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main.py
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main.py
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import logging, os
import threading
import schedule
import random
import asyncio, aiohttp
import traceback
import copy
import json, re
from functools import partial
import http.cookies
from typing import *
from flask import Flask, send_from_directory, render_template, request, jsonify
from flask_cors import CORS
# 按键监听语音聊天板块
import keyboard
import pyaudio
import wave
import numpy as np
import speech_recognition as sr
from aip import AipSpeech
import signal
import time
from utils.common import Common
from utils.config import Config
from utils.logger import Configure_logger
from utils.my_handle import My_handle
"""
___ _
|_ _| | ____ _ _ __ ___ ___
| || |/ / _` | '__/ _ \/ __|
| || < (_| | | | (_) \__ \
|___|_|\_\__,_|_| \___/|___/
"""
config = None
common = None
my_handle = None
last_liveroom_data = None
last_username_list = None
# 空闲时间计数器
global_idle_time = 0
# 配置文件路径
config_path = "config.json"
# 点火起飞
def start_server():
global config, common, my_handle, last_username_list, config_path, last_liveroom_data
global do_listen_and_comment_thread, stop_do_listen_and_comment_thread_event
# 按键监听相关
do_listen_and_comment_thread = None
stop_do_listen_and_comment_thread_event = threading.Event()
# 冷却时间 0.5 秒
cooldown = 0.5
last_pressed = 0
# 获取 httpx 库的日志记录器
httpx_logger = logging.getLogger("httpx")
# 设置 httpx 日志记录器的级别为 WARNING
httpx_logger.setLevel(logging.WARNING)
# 最新的直播间数据
last_liveroom_data = {
'OnlineUserCount': 0,
'TotalUserCount': 0,
'TotalUserCountStr': '0',
'OnlineUserCountStr': '0',
'MsgId': 0,
'User': None,
'Content': '当前直播间人数 0,累计直播间人数 0',
'RoomId': 0
}
# 最新入场的用户名列表
last_username_list = [""]
my_handle = My_handle(config_path)
if my_handle is None:
logging.error("程序初始化失败!")
os._exit(0)
if platform != "wxlive":
# HTTP API线程
def http_api_thread():
app = Flask(__name__, static_folder='./')
CORS(app) # 允许跨域请求
@app.route('/send', methods=['POST'])
def send():
global my_handle, config
try:
try:
data_json = request.get_json()
logging.info(f"API收到数据:{data_json}")
if data_json["type"] == "reread":
my_handle.reread_handle(data_json)
elif data_json["type"] == "comment":
my_handle.process_data(data_json, "comment")
elif data_json["type"] == "tuning":
my_handle.tuning_handle(data_json)
return jsonify({"code": 200, "message": "发送数据成功!"})
except Exception as e:
logging.error(f"发送数据失败!{e}")
return jsonify({"code": -1, "message": f"发送数据失败!{e}"})
except Exception as e:
return jsonify({"code": -1, "message": f"发送数据失败!{e}"})
app.run(host=config.get("api_ip"), port=config.get("api_port"), debug=False)
# HTTP API线程并启动
schedule_thread = threading.Thread(target=http_api_thread)
schedule_thread.start()
# 添加用户名到最新的用户名列表
def add_username_to_last_username_list(data):
global last_username_list
# 添加数据到 最新入场的用户名列表
last_username_list.append(data)
# 保留最新的3个数据
last_username_list = last_username_list[-3:]
"""
按键监听板块
"""
# 录音功能(录音时间过短进入openai的语音转文字会报错,请一定注意)
def record_audio():
pressdown_num = 0
CHUNK = 1024
FORMAT = pyaudio.paInt16
CHANNELS = 1
RATE = 44100
WAVE_OUTPUT_FILENAME = "out/record.wav"
p = pyaudio.PyAudio()
stream = p.open(format=FORMAT,
channels=CHANNELS,
rate=RATE,
input=True,
frames_per_buffer=CHUNK)
frames = []
print("Recording...")
flag = 0
while 1:
while keyboard.is_pressed('RIGHT_SHIFT'):
flag = 1
data = stream.read(CHUNK)
frames.append(data)
pressdown_num = pressdown_num + 1
if flag:
break
print("Stopped recording.")
stream.stop_stream()
stream.close()
p.terminate()
wf = wave.open(WAVE_OUTPUT_FILENAME, 'wb')
wf.setnchannels(CHANNELS)
wf.setsampwidth(p.get_sample_size(FORMAT))
wf.setframerate(RATE)
wf.writeframes(b''.join(frames))
wf.close()
if pressdown_num >= 5: # 粗糙的处理手段
return 1
else:
print("杂鱼杂鱼,好短好短(录音时间过短,按右shift重新录制)")
return 0
# THRESHOLD 设置音量阈值,默认值800.0,根据实际情况调整 silence_threshold 设置沉默阈值,根据实际情况调整
def audio_listen(volume_threshold=800.0, silence_threshold=15):
audio = pyaudio.PyAudio()
# 设置音频参数
FORMAT = pyaudio.paInt16
CHANNELS = 1
RATE = 16000
CHUNK = 1024
stream = audio.open(
format=FORMAT,
channels=CHANNELS,
rate=RATE,
input=True,
frames_per_buffer=CHUNK,
input_device_index=int(config.get("talk", "device_index"))
)
frames = [] # 存储录制的音频帧
is_speaking = False # 是否在说话
silent_count = 0 # 沉默计数
speaking_flag = False #录入标志位 不重要
while True:
# 播放中不录音
if config.get("talk", "no_recording_during_playback"):
# 存在待合成音频 或 已合成音频还未播放 或 播放中 或 在数据处理中
if my_handle.is_audio_queue_empty() != 15 or my_handle.is_handle_empty() == 1:
time.sleep(float(config.get("talk", "no_recording_during_playback_sleep_interval")))
continue
# 读取音频数据
data = stream.read(CHUNK)
audio_data = np.frombuffer(data, dtype=np.short)
max_dB = np.max(audio_data)
# print(max_dB)
if max_dB > volume_threshold:
is_speaking = True
silent_count = 0
elif is_speaking is True:
silent_count += 1
if is_speaking is True:
frames.append(data)
if speaking_flag is False:
logging.info("[录入中……]")
speaking_flag = True
if silent_count >= silence_threshold:
break
logging.info("[语音录入完成]")
# 将音频保存为WAV文件
'''with wave.open(WAVE_OUTPUT_FILENAME, 'wb') as wf:
wf.setnchannels(CHANNELS)
wf.setsampwidth(pyaudio.get_sample_size(FORMAT))
wf.setframerate(RATE)
wf.writeframes(b''.join(frames))'''
return frames
# 执行录音、识别&提交
def do_listen_and_comment(status=True):
global stop_do_listen_and_comment_thread_event
config = Config(config_path)
# 是否启用按键监听,不启用的话就不用执行了
if False == config.get("talk", "key_listener_enable"):
return
while True:
try:
# 检查是否收到停止事件
if stop_do_listen_and_comment_thread_event.is_set():
logging.info(f'停止录音~')
break
config = Config(config_path)
# 根据接入的语音识别类型执行
if "baidu" == config.get("talk", "type"):
# 设置音频参数
FORMAT = pyaudio.paInt16
CHANNELS = config.get("talk", "CHANNELS")
RATE = config.get("talk", "RATE")
audio_out_path = config.get("play_audio", "out_path")
if not os.path.isabs(audio_out_path):
if not audio_out_path.startswith('./'):
audio_out_path = './' + audio_out_path
file_name = 'baidu_' + common.get_bj_time(4) + '.wav'
WAVE_OUTPUT_FILENAME = common.get_new_audio_path(audio_out_path, file_name)
# WAVE_OUTPUT_FILENAME = './out/baidu_' + common.get_bj_time(4) + '.wav'
frames = audio_listen(config.get("talk", "volume_threshold"), config.get("talk", "silence_threshold"))
# 将音频保存为WAV文件
with wave.open(WAVE_OUTPUT_FILENAME, 'wb') as wf:
wf.setnchannels(CHANNELS)
wf.setsampwidth(pyaudio.get_sample_size(FORMAT))
wf.setframerate(RATE)
wf.writeframes(b''.join(frames))
# 读取音频文件
with open(WAVE_OUTPUT_FILENAME, 'rb') as fp:
audio = fp.read()
# 初始化 AipSpeech 对象
baidu_client = AipSpeech(config.get("talk", "baidu", "app_id"), config.get("talk", "baidu", "api_key"), config.get("talk", "baidu", "secret_key"))
# 识别音频文件
res = baidu_client.asr(audio, 'wav', 16000, {
'dev_pid': 1536,
})
if res['err_no'] == 0:
content = res['result'][0]
# 输出识别结果
logging.info("识别结果:" + content)
username = config.get("talk", "username")
data = {
"platform": "本地聊天",
"username": username,
"content": content
}
my_handle.process_data(data, "talk")
else:
logging.error(f"百度接口报错:{res}")
elif "google" == config.get("talk", "type"):
# 创建Recognizer对象
r = sr.Recognizer()
try:
# 打开麦克风进行录音
with sr.Microphone() as source:
logging.info(f'录音中...')
# 从麦克风获取音频数据
audio = r.listen(source)
logging.info("成功录制")
# 进行谷歌实时语音识别 en-US zh-CN ja-JP
content = r.recognize_google(audio, language=config.get("talk", "google", "tgt_lang"))
# 输出识别结果
# logging.info("识别结果:" + content)
username = config.get("talk", "username")
data = {
"platform": "本地聊天",
"username": username,
"content": content
}
my_handle.process_data(data, "talk")
except sr.UnknownValueError:
logging.warning("无法识别输入的语音")
except sr.RequestError as e:
logging.error("请求出错:" + str(e))
elif "faster_whisper" == config.get("talk", "type"):
from faster_whisper import WhisperModel
# 设置音频参数
FORMAT = pyaudio.paInt16
CHANNELS = config.get("talk", "CHANNELS")
RATE = config.get("talk", "RATE")
audio_out_path = config.get("play_audio", "out_path")
if not os.path.isabs(audio_out_path):
if not audio_out_path.startswith('./'):
audio_out_path = './' + audio_out_path
file_name = 'faster_whisper_' + common.get_bj_time(4) + '.wav'
WAVE_OUTPUT_FILENAME = common.get_new_audio_path(audio_out_path, file_name)
# WAVE_OUTPUT_FILENAME = './out/faster_whisper_' + common.get_bj_time(4) + '.wav'
frames = audio_listen(config.get("talk", "volume_threshold"), config.get("talk", "silence_threshold"))
# 将音频保存为WAV文件
with wave.open(WAVE_OUTPUT_FILENAME, 'wb') as wf:
wf.setnchannels(CHANNELS)
wf.setsampwidth(pyaudio.get_sample_size(FORMAT))
wf.setframerate(RATE)
wf.writeframes(b''.join(frames))
# Run on GPU with FP16
model = WhisperModel(model_size_or_path=config.get("talk", "faster_whisper", "model_size"), \
device=config.get("talk", "faster_whisper", "device"), \
compute_type=config.get("talk", "faster_whisper", "compute_type"), \
download_root=config.get("talk", "faster_whisper", "download_root"))
segments, info = model.transcribe(WAVE_OUTPUT_FILENAME, beam_size=config.get("talk", "faster_whisper", "beam_size"))
logging.debug("识别语言为:'%s',概率:%f" % (info.language, info.language_probability))
content = ""
for segment in segments:
logging.info("[%.2fs -> %.2fs] %s" % (segment.start, segment.end, segment.text))
content += segment.text + "。"
if content == "":
return
# 输出识别结果
logging.info("识别结果:" + content)
username = config.get("talk", "username")
data = {
"platform": "本地聊天",
"username": username,
"content": content
}
my_handle.process_data(data, "talk")
if not status:
return
except Exception as e:
logging.error(traceback.format_exc())
def on_key_press(event):
global do_listen_and_comment_thread, stop_do_listen_and_comment_thread_event
# 是否启用按键监听,不启用的话就不用执行了
if False == config.get("talk", "key_listener_enable"):
return
# if event.name in ['z', 'Z', 'c', 'C'] and keyboard.is_pressed('ctrl'):
# print("退出程序")
# os._exit(0)
# 按键CD
current_time = time.time()
if current_time - last_pressed < cooldown:
return
"""
触发按键部分的判断
"""
trigger_key_lower = None
stop_trigger_key_lower = None
# trigger_key是字母, 整个小写
if trigger_key.isalpha():
trigger_key_lower = trigger_key.lower()
# stop_trigger_key是字母, 整个小写
if stop_trigger_key.isalpha():
stop_trigger_key_lower = stop_trigger_key.lower()
if trigger_key_lower:
if event.name == trigger_key or event.name == trigger_key_lower:
logging.info(f'检测到单击键盘 {event.name},即将开始录音~')
elif event.name == stop_trigger_key or event.name == stop_trigger_key_lower:
logging.info(f'检测到单击键盘 {event.name},即将停止录音~')
stop_do_listen_and_comment_thread_event.set()
return
else:
return
else:
if event.name == trigger_key:
logging.info(f'检测到单击键盘 {event.name},即将开始录音~')
elif event.name == stop_trigger_key:
logging.info(f'检测到单击键盘 {event.name},即将停止录音~')
stop_do_listen_and_comment_thread_event.set()
return
else:
return
# 是否启用连续对话模式
if config.get("talk", "continuous_talk"):
stop_do_listen_and_comment_thread_event.clear()
do_listen_and_comment_thread = threading.Thread(target=do_listen_and_comment, args=(True,))
do_listen_and_comment_thread.start()
else:
stop_do_listen_and_comment_thread_event.clear()
do_listen_and_comment_thread = threading.Thread(target=do_listen_and_comment, args=(False,))
do_listen_and_comment_thread.start()
# 按键监听
def key_listener():
# 注册按键按下事件的回调函数
keyboard.on_press(on_key_press)
try:
# 进入监听状态,等待按键按下
keyboard.wait()
except KeyboardInterrupt:
os._exit(0)
# 从配置文件中读取触发键的字符串配置
trigger_key = config.get("talk", "trigger_key")
stop_trigger_key = config.get("talk", "stop_trigger_key")
if config.get("talk", "key_listener_enable"):
logging.info(f'单击键盘 {trigger_key} 按键进行录音喵~ 由于其他任务还要启动,如果按键没有反应,请等待一段时间')
# 创建并启动按键监听线程
thread = threading.Thread(target=key_listener)
thread.start()
# 定时任务
def schedule_task(index):
global config, common, my_handle, last_liveroom_data, last_username_list
logging.debug("定时任务执行中...")
hour, min = common.get_bj_time(6)
if 0 <= hour and hour < 6:
time = f"凌晨{hour}点{min}分"
elif 6 <= hour and hour < 9:
time = f"早晨{hour}点{min}分"
elif 9 <= hour and hour < 12:
time = f"上午{hour}点{min}分"
elif hour == 12:
time = f"中午{hour}点{min}分"
elif 13 <= hour and hour < 18:
time = f"下午{hour - 12}点{min}分"
elif 18 <= hour and hour < 20:
time = f"傍晚{hour - 12}点{min}分"
elif 20 <= hour and hour < 24:
time = f"晚上{hour - 12}点{min}分"
# 根据对应索引从列表中随机获取一个值
random_copy = random.choice(config.get("schedule")[index]["copy"])
# 假设有多个未知变量,用户可以在此处定义动态变量
variables = {
'time': time,
'user_num': "N",
'last_username': last_username_list[-1],
}
# 有用户数据情况的平台特殊处理
if platform in ["dy", "tiktok"]:
variables['user_num'] = last_liveroom_data["OnlineUserCount"]
# 使用字典进行字符串替换
if any(var in random_copy for var in variables):
content = random_copy.format(**{var: value for var, value in variables.items() if var in random_copy})
else:
content = random_copy
data = {
"platform": platform,
"username": None,
"content": content
}
logging.info(f"定时任务:{content}")
my_handle.process_data(data, "schedule")
# 启动定时任务
def run_schedule():
global config
try:
for index, task in enumerate(config.get("schedule")):
if task["enable"]:
# logging.info(task)
# 设置定时任务,每隔n秒执行一次
schedule.every(task["time"]).seconds.do(partial(schedule_task, index))
except Exception as e:
logging.error(traceback.format_exc())
while True:
schedule.run_pending()
# time.sleep(1) # 控制每次循环的间隔时间,避免过多占用 CPU 资源
if any(item['enable'] for item in config.get("schedule")):
# 创建定时任务子线程并启动
schedule_thread = threading.Thread(target=run_schedule)
schedule_thread.start()
# 启动动态文案
async def run_trends_copywriting():
global config
try:
if False == config.get("trends_copywriting", "enable"):
return
logging.info(f"动态文案任务线程运行中...")
while True:
# 文案文件路径列表
copywriting_file_path_list = []
# 获取动态文案列表
for copywriting in config.get("trends_copywriting", "copywriting"):
# 获取文件夹内所有文件的文件绝对路径,包括文件扩展名
for tmp in common.get_all_file_paths(copywriting["folder_path"]):
copywriting_file_path_list.append(tmp)
# 是否开启随机播放
if config.get("trends_copywriting", "random_play"):
random.shuffle(copywriting_file_path_list)
logging.debug(f"copywriting_file_path_list={copywriting_file_path_list}")
# 遍历文案文件路径列表
for copywriting_file_path in copywriting_file_path_list:
# 获取文案文件内容
copywriting_file_content = common.read_file_return_content(copywriting_file_path)
# 是否启用提示词对文案内容进行转换
if copywriting["prompt_change_enable"]:
data_json = {
"username": "trends_copywriting",
"content": copywriting["prompt_change_content"] + copywriting_file_content
}
# 调用函数进行LLM处理,以及生成回复内容,进行音频合成,需要好好考虑考虑实现
data_json["content"] = my_handle.llm_handle(config.get("trends_copywriting", "llm_type"), data_json)
else:
data_json = {
"username": "trends_copywriting",
"content": copywriting_file_content
}
logging.debug(f'copywriting_file_content={copywriting_file_content},content={data_json["content"]}')
# 空数据判断
if data_json["content"] != None and data_json["content"] != "":
# 发给直接复读进行处理
my_handle.reread_handle(data_json, filter=True)
await asyncio.sleep(config.get("trends_copywriting", "play_interval"))
except Exception as e:
logging.error(traceback.format_exc())
if config.get("trends_copywriting", "enable"):
# 创建动态文案子线程并启动
threading.Thread(target=lambda: asyncio.run(run_trends_copywriting())).start()
# 闲时任务
async def idle_time_task():
global config, global_idle_time
try:
if False == config.get("idle_time_task", "enable"):
return
logging.info(f"闲时任务线程运行中...")
# 记录上一次触发的任务类型
last_mode = 0
comment_copy_list = None
local_audio_path_list = None
overflow_time = int(config.get("idle_time_task", "idle_time"))
# 是否开启了随机闲时时间
if config.get("idle_time_task", "random_time"):
overflow_time = random.randint(0, overflow_time)
logging.info(f"闲时时间={overflow_time}秒")
def load_data_list(type):
if type == "comment":
tmp = config.get("idle_time_task", "comment", "copy")
elif type == "local_audio":
tmp = config.get("idle_time_task", "local_audio", "path")
tmp2 = copy.copy(tmp)
return tmp2
comment_copy_list = load_data_list("comment")
local_audio_path_list = load_data_list("local_audio")
logging.debug(f"comment_copy_list={comment_copy_list}")
logging.debug(f"local_audio_path_list={local_audio_path_list}")
while True:
# 每隔一秒的睡眠进行闲时计数
await asyncio.sleep(1)
global_idle_time = global_idle_time + 1
# 闲时计数达到指定值,进行闲时任务处理
if global_idle_time >= overflow_time:
# 闲时计数清零
global_idle_time = 0
# 闲时任务处理
if config.get("idle_time_task", "comment", "enable"):
if last_mode == 0 or not config.get("idle_time_task", "local_audio", "enable"):
# 是否开启了随机触发
if config.get("idle_time_task", "comment", "random"):
logging.debug("切换到文案触发模式")
if comment_copy_list != []:
# 随机打乱列表中的元素
random.shuffle(comment_copy_list)
comment_copy = comment_copy_list.pop(0)
else:
# 刷新list数据
comment_copy_list = load_data_list("comment")
# 随机打乱列表中的元素
random.shuffle(comment_copy_list)
comment_copy = comment_copy_list.pop(0)
else:
if comment_copy_list != []:
comment_copy = comment_copy_list.pop(0)
else:
# 刷新list数据
comment_copy_list = load_data_list("comment")
comment_copy = comment_copy_list.pop(0)
# 发送给处理函数
data = {
"platform": platform,
"username": "闲时任务",
"type": "comment",
"content": comment_copy
}
my_handle.process_data(data, "idle_time_task")
# 模式切换
last_mode = 1
overflow_time = int(config.get("idle_time_task", "idle_time"))
# 是否开启了随机闲时时间
if config.get("idle_time_task", "random_time"):
overflow_time = random.randint(0, overflow_time)
logging.info(f"闲时时间={overflow_time}秒")
continue
if config.get("idle_time_task", "local_audio", "enable"):
if last_mode == 1 or (not config.get("idle_time_task", "comment", "enable")):
logging.debug("切换到本地音频模式")
# 是否开启了随机触发
if config.get("idle_time_task", "local_audio", "random"):
if local_audio_path_list != []:
# 随机打乱列表中的元素
random.shuffle(local_audio_path_list)
local_audio_path = local_audio_path_list.pop(0)
else:
# 刷新list数据
local_audio_path_list = load_data_list("local_audio")
# 随机打乱列表中的元素
random.shuffle(local_audio_path_list)
local_audio_path = local_audio_path_list.pop(0)
else:
if local_audio_path_list != []:
local_audio_path = local_audio_path_list.pop(0)
else:
# 刷新list数据
local_audio_path_list = load_data_list("local_audio")
local_audio_path = local_audio_path_list.pop(0)
logging.debug(f"local_audio_path={local_audio_path}")
# 发送给处理函数
data = {
"platform": platform,
"username": "闲时任务",
"type": "local_audio",
"content": common.extract_filename(local_audio_path, False),
"file_path": local_audio_path
}
my_handle.process_data(data, "idle_time_task")
# 模式切换
last_mode = 0
overflow_time = int(config.get("idle_time_task", "idle_time"))
# 是否开启了随机闲时时间
if config.get("idle_time_task", "random_time"):
overflow_time = random.randint(0, overflow_time)
logging.info(f"闲时时间={overflow_time}秒")
continue
except Exception as e:
logging.error(traceback.format_exc())
if config.get("idle_time_task", "enable"):
# 创建闲时任务子线程并启动
threading.Thread(target=lambda: asyncio.run(idle_time_task())).start()
# 图像识别 定时任务
def image_recognition_schedule_task():
global config, common, my_handle
logging.debug("图像识别 定时任务执行中...")
data = {
"platform": platform,
"username": None,
"content": ""
}
logging.info(f"图像识别定时任务触发")
my_handle.process_data(data, "image_recognition_schedule")
# 启动图像识别 定时任务
def run_image_recognition_schedule():
global config
try:
schedule.every(config.get("image_recognition", "loop_screenshot_delay")).seconds.do(partial(image_recognition_schedule_task))
except Exception as e:
logging.error(traceback.format_exc())
while True:
schedule.run_pending()
# time.sleep(1) # 控制每次循环的间隔时间,避免过多占用 CPU 资源
if config.get("image_recognition", "loop_screenshot_enable"):
# 创建定时任务子线程并启动
image_recognition_schedule_thread = threading.Thread(target=run_image_recognition_schedule)
image_recognition_schedule_thread.start()
logging.info(f"当前平台:{platform}")
if platform == "bilibili":
from bilibili_api import Credential, live, sync, login
try:
if config.get("bilibili", "login_type") == "cookie":
logging.info("b站登录后F12抓网络包获取cookie,强烈建议使用小号!有封号风险")
logging.info("b站登录后,F12控制台,输入 window.localStorage.ac_time_value 回车获取(如果没有,请重新登录)")
bilibili_cookie = config.get("bilibili", "cookie")
bilibili_ac_time_value = config.get("bilibili", "ac_time_value")
if bilibili_ac_time_value == "":
bilibili_ac_time_value = None
# print(f'SESSDATA={common.parse_cookie_data(bilibili_cookie, "SESSDATA")}')
# print(f'bili_jct={common.parse_cookie_data(bilibili_cookie, "bili_jct")}')
# print(f'buvid3={common.parse_cookie_data(bilibili_cookie, "buvid3")}')
# print(f'DedeUserID={common.parse_cookie_data(bilibili_cookie, "DedeUserID")}')
# 生成一个 Credential 对象
credential = Credential(
sessdata=common.parse_cookie_data(bilibili_cookie, "SESSDATA"),
bili_jct=common.parse_cookie_data(bilibili_cookie, "bili_jct"),
buvid3=common.parse_cookie_data(bilibili_cookie, "buvid3"),
dedeuserid=common.parse_cookie_data(bilibili_cookie, "DedeUserID"),
ac_time_value=bilibili_ac_time_value
)
elif config.get("bilibili", "login_type") == "手机扫码":
credential = login.login_with_qrcode()
elif config.get("bilibili", "login_type") == "手机扫码-终端":
credential = login.login_with_qrcode_term()
elif config.get("bilibili", "login_type") == "账号密码登录":
bilibili_username = config.get("bilibili", "username")
bilibili_password = config.get("bilibili", "password")
credential = login.login_with_password(bilibili_username, bilibili_password)
elif config.get("bilibili", "login_type") == "不登录":
credential = None
else:
credential = login.login_with_qrcode()
# 初始化 Bilibili 直播间
room = live.LiveDanmaku(my_handle.get_room_id(), credential=credential)
except Exception as e:
logging.error(traceback.format_exc())
my_handle.abnormal_alarm_handle("platform")
# os._exit(0)
"""
DANMU_MSG: 用户发送弹幕
SEND_GIFT: 礼物
COMBO_SEND:礼物连击
GUARD_BUY:续费大航海
SUPER_CHAT_MESSAGE:醒目留言(SC)
SUPER_CHAT_MESSAGE_JPN:醒目留言(带日语翻译?)
WELCOME: 老爷进入房间
WELCOME_GUARD: 房管进入房间
NOTICE_MSG: 系统通知(全频道广播之类的)
PREPARING: 直播准备中
LIVE: 直播开始
ROOM_REAL_TIME_MESSAGE_UPDATE: 粉丝数等更新
ENTRY_EFFECT: 进场特效
ROOM_RANK: 房间排名更新
INTERACT_WORD: 用户进入直播间
ACTIVITY_BANNER_UPDATE_V2: 好像是房间名旁边那个xx小时榜
本模块自定义事件:
VIEW: 直播间人气更新
ALL: 所有事件
DISCONNECT: 断开连接(传入连接状态码参数)
TIMEOUT: 心跳响应超时
VERIFICATION_SUCCESSFUL: 认证成功
"""
@room.on('DANMU_MSG')
async def _(event):
"""
处理直播间弹幕事件
:param event: 弹幕事件数据
"""
global global_idle_time
# 闲时计数清零
global_idle_time = 0
content = event["data"]["info"][1] # 获取弹幕内容
username = event["data"]["info"][2][1] # 获取发送弹幕的用户昵称
logging.info(f"[{username}]: {content}")
data = {
"platform": platform,
"username": username,
"content": content
}
my_handle.process_data(data, "comment")
@room.on('COMBO_SEND')
async def _(event):
"""
处理直播间礼物连击事件
:param event: 礼物连击事件数据
"""
gift_name = event["data"]["data"]["gift_name"]
username = event["data"]["data"]["uname"]
# 礼物数量
combo_num = event["data"]["data"]["combo_num"]
# 总金额
combo_total_coin = event["data"]["data"]["combo_total_coin"]
logging.info(f"用户:{username} 赠送 {combo_num} 个 {gift_name},总计 {combo_total_coin}电池")
data = {
"platform": platform,
"gift_name": gift_name,
"username": username,
"num": combo_num,
"unit_price": combo_total_coin / combo_num / 1000,
"total_price": combo_total_coin / 1000
}
my_handle.process_data(data, "gift")
@room.on('SEND_GIFT')
async def _(event):
"""
处理直播间礼物事件
:param event: 礼物事件数据
"""
# print(event)
gift_name = event["data"]["data"]["giftName"]
username = event["data"]["data"]["uname"]
# 礼物数量
num = event["data"]["data"]["num"]
# 总金额
combo_total_coin = event["data"]["data"]["combo_total_coin"]
# 单个礼物金额
discount_price = event["data"]["data"]["discount_price"]
logging.info(f"用户:{username} 赠送 {num} 个 {gift_name},单价 {discount_price}电池,总计 {combo_total_coin}电池")
data = {
"platform": platform,
"gift_name": gift_name,
"username": username,
"num": num,
"unit_price": discount_price / 1000,
"total_price": combo_total_coin / 1000
}
my_handle.process_data(data, "gift")
@room.on('GUARD_BUY')
async def _(event):
"""
处理直播间续费大航海事件
:param event: 续费大航海事件数据
"""
logging.info(event)
@room.on('SUPER_CHAT_MESSAGE')
async def _(event):
"""
处理直播间醒目留言(SC)事件
:param event: 醒目留言(SC)事件数据
"""
message = event["data"]["data"]["message"]
uname = event["data"]["data"]["user_info"]["uname"]
price = event["data"]["data"]["price"]
logging.info(f"用户:{uname} 发送 {price}元 SC:{message}")
data = {
"platform": platform,
"gift_name": "SC",
"username": uname,