gh-115754: Expose constants (ex: Py_None) as public ABI symbols (stable ABI)

[vstinner]

Currently, the C API implements Py_None, Py_True, Py_False, Py_Ellipsis and Py_NotImplemented constants by referring to private symbols at the ABI level:

#define Py_None (&_Py_NoneStruct)
#define Py_False _PyObject_CAST(&_Py_FalseStruct)
#define Py_True _PyObject_CAST(&_Py_TrueStruct)
#define Py_Ellipsis (&_Py_EllipsisObject)
#define Py_NotImplemented (&_Py_NotImplementedStruct)

In the stable ABI, I would like to avoid referring to private symbols, but only use public symbols.

The issue https://github.com/python/cpython/issues/115754 discussed two options:

• (A) Expose "Py_None" API as PyObject *Py_None symbol at the ABI level.
• (B) Implement "Py_None" API as a function call. Example: #define Py_None Py_GetNone() with PyObject* Py_GetNone(void), where Py_GetNone() cannot fail.

Please read the issue https://github.com/python/cpython/issues/115754 discussion, especially @zooba's comment https://github.com/python/cpython/issues/115754#issuecomment-1959798283 which lists possible constraints of such API. Extract:

• lazy type initialization
• thread/interpreter-local types
• synchronized/locked access
• switch from singleton to non-singleton
• always return new references
• run-time library delegation (e.g. load python3.dll and have it forward to whichever python3x.dll it's using)
• static analysis for reference counts
• "fake" singletons
• deprecation/warnings/errors
• GIL enforcement

Please vote for your preferred option, or add a comment if you want a 3rd option.

• @encukou: option (B)
• @gvanrossum: option (A) -- I don't have time for this, but I'm surprised you haven't asked @ericsnowcurrently yet.
• @iritkatriel:: option (B)
• @vstinner: option (A)
• @zooba: option (B)

I wrote https://github.com/python/cpython/pull/115755 which is a simple change implementing option (A).

---

I prefer option (A). I agree that option (B) avoids any potential/hypothetical issue in the future, but I don't want to write a perfect API/ABI, only make pragmatic changes.

Option (B) can have a (significant?) impact on performance, especially on hot code. So far, nobody ran microbenchmarks, no number is available.

I would prefer to only consider option (B) once we will deeply design the stable ABI. Right now, we are far from being able to support tagged pointers for example. I would prefer to not pay a performance overhead for a theoretical issue :-(

Note: Subinterpreters are sharing singletons thanks to immortal objects (PEP 683, Python 3.12).

---

By the way, I already added Py_Is(x, y), Py_IsNone(x), Py_IsTrue(x) and Py_IsNone(x) for PyPy. In PyPy, you cannot simply compare an object to a constant memory address (if (x == Py_None) ...), since PyPy objects can be moved in memory.

This issue is specific to CPython. Other Python implementations are free to use a different implementation and a different ABI.

[vstinner]

@gvanrossum:

I don't have time for this, but I'm surprised you haven't asked @ericsnowcurrently yet.

I wrote:

Note: Subinterpreters are sharing singletons thanks to immortal objects (PEP 683, Python 3.12).

In the past, I proposed adding Py_GetNone() and have per-interpreter singletons: https://github.com/python/cpython/issues/83692 Apparently, @ericsnowcurrently didn't like this idea and it was decided to go with immortal objects instead.

[encukou]

I prefer that stable ABI is useful for alternative implementations: they nicely show the design space that CPython might want to explore in the future. If we want to hide implementation details, looking at PyPy is a pretty good way to do it. Hence, I voted for option B.

I would prefer to only consider option (B) once we will deeply design the stable ABI.

I'd prefer that we do that now -- for new additions. If we don't want to design new API now, let's stick to what works.

[ericsnowcurrently]

• (B) Implement "Py_None" API as a function call. Example: #define Py_None Py_GetNone() with PyObject* Py_GetNone(void), where Py_GetNone() cannot fail.

A similar option, which I believe @zooba suggested:

• (C) Implement a generic getter. Example: #define Py_None Py_GetBuiltinObject(Py_NONE).

[ericsnowcurrently]

• (A) Expose "Py_None" API as PyObject *Py_None symbol at the ABI level.

Objects exposed directly by the C-API were one of the few hard problems I had to solve for a per-interpreter GIL. If it hadn't been for immortal objects, I would have had to either do some messy macro trickery or introduce costly fixup code across most of the C-API implementation (using the existing symbols as . In addition to the extra complexity, the macro hacks would have probably been a further pain point for other compilers/implementations. The fixup code solution would have been fragile. It also doesn't help that we expose values for some of the objects (e.g. the non-exception builtin types) rather than just pointers. Note that even with object immortality I still had to add a trick for static builtin types, to accommodate tp_dict and tp_subclasses. Overall, the whole situation was a real pain.

Everything would have been drastically simpler if we had never exposed the objects directly in the first place. With that in mind, I firmly favor option (B). Let's move away from exposing objects directly in the C-API, rather than doing it more.

[vstinner]

Option (B) can have a (significant?) impact on performance, especially on hot code. So far, nobody ran microbenchmarks, no number is available.

Hum, I will try to work on a benchmark to have numbers. It may help to take a decision.

[vstinner]

I wrote https://github.com/python/cpython/pull/116572 to measure the performance overhead. I modified the constant everywhere for this benchmark, including inside Python internals. So the measurement is the worst case scenario.

Results with PGO, LTO and CPU isolation on Linux: https://github.com/python/cpython/pull/116572#issuecomment-1987822227

• Around 2x slower on a microbenchmark.
• I'm not sure how to read pyperformance benchmark results. The overall summary is 1.01x faster: so it's not 2x slower, and "a little bit faster" can be just noise in the measurement.

6 benchmarks are at least 1.05x slower:

| sqlite_synth                  | 3.73 us  | 3.90 us: 1.05x slower  |
+-------------------------------+----------+------------------------+
| typing_runtime_protocols      | 172 us   | 180 us: 1.05x slower   |
+-------------------------------+----------+------------------------+
| json_dumps                    | 15.5 ms  | 16.5 ms: 1.06x slower  |
+-------------------------------+----------+------------------------+
| pickle                        | 17.6 us  | 19.7 us: 1.12x slower  |
+-------------------------------+----------+------------------------+
| pickle_dict                   | 43.1 us  | 50.2 us: 1.17x slower  |
+-------------------------------+----------+------------------------+
| pickle_list                   | 6.64 us  | 7.87 us: 1.19x slower  |

3 benchmarks are at least 1.05x faster:

| coverage                      | 499 ms   | 152 ms: 3.29x faster   |
+-------------------------------+----------+------------------------+
| dask                          | 885 ms   | 628 ms: 1.41x faster   |
+-------------------------------+----------+------------------------+
| logging_silent                | 166 ns   | 155 ns: 1.07x faster   |

3x faster for coverage looks really strange. Maybe I didn't run benchmarks properly, I'm not sure.

[vstinner]

Since the majority seems to prefer function calls, I prepared a full PR which documents the change: https://github.com/python/cpython/pull/116572 It's ready to be merged, waiting for a decision :-)

@iritkatriel: Do you have an opinion on this decision? Tell me if you need more details.

[iritkatriel]

There doesn't seem much of a perf impact, so yeah I think option B makes more sense.

[gvanrossum]

Maybe ask Mike Droettboom to help with benchmarking this?

On Mon, Mar 11, 2024 at 3:25 AM Irit Katriel @.***> wrote:

There doesn't seem much of a perf impact, so yeah I think option B makes more sense.

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[vstinner]

Maybe ask Mike Droettboom to help with benchmarking this?

I already ran a microbenchmark and pyperformance. Do you need more benchmarks? I'm not sure that I get your comment.

[gvanrossum]

Maybe ask Mike Droettboom to help with benchmarking this?

I already ran a microbenchmark and pyperformance. Do you need more benchmarks? I'm not sure that I get your comment.

I am used to having the benchmark output in the specific presentation that we use for our team's benchmarking: https://github.com/faster-cpython/benchmarking-public/blob/main/README.md

But I now see that you did run pyperformance and found that it doesn't have a significant effect so I'll accept that.

My vote would currently be (A), since I abhor the idea of a macro that looks like a variable reference but actually expands to a call. Didn't we introduce immortal objects specifically so that we could have a single None object shared between interpreters?

[vstinner]

I wrote 3 implementations so they can be compared:

• https://github.com/python/cpython/pull/115755 exposes Py_None, Py_False, Py_True, Ellipsis and NotImplemented as symbols at the ABI level.
• https://github.com/python/cpython/pull/116572 adds _Py_GetNone(), _Py_GetFalse(), _Py_GetTrue(), _Py_GetEllipsis() and _Py_GetNotImplemented() functions (5 functions).
• https://github.com/python/cpython/pull/116883 adds only 2 functions: Py_GetConstantRef() and Py_GetConstant(). Moreover, it adds 5 constants: zero, one, empty string, empty bytes string, empty tuple.

So the majority prefers option (B): Implement "Py_None" API as a function call.

Between adding 5 functions for 5 constants and adding 2 functions for 10 constants, I prefer the "Py_GetConstantRef()" approach: only add 2 functions. Moreover, it gives the choice between borrowed and strong references, even if in practice, both are the same.

[vstinner]

I close the issue, the decision is to use function calls.

The discussion on the actual implementation can happen directly on the pull request.