semvec/pypi-packages huggingface dataset:
gfiberspeedtest 1.0.1
Run a Google Fiber speedtest via cli
License: MIT
Keywords: googlefiber,speedtest

Google Fiber Speedtest cli
==========================

A simple python module to perform a google fiber speedtest, either by running
from the terminal or importing the module into your python project.
This module uses a high-level solution, in which the google fiber speedtest
webpage is loaded and manipulated with selenium. After the speedtest has 
been completed, the results will be scraped and returned.
flask-debugtoolbar-flamegraph 0.1.2
Flamegraphs for Flask Debug Toolbar
License: MIT
Keywords: flask_debugtoolbar_flamegraph

===============================
Flask Debugtoobar Flame Graph
===============================

Based on the awesome [djdt-flamegraph](https://github.com/23andMe/djdt-flamegraph) project.

Get a flame graph of the current request.

.. image:: https://img.shields.io/pypi/v/flask-debugtoolbar-flamegraph.svg
        :target: https://pypi.python.org/pypi/flask-debugtoolbar-flamegraph

Screenshot
----------

.. image:: https://raw.githubusercontent.com/23andMe/djdt-flamegraph/master/flamegraph-screenshot.png

Features
--------

* Uses https://github.com/brendangregg/FlameGraph to generate a flamegraph right in the debug panel.

Install
-------
* Add ``flask_debugtoolbar_flamegraph`` to your ``requirements.txt``.
* Add ``flask_debugtoolbar_flamegraph.FlamegraphPanel`` to ``DEBUG_TB_PANELS``.
* Run your server with ``python manage.py runserver --nothreading --noreload``

Notes
-----
* ``ValueError at /: signal only works in main thread``: Flame graphs can only be generated in a single threaded server.
* Flame graphs are disabled by default. You'll have to enable it by clicking the checkbox next to it in the Debug Toolbar.
* Probably won't work on Windows.
preprocessing 0.1.13
pre-processing package for text strings
License: MIT
Requires Python: >=3
Keywords: text pre-processing

.. image:: logo.png
   :align: center
   :alt: Spotlight Data Logo

'preprocessing'
===============
.. image:: https://readthedocs.org/projects/preprocessing/badge/?version=latest
   :target: http://preprocessing.readthedocs.io/en/latest/?badge=latest
   :alt: Documentation Status

Summary
-------

Text pre-processing package to aid in NLP package development for Python3. With this package you 
can order text cleaning functions in the order you prefer rather than relying on the order of an 
arbitrary NLP package.

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

pip:

.. code-block:: console

   pip install preprocessing

PyPI - You can also download the source distribution from:

`https://pypi.python.org/pypi/preprocessing/ 
<https://pypi.python.org/pypi/preprocessing/>`_

You can then perform:

.. code-block:: console

   pip install <path_to_tar_file>

on the tar file, or

.. code-block:: console

   python setup.py install

on/inside, respectively, the extracted package to install *preprocessing*.

Example
-------

Once you have the package installed, implementing it with Python3 takes the following form:

.. code-block:: python

   import preprocessing.text as ptext
   from preprocessing.text import keyword_tokenize, remove_unbound_punct, remove_urls

   text_string = "important string at: http://example.com"

   clean_string = ptext.preprocess_text(text_string, [
       remove_urls,
       remove_unbound_punct,
       keyword_tokenize
   ])

>>> print(clean_string)
"important string"

Should the functions be performed in a different order (i.e. keyword_tokenize -> remove_urls -> 
remove_non_bound_punct) :

>>> print(clean_string)
"important string http example.com"

Organisation
------------

This package is comprised of a single module with no intended subpackages currently. The 
*preprocessing* package is dependent on NLTK for tokenizers and stopwords. However, ignoring this,
the package only has built-in dependencies from Python 3.

Contributing
------------

If you feel like contributing:

* `Check for open issues <https://github.com/SpotlightData/preprocessing/issues>`_ or open a new issue
* Fork the preprocessing repository to start making your changes
* Write a test which shows the bug was fixed or that the feature works as expected
* Send a pull request and remember to add yourself to `CONTRIBUTORS.md <https://github.com/SpotlightData/preprocessing/blob/master/CONTRIBUTORS.md>`_

License
-------

This project is licensed under the MIT license (see `LICENSE <https://github.com/SpotlightData/preprocessing/blob/master/LICENSE>`_)
aliyun-mns 1.1.5
Aliyun Message Service Library
License: MIT


    Mns provides interfaces to Aliyun Message Service.
    mnscmd lets you do these actions: create/get/list/set/delete queue, send/receive/peek/change/delete message from/to queue, create/get/list/set/delete topic, publish message to topic, subscribe/get/list/set/unsubscribe subscription.