Mailman 3 December 2010 - Python-ideas

i18n and Python tracebacks
by Andre Roberge 28 Oct '12

28 Oct '12

I think it would be a good idea if Python tracebacks could be translated into languages other than English - and it would set a good example. For example, using French as my default local language, instead of >>> 1/0 Traceback (most recent call last): File "<stdin>", line 1, in <module> ZeroDivisionError: integer division or modulo by zero I might get something like >>> 1/0 Suivi d'erreur (appel le plus récent en dernier) : Fichier "<stdin>", à la ligne 1, dans <module> ZeroDivisionError: division entière ou modulo par zéro André

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Cofunctions PEP - Revision 4
by Greg Ewing 13 Oct '12

13 Oct '12

Here's an updated version of the PEP reflecting my recent suggestions on how to eliminate 'codef'. PEP: XXX Title: Cofunctions Version: $Revision$ Last-Modified: $Date$ Author: Gregory Ewing <greg.ewing(a)canterbury.ac.nz> Status: Draft Type: Standards Track Content-Type: text/x-rst Created: 13-Feb-2009 Python-Version: 3.x Post-History: Abstract ======== A syntax is proposed for defining and calling a special type of generator called a 'cofunction'. It is designed to provide a streamlined way of writing generator-based coroutines, and allow the early detection of certain kinds of error that are easily made when writing such code, which otherwise tend to cause hard-to-diagnose symptoms. This proposal builds on the 'yield from' mechanism described in PEP 380, and describes some of the semantics of cofunctions in terms of it. However, it would be possible to define and implement cofunctions independently of PEP 380 if so desired. Specification ============= Cofunction definitions ---------------------- A cofunction is a special kind of generator, distinguished by the presence of the keyword ``cocall`` (defined below) at least once in its body. It may also contain ``yield`` and/or ``yield from`` expressions, which behave as they do in other generators. From the outside, the distinguishing feature of a cofunction is that it cannot be called the same way as an ordinary function. An exception is raised if an ordinary call to a cofunction is attempted. Cocalls ------- Calls from one cofunction to another are made by marking the call with a new keyword ``cocall``. The expression :: cocall f(*args, **kwds) is evaluated by first checking whether the object ``f`` implements a ``__cocall__`` method. If it does, the cocall expression is equivalent to :: yield from f.__cocall__(*args, **kwds) except that the object returned by __cocall__ is expected to be an iterator, so the step of calling iter() on it is skipped. If ``f`` does not have a ``__cocall__`` method, or the ``__cocall__`` method returns ``NotImplemented``, then the cocall expression is treated as an ordinary call, and the ``__call__`` method of ``f`` is invoked. Objects which implement __cocall__ are expected to return an object obeying the iterator protocol. Cofunctions respond to __cocall__ the same way as ordinary generator functions respond to __call__, i.e. by returning a generator-iterator. Certain objects that wrap other callable objects, notably bound methods, will be given __cocall__ implementations that delegate to the underlying object. Grammar ------- The full syntax of a cocall expression is described by the following grammar lines: :: atom: cocall | <existing alternatives for atom> cocall: 'cocall' atom cotrailer* '(' [arglist] ')' cotrailer: '[' subscriptlist ']' | '.' NAME Note that this syntax allows cocalls to methods and elements of sequences or mappings to be expressed naturally. For example, the following are valid: :: y = cocall self.foo(x) y = cocall funcdict[key](x) y = cocall a.b.c[i].d(x) Also note that the final calling parentheses are mandatory, so that for example the following is invalid syntax: :: y = cocall f # INVALID New builtins, attributes and C API functions -------------------------------------------- To facilitate interfacing cofunctions with non-coroutine code, there will be a built-in function ``costart`` whose definition is equivalent to :: def costart(obj, *args, **kwds): try: m = obj.__cocall__ except AttributeError: result = NotImplemented else: result = m(*args, **kwds) if result is NotImplemented: raise TypeError("Object does not support cocall") return result There will also be a corresponding C API function :: PyObject *PyObject_CoCall(PyObject *obj, PyObject *args, PyObject *kwds) It is left unspecified for now whether a cofunction is a distinct type of object or, like a generator function, is simply a specially-marked function instance. If the latter, a read-only boolean attribute ``__iscofunction__`` should be provided to allow testing whether a given function object is a cofunction. Motivation and Rationale ======================== The ``yield from`` syntax is reasonably self-explanatory when used for the purpose of delegating part of the work of a generator to another function. It can also be used to good effect in the implementation of generator-based coroutines, but it reads somewhat awkwardly when used for that purpose, and tends to obscure the true intent of the code. Furthermore, using generators as coroutines is somewhat error-prone. If one forgets to use ``yield from`` when it should have been used, or uses it when it shouldn't have, the symptoms that result can be extremely obscure and confusing. Finally, sometimes there is a need for a function to be a coroutine even though it does not yield anything, and in these cases it is necessary to resort to kludges such as ``if 0: yield`` to force it to be a generator. The ``cocall`` construct address the first issue by making the syntax directly reflect the intent, that is, that the function being called forms part of a coroutine. The second issue is addressed by making it impossible to mix coroutine and non-coroutine code in ways that don't make sense. If the rules are violated, an exception is raised that points out exactly what and where the problem is. Lastly, the need for dummy yields is eliminated by making it possible for a cofunction to call both cofunctions and ordinary functions with the same syntax, so that an ordinary function can be used in place of a cofunction that yields zero times. Record of Discussion ==================== An earlier version of this proposal required a special keyword ``codef`` to be used in place of ``def`` when defining a cofunction, and disallowed calling an ordinary function using ``cocall``. However, it became evident that these features were not necessary, and the ``codef`` keyword was dropped in the interests of minimising the number of new keywords required. The use of a decorator instead of ``codef`` was also suggested, but the current proposal makes this unnecessary as well. It has been questioned whether some combination of decorators and functions could be used instead of a dedicated ``cocall`` syntax. While this might be possible, to achieve equivalent error-detecting power it would be necessary to write cofunction calls as something like :: yield from cocall(f)(args) making them even more verbose and inelegant than an unadorned ``yield from``. It is also not clear whether it is possible to achieve all of the benefits of the cocall syntax using this kind of approach. Prototype Implementation ======================== An implementation of an earlier version of this proposal in the form of patches to Python 3.1.2 can be found here: http://www.cosc.canterbury.ac.nz/greg.ewing/python/generators/cofunctions.h… If this version of the proposal is received favourably, the implementation will be updated to match. 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 coding: utf-8 End:

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Bring back callable()
by Antoine Pitrou 07 Mar '11

07 Mar '11

Hello, Python 3 has removed callable() under the justification that's it's not very useful and duck typing (EAFP) should be used instead. However, it has since been felt by many people that it was an annoying loss; there are situations where you truly want to know whether something is a callable without actually calling it (for example when writing sophisticated decorators, or simply when you want to inform the user of an API misuse). The substitute of writing `isinstance(x, collections.Callable)` is not good, 1) because it's wordier 2) because collections is really not an intuitive place where to look for a Callable ABC. So, I would advocate bringing back the callable() builtin, which was easy to use, helpful and semantically sane. Regards Antoine.

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Module aliases and/or "real names"
by Nick Coghlan 12 Jan '11

12 Jan '11

Disclaimer: this is a currently half-baked idea that needs some discussion here if it is going to turn into something a bit more coherent :) On and off, I've been pondering the problem of the way implementation details (like the real file structures of the multiprocessing and unittest packages, or whether or not an interpreter use the pure Python or the C accelerated version of various modules) leak out into the world via the __module__ attribute on various components. This mostly comes up when discussing pickle compatibility between 2.x and 3.x, but in can show up in various guises whenever you start relying on dynamic introspection. As, I see it, there are 3 basic ways of dealing with the problem: 1. Allow objects to lie about their source module This is likely a terrible idea, since a function's global namespace reference would disagree with its module reference. I suspect much weirdness would result. 2. A pickle-specific module alias registry, since that is where the problem comes up most often A possible approach, but not necessarily a good one (since it isn't really a pickle-specific problem). 3. An inspect-based module alias registry That is, an additional query API (get_canonical_module_name?) in the inspect module that translates from the implementation detail module name to the "preferred" module name. The implementation could be as simple as a "__canonical__" attribute in the module namespace. I actually quite like option 3, with various things (such as pydoc) updated to show *both* names when they're different. That way people will know where to find official documentation for objects from pseudo-packages and acceleration modules (i.e. under the canonical name), without hiding where the actual implementation came from. Pickle *generation* could then be updated to only send canonical module names during normal operation, reducing the exposure of implementation details like pseudo-packages and acceleration modules. Whether or not runpy should set __canonical__ on the main module would be an open question (probably not, *unless* runpy was also updated to add the main module to sys.modules under its real name as well __main__). Cheers, Nick. -- Nick Coghlan | ncoghlan(a)gmail.com | Brisbane, Australia

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python -c "..." should output result like the interpreter
by Michael Foord 05 Jan '11

05 Jan '11

Hello all, I often use python as a calculator or for simple operations using -c. It would be enormously useful if python -c "..." would output on stdout the result of the last evaluated expression in the same way that the interactive interpreter does. The following outputs nothing: python -c "12 / 4.1" So you always have to prefix expressions with print to see the result. Michael -- http://www.voidspace.org.uk/ May you do good and not evil May you find forgiveness for yourself and forgive others May you share freely, never taking more than you give. -- the sqlite blessing http://www.sqlite.org/different.html

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Optimizing builtins
by Guido van Rossum 03 Jan '11

03 Jan '11

[Changed subject *and* list] > 2010/12/31 Maciej Fijalkowski <fijall(a)gmail.com> >> How do you know that range is a builtin you're thinking >> about and not some other object? On Fri, Dec 31, 2010 at 7:02 AM, Cesare Di Mauro <cesare.di.mauro(a)gmail.com> wrote: > By a special opcode which could do this work. ]:-) That can't be the answer, because then the question would become "how does the compiler know it can use the special opcode". This particular issue (generating special opcodes for certain builtins) has actually been discussed many times before. Alas, given Python's extremely dynamic promises it is very hard to do it in a way that is *guaranteed* not to change the semantics. For example, I could have replaced builtins['range'] with something else; or I could have inserted a variable named 'range' into the module's __dict__. (Note that I am not talking about just creating a global variable named 'range' in the module; those the compiler could recognize. I am talking about interceptions that a compiler cannot see, assuming it compiles each module independently, i.e. without whole-program optimizations.) Now, *in practice* such manipulations are rare (with the possible exception of people replacing open() with something providing hooks for e.g. a virtual filesystem) and there is probably some benefit to be had. (I expect that the biggest benefit might well be from replacing len() with an opcode.) I have in the past proposed to change the official semantics of the language subtly to allow such optimizations (i.e. recognizing builtins and replacing them with dedicated opcodes). There should also be a simple way to disable them, e.g. by setting "len = len" at the top of a module, one would be signalling that len() is not to be replaced by an opcode. But it remains messy and nobody has really gotten very far with implementing this. It is certainly not "low-hanging fruit" to do it properly. I should also refer people interested in this subject to at least three PEPs that were written about this topic: PEP 266, PEP 267 and PEP 280. All three have been deferred, since nobody was bold enough to implement at least one of them well enough to be able to tell if it was even worth the trouble. I haven't read either of those in a long time, and they may well be outdated by current JIT technology. I just want to warn folks that it's not such a simple matter to replace "for i in range(....):" with a special opcode. (FWIW, optimizing "x[i] = i" would be much simpler -- I don't really care about the argument that a debugger might interfere. But again, apart from the simplest cases, it requires a sophisticated parser to determine that it is really safe to do so.) -- --Guido van Rossum (python.org/~guido)

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ML Style Pattern Matching for Python
by Eike Welk 01 Jan '11

01 Jan '11

After learning a bit of Ocaml I started to like its pattern matching features. Since then I want to have a "match" statement in Python. I wonder if anybody else would like this too. ML style pattern matching is syntactic sugar, that combines "if" statements with tuple unpacking, access to object attributes, and assignments. It is a compact, yet very readable syntax for algorithms, that would otherwise require nested "if" statements. It is especially useful for writing interpreters, and processing complex trees. Instead of a specification in BNF, here is a function written with the proposed pattern matching syntax. It demonstrates the features that I find most important. The comments and the print statements explain what is done. Proposed Syntax --------------- def foo(x): match x with | 1 -> # Equality print("x is equal to 1") | a:int -> # Type check print("x has type int: %s" % a) | (a, b) -> # Tuple unpacking print("x is a tuple with length 2: (%s, %s)" % (a, b)) | {| a, b |} -> # Attribute existence and access print("x is an object with attributes 'a' and 'b'.") print("a=%s, b=%s" % (a, b)) # Additional condition | (a, b, c) with a > b -> print("x is a tuple with length 3: (%s, %s, %s)" % (a, b, c)) print("The first element is greater than the second element.") # Complex case | {| c:int, d=1 |}:Foo -> print("x has type Foo") print("x is an object with attributes 'c' and 'd'.") print("'c' has type 'int', 'd' is equal to 1.") print("c=%s, d=%s" % (c, d)) # Default case | _ -> print("x can be anything") Equivalent Current Python ------------------------- The first four cases could be handled more simply, but handling all cases in the same way leads IMHO to more simple code overall. def foo(x): while True: # Equality if x == 1: print("x is equal to 1") break # Type check if isinstance(x, int): a = x print("x is an integer: %s" % a) break # Tuple unpacking if isinstance(x, tuple) and len(x) == 2: a, b = x print("x is a tuple with length 2: (%s, %s)" % (a, b)) break # Attribute existence testing and access if hasattr(x, "a") and hasattr(x, "b"): a, b = x.a, x.b print("x is an object with attributes 'a' and 'b'.") print("a=%s, b=%s" % (a, b)) break # Additional condition if isinstance(x, tuple) and len(x) == 3: a, b, c = x if a > b : print("x is a tuple with length 3: (%s, %s, %s)" % (a, b, c)) print("The first element is greater than the second " "element.") break # Complex case if isinstance(x, Foo) and hasattr(x, "c") and hasattr(x, "d"): c, d = x.c, x.d if isinstance(c, int) and d == 1: print("x has type Foo") print("x is an object with attributes 'c' and 'd'.") print("'c' has type 'int', 'd' is equal to 1.") print("c=%s, d=%s" % (c, d)) break # Default case print("x can be anything") break Additional Code to Run Function "foo" ------------------------------------- class Bar(object): def __init__(self, a, b): self.a = a self.b = b class Foo(object): def __init__(self, c, d): self.c = c self.d = d foo(1) # Equality foo(2) # Type check foo((1, 2)) # Tuple unpacking foo(Bar(1, 2)) # Attribute existence testing and access foo((2, 1, 3)) # Additional condition foo(Foo(2, 1)) # Complex case foo("hello") # Default case I left out dict and set, because I'm not sure how they should be handled. I think list should be handled like tuples. Probably there should be a universal matching syntax for all sequences, similarly to the already existing syntax: a, b, *c = s I don't really like the "->" digraph at the end of each match case. A colon would be much more consistent, but I use colons already for type checking (a:int). I generally think that Python should acquire more features from functional languages. In analogy to "RPython" it should ultimately lead to "MLPython", a subset of the Python language that can be type checked and reasoned about by external tools, similarly to what is possible with Ocaml. Eike.

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for info: pattern matching in a C-like language
by spir 22 Dec '10

22 Dec '10

Hello, Just found this http://dvanderboom.wordpress.com/2010/05/08/the-archetype-language-part-4/ (goto "Pattern Matching") which looks very much like Eike's recent proposal to the python-ideas mailing list. Denis -- -- -- -- -- -- -- vit esse estrany ☣ spir.wikidot.com

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Re: [Python-ideas] ML Style Pattern Matching for Python
by M Daoust 18 Dec '10

18 Dec '10

> Date: Sat, 18 Dec 2010 12:45:49 +0100 > From: spir <denis.spir(a)gmail.com> > To: python-ideas(a)python.org > Subject: Re: [Python-ideas] ML Style Pattern Matching for Python > Message-ID: <20101218124549.35a0d1c9@o> > Content-Type: text/plain; charset=UTF-8 > > On Sat, 18 Dec 2010 12:23:45 +0100 > Eike Welk <eike.welk(a)gmx.net> wrote: > > ... > > I want composite object literal notation as well. But certainly not {| a=1, b=2 |}. Rather (a=1, b=2) or (a:1, b:2). > Untyped case would created an instance of Object (but since as of now they can't have attrs, there should be another modif), or of a new FreeObject subtype of Object. > ... > > Denis "(a=1, b=2) or (a:1, b:2)" These look to me like they should produce a named-tuple instance. I usually just use: ... class Simple(object): ... def __init__(self, **kwargs): ... self.__dict__.update(kwargs) ... Simple(a=1,b=2) -Mark

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Re: [Python-ideas] Python-ideas Digest, Vol 49, Issue 10
by M Daoust 16 Dec '10

16 Dec '10

> Date: Tue, 14 Dec 2010 13:19:24 +0000 > From: Michael Foord <fuzzyman(a)voidspace.org.uk> > To: "Gregory P. Smith" <greg(a)krypto.org> > Cc: Python-Ideas <python-ideas(a)python.org> > Subject: Re: [Python-ideas] replace boolean methods on builtin types > with properties [py4k?] > Message-ID: > <AANLkTi=yEZ2i8j0CFF0V_P82S=WjULBFCq2gamO_xGu8(a)mail.gmail.com> > Content-Type: text/plain; charset="iso-8859-1" > > > On 13 December 2010 22:35, Gregory P. Smith <greg(a)krypto.org> wrote: > > > > A hack could be done today to have these behave as both functions and > > properties by having the property return a callable bool derived class that > > returns itself. But that seems a bit too cool yet gross... > > > > > bool derived class... good luck with that. :-) > > Michael Well it it doesn't sound that odd to me. This it's one of the (few) things I miss from Matlab. Not that parentheses are optional for function calls, but that 'true', 'false', 'Inf' and 'NaN' act both as their respective values, and as functions. Like 'ones' and 'zeros' they can be called with a size tuple to get an array of nd-array of that value. -Mark

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