Abstract

This PEP proposes a change to generators: when StopIteration is raised inside a generator, it is replaced with RuntimeError. (More precisely, this happens when the exception is about to bubble out of the generator’s stack frame.) Because the change is backwards incompatible, the feature is initially introduced using a __future__ statement.

Acceptance

This PEP was accepted by the BDFL on November 22. Because of the exceptionally short period from first draft to acceptance, the main objections brought up after acceptance were carefully considered and have been reflected in the “Alternate proposals” section below. However, none of the discussion changed the BDFL’s mind and the PEP’s acceptance is now final. (Suggestions for clarifying edits are still welcome – unlike IETF RFCs, the text of a PEP is not cast in stone after its acceptance, although the core design/plan/specification should not change after acceptance.)

Rationale

The interaction of generators and StopIteration is currently somewhat surprising, and can conceal obscure bugs. An unexpected exception should not result in subtly altered behaviour, but should cause a noisy and easily-debugged traceback. Currently, StopIteration raised accidentally inside a generator function will be interpreted as the end of the iteration by the loop construct driving the generator.

The main goal of the proposal is to ease debugging in the situation where an unguarded next() call (perhaps several stack frames deep) raises StopIteration and causes the iteration controlled by the generator to terminate silently. (Whereas, when some other exception is raised, a traceback is printed pinpointing the cause of the problem.)

This is particularly pernicious in combination with the yield from construct of PEP 380, as it breaks the abstraction that a subgenerator may be factored out of a generator. That PEP notes this limitation, but notes that “use cases for these [are] rare to non-existent”. Unfortunately while intentional use is rare, it is easy to stumble on these cases by accident:

import contextlib

@contextlib.contextmanager
def transaction():
    print('begin')
    try:
        yield from do_it()
    except:
        print('rollback')
        raise
    else:
        print('commit')

def do_it():
    print('Refactored initial setup')
    yield # Body of with-statement is executed here
    print('Refactored finalization of successful transaction')

def gene():
    for i in range(2):
        with transaction():
            yield i
            # return
            raise StopIteration  # This is wrong
        print('Should not be reached')

for i in gene():
    print('main: i =', i)

Here factoring out do_it into a subgenerator has introduced a subtle bug: if the wrapped block raises StopIteration, under the current behavior this exception will be swallowed by the context manager; and, worse, the finalization is silently skipped! Similarly problematic behavior occurs when an asyncio coroutine raises StopIteration, causing it to terminate silently, or when next is used to take the first result from an iterator that unexpectedly turns out to be empty, for example:

# using the same context manager as above
import pathlib

with transaction():
    print('commit file {}'.format(
        # I can never remember what the README extension is
        next(pathlib.Path('/some/dir').glob('README*'))))

In both cases, the refactoring abstraction of yield from breaks in the presence of bugs in client code.

Additionally, the proposal reduces the difference between list comprehensions and generator expressions, preventing surprises such as the one that started this discussion [2]. Henceforth, the following statements will produce the same result if either produces a result at all:

a = list(F(x) for x in xs if P(x))
a = [F(x) for x in xs if P(x)]

With the current state of affairs, it is possible to write a function F(x) or a predicate P(x) that causes the first form to produce a (truncated) result, while the second form raises an exception (namely, StopIteration). With the proposed change, both forms will raise an exception at this point (albeit RuntimeError in the first case and StopIteration in the second).

Finally, the proposal also clears up the confusion about how to terminate a generator: the proper way is return, not raise StopIteration.

As an added bonus, the above changes bring generator functions much more in line with regular functions. If you wish to take a piece of code presented as a generator and turn it into something else, you can usually do this fairly simply, by replacing every yield with a call to print() or list.append(); however, if there are any bare next() calls in the code, you have to be aware of them. If the code was originally written without relying on StopIteration terminating the function, the transformation would be that much easier.

Background information

When a generator frame is (re)started as a result of a __next__() (or send() or throw()) call, one of three outcomes can occur:

• A yield point is reached, and the yielded value is returned.
• The frame is returned from; StopIteration is raised.
• An exception is raised, which bubbles out.

In the latter two cases the frame is abandoned (and the generator object’s gi_frame attribute is set to None).

Proposal

If a StopIteration is about to bubble out of a generator frame, it is replaced with RuntimeError, which causes the next() call (which invoked the generator) to fail, passing that exception out. From then on it’s just like any old exception. [3]

This affects the third outcome listed above, without altering any other effects. Furthermore, it only affects this outcome when the exception raised is StopIteration (or a subclass thereof).

Note that the proposed replacement happens at the point where the exception is about to bubble out of the frame, i.e. after any except or finally blocks that could affect it have been exited. The StopIteration raised by returning from the frame is not affected (the point being that StopIteration means that the generator terminated “normally”, i.e. it did not raise an exception).

A subtle issue is what will happen if the caller, having caught the RuntimeError, calls the generator object’s __next__() method again. The answer is that from this point on it will raise StopIteration – the behavior is the same as when any other exception was raised by the generator.

Another logical consequence of the proposal: if someone uses g.throw(StopIteration) to throw a StopIteration exception into a generator, if the generator doesn’t catch it (which it could do using a try/except around the yield), it will be transformed into RuntimeError.

During the transition phase, the new feature must be enabled per-module using:

from __future__ import generator_stop

Any generator function constructed under the influence of this directive will have the REPLACE_STOPITERATION flag set on its code object, and generators with the flag set will behave according to this proposal. Once the feature becomes standard, the flag may be dropped; code should not inspect generators for it.

A proof-of-concept patch has been created to facilitate testing. [4]

Consequences for existing code

This change will affect existing code that depends on StopIteration bubbling up. The pure Python reference implementation of groupby [5] currently has comments “Exit on StopIteration” where it is expected that the exception will propagate and then be handled. This will be unusual, but not unknown, and such constructs will fail. Other examples abound, e.g. [6], [7].

(Alyssa Coghlan comments: “””If you wanted to factor out a helper function that terminated the generator you’d have to do “return yield from helper()” rather than just “helper()”.”””)

There are also examples of generator expressions floating around that rely on a StopIteration raised by the expression, the target or the predicate (rather than by the __next__() call implied in the for loop proper).

if other == self:
    raise StopIteration

if other == self:
    return

if context is None:
    while True:
        yield next(line_pair_iterator)

if context is None:
    yield from line_pair_iterator
    return

if context is None:
    for line in line_pair_iterator:
        yield line
    return

def parser(f):
    while True:
        data = next(f)
        while True:
            line = next(f)
            if line == "- end -": break
            data += line
        yield data

def parser(f):
    while True:
        try:
            data = next(f)
            while True:
                line = next(f)
                if line == "- end -": break
                data += line
            yield data
        except StopIteration:
            return

def parser(f):
    for data in f:
        while True:
            line = next(f)
            if line == "- end -": break
            data += line
        yield data

def stop():
    raise StopIteration
print(list(x for x in range(10) if x < 5 or stop()))
# prints [0, 1, 2, 3, 4]

def gen():
    for x in range(10):
        if x >= 5: return
        yield x
print(list(gen()))
# prints [0, 1, 2, 3, 4]

Explanation of generators, iterators, and StopIteration

The proposal does not change the relationship between generators and iterators: a generator object is still an iterator, and not all iterators are generators. Generators have additional methods that iterators don’t have, like send and throw. All this is unchanged. Nothing changes for generator users – only authors of generator functions may have to learn something new. (This includes authors of generator expressions that depend on early termination of the iteration by a StopIteration raised in a condition.)

An iterator is an object with a __next__ method. Like many other special methods, it may either return a value, or raise a specific exception - in this case, StopIteration - to signal that it has no value to return. In this, it is similar to __getattr__ (can raise AttributeError), __getitem__ (can raise KeyError), and so on. A helper function for an iterator can be written to follow the same protocol; for example:

def helper(x, y):
    if x > y: return 1 / (x - y)
    raise StopIteration

def __next__(self):
    if self.a: return helper(self.b, self.c)
    return helper(self.d, self.e)

Both forms of signalling are carried through: a returned value is returned, an exception bubbles up. The helper is written to match the protocol of the calling function.

A generator function is one which contains a yield expression. Each time it is (re)started, it may either yield a value, or return (including “falling off the end”). A helper function for a generator can also be written, but it must also follow generator protocol:

def helper(x, y):
    if x > y: yield 1 / (x - y)

def gen(self):
    if self.a: return (yield from helper(self.b, self.c))
    return (yield from helper(self.d, self.e))

In both cases, any unexpected exception will bubble up. Due to the nature of generators and iterators, an unexpected StopIteration inside a generator will be converted into RuntimeError, but beyond that, all exceptions will propagate normally.

Transition plan

• Python 3.5: Enable new semantics under __future__ import; silent deprecation warning if StopIteration bubbles out of a generator not under __future__ import.
• Python 3.6: Non-silent deprecation warning.
• Python 3.7: Enable new semantics everywhere.

Alternate proposals

from itertools import allow_implicit_stop

@allow_implicit_stop
def my_generator():
    ...
    yield next(it)
    ...

def my_generator():
    try:
        ...
        yield next(it)
        ...
    except StopIteration
        return

Criticism

Unofficial and apocryphal statistics suggest that this is seldom, if ever, a problem. [13] Code does exist which relies on the current behaviour (e.g. [3], [6], [7]), and there is the concern that this would be unnecessary code churn to achieve little or no gain.

Steven D’Aprano started an informal survey on comp.lang.python [14]; at the time of writing only two responses have been received: one was in favor of changing list comprehensions to match generator expressions (!), the other was in favor of this PEP’s main proposal.

The existing model has been compared to the perfectly-acceptable issues inherent to every other case where an exception has special meaning. For instance, an unexpected KeyError inside a __getitem__ method will be interpreted as failure, rather than permitted to bubble up. However, there is a difference. Special methods use return to indicate normality, and raise to signal abnormality; generators yield to indicate data, and return to signal the abnormal state. This makes explicitly raising StopIteration entirely redundant, and potentially surprising. If other special methods had dedicated keywords to distinguish between their return paths, they too could turn unexpected exceptions into RuntimeError; the fact that they cannot should not preclude generators from doing so.

References

Copyright

This document has been placed in the public domain.