semvec/pypi-packages huggingface dataset:
tq010or-distributions 0.0.1rc0
This is a package for common distributions, e.g. Gaussian, Binomial
Requires Python: >=3.6

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# Distribution: A package to demonstrate a few statistical distributions

This **tq010or-distribution** package is a demo for a few statistical distributions.

## Features

- Can **sample** from the distribution
- Can **estimate** distribution parameters with **samples**
- Easy **plot** integration
- Support Gaussian and Binomial (as of July 2020) 
- Extensible to include other distributions

## Installation

- **Operating system**: Linux · Windows (Cygwin, MinGW, Visual Studio)
- **Python version**: Python 3.6+

### pip

```bash
pip install tq010or-distribution
```

Or you can install them in your virtual environment:
```bash
python -m venv .env
source .env/bin/activate
pip install tq010or-distribution
```

### Usage
```bash
>>> from distributions.gaussian import Gaussian
>>> g = Gaussian(0, 1)
>>> print(g)
Gaussian(0, 1)
>>> samples = g.sample(10000)
>>> ge = Gaussian.estimate(samples)
>>> print(ge)
Gaussian(0.016869274639641572, 0.9910041611791893)
>>> g1 = Gaussian(0, 3)
>>> g2 = Gaussian(1, 4)
>>> g3 = g1 + g2
>>> assert g3 == g1 + g2
>>> 
```

## Run tests

```bash
python -c "import os; import distributions; print(os.path.dirname(distributions.__file__))"
pip install -r path/to/requirements.txt
python -m pytest <distributions-directory>
```
ipadic 1.0.0
IPAdic packaged for Python

# ipadic-py

This is a version of IPAdic packaged for use in Python with
[mecab-python3](https://github.com/SamuraiT/mecab-python3) or
[fugashi](https://github.com/polm/fugashi). 

# You Shouldn't Use This

This is the version of IPAdic included with MeCab. It hasn't been updated since
at least 2007. The organization that created it no longer does this kind of
work. The contact URLs listed in the source no longer resolve. It doesn't
contain important recent terms like 令和, the current era name.

Instead you should use [Unidic](https://unidic.ninjal.ac.jp/), which is
maintained by NINJAL. 

This package is provided for compatability with old benchmarks or models.

## Usage

To install:

    pip install ipadic

To initialize with mecab-python3:

    import MeCab
    import ipadic
    tagger = MeCab.Tagger(ipadic.MECAB_ARGS)
    print(tagger.parse("図書館にいた事がバレた"))

# License

IPAdic is copyright the Nara Institute of Science and Technology and ICOT. For
details see the COPYING file included in this distribution. This version of the
dictionary is distributed in compliance with the terms specified in that file.

The code in this repository is by Paul McCann and is available under the MIT or
WTFPL license, as you prefer.
TextProcess-Ora 0.0.5
compute similar scores of two text
Requires Python: >=2.7

# TextProcess Package
这是一个文本预处理的python库，主要是在做自然语言处理任务时，对文本进行一些预处理工作。

# 支持的功能
* 英文字母大写转小写
* 中文繁体转简体
* 中文简体转繁体
* 全角转半角
* 去除emotion表情
* 将emotion表情替换成文字描述
* 去除控制字符
* 去除超链接tag，href
* 去除http超链接
* 将长数字转换成特殊字符
* 过滤括号及括号内的内容【xxxxx】/（xxxxxxx）/ [xxxx] 【.*】|（.*）|\[.*\]
* 过滤连续标点和空格
* 只保留中文字符
* 保留中文和英文
* 保留中文和英文及数字
# 安装方法
```pip install TextProcess-Ora```

# 使用方法
```
import TextProcess.TextProcess as tp


if __name__ == '__main__':
    test_string = u'我��愛你中華https://<a></a>,,,,,, Hello Word 121233124234213 [sdfsd]{}【】'
    test = tp.TextProcess()
    # 英文字母大写转小写
    print(test.strLower(test_string))
    # '我��你中华<http://><a></a>, hello word。'

    # 中文繁体转简体
    print(test.Tra2Sim(test_string, 'zh-hans'))

    # 中文简体转繁体
    print(test.Tra2Sim(test_string, 'zh-hant'))

    # 全角转半角
    print(test.strQ2B(test_string))

    # 去除emotion表情
    print(test.replace_emotion(test_string,""))

    # 将emotion表情替换成文字描述
    print(test.convert_emotion(test_string))

    # 去除控制字符
    print(test.replace_control_character(test_string, ''))

    # 去除超链接tag，href
    print(test.remove_ahref(test_string, ''))

    # 去除http超链接
    print(test.remove_http(test_string, ''))

    # 将长数字转换成特殊字符
    print(test.replace_long_num(test_string, 'LONG_NUM'))

    # 过滤括号及括号内的内容【xxxxx】/（xxxxxxx）/ [xxxx] 【.*】|（.*）|\[.*\]
    print(test.replace_brackets(test_string, ''))

    # 过滤连续标点和空格
    print(test.remove_commas(test_string))

    # 只保留中文字符
    print(test.remove_not_che(test_string))

    # 保留中文和英文
    print(test.keep_chi_eng(test_string, ''))

    # 保留中文和英文及数字
    print(test.keep_chi_eng_num(test_string, ''))

    # 一条龙服务 基本过滤
    print(test.evaluate(test_string, 'OnlinePipe'))

    #一条龙服务 强过滤
    print(test.evaluate(test_string, 'OnlinePipeStrictMore'))

    #一条龙服务 极强过滤
    print(test.evaluate(test_string, 'OnlinePipeStrictMost'))
```