和上一台很像，但更紧凑。 (布尔值只是数字)

breaker = False #our mighty loop exiter!
while True:
    while True:
        ok = get_input("Is this ok? (y/n)")
        breaker+= (ok.lower() == "y")
        break

    if breaker: # the interesting part!
        break   # <--- !

这是另一种简短的方法。缺点是你只能打破外部循环，但有时这正是你想要的。

for a in xrange(10):
    for b in xrange(20):
        if something(a, b):
            # Break the inner loop...
            break
    else:
        # Continue if the inner loop wasn't broken.
        continue
    # Inner loop was broken, break the outer.
    break

这使用了for / else结构:为什么python在for和while循环之后使用'else' ?

关键洞见:似乎只有外部循环总是会破裂。但如果内环不破裂，外环也不会破裂。

这里的continue语句很神奇。它在for-else从句中。根据定义，如果没有内部断裂，就会发生这种情况。在这种情况下，继续巧妙地绕过外部中断。

我个人会做的是使用一个boolean，当我准备跳出外部循环时切换。例如

while True:
    #snip: print out current state
    quit = False
    while True:
        ok = input("Is this ok? (y/n)")
        if ok.lower() == "y":
            quit = True
            break # this should work now :-)
        if ok.lower() == "n":
            quit = True
            break # This should work too :-)
    if quit:
        break
    #do more processing with menus and stuff

以下是一个非常简短的版本: 创建名为break_out_nested.py的文件

import itertools
import sys

it = sys.modules[__name__] # this allows us to share variables with break_out_nested.py when we import it 


def bol(*args):
    condi = args[-1] # the condition function
    i = args[:-1] # all iterables 
    for p in itertools.product(*i): # itertools.product creates the nested loop
        if condi(): # if the condition is True, we return 
            return
        yield p # if not, we yield the result 

现在你只需要几行就可以打破嵌套的循环(数据来自Rafiq的例子)

from break_out_nested import it, bol # import what we have just created

# you need to create new variables as attributes of it,
# because break_out_nested has only access to these variables
it.i, it.j, it.k = 1, 1, 1
# the break condition
def cond(): return it.i % 3 == 0 and it.j % 3 == 0 and it.k % 3 == 0

# The condition will be checked in each loop 
for it.i, it.j, it.k in bol(range(1, 6, 1), range(1, 11, 2, ), range(1, 21, 4), cond):
    print(it.i, it.j, it.k)

更多的例子:

def cond(): return it.i + it.j + it.k == 777

it.i, it.j, it.k = 0, 0, 0
for it.i, it.j, it.k in bol(range(100), range(1000), range(10000), cond):
    print(it.i, it.j, it.k)




def cond(): return it.i + it.j + it.k >= 100000

it.i, it.j, it.k = 0, 0, 0
# you dont have to use it.i, it.j, it.k as the loop variables, you can
# use anything you want, but you have to update the variables somewhere
for i, j, k in bol(range(100), range(1000), range(10000), cond):
    it.i, it.j, it.k = i * 10, j * 100, k * 100
    print(it.i, it.j, it.k)

将循环逻辑分解为迭代器，迭代器产生循环变量并在完成时返回——这里有一个简单的迭代器，它将图像按行/列排列，直到我们用完图像或找不到放置它们的位置:

def it(rows, cols, images):
    i = 0
    for r in xrange(rows):
        for c in xrange(cols):
            if i >= len(images):
                return
            yield r, c, images[i]
            i += 1 

for r, c, image in it(rows=4, cols=4, images=['a.jpg', 'b.jpg', 'c.jpg']):
    ... do something with r, c, image ...

这样做的优点是将复杂的循环逻辑和处理分开。

解决方法有两种

举个例子:这两个矩阵相等/相同吗? 矩阵x1和矩阵x2是相同大小的，n，二维矩阵。

第一个解决方案，没有函数

same_matrices = True
inner_loop_broken_once = False
n = len(matrix1)

for i in range(n):
    for j in range(n):

        if matrix1[i][j] != matrix2[i][j]:
            same_matrices = False
            inner_loop_broken_once = True
            break

    if inner_loop_broken_once:
        break

第二个解决方案，用函数

这是我案子的最终解决方案。

def are_two_matrices_the_same (matrix1, matrix2):
    n = len(matrix1)
    for i in range(n):
        for j in range(n):
            if matrix1[i][j] != matrix2[i][j]:
                return False
    return True