Python-ideas October 2010

python-ideas@python.org

67 participants
31 discussions

by Andre Roberge

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

8 years, 9 months

Cofunctions PEP - Revision 4

by Greg Ewing

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:

8 years, 9 months

Possible PEP 380 tweak

by Guido van Rossum

[Changed subject] > On 2010-10-25 04:37, Guido van Rossum wrote: >> This should not require threads. >> >> Here's a bare-bones sketch using generators: [...] On Mon, Oct 25, 2010 at 3:19 AM, Jacob Holm <jh(a)improva.dk> wrote: > If you don't care about allowing the funcs to raise StopIteration, this > can actually be simplified to: [...] Indeed, I realized this after posting. :-) I had several other ideas for improvements, e.g. being able to pass an initial value to the reduce-like function or even being able to supply a reduce-like function of one's own. > More interesting (to me at least) is that this is an excellent example > of why I would like to see a version of PEP380 where "close" on a > generator can return a value (AFAICT the version of PEP380 on > http://www.python.org/dev/peps/pep-0380 is not up-to-date and does not > mention this possibility, or even link to the heated discussion we had > on python-ideas around march/april 2009). Can you dig up the link here? I recall that discussion but I don't recall a clear conclusion coming from it -- just heated debate. Based on my example I have to agree that returning a value from close() would be nice. There is a little detail, how multiple arguments to StopIteration should be interpreted, but that's not so important if it's being raised by a return statement. > Assuming that "close" on a reduce_collector generator instance returns > the value of the StopIteration raised by the "return" statements, we can > simplify the code even further: > > > def reduce_collector(func): > try: > outcome = yield > except GeneratorExit: > return None > while True: > try: > val = yield > except GeneratorExit: > return outcome > outcome = func(outcome, val) > > def parallel_reduce(iterable, funcs): > collectors = [reduce_collector(func) for func in funcs] > for coll in collectors: > next(coll) > for val in iterable: > for coll in collectors: > coll.send(val) > return [coll.close() for coll in collectors] > > > Yes, this is only saving a few lines, but I find it *much* more readable... I totally agree that not having to call throw() and catch whatever it bounces back is much nicer. (Now I wish there was a way to avoid the "try..except GeneratorExit" construct in the generator, but I think I should stop while I'm ahead. :-) The interesting thing is that I've been dealing with generators used as coroutines or tasks intensely on and off since July, and I haven't had a single need for any of the three patterns that this example happened to demonstrate: - the need to "prime" the generator in a separate step - throwing and catching GeneratorExit - getting a value from close() (I did have a lot of use for send(), throw(), and extracting a value from StopIteration.) In my context, generators are used to emulate concurrently running tasks, and "yield" is always used to mean "block until this piece of async I/O is complete, and wake me up with the result". This is similar to the "classic" trampoline code found in PEP 342. In fact, when I wrote the example for this thread, I fumbled a bit because the use of generators there is different than I had been using them (though it was no doubt thanks to having worked with them intensely that I came up with the example quickly). So, it is clear that generators are extremely versatile, and PEP 380 deserves several good use cases to explain all the API subtleties. BTW, while I have you, what do you think of Greg's "cofunctions" proposal? -- --Guido van Rossum (python.org/~guido)

10 years, 7 months

Re: [Python-ideas] stats module Was: minmax() function ...

by Steven D'Aprano

Seconding Raymond's 'drat'. Resending to python-ideas. On Sat, 16 Oct 2010 07:00:16 am Raymond Hettinger wrote: > Hello guys. If you don't mind, I would like to hijack your thread > :-) Please do :) > A few years ago, Guido and other python devvers supported a > proposal I made to create a stats module, but I didn't have time > to develop it. [...] > I think the creativity and energy of this group is much better > directed at building a quality stats module (perhaps with some R-like > capabilities). +1 Are you still interested in working on it, or is this a subtle hint that somebody else should do so? -- Steven D'Aprano

10 years, 8 months

Re: [Python-ideas] Possible PEP 380 tweak

by Greg Ewing

I've been pondering the whole close()-returning-a-value thing I've convinced myself once again that it's a bad idea. Essentially the problem is that we're trying to make the close() method, and consequently GeneratorExit, serve two different and incompatible roles. One role (the one it currently serves) is as an emergency bail-out mechanism. In that role, when we have a stack of generators delegating via yield-from, we want things to behave as thought the GeneratorExit originates in the innermost one and propagates back out of the entire stack. We don't want any of the intermediate generators to catch it and turn it into a StopIteration, because that would give the next outer one the misleading impression that it's business as usual, but it's not. This is why PEP 380 currently specifies that, after calling the close() method of the subgenerator, GeneratorExit is unconditionally re-raised in the delegating generator. The proponents of close()-returning-a-value, however, want GeneratorExit to serve another role: as a way of signalling to a consuming generator (i.e. one that is having values passed into it using send()) that there are no more values left to pass in. It seems to me that this is analogous to a function reading values from a file, or getting them from an iterator. The behaviour that's usually required in the presence of delegation is quite different in those cases. Consider a function f1, that calls another function f2, which loops reading from a file. When f2 reaches the end of the file, this is a signal that it should finish what it's doing and return a value to f1, which then continues in its usual way. Similarly, if f2 uses a for-loop to iterate over something, when the iterator is exhausted, f2 continues and returns normally. I don't see how GeneratorExit can be made to fulfil this role, i.e. as a "producer exhausted" signal, without compromising its existing one. And if that idea is dropped, the idea of close() returning a value no longer has much motivation that I can see. So how should "producer exhausted" be signalled, and how should the result of a consumer generator be returned? As for returning the result, I think it should be done using the existing PEP 380 mechanism, i.e. the generator executes a "return", consequently raising StopIteration with the value. A delegating generator will then see this as the result of a yield-from and continue normally. As for the signalling mechanism, I think that's entirely a matter for the producer and consumer to decide between themselves. One way would be to send() in a sentinel value, if there is a suitable out-of-band value available. Another would be to throw() in some pre-arranged exception, perhaps EOFError as a suggested convention. If we look at files as an analogy, we see a similar range of conventions. Most file reading operations return an empty string or bytes object on EOF. Some, such as readline(), raise an exception, because the empty element of the relevant type is also a valid return value. As an example, a consumer generator using None as a sentinel value might look like this: def summer(): tot = 0 while 1: x = yield if x is None: break tot += x return tot and a producer using it: s = summer() s.next() for x in values: s.send(x) try: s.send(None) except StopIteration as e: result = e.value Having to catch StopIteration is a little tedious, but it could easily be encapsulated in a helper function: def close_consumer(g, sentinel): try: g.send(sentinel) except StopIteration as e: return e.value The helper function could also take care of another issue that arises. What happens if a delegating consumer carries on after a subconsumer has finished and yields again? The analogous situation with files is trying to read from a file that has already signalled EOF before. In that case, the file simply signals EOF again. Similarly, calling next() on an exhausted iterator raises StopIteration again. So, if a "finished" consumer yields again, and we are using a sentinel value, the yield should return the sentinel again. We can get this behaviour by writing our helper function like this: def close_consumer(g, sentinel): while 1: try: g.send(sentinel) except StopIteration as e: return e.value So in summary, I think PEP 380 and current generator semantics are fine as they stand with regard to the behaviour of close(). Signalling the end of a stream of values to a consumer generator can and should be handled by convention, using existing facilities. -- Greg

10 years, 8 months

Accepting "?" as a valid character for identifiers

by Andre Roberge

In some languages (e.g. Scheme, Ruby, etc.), the question mark character (?) is a valid character for identifiers. I find that using it well can improve readability of programs written in those languages. Python 3 now allow all kinds of unicode characters in source code for identifiers. This is fantastic when one wants to teach programming to non-English speakers and have them use meaningful identifiers. While Python 3 does not allow ?, it does allow characters like ʔ ( http://en.wikipedia.org/wiki/Glottal_stop_%28letter%29) which can be used to good effect in writing valid identifiers such as functions that return either True or False, etc., thus improving (imo) readability. Given that one can legally mimic ? in Python identifiers, and given that the ? symbol is not used for anything in Python, would it be possible to consider allowing the use of ? as a valid character in an identifier? André

10 years, 8 months

Ordered storage of keyword arguments

by Chris Rose

I'd like to resurrect a discussion that went on a little over a year ago [1] started by Michael Foord suggesting that it'd be nice if keyword arguments' storage was implemented as an ordered dict as opposed to the current unordered form. I'm interested in picking this up for implementation, which presumably will require moving the implementation of the existing ordereddict class into the C library. Are there any issues that this might cause in implementation on the py3k development line? [1] http://mail.python.org/pipermail/python-ideas/2009-April/004163.html -- Chris R. Not to be taken literally, internally, or seriously.

10 years, 9 months

Re: [Python-ideas] Possible PEP 380 tweak

by Greg Ewing

Guido van Rossum wrote: > I'd also like to convince you to change g.close() so that it captures > and returns the return value from StopIteration if it has one. Looking at this again, I find that I'm not really sure how this impacts PEP 380. The current expansion specifies that when a delegating generator is closed, the subgenerator's close() method is called, any value it returns is ignored, and GeneratorExit is re-raised. If that close() call were to return a value, what do you think should be done with it? -- Greg

10 years, 9 months

dict changes [was: Ordered storage of keyword arguments]

by Jim Jewett

On 10/28/10, Antoine Pitrou <solipsis(a)pitrou.net> wrote: > On Thu, 28 Oct 2010 19:58:59 +0200 > spir <denis.spir(a)gmail.com> wrote: >> What does the current implementation use as buckets? > It uses an open addressing strategy. Each dict entry holds three > pointer-sized fields: key object, value object, and cached hash value > of the key. > (set entries have only two fields, since they don't hold a value object) Has anyone benchmarked not storing the hash value here? For a string dict, that hash should already be available on the string object itself, so it is redundant. Keeping it obviously improves cache locality, but ... it also makes the dict objects 50% larger, and there is a chance that the strings themselves would already be in cache anyhow. And if strings were reliably interned, the comparison check should normally just be a pointer compare -- possibly fast enough that the "different hash" shortcut doesn't buy anything. [caveats about still needing to go to the slower dict implementation for string subclasses] -jJ

10 years, 9 months

ExternalMemory

by Kristján Valur Jónsson

I find myself sometimes, when writing IO Code from C, wanting to pass memory that I have allocated internally and filled with data, to Python without copying it into a string object. To this end, I have locally created a (2.x) method called PyBuffer_FromMemoryAndDestructor(), which is the same as PyBuffer_FromMemory() except that it will call a provided destructor function with an optional arg, to release the memory address given, when no longer in use. First of all, I'd futilely like to suggest this change for 2.x. The existing PyBuffer_FromMemory() provides no lifetime management. Second, the ByBuffer object doesn't support the new Py_buffer interface, so you can't really use this then, like putting a memoryview around it. This is a fixable bug, otoh. Thirdly, in py3k I think the situation is different. There you would (probably, correct me if I'm wrong) emulate the old PyBuffer_FromMemory with a combination of the new PyBuffer_FromContiguous and a PyMemoryView_FromBuffer(). But this also does not allow any lifetime magement of the external memory. So, for py3k, I'd actually like to extend the Memoryview object, and provide something like PyMemoryView_FromExternal() that takes an optional pointer to a "void destructor(void *arg, void *ptr)) and an (void *arg), to be called when the buffer is released. K

10 years, 9 months

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Python-ideas October 2010