semvec/pypi-packages huggingface dataset:
async-mediawiki 0.2.0
Async Mediawiki Python library
License: MIT

# async-mediawiki
An asynchronous python libary to get mediawiki content

[![Codacy Badge](https://api.codacy.com/project/badge/Grade/bbab3395b87049748a95e9f0d8c73d42)](https://app.codacy.com/app/Gelbpunkt/async-mediawiki?utm_source=github.com&utm_medium=referral&utm_content=Gelbpunkt/async-mediawiki&utm_campaign=Badge_Grade_Dashboard)
[![BCH compliance](https://bettercodehub.com/edge/badge/Gelbpunkt/async-mediawiki?branch=master)](https://bettercodehub.com/)
[![FOSSA Status](https://app.fossa.io/api/projects/git%2Bgithub.com%2FGelbpunkt%2Fasync-mediawiki.svg?type=shield)](https://app.fossa.io/projects/git%2Bgithub.com%2FGelbpunkt%2Fasync-mediawiki?ref=badge_shield)
[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/ambv/black)

## Installation

It requires Python 3.6 or above and aiohttp

`pip3 install async-mediawiki`

Development Version:

`pip3 install git+https://github.com/Gelbpunkt/async-mediawiki`

## Usage
```python
import async_mediawiki as mw

wiki = mw.Wiki("wiki api url here") #make a Wiki object which is the key to the library
wiki = mw.Wiki.wikipedia("en") #alternate constructor for Wikipedia Wikis
await wiki.create_account("test", "pass1234") #create an account in the wiki
await wiki.login("test", "pass1234") #login with the newly made user
await wiki.get_random_pages(3) #get a list of pages

page = wiki.get_page("Mediawiki") #get a specific page
print(await page.html) #print the pure page html
print(await page.markdown) #print the pure page markdown (wiki code)
print(await page.text) #print the page's text (library handled filtering of the HTML)

await page.edit("That's a nice lib!") #edit the page, automatically uses the logged in user or anonymous
await wiki.close() #the Wiki object also supports a context manager (async with) to close automatically
```

## License
[![FOSSA Status](https://app.fossa.io/api/projects/git%2Bgithub.com%2FGelbpunkt%2Fasync-mediawiki.svg?type=large)](https://app.fossa.io/projects/git%2Bgithub.com%2FGelbpunkt%2Fasync-mediawiki?ref=badge_large)
ClassificaIO 1.1.5.1
Graphical User Interface for machine learning classification algorithms from scikit-learn
License: MIT
Keywords: machine learning

ClassificaIO
============

This repository contains ClassificaIO, a Python package that provides a
graphical user   (GUI) for machine learning classification algorithms from
scikit-learn.

ClassificaIO Installation Instructions
======================================

A. INSTALLATION
---------------

Recommended Pre-Installation Requirements
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

To install ClassificaIO on any platform you need:
 1. A Python distribution - ClassificaIO was built usining Anaconda distribution,
    python 3.6.

Installation Instructions
~~~~~~~~~~~~~~~~~~~~~~~~~
1. Mac or Windows
~~~~~~~~~~~~~~~~~~~~~~~~~


To install the current ClassificaIO release use pip:

.. code:: bash

    pip install ClassificaIO

Alternatively, you can install directly from github using:

.. code:: bash

    pip install git+https://github.com/gmiaslab/ClassificaIO/

2. Linux
~~~~~~~~~

First install the current release of tkinter and pip

.. code:: bash

	sudo apt-get install python3-tk
	sudo apt-get install python3-pip

To install the current ClassificaIO release use pip

.. code:: bash

    pip3 install ClassificaIO

Alternatively, you can install directly from github using:

.. code:: bash

    pip3 install git+https://github.com/gmiaslab/ClassificaIO/


B. RUNNING ClassificaIO
-----------------------

After installation you can run:

.. code:: python

    >>> from ClassificaIO import ClassificaIO
    >>> ClassificaIO.gui()

C. DOCUMENTATION
----------------

Documentation for ClassificaIO is provided in the manual, available
online at: \*
https://github.com/gmiaslab/manuals/blob/master/ClassificaIO/ClassificaIO_UserManual.pdf

The manual can also be accessed directly through the Help menu in
ClassificaIO that points to the above location.

D. LICENSING
------------

ClassificaIO is provided under an MIT license.

E. OTHER CONTACT INFORMATION
----------------------------

-  Contributions: Raeuf Roushangar, George I. Mias
-  G.MiasLab (https://georgemias.org)
-  e-mail: gmiaslab@gmail.com
-  twitter: @gmiaslab
asynapplicationinsights 0.0.4
Azure Application Insights client using asyncio
License: MIT
Keywords: asyncio aiohttp azure application insights telemetry

Azure Application Insights client using asyncio and aiohttp
----------------------------------------------------------------
`Azure Application Insights <https://azure.microsoft.com/en-us/services/application-insights/>`_ Python SDK using asyncio, including a middleware for *aiohttp* web framework.

Why
````````````````````````````````````````````````````````````````
The official `Python SDK for Application Insights <https://github.com/Microsoft/ApplicationInsights-Python>`_ from Microsoft is designed to work with both 2.x and 3.x versions of Python language.

This repository contains an alternative Python SDK for Application Insights with support for ``asyncio`` and ``async/await`` syntax, targeting Python >=3.6 and also taking advantage of support for type hinting, available since recent versions of Python language.

To install:
    >>> pip install asynapplicationinsights

Repository
----------------------------------------------------------------
GitHub: https://github.com/RobertoPrevato/asynapplicationinsights

Documentation
----------------------------------------------------------------
Wiki: https://github.com/RobertoPrevato/asynapplicationinsights/wiki