python generator - What does the “yield” keyword do?

python generator to list / python / iterator / generator / yield / coroutine

What is the use of the yield keyword in Python, and what does it do?

For example, I'm trying to understand this code1:

def _get_child_candidates(self, distance, min_dist, max_dist):
    if self._leftchild and distance - max_dist < self._median:
        yield self._leftchild
    if self._rightchild and distance + max_dist >= self._median:
        yield self._rightchild  

And this is the caller:

result, candidates = [], [self]
while candidates:
    node = candidates.pop()
    distance = node._get_dist(obj)
    if distance <= max_dist and distance >= min_dist:
        result.extend(node._values)
    candidates.extend(node._get_child_candidates(distance, min_dist, max_dist))
return result

iliketocode



Answer #1

Instead of this:

def square_list(n):
    the_list = []                         # Replace
    for x in range(n):
        y = x * x
        the_list.append(y)                # these
    return the_list                       # lines

do this:

def square_yield(n):
    for x in range(n):
        y = x * x
        yield y                           # with this one.

Whenever you find yourself building a list from scratch, yield each piece instead.

yield is a sugary way to say

Same behavior:

>>> for square in square_list(4):
...     print(square)
...
0
1
4
9
>>> for square in square_yield(4):
...     print(square)
...
0
1
4
9

Yield is versatile. Data doesn't have to be stored all together, it can be made available one at a time. It can be infinite.

>>> def squares_all_of_them():
...     x = 0
...     while True:
...         yield x * x
...         x += 1
...
>>> squares = squares_all_of_them()
>>> for _ in range(4):
...     print(next(squares))
...
0
1
4
9
>>> list(square_yield(4))
[0, 1, 4, 9]