在这个示例中,我们将创建一个线程来执行一个时间较长的任务,并使用threading将任务放入后台执行。 importthreadingimporttime# 定义一个任务类classBackgroundTask(threading.Thread):def__init__(self,name):super().__init__()self.name=namedefrun(self):print(f"
Note that the interactive interpreter employs behavior that will yield different results, so you should run the following code from a file: Python from sys import getrefcount print("--- Before assignment ---") print(f"References to value_1: {getrefcount('value_1')}") print(f"References...
background_proc = threading.Thread(target=run_or_daemon, name='background_process') no_background_proc = threading.Thread(target=run_or_daemon, name='no_background_process') background_proc.daemon =True# no_background_proc.daemon = Falseno_background_proc.start() background_proc.start()#...
以下是一个使用threading模块的示例,其中一个线程会更新GUI界面上的标签内容: import tkinter as tkimport threadingimport timedef update_label():for i in range(100):label.config(text=f"Count: {i}")time.sleep(1)root = tk.Tk()label = tk.Label(root, text="Count: 0")label.pack()thread = t...
import timeimport threadingclass DataFetcher(threading.Thread): def run(self): while True: # 从数据源获取数据 time.sleep(update_interval)class DataAnalyzer(threading.Thread): def run(self): while True: # 分析已获取的数据 time.sleep(update_interval)class DisplayUpdater(thre...
def background_thread(): while True: socketio.sleep(5) t = random.randint(1, 100) socketio.emit('server_response', {'data': t}, namespace='/test_conn') if __name__ == '__main__': socketio.run(app, debug=True) 1.
start() for t in thread] [t.join() for t in thread] 七、谷歌翻译 - googletrans 自动语言检测,批量翻译,语言检测等 代码语言:python 代码运行次数:1 运行 AI代码解释 from googletrans import Translator translator = Translator() # 未提供源语言以及翻译的最终语言,会自动翻译成英文 translator.translate(...
pygame.draw.rect(screen, self._color, [self._x, self._y,80, 40], 0)defmain():classBackgroundThread(Thread):defrun(self): nonlocal screen is_go_on=Truewhileis_go_on: screen.fill(Color.GRAY) pygame.draw.line(screen, Color.BLACK, (130, 0), (130, 600), 4) ...
https://github.com/VivekPa/AlphaAI.git cd AlphaAI pip install -r requirements.txt python run....
self.action_images=random.choice(self.pet_images)self.action_max_len=len(self.action_images)self.action_pointer=0self.runFrame()defrunFrame(self):ifself.action_pointer==self.action_max_len:self.is_running_action=False self.action_pointer=0self.action_max_len=0self.setImage(self.action_images...