频道机器人是基于QQ开放生态的高级扩展服务,通过开放的接口,能够与QQ频道用户实现交互形式丰富的互动。
该教程主要是面向新接触QQ频道机器人的开发者,通过教程可以学习到如何通过Python的官方SDK实现一些机器人的基本功能。
请先 完成机器人注册和添加,获取机器人相关的信息。相关教程可点击查看 QQ机器人快速注册指南 实验准备
机器人SDK: 提供开发者使用的基于OpenAPI的官方SDK,优势主要在于服务稳定性及维护频率高 机器人AppID: 注册机器人后系统分配的唯一ID标识,在完成机器人注册和添加的教程可以获取 机器人Token: 注册机器人后使用OpenAPI系统分配的密钥,在完成机器人注册和添加的教程可以获取,请注意不要外泄。
安装Python3 推荐使用Python3,实验环境已经预安装,可执行下面命令,进行Python版本验证
pythonpython3 --version
在终端执行下面命令安装机器人PythonSDK:
pythonpip install qq-bot
同时,由于需要读取 yaml 文件的内容,我们也需要安装 pyyaml
pythonpip install pyyaml
创建一个 demo 项目文件夹 在 demo 文件夹下创建名为 config.yaml 的配置文件
pythontouch config.yaml
接着,在 demo 文件夹下创建一个名为 robot.py 的文件:
pythontouch robot.py
导入Token 和 AppID 请点击打开 config.yaml 文件,并填入自己机器人的 AppID 和 Token ,注意保存
pythontoken:
appid: "123"
token: "xxxx"
请点击打开 robot.py ,并在文件中复制导入相关依赖包的代码,注意保存
robot.py
pythonimport asyncio
import json
import os.path
import threading
from typing import Dict, List
import aiohttp
import qqbot
from qqbot.core.util.yaml_util import YamlUtil
from qqbot.model.message import MessageEmbed, MessageEmbedField, MessageEmbedThumbnail, CreateDirectMessageRequest, \
MessageArk, MessageArkKv, MessageArkObj, MessageArkObjKv
test_config = YamlUtil.read(os.path.join(os.path.dirname(__file__), "config.yaml"))
在 robot.py 文件中添加如下代码,注意保存 :
robot.py
pythonasync def _message_handler(event, message: qqbot.Message):
"""
定义事件回调的处理
:param event: 事件类型
:param message: 事件对象(如监听消息是Message对象)
"""
msg_api = qqbot.AsyncMessageAPI(t_token, False)
# 打印返回信息
qqbot.logger.info("event %s" % event + ",receive message %s" % message.content)
# 发送消息告知用户
message_to_send = qqbot.MessageSendRequest(content="你好", msg_id=message.id)
await msg_api.post_message(message.channel_id, message_to_send)
# async的异步接口的使用示例
if __name__ == "__main__":
t_token = qqbot.Token(test_config["token"]["appid"], test_config["token"]["token"])
# @机器人后推送被动消息
qqbot_handler = qqbot.Handler(
qqbot.HandlerType.AT_MESSAGE_EVENT_HANDLER, _message_handler
)
qqbot.async_listen_events(t_token, False, qqbot_handler)
在终端命令行输入并执行下列命令,运行机器人
pythonpython3 /home/demo/robot.py
这时在频道内 @机器人 hello 指令就可以收到回复了
首先,在 robot.py 中添加用于获取天气数据的函数,注意保存
:
robot.py
pythonasync def get_weather(city_name: str) -> Dict:
"""
获取天气信息
:return: 返回天气数据的json对象
"""
weather_api_url = "http://api.k780.com/?app=weather.today&cityNm=" + city_name + "&appkey=10003&sign=b59bc3ef6191eb9f747dd4e83c99f2a4&format=json"
async with aiohttp.ClientSession() as session:
async with session.get(
url=weather_api_url,
timeout=5,
) as resp:
content = await resp.text()
content_json_obj = json.loads(content)
return content_json_obj
上面链接的天气API使用的 sign=b59bc3ef6191eb9f747dd4e83c99f2a4 可能会过期,如下图指引 请前往天气API地址查看最新的测试sign并替换,或注册账号申请一个免费sign
修改 _message_handler 方法 在 _message_handler 方法中,加入调用 get_weather 函数并发送天气的代码。完整 _message_handler 的实现如下:
robot.py
pythonasync def _message_handler(event, message: qqbot.Message):
"""
定义事件回调的处理
:param event: 事件类型
:param message: 事件对象(如监听消息是Message对象)
"""
msg_api = qqbot.AsyncMessageAPI(t_token, False)
# 打印返回信息
qqbot.logger.info("event %s" % event + ",receive message %s" % message.content)
# 获取天气数据并发送消息告知用户
weather_dict = await get_weather("深圳")
weather_desc = weather_dict['result']['citynm'] + " " \
+ weather_dict['result']['weather'] + " " \
+ weather_dict['result']['days'] + " " \
+ weather_dict['result']['week']
message_to_send = qqbot.MessageSendRequest(msg_id=message.id, content=weather_desc, image=weather_dict['result']['weather_icon'])
await msg_api.post_message(message.channel_id, message_to_send)
在终端命令行输入并执行下列命令,运行机器人
ptyhonpython3 /home/demo/robot.py
效果图如下:
ptyhonimport asyncio import json import os.path import threading from typing import Dict, List import aiohttp import qqbot from qqbot.core.util.yaml_util import YamlUtil from qqbot.model.message import MessageEmbed, MessageEmbedField, MessageEmbedThumbnail, CreateDirectMessageRequest, \ MessageArk, MessageArkKv, MessageArkObj, MessageArkObjKv test_config = YamlUtil.read(os.path.join(os.path.dirname(__file__), "config.yaml")) async def _message_handler(event, message: qqbot.Message): """ 定义事件回调的处理 :param event: 事件类型 :param message: 事件对象(如监听消息是Message对象) """ msg_api = qqbot.AsyncMessageAPI(t_token, False) # 打印返回信息 qqbot.logger.info("event %s" % event + ",receive message %s" % message.content) # 获取天气数据并发送消息告知用户 weather_dict = await get_weather("北京") weather_desc = weather_dict['result']['citynm'] + " " \ + weather_dict['result']['weather'] + " " \ + weather_dict['result']['days'] + " " \ + weather_dict['result']['week'] message_to_send = qqbot.MessageSendRequest(msg_id=message.id, content=weather_desc, image=weather_dict['result']['weather_icon']) await msg_api.post_message(message.channel_id, message_to_send) async def get_weather(city_name: str) -> Dict: """ 获取天气信息 :return: 返回天气数据的json对象 """ weather_api_url = "http://api.k780.com/?app=weather.today&cityNm=" + city_name + "&appkey=65849&sign=a54c59baa7a0c590cbf17d699be41b1d&format=json" async with aiohttp.ClientSession() as session: async with session.get( url=weather_api_url, timeout=5, ) as resp: content = await resp.text() content_json_obj = json.loads(content) return content_json_obj # async的异步接口的使用示例 if __name__ == "__main__": t_token = qqbot.Token(test_config["token"]["appid"], test_config["token"]["token"]) # @机器人后推送被动消息 qqbot_handler = qqbot.Handler( qqbot.HandlerType.AT_MESSAGE_EVENT_HANDLER, _message_handler ) qqbot.async_listen_events(t_token, False, qqbot_handler) await msg_api.post_message(message.channel_id, message_to_send)
上面的教程只实现一个简单的获取天气的功能,但是我们做的是天气机器人,希望实现一个报告天气的功能。一般的天气应用都会在一个特定时间给你推送天气通知,在频道机器人中,你可以通过主动消息来实现这个功能。
在 robot.py 中添加定时发送消息的函数,代码如下:
robot.py
ptyhonasync def send_weather_message_by_time(): """ 任务描述:每天推送一次普通天气消息(演示方便改为100s定时运行) """ # 获取天气数据 weather_dict = await get_weather("深圳") # 获取频道列表都取首个频道的首个子频道推送 user_api = qqbot.AsyncUserAPI(t_token, False) guilds = await user_api.me_guilds() guilds_id = guilds[0].id channel_api = qqbot.AsyncChannelAPI(t_token, False) channels = await channel_api.get_channels(guilds_id) channels_id = channels[0].id qqbot.logger.info("channelid %s" % channel_id) # 推送消息 weather = "当前天气是:" + weather_dict['result']['weather'] send = qqbot.MessageSendRequest(content=weather) msg_api = qqbot.AsyncMessageAPI(t_token, False) await msg_api.post_message(channels_id, send) # 如果需要每天都执行,加上下面两句 t = threading.Timer(100, await send_weather_message_by_time) t.start()
在****main**中添加执行send_weather_message_by_time()**的语句:
# 定时推送主动消息 send_weather_message_by_time()`
编写完毕,注意保存
我们希望能提供不同用户不同地方的天气,但是发太多的消息会影响其它的用户。针对这种情况,我们可以通过私信来实现。下面函数中,当我们@机器人hello时收到机器人的私信。
私信中我们不使用ark,而是使用Embed。Embed也是一种结构化消息,它比Ark简单
在 robot.py 添加发送Embed的函数如下:
robot.py
pythonasync def send_weather_embed_direct_message(weather_dict, guild_id, user_id):
"""
被动回复-私信推送天气内嵌消息
:param user_id: 用户ID
:param weather_dict: 天气数据字典
:param guild_id: 发送私信需要的源频道ID
"""
# 构造消息发送请求数据对象
embed = MessageEmbed()
embed.title = weather_dict['result']['citynm'] + " " + weather_dict['result']['weather']
embed.prompt = "天气消息推送"
# 构造内嵌消息缩略图
thumbnail = MessageEmbedThumbnail()
thumbnail.url = weather_dict['result']['weather_icon']
embed.thumbnail = thumbnail
# 构造内嵌消息fields
embed.fields = [MessageEmbedField(name="当日温度区间:" + weather_dict['result']['temperature']),
MessageEmbedField(name="当前温度:" + weather_dict['result']['temperature_curr']),
MessageEmbedField(name="最高温度:" + weather_dict['result']['temp_high']),
MessageEmbedField(name="最低温度:" + weather_dict['result']['temp_low']),
MessageEmbedField(name="当前湿度:" + weather_dict['result']['humidity'])]
# 通过api发送回复消息
send = qqbot.MessageSendRequest(embed=embed, content="")
dms_api = qqbot.AsyncDmsAPI(t_token, False)
direct_message_guild = await dms_api.create_direct_message(CreateDirectMessageRequest(guild_id, user_id))
await dms_api.post_direct_message(direct_message_guild.guild_id, send)
qqbot.logger.info("/私信推送天气内嵌消息 成功")
在_message_handler中调用刚刚添加的函数,使机器人是在私信里给你发送Embed
robot.py
elif "/私信天气" in content: # 通过空格区分城市参数 split = content.split("/私信天气 ") weather = await get_weather(split[1]) await send_weather_embed_direct_message(weather, message.guild_id, message.author.id)
编写完毕,注意保存
在终端命令行输入并执行下列命令,运行机器人
python3 /home/demo/robot.py
在频道中执行下列步骤验证效果:
当用户想要查看全国或者某个省份的天气情况,一次次@机器人就显得十分麻烦,这个时候你可以使用小程序来解决这个问题。了解具体的小程序开发可以看 QQ小程序开发文档,这里只介绍如何通过机器人打开小程序。
机器人打开小程序非常简单,只需要按照下面配置就可以了,不需要增加额外的代码:
配置好后,我们@机器人就可以看到我们设置的服务了,点击就可以打开设置的小程序
使用指令 每次@机器人输入指令太麻烦了,有没有简单的方式呢?机器人提供了指令配置,当你输入/时就会产出你配置的指令面板。
配置方式如下:
配置好后,当我们输入/时,就可以看到配置的面板了
完整代码可查看github: 天气机器人-Python实现版
python#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import asyncio
import json
import os.path
import time
from multiprocessing import Process
from typing import Dict, List
import aiohttp
import qqbot
import schedule
from qqbot.core.util.yaml_util import YamlUtil
from qqbot.model.message import MessageEmbed, MessageEmbedField, MessageEmbedThumbnail, CreateDirectMessageRequest, \
MessageArk, MessageArkKv, MessageArkObj, MessageArkObjKv
test_config = YamlUtil.read(os.path.join(os.path.dirname(__file__), "config.yaml"))
public_channel_id = ""
async def _message_handler(event, message: qqbot.Message):
"""
定义事件回调的处理
:param event: 事件类型
:param message: 事件对象(如监听消息是Message对象)
"""
msg_api = qqbot.AsyncMessageAPI(t_token, False)
# 打印返回信息
content = message.content
qqbot.logger.info("event %s" % event + ",receive message %s" % content)
# 根据指令触发不同的推送消息
if "/天气 " in content:
split = content.split("/天气 ")
weather = await get_weather(split[1])
await send_weather_ark_message(weather, message.channel_id, message.id)
elif "/私信天气 " in content:
split = content.split("/私信天气 ")
weather = await get_weather(split[1])
await send_weather_embed_direct_message(weather, message.guild_id, message.author.id)
if "/当前天气 " in content:
split = content.split("/当前天气 ")
weather = await get_weather(split[1])
await send_weather_ark_message(weather, message.channel_id, message.id)
elif "/未来天气 " in content:
split = content.split("/未来天气 ")
future_weather = await get_future_weather(split[1])
await send_future_weather_ark_message(future_weather, message.channel_id, message.id)
elif "/空气质量 " in content:
split = content.split("/空气质量 ")
aqi_dict = await get_aqi(split[1])
await send_aqi_ark_message(aqi_dict, message.channel_id, message.id)
elif "/穿衣指数 " in content:
split = content.split("/穿衣指数 ")
weather_life_dict = await get_weather_life_index(split[1])
await send_clothes_ark_message(weather_life_dict, message.channel_id, message.id)
elif "/紫外线指数 " in content:
split = content.split("/紫外线指数 ")
weather_life_dict = await get_weather_life_index(split[1].strip())
await send_uv_ark_message(weather_life_dict, message.channel_id, message.id)
async def _create_weather_ark_obj_list(weather_dict) -> List[MessageArkObj]:
obj_list = [MessageArkObj(obj_kv=[MessageArkObjKv(key="desc", value=weather_dict['result']['citynm'] + " " + weather_dict['result']['weather'])]),
MessageArkObj(obj_kv=[MessageArkObjKv(key="desc", value="当日温度区间:" + weather_dict['result']['temperature'])]),
MessageArkObj(obj_kv=[MessageArkObjKv(key="desc", value="当前温度:" + weather_dict['result']['temperature_curr'])]),
MessageArkObj(obj_kv=[MessageArkObjKv(key="desc", value="当前湿度:" + weather_dict['result']['humidity'])])]
return obj_list
async def _create_future_weather_ark_obj_list(weather_dict) -> List[MessageArkObj]:
obj_list = [MessageArkObj(obj_kv=[MessageArkObjKv(key="desc", value=weather_dict['result'][0]['citynm'] + "未来三天天气预报")]),
MessageArkObj(obj_kv=[MessageArkObjKv(key="desc", value="明天:" + weather_dict['result'][1]['weather'] + ", " + weather_dict['result'][1]['temperature'])]),
MessageArkObj(obj_kv=[MessageArkObjKv(key="desc", value="后天:" + weather_dict['result'][2]['weather'] + ", " + weather_dict['result'][2]['temperature'])]),
MessageArkObj(obj_kv=[MessageArkObjKv(key="desc", value="外后天:" + weather_dict['result'][3]['weather'] + ", " + weather_dict['result'][3]['temperature'])])]
return obj_list
async def _create_clothes_ark_obj_list(life_index_dic) -> List[MessageArkObj]:
obj_list = [MessageArkObj(obj_kv=[MessageArkObjKv(key="desc", value="城市:" + life_index_dic['result'][0]['citynm'])]),
MessageArkObj(obj_kv=[MessageArkObjKv(key="desc", value="体感:" + life_index_dic['result'][0]['lifeindex_ct_attr'])]),
MessageArkObj(obj_kv=[MessageArkObjKv(key="desc", value="建议:" + life_index_dic['result'][0]['lifeindex_ct_dese'])])]
return obj_list
async def _create_uv_ark_obj_list(life_index_dic) -> List[MessageArkObj]:
obj_list = [MessageArkObj(obj_kv=[MessageArkObjKv(key="desc", value="城市:" + life_index_dic['result'][0]['citynm'])]),
MessageArkObj(obj_kv=[MessageArkObjKv(key="desc", value="紫外线指数:" + life_index_dic['result'][0]['lifeindex_uv_attr'])]),
MessageArkObj(obj_kv=[MessageArkObjKv(key="desc", value="建议:" + life_index_dic['result'][0]['lifeindex_uv_dese'])])]
return obj_list
async def _create_aqi_ark_obj_list(aqi_dict) -> List[MessageArkObj]:
obj_list = [MessageArkObj(obj_kv=[MessageArkObjKv(key="desc", value="城市:" + aqi_dict['result']['citynm'])]),
MessageArkObj(obj_kv=[MessageArkObjKv(key="desc", value="空气质量:" + aqi_dict['result']['aqi_levnm'])]),
MessageArkObj(obj_kv=[MessageArkObjKv(key="desc", value="PM2.5:" + aqi_dict['result']['aqi_scope'])]),
MessageArkObj(obj_kv=[MessageArkObjKv(key="desc", value="建议:" + aqi_dict['result']['aqi_remark'])])]
return obj_list
async def send_weather_ark_message(weather_dict, channel_id, message_id):
"""
被动回复-子频道推送模版消息
:param channel_id: 回复消息的子频道ID
:param message_id: 回复消息ID
:param weather_dict:天气消息
"""
# 构造消息发送请求数据对象
ark = MessageArk()
# 模版ID=23
ark.template_id = 23
ark.kv = [MessageArkKv(key="#DESC#", value="描述"),
MessageArkKv(key="#PROMPT#", value="提示消息"),
MessageArkKv(key="#LIST#", obj=await _create_weather_ark_obj_list(weather_dict))]
# 通过api发送回复消息
send = qqbot.MessageSendRequest(content="", ark=ark, msg_id=message_id)
msg_api = qqbot.AsyncMessageAPI(t_token, False)
await msg_api.post_message(channel_id, send)
async def send_weather_embed_direct_message(weather_dict, guild_id, user_id):
"""
被动回复-私信推送天气内嵌消息
:param user_id: 用户ID
:param weather_dict: 天气数据字典
:param guild_id: 发送私信需要的源频道ID
"""
# 构造消息发送请求数据对象
embed = MessageEmbed()
embed.title = weather_dict['result']['citynm'] + " " + weather_dict['result']['weather']
embed.prompt = "天气消息推送"
# 构造内嵌消息缩略图
thumbnail = MessageEmbedThumbnail()
thumbnail.url = weather_dict['result']['weather_icon']
embed.thumbnail = thumbnail
# 构造内嵌消息fields
embed.fields = [MessageEmbedField(name="当日温度区间:" + weather_dict['result']['temperature']),
MessageEmbedField(name="当前温度:" + weather_dict['result']['temperature_curr']),
MessageEmbedField(name="最高温度:" + weather_dict['result']['temp_high']),
MessageEmbedField(name="最低温度:" + weather_dict['result']['temp_low']),
MessageEmbedField(name="当前湿度:" + weather_dict['result']['humidity'])]
# 通过api发送回复消息
send = qqbot.MessageSendRequest(embed=embed, content="")
dms_api = qqbot.AsyncDmsAPI(t_token, False)
direct_message_guild = await dms_api.create_direct_message(CreateDirectMessageRequest(guild_id, user_id))
await dms_api.post_direct_message(direct_message_guild.guild_id, send)
qqbot.logger.info("/私信推送天气内嵌消息 成功")
async def send_clothes_ark_message(life_index_dict, channel_id, message_id):
"""
被动回复-子频道推送穿衣指数
:param channel_id: 回复消息的子频道ID
:param message_id: 回复消息ID
:param life_index_dict:天气消息
"""
# 构造消息发送请求数据对象
ark = MessageArk()
# 模版ID=23
ark.template_id = 23
ark.kv = [MessageArkKv(key="#DESC#", value="描述"),
MessageArkKv(key="#PROMPT#", value="提示消息"),
MessageArkKv(key="#LIST#", obj=await _create_clothes_ark_obj_list(life_index_dict))]
# 通过api发送回复消息
send = qqbot.MessageSendRequest(content="", ark=ark, msg_id=message_id)
msg_api = qqbot.AsyncMessageAPI(t_token, False)
await msg_api.post_message(channel_id, send)
async def send_uv_ark_message(life_index_dict, channel_id, message_id):
"""
被动回复-子频道推送紫外线指数
:param channel_id: 回复消息的子频道ID
:param message_id: 回复消息ID
:param life_index_dict:天气消息
"""
# 构造消息发送请求数据对象
ark = MessageArk()
# 模版ID=23
ark.template_id = 23
ark.kv = [MessageArkKv(key="#DESC#", value="描述"),
MessageArkKv(key="#PROMPT#", value="提示消息"),
MessageArkKv(key="#LIST#", obj=await _create_uv_ark_obj_list(life_index_dict))]
# 通过api发送回复消息
send = qqbot.MessageSendRequest(content="", ark=ark, msg_id=message_id)
msg_api = qqbot.AsyncMessageAPI(t_token, False)
await msg_api.post_message(channel_id, send)
async def send_aqi_ark_message(aqi_dict, channel_id, message_id):
"""
被动回复-子频道推送 PM2.5 空气质量指数
:param channel_id: 回复消息的子频道ID
:param message_id: 回复消息ID
:param aqi_dict:空气质量数据
"""
# 构造消息发送请求数据对象
ark = MessageArk()
# 模版ID=23
ark.template_id = 23
ark.kv = [MessageArkKv(key="#DESC#", value="描述"),
MessageArkKv(key="#PROMPT#", value="提示消息"),
MessageArkKv(key="#LIST#", obj=await _create_aqi_ark_obj_list(aqi_dict))]
# 通过api发送回复消息
send = qqbot.MessageSendRequest(content="", ark=ark, msg_id=message_id)
msg_api = qqbot.AsyncMessageAPI(t_token, False)
await msg_api.post_message(channel_id, send)
async def send_future_weather_ark_message(future_weather_dict, channel_id, message_id):
"""
被动回复-子频道推送未来三天天气
:param channel_id: 回复消息的子频道ID
:param message_id: 回复消息ID
:param future_weather_dict:空气质量数据
"""
# 构造消息发送请求数据对象
ark = MessageArk()
# 模版ID=23
ark.template_id = 23
ark.kv = [MessageArkKv(key="#DESC#", value="描述"),
MessageArkKv(key="#PROMPT#", value="提示消息"),
MessageArkKv(key="#LIST#", obj=await _create_future_weather_ark_obj_list(future_weather_dict))]
# 通过api发送回复消息
send = qqbot.MessageSendRequest(content="", ark=ark, msg_id=message_id)
msg_api = qqbot.AsyncMessageAPI(t_token, False)
await msg_api.post_message(channel_id, send)
async def get_weather(city_name: str) -> Dict:
"""
获取天气信息
:return: 返回天气数据的json对象
返回示例
{
"success":"1",
"result":{
"weaid":"1",
"days":"2022-03-04",
"week":"星期五",
"cityno":"beijing",
"citynm":"北京",
"cityid":"101010100",
"temperature":"13℃/-1℃",
"temperature_curr":"10℃",
"humidity":"17%",
"aqi":"98",
"weather":"扬沙转晴",
"weather_curr":"扬沙",
"weather_icon":"http://api.k780.com/upload/weather/d/30.gif",
"weather_icon1":"",
"wind":"西北风",
"winp":"4级",
"temp_high":"13",
"temp_low":"-1",
"temp_curr":"10",
"humi_high":"0",
"humi_low":"0",
"weatid":"31",
"weatid1":"",
"windid":"7",
"winpid":"4",
"weather_iconid":"30"
}
}
"""
weather_api_url = "http://api.k780.com/?app=weather.today&cityNm=" + city_name + "&appkey=00000&sign=wdnmdzijiquhuaqianshenqing&format=json"
async with aiohttp.ClientSession() as session:
async with session.get(
url=weather_api_url,
timeout=5,
) as resp:
content = await resp.text()
content_json_obj = json.loads(content)
return content_json_obj
async def get_future_weather(city_name: str) -> Dict:
"""
获取未来几天的天气信息
:return: 返回天气数据的json对象
返回示例(返回值过长,部分省略)
{
"success": "1",
"result": [{
"weaid": "1",
"days": "2014-07-30",
"week": "星期三",
"cityno": "beijing",
"citynm": "北京",
"cityid": "101010100",
"temperature": "23℃/11℃", /*温度*/
"humidity": "0%/0%", /*湿度,后期气像局未提供,如有需要可使用weather.today接口 */
"weather": "多云转晴",
"weather_icon": "http://api.k780.com/upload/weather/d/1.gif", /*气象图标(白天) 全部气象图标下载*/
"weather_icon1": "http://api.k780.com/upload/weather/d/0.gif", /*气象图标(夜间) 全部气象图标下载*/
"wind": "微风", /*风向*/
"winp": "小于3级", /*风力*/
"temp_high": "31", /*最高温度*/
"temp_low": "24", /*最低温度*/
"humi_high": "0", /*湿度栏位已不再更新*/
"humi_low": "0",/*湿度栏位已不再更新*/
"weatid": "2", /*白天天气ID,可对照weather.wtype接口中weaid*/
"weatid1": "1", /*夜间天气ID,可对照weather.wtype接口中weaid*/
"windid": "1", /*风向ID(暂无对照表)*/
"winpid": "2" /*风力ID(暂无对照表)*/
"weather_iconid": "1", /*气象图标编号(白天),对应weather_icon 1.gif*/
"weather_iconid1": "0" /*气象图标编号(夜间),对应weather_icon1 0.gif*/
},
......
"""
weather_api_url = "http://api.k780.com/?app=weather.future&cityNm=" + city_name + "&appkey=00000&sign=nmsl&format=json"
async with aiohttp.ClientSession() as session:
async with session.get(
url=weather_api_url,
timeout=5,
) as resp:
content = await resp.text()
content_json_obj = json.loads(content)
return content_json_obj
async def get_weather_life_index(citi_name: str) -> Dict:
"""
获取生活指数
:return: 返回天气数据的json对象
返回示例
{
success: "1",
result: {
2017-04-17: {
weaid: "1",
days: "2017-04-17",
week_1: "星期一",
simcode: "beijing",
citynm: "北京",
cityid: "101010100",
lifeindex_uv_id: "101",
lifeindex_uv_typeno: "uv",
lifeindex_uv_typenm: "紫外线指数",
lifeindex_uv_attr: "弱",
lifeindex_uv_dese: "辐射较弱,涂擦SPF12-15、PA+护肤品。",
lifeindex_gm_id: "111",
lifeindex_gm_typeno: "gm",
lifeindex_gm_typenm: "感冒指数",
lifeindex_gm_attr: "少发",
lifeindex_gm_dese: "无明显降温,感冒机率较低。",
lifeindex_ct_id: "108",
lifeindex_ct_typeno: "ct",
lifeindex_ct_typenm: "穿衣指数",
lifeindex_ct_attr: "较舒适",
lifeindex_ct_dese: "建议穿薄外套或牛仔裤等服装。",
lifeindex_xc_id: "112",
lifeindex_xc_typeno: "xc",
lifeindex_xc_typenm: "洗车指数",
lifeindex_xc_attr: "较适宜",
lifeindex_xc_dese: "无雨且风力较小,易保持清洁度。",
lifeindex_yd_id: "114",
lifeindex_yd_typeno: "yd",
lifeindex_yd_typenm: "运动指数",
lifeindex_yd_attr: "较适宜",
lifeindex_yd_dese: "风力稍强,推荐您进行室内运动。",
lifeindex_kq_id: "109",
lifeindex_kq_typeno: "kq",
lifeindex_kq_typenm: "空气污染扩散指数",
lifeindex_kq_attr: "良",
lifeindex_kq_dese: "气象条件有利于空气污染物扩散。"
},
...
"""
weather_api_url = "http://api.k780.com/?app=weather.lifeindex&cityNm=" + citi_name + "&appkey=00000&sign=0nmsl&format=json"
async with aiohttp.ClientSession() as session:
async with session.get(
url=weather_api_url,
timeout=5
) as resp:
content = await resp.text()
content_json_obj = json.loads(content)
return content_json_obj
async def get_aqi(citi_name: str) -> Dict:
"""
获取空气质量(aqi)数据
:return: 返回空气质量数据的json对象
返回示例
{
success: "1",
result: {
"success": "1",
"result": {
"weaid": "180",
"cityno": "gdzhongshan",
"citynm": "中山",
"cityid": "101281701",
"aqi": "18",
"aqi_scope": "0-50",
"aqi_levid": "1",
"aqi_levnm": "优",
"aqi_remark": "参加户外活动呼吸清新空气"
}
"""
weather_api_url = "http://api.k780.com/?app=weather.pm25&cityNm=" + citi_name + "&appkey=0000&sign=nmsl&format=json"
async with aiohttp.ClientSession() as session:
async with session.get(
url=weather_api_url,
timeout=5
) as resp:
content = await resp.text()
content_json_obj = json.loads(content)
return content_json_obj
def set_schedule_task():
schedule.every(10).seconds.do(send_weather_message_by_time)
while True:
schedule.run_pending()
time.sleep(1)
def send_weather_message_by_time():
"""
任务描述:每天推送一次普通天气消息
"""
loop = asyncio.get_event_loop()
token = qqbot.Token(test_config["token"]["appid"], test_config["token"]["token"])
# 获取频道列表,取首个频道的首个子频道推送
global public_channel_id
if not public_channel_id:
user_api = qqbot.AsyncUserAPI(token, False)
guild_id = loop.run_until_complete(user_api.me_guilds())[0].id
channel_api = qqbot.AsyncChannelAPI(token, False)
public_channel_id = loop.run_until_complete(channel_api.get_channels(guild_id))[0].id
# 获取天气数据
weather_dict = loop.run_until_complete(get_weather("深圳"))
# 推送消息
content = "当日温度区间:" + weather_dict['result']['temperature']
send = qqbot.MessageSendRequest(content=content)
msg_api = qqbot.AsyncMessageAPI(token, False)
loop.run_until_complete(msg_api.post_message("2568610", send))
# async的异步接口的使用示例
if __name__ == "__main__":
# 定时推送主动消息
Process(target=set_schedule_task).start()
# @机器人后推送被动消息
t_token = qqbot.Token(test_config["token"]["appid"], test_config["token"]["token"])
qqbot_handler = qqbot.Handler(
qqbot.HandlerType.AT_MESSAGE_EVENT_HANDLER, _message_handler
)
qqbot.async_listen_events(t_token, False, qqbot_handler)