[Python-Dev] frame evaluation API PEP (original) (raw)

Brett Cannon brett at python.org
Sun Jun 19 21:29:45 EDT 2016

On Sat, 18 Jun 2016 at 21:49 Guido van Rossum <guido at python.org> wrote:

Hi Brett,

I've got a few questions about the specific design. Probably you know the answers, it would be nice to have them in the PEP.

Once you're happy with my answers I'll update the PEP.

First, why not have a global hook? What does a hook per interpreter give you? Would even finer granularity buy anything?

We initially considered a per-code object hook, but we figured it was unnecessary to have that level of control, especially since people like Numba have gotten away with not needing it for this long (although I suspect that's because they are a decorator so they can just return an object that overrides call()). We didn't think that a global one was appropriate as different workloads may call for different JITs/debuggers/etc. and there is no guarantee that you are executing every interpreter with the same workload. Plus we figured people might simply import their JIT of choice and as a side-effect set the hook, and since imports are a per-interpreter thing that seemed to suggest the granularity of interpreters.

IOW it seemed to be more in line with sys.settrace() than some global thing for the process.

Next, I'm a bit (but no more than a bit) concerned about the extra 8 bytes per code object, especially since for most people this is just waste (assuming most people won't be using Pyjion or Numba). Could it be a compile-time feature (requiring recompilation of CPython but not extensions)?

Probably. It does water down potential usage thanks to needing a special build. If the decision is "special build or not", I would simply pull out this part of the proposal as I wouldn't want to add a flag that influences what is or is not possible for an interpreter.

Could you figure out some other way to store per-code-object data? It seems you considered this but decided that the coextra field was simpler and faster; I'm basically pushing a little harder on this. Of course most of the PEP would disappear without this feature; the extra interpreter field is fine.

Dino and I thought of two potential alternatives, neither of which we have taken the time to implement and benchmark. One is to simply have a hash table of memory addresses to JIT data that is kept on the JIT side of things. Obviously it would be nice to avoid the overhead of a hash table lookup on every function call. This also doesn't help minimize memory when the code object gets GC'ed.

The other potential solution we came up with was to use weakrefs. I have not looked into the details, but we were thinking that if we registered the JIT data object as a weakref on the code object, couldn't we iterate through the weakrefs attached to the code object to look for the JIT data object, and then get the reference that way? It would let us avoid a more expensive hash table lookup if we assume most code objects won't have a weakref on it (assuming weakrefs are stored in a list), and it gives us the proper cleanup semantics we want by getting the weakref cleanup callback execution to make sure we decref the JIT data object appropriately. But as I said, I have not looked into the feasibility of this at all to know if I'm remembering the weakref implementation details correctly.

Finally, there are some error messages from pep2html.py: https://www.python.org/dev/peps/pep-0523/#copyright

All fixed in https://github.com/python/peps/commit/6929f850a5af07e51d0163558a5fe8d6b85dccfe .

-Brett

--Guido On Fri, Jun 17, 2016 at 7:58 PM, Brett Cannon <brett at python.org> wrote: I have taken PEP 523 for this: https://github.com/python/peps/blob/master/pep-0523.txt .

I'm waiting until Guido gets back from vacation, at which point I'll ask for a pronouncement or assignment of a BDFL delegate. On Fri, 3 Jun 2016 at 14:37 Brett Cannon <brett at python.org> wrote:

For those of you who follow python-ideas or were at the PyCon US 2016 language summit, you have already seen/heard about this PEP. For those of you who don't fall into either of those categories, this PEP proposed a frame evaluation API for CPython. The motivating example of this work has been Pyjion, the experimental CPython JIT Dino Viehland and I have been working on in our spare time at Microsoft. The API also works for debugging, though, as already demonstrated by Google having added a very similar API internally for debugging purposes.

The PEP is pasted in below and also available in rendered form at https://github.com/Microsoft/Pyjion/blob/master/pep.rst (I will assign myself a PEP # once discussion is finished as it's easier to work in git for this for the rich rendering of the in-progress PEP). I should mention that the difference from python-ideas and the language summit in the PEP are the listed support from Google's use of a very similar API as well as clarifying the coextra field on code objects doesn't change their immutability (at least from the view of the PEP). ---------- PEP: NNN Title: Adding a frame evaluation API to CPython Version: RevisionRevisionRevision Last-Modified: DateDateDate Author: Brett Cannon <brett at python.org>, Dino Viehland <dinov at microsoft.com> Status: Draft Type: Standards Track Content-Type: text/x-rst Created: 16-May-2016 Post-History: 16-May-2016 03-Jun-2016

Abstract ======== This PEP proposes to expand CPython's C API [#c-api] to allow for the specification of a per-interpreter function pointer to handle the evaluation of frames [#pyevalevalframeex]. This proposal also suggests adding a new field to code objects [#pycodeobject] to store arbitrary data for use by the frame evaluation function. Rationale ========= One place where flexibility has been lacking in Python is in the direct execution of Python code. While CPython's C API [#c-api] allows for constructing the data going into a frame object and then evaluating it via PyEvalEvalFrameEx() [#pyevalevalframeex], control over the execution of Python code comes down to individual objects instead of a hollistic control of execution at the frame level. While wanting to have influence over frame evaluation may seem a bit too low-level, it does open the possibility for things such as a method-level JIT to be introduced into CPython without CPython itself having to provide one. By allowing external C code to control frame evaluation, a JIT can participate in the execution of Python code at the key point where evaluation occurs. This then allows for a JIT to conditionally recompile Python bytecode to machine code as desired while still allowing for executing regular CPython bytecode when running the JIT is not desired. This can be accomplished by allowing interpreters to specify what function to call to evaluate a frame. And by placing the API at the frame evaluation level it allows for a complete view of the execution environment of the code for the JIT. This ability to specify a frame evaluation function also allows for other use-cases beyond just opening CPython up to a JIT. For instance, it would not be difficult to implement a tracing or profiling function at the call level with this API. While CPython does provide the ability to set a tracing or profiling function at the Python level, this would be able to match the data collection of the profiler and quite possibly be faster for tracing by simply skipping per-line tracing support. It also opens up the possibility of debugging where the frame evaluation function only performs special debugging work when it detects it is about to execute a specific code object. In that instance the bytecode could be theoretically rewritten in-place to inject a breakpoint function call at the proper point for help in debugging while not having to do a heavy-handed approach as required by sys.settrace(). To help facilitate these use-cases, we are also proposing the adding of a "scratch space" on code objects via a new field. This will allow per-code object data to be stored with the code object itself for easy retrieval by the frame evaluation function as necessary. The field itself will simply be a PyObject * type so that any data stored in the field will participate in normal object memory management. Proposal ======== All proposed C API changes below will not be part of the stable ABI. Expanding PyCodeObject -------------------------- One field is to be added to the PyCodeObject struct [#pycodeobject]:: typedef struct { ... PyObject coextra; / "Scratch space" for the code object. */ } PyCodeObject; The coextra will be NULL by default and will not be used by CPython itself. Third-party code is free to use the field as desired. Values stored in the field are expected to not be required in order for the code object to function, allowing the loss of the data of the field to be acceptable (this keeps the code object as immutable from a functionality point-of-view; this is slightly contentious and so is listed as an open issue in Is coextra needed?). The field will be freed like all other fields on PyCodeObject during deallocation using PyXDECREF(). It is not recommended that multiple users attempt to use the coextra simultaneously. While a dictionary could theoretically be set to the field and various users could use a key specific to the project, there is still the issue of key collisions as well as performance degradation from using a dictionary lookup on every frame evaluation. Users are expected to do a type check to make sure that the field has not been previously set by someone else. Expanding PyInterpreterState -------------------------------- The entrypoint for the frame evalution function is per-interpreter:: // Same type signature as PyEvalEvalFrameEx(). _typedef PyObject* (stdcall PyFrameEvalFunction)(PyFrameObject, int); typedef struct { ... PyFrameEvalFunction evalframe; } PyInterpreterState; By default, the evalframe field will be initialized to a function pointer that represents what PyEvalEvalFrameEx() currently is (called PyEvalEvalFrameDefault(), discussed later in this PEP). Third-party code may then set their own frame evaluation function instead to control the execution of Python code. A pointer comparison can be used to detect if the field is set to PyEvalEvalFrameDefault() and thus has not been mutated yet. Changes to Python/ceval.c ----------------------------- PyEvalEvalFrameEx() [#pyevalevalframeex] as it currently stands will be renamed to PyEvalEvalFrameDefault(). The new PyEvalEvalFrameEx() will then become:: PyObject * PyEvalEvalFrameEx(PyFrameObject *frame, int throwflag) { PyThreadState *tstate = PyThreadStateGET(); return tstate->interp->evalframe(frame, throwflag); } This allows third-party code to place themselves directly in the path of Python code execution while being backwards-compatible with code already using the pre-existing C API. Updating python-gdb.py -------------------------- The generated python-gdb.py file used for Python support in GDB makes some hard-coded assumptions about PyEvalEvalFrameEx(), e.g. the names of local variables. It will need to be updated to work with the proposed changes. Performance impact ================== As this PEP is proposing an API to add pluggability, performance impact is considered only in the case where no third-party code has made any changes. Several runs of pybench [#pybench] consistently showed no performance cost from the API change alone. A run of the Python benchmark suite [#py-benchmarks] showed no measurable cost in performance. In terms of memory impact, since there are typically not many CPython interpreters executing in a single process that means the impact of coextra being added to PyCodeObject is the only worry. According to [#code-object-count], a run of the Python test suite results in about 72,395 code objects being created. On a 64-bit CPU that would result in 579,160 bytes of extra memory being used if all code objects were alive at once and had nothing set in their coextra fields. Example Usage ============= A JIT for CPython ----------------- Pyjion '''''' The Pyjion project [#pyjion] has used this proposed API to implement a JIT for CPython using the CoreCLR's JIT [#coreclr]. Each code object has its coextra field set to a PyjionJittedCode object which stores four pieces of information: 1. Execution count 2. A boolean representing whether a previous attempt to JIT failed 3. A function pointer to a trampoline (which can be type tracing or not) 4. A void pointer to any JIT-compiled machine code The frame evaluation function has (roughly) the following algorithm:: def evalframe(frame, throwflag): pyjioncode = frame.code.coextra if not pyjioncode: frame.code.coextra = PyjionJittedCode() elif not pyjioncode.jitfailed: if not pyjioncode.jitcode: return pyjioncode.eval(pyjioncode.jitcode, frame) elif pyjioncode.execcount > 20000: if jitcompile(frame): return pyjioncode.eval(pyjioncode.jitcode, frame) else: pyjioncode.jitfailed = True pyjioncode.execcount += 1 return PyEvalEvalFrameDefault(frame, throwflag) The key point, though, is that all of this work and logic is separate from CPython and yet with the proposed API changes it is able to provide a JIT that is compliant with Python semantics (as of this writing, performance is almost equivalent to CPython without the new API). This means there's nothing technically preventing others from implementing their own JITs for CPython by utilizing the proposed API. Other JITs '''''''''' It should be mentioned that the Pyston team was consulted on an earlier version of this PEP that was more JIT-specific and they were not interested in utilizing the changes proposed because they want control over memory layout they had no interest in directly supporting CPython itself. An informal discusion with a developer on the PyPy team led to a similar comment. Numba [#numba], on the other hand, suggested that they would be interested in the proposed change in a post-1.0 future for themselves [#numba-interest]. The experimental Coconut JIT [#coconut] could have benefitted from this PEP. In private conversations with Coconut's creator we were told that our API was probably superior to the one they developed for Coconut to add JIT support to CPython. Debugging --------- In conversations with the Python Tools for Visual Studio team (PTVS) [#ptvs], they thought they would find these API changes useful for implementing more performant debugging. As mentioned in the Rationale section, this API would allow for switching on debugging functionality only in frames where it is needed. This could allow for either skipping information that sys.settrace() normally provides and even go as far as to dynamically rewrite bytecode prior to execution to inject e.g. breakpoints in the bytecode. It also turns out that Google has provided a very similar API internally for years. It has been used for performant debugging purposes. Implementation ============== A set of patches implementing the proposed API is available through the Pyjion project [#pyjion]. In its current form it has more changes to CPython than just this proposed API, but that is for ease of development instead of strict requirements to accomplish its goals. Open Issues =========== Allow evalframe to be NULL ----------------------------------- Currently the frame evaluation function is expected to always be set. It could very easily simply default to NULL instead which would signal to use PyEvalEvalFrameDefault(). The current proposal of not special-casing the field seemed the most straight-forward, but it does require that the field not accidentally be cleared, else a crash may occur. Is coextra needed? ------------------- While discussing this PEP at PyCon US 2016, some core developers expressed their worry of the coextra field making code objects mutable. The thinking seemed to be that having a field that was mutated after the creation of the code object made the object seem mutable, even though no other aspect of code objects changed. The view of this PEP is that the coextra field doesn't change the fact that code objects are immutable. The field is specified in this PEP as to not contain information required to make the code object usable, making it more of a caching field. It could be viewed as similar to the UTF-8 cache that string objects have internally; strings are still considered immutable even though they have a field that is conditionally set. The field is also not strictly necessary. While the field greatly simplifies attaching extra information to code objects, other options such as keeping a mapping of code object memory addresses to what would have been kept in coextra or perhaps using a weak reference of the data on the code object and then iterating through the weak references until the attached data is found is possible. But obviously all of these solutions are not as simple or performant as adding the coextra field. Rejected Ideas ============== A JIT-specific C API -------------------- Originally this PEP was going to propose a much larger API change which was more JIT-specific. After soliciting feedback from the Numba team [#numba], though, it became clear that the API was unnecessarily large. The realization was made that all that was truly needed was the opportunity to provide a trampoline function to handle execution of Python code that had been JIT-compiled and a way to attach that compiled machine code along with other critical data to the corresponding Python code object. Once it was shown that there was no loss in functionality or in performance while minimizing the API changes required, the proposal was changed to its current form. References ========== .. [#pyjion] Pyjion project (https://github.com/microsoft/pyjion) .. [#c-api] CPython's C API (https://docs.python.org/3/c-api/index.html) .. [#pycodeobject] PyCodeObject (https://docs.python.org/3/c-api/code.html#c.PyCodeObject) .. [#coreclr] .NET Core Runtime (CoreCLR) (https://github.com/dotnet/coreclr) .. [#pyevalevalframeex] PyEvalEvalFrameEx() ( https://docs.python.org/3/c-api/veryhigh.html?highlight=pyframeobject#c.PyEvalEvalFrameEx ) .. [#pycodeobject] PyCodeObject (https://docs.python.org/3/c-api/code.html#c.PyCodeObject) .. [#numba] Numba (http://numba.pydata.org/) .. [#numba-interest] numba-users mailing list: "Would the C API for a JIT entrypoint being proposed by Pyjion help out Numba?" ( https://groups.google.com/a/continuum.io/forum/#!topic/numba-users/yRl0t8-m1g ) .. [#code-object-count] [Python-Dev] Opcode cache in ceval loop ( https://mail.python.org/pipermail/python-dev/2016-February/143025.html) .. [#py-benchmarks] Python benchmark suite (https://hg.python.org/benchmarks) .. [#pyston] Pyston (http://pyston.org) .. [#pypy] PyPy (http://pypy.org/) .. [#ptvs] Python Tools for Visual Studio (http://microsoft.github.io/PTVS/) .. [#coconut] Coconut (https://github.com/davidmalcolm/coconut) Copyright ========= This document has been placed in the public domain. .. Local Variables: mode: indented-text indent-tabs-mode: nil sentence-end-double-space: t fill-column: 70 coding: utf-8 End:

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