Differences between generator comprehension expres

Question

There are, as far as I know, three ways to create a generator through a comprehension¹.

The classical one:

def f1():
    g = (i for i in range(10))

The yield variant:

def f2():
    g = [(yield i) for i in range(10)]

The yield from variant (that raises a SyntaxError except inside of a function):

def f3():
    g = [(yield from range(10))]

The three variants lead to different bytecode, which is not really surprising. It would seem logical that the first one is the best, since it's a dedicated, straightforward syntax to create a generator through comprehension. However, it is not the one that produces the shortest bytecode.

Disassembled in Python 3.6

Classical generator comprehension

>>> dis.dis(f1)
4           0 LOAD_CONST               1 (<code object <genexpr> at...>)
            2 LOAD_CONST               2 ('f1.<locals>.<genexpr>')
            4 MAKE_FUNCTION            0
            6 LOAD_GLOBAL              0 (range)
            8 LOAD_CONST               3 (10)
           10 CALL_FUNCTION            1
           12 GET_ITER
           14 CALL_FUNCTION            1
           16 STORE_FAST               0 (g)

5          18 LOAD_FAST                0 (g)
           20 RETURN_VALUE

yield variant

>>> dis.dis(f2)
8           0 LOAD_CONST               1 (<code object <listcomp> at...>)
            2 LOAD_CONST               2 ('f2.<locals>.<listcomp>')
            4 MAKE_FUNCTION            0
            6 LOAD_GLOBAL              0 (range)
            8 LOAD_CONST               3 (10)
           10 CALL_FUNCTION            1
           12 GET_ITER
           14 CALL_FUNCTION            1
           16 STORE_FAST               0 (g)

9          18 LOAD_FAST                0 (g)
           20 RETURN_VALUE

yield from variant

>>> dis.dis(f3)
12           0 LOAD_GLOBAL              0 (range)
             2 LOAD_CONST               1 (10)
             4 CALL_FUNCTION            1
             6 GET_YIELD_FROM_ITER
             8 LOAD_CONST               0 (None)
            10 YIELD_FROM
            12 BUILD_LIST               1
            14 STORE_FAST               0 (g)

13          16 LOAD_FAST                0 (g)
            18 RETURN_VALUE

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In addition, a timeit comparison shows that the yield from variant is the fastest (still run with Python 3.6):

>>> timeit(f1)
0.5334039637357152

>>> timeit(f2)
0.5358906506760719

>>> timeit(f3)
0.19329123352712596

f3 is more or less 2.7 times as fast as f1 and f2.

As Leon mentioned in a comment, the efficiency of a generator is best measured by the speed it can be iterated over. So I changed the three functions so they iterate over the generators, and call a dummy function.

def f():
    pass

def fn():
    g = ...
    for _ in g:
        f()

The results are even more blatant:

>>> timeit(f1)
1.6017412817975778

>>> timeit(f2)
1.778684261368946

>>> timeit(f3)
0.1960603619517669

f3 is now 8.4 times as fast as f1, and 9.3 times as fast as f2.

Note: The results are more or less the same when the iterable is not range(10) but a static iterable, such as [0, 1, 2, 3, 4, 5]. Therefore, the difference of speed has nothing to do with range being somehow optimized.

---

So, what are the differences between the three ways? More specifically, what is the difference between the yield from variant and the two other?

Is this normal behaviour that the natural construct (elt for elt in it) is slower than the tricky [(yield from it)]? Shall I from now on replace the former by the latter in all of my scripts, or is there any drawbacks to using the yield from construct?

---

Edit

This is all related, so I don't feel like opening a new question, but this is getting even stranger. I tried comparing range(10) and [(yield from range(10))].

def f1():
    for i in range(10):
        print(i)

def f2():
    for i in [(yield from range(10))]:
        print(i)

>>> timeit(f1, number=100000)
26.715589237537195

>>> timeit(f2, number=100000)
0.019948781941049987

So. Now, iterating over [(yield from range(10))] is 186 times as fast as iterating over a bare range(10)?

How do you explain why iterating over [(yield from range(10))] is so much faster than iterating over range(10)?

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^{1: For the sceptical, the three expressions that follow do produce a generator object; try and call type on them.}

Answer 1

This is what you should be doing:

g = (i for i in range(10))

It's a generator expression. It's equivalent to

def temp(outer):
    for i in outer:
        yield i
g = temp(range(10))

but if you just wanted an iterable with the elements of range(10), you could have done

g = range(10)

You do not need to wrap any of this in a function.

If you're here to learn what code to write, you can stop reading. The rest of this post is a long and technical explanation of why the other code snippets are broken and should not be used, including an explanation of why your timings are broken too.

---

This:

g = [(yield i) for i in range(10)]

is a broken construct that should have been taken out years ago. 8 years after the problem was originally reported, the process to remove it is finally beginning. Don't do it.

While it's still in the language, on Python 3, it's equivalent to

def temp(outer):
    l = []
    for i in outer:
        l.append((yield i))
    return l
g = temp(range(10))

List comprehensions are supposed to return lists, but because of the yield, this one doesn't. It acts kind of like a generator expression, and it yields the same things as your first snippet, but it builds an unnecessary list and attaches it to the StopIteration raised at the end.

>>> g = [(yield i) for i in range(10)]
>>> [next(g) for i in range(10)]
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
>>> next(g)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
StopIteration: [None, None, None, None, None, None, None, None, None, None]

This is confusing and a waste of memory. Don't do it. (If you want to know where all those Nones are coming from, read PEP 342.)

On Python 2, g = [(yield i) for i in range(10)] does something entirely different. Python 2 doesn't give list comprehensions their own scope - specifically list comprehensions, not dict or set comprehensions - so the yield is executed by whatever function contains this line. On Python 2, this:

def f():
    g = [(yield i) for i in range(10)]

is equivalent to

def f():
    temp = []
    for i in range(10):
        temp.append((yield i))
    g = temp

making f a generator-based coroutine, in the pre-async sense. Again, if your goal was to get a generator, you've wasted a bunch of time building a pointless list.

---

This:

g = [(yield from range(10))]

is silly, but none of the blame is on Python this time.

There is no comprehension or genexp here at all. The brackets are not a list comprehension; all the work is done by yield from, and then you build a 1-element list containing the (useless) return value of yield from. Your f3:

def f3():
    g = [(yield from range(10))]

when stripped of the unnecessary list-building, simplifies to

def f3():
    yield from range(10)

or, ignoring all the coroutine support stuff yield from does,

def f3():
    for i in range(10):
        yield i

---

Your timings are also broken.

In your first timing, f1 and f2 create generator objects that can be used inside those functions, though f2's generator is weird. f3 doesn't do that; f3 is a generator function. f3's body does not run in your timings, and if it did, its g would behave quite unlike the other functions' gs. A timing that would actually be comparable with f1 and f2 would be

def f4():
    g = f3()

In your second timing, f2 doesn't actually run, for the same reason f3 was broken in the previous timing. In your second timing, f2 is not iterating over a generator. Instead, the yield from turns f2 into a generator function itself.

Answer 2

g = [(yield i) for i in range(10)]

This construct accumulates the data that is/may be passed back into the generator through its send() method and returns it via the StopIteration exception when the iteration is exhausted¹:

>>> g = [(yield i) for i in range(3)]
>>> next(g)
0
>>> g.send('abc')
1
>>> g.send(123)
2
>>> g.send(4.5)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
StopIteration: ['abc', 123, 4.5]
>>> #          ^^^^^^^^^^^^^^^^^

No such thing happens with plain generator comprehension:

>>> g = (i for i in range(3))
>>> next(g)
0
>>> g.send('abc')
1
>>> g.send(123)
2
>>> g.send(4.5)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
StopIteration
>>> 

As for the yield from version - in Python 3.5 (which I am using) it doesn't work outside functions, so the illustration is a little different:

>>> def f(): return [(yield from range(3))]
... 
>>> g = f()
>>> next(g)
0
>>> g.send(1)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "<stdin>", line 1, in f
AttributeError: 'range_iterator' object has no attribute 'send'

OK, send() doesn't work for a generator yielding from range() but let's at least see what's at the end of the iteration:

>>> g = f()
>>> next(g)
0
>>> next(g)
1
>>> next(g)
2
>>> next(g)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
StopIteration: [None]
>>> #          ^^^^^^

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¹ Note that even if you don't use the send() method, send(None) is assumed, therefore a generator constructed in this way always uses more memory than plain generator comprehension (since it has to accumulate the results of the yield expression till the end of the iteration):

>>> g = [(yield i) for i in range(3)]
>>> next(g)
0
>>> next(g)
1
>>> next(g)
2
>>> next(g)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
StopIteration: [None, None, None]

---

UPDATE

Regarding the performance differences between the three variants. yield from beats the other two because it eliminates a level of indirection (which, to the best of my understanding, is one of the two main reasons why yield from was introduced). However, in this particular example yield from itself is superfluous - g = [(yield from range(10))] is actually almost identical to g = range(10).

Answer 3

This might not do what you think it does.

def f2():
    for i in [(yield from range(10))]:
        print(i)

Call it:

>>> def f2():
...     for i in [(yield from range(10))]:
...         print(i)
...
>>> f2() #Doesn't print.
<generator object f2 at 0x02C0DF00>
>>> set(f2()) #Prints `None`, because `(yield from range(10))` evaluates to `None`.
None
{0, 1, 2, 3, 4, 5, 6, 7, 8, 9}

Because the yield from is not within a comprehension, it is bound to the f2 function instead of an implicit function, turning f2 into a generator function.

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I remembered seeing someone point out that it was not actually iterating, but I can't remember where I saw that. I was testing the code myself when I rediscovered this. I didn't find the source searching through the mailing list post nor the bug tracker thread. If someone finds the source, please tell me or add it to the post itself, so it can be credited.