semvec/pypi-packages huggingface dataset:
git-history-profiler 0.0.2
Performance and stability profiling over commit historys.
License: MIT
Keywords: git profiling

git_history_profiler
====================

|PyPI|

Performance and stability profiling over the git commit history.

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

.. code:: bash

    $ pip install git_history_profiler

Usage
-----

.. code:: bash

    $ git_history_profiler --help
    Usage: git_history_profiler [OPTIONS] REPO_URL

      Performance and stability profiling over the git commit history.

    Options:
      --config PATH      Path to config.  [required]
      -c, --commit TEXT  Commit id to consider.
      --help             Show this message and exit.

Try out the example:

.. code:: bash

    $ ./examples/create_test_repository.sh ./test_repo/
    $ git_history_profiler ./test_repo/ --config ./examples/config.yml

Afterwards, check out ``./profiling_results/``.

.. |PyPI| image:: https://img.shields.io/pypi/v/git_history_profiler.svg?style=flat
   :target: https://pypi.org/project/git-history-profiler/
twitter-analysis 0.0.5
Get tweets from the Twitter Frontend API.
License: MIT


Twitter Analysis
===============

Twitter's API is annoying to work with, and has lots of limitations —
luckily their frontend (JavaScript) has it's own API, which Kennethreitz reverse–engineered.
No API rate limits. No restrictions. Extremely fast.

You can use this library to get the text of any user's Tweets and use the results for analysis.

Usage
=====

.. code-block:: pycon

    >>> from twitter_analysis import get_tweets

    >>> for tweet in get_tweets('kennethreitz', tweets=100):
    >>>     print(tweet)
    P.S. your API is a user interface
    s3monkey just hit 100 github stars! Thanks, y’all!
    I’m not sure what this /dev/fd/5 business is, but it’s driving me up the wall.
    …

It appears you can ask for up to 450 tweets reliably (25 html pages).

Installation
============

.. code-block:: shell

    $ pipenv install twitter-analysis

Only Python 3.6+ is supported


LICENSE
=======

MIT
Quark-Xpress-Tags-to-xml 1.1
Convert Quark Xpress Tags to XML
License: MIT
Requires Python: >=3


Convert Quark Xpress tagged text (Tags, xtags) to XML.

This module is intended as a pre-processing step in the conversion of
Quark Xpress tagged text to (semantic) HTML; as such it does not
attempt to convert every single tag to XML, but only those that are
relevant to the production of semantic, HTML5-compliant HTML. 

This means that Paragraph and Character style sheet definitions are
ignored; we only care about the apllied style sheet names. It also
means that import character attributes like <i> and <b>, but ignore 
tags related to print typesseting only (tracking, kerning,
baseline shift, etc.) by default , though they can be turned on.

The module doen't actually produced XML but an Element Tree, in case 
you'd like to do further processing on the tree itself before
serialising it with lxml.etree.tostring(). The serialised XML can
then be turned to HTML with e.g. BeautifulSoup for postprocessing
(for example, mapping Quark paragraph stylesheet to CSS classes, 
character tags and stylesheets to semantic HTML tags, rolling up
indented quotes to <blockquote>, etc.)

Outputs UTF-8.

Usage:

>>> from quark_tagged_text import get_encoding, to_xml
>>> from lxml.etree import tostring
>>> encoding = get_encoding(<source file>)
>>> with open(<source file>, encoding=encoding) as tagged_text:
>>>     element_tree = to_xml(tagged_text) 
>>> serialised_xml = tostring(element_tree, encoding='utf-8')

You can also call `to_xml` with a `css=True` argument. This will attempt
to convert some character styles into inline CSS (works with fonts, 
small caps, uppercase, strikethrough).