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        "author": "Michael Selik",
        "author_email": "michael.selik@gmail.com",
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        "classifiers": [
            "Development Status :: 4 - Beta",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: MIT License",
            "Operating System :: OS Independent",
            "Programming Language :: Python",
            "Topic :: Text Processing",
            "Topic :: Utilities"
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        "description": "========\nXport\n========\n\nPython reader for SAS XPORT data transport files (``*.xpt``).\n\n\n\nWhat's it for?\n==============\n\nXPORT is the binary file format used by a bunch of `United States\ngovernment agencies`_ for publishing data sets. It made a lot of sense\nif you were trying to read data files on your IBM mainframe back in\n1988.\n\nThe official `SAS specification for XPORT`_ is relatively\nstraightforward. The hardest part is converting IBM-format floating\npoint to IEEE-format, which the specification explains in detail.\n\nThere was an `update to the XPT specification`_ for SAS v8 and above.\nThis module *has not yet been updated* to work with the new version.\nHowever, if you're using SAS v8+, you're probably not using XPT\nformat. The changes to the format appear to be trivial changes to the\nmetadata, but this module's current error-checking will raise a\n``ParseError``. If you'd like an update for v8, please let me know by\n`submitting an issue`_.\n\n.. _United States government agencies: https://www.google.com/search?q=site:.gov+xpt+file\n\n.. _SAS specification for XPORT: http://support.sas.com/techsup/technote/ts140.pdf\n\n.. _update to the XPT specification: https://support.sas.com/techsup/technote/ts140_2.pdf\n\n.. _submitting an issue: https://github.com/selik/xport/issues/new\n\n\n\nReading XPT\n===========\n\nThis module mimics the ``csv`` module of the standard library,\nproviding ``Reader`` and ``DictReader`` classes. Note that\n``xport.Reader`` is capitalized, unlike ``csv.reader``.\n\n.. code:: python\n\n    with open('example.xpt', 'rb') as f:\n        for row in xport.Reader(f):\n            print row\n\n\n\nValues in the row will be either a unicode string or a float, as\nspecified by the XPT file metadata. Note that since XPT files are in\nan unusual binary format, you should open them using mode ``'rb'``.\nFor convenience, you can also use the ``NamedTupleReader`` to get each\nrow as a namedtuple, with an attribute for each field in the dataset.\n\n\n\nThe ``Reader`` object has a handful of metadata attributes:\n\n* ``Reader.fields`` -- Names of the fields in each observation.\n\n* ``Reader.version`` -- SAS version number used to create the XPT file.\n\n* ``Reader.os`` -- Operating system used to create the XPT file.\n\n* ``Reader.created`` -- Date and time that the XPT file was created.\n\n* ``Reader.modified`` -- Date and time that the XPT file was last modified.\n\n\n\nThe module also provides a handful of utility functions for reading\nthe whole XPT file and loading the rows into a Python data structure.\nThe ``to_rows`` function will simply return a list of rows. The\n``to_columns`` function will return the data as columns rather than\nrows. The columns will be an ``OrderedDict`` mapping the column labels\nas strings to the column values as lists of either strings or floats.\nFor convenient conversion to a `NumPy`_ array or `Pandas`_ dataframe,\nyou can use ``to_numpy`` and ``to_dataframe``.\n\n.. code:: python\n\n    with open('example.xpt', 'rb') as f:\n        columns = xport.to_columns(f)\n\n    with open('example.xpt', 'rb') as f:\n        a = xport.to_numpy(f)\n\n    with open('example.xpt', 'rb') as f:\n        df = xport.to_dataframe(f)\n\n.. _NumPy: http://www.numpy.org/\n\n.. _Pandas: http://pandas.pydata.org/\n\n\n\nYou can also use the ``xport`` module as a command-line tool to convert an XPT\nfile to CSV (comma-separated values) file.::\n\n    $ python -m xport example.xpt > example.csv\n\n\n\nIf you want to access specific records, you should gather the rows in\na list or use one of ``itertools`` recipes_ for quickly consuming and\nthrowing away unncessary elements.\n\n.. code:: python\n\n    # Collect all the records in a list for random access\n    rows = list(xport.Reader(f))\n\n    # Select only record 42\n    from itertools import islice\n    row = next(islice(xport.Reader(f), 42, None))\n\n    # Select only the last 42 records\n    from collections import deque\n    rows = deque(xport.Reader(f), maxlen=42)\n\n.. _recipes: https://docs.python.org/2/library/itertools.html#recipes\n\n\n\nWriting XPT\n===========\n\nThe ``from_columns`` function will write an XPT file from a mapping of\nlabels (as string) to columns (as iterable) or an iterable of (label,\ncolumn) pairs.\n\n.. code:: python\n\n    # a mapping of labels to columns\n    mapping = {'numbers': [1, 3.14, 42],\n               'text': ['life', 'universe', 'everything']}\n\n    with open('answers.xpt', 'wb') as f:\n        xport.from_columns(mapping, f)\n\n\n\nColumn labels are restricted to 40 characters. Column names are\nrestricted to 8 characters and will be automatically created based on\nthe column label -- the first 8 characters, non-alphabet characters\nreplaced with underscores, padded to 8 characters if necessary. All\ntext strings, including column labels, will be converted to bytes\nusing the ISO-8859-1 encoding.\n\nUnfortunately, writing XPT files cannot cleanly mimic the ``csv``\nmodule, because we must examine all rows before writing any rows to\ncorrectly write the XPT file headers.\n\n\n\nThe ``from_rows`` function expects an iterable of iterables, like a\nlist of tuples. In this case, the column labels have not been\nspecified and will automatically be assigned as 'x0', 'x1', 'x2', ...,\n'xM'.\n\n.. code:: python\n\n    rows = [('a', 1), ('b', 2)]\n\n    with open('example.xpt', 'wb') as f:\n        xport.from_rows(rows, f)\n\n\n\nTo specify the column labels for ``from_rows``, each row can be a\nmapping (such as a ``dict``) of the column labels to that row's\nvalues. Each row should have the same keys. Passing in rows as\nnamedtuples, or any instance of a ``tuple`` that has a ``._fields``\nattribute, will set the column labels to the attribute names of the\nfirst row.\n\n.. code:: python\n\n    rows = [{'letters': 'a', 'numbers': 1},\n            {'letters': 'b', 'numbers': 2}]\n\n    with open('example.xpt', 'wb') as f:\n        xport.from_rows(rows, f)\n\n\n\nFeature requests\n================\n\nI'm happy to fix bugs, improve the interface, or make the module\nfaster. Just `submit an issue`_ and I'll take a look.\n\n.. _submit an issue: https://github.com/selik/xport/issues/new\n\n\n\nRecent changes\n==============\n\n* Switched from ``load``/``dump`` with mode flags to ``to_rows``,\n  ``to_columns``, ``from_rows`` and ``from_columns``.\n\n* ``Reader`` yields regular tuples, not namedtuples.\n\n\nAuthors\n=======\n\nOriginal version by `Jack Cushman`_, 2012.\nMajor revision by Michael Selik, 2016.\n\n.. _Jack Cushman: https://github.com/jcushman\n\n\n",
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