第四周練習 part3 --- 清單生成式、多線程的實作

清單生成式

# 清單生成式


a = [i * 2 for i in range(10)]
print(a)


def func(j):
    j = j / 2
    return j

b = [func(i) for i in range(100)]

for i in b:
    print(i)


c = (i * 2 for i in range(1000))
for i in c:
    if i < 530:
        print(i)

d = (i * 3 for i in range(10))
# 隻有一個 next 方法，用的不多，一般都用循環調用
print(d.__next__())
print(d.__next__())
print(d.__next__())
print(d.__next__())      

斐波那契數列

# 斐波那契數列，用函數生成
# 用函數做生成器，能夠随時調用，中間可以幹别的事，不必等待循環結束


def fib(max):
    n, a, b = 0, 0, 1
    while n < max:
        yield b  # 原來是 print（b），為函數，現在是生成器
        a, b = b, a + b
        n = n + 1
    return 'done'

f = fib(6)
# print(f)
# print(f.__next__())
# print(f.__next__())

while True:
    try:
        x = next(f)
        print('f:', x)
    except StopIteration as e:
        print('Generator return value:', e.value)
        break

# while True:
#     x = next(f)
#     print('f:', x)      

多線程的實作

1 # 生産者消費者模型，單線程實作并行效果
 2 
 3 import time
 4 
 5 
 6 def consumer(name):
 7     print('%s starts eating pizza!' % name)
 8     while True:
 9         pizza = yield
10         print('Pizza [%s] is coming and eaten by [%s]' % (pizza, name))
11 
12 
13 def producer(name):
14     c1 = consumer('A')  # 定義了生成器
15     c2 = consumer('B')
16     c1.__next__()  # 使執行生成器裡的語句，遇到 yield 停止，執行 c2
17     c2.__next__()
18     print('Ready to make pizza!')
19     for i in range(5):
20         time.sleep(2)
21         print('%s Have made 2 Pizza' % name)
22         c1.send(i)  # 回到 yield，将 i 傳給了 pizza
23         c2.send(i)
24 
25 
26 producer('Lief')      

轉載于:https://www.cnblogs.com/lief/p/8718856.html