Mailman 3 December 2021 - Python-Dev

PEP 651, Robust Stack Overflow Handling, Rejection notice
by Python Steering Council Jan. 31, 2022

Jan. 31, 2022

Hi Mark, Thank you for submitting PEP 651. The Steering Council has spent the past two weeks reviewing PEP 651. After careful consideration, we have decided to reject the PEP. The following were the key points that led us to this decision: * The benefits are not compelling enough. Deep recursion is not a common tool in Python, and even with PEP 651 it would not be efficient enough to make it a common tool. * The benefit of PEP 651 is negated as soon as a non-Python function is involved in the recursion, making the likelihood of it being useful even smaller. It also creates easy pitfalls for users who do end up relying on recursion. * We believe the PEP understates the disruption created by the technical solution of multiple Python stack frames per C call. Although this may be solvable, it will certainly cause substantial disruption to existing debuggers, tracers, and state inspection tools as they need to adapt to this change (which may not be trivial). * As the way to approach this will be platform-specific (as some parts of the proposal are not portable), this can cause generic Python code to behave differently on different platforms, making this kind of code less portable and less predictable. In the end, the benefit of the PEP does not outweigh the cost of the potential breakage, confusion, and unpredictability of the feature. With our appreciation, The Python Steering Council

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The current state of typing PEPs
by Barry Warsaw Jan. 24, 2022

Jan. 24, 2022

Does PEP 563 or 649 satisfy static and dynamic typing needs? In the interest of full transparency, we want to let the Python community know that the Steering Council continues to discuss PEP 563 (Postponed Evaluation of Annotations) and PEP 649 (Deferred Evaluation Of Annotations Using Descriptors). We have concluded that we lack enough detailed information to make a decision in favor of either PEP. As we see it, adopting either PEP 563 or PEP 649 as the default would be insufficient. They will not fully resolve the existing problems these PEPs intend to fix, will break some existing code, and likely don’t address all the use cases and requirements across the static and dynamic typing constituents. We are also uncertain as to the best migration path from the current state of affairs. Defer decision on PEP 563 and 649 in 3.11 As such, at this time, the only reasonable path forward that the SC sees is to defer the decision in Python 3.11 again, essentially keeping the 3.10 status quo. We know that this is far from ideal, but it’s also the safest path since we can’t clearly make the situation better, and we don’t have confidence that either PEP solves the problems once and for all. Pragmatically, we don’t want to make the situation worse, and we really don’t want to find ourselves back here again in a couple of releases because we overlooked an important requirement for a set of users. Calling for help from static and dynamic typing users This is also a call to you, the folks who both care deeply about typing in Python, and have a solid understanding of the subject matter (or willingness to learn) to help us! There are use cases we don’t know about, and unclear requirements from both the static and dynamic typing users. We need help in defining those requirements clearly, in uncovering the use cases we’re not aware of, and most importantly, being an interface to typing enthusiasts to help build consensus with either of the proposed PEPs, or some other solution that doesn’t yet have a PEP (such as suggestions made by Łukasz in his blog post here: https://lukasz.langa.pl/61df599c-d9d8-4938-868b-36b67fdb4448/). Volunteer to be a typing PEP shepherd We’re looking for someone(s) who can be neutral as to the solution, knowledgeable enough to understand all sides of the problem, willing to serve as not quite a PEP author, not a PEP Delegate, but more than a PEP shepherd. If you are that person, please let us know! Cheers, -Barry (on behalf of the Python Steering Council)

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RFC on PEP 673: Self Type
by Pradeep Kumar Srinivasan Jan. 20, 2022

Jan. 20, 2022

This PEP [1] introduces a simple and intuitive way to annotate methods and classmethods that return an instance of their class. Such methods and classmethods occur quite frequently, but the existing way to annotate them correctly is quite arcane and error-prone. The PEP introduces a special type `Self` to represent the type of the `self` parameter, similar to the `this` type in TypeScript and the `Self` type in Rust. We have implementations for mypy and pyright. The PEP does not affect CPython directly except for the addition of one special form (Self) to typing.py [2]. Since we have reached consensus on the PEP in typing-sig [3], we wanted to get your comments and suggestions before submitting to the Steering Council. Thanks, Pradeep Kumar Srinivasan James Hilton-Balfe [1]: https://www.python.org/dev/peps/pep-0673/ [2]: Adding `Self` to typing_extensions.py: https://github.com/python/typing/pull/933 [3]: See the comments from typing-sig members on the Google doc: https://docs.google.com/document/d/1ujuSMXDmSIOJpiZyV7mvBEC8P-y55AgSzXcvhrZ…

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SC Acceptance: PEP 646 -- Variadic Generics
by Barry Warsaw Jan. 19, 2022

Jan. 19, 2022

Hello Mark, Matthew, Pradeep, Vincent, and Guido, The Python Steering Council discussed the latest version of PEP 646 (Variadic Generics) at our last meeting, and have unanimously decided to accept the PEP. Congratulations! We want to specifically mention that we appreciate the way you called out the Python grammar changes required by the typing features you proposed. As we’ve said before, the Steering Council strongly believes that the typing language and the “general” Python programming language should remain aligned, so the implications of syntax change proposed in the PEP for typing needed to be addressed for non-typed Python as well. The PEP explains this change well, and does a good job of justifying the semantics and usefulness of the change for non-type related purposes. Please feel free to change the PEP status to Accepted, and to merge your changes to Python 3.11 at your convenience. With our appreciation, -Barry (on behalf of the Python Steering Council)

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PEP 646 (Variadic Generics): final call for comments
by Matthew Rahtz Jan. 18, 2022

Jan. 18, 2022

Hi everyone, We've got to the stage now with PEP 646 that we're feeling pretty happy with it. So far though we've mainly been workshopping it in typing-sig, so as PEP 1 requires we're asking for some feedback here too before submitting it to the steering council. If you have time over the next couple of weeks, please take a look at the current draft and let us know your thoughts: https://www.python.org/dev/peps/pep-0646/ (Note that the final couple of sections are out of date; https://github.com/python/peps/pull/1880 clarifies which grammar changes would be required, now that PEP 637 has been rejected. We also have a second PR in progress at https://github.com/python/peps/pull/1881 clarifying some of the motivation.) Thanks! Matthew and Pradeep

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Is anyone using 15-bit PyLong digits (PYLONG_BITS_IN_DIGIT=15)?
by Mark Dickinson Jan. 18, 2022

Jan. 18, 2022

tl;dr: I'd like to deprecate and eventually remove the option to use 15-bit digits in the PyLong implementation. Before doing so, I'd like to find out whether there's anyone still using 15-bit PyLong digits, and if so, why they're doing so. History: the use of 30-bit digits in PyLong was introduced for Python 3.1 and Python 2.7, to improve performance of int (Python 3) / long (Python 2) arithmetic. At that time, we retained the option to use 15-bit digits, for two reasons: - (1) use of 30-bit digits required C99 features (uint64_t and friends) at a time when we hadn't yet committed to requiring C99 - (2) it wasn't clear whether 30-bit digits would be a performance win on 32-bit operating systems Twelve years later, reason (1) no longer applies, and I suspect that: - No-one is deliberately using the 15-bit digit option. - There are few machines where using 15-bit digits is faster than using 30-bit digits. But I don't have solid data on either of these suspicions, hence this post. Removing the 15-bit digit option would simplify the code (there's significant mental effort required to ensure we don't break things for 15-bit builds when modifying Objects/longobject.c, and 15-bit builds don't appear to be exercised by the buildbots), remove a hidden compatibility trap (see b.p.o. issue 35037), widen the applicability of the various fast paths for arithmetic operations, and allow for some minor fast-path small-integer optimisations based on the fact that we'd be able to assume that presence of *two* extra bits in the C integer type rather than just one. As an example of the latter: if `a` and `b` are PyLongs that fit in a single digit, then with 15-bit digits and a 16-bit `digit` and `sdigit` type, `a + b` can't currently safely (i.e., without undefined behaviour from overflow) be computed with the C type `sdigit`. With 30-bit digits and a 32-bit `digit` and `sdigit` type, `a + b` is safe. Mark *References* Related b.p.o. issue: https://bugs.python.org/issue45569 MinGW compatibility issue: https://bugs.python.org/issue35037 Introduction of 30-bit digits: https://bugs.python.org/issue4258

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PEP 674: Disallow using macros as l-value
by Victor Stinner Jan. 12, 2022

Jan. 12, 2022

Hi, I propose to disallow using macros as l-value. Read and comment the plain text below, or read the PEP 674 online, https://python.github.io/peps/pep-0674/ While I'm not sure that the proposed changes are really controversial, I decided to write a formal PEP since the incompatible changes are not following the PEP 387 deprecation process and so a format PEP 387 exception is better. Well, the list of modified macros is also quite long. Moreover, a PEP is a way to document and announce the changes ;-) The Py_TYPE() and Py_SIZE() changes are already approved the Steering Council, but I prefer to list them in the PEP: https://github.com/python/steering-council/issues/79 In practice, I'm only aware of 4 projects impacted by these changes, and I wrote the pythoncapi_compat project which updates automatically C extensions: add Python 3.11 support, without losing support for older Python versions. I already prepared major projects like Cython and numpy for these changes (in total, 14 impacted projects have already been updated). Victor --- PEP: 674 Title: Disallow using macros as l-value Author: Victor Stinner <vstinner(a)python.org> Status: Draft Type: Standards Track Content-Type: text/x-rst Created: 30-Oct-2021 Python-Version: 3.11 Abstract ======== Incompatible C API change disallowing using macros as l-value to allow evolving CPython internals and to ease the C API implementation on other Python implementation. In practice, the majority of projects impacted by these incompatible changes should only have to make two changes: * Replace ``Py_TYPE(obj) = new_type;`` with ``Py_SET_TYPE(obj, new_type);``. * Replace ``Py_SIZE(obj) = new_size;`` with ``Py_SET_SIZE(obj, new_size);``. Rationale ========= Using a macro as a l-value -------------------------- In the Python C API, some functions are implemented as macro because writing a macro is simpler than writing a regular function. If a macro exposes directly a struture member, it is technically possible to use this macro to not only get the structure member but also set it. Example with the Python 3.10 ``Py_TYPE()`` macro:: #define Py_TYPE(ob) (((PyObject *)(ob))->ob_type) This macro can be used as a **r-value** to **get** an object type:: type = Py_TYPE(object); It can also be used as **l-value** to **set** an object type:: Py_TYPE(object) = new_type; It is also possible to set an object reference count and an object size using ``Py_REFCNT()`` and ``Py_SIZE()`` macros. Setting directly an object attribute relies on the current exact CPython implementation. Implementing this feature in other Python implementations can make their C API implementation less efficient. CPython nogil fork ------------------ Sam Gross forked Python 3.8 to remove the GIL: the `nogil branch <https://github.com/colesbury/nogil/>`_. This fork has no ``PyObject.ob_refcnt`` member, but a more elaborated implementation for reference counting, and so the ``Py_REFCNT(obj) = new_refcnt;`` code fails with a compiler error. Merging the nogil fork into the upstream CPython main branch requires first to fix this C API compatibility issue. It is a concrete example of a Python optimization blocked indirectly by the C API. This issue was already fixed in Python 3.10: the ``Py_REFCNT()`` macro has been already modified to disallow using it as a l-value. HPy project ----------- The `HPy project <https://hpyproject.org/>`_ is a brand new C API for Python using only handles and function calls: handles are opaque, structure members cannot be accessed directly,and pointers cannot be dereferenced. Disallowing the usage of macros as l-value helps the migration of existing C extensions to HPy by reducing differences between the C API and the HPy API. PyPy cpyext module ------------------ In PyPy, when a Python object is accessed by the Python C API, the PyPy ``cpyext`` module has to convert PyPy object to a CPython object. While PyPy objects are designed to be efficient with the PyPy JIT compiler, CPython objects are less efficient and increase the memory usage. This PEP alone is not enough to get rid of the CPython objects in the PyPy ``cpyext`` module, but it is a step towards this long term goal. PyPy already supports HPy which is a better solution in the long term. Specification ============= Disallow using macros as l-value -------------------------------- PyObject and PyVarObject macros ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ * ``Py_TYPE()``: ``Py_SET_TYPE()`` must be used instead * ``Py_SIZE()``: ``Py_SET_SIZE()`` must be used instead "GET" macros ^^^^^^^^^^^^ * ``PyByteArray_GET_SIZE()`` * ``PyBytes_GET_SIZE()`` * ``PyCFunction_GET_CLASS()`` * ``PyCFunction_GET_FLAGS()`` * ``PyCFunction_GET_FUNCTION()`` * ``PyCFunction_GET_SELF()`` * ``PyCell_GET()`` * ``PyCode_GetNumFree()`` * ``PyDict_GET_SIZE()`` * ``PyFunction_GET_ANNOTATIONS()`` * ``PyFunction_GET_CLOSURE()`` * ``PyFunction_GET_CODE()`` * ``PyFunction_GET_DEFAULTS()`` * ``PyFunction_GET_GLOBALS()`` * ``PyFunction_GET_KW_DEFAULTS()`` * ``PyFunction_GET_MODULE()`` * ``PyHeapType_GET_MEMBERS()`` * ``PyInstanceMethod_GET_FUNCTION()`` * ``PyList_GET_SIZE()`` * ``PyMemoryView_GET_BASE()`` * ``PyMemoryView_GET_BUFFER()`` * ``PyMethod_GET_FUNCTION()`` * ``PyMethod_GET_SELF()`` * ``PySet_GET_SIZE()`` * ``PyTuple_GET_SIZE()`` * ``PyUnicode_GET_DATA_SIZE()`` * ``PyUnicode_GET_LENGTH()`` * ``PyUnicode_GET_LENGTH()`` * ``PyUnicode_GET_SIZE()`` * ``PyWeakref_GET_OBJECT()`` "AS" macros ^^^^^^^^^^^ * ``PyByteArray_AS_STRING()`` * ``PyBytes_AS_STRING()`` * ``PyFloat_AS_DOUBLE()`` * ``PyUnicode_AS_DATA()`` * ``PyUnicode_AS_UNICODE()`` PyUnicode macros ^^^^^^^^^^^^^^^^ * ``PyUnicode_1BYTE_DATA()`` * ``PyUnicode_2BYTE_DATA()`` * ``PyUnicode_4BYTE_DATA()`` * ``PyUnicode_DATA()`` * ``PyUnicode_IS_ASCII()`` * ``PyUnicode_IS_COMPACT()`` * ``PyUnicode_IS_READY()`` * ``PyUnicode_KIND()`` * ``PyUnicode_READ()`` * ``PyUnicode_READ_CHAR()`` PyDateTime "GET" macros ^^^^^^^^^^^^^^^^^^^^^^^ * ``PyDateTime_DATE_GET_FOLD()`` * ``PyDateTime_DATE_GET_HOUR()`` * ``PyDateTime_DATE_GET_MICROSECOND()`` * ``PyDateTime_DATE_GET_MINUTE()`` * ``PyDateTime_DATE_GET_SECOND()`` * ``PyDateTime_DATE_GET_TZINFO()`` * ``PyDateTime_DELTA_GET_DAYS()`` * ``PyDateTime_DELTA_GET_MICROSECONDS()`` * ``PyDateTime_DELTA_GET_SECONDS()`` * ``PyDateTime_GET_DAY()`` * ``PyDateTime_GET_MONTH()`` * ``PyDateTime_GET_YEAR()`` * ``PyDateTime_TIME_GET_FOLD()`` * ``PyDateTime_TIME_GET_HOUR()`` * ``PyDateTime_TIME_GET_MICROSECOND()`` * ``PyDateTime_TIME_GET_MINUTE()`` * ``PyDateTime_TIME_GET_SECOND()`` * ``PyDateTime_TIME_GET_TZINFO()`` PyDescr macros ^^^^^^^^^^^^^^ * ``PyDescr_NAME()`` * ``PyDescr_TYPE()`` Port C extensions to Python 3.11 -------------------------------- In practice, the majority of projects impacted by these PEP incompatible changes should only have to make two changes: * Replace ``Py_TYPE(obj) = new_type;`` with ``Py_SET_TYPE(obj, new_type);``. * Replace ``Py_SIZE(obj) = new_size;`` with ``Py_SET_SIZE(obj, new_size);``. The `pythoncapi_compat project <https://github.com/pythoncapi/pythoncapi_compat>`_ can be used to update automatically C extensions: add Python 3.11 support without losing support with older Python versions. The project provides a header file which provides ``Py_SET_REFCNT()``, ``Py_SET_TYPE()`` and ``Py_SET_SIZE()`` functions to Python 3.8 and older. PyTuple_GET_ITEM() and PyList_GET_ITEM() ---------------------------------------- The ``PyTuple_GET_ITEM()`` and ``PyList_GET_ITEM()`` macros are left unchanged. The code pattern ``&PyTuple_GET_ITEM(tuple, 0)`` and ``&PyList_GET_ITEM(list, 0)`` is still commonly used to get access to the inner ``PyObject**`` array. Changing these macros would require to add a new API to get access to the inner array which is out of the scope of this PEP. Backwards Compatibility ======================= The proposed C API changes are backward incompatible on purpose. In practice, only a minority of third party projects are affected (16 projects are known to be broken) and `most of them have already been updated for these changes <https://bugs.python.org/issue39573#msg401378>`__ (12 on 16). Most projects are broken by ``Py_TYPE()`` and ``Py_SIZE()`` changes. These two macros have been converted to static inline macro in Python 3.10 alpha versions, but the change had to be reverted since it broke too many projects. In the meanwhile, many projects, like Cython, have been prepared for this change by using ``Py_SET_TYPE()`` and ``Py_SET_SIZE()``. For example, projects using Cython only have to regenerate their outdated generated C code to become compatible. For the "GET" functions like ``PyDict_GET_SIZE()``, no project in the PyPI top 5000 projects use these functions as l-value. The ``PyFloat_AS_DOUBLE()`` function is not used as a l-value in the PyPI top 5000 projects. The ``PyBytes_AS_STRING()`` and ``PyByteArray_AS_STRING()`` are used as l-value but only to modify string characters, not to override the ``PyBytesObject.ob_sval`` or ``PyByteArrayObject.ob_start`` member. For example, Cython uses the following code which remains valid:: PyByteArray_AS_STRING(string)[i] = (char) v; This change does not follow the PEP 387 deprecation process. There is no known way to emit a deprecation warning when a macro is used as a l-value, but not when it's used differently (ex: r-value). Rejected Idea: Leave the macros as they are =========================================== The documentation of each function can discourage developers to use macros to modify Python objects. If these is a need to make an assignment, a setter function can be added and the macro documentation can require to use the setter function. For example, a ``Py_SET_TYPE()`` function has been added to Python 3.9 and the ``Py_TYPE()`` documentation now requires to use the ``Py_SET_TYPE()`` function to set an object type. If developers use macros as l-value, it's their responsibility when their code breaks, not the Python responsibility. We are operating under the consenting adults principle: we expect users of the Python C API to use it as documented and expect them to take care of the fallout, if things break when they don't. This idea was rejected because only few developers read the documentation, and only a minority is tracking changes of the Python C API documentation. The majority of developers are only using CPython and so are not aware of compatibility issues with other Python implementations. Moreover, continuing to allow using macros as l-value does not solve issues of the nogil, PyPy and HPy projects. Macros already modified ======================= The following C API macros have already been modified to disallow using them as l-value: * ``PyCell_SET()`` * ``PyList_SET_ITEM()`` * ``PyTuple_SET_ITEM()`` * ``Py_REFCNT()`` (Python 3.10): ``Py_SET_REFCNT()`` must be used * ``_PyGCHead_SET_FINALIZED()`` * ``_PyGCHead_SET_NEXT()`` * ``asdl_seq_GET()`` * ``asdl_seq_GET_UNTYPED()`` * ``asdl_seq_LEN()`` * ``asdl_seq_SET()`` * ``asdl_seq_SET_UNTYPED()`` For example, ``PyList_SET_ITEM(list, 0, item) < 0`` now fails with a compiler error as expected. References ========== * `Python C API: Add functions to access PyObject <https://vstinner.github.io/c-api-abstract-pyobject.html>`_ (October 2021) article by Victor Stinner * `[C API] Disallow using PyFloat_AS_DOUBLE() as l-value <https://bugs.python.org/issue45476>`_ (October 2021) * `[capi-sig] Py_TYPE() and Py_SIZE() become static inline functions <https://mail.python.org/archives/list/capi-sig@python.org/thread/WGRLTHTHC3…>`_ (September 2021) * `[C API] Avoid accessing PyObject and PyVarObject members directly: add Py_SET_TYPE() and Py_IS_TYPE(), disallow Py_TYPE(obj)=type <https://bugs.python.org/issue39573>`__ (February 2020) * `bpo-30459: PyList_SET_ITEM could be safer <https://bugs.python.org/issue30459>`_ (May 2017) Copyright ========= This document is placed in the public domain or under the CC0-1.0-Universal license, whichever is more permissive.

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my plans for subinterpreters (and a per-interpreter GIL)
by Eric Snow Jan. 6, 2022

Jan. 6, 2022

Hi all, I'm still hoping to land a per-interpreter GIL for 3.11. There is still a decent amount of work to be done but little of it will require solving any big problems: * pull remaining static globals into _PyRuntimeState and PyInterpreterState * minor updates to PEP 554 * finish up the last couple pieces of the PEP 554 implementation * maybe publish a companion PEP about per-interpreter GIL There are also a few decisions to be made. I'll open a couple of other threads to get feedback on those. Here I'd like your thoughts on the following: Do we need a PEP about per-interpreter GIL? I haven't thought there would be much value in such a PEP. There doesn't seem to be any decision that needs to be made. At best the PEP would be an explanation of the project, where: * the objective has gotten a lot of support (and we're working on addressing the concerns of the few objectors) * most of the required work is worth doing regardless (e.g. improve runtime init/fini, eliminate static globals) * the performance impact is likely to be a net improvement * it is fully backward compatible and the C-API is essentially unaffected So the value of a PEP would be in consolidating an explanation of the project into a single document. It seems like a poor fit for a PEP. (You might wonder, "what about PEP 554?" I purposefully avoided any discussion of the GIL in PEP 554. It's purpose is to expose subinterpreters to Python code.) However, perhaps I'm too close to it all. I'd like your thoughts on the matter. Thanks! -eric

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Function Prototypes
by asleep.cult＠gmail.com Jan. 5, 2022

Jan. 5, 2022

Hello In thread about PEP 677, I (with the help of another proposal) came up with an alternative to typing.Callable called function prototypes. The basic concept is to create a function prototype object when the body of a function is omitted. The thread can be found here: https://mail.python.org/archives/list/python-dev@python.org/thread/OGACYN2X… Mark Shannon initially proposed that functions be used as types and provided this example: @Callable def IntToIntFunc(a:int)->int: pass def flat_map( l: list[int], func: IntToIntFunc ) -> list[int]: .... I further proposed that we make the body of a function non-mandatory and create a function prototype if it is omitted. I provided these examples: import typing @typing.Callable def IntToIntFunc(a: int) -> int def flat_map( l: list[int], func: IntToIntFunc ) -> list[int]: ... import ctypes @ctypes.CFUNCTYPE def f(x: int) -> bool I have since taken it upon myself to implement this in a fork of cpython: https://github.com/asleep-cult/cpython To remain consistent with function definitions, I have also added an alternative lambda syntax that allows you to annotate arguments and the return type. The syntax requires you to parenthesize the argument list: lambda (a: int, b: int) -> int: ... This new lambda syntax also allows you to create a function prototype by omitting the body. The original example can be rewritten as follows: def flat_map( l: list[int], func: lambda (a: int) -> int ) -> list[int]: ... Problems: - It is not possible to use ParamSpec with this - The lambda prototype syntax might be jarring - Some people might accidentally forget the function body Here is some feedback that I have already collected: "Yeah, making the body optional (without looking at decorators) is not acceptable either. Too easy to do by mistake (I still do this All. The. Time. :-)" - Guido van Rossum "i would strongly prefer this over the existing pep" - Ronny Pfannschmidt "I find this unnecessary and unreadable. Python isn't C or Java." - BundleOfJoysticks (Reddit)

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RFC on Callable Syntax PEP
by Steven Troxler Jan. 4, 2022

Jan. 4, 2022

Hello all, Thanks everyone for comments on our earlier thread [1] about callable type syntax. We now have a draft PEP [2] proposing an arrow-based syntax for callable types, for example: ``` (int, str) -> bool # equivalent to Callable[[int, str], bool] ``` In support of the PEP we also have: - a reference implementation of the parser [3] to ensure the grammar is correct (tests [5], [6], [7]) - a detailed specification of planned runtime behavior [4], which is not yet in the reference implementation We'd like to get your feedback about the PEP in general, and especially details and edge cases we need to consider regarding runtime behavior. Cheers, Steven Troxler --------- [1] Earlier python-dev thread https://mail.python.org/archives/list/python-dev@python.org/thread/VBHJOS3L… [2] PEP 677: https://www.python.org/dev/peps/pep-0677/ [3] Reference implementation of Parser: https://github.com/stroxler/cpython/tree/callable-type-syntax--shorthand [4] Details on the runtime behavior: https://docs.google.com/document/d/15nmTDA_39Lo-EULQQwdwYx_Q1IYX4dD5WPnHbFG… [5] Ast tests for parser changes: https://github.com/stroxler/cpython/blob/20eb59fdca0d6d8dbe4efa3b04038c7c22… [6] Easy-read tests of examples from the PEP: https://github.com/stroxler/cpython/blob/callable-type-syntax--shorthand/Li… [7] Test sanity checking hundreds of examples pulled from typeshed: https://github.com/stroxler/cpython/blob/callable-type-syntax--shorthand/Li…

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