Mailman 3 ফেব্রুয়ারি 2021 - Python-Dev

Mixed Python/C debugging
by Skip Montanaro 26 এপ্রিল, 2023

26 এপ্রিল, 2023

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

5 6

PEP 448 review
by Guido van Rossum 29 মার্চ, 2023

29 মার্চ, 2023

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)

7 17

PEP 638: Syntactic macros
by Mark Shannon 5 ফেব্রুয়ারি, 2023

5 ফেব্রুয়ারি, 2023

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

16 25

Speeding up CPython
by Mark Shannon 18 মে, 2021

18 মে, 2021

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.

33 77

PEP 1, PEP Purpose and Guidelines
by barry＠zope.com 18 মে, 2021

18 মে, 2021

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:

8 14

Let's Fix Class Annotations -- And Maybe Annotations Generally
by Larry Hastings 24 এপ্রিল, 2021

24 এপ্রিল, 2021

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/

10 44

Boundaries between numbers and identifiers
by Serhiy Storchaka 15 এপ্রিল, 2021

15 এপ্রিল, 2021

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.

8 10

Status of PEP 649 -- Deferred Evaluation Of Annotations Using Descriptors
by Guido van Rossum 30 মার্চ, 2021

30 মার্চ, 2021

Hi Larry, Can you give us a status update for your PEP 649? I don't recall reading anything about it in the past few weeks. I am super excited about this solution to the problem (even if there are a few issues to work through) and I think it will provide better backwards compatibility than the current plan for Python 3.10 (PEP 563, from __future__ import annotations, causing all annotations to be stringified). If we don't get this into 3.10, we'd have a much more complicated transition. There are only two more alphas before 3.10b1 gets released! And we'd have to get this approved by the Steering Council, which can take a few weeks (cut them some slack, they have a big backlog). Fortunately you already have an implementation that can be landed quickly once the PEP is accepted. -- --Guido van Rossum (python.org/~guido) *Pronouns: he/him **(why is my pronoun here?)* <http://feministing.com/2015/02/03/how-using-they-as-a-singular-pronoun-can-…>

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Merge Request Review Reminder
by Faisal Mahmood 23 মার্চ, 2021

23 মার্চ, 2021

Hello, I hope you are all well, I currently have an issue / merge request that has become stale and as per the guidelines I am sending this e-mail to request someone to review it for me please. Issue Number: 42861 (https://bugs.python.org/issue42861) Pull Request: 24180 (https://github.com/python/cpython/pull/24180) This is my first contribution to CPython and I am very keen to get this added as I think it is an almost essential enhancement missing from the ipaddress module. I would greatly appreciate if someone can take a look and give me feedback, I am more than happy to help explain things, as I appreciate this is not the most straightforward thing to do. Effectively, this method allows you to get the next closest network of any prefix size, it works by effectively adding 1 to the host portion of the network. There is actually a very nice guide someone made on stackexchange explaining how to do this calculation manually, I simply followed this logic and have tested it as much as possible and it seems to work great. See here: https://networkengineering.stackexchange.com/questions/7106/how-do-you-calc… Please let me know if there is anything else I can do to help get this merged. Kind regards, Faisal.

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Python Language Summit 2021 Signups Are Now Open
by Łukasz Langa 22 মার্চ, 2021

22 মার্চ, 2021

I’m happy to announce that we’ve opened the sign-up forms for the 2021 Python Language Summit! TL;DR When: Tuesday, May 11, 2021 (4 hours) and Wednesday, May 12, 2021 (4 hours). Exact times TBD depending on attendee timezones. Where: Online via Zoom (link will be sent via email to attendees) Co-chairs: Mariatta Wijaya & Łukasz Langa Blogger: Joanna Jablonski Sign up to attend and actively participate: https://forms.gle/cgmGnmQMDhD2mhHY8 <https://forms.gle/cgmGnmQMDhD2mhHY8> (closes after March 22nd, 2021 AoE) Propose a topic: https://forms.gle/Jui9mxsHrB4fVvAB8 <https://forms.gle/Jui9mxsHrB4fVvAB8> (closes after March 22nd, 2021 AoE) To get an idea of past Python Language Summits, you can read these blog posts: 2020: Python Software Foundation News: The 2020 Python Language Summit <https://pyfound.blogspot.com/2020/04/the-2020-python-language-summit.html> 2019: http://pyfound.blogspot.com/2019/05/the-2019-python-language-summit.html <http://pyfound.blogspot.com/2019/05/the-2019-python-language-summit.html> 2018: The 2018 Python Language Summit [LWN.net] <https://lwn.net/Articles/754152/> 2017: The 2017 Python Language Summit [LWN.net] <https://lwn.net/Articles/723251/> Do I need to sign up if I’m a Python core developer? Yes please! While in the past we have limited attendance to 50 people, this time, due to virtual format, we will be a bit more flexible, but will still keep it small and manageable. We aren’t planning to go beyond 80 participants. Please register to reserve your space. Can I sign up if I’m not a Python core developer? Yes you can. In the past, we had quite a number of participants who were not Python core devs. Among them were maintainers and representatives from BeeWare, CircuitPython, PSF board member, PyCharm, PyPA, etc. Register if you want to participate. Note that until you hear back from us, your attendance is not confirmed. As explained in the question above, our “space” is more flexible than usual, but in the interest of maintaining a vigorous discussion space, we might still be unable to invite everyone who signs up. What kind of topics are covered? Python Language Summit is a special event with very specific audience: Python core developers. Ideally your topic is not an “announcement” or “project status” but rather something that will encourage further discussion and questions. The more controversial, the better. An open issue, group of issues, or a PEP that is awaiting decision are all good topics to propose. You can also further explain why this is better discussed in person instead of online. According to last year’s feedback, our audience prefer more discussions and shorter talks. Who can present a talk? Anyone, even if you’re not a Python core developer. However, please understand that we will have to be selective as space and time are limited. In particular, we are prioritizing active core contributors, as well as those who we believe will be able to improve the quality of the discussions at the event and bring a more diverse perspective to core Python developers. Note that your topic is not confirmed until you hear back from us. Code of Conduct PyCon’s Code of Conduct <https://us.pycon.org/2020/about/code-of-conduct/> applies and will be enforced. Thanks! @mariatta <https://discuss.python.org/u/mariatta> & @ambv <https://discuss.python.org/u/ambv>

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