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    "info": {
        "author": "Jetic G\u016b, Rory Wang",
        "author_email": "jeticg@sfu.ca",
        "bugtrack_url": null,
        "classifiers": [
            "License :: OSI Approved :: MIT License",
            "Operating System :: OS Independent",
            "Programming Language :: Python"
        ],
        "description": "# natlang: Natural Language Data Loading Tools\nmaster: [![Build Status](https://travis-ci.com/jeticg/datatool.svg?branch=master)](https://travis-ci.com/jeticg/datatool)\ndev: [![Build Status](https://travis-ci.com/jeticg/datatool.svg?branch=dev)](https://travis-ci.com/jeticg/datatool)\n\nData loader/common data structures and other tools\n\nMost of the code are Python2/3 compatible.\nFor the version of python for specific modules, please check the second line of\neach source file.\n\n## 0. Usage\n\nInstall using pip will get you the latest tested version of `natlang`.\n\n    > pip install natlang\n\nAlternatively, you can also install from source using the following command:\n\n    > python setup.py install\n\nIf you want to load up a dataset, then just do this:\n\n    > import natlang as nl\n    > data = nl.load(filePattern, format=ChoosenFormat)\n    > # ChoosenFormat here can be an actual imported format or string.\n    > # Alternatively, you can also pass a loader func in using nl.load(filePatttern, loader=func)\n\nFor parallel datasets:\n\n    > import natlang as nl\n    > data = nl.biload(srcPattern, tgtPattern, srcFormat, tgtFormat)\n    > # Loader option similar to nl.load also applies here. src stands for source, tgt stands for target.\n\n## 1. Format\n\nAll supported formats are placed under `src/format`.\nCurrently the following formats are tested:\n\n1. `txt`: simple text format. Sentences are separated by `\\n`, tokens/words are\nseparated by whitespace.\n\n2. `tree`: constituency tree format. Run `python -i format/tree.py` to play\naround.\n\n3. `semanticFrame`: Propbank/Nombank frame loader. Returns bundles of frames\nfor analysis.\n\n4. `AMR`: Abstract Meaning Representation. Run `python -i format/AMR.py` to\nplay around.\n\n5. `conll`: General CoNLL format loader. Default is CoNLL_U. Run\n`python -i format/conll.py` to play around.\n\n### 1.1 Recommended Functions\n\nFor formats supporting being loaded from a file, one should implement a `load`\nfunction in the format file (see 2.1).\n\nFor formats supporting being exported, each instance of that format should have\nan `export` method that outputs a string.\n\n## 2. Loader\n\n### 2.1 Individual Loader\n\nEach format has its own loader.\nIt is defined as `format.FORMAT.load`.\nThe `load` function has the following interface:\n\n    def load(file, linesToLoad=sys.maxsize)\n\nAt test time, the `load` function would be expected to parse the file\ndescription and read from it.\nIt will return the first `linesToLoad` entries as a list.\n\nFor example, if one wishes to use load a file in constituency tree format (see\nexample in `tests/sampleTree.txt`), one could do the following:\n\n    from datatool.format import tree\n    x = tree.load(\"datatool/tests/sampleTree.txt\")\n\n### 2.2 Class `ParallelDataLoader`\n\nThis class allows one to load parallel corpora (L1, L2) in any format.\nYou can specify the format for L1 and L2 side separately.\n\n    from datatool.loader import ParallelDataLoader\n    loader = ParallelDataLoader(srcFormat='txtOrTree', tgtFormat='txtOrTree')\n\nHere, `'txtOrTree'` is the default value for `srcFormat` and `tgtFormat`.\nNote that under the `format` folder, except for data structures for specific\nformats, there are also mere loaders and `'txtOrTree'` is one that can handle\nboth `tree` and `txt`.\n\nAfter initialising the loader, one can just go ahead and run:\n\n    loader.load(fFile, eFile, linesToLoad)\n\nThe loader will automatically align the parallel text and output a list of\ntuples, each containing a single entry in L1 and L2.\nEntries with either L1 or L2 being `None` or of length 0 will be omitted.\n\n## 3. Exporter\n\nUsage:\n\n    from datatool.exporter import exportToFile, RealtimeExporter\n\n### 3.1 Function `exportToFile`\n\nExport a `txt` format dataset or `tree` format dataset (not single entry, but\nrather a dataset) to file.\n\n### 3.2 Class `RealtimeExporter`\n\nThe code is pretty self-explanatory.\nIf the export function of a specific format takes quite a bit of time, this\nmethod is recommended.\n\n\n",
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