如何写一个生成器class?

How to write a generator class?

我看到很多生成器函数的例子,但我想知道如何为 classes 编写生成器。比方说,我想将斐波那契数列写成 class。

class Fib:
    def __init__(self):
        self.a, self.b = 0, 1

    def __next__(self):
        yield self.a
        self.a, self.b = self.b, self.a+self.b

f = Fib()

for i in range(3):
    print(next(f))

输出:

<generator object __next__ at 0x000000000A3E4F68>
<generator object __next__ at 0x000000000A3E4F68>
<generator object __next__ at 0x000000000A3E4F68>

为什么值 self.a 没有被打印出来?另外,如何为生成器编写 unittest

__next__ 应该 return 一个项目,而不是放弃它。

您可以编写以下内容,其中 Fib.__iter__ return 是合适的迭代器:

class Fib:
    def __init__(self, n):
        self.n = n
        self.a, self.b = 0, 1

    def __iter__(self):
        for i in range(self.n):
            yield self.a
            self.a, self.b = self.b, self.a+self.b

f = Fib(10)

for i in f:
    print i

或者通过定义 __next__.

使每个实例本身成为一个迭代器
class Fib:
    def __init__(self):
        self.a, self.b = 0, 1

    def __iter__(self):
        return self

    def __next__(self):
        x = self.a
        self.a, self.b = self.b, self.a + self.b
        return x

f = Fib()

for i in range(10):
    print next(f)

How to write a generator class?

你快到了,写了一个 Iterator class(我在答案的末尾展示了一个生成器),但是 __next__ 被调用了每次使用 next 调用该对象时,都会返回一个生成器对象。相反,为了使您的代码以最少的更改和最少的代码行工作,请使用 __iter__,这会使您的 class 实例化一个 iterable(这是技术上不是 generator):

class Fib:
    def __init__(self):
        self.a, self.b = 0, 1
    def __iter__(self):
        while True:
            yield self.a
            self.a, self.b = self.b, self.a+self.b

当我们将可迭代对象传递给 iter() 时,它会为我们提供一个 迭代器 :

>>> f = iter(Fib())
>>> for i in range(3):
...     print(next(f))
...
0
1
1

要使 class 本身成为 迭代器 ,它确实需要 __next__:

class Fib:
    def __init__(self):
        self.a, self.b = 0, 1        
    def __next__(self):
        return_value = self.a
        self.a, self.b = self.b, self.a+self.b
        return return_value
    def __iter__(self):
        return self

现在,由于 iter 只是 returns 实例本身,我们不需要调用它:

>>> f = Fib()
>>> for i in range(3):
...     print(next(f))
...
0
1
1

Why is the value self.a not getting printed?

这是你的原始代码和我的评论:

class Fib:
    def __init__(self):
        self.a, self.b = 0, 1
        
    def __next__(self):
        yield self.a          # yield makes .__next__() return a generator!
        self.a, self.b = self.b, self.a+self.b

f = Fib()

for i in range(3):
    print(next(f))

所以每次你调用 next(f) 你都会得到生成器对象 __next__ returns:

<generator object __next__ at 0x000000000A3E4F68>
<generator object __next__ at 0x000000000A3E4F68>
<generator object __next__ at 0x000000000A3E4F68>

Also, how do I write unittest for generators?

您仍然需要为 Generator

实现发送和抛出方法
from collections.abc import Iterator, Generator
import unittest

class Test(unittest.TestCase):
    def test_Fib(self):
        f = Fib()
        self.assertEqual(next(f), 0)
        self.assertEqual(next(f), 1)
        self.assertEqual(next(f), 1)
        self.assertEqual(next(f), 2) #etc...
    def test_Fib_is_iterator(self):
        f = Fib()
        self.assertIsInstance(f, Iterator)
    def test_Fib_is_generator(self):
        f = Fib()
        self.assertIsInstance(f, Generator)

现在:

>>> unittest.main(exit=False)
..F
======================================================================
FAIL: test_Fib_is_generator (__main__.Test)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "<stdin>", line 7, in test_Fib_is_generator
AssertionError: <__main__.Fib object at 0x00000000031A6320> is not an instance of <class 'collections.abc.Generator'>

----------------------------------------------------------------------
Ran 3 tests in 0.001s

FAILED (failures=1)
<unittest.main.TestProgram object at 0x0000000002CAC780>

所以让我们实现一个生成器对象,并利用集合模块中的 Generator 抽象基础 class(请参阅其 implementation), which means we only need to implement send and throw - giving us close, __iter__ (returns self), and __next__ (same as .send(None)) for free (see the Python data model on coroutines 的源代码):

class Fib(Generator):
    def __init__(self):
        self.a, self.b = 0, 1        
    def send(self, ignored_arg):
        return_value = self.a
        self.a, self.b = self.b, self.a+self.b
        return return_value
    def throw(self, type=None, value=None, traceback=None):
        raise StopIteration
    

并使用上面相同的测试:

>>> unittest.main(exit=False)
...
----------------------------------------------------------------------
Ran 3 tests in 0.002s

OK
<unittest.main.TestProgram object at 0x00000000031F7CC0>

Python 2

ABCGenerator只在Python3中,要做到没有Generator,我们至少要写close__iter__,和 __next__ 除了我们上面定义的方法。

class Fib(object):
    def __init__(self):
        self.a, self.b = 0, 1        
    def send(self, ignored_arg):
        return_value = self.a
        self.a, self.b = self.b, self.a+self.b
        return return_value
    def throw(self, type=None, value=None, traceback=None):
        raise StopIteration
    def __iter__(self):
        return self
    def next(self):
        return self.send(None)
    def close(self):
        """Raise GeneratorExit inside generator.
        """
        try:
            self.throw(GeneratorExit)
        except (GeneratorExit, StopIteration):
            pass
        else:
            raise RuntimeError("generator ignored GeneratorExit")

注意我直接从Python3standard library复制了close,没有修改

不要在 __next__ 函数中使用 yield 并实现 next 也是为了与 python2.7+

兼容

代码

class Fib:
    def __init__(self):
        self.a, self.b = 0, 1
    def __next__(self):
        a = self.a
        self.a, self.b = self.b, self.a+self.b
        return a
    def next(self):
        return self.__next__()

如果你给class一个__iter__()方法implemented as a generator,“它会自动return一个迭代器对象(技术上,一个生成器对象)”调用时,所以 that 对象的 __iter__()__next__() 方法将被使用。

我的意思是:

class Fib:
    def __init__(self):
        self.a, self.b = 0, 1

    def __iter__(self):
        while True:
            value, self.a, self.b = self.a, self.b, self.a+self.b
            yield value

f = Fib()

for i, value in enumerate(f, 1):
    print(value)
    if i > 5:
        break

输出:

0
1
1
2
3
5

在方法中使用 yield 使该方法成为 生成器 ,并调用该方法 returns 成为 生成器迭代器 . next() 需要一个生成器迭代器来实现 __next__()returns 一个项目。这就是为什么 yielding in __next__() 会导致生成器 class 在调用 next() 时输出生成器迭代器。

https://docs.python.org/3/glossary.html#term-generator

实现接口时,您需要定义方法并将它们映射到您的 class 实现。在这种情况下,__next__() 方法需要调用生成器迭代器。

class Fib:
    def __init__(self):
        self.a, self.b = 0, 1
        self.generator_iterator = self.generator()

    def __next__(self):
        return next(self.generator_iterator)

    def generator(self):
        while True:
            yield self.a
            self.a, self.b = self.b, self.a+self.b

f = Fib()

for i in range(3):
    print(next(f))
# 0
# 1
# 1