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concurrent iteration. (This is prep work for enabling specialization of FOR_ITER in free-threaded builds.) The basic premise is: - Iterating over a shared _iterable_ (list, tuple or range) should be safe, not involve data races, and behave like iteration normally does. - Using a shared _iterator_ should not crash or involve data races, and should only produce items regular iteration would produce. It is _not_ guaranteed to produce all items, or produce each item only once. Providing stronger guarantees is possible for some of these iterators, but it's not always straight-forward and can significantly hamper the common case. Since iterators in general aren't shared between threads, and it's simply impossible to concurrently use many iterators (like generators), better to make sharing iterators without explicit synchronization clearly wrong. Specific issues fixed in order to make the tests pass: - List iteration could occasionally crash when a shared list wasn't already marked as shared when reallocated. - Tuple iteration could occasionally crash when the iterator's reference to the tuple was cleared on exhaustion. Like with list iteration, in free-threaded builds we can't safely and efficiently clear the iterator's reference to the iterable (doing it safely would mean extra, slow refcount operations), so just keep the iterable reference around. - Fast range iterators (for integers that fit in C longs) shared between threads would sometimes produce values past the end of the range, because the iterators use two bits of state that we can't efficiently update atomically. Rewriting the iterators to have a single bit of state is possible, but probably means more math for each iteration and may not be worth it. - Long range iterators (for other numbers) shared between threads would crash catastrophically in a variety of ways. This now uses a critical section. Rewriting this to be more efficient is probably possible, but since it deals with arbitrary Python objects it's difficult to get right. There seem to be no more exising races in list_get_item_ref, so drop it from the tsan suppression list.
actually correct and the real problem was an incorrect assert. The fast path still contains notionally unsafe uses of memcpy/memmove, so add list_get_item_ref back to the TSan suppressions file.
iterators, and fix build failures because labels can't technically be at the end of compound statements (a statement must follow the label, even if it's empty).
…len and tupleiter_setstate appropriately relaxed.
iterator test to accept the current behaviour of the fast range iterator and avoid testing the (very unsafe) long range iterator, use threading.Barrier where appropriate, and add comments to the unsafe uses of memcpy/memmove in free-threaded builds.
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PTAL. |
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relaxed atomics. (These are not performance-sensitive parts of the code, and this lets us detect races elsewhere involving the iterators.)
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@colesbury Do you still want to look at this? |
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LGTM
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Make tuple iteration more thread-safe, and actually test concurrent iteration of tuple, range and list. (This is prep work for enabling specialization of FOR_ITER in free-threaded builds.) The basic premise is:
Iterating over a shared iterable (list, tuple or range) should be safe, not involve data races, and behave like iteration normally does.
Using a shared iterator should not crash or involve data races, and should only produce items regular iteration would produce. It is not guaranteed to produce all items, or produce each item only once. (This is not the case for range iteration even after this PR.)
Providing stronger guarantees is possible for some of these iterators, but it's not always straight-forward and can significantly hamper the common case. Since iterators in general aren't shared between threads, and it's simply impossible to concurrently use many iterators (like generators), better to make sharing iterators without explicit synchronization clearly wrong.
Specific issues fixed in order to make the tests pass:
List iteration could occasionally fail an assertion when a shared list was shrunk and an item past the new end was retrieved concurrently. There's still some unsafety when deleting/inserting multiple items through for example slice assignment, which uses memmove/memcpy.
Tuple iteration could occasionally crash when the iterator's reference to the tuple was cleared on exhaustion. Like with list iteration, in free-threaded builds we can't safely and efficiently clear the iterator's reference to the iterable (doing it safely would mean extra, slow refcount operations), so just keep the iterable reference around.