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        "author": "\u00c1lvaro Justen",
        "author_email": "alvarojusten@gmail.com",
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        "classifiers": [
            "Development Status :: 3 - Alpha",
            "Intended Audience :: Developers",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: GNU General Public License (GPL)",
            "Natural Language :: English",
            "Operating System :: OS Independent",
            "Programming Language :: Python :: 2.7",
            "Topic :: Software Development :: Libraries :: Python Modules"
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        "description": "outputty\n========\n\n``outputty`` is a simple Python library that helps you importing, filtering\nand exporting data. It is composed by a main ``Table`` class and a lot of\nplugins that helps importing and exporting data to/from ``Table``.\n\nYou can write your own plugin easily (see ``outputty/plugin_*.py`` for\nexamples). Some examples of plugins are: CSV, text, HTML and histogram.\n\n\nInstallation\n------------\n\nAs simple as executing::\n\n    pip install outputty\n\n\nNote: as ``pip`` tries to compile everything and ``outputty`` depends on\n``MySQL-Python`` package (which needs compilation), you need to have\nlibmysqlclient's headers, compilers and related stuff. To install it on\nDebian/Ubuntu, just execute::\n\n    apt-get install build-essential libmysqlclient-dev\n\n\nExample\n-------\n\nCode time!::\n\n    >>> from outputty import Table\n    >>> my_table = Table(headers=['name', 'age']) # headers are the columns\n    >>> my_table.append(('\u00c1lvaro Justen', 24)) # a row as tuple\n    >>> my_table.append({'name': 'Other User', 'age': 99}) # a row as dict\n    >>> print my_table # a text representation of Table\n    +---------------+-----+\n    |      name     | age |\n    +---------------+-----+\n    | \u00c1lvaro Justen |  24 |\n    |    Other User |  99 |\n    +---------------+-----+\n\n    >>> print 'First row:', my_table[0] # Table is indexable\n    First row: [u'\\xc1lvaro Justen', 24]\n\n    >>> print 'Sum of ages:', sum(my_table['age']) # you can get columns too\n    Sum of ages: 123\n\n    >>> my_table.write('csv', 'my-table.csv') # CSV plugin will save its contents in a file\n    >>> # let's see what's in the file...\n    >>> print open('my-table.csv').read()\n    \"name\",\"age\"\n    \"\u00c1lvaro Justen\",\"24\"\n    \"Other User\",\"99\"\n\n    >>> # let's use HTML plugin!\n    >>> print my_table.write('html') # without filename ``write`` will return a string\n    <table>\n      <thead>\n        <tr class=\"header\">\n          <th>name</th>\n          <th>age</th>\n        </tr>\n      </thead>\n      <tbody>\n        <tr class=\"odd\">\n          <td>\u00c1lvaro Justen</td>\n          <td>24</td>\n        </tr>\n        <tr class=\"even\">\n          <td>Other User</td>\n          <td>99</td>\n        </tr>\n      </tbody>\n    </table>\n\n\n``Table`` have **a lot** of other features. To learn more (by examples), read\n`outputty tutorial <https://github.com/turicas/outputty/blob/master/tutorial.rst>`_\nand see ``examples`` folder. Enjoy!\n\n\nNew Features\n------------\n\nYes, there are a lot of features to add (it's just the begining). If you\nwant to contribute, please see our\n`outputty wishlist <https://github.com/turicas/outputty/blob/master/WISHLIST.rst>`_.\n\nYou can also use the `outputty Issue Tracking System on GitHub <https://github.com/turicas/outputty/issues>`_\nto report bugs.\n\n\nContributing\n------------\n\nIf you want to contribute to this project, please:\n\n- Install dependencies for development running ``pip install -r requirements/development.txt``.\n- Execute ``make test`` to run all tests -- please run **all tests** *before*\n  pushing.\n\n  - To run just one test file execute:\n    ``nosetests --with-coverage --cover-package outputty  tests/test_your-test-file.py``\n  - Try to have a test-coverage of 100%.\n  - Use `Test-driven development <http://en.wikipedia.org/wiki/Test-driven_development>`_.\n\n- Use `nvie's gitflow <https://github.com/nvie/gitflow>`_ - to learn, read\n  `A Successful Git branching model <http://nvie.com/posts/a-successful-git-branching-model/>`_.\n\n- Create/update documentation (README/docstrings/man page)\n\n  - **Do NOT** edit ``README.rst`` and ``tutorial.rst``, edit\n    ``README-template.rst`` or ``tutorial-template.rst`` instead and run\n    ``make create-docs`` to create the new ``README.rst`` and\n    ``tutorial.rst`` (before committing). The tutorial will be created based on\n    files in ``examples`` folder.\n\n\nNew Plugins\n~~~~~~~~~~~\n\nIf you want to create a new plugin to import/export from/to some new\nresource, please see files ``outputty/plugin_*.py`` as examples. They are so\nsimple, please follow these steps:\n\n- Create a file named ``outputty/plugin_name.py``, where ``name`` is the name of\n  your plugin.\n\n- Create ``read`` and/or ``write`` functions in this file. These functions receive\n  the ``Table`` object and optional parameters.\n\n  - ``read``: should read data from the resource specified in parameters and put\n    this data in ``Table`` (using ``Table.append`` or ``Table.extend``).\n  - ``write``: should read data from ``Table`` (iterating over it, using slicing\n    etc.) and write this data to the resource specified in parameters.\n\n- Call your plugin executing ``my_table.write('name', optional_parameters...)``\n  or ``my_table.read('name', optional_parameters...)`` (where ``name`` is your\n  plugin's name) - when you execute it ``outputty`` will call\n  ``outputty.plugin_name.read``/``outputty.plugin_name.write``.\n\n\nEncoding and Decoding\n+++++++++++++++++++++\n\nYour plugin's ``read`` function **must** put all data inside in unicode and your\nplugin's ``write`` function will receive a ``Table`` object with all data in\nunicode (it should not change this). But if you need to decode/encode\nbefore/after doing some actions in your plugin, you can use ``Table.decode()``\nand ``Table.encode()``.\n\n\nContributors\n~~~~~~~~~~~~\n\nThis software is written and maintained by\n`\u00c1lvaro Justen <https://github.com/turicas>`_ but received a lot of\ncontributions. My sincerely thanks to:\n\n- `Funda\u00e7\u00e3o Get\u00falio Vargas <http://www.fgv.br/>`_ for letting me invest my time\n  on it.\n- `Douglas Andrade <https://github.com/douglas>`_ for showing me\n  `textwrap.dedent` and writting more legible tests.\n- `Fl\u00e1vio Coelho <https://github.com/fccoelho>`_ for creating `histogram` and\n  giving a lot of suggestions.\n- `Renne Rocha <https://github.com/rennerocha>`_ for creating `order_by`.\n- `Tatiana Al-Chueyr <https://github.com/tatiana>`_ for designing and coding\n  architecture proposals and suggestions for the plugin API (including the\n  architecture we are using).\n- `Fl\u00e1vio Amieiro <https://github.com/flavioamieiro>`_ for a lot of suggestions\n  and interpretations about design.\n\n\n\nRelated Software\n----------------\n\n- outputty-like:\n\n    - `tablib <https://github.com/kennethreitz/tablib>`_: format-agnostic tabular\n      dataset library.\n    - `PyTables <http://www.pytables.org/>`_: package for managing hierarchical\n      datasets and designed to efficiently and easily cope with extremely large\n      amounts of data.\n    - `csvstudio <http://code.google.com/p/csvstudio/>`_: Python tool to analyze\n      csv files.\n    - `csvsimple <http://pypi.python.org/pypi/csvsimple>`_: a simple tool to\n      handle CSV data.\n    - `toolshed <http://pypi.python.org/pypi/toolshed>`_: less boiler-plate.\n    - `buzhug <http://buzhug.sourceforge.net/>`_: a fast, pure-Python\n      database engine.\n\n- Data analysis:\n\n    - `pyf <http://pyfproject.org/>`_: framework and platform dedicated to large\n      data processing, mining, transforming, reporting and more.\n    - `pygrametl <http://pygrametl.org/>`_: Python framework which offers\n      commonly used functionality for development of Extract-Transform-Load\n      (ETL) processes.\n    - `etlpy <http://sourceforge.net/projects/etlpy>`_ seems to be a dead project.\n    - `orange <http://orange.biolab.si/>`_: data visualization and analysis for\n      novice and experts.\n    - `Ruffus <http://ruffus.org.uk/>`_: lightweight python module to run\n      computational pipelines.\n    - `webstore <https://github.com/okfn/webstore>`_: web-api enabled datastore\n      backed onto sql databases\n\n- Command-line tools:\n\n    - `fabulous <http://lobstertech.com/fabulous.html>`_: library designed to\n      make the output of terminal applications look fabulous.\n    - `termcolor <http://pypi.python.org/pypi/termcolor>`_: ANSII Color\n      formatting for output in terminal.\n    - `clint <https://github.com/kennethreitz/clint>`_: Python Command-line\n      Application Tools.\n\n- Other:\n\n    - `pyspread <http://manns.github.com/pyspread/>`_: non-traditional\n      spreadsheet application.",
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