semvec/pypi-packages huggingface dataset:
NRCLex 4.0
An affect generator based on TextBlob and the NRC affect lexicon.  Note that lexicon license is for research purposes only.
Requires Python: >=2.7

# NRCLex

(C) 2019 Mark M. Bailey, PhD

## About
NRCLex will measure emotional affect from a body of text.  Affect dictionary contains approximately 27,000 words, and is based on the National Research Council Canada (NRC) affect lexicon (see link below) and the NLTK library's WordNet synonym sets.

Lexicon source is (C) 2016 National Research Council Canada (NRC) and this package is **for research purposes only**. Source: http://saifmohammad.com/WebPages/NRC-Emotion-Lexicon.htm As per the terms of use of the NRC Emotion Lexicon, if you use the lexicon or any derivative from it, cite this paper: Crowdsourcing a Word-Emotion Association Lexicon, Saif Mohammad and Peter Turney, Computational Intelligence, 29 (3), 436-465, 2013.

NLTK data is (C) 2019, NLTK Project.  Source: [NLTK] (https://www.nltk.org/).  Reference: Bird, Steven, Edward Loper and Ewan Klein (2009), Natural Language Processing with Python. Oâ€™Reilly Media Inc.

## Update
* Finally got around to cleaning this up a bit.  Updated PyPI package with current version.  Thanks to all the contributors for cleaning up my terrible code!
* Expanded NRC lexicon from approximately 10,000 words to 27,000 based on WordNet synonyms.
* Minor bug fixes.
* Contributor updated NTC library.

## Installation
`pip install NRCLex`

## Affects
Emotional affects measured include the following:

* fear
* anger
* anticipation
* trust
* surprise
* positive
* negative
* sadness
* disgust
* joy

## Sample Usage

`from nrclex import NRCLex`<br><br>


*#Instantiate NRCLex object, you can pass your own dictionary filename in json format.*<br>

`text_object = NRCLex(lexicon_file='nrc_en.json')`<br><br>


*#You can pass your raw text to this method(for best results, 'text' should be unicode).*<br>

`text_object.load_raw_text(text: str)`<br><br>


*#You can pass your already tokenized text as a list of tokens, if you want to use an already tokenized input.
This usage assumes that the text is correctly tokenized and does not make use of TextBlob.*<br>

`text_object.load_token_list(list_of_tokens: list)`<br><br>


*#Return words list.*<br>

`text_object.words`<br><br>


*#Return sentences list.*<br>

`text_object.sentences`<br><br>


*#Return affect list.*<br>

`text_object.affect_list`<br><br>


*#Return affect dictionary.*<br>

`text_object.affect_dict`<br><br>


*#Return raw emotional counts.*<br>

`text_object.raw_emotion_scores`<br><br>


*#Return highest emotions.*<br>

`text_object.top_emotions`<br><br>


*#Return affect frequencies.*<br>

`text_object.affect_frequencies`
nonebot-plugin-mcqq-mcrcon-test 0.0.4
基于NoneBot的QQ群聊与Minecraft Server消息互通插件

# nonebot-plugin-mcqq

基于 `NoneBot` 的与 `Minecraft Server` 互通消息插件

支持QQ群、QQ频道

# 文档

- [正在不断更新的文档](https://doc.scareye.com/mc_qq/)

# 功能

- 即将更新
  - 适用于原版服务端的 `MCRCON` + `WebSockets` 分支版本
  - 理论上同样适用于纯 `MOD` 端
  - 缺陷为 Server 发送到 Bot 的第一条消息会失败，后续消息正常
  - `[图片]`、`[视频]` 等特殊消息可通过点击在浏览器查看

- 推送消息列表
  - 服务器 -> QQ
    - 加入 / 离开 服务器消息
    - 玩家聊天信息
  - QQ -> 服务器
    - 群员聊天文本
    - 图片、视频等内容转换为 `[图片]`、`[视频]`
  - 计划
    - 将图片、视频等消息更改为可单击通过浏览器打开

- 特殊消息支持
  - 群聊
    - [x] @ 消息
    - [x] 回复消息
  - 频道
    - [ ] @ 消息
    - [ ] 回复消息
  - 未支持的消息已被替换，如： `[图片]`、 `[视频]` 等等

# 特别感谢
- [@SK-415](https://github.com/SK-415) ：感谢SK佬给予许多优秀的建议和耐心的解答。
- [@zhz-红石头](https://github.com/zhzhongshi) ：感谢红石头在代码上的帮助
- [NoneBot2](https://github.com/nonebot/nonebot2)： 插件使用的开发框架。
- [go-cqhttp](https://github.com/Mrs4s/go-cqhttp)： 稳定完善的 CQHTTP 实现。
Pyttoresque 1.1.1
Library for working with NyanCAD tools
Requires Python: >=3.6

<!--
SPDX-FileCopyrightText: 2022 Pepijn de Vos

SPDX-License-Identifier: MPL-2.0
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# Pyttoresque

A Python library for working with NyanCAD tools.

* `pyttoresque.netlist`: downloading schematics from a Mosaic CouchDB and generating SPICE netlists.
* `pyttoresque.simserver`: simulate netlists on a simulation server and stream results.
* `pyttoresque.app`: a Jupyter server extension to host Mosaic and Bokeh on Jupyter

https://nyancad.github.io/Mosaic/

This project was funded through the <a href="/PET">NGI0 PET</a> Fund, a fund established by <a href="https://nlnet.nl">NLnet</a> with financial support from the European Commission's <a href="https://ngi.eu">Next Generation Internet</a> programme, under the aegis of DG Communications Networks, Content and Technology under grant agreement N<sup>o</sup> 825310.