semvec/pypi-packages huggingface dataset:
verge 0.1.0
Parallel execution inspired by GNU Parallel
License: MIT

=====
Verge
=====

``verge`` is a job executor inspired by `GNU Parallel
<https://www.gnu.org/software/parallel/>`_, implemented with `Twisted
<https://twistedmatrix.com>`_.


Installation
------------

``pip install verge``

There's a `wheel <http://pythonwheels.com/>`_ built, in case you're into that
(you should be).


Examples
--------

Some useful examples can be found in the GNU Parallel `documentation
<https://www.gnu.org/software/parallel/man.html#https://www.gnu.org/software/parallel/man.html#example__working_as_xargs__n1__argument_appending>`_
Right now ``verge`` doesn't support much, but what it does support should allow
just dropping ``verge`` in everywhere you would have put ``parallel``.
words 0.0.1
Tool to get a large collection of words.
License: MIT
Keywords: words,dictionary,lexicon

words
=====

Get large collection of words from books.

Usage
-----

1. Make a directory called ``books/``
2. Put ``.txt`` files in it. Presumably large ones, i.e. books, which are easily available from Gutenberg_.
3. Run ``words.py`` and wait a moment.
4. Receive ``dictionary.txt``.

Description
-----------

`words.py` simply reads each of the books and puts each of the words in a book filtering any that obviously aren't words (anything containing numbers or punctuation).

NOTE: This method may generate non-words which look like words. It is worth revieiwng the lexicon before any serious use.

.. _Gutenberg: http://www.gutenberg.org/
object_pool 0.2
thread-safe python object pool
License: MIT

object\_pool
============

object\_poll is a simple thread-safe generic python object pool. Typical
use:

.. code:: python

    import memcache
    import object_pool

    memcache_pool = ObjectPool(lambda: memcache.Client(['127.0.0.1:11211']), max_size=10)
    with memcache_pool.item() as memcache:
        memcache.set(b'key', b'value')

The ``with`` statement is not required:

.. code:: python

    try:
        memcache = memcache_pool.get()
    finally:
        memcache_pool.put(memcache)

It supports a ``timeout`` argument as well:

.. code:: python

    try:
        memcache = memcache_pool.get(timeout=1.0)
    except ObjectPoolTimeout:
        import logging
        logging.warning('timed out trying to get memcache connection')