semvec/pypi-packages huggingface dataset:
text2emotion 0.0.5
Detecting emotions behind the text, text2emotion package will help you to understand the emotions in textual meassages.
License: MIT

# What is emotion?
Emotion is a biological state associated with the nervous system brought on by neurophysiological changes variously associated with thoughts, feelings, behavioural responses, and a degree of pleasure or displeasure.
(Source: Wikipedia)

Human being can easily identify the emotions from text and experience it. But what about the machines, are they able to identify the emotions from text?

#### text2emotion is the python package which will help you to extract the emotions from the content.

- Processes any textual message and recognize the emotions embedded in it.
- Compatible with 5 different emotion categories as Happy, Angry, Sad, Surprise and Fear.

## Features
> ##### 1. Text Pre-processing
> At first we have the major goal to perform data cleaning and make the content suitable for emotion analysis.
> - Remove the unwanted textual part from the message.
> - Perform the natural language processing techniques.
> - Bring out the well pre-processed text from the text pre-processing.
> ##### 2. Emotion Investigation
> Detect emotion from every word that we got from pre-processed text and take a count of it for further analytical process.
> - Find the appropriate words that express emotions or feelings.
> - Check the emotion category of each word.
> - Store the count of emotions relevant to the words found.
> ##### 3. Emotion Analysis
> After emotion investigation, there is the time of getting the significant output for the textual message we input earlier.
> - The output will be in the form of dictionary.
> - There will be keys as emotion categories and values as emotion score.
> - Higher the score of a particular emotion category, we can conclude that the message belongs to that category.

## How to use?
#### [Check Demo on Colab](https://bit.ly/3hlXujZ)

## App Deployment
Here's the code implementation with **Streamlit App** for the users.
1. Enter the text.
2. Hit the submit button.
3. Tada!! Get the output in visual form.
#### [Check Demo of App](https://text2emotion.herokuapp.com/)

Let's experience the library, test your multiple use cases on web app and check whether the library performs as per your expectations.
AirSpider 2.0.4
An Easy-to-use and Fast Python Spider Framework
License: MIT
Requires Python: >=3.6

<p align="center">
    <img src="https://picreso.oss-cn-beijing.aliyuncs.com/airs.png" width="150px">
  <p align="center" style="font-weight:bold">
    Distributed  -  Asynchronous  - Easy-to-use
  <br>
   <br>
 		An Easy-to-use and Fast Python Spider Framework
  <img src="http://picreso.oss-cn-beijing.aliyuncs.com/airdemo.png">
</p>




---

## Overview

> + **AirSpider** is a high-performance asynchronous crawler framework for developers 
> + Based on Redis: task distribution, task deduplication, and distributed ☁️

## Requirements

- Python 3.6
- Works on Linux, Windows, macOS

## Features

+  Quick to Start
+  Low Coupling 
+  High Cohesion 
+  Easy Expansion
+  Orderly Workflow 

## Installation

``` shell
# For Linux && MacOS
pip3 install airspider


# For Windows
pip3 install airspider


```

  ## Documents

  + [Introduction](https://github.com/Xunzhuo/AirSpider/tree/master/Docs/cn/introduction.md)：Introduction to **AirSpider**
  + [Tutorials](https://github.com/Xunzhuo/AirSpider/tree/master/Docs/cn/tutorials.md)： Quick to program a Spider By **AirSpider**
  + [Plugins](https://github.com/Xunzhuo/AirSpider/tree/master/Docs/cn/plugins.md)：Program extensions for **AirSpider**

  ## Topics

  - [Item](https://github.com/Xunzhuo/AirSpider/tree/master/Docs/cn/topics/item.md)：Define Target in HTML
  - [Selector](https://github.com/Xunzhuo/AirSpider/tree/master/Docs/cn/topics/selector.md)：Select Target from HTML
  - [Request](https://github.com/Xunzhuo/AirSpider/tree/master/Docs/cn/topics/request.md)：Request Part
  - [Response](https://github.com/Xunzhuo/AirSpider/tree/master/Docs/cn/topics/response.md)：Response Part
  - [Middleware](https://github.com/Xunzhuo/AirSpider/tree/master/Docs/cn/topics/middleware.md)：Make Airspider Support to Extensions
  - [Spider](https://github.com/Xunzhuo/AirSpider/tree/master/Docs/cn/topics/spider.md)：Entrance for AirSpider

## TODO

+ Complete Plugins of Redis
+ Complete Distributed Architecture

## Contributing

**AirSpider**🕷️ is still under **Developing**

> Feel free to open issues💬 and pull requests

- Report or Fix bugs
- Build Powerful plugins
- Make documentation Better
- Add Examples of Spiders 

![](http://picreso.oss-cn-beijing.aliyuncs.com/monkey.jpg)
raindancesvi 0.1.0
A machine learning package
License: MIT
Requires Python: >=3.6
Keywords: machine learning rd6 inclass raindances

# Welcome to RainDancesVI!

RainDancesVI is TensorFlow-based implementation of Independent Classifier Networks (InClass nets) in Python 3. InClass nets can be used for

* Nonparametric estimatimation of conditional independence mixture models
* Unsupervised classification

Project website: <https://prasanthcakewalk.gitlab.io/raindancesvi/>  

### References and citation guide

If you use the techniques implemented in RainDancesVI in your work, please consider citing the original paper that introduced them.

* Konstantin K. Matchev, Prasanth Shyamsundar, _"InClass Nets: Independent Classifier Networks for Nonparametric Estimation of Conditional Independence Mixture Models and Unsupervised Classification"_, [arXiv:2009.00131 [stat.ML]](https://arxiv.org/abs/2009.00131).

### Copyright

Copyright &copy; 2020 Konstantin Matchev and Prasanth Shyamsundar  
<details>
<summary>RainDancesVI is licensed under the MIT License (click to expand).</summary>
<br>
Permission is hereby granted, free of charge, to any person obtaining a copy
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copies of the Software, and to permit persons to whom the Software is
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The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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