Mailman 3 September 2022 - Python-Dev

Proposal: Allow non-default after default arguments
by Sebastian Rittau 16 Oct '23

16 Oct '23

Currently, Python doesn't allow non-default arguments after default arguments: >>> def foo(x=None, y): pass File "<stdin>", line 1 def foo(x=None, y): pass ^ SyntaxError: non-default argument follows default argument I believe that at the time this was introduced, no use cases for this were known and this is is supposed to prevent a source of bugs. I have two use cases for this, one fringe, but valid, the other more important: The fringe use case: Suppose you have a function that takes a 2D coordinate value as separate "x" and "y" arguments. The "x" argument is optional, the "y" argument isn't. Currently there are two ways to do this, none of them particularly great: def foo(y, x): # reverse x and y arguments, confusing ... def foo(x, y=None): # Treat the x argument as y if only one argument is provided if y is None: x, y = y, x ... To me, the "natural" solution looks like this: def foo(x=None, y): ... # Called like this: foo(1, 2) foo(y=2) This could also be useful when evolving APIs. For example there is a function "bar" that takes two required arguments. In a later version, the first argument gains a useful default, the second doesn't. There is no sensible way to evolve the API at the moment. The more important use case involves @overloads. A condensed example of a function where the return type depends on an "encoding" parameter, followed by further parameters that could be called like this: foo(123, "utf-8") # would return bytes foo(encoding="utf-8") foo(123, None) # would return str foo(encoding=None) foo(x=123) # would return str foo() This could ideally be written as: @overload def foo(x: int = ..., encoding: None = ...) -> str: ... @overload def foo(x: int = ..., encoding: str) -> bytes: ... # plus the actual implementation But due to the syntax constraint, this needs to be hacked around with a third overload: @overload def foo(x: int = ... encoding: None = ...) -> str: ... @overload def foo(x: int, encoding: str) -> bytes: ... # for foo(123, "utf-8") @overload def foo(*, encoding: str) -> bytes: ... # for foo(encoding="utf-8") Not only is this hard to read, real examples in typeshed are usually more complex, with many arguments before or after the affected argument or even multiple affected arguments. This often becomes too complex to write or maintain. Here is one example from the wild: https://github.com/python/typeshed/blob/b95b729b9e07ab21d252701af0f5b740467… Allowing non-default arguments after default arguments would solve both use cases above and eliminates a special case. I'm also not sure what exactly the current SyntaxError really protects us from. Adding a non-default after a default argument can't really lead bugs. - Sebastian

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Python multithreading without the GIL
by Sam Gross 31 Jul '23

31 Jul '23

Hi, I've been working on changes to CPython to allow it to run without the global interpreter lock. I'd like to share a working proof-of-concept that can run without the GIL. The proof-of-concept involves substantial changes to CPython internals, but relatively few changes to the C-API. It is compatible with many C extensions: extensions must be rebuilt, but usually require small or no modifications to source code. I've built compatible versions of packages from the scientific Python ecosystem, and they are installable through the bundled "pip". Source code: https://github.com/colesbury/nogil Design overview: https://docs.google.com/document/d/18CXhDb1ygxg-YXNBJNzfzZsDFosB5e6BfnXLlej… My goal with the proof-of-concept is to demonstrate that removing the GIL is feasible and worthwhile, and that the technical ideas of the project could serve as a basis of such an effort. I'd like to start a discussion about these ideas and gauge the community's interest in this approach to removing the GIL. Regards, Sam Gross colesbury(a)gmail.com / sgross(a)fb.com

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Mixed Python/C debugging
by Skip Montanaro 26 Apr '23

26 Apr '23

Having tried comp.lang.python with no response, I turn here... After at least ten years away from Python's run-time interpreter & byte code compiler, I'm getting set to familiarize myself with that again. This will, I think, entail debugging a mixed Python/C environment. I'm an Emacs user and am aware that GDB since 7.0 has support for debugging at the Python code level. Is Emacs+GDB my best bet? Are there any Python IDEs which support C-level breakpoints and debugging? Thanks, Skip

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PEP 448 review
by Guido van Rossum 29 Mar '23

29 Mar '23

I'm back, I've re-read the PEP, and I've re-read the long thread with "(no subject)". I think Georg Brandl nailed it: """ *I like the "sequence and dict flattening" part of the PEP, mostly because itis consistent and should be easy to understand, but the comprehension syntaxenhancements seem to be bad for readability and "comprehending" what the codedoes.The call syntax part is a mixed bag on the one hand it is nice to be consistent with the extended possibilities in literals (flattening), but on the other hand there would be small but annoying inconsistencies anyways (e.g. the duplicate kwarg case above).* """ Greg Ewing followed up explaining that the inconsistency between dict flattening and call syntax is inherent in the pre-existing different rules for dicts vs. keyword args: {'a':1, 'a':2} results in {'a':2}, while f(a=1, a=2) is an error. (This form is a SyntaxError; the dynamic case f(a=1, **{'a': 1}) is a TypeError.) For me, allowing f(*a, *b) and f(**d, **e) and all the other combinations for function calls proposed by the PEP is an easy +1 -- it's a straightforward extension of the existing pattern, and anybody who knows what f(x, *a) does will understand f(x, *a, y, *b). Guessing what f(**d, **e) means shouldn't be hard either. Understanding the edge case for duplicate keys with f(**d, **e) is a little harder, but the error messages are pretty clear, and it is not a new edge case. The sequence and dict flattening syntax proposals are also clean and logical -- we already have *-unpacking on the receiving side, so allowing *x in tuple expressions reads pretty naturally (and the similarity with *a in argument lists certainly helps). From here, having [a, *x, b, *y] is also natural, and then the extension to other displays is natural: {a, *x, b, *y} and {a:1, **d, b:2, **e}. This, too, gets a +1 from me. So that leaves comprehensions. IIRC, during the development of the patch we realized that f(*x for x in xs) is sufficiently ambiguous that we decided to disallow it -- note that f(x for x in xs) is already somewhat of a special case because an argument can only be a "bare" generator expression if it is the only argument. The same reasoning doesn't apply (in that form) to list, set and dict comprehensions -- while f(x for x in xs) is identical in meaning to f((x for x in xs)), [x for x in xs] is NOT the same as [(x for x in xs)] (that's a list of one element, and the element is a generator expression). The basic premise of this part of the proposal is that if you have a few iterables, the new proposal (without comprehensions) lets you create a list or generator expression that iterates over all of them, essentially flattening them: >>> xs = [1, 2, 3] >>> ys = ['abc', 'def'] >>> zs = [99] >>> [*xs, *ys, *zs] [1, 2, 3, 'abc', 'def', 99] >>> But now suppose you have a list of iterables: >>> xss = [[1, 2, 3], ['abc', 'def'], [99]] >>> [*xss[0], *xss[1], *xss[2]] [1, 2, 3, 'abc', 'def', 99] >>> Wouldn't it be nice if you could write the latter using a comprehension? >>> xss = [[1, 2, 3], ['abc', 'def'], [99]] >>> [*xs for xs in xss] [1, 2, 3, 'abc', 'def', 99] >>> This is somewhat seductive, and the following is even nicer: the *xs position may be an expression, e.g.: >>> xss = [[1, 2, 3], ['abc', 'def'], [99]] >>> [*xs[:2] for xs in xss] [1, 2, 'abc', 'def', 99] >>> On the other hand, I had to explore the possibilities here by experimenting in the interpreter, and I discovered some odd edge cases (e.g. you can parenthesize the starred expression, but that seems a syntactic accident). All in all I am personally +0 on the comprehension part of the PEP, and I like that it provides a way to "flatten" a sequence of sequences, but I think very few people in the thread have supported this part. Therefore I would like to ask Neil to update the PEP and the patch to take out the comprehension part, so that the two "easy wins" can make it into Python 3.5 (basically, I am accepting two-thirds of the PEP :-). There is some time yet until alpha 2. I would also like code reviewers (Benjamin?) to start reviewing the patch <http://bugs.python.org/issue2292>, taking into account that the comprehension part needs to be removed. -- --Guido van Rossum (python.org/~guido)

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PEP 638: Syntactic macros
by Mark Shannon 05 Feb '23

05 Feb '23

Hi everyone, I've submitted my PEP on syntactic macros as PEP 638. https://www.python.org/dev/peps/pep-0638/ All comments and suggestions are welcome. Cheers, Mark

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Switching to Discourse
by Petr Viktorin 26 Jan '23

26 Jan '23

Hello, Currently development discussions are split between multiple communication channels, for example: - python-dev and discuss.python.org for design discussions, - GitHub Issues and Pull Requests for specific changes, - IRC, Discord and private chats for real-time discussions, - Topic-specific channels like typing-sig. While most of these serve different needs, there is too much overlap between python-dev and discuss.python.org. It seems that for most people, this situation is worse than sticking to either one platform – even if we don't go with that person's favorite. The discuss.python.org experiment has been going on for quite a while, and while the platform is not without its issues, we consider it a success. The Core Development category is busier than python-dev. According to staff, discuss.python.org is much easier to moderate.. If you're following python-dev but not discuss.python.org, you're missing out. The Steering Council would like to switch from python-dev to discuss.python.org. Practically, this means: - Moving the required PEP announcements to discuss.python.org - Moving discuss.python.org up in the devguide communications page (https://devguide.python.org/communication/) - And that's it? I imagine that the mailing list will stay around for continuing past discussion threads and for announcements, eventually switching to auto-reject incoming messages with a pointer to discuss.python.org. To be clear, discuss.python.org allows editing posts, which is frankly handy for typos and clarifications. Editing alone should not be used for adding new info -- we should cultivate a culture of being friendly to mail users & notification watchers. This probably bears repeating in a few places. We're aware not everyone wants to use the discuss.python.org website, but there are some ways to avoid it: - For new PEPs, you can point your RSS client to https://www.python.org/dev/peps/peps.rss – it's not e-mail, but many email clients have RSS support. You can also watch the Steering Council issues on GitHub (https://github.com/python/steering-council/issues/) for important questions and discussions. - You can use discuss.python.org's “mailing list mode” (which subscribes you to all new posts), possibly with filtering and/or categorizing messages locally. However, we would like to know if this will pose an undue burden to anyone, if there are workflows or usage problems that we are not aware of. As mentioned, this is something the Steering Council thinks is a good idea, but we want to make sure we're aware of all the impact when we make the final decision. – Petr, on behalf of the Steering Council

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How about using modern C++ in development of CPython ?
by redradist＠gmail.com 19 Oct '22

19 Oct '22

Hi all, What about of using modern C++ in developing CPython ? With C++ we can get the following benefits: 1) Readability - less code, most code is hidden by abstraction without losing performance 2) Maintainability - no code duplication in favor of using reusable classes 3) RAII - Resource Acquisition Is Initialization, predictable allocation and free resources ...

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Moving to Discourse
by Petr Viktorin 23 Sep '22

23 Sep '22

As mentioned previously [0], the Steering Council decided to switch from python-dev to Discourse (discuss.python.org). We're aware that Discourse is not perfect. The previous mail thread [0] lists various shortcomings, as well as some workarounds. However, we don't see anything that would block Python development. Practically, the switch means that: - New PEPs should be announced in the PEPs category on Discourse (rather than on this list), and - The Devguide will list Discourse, rather than mailing lists, as the primary communication channel. Note that you can have development-related discussions anywhere, as long as you (eventually) include all relevant people. You're welcome to continue using python-dev and other mailing lists, IRC, in-person sprints, etc. But for PEP-level changes, we believe python-dev no longer reaches the proper audience. For the related docs changes, see [peps-2775] and [devguide-945]. Note that this is documentation, not law – if something is unclear or doesn't make sense, please ask for clarification or propose edits. [0]: https://mail.python.org/archives/list/python-dev@python.org/thread/VHFLDK43… [peps-2775]: https://github.com/python/peps/pull/2775 [devguide-945]: https://github.com/python/devguide/pull/945 — Petr, on behalf of the Steering Council

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PEP 505 (None-aware operators) for Python 3.11
by Doug Swarin 21 Sep '22

21 Sep '22

Hello, I've been following PEP 505 (https://www.python.org/dev/peps/pep-0505/) since it was first proposed for Python 3.8. It's been deferred for some time and I'm interested in seeing it in Python 3.11, but I know there were also a number of objections which resulted in it being deferred (including by one of the original authors, Mr. Dower). I did email both Mr. Dower and Mr. Haase and they graciously gave me their permission to bring it up on this list for discussion and hopefully final pronouncement one way or the other. I personally believe that the PEP will result in a significant reduction in boilerplate code, and it is substantially similar to the same operators now found in a number of other languages, especially C# and JavaScript (https://wikipedia.org/wiki/Null_coalescing_operator and https://wikipedia.org/wiki/Safe_navigation_operator). I believe strong and valid arguments can be made about the use of None being a fundamental flaw in some types of coding (and that adding additional support for it to the language will increase the use of None in this way), but I also believe there are many use cases in programming where it is by far the simplest way to express various semantics, and the fact exists that None is already used extensively in large quantities of code, and further that there is already a great deal of code written to constantly test against None and break out of a statement without throwing an error. I also understand the argument that especially the maybe-dot (?.) and maybe-subscript (?[) operators can decrease readability of code and also believe these are valid arguments against it. While I believe the existence and use of these operators in other languages definitely helps the case that these can be used and understood successfully, I think it is entirely valid to either consider other syntax (though I prefer the chosen syntax of PEP 505), or even to reduce PEP 505 to having only the coalesce operator (??) and the maybe-assign operator (??=). Separately, I have implemented a pure-Python solution for PEP505 (which is definitely rather beta) which might help test the waters for a final implementation in CPython (though the CPython implementation would of course be much more efficient). It can be found at https://pypi.org/project/pep505/ Thanks, Doug

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Annotating pure functions to improve inline caching/optimization
by Philipp Burch 19 Sep '22

19 Sep '22

Hello everyone, the docs on the upcoming 3.11 release state > This [specializing adaptive interpreter] also brings in another concept called inline caching, where Python caches the results of expensive operations directly in the bytecode. I wonder how this caching works, given that the dynamic nature means that virtually every operation could have side effects, causing wrong behaviour when cached. The only mitigation for this that I can imagine is that caching just occurs for basic operations defined in the standard library, where it is known that they are free of side effects or "pure". A web search did reveal some discussions[1,2] and a module related to dealing with pure functions, but, as far as I see, not related to optimization. As an example, consider a code like this: ```py @pure def rot_factor(angle_deg: float) -> complex: # This could also be a much more expensive calculation. return cmath.exp(angle_deg / 180 * cmath.pi * 1j) # ... res: List[Tuple(complex, complex, complex, float)] = [] for x in many: res.append(( x * rot_factor(90), x * rot_factor(45), x * rot_factor(-45), x * math.sin(math.pi/8), )) ``` The problem with this code is obvious, every loop iteration calls `rot_factor()` with 90, 45 and -45 and will get exactly the same set of results. The last factor might already be inline cached by the interpreter, since it probably knows that `math.pi` is a constant and `math.sin()` is a pure function. Optimizing this by hand (not considering a list comprehension or other more sophisticated improvements) is easy, but not very pretty: ```py f_p90 = rot_factor(90) f_p45 = rot_factor(45) f_m45 = rot_factor(-45) f_sin = math.sin(math.pi / 8) res: List[Tuple(complex, complex, complex, float)] = [] for x in many: res.append(( x * f_p90, x * f_p45, x * f_m45, x * f_sin, )) ``` I actually find myself often factoring such data out of loops in Python, whereas in C I would just leave that to the optimizer/compiler. An available option would be to use `@lru_cache` for `rot_factor()`, but this will still cause the same dictionary lookups in every iteration and it may not work at all in case the function argument(s) is/are not hashable. Now, if the interpreter understood the `@pure` decorator for `rot_factor()` indicated above would give it the same opportunity to cache the three results throughout the loop, basically creating the manually-optimized code above. For these completely static values, it could even precompute the results and integrate them into the bytecode. Has anything like this been considered already, or is the interpreter itself capable to perform such optimizations? Thanks and best regards, Philipp [1] 'pure' type annotation for mypy: https://github.com/python/mypy/issues/4468 [2] pure-func module: https://pypi.org/project/pure-func/

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