semvec/pypi-packages huggingface dataset:
sidsd16 0.0.1
A package to detect intent from utterances.
Requires Python: >=3.6

# Intent Recognition

This is a package to detect intent of utterances, trained on the SNIPS dataset.

It can detection any of the following intents in an input utterance:
1. PlayMusic	
2. GetWeather	
3. BookRestaurant	
4. RateBook	
5. SearchScreeningEvent	
6. SearchCreativeWork	
7. AddToPlaylist	

Example usage:

import intent_recognition

predictor = intent_recognition.Predictor()

confidence, pred_intent = predictor("find animated movies playing near me")
asyncfileserver 0.2.0
File Server
Requires Python: >=3.7

![Test and Coverage Measuring](https://github.com/tarc/asyncfileserver/workflows/Test%20and%20Coverage%20Measuring/badge.svg?branch=master) [![codecov](https://codecov.io/gh/tarc/asyncfileserver/branch/master/graph/badge.svg)](https://codecov.io/gh/tarc/asyncfileserver)

# Simple File Server Featuring Python Async Constructs

This is a toy project to excercise the new async facilities from python 3.5+.

This project features [Github Actions](https://github.com/features/actions)
to automate testing, package publishing and even to bump versions and tag
them to the repository.

The package is published to [PyPI](https://pypi.org/) as
[asyncfileserver](https://pypi.org/project/asyncfileserver/). The test
coverage report is provided by [Codecov](https://codecov.io/).
sidsd15 0.0.1
A package to detect intent from utterances.
Requires Python: >=3.6

# Intent Recognition

This is a package to detect intent of utterances, trained on the SNIPS dataset.

It can detection any of the following intents in an input utterance:
1. PlayMusic	
2. GetWeather	
3. BookRestaurant	
4. RateBook	
5. SearchScreeningEvent	
6. SearchCreativeWork	
7. AddToPlaylist	

Example usage:

import intent_recognition

predictor = intent_recognition.Predictor()

confidence, pred_intent = predictor("find animated movies playing near me")
buptgw 0.1.1
login to gw.bupt.edu.cn to access the Internet
Requires Python: >=3.5
Keywords: bupt network gateway login

# BUPT Gateway Login

用于登录北京邮电大学校园网的命令行程序。跨平台，仅 Python 3。

可以从文件读取用户名和密码自动登录，或者通过参数指定用户名密码，也可以交互式输入用户名密码。

更新：

- 0.1.0：增加 check_net_account 函数，用于通过学校 VPN 登录页面检查上网账号是否正确。

已知问题：

- check_net_account 在校园网某些网络环境下不能工作。（在某些服务器上请求该页面，可以建立连接但服务器无响应）

## 安装

直接使用 pip 安装

`pip install buptgw`

---
如果有问题可以使用 pypi 源，且支持 IPv6，校园网电脑无需登录网络即可访问

`pip install -i https://pypi.org/simple buptgw`

如果你没有 root 权限，可以添加 `--user` 参数即

`pip install buptgw --user` 或
`pip install -i https://pypi.org/simple buptgw --user`

另外在某些比较旧版本系统上 pip 指向 pip2，所以需要使用 pip3 代替命令中的 pip

## 使用

登录 `buptgw -i` 

退出 `buptgw -o`

保存用户名密码到文件（下次登录无需手动输入） `buptgw -w`  

### 全部参数

```
Usage: buptgw -i|-o|-w  [-c <config_file>] [-u <username>] [-p <password>]
    -i                login
    -o                logout
    -w                write username and password to config file
    -c <config_path>  config file path, optional, defualt is ~/.buptgw
    -u <username>
    -p <password>
```

参数 `-i` 代表登录 `-o` 代表退出，`-w` 把用户名和密码写入配置文件，这三个只能选择一个

`-c` 指定配置文件路径（存储用户名和密码），对 `-i` 和 `-w` 有效。如果不指定配置文件，默认为 ~/.buptgw。

`-u` 指定用户名，如果不指定，会从配置文件读取，如果读取失败则要求输入

`-p` 指定密码，如果不指定，则要求输入（如果用户名也没输入则一并从配置文件读取）

### 在 python 中调用

```python
import buptgw

buptgw.login('2018xxxxxx', 'passwd') # 登录，xxx 处替换为正确的学号和密码
buptgw.logout() # 退出

buptgw.check_net_account('2018xxxxxx', 'passwd') # 检查该学号/密码是否匹配，如果匹配返回 True，不匹配返回 False
```

### 实现开机自动登录

#### window

windows 下编写 bat 文件（xxx 处替换为正确的学号和密码），例如保存为 network.bat （**注意，不能**保存为 buptgw.bat 这样会导致这个文件自己调用自己）

```bat
buptgw -i -u 2018xxxxxx -p xxxxx
```

然后把这个文件放到系统的启动目录下，一般来说，通过运行（快捷键是 win + R），输入 `shell:startup ` 可以快速打开启动目录。

#### Linux

把登录命令写入 ~/.profile 中





作者博客 ：https://es2q.com
sidsd14 0.0.1
A package to detect intent from utterances.
Requires Python: >=3.6

# Intent Recognition

This is a package to detect intent of utterances, trained on the SNIPS dataset.

It can detection any of the following intents in an input utterance:
1. PlayMusic	
2. GetWeather	
3. BookRestaurant	
4. RateBook	
5. SearchScreeningEvent	
6. SearchCreativeWork	
7. AddToPlaylist	

Example usage:

import intent_recognition

predictor = intent_recognition.Predictor()

confidence, pred_intent = predictor("find animated movies playing near me")
sidsd13 0.0.1
A package to detect intent from utterances.
Requires Python: >=3.6

# Intent Recognition

This is a package to detect intent of utterances, trained on the SNIPS dataset.

It can detection any of the following intents in an input utterance:
1. PlayMusic	
2. GetWeather	
3. BookRestaurant	
4. RateBook	
5. SearchScreeningEvent	
6. SearchCreativeWork	
7. AddToPlaylist	

Example usage:

import intent_recognition

predictor = intent_recognition.Predictor()

confidence, pred_intent = predictor("find animated movies playing near me")
xtalpi 0.0.1
xtalpi
Requires Python: >=3.5
Keywords: xtalpi

======
Xtalpi
======




.. image:: https://pyup.io/repos/github/taceywong/xtalpi/shield.svg
     :target: https://pyup.io/repos/github/taceywong/xtalpi/
     :alt: Updates





Features
--------

* TODO


=======
History
=======

0.0.1 (2020-10-28)
------------------

* First release on PyPI.