如何编写一个生成器类? [英] How to write a generator class?

问题描述

我看到了许多生成器函数的示例，但是我想知道如何为类编写生成器.可以说，我想写斐波那契数列作为一个类.

I see lot of examples of generator functions, but I want to know how to write generators for classes. Lets say, I wanted to write Fibonacci series as a 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>

为什么不打印值self.a?另外，如何为生成器编写unittest?

Why is the value self.a not getting printed? Also, how do I write unittest for generators?

推荐答案

如何编写生成器类?

您快到了，正在编写一个 Iterator 类(我在答案的末尾显示了一个Generator)，但是每次您使用next调用该对象时，都会调用__next__，返回一个生成器对象.相反，要使您的代码以最少的更改和最少的代码行工作，请使用__iter__，它使您的类实例化一个 iterable (从技术上讲，它不是 generator ):

You're almost there, writing an Iterator class (I show a Generator at the end of the answer), but __next__ gets called every time you call the object with next, returning a generator object. Instead, to make your code work with the least changes, and the fewest lines of code, use __iter__, which makes your class instantiate an iterable (which isn't technically a 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

当我们将迭代器传递给iter()时，它为我们提供了 iterator :

When we pass an iterable to iter(), it gives us an iterator:

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

要使类本身成为 iterator ，它确实需要__next__:

To make the class itself an iterator, it does require a __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仅返回实例本身，因此我们无需调用它:

And now, since iter just returns the instance itself, we don't need to call it:

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

为什么self.a值无法打印?

这是您的原始代码，上面有我的评论:

Here's your original code with my comments:

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))

因此，每次调用next(f)时，都会得到__next__返回的生成器对象:

So every time you called next(f) you got the generator object that __next__ returns:

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

此外，我该如何为生成器编写单元测试?

您仍然需要为Generator

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>

因此，让我们实现一个生成器对象，并利用collections模块中的Generator抽象基类(请参见源代码中的 Python协程数据模型):

So let's implement a generator object, and leverage the Generator abstract base class from the collections module (see the source for its 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):

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
    

并使用与上面相同的测试:

and using the same tests above:

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

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

Python 2

ABC Generator仅在Python 3中.要在没有Generator的情况下执行此操作，除了上面定义的方法外，我们还至少需要编写close，__iter__和__next__. /p>

Python 2

The ABC Generator is only in Python 3. To do this without Generator, we need to write at least close, __iter__, and __next__ in addition to the methods we defined above.

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")

请注意，我直接从Python 3 标准库复制了close ，无需修改.

Note that I copied close directly from the Python 3 standard library, without modification.

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