semvec/pypi-packages huggingface dataset:
botoy 9.11
OPQBot/IOTQQ/IOTBot的Python开发助手
License: MIT
Requires Python: >=3.8
Keywords: iotbot, iotqq, OPQ, OPQBot, botoy

# botoy

[![QQ Group](https://img.shields.io/badge/QQ%E7%BE%A4-856337734-important?style=flat-square&logo=tencentqq)](https://jq.qq.com/?_wv=1027&k=K8iQy7i7)

[![pypi](https://img.shields.io/pypi/v/botoy?style=flat-square 'pypi')](https://pypi.org/project/botoy/)
[![python](https://img.shields.io/badge/python-3.8+-blue 'python')](https://pypi.org/project/botoy/)
[![Lines of code](https://img.shields.io/tokei/lines/github/opq-osc/botoy?label=lines&style=flat-square)](https://github.com/opq-osc/botoy)
[![GitHub code size in bytes](https://img.shields.io/github/languages/code-size/opq-osc/botoy?style=flat-square)](https://github.com/opq-osc/botoy)
[![LICENSE](https://img.shields.io/github/license/opq-osc/botoy?style=flat-square)](https://github.com/opq-osc/botoy/blob/main/LICENSE)

对机器人框架[OPQ](https://github.com/OPQBOT/OPQ/)接口的 Python 封装,
因为功能模块耦合度低, 所以你可以完全使用该框架开发，也可以选取需要的内容到自己的项目中

---

## 安装

```shell
pip install botoy -i https://pypi.org/simple --upgrade
```

## 示例

如果你配置好了 OPQ，并且配置保持默认(bot 连接地址`http://127.0.0.1:8086`)，
下面示例可实现在收到群消息内容为 `test` 时回复 `ok`

新建文件 `bot.py`

```python
from botoy import bot, ctx, S

@bot
async def test():
    if ctx.g and ctx.g.text == 'test':
        await S.text('ok')

bot.print_receivers()
bot.run()
```

运行 `python bot.py`

```
+------+--------+-------+----------------+
| Name | Author | Usage |      Meta      |
+------+--------+-------+----------------+
| test |        |       | test.py line 4 |
+------+--------+-------+----------------+
ℹ️ 04-15 19:21:58 INFO 连接中[ws://localhost:8086/ws]...
✔️ 04-15 19:21:58 SUCCESS 连接成功!
```

# [文档](https://botoy.readthedocs.io/)

<!-- # [简单例子](https://github.com/opq-osc/botoy-plugins) -->

<!-- # [插件模板](https://github.com/opq-osc/botoy-plugin-template) -->

# 感谢

[yuban10703](https://github.com/yuban10703)
[milkice](https://github.com/milkice233)

# LICENSE

MIT

# CHANGE LOG

# See [releases](https://github.com/xiyaowong/botoy/releases)

## 0.0.2

- 修复模块导入错误

## V0.0.1

初次发布
validataclass 0.11.0
Library for input validation designed for (but not restricted to) JSON-based APIs, neatly integrating with dataclasses.
License: MIT
Requires Python: >=3.8

# validataclass

[![Unit tests](https://github.com/binary-butterfly/validataclass/actions/workflows/tests.yml/badge.svg)
](https://github.com/binary-butterfly/validataclass/actions/workflows/tests.yml)

Python library for input validation designed for (but not restricted to) JSON-based APIs, neatly integrating with
dataclasses.

**Status:** Beta.


## Installation

validataclass is available on [PyPI](https://pypi.org/project/validataclass/).

To install it using [pip](https://pip.pypa.io/en/stable/getting-started/), just run:

```shell
pip install validataclass
```

If you add the package to your dependencies, it is recommended to use
[compatible release](https://www.python.org/dev/peps/pep-0440/#compatible-release) version specifiers to make sure you
always get the latest version of the library but without running into breaking changes:

```shell
pip install validataclass~=0.11.0
```

However, keep in mind that the library still is in its beta phase (as indicated by the major version of 0). There can
and will be smaller breaking changes between 0.x minor versions, but we will try to keep them at a minimum and save the
big breaking changes for the release of version 1.0.0.


## Usage

See [`docs/`](https://github.com/binary-butterfly/validataclass/blob/main/docs/index.md) for documentation on how to use
this library and for examples.

(**Note:** The documentation is mostly done now, but still a work in progress.)


## Development

### Virtual environment

To setup a virtualenv for development of the library, run `make venv`.

Alternatively you can manually run the following commands (which do the same as the make target):

```
$ virtualenv venv
$ source venv/bin/activate
$ pip install -r requirements.txt
$ pip install -e .
```


### Running unit tests

Unit tests can be run using `make tox` or by directly executing `tox`.

For this to work you need to either be inside the virtualenv (see above) or to have [tox](https://tox.wiki/en/latest/)
installed in your system locally.