Karpov 7.3, 9.1, 9.2

Practice/Karpov_A/Lec9/t9_1.py

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+import time
+import threading
+
+
+def find_primes(start, end):
+    primes = []
+    start_time = time.time()
+    for i in range(start, end + 1):
+        if i > 1:
+            for n in range(2, i):
+                if (i % n) == 0:
+                    break
+            else:
+                primes.append(i)
+    print(f"Диапазон от {start} до {end}, время обработки {time.time() - start_time} сек.")
+    return primes
+
+begin = [3, 10001, 20001]
+finish = [10000, 20000, 30000]
+
+start_seq = time.time()
+for i in range(3):
+    find_primes(begin[i], finish[i])
+print(f"Общее время: {time.time() - start_seq} сек.")
+
+start_thr = time.time()
+threads = []
+for i in range(3):
+    thread = threading.Thread(target=find_primes, args=(begin[i], finish[i]))
+    threads.append(thread)
+    thread.start()
+for thr in threads:
+    thr.join()
+print(f"Многопоцессорность: {time.time() - start_thr}")

Practice/Karpov_A/Lec9/t9_2.py

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+from multiprocessing import Process
+import time
+
+def add(*args):
+    start_time = time.time()
+    if isinstance(args[0], int) or isinstance(args[0], float):
+        back = 0
+    elif isinstance(args[0], list):
+        back = list()
+    else:
+        back = ''
+
+    for elem in args:
+        back += elem
+
+    print('Сложение для {}, затрачено {} sec.'.format(type(args[0]), time.time() - start_time))
+    print(back)
+
+if __name__ == '__main__':
+    args = [('aaa', 'bbbb', 'cccc'),
+            (1, 2, 3, 4,),
+            (1.1, 2.2, 3.3, 4.4,),
+            ([1, 2, 3], ['asd', 'rrr'], [10.3, 2.2],)]
+
+    def my_proc(func, args):
+        multiprocess = []
+        for arg in args:
+            multiprocess.append(Process(target=func, args=arg))
+        for p in multiprocess:
+            p.start()
+            yield p
+
+    new_list = list(my_proc(add, args))
+
+    for p in new_list:
+        p.join()

Practice/Karpov_A/t7_3.py

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+import random
+import pickle
+
+class Human():
+    def __init__(self, first_name, last_name, age, hair_color, p_of_residence):
+        self.first_name = first_name
+        self.last_name = last_name
+        self.age = age
+        self.hair_color = hair_color
+        self.p_of_residence = p_of_residence
+    def __str__(self):
+        return f"Human: first_name={self.first_name}, last_name={self.last_name}, age={self.age}, hair_color={self.hair_color}," \
+               f" p_of_residence={self.p_of_residence}"
+
+def fun(num):
+    f_name = ['Anton', 'Ksenia', 'Serg', 'Pavel', 'Cemen']
+    l_name = ['Abramov', 'Kitov', 'Block', 'Kazakov', 'Ivanov']
+    p_of_r = ['Moscow', 'Nizhny Novgorod', 'Vladimir', 'St. Petersburg', 'Kazan']
+    hair_color = ['Green', 'Red', 'Blue', 'Gray', 'Black']
+    people = []
+    for i in range(num):
+        people.append(Human(random.choice(f_name), random.choice(l_name), random.randint(1, 115), random.choice(hair_color), random.choice(p_of_r)))
+    for i in people:
+        print(i)
+    with open('data.pickle', 'wb') as f:
+        pickle.dump(people, f)
+    return people
+
+def fun1(file):
+    with open(file, 'rb') as f:
+        data_new = pickle.load(f)
+    for line in data_new:
+        print(line)
+    return data_new
+
+fun(5)
+fun1('data.pickle')