Mailman 3 April 2015 - Python-ideas

@classproperty, @abc.abstractclasspropery, etc.
by K. Richard Pixley 16 Dec '20

16 Dec '20

There's a whole matrix of these and I'm wondering why the matrix is currently sparse rather than implementing them all. Or rather, why we can't stack them as: class foo(object): @classmethod @property def bar(cls, ...): ... Essentially the permutation are, I think: {'unadorned'|abc.abstract}{'normal'|static|class}{method|property|non-callable attribute}. concreteness implicit first arg type name comments {unadorned} {unadorned} method def foo(): exists now {unadorned} {unadorned} property @property exists now {unadorned} {unadorned} non-callable attribute x = 2 exists now {unadorned} static method @staticmethod exists now {unadorned} static property @staticproperty proposing {unadorned} static non-callable attribute {degenerate case - variables don't have arguments} unnecessary {unadorned} class method @classmethod exists now {unadorned} class property @classproperty or @classmethod;@property proposing {unadorned} class non-callable attribute {degenerate case - variables don't have arguments} unnecessary abc.abstract {unadorned} method @abc.abstractmethod exists now abc.abstract {unadorned} property @abc.abstractproperty exists now abc.abstract {unadorned} non-callable attribute @abc.abstractattribute or @abc.abstract;@attribute proposing abc.abstract static method @abc.abstractstaticmethod exists now abc.abstract static property @abc.staticproperty proposing abc.abstract static non-callable attribute {degenerate case - variables don't have arguments} unnecessary abc.abstract class method @abc.abstractclassmethod exists now abc.abstract class property @abc.abstractclassproperty proposing abc.abstract class non-callable attribute {degenerate case - variables don't have arguments} unnecessary I think the meanings of the new ones are pretty straightforward, but in case they are not... @staticproperty - like @property only without an implicit first argument. Allows the property to be called directly from the class without requiring a throw-away instance. @classproperty - like @property, only the implicit first argument to the method is the class. Allows the property to be called directly from the class without requiring a throw-away instance. @abc.abstractattribute - a simple, non-callable variable that must be overridden in subclasses @abc.abstractstaticproperty - like @abc.abstractproperty only for @staticproperty @abc.abstractclassproperty - like @abc.abstractproperty only for @classproperty --rich

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Specify number of items to allocate for array.array() constructor
by Sven Rahmann 22 Feb '20

22 Feb '20

At the moment, the array module of the standard library allows to create arrays of different numeric types and to initialize them from an iterable (eg, another array). What's missing is the possiblity to specify the final size of the array (number of items), especially for large arrays. I'm thinking of suffix arrays (a text indexing data structure) for large texts, eg the human genome and its reverse complement (about 6 billion characters from the alphabet ACGT). The suffix array is a long int array of the same size (8 bytes per number, so it occupies about 48 GB memory). At the moment I am extending an array in chunks of several million items at a time at a time, which is slow and not elegant. The function below also initializes each item in the array to a given value (0 by default). Is there a reason why there the array.array constructor does not allow to simply specify the number of items that should be allocated? (I do not really care about the contents.) Would this be a worthwhile addition to / modification of the array module? My suggestions is to modify array generation in such a way that you could pass an iterator (as now) as second argument, but if you pass a single integer value, it should be treated as the number of items to allocate. Here is my current workaround (which is slow): def filled_array(typecode, n, value=0, bsize=(1<<22)): """returns a new array with given typecode (eg, "l" for long int, as in the array module) with n entries, initialized to the given value (default 0) """ a = array.array(typecode, [value]*bsize) x = array.array(typecode) r = n while r >= bsize: x.extend(a) r -= bsize x.extend([value]*r) return x

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Implicit string literal concatenation considered harmful?
by Guido van Rossum 14 Mar '18

14 Mar '18

I just spent a few minutes staring at a bug caused by a missing comma -- I got a mysterious argument count error because instead of foo('a', 'b') I had written foo('a' 'b'). This is a fairly common mistake, and IIRC at Google we even had a lint rule against this (there was also a Python dialect used for some specific purpose where this was explicitly forbidden). Now, with modern compiler technology, we can (and in fact do) evaluate compile-time string literal concatenation with the '+' operator, so there's really no reason to support 'a' 'b' any more. (The reason was always rather flimsy; I copied it from C but the reason why it's needed there doesn't really apply to Python, as it is mostly useful inside macros.) Would it be reasonable to start deprecating this and eventually remove it from the language? -- --Guido van Rossum (python.org/~guido)

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Reprs of classes and functions
by Serhiy Storchaka 05 Aug '15

05 Aug '15

This idea is already casually mentioned, but sank deep into the threads of the discussion. Raise it up. Currently reprs of classes and functions look as: >>> int <class 'int'> >>> int.from_bytes <built-in method from_bytes of type object at 0x826cf60> >>> open <built-in function open> >>> import collections >>> collections.Counter <class 'collections.Counter'> >>> collections.Counter.fromkeys <bound method Counter.fromkeys of <class 'collections.Counter'>> >>> collections.namedtuple <function namedtuple at 0xb6fc4adc> What if change default reprs of classes and functions to just full qualified name __module__ + '.' + __qualname__ (or just __qualname__ if __module__ is builtins)? This will look more neatly. And such reprs are evaluable.

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More general "for" loop handling
by Todd 03 May '15

03 May '15

Looking at pep 492, it seems to me the handling of "for" loops has use outside of just asyncio. The primary use-case I can think of is multiprocessing and multithreading. For example, you could create a multiprocessing pool, and let the pool handle the items in a "for" loop, like so: from multiprocessing import Pool mypool = Pool(10, maxtasksperchild=2) mypool for item in items: do_something_here do_something_else do_yet_another_thing Or something similar with third-party modules: from greenlet import greenlet greenlet for item in items: do_something_here do_something_else do_yet_another_thing Of course this sort of thing is possible with iterators and maps today, but I think a lot of the same advantages that apply to asyncio also apply to these sorts of cases. So I think that, rather than having a special keyword just for asyncio, I think it would be better to have a more flexible approach. Perhaps something like a "__for__" magic method that lets a class implement "for" loop handling, along with the corresponding changes in how the language processes the "for" loop.

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PEP 492 terminology - (native) coroutine objects
by Oscar Benjamin 01 May '15

01 May '15

Looking through PEP 492 I dislike the terminology. With generators I can do: >>> def f(): yield ... >>> g = f() >>> g <generator object f at 0x7fb81dadc798> So f is a generator function and g is generator. That's all pretty clear and "generator" is IMO a great name. The term "generator function" is also unambiguous for f. With PEP 492 it seems that I would get something like: >>> async def af(): pass >>> ag = af() >>> ag <coroutine_object object af at 0x7fb81dadc828> According to the terminology in the PEP af is a coroutine but since the word coroutine also refers to some generators in a looser sense I should use "native coroutine" to disambiguate. ag is a "coroutine object" but again I should use "native coroutine object" to explicitly name the type because without the word "native" it also refers to other things. I think that if the terminology is already ambiguous with related language constructs before it's introduced then it would be better to change it now. The word coroutine (without "native" modifier) is used by the PEP to refer to both generator based coroutines and the new async def functions. I think it's reasonable to use the word as a generic term in this sense. Python's idea of coroutines (both types) doesn't seem to match with the pre-existing general definitions but they are at least generalisations of functions so it can be reasonable to describe them that way loosely. Greg's suggestion to call an async def function (af above) an "async function" seems like a big improvement. It clearly labels the purpose: a function for use in a asynchronous execution probably with the asyncio module. It also matches directly with the syntax: a function prefixed with the word "async". There would be no ambiguity between which of af or ag is referred to by the term. It seems harder to think of a good name for ag though. ag is a wrapper around a suspended call stack with methods to resume the stack so describing what is is doesn't lead to anything helpful. OTOH the purpose of ag is often described as implementing a "minithread" so the word "minithread" makes intuitive sense to me. That way async code is done by writing async functions that return minithreads. An event loop schedules the minthreads etc. (I'm trying to imagine explaining this to someone...) I'm not sure what the best word is for a coroutine object but the current terminology clearly has room for improvement. For a start using the word "object" in the name of a type is a bit rubbish in a language where everything is an object. Worse the PEP is reusing words that have already been used with different meanings so that it's already ambiguous. A concrete builtin language type such as the coroutine object deserves a good, short, one-word name that will not be confused with other things. -- Oscar

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Re: [Python-ideas] Top 10 Python modules that need a redesign Was: Geo coordinates conversion in stdlib
by Alexander Belopolsky 01 May '15

01 May '15

On Mon, Mar 23, 2015 at 2:08 AM, anatoly techtonik <techtonik(a)gmail.com> wrote: > > That's nice to know, but IIRC datetime is from the top 10 Python > modules that need a redesign. Things contained therein doesn't pass > human usability check, and are not used as a result. Where have you been when PEP 3108 was discussed? I have not seen any other list of Python modules that needed a redesign, so I cannot tell what's on your top ten list. Speaking of the datetime module, in what sense does it not "pass human usability check"? It does have a few quirks, for example I would rather see date accept a single argument in the constructor which may be a string, another date or a tuple, but I am not even sure this desire is shared by many other humans. It would be nice if datetime classes were named in CamelCase according to PEP 8 conventions, but again this is a very minor quirk. In my view, if anyone is to blame for the "human usability" of the datetime module, it would be Pope Gregory XIII, Benjamin Franklin and scores of unnamed astronomers who made modern timekeeping such a mess.

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Letting context managers react to yields inside their scope
by Nathaniel Smith 30 Apr '15

30 Apr '15

Hi all, Well, after a few days no-one has responded to my post on another thread about this [1], but the more I thought about it the more this seemed like a good idea, so I wrote up a little more-formal proposal (attached) for letting context managers react to 'yield's that occur within their 'with' block. This should in many ways be treated as a straw man proposal -- there's tons I don't know about how async code is written in Python these days -- but it seems like a good idea to me and I'd like to hear what everyone else thinks :-). -n [1] https://mail.python.org/pipermail/python-ideas/2015-April/033176.html -- Nathaniel J. Smith -- http://vorpus.org

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Bytestrings in Python 2
by Serhiy Storchaka 26 Apr '15

26 Apr '15

Here is an idea that perhaps will help to prepare Python 2 code for converting to Python 3. Currently bytes is just an alias of str in Python 2, and the "b" prefix of string literals is ignored. There are no differences between natural strings and bytes. I propose to add special bit to str instances and set it for bytes literals and strings created from binary sources (read from binary files, received from sockets, the result of unicode.encode() and struct.pack(), etc). With -3 flag operations with binary strings that doesn't allowed for bytes in Python 3 (e.g. encoding or coercing to unicode) will emit a warning. Unfortunately we can't change the bytes constructor in minor version, it should left an alias to str in 2.7. So the result of bytes() will be not tagged as binary string. May be it is too late for this.

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Generator/Coroutiine Ontology (was async/await in Python)
by Rustom Mody 25 Apr '15

25 Apr '15

On Sat, Apr 18, 2015 at 12:28 AM, Yury Selivanov <yselivanov.ml(a)gmail.com> wrote: > Hello python-ideas, > > Here's my proposal to add async/await in Python. > > I believe that PEPs 380 and 3156 were a major breakthrough for Python 3, I am also interested in this topic --- from the other side. As a teacher of python it is my finding that the terminology/documentation around generators is rather chaotic and messy. Basically given: def foo(): yield 1 bar = foo() what do we call foo and what do we call bar? It is suggested that foo is "generator-function" and bar is "generator-object" Unfortunately python does not aid this distinction; witness >>> def foo(): ... yield 1 ... >>> bar = foo() >>> type(foo) <class 'function'> >>> type(bar) <class 'generator'> >>> I asked about this on the python list http://code.activestate.com/lists/python-list/682286/ And it seems that many more dark corners emerged in the docs on this subject in that discussion. Should I start a separate thread?

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