Metadata-Version: 1.1
Name: chores
Version: 0.6.3
Summary: The next-generation for loop and work tracker
Home-page: UNKNOWN
Author: Jonathan Eunice
Author-email: jonathan.eunice@gmail.com
License: UNKNOWN
Description: 
        | |version| |downloads| |supported-versions| |supported-implementations|
        
        .. |version| image:: http://img.shields.io/pypi/v/chores.svg?style=flat
            :alt: PyPI Package latest release
            :target: https://pypi.python.org/pypi/chores
        
        .. |downloads| image:: http://img.shields.io/pypi/dm/chores.svg?style=flat
            :alt: PyPI Package monthly downloads
            :target: https://pypi.python.org/pypi/chores
        
        .. |supported-versions| image:: https://img.shields.io/pypi/pyversions/chores.svg
            :alt: Supported versions
            :target: https://pypi.python.org/pypi/chores
        
        .. |supported-implementations| image:: https://img.shields.io/pypi/implementation/chores.svg
            :alt: Supported implementations
            :target: https://pypi.python.org/pypi/chores
        
        
        Just about all programs process "items" of one sort or another. That's what
        loops are for, right?
        
        But with the exception of the current loop value or index, programming
        languages don't help track how processing is going. How many items have been
        *successfully* processed? How many *errors* are there? How far along the
        total job are we right now? Which items had problems that need to be looked
        at later?
        
        Even though these bookkeeping tasks are essential to just about every
        program, they're "left to the reader." "Here are some basic loops. Have
        fun!" So developers "reinvent the wheel," tracking status with *ad hoc*
        containers, counters, and status flags for every new program. Not so
        high-level after all, huh?
        
        ``chores`` fights needless this complexity, errors, and effort by providing
        a simple, repeatable pattern for processing items and tracking their status.
        
        The documentation can be found at `Read the Docs
        <http://chores.readthedocs.org/en/latest/>`_.
        
        Usage
        =====
        
        ::
        
            from chores import Chores
        
            chores = Chores('Jones able baker charlie 8348 Smith Brown Davis'.split())
        
            for c in chores:
                status = 'name' if c.istitle() else 'other'
                chores.mark(c, status)
        
            print chores.count('name'), "names,", \
                  chores.count('^name'), "others"
        
        Yields::
        
            4 names, 4 others
        
        Or if you decide you actually want more information, change just the output
        statements::
        
            print todos.count('name'),  "names:", todos.marked('name')
            print todos.count('^name'), "others:", todos.marked('^name')
        
        Now you get::
        
            4 names: ['Jones', 'Smith', 'Brown', 'Davis']
            4 others: ['able', 'baker', 'charlie', '8348']
        
        Discussion
        ==========
        
        Many programs track the status of items being processed with various lists,
        dictionaries, sets, counters, and status flags. ``chores`` might not seem a
        great advance at first, since it has the same kind of initialization and
        looping.
        
        But it gets more interesting at the end of the processing loop, where the
        summary or report of what was processed, the disposition of each item worked
        on, what items yielded errors or other conditions, and what special cases
        were handled is produced.
        
        In the examples above, we never had to keep a counter of how many names were found,
        or how many non-names. When we decided we wanted to change the output from
        summary counts to a full listing, we didn't have go back and collect
        different information. We just differently displayed information already at
        at hand. Also note that the order of the results is nicely maintained.
        When we're reviewing reports about "what transpired," we don't have to work
        very hard to correlate the results with the inputs; unlike when using ``dict``
        and ``set`` structures, items are reported on in the same order they arrived.
        
        Typically a developer will start with only a little thought about various
        dispositions for each item being processed. Over time, she'll start to
        realize: "I need to count those cases, so I can report on them!" Or, "I kept
        an error counter, but I really should have been keeping a list of which
        items broke, because I now have to tell the user not just how many went
        wrong, but which ones in particular." Or "I need to keep track of which ones
        failed the main processing so that I can do more intensive processing on
        just those special cases." Then she'll go back and add counters, collection
        lists, and so on--adding a fair amount of *ad hoc* code that must be built,
        tested, and debugged.
        
        This is especially tricky for data that needs to move through multiple
        stages or phases of work. The developer then has to add structures to
        communicate from earlier processing steps to later ones.
        
        With ``chores``, there's no need for such custom work. It takes over
        tracking which items led to which outcomes. It's always ready to render
        quality information, either for reporting or for managing subsequent
        processing. Bookkeeping information is readily available in
        a tidy, logical format, with no additional development effort.
        
        ``chores`` especially shows its virtues as processing code becomes
        more intricate and as program needs evolve over time.
        
        Additional information can be found at `Read the Docs
        <http://chores.readthedocs.org/en/latest/>`_.
        
        Notes
        =====
        
         *  I've successfully used ``chores`` in my own projects, and it has a
            real test suite. But realistically it should be considered
            "early beta" code. It's explicitly part of experiment to up-level
            development tasks, so its API and mode of use will evolve.
        
         *  ``chores`` is an example of "cross-cutting"--dealing with several
            apparently disconnected concerns in a concerted way because they are,
            in fact, connected, and need to be handled systematically.
        
         *  Automated multi-version testing managed with the wonderful `pytest
            <http://pypi.python.org/pypi/pytest>`_ and `tox
            <http://pypi.python.org/pypi/tox>`_. Successfully packaged for, and
            tested against, all late-model versions of Python: 2.6, 2.7, 3.2, 3.3,
            and 3.4, as well as PyPy 2.6.0 (based on 2.7.9) and PyPy3 2.4.0 (based
            on 3.2.5). Should run fine on Python 3.5, though py.test is broken on
            its pre-release iterations.
        
         *  The author, `Jonathan Eunice <mailto:jonathan.eunice@gmail.com>`_ or
            `@jeunice on Twitter <http://twitter.com/jeunice>`_
            welcomes your comments and suggestions.
        
        Installation
        ============
        
        To install or upgrade to the latest version::
        
            pip install -U chores
        
        To ``easy_install`` under a specific Python version (3.3 in this example)::
        
            python3.3 -m easy_install --upgrade chores
        
        (You may need to prefix these with ``sudo`` command to authorize
        installation. In environments without super-user privileges, you may want to
        use ``pip``'s ``--user`` option, to install only for a single user, rather
        than system-wide.)
        
Keywords: chore chores status work queue task job processing stages phases for loop
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Operating System :: OS Independent
Classifier: License :: OSI Approved :: BSD License
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2.6
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.2
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Programming Language :: Python :: Implementation :: PyPy
Classifier: Topic :: Software Development :: Libraries :: Python Modules
