283 lines
7.5 KiB
Markdown
283 lines
7.5 KiB
Markdown
# 多工
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### 用到多工場合:
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* 同時間須顯示許多資料
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* 讀取model和AI運算
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* 需要長時間掛在背景執行
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### 線程/進程 差異
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* 多線程(Thread)
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簡單講:一個人有2隻手，然後可以同時進行
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* 多進程(Process)
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簡單講:聯合其他人一起做
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##
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## 多線程
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### 正常使用
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#### 2個線程幾乎同時啟動
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```python
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import threading
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from queue import Queue #Thread 無法回傳值，所以要使用 Queue.put() 將要傳回的值存入 Queue，再用 Queue.get() 取出
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import time
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import os
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# A報數
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def A_Count_off():
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for i in range(0,5):
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print(f'A : {i}')
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time.sleep(0.5)
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# B報數
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def B_Count_off():
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for i in range(5,10):
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print(f'B : {i}')
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time.sleep(0.5)
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thread_list=[A_Count_off,B_Count_off]
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thread_num =[]
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for i in range(0,len(thread_list)):
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thread_num.append(threading.Thread(target=thread_list[i]))
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for i in range(0,len(thread_num)):
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thread_num[i].join()
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```
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### 非正常使用
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#### 第2個線程要等到第1個線程運行完才會啟動
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##### 失去多線程意義
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```python
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# A報數
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def A_Count_off():
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for i in range(0,5):
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print(f'A : {i}')
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time.sleep(0.5)
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# B報數
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def B_Count_off():
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for i in range(5,10):
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print(f'B : {i}')
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time.sleep(0.5)
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thread_list=[A_Count_off,B_Count_off]
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thread_num =[]
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for i in range(0,len(thread_num)):
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thread_num[i].start()
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thread_num[i].join()
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```
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### 攜帶參數
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```python
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def Count_off(code_name):
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print('process {} '.format(os.getpid()))
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print('thread {} '.format(threading.current_thread().name))
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for i in range(0,5):
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print(f'{code_name} : {i}')
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time.sleep(0.5)
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thread_name_list=["A","B","C","D"]
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thread_list=[]
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for i in range(0,len(thread_name_list)):
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thread_list.append(threading.Thread(target=Count_off,args=thread_name_list[i])) # 攜帶參數
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for i in range(0,len(thread_list)):
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thread_list[i].start()
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for i in range(0,len(thread_list)):
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thread_list[i].join()
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```
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### 使用class的方式(推薦使用)
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#### 後續觀看程式碼及維護，會提高不少
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* start會使用分出去的線程
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* run會使用主線程
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```python
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class Thread_class(threading.Thread):
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def __init__(self,code_name):
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threading.Thread.__init__(self)
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self.code_name = code_name
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def run(self):
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print('process {} '.format(os.getpid())) # 查看進程
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print('thread {} '.format(threading.current_thread().name)) # 查看線程
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for i in range(0,5):
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print(f'{self.code_name} : {i}')
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time.sleep(0.5)
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def test_return(self):
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return(f'{self.code_name}=END')
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thread_name_list=["A","B","C","D"]
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thread_list=[]
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for i in range(0,len(thread_name_list)):
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thread_list.append(Thread_class(thread_name_list[i]))
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for i in range(0,len(thread_list)):
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thread_list[i].start() # 啟動額外線程
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for i in range(0,len(thread_list)):
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thread_list[i].join()
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```
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```python
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class Thread_class(threading.Thread):
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def __init__(self,code_name):
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threading.Thread.__init__(self)
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self.code_name = code_name
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def run(self):
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print('process {} '.format(os.getpid())) # 查看進程
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print('thread {} '.format(threading.current_thread().name)) # 查看線程
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for i in range(0,5):
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print(f'{self.code_name} : {i}')
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time.sleep(0.5)
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def test_return(self):
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return(f'{self.code_name}=END')
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thread_name_list=["A","B","C","D"]
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thread_list=[]
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for i in range(0,len(thread_name_list)):
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thread_list.append(Thread_class(thread_name_list[i]))
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for i in range(0,len(thread_list)):
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thread_list[i].run() # 這樣只會套用到 呼叫method,會用主線程去調用
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for i in range(0,len(thread_list)):
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thread_list[i].join()
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```
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### Qthread:
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* 使用方式與thread相似
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* 多了信號槽使用(可以擁有多個)
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* 方便與主UI的線程溝通
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```python
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class ReadTime(QtCore.QThread): # 讀取時間
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time_out = pyqtSignal(str) # 聲明一個帶字串參數的信號槽
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def __init__(self, parent=None):
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super().__init__(parent)
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def run(self):
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while True:
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result = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime()) # 讀取當下時間
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self.time_out.emit(f'{result}') # 傳送信号
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self.msleep(500) # 休眠0.5秒
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```
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##
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## 多進程
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### 多進程與多線程的寫法極為相似
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#### 正常使用:
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#### 2個進程幾乎同時啟動
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```python
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# A報數
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def A_Count_off():
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for i in range(0,5):
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print(f'A : {i}')
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time.sleep(0.5)
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# B報數
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def B_Count_off():
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for i in range(5,10):
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print(f'B : {i}')
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time.sleep(0.5)
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if __name__=='__main__':
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process_list=[A_Count_off,B_Count_off]
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process_name =[]
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for i in range(0,len(process_list)):
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process_name.append(mp.Process(target=process_list[i]))
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for i in range(0,len(process_name)):
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process_name[i].start()
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for i in range(0,len(process_name)):
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process_name[i].join()
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```
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### 非正常使用:
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#### 第2個進程要等到第1個進程運行完才會啟動
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#### 失去多進程意義
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```python
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# A報數
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def A_Count_off():
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for i in range(0,5):
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print(f'A : {i}')
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time.sleep(0.5)
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# B報數
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def B_Count_off():
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for i in range(5,10):
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print(f'B : {i}')
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time.sleep(0.5)
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if __name__=='__main__':
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process_list=[A_Count_off,B_Count_off]
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process_name =[]
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for i in range(0,len(process_list)):
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process_name.append(mp.Process(target=process_list[i]))
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for i in range(0,len(process_name)):
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process_name[i].start()
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process_name[i].join()
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```
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### 攜帶參數
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```python
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if __name__=='__main__':
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process_name_list=["A","B","C","D"]
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process_list=[]
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for i in range(0,len(process_name_list)):
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process_list.append(mp.Process(target=Count_off,args=process_name_list[i])) # 攜帶參數
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```
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### 使用class的方式(推薦使用)
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#### 後續觀看程式碼及維護，會提高不少
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* start會使用分出去的進程
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* run會使用主線程
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* 但start後，無法直接調用此class的參數，等等會大概說明
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```python
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class Process_class(mp.Process):
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def __init__(self, code_name):
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mp.Process.__init__(self)
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self.code_name = code_name
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def run(self):
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print('process {} '.format(os.getpid())) # 查看進程
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print('thread {} '.format(threading.current_thread().name)) # 查看線程
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for i in range(0,5):
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print(f'{self.code_name} : {i}')
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time.sleep(0.5)
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def test_return(self):
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return(f'{self.code_name}=END')
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if __name__=='__main__':
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start_time = time.time()
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process_name_list = ["A", "B", "C", "D"]
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process_list = []
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for i in range(0, len(process_name_list)):
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process_list.append(Process_class(process_name_list[i]))
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for i in range(0, len(process_list)):
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process_list[i].start()
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for i in range(0, len(process_list)):
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process_list[i].join()
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for i in range(0, len(process_list)):
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print(process_list[i].test_return())
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```
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### 多進程的溝通方式
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#### 多進程的溝通方式需要透過Queue或pipe
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參考資料
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http://www.taroballz.com/2018/01/11/processing_communcation/
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多線程由於共享記憶體溝通方式比多進程方便
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2者差異的參考資料
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https://blog.csdn.net/Victor2code/article/details/109005171
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#### 用團隊合作方式來理解，每個人都在做自己的事，若沒有溝通或是告知(Queue)，則沒有辦法獲取資料
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