Python-Dev March 2021

python-dev@python.org

96 participants
62 discussions

PEP 646 (Variadic Generics): final call for comments

by Matthew Rahtz

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and let us know your thoughts: https://www.python.org/dev/peps/pep-0646/ (Note that the final couple of sections are out of date; https://github.com/python/peps/pull/1880 clarifies which grammar changes would be required, now that PEP 637 has been rejected.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

2 months, 1 week

Speeding up CPython

by Mark Shannon

Hi everyone, CPython is slow. We all know that, yet little is done to fix it. I'd like to change that. I have a plan to speed up CPython by a factor of five over the next few years. But it needs funding. I am aware that there have been several promised speed ups in the past that have failed. You might wonder why this is different. Here are three reasons: 1. I already have working code for the first stage. 2. I'm not promising a silver bullet. I recognize that this is a substantial amount of work and needs funding. 3. I have extensive experience in VM implementation, not to mention a PhD in the subject. My ideas for possible funding, as well as the actual plan of development, can be found here: https://github.com/markshannon/faster-cpython I'd love to hear your thoughts on this. Cheers, Mark.

5 months

PEP 1, PEP Purpose and Guidelines

by barry＠zope.com

It has been a while since I posted a copy of PEP 1 to the mailing lists and newsgroups. I've recently done some updating of a few sections, so in the interest of gaining wider community participation in the Python development process, I'm posting the latest revision of PEP 1 here. A version of the PEP is always available on-line at http://www.python.org/peps/pep-0001.html Enjoy, -Barry -------------------- snip snip -------------------- PEP: 1 Title: PEP Purpose and Guidelines Version: $Revision: 1.36 $ Last-Modified: $Date: 2002/07/29 18:34:59 $ Author: Barry A. Warsaw, Jeremy Hylton Status: Active Type: Informational Created: 13-Jun-2000 Post-History: 21-Mar-2001, 29-Jul-2002 What is a PEP? PEP stands for Python Enhancement Proposal. A PEP is a design document providing information to the Python community, or describing a new feature for Python. The PEP should provide a concise technical specification of the feature and a rationale for the feature. We intend PEPs to be the primary mechanisms for proposing new features, for collecting community input on an issue, and for documenting the design decisions that have gone into Python. The PEP author is responsible for building consensus within the community and documenting dissenting opinions. Because the PEPs are maintained as plain text files under CVS control, their revision history is the historical record of the feature proposal[1]. Kinds of PEPs There are two kinds of PEPs. A standards track PEP describes a new feature or implementation for Python. An informational PEP describes a Python design issue, or provides general guidelines or information to the Python community, but does not propose a new feature. Informational PEPs do not necessarily represent a Python community consensus or recommendation, so users and implementors are free to ignore informational PEPs or follow their advice. PEP Work Flow The PEP editor, Barry Warsaw <peps(a)python.org>, assigns numbers for each PEP and changes its status. The PEP process begins with a new idea for Python. It is highly recommended that a single PEP contain a single key proposal or new idea. The more focussed the PEP, the more successfully it tends to be. The PEP editor reserves the right to reject PEP proposals if they appear too unfocussed or too broad. If in doubt, split your PEP into several well-focussed ones. Each PEP must have a champion -- someone who writes the PEP using the style and format described below, shepherds the discussions in the appropriate forums, and attempts to build community consensus around the idea. The PEP champion (a.k.a. Author) should first attempt to ascertain whether the idea is PEP-able. Small enhancements or patches often don't need a PEP and can be injected into the Python development work flow with a patch submission to the SourceForge patch manager[2] or feature request tracker[3]. The PEP champion then emails the PEP editor <peps(a)python.org> with a proposed title and a rough, but fleshed out, draft of the PEP. This draft must be written in PEP style as described below. If the PEP editor approves, he will assign the PEP a number, label it as standards track or informational, give it status 'draft', and create and check-in the initial draft of the PEP. The PEP editor will not unreasonably deny a PEP. Reasons for denying PEP status include duplication of effort, being technically unsound, not providing proper motivation or addressing backwards compatibility, or not in keeping with the Python philosophy. The BDFL (Benevolent Dictator for Life, Guido van Rossum) can be consulted during the approval phase, and is the final arbitrator of the draft's PEP-ability. If a pre-PEP is rejected, the author may elect to take the pre-PEP to the comp.lang.python newsgroup (a.k.a. python-list(a)python.org mailing list) to help flesh it out, gain feedback and consensus from the community at large, and improve the PEP for re-submission. The author of the PEP is then responsible for posting the PEP to the community forums, and marshaling community support for it. As updates are necessary, the PEP author can check in new versions if they have CVS commit permissions, or can email new PEP versions to the PEP editor for committing. Standards track PEPs consists of two parts, a design document and a reference implementation. The PEP should be reviewed and accepted before a reference implementation is begun, unless a reference implementation will aid people in studying the PEP. Standards Track PEPs must include an implementation - in the form of code, patch, or URL to same - before it can be considered Final. PEP authors are responsible for collecting community feedback on a PEP before submitting it for review. A PEP that has not been discussed on python-list(a)python.org and/or python-dev(a)python.org will not be accepted. However, wherever possible, long open-ended discussions on public mailing lists should be avoided. Strategies to keep the discussions efficient include, setting up a separate SIG mailing list for the topic, having the PEP author accept private comments in the early design phases, etc. PEP authors should use their discretion here. Once the authors have completed a PEP, they must inform the PEP editor that it is ready for review. PEPs are reviewed by the BDFL and his chosen consultants, who may accept or reject a PEP or send it back to the author(s) for revision. Once a PEP has been accepted, the reference implementation must be completed. When the reference implementation is complete and accepted by the BDFL, the status will be changed to `Final.' A PEP can also be assigned status `Deferred.' The PEP author or editor can assign the PEP this status when no progress is being made on the PEP. Once a PEP is deferred, the PEP editor can re-assign it to draft status. A PEP can also be `Rejected'. Perhaps after all is said and done it was not a good idea. It is still important to have a record of this fact. PEPs can also be replaced by a different PEP, rendering the original obsolete. This is intended for Informational PEPs, where version 2 of an API can replace version 1. PEP work flow is as follows: Draft -> Accepted -> Final -> Replaced ^ +----> Rejected v Deferred Some informational PEPs may also have a status of `Active' if they are never meant to be completed. E.g. PEP 1. What belongs in a successful PEP? Each PEP should have the following parts: 1. Preamble -- RFC822 style headers containing meta-data about the PEP, including the PEP number, a short descriptive title (limited to a maximum of 44 characters), the names, and optionally the contact info for each author, etc. 2. Abstract -- a short (~200 word) description of the technical issue being addressed. 3. Copyright/public domain -- Each PEP must either be explicitly labelled as placed in the public domain (see this PEP as an example) or licensed under the Open Publication License[4]. 4. Specification -- The technical specification should describe the syntax and semantics of any new language feature. The specification should be detailed enough to allow competing, interoperable implementations for any of the current Python platforms (CPython, JPython, Python .NET). 5. Motivation -- The motivation is critical for PEPs that want to change the Python language. It should clearly explain why the existing language specification is inadequate to address the problem that the PEP solves. PEP submissions without sufficient motivation may be rejected outright. 6. Rationale -- The rationale fleshes out the specification by describing what motivated the design and why particular design decisions were made. It should describe alternate designs that were considered and related work, e.g. how the feature is supported in other languages. The rationale should provide evidence of consensus within the community and discuss important objections or concerns raised during discussion. 7. Backwards Compatibility -- All PEPs that introduce backwards incompatibilities must include a section describing these incompatibilities and their severity. The PEP must explain how the author proposes to deal with these incompatibilities. PEP submissions without a sufficient backwards compatibility treatise may be rejected outright. 8. Reference Implementation -- The reference implementation must be completed before any PEP is given status 'Final,' but it need not be completed before the PEP is accepted. It is better to finish the specification and rationale first and reach consensus on it before writing code. The final implementation must include test code and documentation appropriate for either the Python language reference or the standard library reference. PEP Template PEPs are written in plain ASCII text, and should adhere to a rigid style. There is a Python script that parses this style and converts the plain text PEP to HTML for viewing on the web[5]. PEP 9 contains a boilerplate[7] template you can use to get started writing your PEP. Each PEP must begin with an RFC822 style header preamble. The headers must appear in the following order. Headers marked with `*' are optional and are described below. All other headers are required. PEP: <pep number> Title: <pep title> Version: <cvs version string> Last-Modified: <cvs date string> Author: <list of authors' real names and optionally, email addrs> * Discussions-To: <email address> Status: <Draft | Active | Accepted | Deferred | Final | Replaced> Type: <Informational | Standards Track> * Requires: <pep numbers> Created: <date created on, in dd-mmm-yyyy format> * Python-Version: <version number> Post-History: <dates of postings to python-list and python-dev> * Replaces: <pep number> * Replaced-By: <pep number> The Author: header lists the names and optionally, the email addresses of all the authors/owners of the PEP. The format of the author entry should be address(a)dom.ain (Random J. User) if the email address is included, and just Random J. User if the address is not given. If there are multiple authors, each should be on a separate line following RFC 822 continuation line conventions. Note that personal email addresses in PEPs will be obscured as a defense against spam harvesters. Standards track PEPs must have a Python-Version: header which indicates the version of Python that the feature will be released with. Informational PEPs do not need a Python-Version: header. While a PEP is in private discussions (usually during the initial Draft phase), a Discussions-To: header will indicate the mailing list or URL where the PEP is being discussed. No Discussions-To: header is necessary if the PEP is being discussed privately with the author, or on the python-list or python-dev email mailing lists. Note that email addresses in the Discussions-To: header will not be obscured. Created: records the date that the PEP was assigned a number, while Post-History: is used to record the dates of when new versions of the PEP are posted to python-list and/or python-dev. Both headers should be in dd-mmm-yyyy format, e.g. 14-Aug-2001. PEPs may have a Requires: header, indicating the PEP numbers that this PEP depends on. PEPs may also have a Replaced-By: header indicating that a PEP has been rendered obsolete by a later document; the value is the number of the PEP that replaces the current document. The newer PEP must have a Replaces: header containing the number of the PEP that it rendered obsolete. PEP Formatting Requirements PEP headings must begin in column zero and the initial letter of each word must be capitalized as in book titles. Acronyms should be in all capitals. The body of each section must be indented 4 spaces. Code samples inside body sections should be indented a further 4 spaces, and other indentation can be used as required to make the text readable. You must use two blank lines between the last line of a section's body and the next section heading. You must adhere to the Emacs convention of adding two spaces at the end of every sentence. You should fill your paragraphs to column 70, but under no circumstances should your lines extend past column 79. If your code samples spill over column 79, you should rewrite them. Tab characters must never appear in the document at all. A PEP should include the standard Emacs stanza included by example at the bottom of this PEP. A PEP must contain a Copyright section, and it is strongly recommended to put the PEP in the public domain. When referencing an external web page in the body of a PEP, you should include the title of the page in the text, with a footnote reference to the URL. Do not include the URL in the body text of the PEP. E.g. Refer to the Python Language web site [1] for more details. ... [1] http://www.python.org When referring to another PEP, include the PEP number in the body text, such as "PEP 1". The title may optionally appear. Add a footnote reference that includes the PEP's title and author. It may optionally include the explicit URL on a separate line, but only in the References section. Note that the pep2html.py script will calculate URLs automatically, e.g.: ... Refer to PEP 1 [7] for more information about PEP style ... References [7] PEP 1, PEP Purpose and Guidelines, Warsaw, Hylton http://www.python.org/peps/pep-0001.html If you decide to provide an explicit URL for a PEP, please use this as the URL template: http://www.python.org/peps/pep-xxxx.html PEP numbers in URLs must be padded with zeros from the left, so as to be exactly 4 characters wide, however PEP numbers in text are never padded. Reporting PEP Bugs, or Submitting PEP Updates How you report a bug, or submit a PEP update depends on several factors, such as the maturity of the PEP, the preferences of the PEP author, and the nature of your comments. For the early draft stages of the PEP, it's probably best to send your comments and changes directly to the PEP author. For more mature, or finished PEPs you may want to submit corrections to the SourceForge bug manager[6] or better yet, the SourceForge patch manager[2] so that your changes don't get lost. If the PEP author is a SF developer, assign the bug/patch to him, otherwise assign it to the PEP editor. When in doubt about where to send your changes, please check first with the PEP author and/or PEP editor. PEP authors who are also SF committers, can update the PEPs themselves by using "cvs commit" to commit their changes. Remember to also push the formatted PEP text out to the web by doing the following: % python pep2html.py -i NUM where NUM is the number of the PEP you want to push out. See % python pep2html.py --help for details. Transferring PEP Ownership It occasionally becomes necessary to transfer ownership of PEPs to a new champion. In general, we'd like to retain the original author as a co-author of the transferred PEP, but that's really up to the original author. A good reason to transfer ownership is because the original author no longer has the time or interest in updating it or following through with the PEP process, or has fallen off the face of the 'net (i.e. is unreachable or not responding to email). A bad reason to transfer ownership is because you don't agree with the direction of the PEP. We try to build consensus around a PEP, but if that's not possible, you can always submit a competing PEP. If you are interested assuming ownership of a PEP, send a message asking to take over, addressed to both the original author and the PEP editor <peps(a)python.org>. If the original author doesn't respond to email in a timely manner, the PEP editor will make a unilateral decision (it's not like such decisions can be reversed. :). References and Footnotes [1] This historical record is available by the normal CVS commands for retrieving older revisions. For those without direct access to the CVS tree, you can browse the current and past PEP revisions via the SourceForge web site at http://cvs.sourceforge.net/cgi-bin/cvsweb.cgi/python/nondist/peps/?cvsroot=… [2] http://sourceforge.net/tracker/?group_id=5470&atid=305470 [3] http://sourceforge.net/tracker/?atid=355470&group_id=5470&func=browse [4] http://www.opencontent.org/openpub/ [5] The script referred to here is pep2html.py, which lives in the same directory in the CVS tree as the PEPs themselves. Try "pep2html.py --help" for details. The URL for viewing PEPs on the web is http://www.python.org/peps/ [6] http://sourceforge.net/tracker/?group_id=5470&atid=305470 [7] PEP 9, Sample PEP Template http://www.python.org/peps/pep-0009.html 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 End:

5 months

On the migration from master to main

by Python Steering Council

From Thomas Wouters, on behalf of and with full support of the Python Steering Council: This discussion seems to have died down a little, but I still want to make a few things clear: Yes, this is a political decision. Very many decisions are political. The existence of an open-source project is inherently political. The decision to try and make python-dev more welcoming, more open, more helpful is also a political decision -- one that the SC feels is absolutely necessary for the long-term health of the Python language. Not wanting to be bothered by political decisions is a political decision; it’s a decision that you’re happy with politics as they are. I’m afraid you can’t avoid politics. This isn’t just about ‘master’ being rooted in slavery. This is about what the community sees and does. As I mentioned before, we’re not leading the pack in this, we’re merely following along with others (like, say, Django). There are undoubtedly other terms and practices that are genuinely offensive, and the decision on how to handle them will be taken on a case-by-case basis, weighing the cost and the benefit in each case. While you may feel the benefit of this change is small and that it has no real impact, we believe that there is little cost to making this change. We believe this change, while a minor inconvenience to some, helps demonstrate our commitment to acting in the best interests of Python's future. Failure to make a small sacrifice, such as this, signals that the Python core development community would be unlikely to undertake real change for greater benefits. This isn’t happening because GitHub/Microsoft made a political decision. It’s happening because it is incredibly easy to make this move, many projects have already done this, and it reflects badly on any project not making this change. Speaking for the whole SC in this, Thomas.

5 months, 1 week

PEP 654: Exception Groups and except* [REPOST]

by Irit Katriel

We would like to present for feedback a new version of PEP 654, which incorporates the feedback we received in the discussions so far: https://www.python.org/dev/peps/pep-0654/ The reference implementation has also been updated along with the PEP. The changes we made since the first post are: 1. Instead of ExceptionGroup(BaseException), we will have two new builtin types: BaseExceptionGroup(BaseException) and ExceptionGroup(BaseExceptionGroup, Exception). This is so that "except Exception" catches ExceptionGroups (but not BaseExceptionGroups). BaseExceptionGroup.__new__ inspects the wrapped exceptions, and if they are all Exception subclasses, it creates an ExceptionGroup instead of a BaseExceptionGroup. 2. The exception group classes are not final - they can be subclassed and split()/subgroup() work correctly if the subclass overrides the derive() instance method as described here: https://www.python.org/dev/peps/pep-0654/#subclassing-exception-groups 3. We had some good suggestions on formatting exception groups, which we have implemented as you can see in the output shown for the examples in the PEP. 4. We expanded the section on handling Exception Groups, to show how subgroup can be used (with side effects) to do something for each leaf exception, and how to iterate correctly when the tracebacks of leaf exceptions are needed: https://www.python.org/dev/peps/pep-0654/#handling-exception-groups 5. We expanded the sections on rationale and backwards compatibility to explain our premise and expectations regarding how exception groups will be used and how the transition to using them will be managed. 6. We added several items to the rejected ideas section. We did not receive any comments (or make any changes) to the proposed semantics of except*, hopefully this is because everyone thought they are sensible. Irit, Yury and Guido

5 months, 2 weeks

SC feedback: PEP 648 -- Extensible customizations of the interpreter at startup

by Barry Warsaw

Hello Mario, Thank you for your submission of PEP 648 (Extensible customizations of the interpreter at startup). The Python Steering Council has reviewed the PEP and before we can pronounce on it, we have some additional questions and comments we’d like you to address. Once these questions are settled, we are requesting that you post the PEP to python-dev for another round of comments. In general, the SC is in favor of deprecating the executable hack capabilities of pth files, and this PEP is currently the most concrete proposal to get there. We would like to eventually go farther, including deprecation of pth files entirely, but that is outside the scope of this PEP. General PEP feedback The introduction of the section titled “Benefits of __sitecustomize__” seems out of place. It forward references the solution without explanation. It also says “The use of a __sitecustomize__ will allow…”; the question is, a __sitecustomize__ what? Directory? File? Perhaps it should be moved to later in the PEP after the semantics of __sitecustomize__ is defined? Some of the terminology used in the PEP could be clarified. For example, I suggest using the term “directory” instead of “folder” throughout the PEP, and use the term “module” or “file” instead of “script” to describe the things inside __sitecustomize__ directories that Python imports, since “scripts” typically describe standalone files that implement applications. For example, must the files be named with .py extension (or presumably .pyc, .pyo) under the normal Python module import rules? (Later in the PEP you do allude to the requirement that the file name must end in .py, but it would be much better to explain this right up front, in a formal specification.) Another ambiguity is what the PEP means by “executing” said “scripts”. Does that mean importing them? Reading them then exec()’ing them? Something else? This section should be clear that Python will import the modules it found, if that’s indeed what the PEP is proposing. The “Backward compatibility” section has this incomplete sentence: “Ignoring those lines in pth files.” There’s this odd grammar in the “Do nothing” section: “After analysing the impact of this change, we believe it is worth given the enhanced experience it brings.” Perhaps it should read “...it is worth it, given the…”? Definition of “site path” The PEP should precisely define what it means when it says “...a folder named __sitecustomize__ located in any site path”. What exactly is a “site path”? Is this any directory on sys.path? Is it a directory named site-packages? This phrase is also ambiguous: “As the folder will be within sys.path, given that it is located in site paths...”. “sys.path” isn’t a thing that can hold a folder, since it’s just a list of strings, and it also can get extended by any number of means, e.g. by setting the PYTHONPATH environment variable at interpreter startup time. So for example, how does PYTHONPATH affect the algorithm? What is the rationale for adding multiple __sitecustomize__ directories, rather than a single directory (or possibly two, one in Python’s system location and one in the user location)? This would simplify the discovery process, and tools like pip can warn the user if a name collision were to occur. I think the PEP needs to be much more crisp and precise in defining the when and how __sitecustomize__ directories are discovered at start up time. Order of Execution I think this section should outline the entire startup execution order. Exactly when do pth files still get evaluated in relationship to __sitecustomize__ discovery? How do pth file sys.path extensions affect the search for __sitecustomize__ directories? This section also says files in __sitecustomize__ will be executed in “file name sorted order”, but the PEP is unclear whether all such files found in every __sitecustomize__ directory will be sorted together, or only within a single __sitecustomize__ directory. Presumably file system encodings are used to determine file name sort order, but I think the PEP should be explicit about this. I’d like to see the execution order for the entire proposed new Python startup sequence as a recipe, or perhaps even some Python pseudo-code. Impact on startup time We still think that startup performance can be a concern. This section needs more data. For example, while the executable part of pth files is being deprecated, both pth and __sitecustomize__ modules will exist. How does this affect startup time in a world where both have to be discovered and processed? The PEP says: “If the user has custom scripts, we think that the impact on the performance of walking each of the folders is acceptable, as the user wants to use this feature.” Does the user really want to use this feature? Won’t it more likely be the system administrator or Python distribution and packaging ecosystem that chooses to use the __sitecustomize__ feature? Maybe the user won’t even know that it’s being used by the packages being installed? The PEP says: ““Running "./python -c pass" with perf on 50 iterations, repeating 50 times the command on each and getting the geometric mean on a commodity laptop did not reveal any substantial raise on CPU time.” We request more information on the experiments performed, and specific numbers so that the startup impact can be reproduced and confirmed by others. E.g. did you run this experiment on a branch of CPython 3.10 with the PEP 648 reference implementation? Did you convert existing uses of executable pth files to __sitecustomize__ modules? How many such modules did you try it with? How many __sitecustomize__ directories were in your tests? Other questions and issues How does this feature interact with virtual environments? What do packaging tools have to do to support this PEP? The PEP mentions setuptools, but what about other packaging tools in common use? The PEP says “This impact will be reduced in the future as we will remove two other imports: "sitecustomize.py" and "usercustomize.py”.” Why not explicitly deprecate these and executable pth files in PEP 648 and begin the countdown at the same time __sitecustomize__ is added to Python? The PEP says: “To facilitate debugging of the Python startup, a new option will be added to the main of the site module to list all scripts that will be executed as part of the __sitecustomize__ initialization.” The PEP should be explicit about what command line switch is being proposed. We think this should probably be an -X option. Do you have any concerns that this feature will be overused? Does separating the execution feature from the path extension feature make it more or less likely to be used by third party library authors? Will the runtime have any access to the list of __sitecustomize__ modules being executed? I.e. will you collect their paths in a new sys module attribute? Will there be any functions to import or list __sitecustomize__ directories or modules after start has completed? We think io.open_code() should be used so that reading the files can be audited. Conclusion The Python Steering Council again wants to thank you for your PEP contribution! We hope you find this feedback constructive and helpful. We look forward to your responses, and an updated PEP. Cheers, -Barry (on behalf of the Python Steering Council)

5 months, 2 weeks

Let's Fix Class Annotations -- And Maybe Annotations Generally

by Larry Hastings

Howdy howdy. While working on my PEP I stumbled over a lot of behavior by annotations that I found inconsistent and inconvenient. I think there are several problems here that needs fixing. This discussion will probably evolve into a PEP, and I'll be happy to steer that process. But I'm less certain about what the right thing to do is. (Although I do know what I'd prefer!) So let's talk about it! Annotations are represented in Python as a dictionary. They can be present on functions, classes, and modules as an attribute called "__annotations__". We start with: how do you get the annotations from one of these objects? Surely it's as easy as this line from Lib/inspect.py shows us: return func.__annotations__ And yes, that's best practice for getting an annotation from a function object. But consider this line from Lib/functools.py: ann = getattr(cls, '__annotations__', {}) Huh. Why doesn't it simply look at cls.__annotations__? It's because the language declares that __annotations__ on a class or module is optional. Since cls.__annotations__ may not be defined, evaluating that might throw an exception. Three-argument getattr() is much safer, and I assert it's best practice for getting the annotations from a module. But consider this line from Lib/dataclasses.py: cls_annotations = cls.__dict__.get('__annotations__', {}) And a very similar line from Lib/typing.py: ann = base.__dict__.get('__annotations__', {}) Huh! Why is this code skipping the attribute entirely, and examining cls.__dict__? It's because the getattr() approach has a subtle bug when dealing with classes. Consider this example: class A: ax:int=3 class B(A): pass print(getattr(B, '__annotations__', {})) That's right, B *inherits* A.__annotations__! So this prints {'ax': int}. This *can't* the intended behavior of __annotations__ on classes. It's only supposed to contain annotations for the fields of B itself, not those of one of its randomly-selected base classes. But that's how it behaves today--and people have had to work around this behavior for years. Examining the class dict is, sadly, best practice for getting __annotations__ from a class. So, already: three different objects can have __annotations__, and there are three different best practices for getting their __annotations__. Let's zoom out for a moment. Here's the list of predefined data fields you can find on classes: __annotations__ __bases__ __class__ __dict__ __doc__ __module__ __mro__ __name__ __qualname__ All of these describe metadata about the class. In every case *except one*, the field is mandatory, which also means it's never inherited. And in every case *except one*, you cannot delete the field. (Though you *are* allowed to overwrite some of them.) You guessed it: __annotations__ is the exception. It's optional, and you're allowed to delete it. And these exceptions are causing problems. It seems to me that, if the only way to correctly use a language-defined attribute of classes is by rooting around in its __dict__, the design is a misfire. (Much of the above also applies to modules, too. The big difference: since modules lack inheritance, you don't need to look in their __dict__.) Now consider what happens if my "delayed annotations of annotations using descriptors" PEP is accepted. If that happens, pulling __annotations__ out of the class dict won't work if they haven't been generated yet. So today's "best practice" becomes tomorrow's "this code doesn't work". To correctly examine class annotations, code would have to do something like this, which should work correctly in any Python 3.x version: if (getattr(cls, '__co_annotations__', None) or ('__annotations__' in cls.__dict__)): ann = cls.__annotations__ else: ann = {} This is getting ridiculous. Let's move on to a related topic. For each of the objects that can have annotations, what happens if o.__annotations__ is set, and you "del o.__annotations__", then you access o.__annotations__? It depends on what the object is, because each of them behaves differently. You already know what happens with classes: if any of the base classes has __annotations__ set, you'll get the first one you find in the MRO. If none of the bases have __annotations__ set you'll get an AttributeError. For a module, if you delete it then try to access it, you'll always get an AttributeError. For a function, if you delete it then try to get it, the function will create a new empty dict, store it as its new annotations dict, and return that. Why does it do that? I'm not sure. The relevent PEP (3107) doesn't specify this behavior. So, annotations can be set on three different object types, and each of those three have a different behavior when you delete the annotations then try to get them again. As a final topic: what are the permitted types for __annotations__? If you say "o.__annotations__ = <x>", what types are and aren't allowed for <x>? For functions, __annotations__ may be assigned to either None or a dict (an object that passes PyDict_Check). Anything else throws a TypeError. For classes and modules, no checking is done whatsoever, and you can set __annotations__ on those two to any Python object. While "a foolish consistency is the hobgoblin of little minds", I don't see the benefit of setting a module's __annotations__ to 2+3j. I think it's long past time that we cleaned up the behavior of annotations. They should be simple and consistent across all objects that support them. At the very least, I think we should make cls.__annotations__ required rather than optional, so that it's never inherited. What should its default value be? An empty dict would be more compatible, but None would be cheaper. Note that creating the empty dict on the fly, the way function objects do, wouldn't really help--because current best practice means looking in cls.__dict__. I also think you shouldn't be able to delete __annotations__ on any of the three objects (function, class, module). It should always be set, so that the best practice for accessing annotations on an object is always o.__annotations__. If I could wave my magic wand and do whatever I wanted, I'd change the semantics for __annotations__ to the following: * Functions, classes, and modules always have an __annotations__ member set. * "del o.__annotations__" always throws a TypeError. * The language will set __annotations__ to a dict if the object has annotations, or None if it has no annotations. * You may set __annotations__, but you can only set it to either None or a dict (passes PyDict_Check). * You may only access __annotations__ as an attribute, and because it's always set, best practice is to use "o.__annotations__" (though getattr will always work too). * How __annotations__ is stored is implementation-specific behavior; looking in the relevant __dict__ is unsupported. This would grant sanity and consistency to __annotations__ in a way it's never so far enjoyed. The problem is, it's a breaking change. But the existing semantics are kind of terrible, so at this point my goal is to break them. I think the best practice needs to stop requiring examining cls.__dict__; in fact I'd prefer people stop doing it altogether. If we change the behavior as part of a new release of Python, code that examines annotations on classes can do a version check: if (sys.version_info.major >=3 and sys.version_info.minor >= 10): def get_annotations(o): return o.__annotations__ or {} else: def get_annotations(o): # eight or ten lines of complex code goes here ... Or code can just use inspect.get_type_hints(), which is tied to the Python version anyway and should always do the right thing. //arry/

5 months, 3 weeks

How about using modern C++ in development of CPython ?

by redradist＠gmail.com

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 ...

5 months, 3 weeks

PEP 644 Accepted -- Require OpenSSL 1.1.1 or newer

by Pablo Galindo Salgado

Hi Christian, Thank you for submitting PEP 644 (Require OpenSSL 1.1.1). After evaluating the situation and discussing the PEP, the Steering Council is happy with the PEP, and hereby accepts it. The SC is of the opinion that this change will make it considerable easier to maintain the extension modules that depend on OpenSSL while allowing us to leverage the new APIs and improvements in the future. As indicated in the PEP, OpenSSL 1.1.1 is the default variant and version of OpenSSL on almost all supported platforms and distributions almost all known Major CI providers provide images with OpenSSL 1.1.1, so we believe this has the right balance to improve the situation without causing major impact or breakage. Nevertheless, the Steering Council would like to see this change reflected properly in the documentation, What's New (linking against the new instructions here: https://docs.python.org/3.10/using/unix.html#custom-openssl) and release manager notices so this is properly communicated to our users. The Steering Council also thanks Christian for his patience explaining different aspects of the PEP, including in the PEP some extra requested information and for considering the concerts raised. Congratulations, Christian! With thanks from the whole Python Steering Council, Pablo Galindo Salgado

6 months

Boundaries between numbers and identifiers

by Serhiy Storchaka

In Python 2.5 `0or[]` was accepted by the Python parser. It became an error in 2.6 because "0o" became recognizing as an incomplete octal number. `1or[]` still is accepted. On other hand, `1if 2else 3` is accepted despites the fact that "2e" can be recognized as an incomplete floating point number. In this case the tokenizer pushes "e" back and returns "2". Shouldn't it do the same with "0o"? It is possible to make `0or[]` be parseable again. Python implementation is able to tokenize this example: $ echo '0or[]' | ./python -m tokenize 1,0-1,1: NUMBER '0' 1,1-1,3: NAME 'or' 1,3-1,4: OP '[' 1,4-1,5: OP ']' 1,5-1,6: NEWLINE '\n' 2,0-2,0: ENDMARKER '' On other hand, all these examples look weird. There is an assymmetry: `1or 2` is a valid syntax, but `1 or2` is not. It is hard to recognize visually the boundary between a number and the following identifier or keyword, especially if numbers can contain letters ("b", "e", "j", "o", "x") and underscores, and identifiers can contain digits. On both sides of the boundary can be letters, digits, and underscores. I propose to change the Python syntax by adding a requirement that there should be a whitespace or delimiter between a numeric literal and the following keyword.

6 months

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Python-Dev March 2021