can flatten each input row into several output rows based\non matching input column names against a pattern. For example, the\nconfiguration:\n```\ncolumns:\n    Subject ID: ID\n    Arm Or Cohort ID: Cohort\n    Study Day: day\npatterns:\n    Result Value Reported: D(?P<day>\\d+)$\n```\nconverts an input row with columns `D1`, `D2` and `D3` into three\noutput rows with column `Study Day` values `1`, `2` and `3`\nand `Result Value Reported` values given by the `D1`, `D2` and `D3`\ninput values, resp.\n\nImmport upload data can be derived solely from fields embedded in\ncolumn names. For example, the configuration:\n```\ncolumns:\n    Analyte Reported: analyte\npatterns:\n    Analyte Reported: (?P<subject>.+)_(?P<day>.+)_(?P<analyte>.+)$\n```\nmatches the input column names against the given pattern and\nwrites one output row per matching column with the `Analyte Reported`\ncolumn set to the embedded _analyte_ match value. In this case,\nno other input rows are read besides the first header row of column\nnames. Note that `Analyte Reported` is assigned the match value\nrather than the matching column value.\n\n## Defaults\n\n`immpload` supplies certain required output columns with a reasonable\ndefault, as follows:\n\n* Animal Subjects (`subjectAnimals.txt`)\n  * `Age Unit` - `Days`\n  * `Age Event` - `Age at infection`\n\n* Experiment Samples (`experimentSamples.*.txt`)\n    * `Experiment ID` - lower-case, underscored `Experiment Name`\n    * `Biosample ID` - `Expsample ID`, if present, otherwise the\n       lower-case, underscored `Biosample Name`, if present,\n       otherwise derived from the `Subject ID`,  `Treatment ID`\n       and `Experiment ID`\n    * `Expsample ID` - `Biosample ID` (defaulted, if necessary)\n* Treatments (`treatments.txt`)\n    * `Name` - derived from the values and units\n    * `User Defined ID` - lower-case, underscored `Name`\n    * `Use Treatment?` - default is `Yes`\n* Assessments (`assessments.txt`)\n    * `Planned Visit ID` - `Study ID` followed by `d` and the `Study Day`\n    * `Panel Name Reported` - copied from the `Assessment Type`\n    * `Assessment Panel ID` - derived from the `Panel Name Reported`\n    * `User Defined ID` - derived from the `Subject ID`,\n      `Planned Visit ID` and `Component Name Reported`\n\nThe default is set if and only if the mapped column value is missing.\n\nDefaults are disabled with the `--no-defaults` option, e.g.:\n```\n$ immpload -o /path/to/output --config /path/to/conf/subjects.yaml \\\n           --no-defaults subjectAnimals /path/to/input/subjects.xslx\n```\nThis is useful when submitting an update to an existing upload.\n\n## Validation\n\nBy default, `imppload` checks the output for required fields. If a\nrequired field is missing, then an error message is displayed and\nprocessing is halted.\n\nValidation is disabled with the `--no-validate` option, e.g.:\n```\n$ immpload -o /path/to/output --config /path/to/conf/subjects.yaml \\\n           --no-validate subjectAnimals /path/to/input/subjects.xslx\n```\nAs with `no-defaults`, `no-validate` is useful when submitting an\nupdate to an existing upload.\n\n## Callbacks\n\nFor advanced usage, the `immpload` Python module can be used directly\nin a Python script with a callback function, e.g.:\n```\nfrom immpload import munger\n\ndef add_results(in_row, in_col_ndx_map, out_col_ndx_map, out_row):\n    \"\"\"\n    Modifies the output row after the configuration-based conversion.\n\n    :param: in_row: the input data row\n    :param: in_col_ndx_map: the input {column: index} dictionary\n    :param: out_col_ndx_map: the output {column: index} dictionary\n    :param: out_row :the output row\n    :return: a list of rows derived from the given output row\n    \"\"\"\n    ###\n    ### Modify out_row or create new output rows here...\n    ###\n    # Return an array of rows.\n    return [out_row]\n\n# Convert the input file.\nmunger.munge('assessments', /path/to/input.xslx, callback=add_results)\n```\n\nThe `munger.munge` method signature is as follows:\n```\ndef munge(template, *in_files, config=None, out_dir=None,\n          sheet=None, input_filter=None, callback=None, **kwargs):\n    \"\"\"\n    Builds the Immport upload file for the given input file.\n    The template is a supported Immport template name, e.g.\n    `assessments`. The output is the Immport upload file,\n    e.g. `assessments,txt`, placed in the output directory.\n\n    The keyword arguments (_kwargs_) are static output\n    _column_`=`_value_ definitions that are applied to every\n    output row. The column name can be underscored, e.g.\n    `Study_ID`.\n\n    Output validation is disabled by default, but recommended\n    for new uploads. Enable validation by setting the _validate_\n    flag parameter to `True`.\n\n    :param template: the required Immport template name\n    :param in_files: the input file(s) to munge\n    :param config: the configuration dictionary or file name\n        of list of file names\n    :param out_dir: the target location (default current directory)\n    :param sheet: for an Excel workbook input file, the sheet to open\n    :param input_filter: optional input row validator which has\n        parameter in_row and returns whether the row is valid\n    :param callback: optional callback with parameters\n        in_row, in_col_ndx_map, out_col_ndx_map and out_row returning\n        an array of rows to write to the output file\n    :param defaults_opt: flag indicating whether to add defaults to the\n        output (default `True`)\n    :param validate_opt: flag indicating whether to validate the\n        output for required fields (default `True`)\n    :param append_opt: append rather than overwrite an existing output\n        file (default False)\n    :param kwargs: the optional static _column_`=`_value_ definitions\n    :return: the output file name\n    \"\"\"\n```",
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