Metadata-Version: 2.1
Name: SHiNiNG
Version: 0.0.1.0
Summary: The easiest and powerful deep-learning-text-classifier based on keras and gensim for human beings and all purposes.
Home-page: https://github.com/eathoublu/SHiNiNG
Author: Lan-Yixiao_Eathoublu
Author-email: 1012950361@qq.com
License: MIT
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Programming Language :: Python :: Implementation :: PyPy
Requires-Python: >=3.6.0
Description-Content-Type: text/markdown
Provides-Extra: fancy feature
Requires-Dist: keras
Requires-Dist: jieba
Requires-Dist: gensim
Requires-Dist: tensorflow
Requires-Dist: numpy
Provides-Extra: fancy feature
Requires-Dist: tqdm; extra == 'fancy feature'


# SHiNiNG nlp toolkit
## The easiest and powerful deep-learning-text-classifier for human beings and all purposes.
## AUTHOR - Lan-Yixiao Eathoublu From Northeastern University Shenyang China.
## Contact: 1012950361@qq.com


## Introduce

This is a lightweight nlp toolkit based on keras, tensorflow, gensim and jieba. So you should install these package at first.
It provided only two APIs which is the easiest and powerful way for users to train there model and use it in production environment for all purposes.


## How to use it?
To use it is easy.
```python

import SHiNiNG

sng = SHiNiNG.Shining()  # get instance of Shining.

```

There’s only two APIs.

```python
Shining().train_from_file(text_src='', tag_src='')  # get data and target split by ‘\n’ in files, you should run this method first to get trained model to predict. All of it is automatically done.
Shining().predict_from_file(src_file_path='')  # get data need to be predict from file, and get the target in ‘output.txt’

```







