要使對(duì)象成為生成器，需通過(guò)定義含yield的函數(shù)、實(shí)現(xiàn)\_\_iter\_\_和\_\_next\_\_方法的可迭代類或使用生成器表達(dá)式實(shí)現(xiàn)按需生成值。1. 定義含yield的函數(shù)，調(diào)用時(shí)返回生成器對(duì)象并逐次生成值；2. 在自定義類中實(shí)現(xiàn)\_\_iter\_\_和\_\_next\_\_方法以控制迭代邏輯；3. 使用生成器表達(dá)式快速創(chuàng)建輕量級(jí)生成器，適用于簡(jiǎn)單變換或過(guò)濾。這些方式均避免將全部數(shù)據(jù)加載至內(nèi)存，從而提升內(nèi)存效率。

To make an object a generator in Python, you don’t necessarily turn the object itself into a generator, but rather create a way for it to produce values on the fly — typically by defining a function or class that yields values using yield, or by implementing iteration logic with __iter__ and __next__. Here's how to do it effectively.

Define a Generator Function Using yield

The most straightforward way to create a generator is by using the yield keyword inside a function. When called, this function returns a generator object that you can iterate over.

def my_generator():
    yield 1
    yield 2
    yield 3

gen = my_generator()
for value in gen:
    print(value)

This prints:

1
2
3

• The function doesn't run all at once; it pauses each time it hits yield.
• This is memory-efficient because it generates values one at a time instead of building a full list in memory.
• You can use loops, conditions, or any logic inside the generator function to control what gets yielded.

Make a Custom Object Iterable That Produces Values Like a Generator

If you have a custom class and want its instances to be iterable in a generator-like fashion, you’ll need to define both __iter__() and __next__() methods.

class MyRange:
    def __init__(self, start, end):
        self.current = start
        self.end = end

    def __iter__(self):
        return self

    def __next__(self):
        if self.current < self.end:
            value = self.current
            self.current  = 1
            return value
        else:
            raise StopIteration

# Usage
for num in MyRange(0, 3):
    print(num)

This prints:

0
1
2

• The __iter__ method should return the iterator object itself (usually self).
• The __next__ method handles returning the next value or raising StopIteration when done.
• This approach gives you fine-grained control over iteration behavior.

Use Generator Expressions for Lightweight Generators

If you just need a quick generator without writing a whole function, you can use a generator expression — similar to list comprehensions, but with parentheses.

squares = (x*x for x in range(5))
for square in squares:
    print(square)

This prints:

0
1
4
9
16

• These are useful for simple transformations or filtering.
• They’re more concise than writing a full generator function.
• Unlike lists, they don’t store all items in memory at once.

So, making an object act like a generator usually means either writing a generator function, creating an iterable class that controls value production, or using a generator expression. It’s not about turning the object into a generator per se, but enabling it to behave like one when iterated over.

基本上就這些。

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