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89 lines
2.2 KiB
Markdown
89 lines
2.2 KiB
Markdown
---
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sidebar_position: 6
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description: 杂项
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---
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# 杂项
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## 特殊装饰器
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`nonebot_plugin_alconna` 提供 了一个 `funcommand` 装饰器，其用于将一个接受任意参数，
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返回 `str` 或 `Message` 或 `MessageSegment` 的函数转换为命令响应器。
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```python
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from nonebot_plugin_alconna import funcommand
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@funcommand()
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async def echo(msg: str):
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return msg
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```
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其等同于
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```python
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from arclet.alconna import Alconna, Args
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from nonebot_plugin_alconna import on_alconna, AlconnaMatch, Match
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echo = on_alconna(Alconna("echo", Args["msg", str]))
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@echo.handle()
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async def echo_exit(msg: Match[str] = AlconnaMatch("msg")):
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await echo.finish(msg.result)
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```
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## 特殊构造器
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`nonebot_plugin_alconna` 提供了一个 `Command` 构造器，其基于 `arclet.alconna.tools` 中的 `AlconnaString`，
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以类似 `Koishi` 中注册命令的方式来构建一个 AlconnaMatcher：
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```python
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from nonebot_plugin_alconna import Command, Arparma
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book = (
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Command("book", "测试")
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.option("writer", "-w <id:int>")
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.option("writer", "--anonymous", {"id": 0})
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.usage("book [-w <id:int> | --anonymous]")
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.shortcut("测试", {"args": ["--anonymous"]})
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.build()
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)
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@book.handle()
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async def _(arp: Arparma):
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await book.send(str(arp.options))
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```
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甚至，你可以设置 `action` 来设定响应行为：
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```python
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book = (
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Command("book", "测试")
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.option("writer", "-w <id:int>")
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.option("writer", "--anonymous", {"id": 0})
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.usage("book [-w <id:int> | --anonymous]")
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.shortcut("测试", {"args": ["--anonymous"]})
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.action(lambda options: str(options)) # 会自动通过 bot.send 发送
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.build()
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)
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```
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## 中间件
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在 `AlconnaMatch`, `AlconnaQuery` 或 `got_path` 中，你可以使用 `middleware` 参数来传入一个对返回值进行处理的函数，
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```python {1, 9}
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from nonebot_plugin_alconna import image_fetch
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mask_cmd = on_alconna(
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Alconna("search", Args["img?", Image]),
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)
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@mask_cmd.handle()
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async def mask_h(matcher: AlconnaMatcher, img: Match[bytes] = AlconnaMatch("img", image_fetch)):
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result = await search_img(img.result)
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await matcher.send(result.content)
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```
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其中，`image_fetch` 是一个中间件，其接受一个 `Image` 对象，并提取图片的二进制数据返回。
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