update

2022.03.16_frequently_used_python_package/multiprocessing_example.py

@@ -2,22 +2,23 @@ from multiprocessing import Process
 import time
 
 def f(name):
-    time.sleep(5)
+    for i in range(5):
-    print('Hello', name)
+        time.sleep(1)
+        print('Hello', name, i)
 
 if __name__ == '__main__':
     start_time = time.time()
-    p1 = Process(target=f, args=('Bob',))
+    f('A')
-    p2 = Process(target=f, args=('Alice',))
+    f('B')
+    end_time = time.time()
+    print(end_time - start_time, '\n')
+
+    start_time = time.time()
+    p1 = Process(target=f, args=('A',))
+    p2 = Process(target=f, args=('B',))
     p1.start()
     p2.start()
     p1.join()
     p2.join()
     end_time = time.time()
-    print(end_time - start_time, '\n')
-
-    start_time = time.time()
-    f('Bob')
-    f('Alice')
-    end_time = time.time()
     print(end_time - start_time)

2022.03.16_frequently_used_python_package/numpy_example.py

@@ -1,21 +1,26 @@
 import numpy as np
-np.zeros((2, 3)) # 零矩阵
+print(np.zeros((2, 3)), '\n') # 零矩阵
-np.identity(3) # 单位矩阵
+print(np.identity(3), '\n') # 单位矩阵
-np.diag([1, 3, 5])  # 对角矩阵
+print(np.diag([1, 3, 5]), '\n')  # 对角矩阵
 matrix1 = np.array([[3, 5+1j], [2, 7]]) # numpy矩阵
-matrix1.shape # 矩阵的维度
+print(matrix1, '\n')
-matrix1.transpose() # 矩阵转置
+print(matrix1.shape, '\n') # 矩阵的维度
-matrix1.conj() # 矩阵所有元素共轭
+print(matrix1.transpose(), '\n') # 矩阵转置
-np.conj(matrix1) # 矩阵所有元素共轭（同上）
+print(matrix1.conj(), '\n') # 矩阵所有元素共轭
-np.arange(1, 5, 1) # 数列（左闭右开）
+print(np.conj(matrix1), '\n') # 矩阵所有元素共轭（同上）
-np.linspace(-2, 2, 5) # 数列（左闭右闭）
+print(np.arange(1, 5, 1), '\n') # 数列（左闭右开）
-np.random.uniform(-2, 2) # 随机数
+print(np.linspace(-2, 2, 5), '\n') # 数列（左闭右闭）
-np.random.randint(0, 2)  # 随机整数（左闭右开）
+print(np.random.uniform(-2, 2), '\n') # 随机数
-np.sort([1, 7, 0, 3])  # 排列
+print(np.random.randint(0, 2), '\n')  # 随机整数（左闭右开）
-np.argsort([1, 7, 0, 3]) # 排列索引
+print(np.sort([1, 7, 0, 3]), '\n') # 排列
-np.linalg.det(matrix1)  # 行列式
+print(np.argsort([1, 7, 0, 3]), '\n') # 排列索引
+print(np.linalg.det(matrix1), '\n')   # 行列式
 matrix2 = np.linalg.inv(matrix1)  # 求逆
-np.matmul(matrix1, matrix2) # 矩阵乘积
+print(matrix2, '\n')
-np.dot(matrix1, matrix2) # 矩阵乘积（同上）
+print(np.matmul(matrix1, matrix2), '\n') # 矩阵乘积
+print(np.dot(matrix1, matrix2), '\n') # 矩阵乘积（同上）
 eigenvalue, eigenvector = np.linalg.eig(matrix1)  # 求本征值，本征向量
+print(eigenvalue, '\n')
+print(eigenvector, '\n')
 matrix3 = np.append(matrix1, matrix2, axis=0) # 增加数组元素或者矩阵的行
+print(matrix3)

2022.03.16_frequently_used_python_package/pickle_example.py

@@ -0,0 +1,7 @@
+import pickle
+data = [1, 2, 3]
+with open('a.txt', 'wb') as f:
+    pickle.dump(data, f)
+with open('a.txt', 'rb') as f:
+    data_load = pickle.load(f)
+print(data_load)

2022.03.16_frequently_used_python_package/python_example.py

@@ -0,0 +1,9 @@
+a = [1, 2] # 数组
+print(a)
+print(len(a)) # 数组长度
+a.append(3) # 增加元素
+print(a)
+b = range(5)  # 数列（从0开始）
+print(b)
+for i0 in b:
+    print(i0)

2022.03.16_frequently_used_python_package/re_example.py

@@ -0,0 +1,23 @@
+import re
+
+# 正则表达式：匹配任意字符（.）；零次或多次（*）；尽可能少地匹配（?）
+
+# re.match 指匹配起始位置的模式，如果起始位置不匹配的话，返回 None
+string = 'this_is_a_test_abc_123'
+result = re.match(pattern='ab(.*?)23', string=string)
+print(result)
+print()
+result = re.match(pattern='this(.*?)abc', string=string)
+print(result.group(0))
+print(result.group(1))
+print()
+
+# re.search 扫描整个字符串并返回第一个成功的匹配。
+string = 'this_is_a_test_abc_123'
+result = re.search(pattern='ab(.*?)23', string=string)
+print(result.group(0))
+print(result.group(1))
+print()
+result = re.search(pattern='this(.*?)abc', string=string)
+print(result.group(0))
+print(result.group(1))

2022.03.16_frequently_used_python_package/threading_example.py

@@ -6,16 +6,23 @@ def print_numbers(x):
         time.sleep(1)
         print(f"Thread {x}: {i}")
 
+# 串行测试
+start_time = time.time()
+print_numbers('A')
+print_numbers('B')
+end_time = time.time()
+print(end_time - start_time, '\n')
+
 # 创建两个线程
 thread1 = threading.Thread(target=print_numbers, args=('A'))
 thread2 = threading.Thread(target=print_numbers, args=('B'))
 
+start_time = time.time()
 # 启动线程
 thread1.start()
 thread2.start()
-
 # 等待两个线程完成
 thread1.join()
 thread2.join()
-
+end_time = time.time()
-print("Both threads have finished.")
+print(end_time - start_time)

2022.03.16_frequently_used_python_package/tqdm_example.py

@@ -0,0 +1,7 @@
+from tqdm import tqdm 
+import time
+import numpy as np
+
+for i in tqdm(np.arange(1, 10)):     
+    time.sleep(0.1)
+    print('', i)