[英]Python yield keyword significance and confusion about generators?
I am confused why didnt we say yield b
and what will the differenccce be if i removed yield a
?我很困惑为什么我们不说
yield b
,如果我删除了yield a
会有什么不同?
I am just confused on how they compare to a normal function?我只是对它们与正常功能的比较感到困惑?
def fibonacci(n):
""" A generator for creating the Fibonacci numbers """
a, b, counter = 0, 1, 0
while True:
if (counter > n):
return
yield a
a, b = b, a + b
counter += 1
f = fibonacci(5)
for x in f:
print(x, " ", end="") #
print()
The normal function would look nearly the same:正常函数看起来几乎相同:
def fibonacci(n):
""" A
function for creating the Fibonacci numbers """
a, b, counter = 0, 1, 0
numbers = []
while True:
if (counter > n):
return numbers
numbers.append(a)
a, b = b, a + b
counter += 1
b
is only used to track the internal state of the process. b
仅用于跟踪进程的内部状态。 a
is the only value ever directly exposed via the iterator or the return value, and b
is only used to compute a
. a
是唯一通过迭代器或返回值直接公开的值,而b
仅用于计算a
。
The regular function computes all the requested Fibonacci numbers, then stores them in a list and returns that list to the caller.常规函数计算所有请求的斐波那契数,然后将它们存储在一个列表中并将该列表返回给调用者。 This may require significant time and memory if
n
is large.如果
n
很大,这可能需要大量的时间和内存。
The generator function, on the other hand, returns almost immediately, because it hasn't computed anything yet.另一方面,生成器函数几乎立即返回,因为它还没有计算任何东西。 It has only returned a
generator
instance, which will, when passed to next
, compute the next Fibonacci number in the sequence and return it, then go back to waiting until you call next
again.它只返回了一个
generator
实例,当传递给next
时,它将计算序列中的下一个斐波那契数并返回它,然后返回等待,直到您再次调用next
。 It only ever uses a small, constant amount of memory, and each call to next
only takes as much time as is needed to perform a handful of additions.它只使用少量恒定的内存,并且每次调用
next
只需要执行少量添加所需的时间。
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