Mailman 3 August 2012 - Python-ideas

@classproperty, @abc.abstractclasspropery, etc.
by K. Richard Pixley Dec. 16, 2020

Dec. 16, 2020

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

10 15

Specify number of items to allocate for array.array() constructor
by Sven Rahmann Feb. 21, 2020

Feb. 21, 2020

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

14 20

format specifier for "not bytes"
by Daniel Holth July 5, 2013

July 5, 2013

While I was implementing JSON-JWS (JSON web signatures), a format which in Python 3 has to go from bytes > unicode > bytes > unicode several times in its construction, I notice I wrote a lot of bugs: "sha256=b'abcdef1234'" When I meant to say: "sha256=abcdef1234" Everything worked perfectly on Python 3 because the verifying code also generated the sha256=b'abcdef1234' as a comparison. I would have never noticed at all unless I had tried to verify the Python 3 output with Python 2. I know I'm a bad person for not having unit tests capable enough to catch this bug, a bug I wrote repeatedly in each layer of the bytes > unicode > bytes > unicode dance, and that there is no excuse for being confused at any time about the type of a variable, but I'm not willing to reform. Instead, I would like a new string formatting operator tentatively called 'notbytes': "sha256=%notbytes" % (b'abcdef1234'). It gives the same error as 'sha256='+b'abc1234' would: TypeError: Can't convert 'bytes' object to str implictly

8 17

hexdump
by anatoly techtonik April 29, 2013

April 29, 2013

Just an idea of usability fix for Python 3. hexdump module (function or bytes method is better) as simple, easy and intuitive way for dumping binary data when writing programs in Python. hexdump(bytes) - produce human readable dump of binary data, byte-by-byte representation, separated by space, 16-byte rows Rationale: 1. Debug. Generic binary data can't be output to console. A separate helper is needed to print, log or store its value in human readable format in database. This takes time. 2. Usability. binascii is ugly: name is not intuitive any more, there are a lot of functions, and it is not clear how it relates to unicode. 3. Serialization. It is convenient to have format that can be displayed in a text editor. Simple tools encourage people to use them. Practical example: >>> print(b) � � � �� >>> b '\xe6\xb0\x08\x04\xe7\x9e\x08\x04\xe7\xbc\x08\x04\xe7\xd5\x08\x04\xe7\xe4\x08\x04\xe6\xb0\x08\x04\xe7\xf0\x08\x04\xe7\xff\x08\x04\xe8\x0b\x08\x04\xe8\x1a\x08\x04\xe6\xb0\x08\x04\xe6\xb0\x08\x04' >>> print(binascii.hexlify(data)) e6b00804e79e0804e7bc0804e7d50804e7e40804e6b00804e7f00804e7ff0804e80b0804e81a0804e6b00804e6b00804 >>> >>> data = hexdump(b) >>> print(data) E6 B0 08 04 E7 9E 08 04 E7 BC 08 04 E7 D5 08 04 E7 E4 08 04 E6 B0 08 04 E7 F0 08 04 E7 FF 08 04 E8 0B 08 04 E8 1A 08 04 E6 B0 08 04 E6 B0 08 04 >>> >>> # achieving the same output with binascii is overcomplicated >>> data_lines = [binascii.hexlify(b)[i:min(i+32, len(binascii.hexlify(b)))] for i in xrange(0, len(binascii.hexlify(b)), 32)] >>> data_lines = [' '.join(l[i:min(i+2, len(l))] for i in xrange(0, len(l), 2)).upper() for l in data_lines] >>> print('\n'.join(data_lines)) E6 B0 08 04 E7 9E 08 04 E7 BC 08 04 E7 D5 08 04 E7 E4 08 04 E6 B0 08 04 E7 F0 08 04 E7 FF 08 04 E8 0B 08 04 E8 1A 08 04 E6 B0 08 04 E6 B0 08 04 On the other side, getting rather useless binascii output from hexdump() is quite trivial: >>> data.replace(' ','').replace('\n','').lower() 'e6b00804e79e0804e7bc0804e7d50804e7e40804e6b00804e7f00804e7ff0804e80b0804e81a0804e6b00804e6b00804' But more practical, for example, would be counting offset from hexdump: >>> print( ''.join( '%05x: %s\n' % (i*16,l) for i,l in enumerate(hexdump(b).split('\n')))) Etc. Conclusion: By providing better building blocks on basic level Python will become a better tool for more useful tasks. References: [1] http://stackoverflow.com/questions/2340319/python-3-1-1-string-to-hex [2] http://en.wikipedia.org/wiki/Hex_dump -- anatoly t.

8 10

Yielding through context managers
by Joshua Bartlett Jan. 8, 2013

Jan. 8, 2013

I'd like to propose adding the ability for context managers to catch and handle control passing into and out of them via yield and generator.send() / generator.next(). For instance, class cd(object): def __init__(self, path): self.inner_path = path def __enter__(self): self.outer_path = os.getcwd() os.chdir(self.inner_path) def __exit__(self, exc_type, exc_val, exc_tb): os.chdir(self.outer_path) def __yield__(self): self.inner_path = os.getcwd() os.chdir(self.outer_path) def __send__(self): self.outer_path = os.getcwd() os.chdir(self.inner_path) Here __yield__() would be called when control is yielded through the with block and __send__() would be called when control is returned via .send() or .next(). To maintain compatibility, it would not be an error to leave either __yield__ or __send__ undefined. The rationale for this is that it's sometimes useful for a context manager to set global or thread-global state as in the example above, but when the code is used in a generator, the author of the generator needs to make assumptions about what the calling code is doing. e.g. def my_generator(path): with cd(path): yield do_something() do_something_else() Even if the author of this generator knows what effect do_something() and do_something_else() have on the current working directory, the author needs to assume that the caller of the generator isn't touching the working directory. For instance, if someone were to create two my_generator() generators with different paths and advance them alternately, the resulting behaviour could be most unexpected. With the proposed change, the context manager would be able to handle this so that the author of the generator doesn't need to make these assumptions. Naturally, nested with blocks would be handled by calling __yield__ from innermost to outermost and __send__ from outermost to innermost. I rather suspect that if this change were included, someone could come up with a variant of the contextlib.contextmanager decorator to simplify writing generators for this sort of situation. Cheers, J. D. Bartlett

6 14

i18n and Python tracebacks
by Andre Roberge Oct. 28, 2012

Oct. 28, 2012

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

9 15

Re: [Python-ideas] Cofunctions - Back to Basics
by Mark Shannon Oct. 20, 2012

Oct. 20, 2012

Greg Ewing wrote: > Mark Shannon wrote: > >> Why not have proper co-routines, instead of hacked-up generators? > > What do you mean by a "proper coroutine"? > A parallel, non-concurrent, thread of execution. It should be able to transfer control from arbitrary places in execution, not within generators. Stackless provides coroutines. Greenlets are also coroutines (I think). Lua has them, and is implemented in ANSI C, so it can be done portably. See: http://www.jucs.org/jucs_10_7/coroutines_in_lua/de_moura_a_l.pdf (One of the examples in the paper uses coroutines to implement generators, which is obviously not required in Python :) ) Cheers, Mark.

9 25

Python as a tool to download stuff for bootstrapping
by anatoly techtonik Oct. 15, 2012

Oct. 15, 2012

This one is practical. I am looking at NaCl SDK download page: https://developers.google.com/native-client/sdk/download "you need Python installed", "download SDK update utility" What makes me sad that update utility is a Python script in a zip file - nacl_sdk.zip which includes shell script and a .bat file for launching this Python script. This makes me kind of sad. You have Python installed. Why can't you just crossplatformly do: mkdir nacl cd nacl python -m urllib get http://commondatastorage.googleapis.com/nativeclient-mirror/nacl/nacl_sdk/u… python update_sdk.py

5 8

Cofunctions PEP - Revision 4
by Greg Ewing Oct. 13, 2012

Oct. 13, 2012

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:

11 29

bdist naming scheme (compatibility tags) PEP
by Daniel Holth Sept. 26, 2012

Sept. 26, 2012

Today pypy and CPython's "setup.py bdist" generate the same filename but incompatible bdists. This makes it difficult to share both bdists in the same folder or index. Instead, they should generate different bdist filenames because one won't work with the other implementation. This PEP specifies a tagging system that includes enough information to decide whether a particular bdist is expected to work on a particular Python. Also at https://bitbucket.org/dholth/python-peps/raw/98cd36228c2e/pep-CTAG.txt Thanks for your feedback, Daniel Holth

5 26

Re: [Python-ideas] issue15824
by Ben Toews Sept. 10, 2012

Sept. 10, 2012

Hello, We have been discussing the value of having namedtuple as the return type for urlparse.urlparse and urlparse.urlsplit. See that thread here: http://bugs.python.org/issue15824 . I jumped the gun and submitted a patch without seeing if anyone else thought different behavior was desirable. My argument is that it would be a major usability improvement if the return type supported item assignment. Currently, something like the following is necessary in order to parse, make changes, and unparse: import urlparse url = list(urlparse.urlparse('http://www.example.com/foo/bar?hehe=haha')) url[1] = 'python.com' new_url = urllib.urlunparse(url) I think this is really clunky. I don't see any reason why we should be using a type that doesn't support item assignment and needs to be casted to a another type in order to make changes. I think an interface like this is more useful: import urlparse url = urlparse.urlparse('http://www.example.com/foo/bar?hehe=haha') url.netloc = 'www.python.com' urlparse.urlunparse(url) What do other people think? -- -Ben Toews

3 2

itertools.chunks(iterable, size, fill=None)
by anatoly techtonik Sept. 3, 2012

Sept. 3, 2012

Now that Python 3 is all about iterators (which is a user killer feature for Python according to StackOverflow - http://stackoverflow.com/questions/tagged/python) would it be nice to introduce more first class functions to work with them? One function to be exact to split string into chunks. itertools.chunks(iterable, size, fill=None) Which is the 33th most voted Python question on SO - http://stackoverflow.com/questions/312443/how-do-you-split-a-list-into-even… P.S. CC'ing to python-dev@ to notify about the thread in python-ideas.

15 25

Verbose traceback formatting
by Mike Graham Aug. 31, 2012

Aug. 31, 2012

It's possible to give a lot more on error than the default traceback gives you. I propose that Python should ship a more verbose formatter and a command line switch to use it. Here's an example of IPython's verbose formatter. I wrote a buggy program: > def f(a): > x = a * 4 > y = a - 4 > return x / y > > def main(): > for i in xrange(100): > f(i) > > main() and then ran it in IPython with verbose tracebacks and got the following output: > ZeroDivisionError Traceback (most recent call last) > > /home/mike/foo.py in <module>() > 8 f(i) > 9 > ---> 10 main() > global main = <function main at 0x10bd7d0> > 11 > 12 > > /home/mike/foo.py in main() > 6 def main(): > 7 for i in xrange(100): > ----> 8 f(i) > global f = <function f at 0x10bd758> > i = 4 > 9 > 10 main() > > /home/mike/foo.py in f(a=4) > 2 x = a * 4 > 3 y = a - 4 > ----> 4 return x / y > x = 16 > y = 0 > 5 > 6 def main(): > > ZeroDivisionError: integer division or modulo by zero This is very handy! The reprs of all locals are input so I can see what the values of a, x, and y were when I had my error and there are a few lines of code on either side of the line that matters to help me get oriented. The former feature is the more powerful one, although enabling this by default is a bad idea; (first and foremost, this can be a security hazard). I can't count how many trips into pdb this would have saved me. I think having this feature be part of Python itself would be very helpful to new learners and to those helping them. I constantly deal with learners seeking help who are unable to clearly provide the actual values and types of the objects in the code they're having trouble with; it would be nice simply to say, "Show me a verbose traceback" and might even help them to debug their code without assistance. Mike

7 11

Add a "hasmethod()" builtin?
by Guido van Rossum Aug. 31, 2012

Aug. 31, 2012

There's a concept that's sometimes useful when explaining behavior of certain Python operations in terms of simpler ones, and it is "does the class of x define a method m?". This currently cannot expressed using hasattr(): hasattr(x, 'm') might find an instance variable named m, but that is not a method (and there are contexts where they are not interchangeable); hasattr(type(x), 'm') might find a *metaclass* method. Example of the former (assume Python 3): class C: def __add__(self, other): return 42 c = C() c.__add__ = lambda *args: 0 c + 1 # prints 42, not 0 Example of the latter: class C: pass c = C() hasattr(C, 'mro') # prints True, since mro() is a method of the standard metaclass ('type'). c.mro() # raises AttributeError The use case I am mainly thinking of is the formal explanation of the semantics of binary (and other) operators, e.g. def __add__(a, b): r = NotImplemented if hasmethod(a, '__add__'): r = a.__add__(b) if r is NotImplemented and hasmethod(b, '__radd__'): r = b.__radd__(a) if r is NotImplemented: raise TypeError return r (Caveat: it's even more complicated if type(b) is a subclass of type(a).) I'm not sure if it would be better if the first argument of hasmethod() was a type instead of an instance (so the example would use hasattr(type(a), '__add__') etc.). It's also interesting to figure out what should happen for proxy types. (Proxy types in general need a better foundation.) Thoughts? -- --Guido van Rossum (python.org/~guido)

5 4

Unpack of sequences
by Carlo Pires Aug. 31, 2012

Aug. 31, 2012

Hi, I was just wondering why unpack of sequences did not follow same behavior of functions parameters. I mean: first, *rest = 'a b c'.split() should work in python, why doesn't it? -- Carlo Pires

17 53

hook zipfile.ZipExtFile to check secure hash sums
by Daniel Holth Aug. 30, 2012

Aug. 30, 2012

I am checking the sha256 sums of all the files in a zip archive as it is being extracted by overriding ZipExtFile._update_crc, but it is inconvenient. It would be nice to have a hook, for example the ZipExtFile constructor could be a property of ZipFile and conveniently replaced with a ZipExtFile subclass.

3 4

inheriting docstrings and mutable docstings for classes
by Mark Adam Aug. 24, 2012

Aug. 24, 2012

On Thu, Jun 9, 2011 at 8:05 PM, Nick Coghlan <ncoghlan(a)gmail.com> wrote: > On Fri, Jun 10, 2011 at 9:54 AM, Eric Snow <ericsnowcurrently(a)gmail.com> > wrote: > > I'm +1 on having __doc__ be inherited. > > -1. Subclasses are not the same thing as the original class so > docstring inheritance should be requested explicitly. > > Hmm, subclasses are supposed to represent an IS-A relationship in my oldschool OOP books, typically a specialization of a more general (ie. abstract) outer class. The multiple-inheritance case does make things a bit more sloppy, but then this problem has already been resolved by the BDFL via MRO, the same could probably apply with docstrings, with the user updating or using a blank docstring when that general rule doesn't work. In any case, I found myself wanting this auto-inheritance for easier testing with doctest. I don't want my subclasses to mess up invariants in my parent classes, and if the doctests were inherited this would be easy to check. Just my (late) 2 cents worth after examining the current python issues list. mark Sorry for any formatting problems, this is a forward after accidently replying only to ncoghlan.

3 2

Programming recommendations (PEP 8) and boolean values
by Michael Foord Aug. 12, 2012

Aug. 12, 2012

Hey all, True and False are singletons, so if you want to check precisely for True and False then an identity check seems appropriate. However the "Programming Recommendations" section of PEP 8 has this to say on the topic: Don't compare boolean values to True or False using ==. Yes: if greeting: No: if greeting == True: Worse: if greeting is True: http://www.python.org/dev/peps/pep-0008/#programming-recommendations It seems to me that there is an important distinction between testing that an object is either the boolean True or False and merely checking the "truthiness" of an object. Many a bug has been caused by an empty container object (or some other falsey object) falling into an "if not value" clause that was actually meant to check for the presence of False or None. Why does PEP 8 recommend not testing "boolean values" (which to me implies "values you expect to be a bool") using equality or identity, and more specifically why does it say that using an identity check is worse than an equality check? As this is Python-ideas and not python-list, my specific suggestion is to modify the wording of that section - or just removing it altogether as I don't think it can be adequately clarified without using lots of words. All the best, Michael Foord -- 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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Standard types documentation (was Re: Programming recommendations (PEP 8) and boolean values)
by Nick Coghlan Aug. 8, 2012

Aug. 8, 2012

On Thu, Aug 9, 2012 at 11:43 AM, Alexander Belopolsky <alexander.belopolsky(a)gmail.com> wrote: > As a result, there is no one place where one can find information > about bool. I wonder if it should go somewhere under section 4.4. > After all, > > >>> isinstance(True, int) > True I'll be working on the builtin types documentation at the PyConAU sprints in a couple of weeks. They haven't aged well :( Cheers, Nick. -- Nick Coghlan | ncoghlan(a)gmail.com | Brisbane, Australia

1 0

Re: [Python-ideas] Programming recommendations (PEP 8) and boolean values
by Steven D'Aprano Aug. 8, 2012

Aug. 8, 2012

Taking the liberty to return this to the mailing list. On 09/08/12 08:05, Michael Foord wrote: >> > Why does the PEP say that == True is preferred to is True? >>> >> >> > >> > Because there surely are still libraries out there that return 0 and 1 >> > as true/false values. The bool type was introduced in (by memory) >> > Python 2.2 or 2.3, so very old code may fail, or worse, silently do the >> > wrong thing if you use "is True". >> > >> > > Surely? I haven't seen one in*years*. Nevertheless, "return 1" is still legal Python and was once the idiomatic way of returning a flag. If you don't have a good reason to break such old code, why break it? -- Steven

1 0

Why no dict.discard?
by MRAB Aug. 7, 2012

Aug. 7, 2012

The 'set' class has a 'discard' method, but dict doesn't. I know that I can just delete the key and catch the exception if it's absent, but I can also 'remove' a member from a set and catch the exception if it's absent, OR just 'discard' it to avoid an exception. How much interest would there be in adding 'discard' to dict too?

2 2

abc.optionalabstractmethod
by Eric Snow Aug. 7, 2012

Aug. 7, 2012

Sometimes you want to specific an optional method in an abstract base class. Currently we don't have a consistent way of doing so, instead having to mix in the old way of defining "abstract" methods: class MyABC(metaclass=ABCMeta): ... def do_something_optional(self): """An optional method for doing something.""" raise NotImplementedError This came up in issue 15502[1], where we are splitting importlib.abc.Finder into MetaPathFinder and PathEntryFinder. These have a method, invalidate_caches(), which is optional. It would be nice to have a new decorator akin to abstractmethod that would allow defining an optional interface in a consistent way. Something like optionalabstractmethod (or some better name). Then the above example would be like this: class MyABC(metaclass=ABCMeta): ... @optionalabstractmethod def do_something_optional(self): """An optional method for doing something.""" Thoughts? -eric [1] http://bugs.python.org/issue15502; Barry Warsaw voiced what I've considered on multiple occasions.

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Re: [Python-ideas] compatibility triples for binary distributions
by Miki Tebeka Aug. 7, 2012

Aug. 7, 2012

IMO implementation names should be compatible with PEP-421<http://www.python.org/dev/peps/pep-0421/>. Also instead of a cryptic long string, maybe some structured one?. For example (JSON): {"implementation":"cpython","machine":"x86_64"} It's longer but more readable IMO (and easier to parse). On Wednesday, July 25, 2012 7:55:34 AM UTC-7, Daniel Holth wrote: > > I am working on a specification that might be useful in the PKG-INFO > Platform or Supported-Platform tags. It tries to express which Python > versions a built distribution works on with a triple > (Implementation+Language Version, ABI, Architecture), anticipating an > ABI that is not tied to a single CPython release. > > A typical tag would be py27-noabi-noarch or cp33-cp33dmu-linux_x86_64. > > cp27-noabi-noarch is a package that requires CPython 2.7 but doesn't > include extension modules. > > The Python implementation is abbreviated. Each implementation has a > two-letter code: > > py: Generic Python > cp: CPython > ip: IronPython > pp: PyPy > jy: Jython > > concatenated with py_version_nodot “27”. The minor version can be > omitted “py2” or “py3” when appropriate. > > The ABI tag is an abbreviated SOABI “cp33m”, or, for “pure Python” > packages, “noabi”. For pypy it was more or less suggested that the ABI > would have to be a hash of the source code revision and the > translation/compilation options. > > The platform tag is distutils.util.get_platform() with all periods and > hyphens replaced with underscore, or the string ‘noarch’. > > I use the term "built distribution" instead of "binary distribution" > because it includes pure python packages that for example have had > 2to3 run ahead of time and are installable without setup.py. > > Will it work? The ABI in particular may be so messy that it should be > lumped with architecture. What is the ABI for packages that use ctypes or > cffi? >

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changing sys.stdout encoding
by Rurpy Aug. 7, 2012

Aug. 7, 2012

In my first foray into Python3 I've encountered this problem: I work in a multi-language environment. I've written a number of tools, mostly command-line, that generate output on stdout. Because these tools and their output are used by various people in varying environments, the tools all have an --encoding option to provide output that meets the needs and preferences of the output's ultimate consumers. In converting them to Python3, I found the best (if not very pleasant) way to do this in Python3 was to put something like this near the top of each tool[*1]: import codecs sys.stdout = codecs.getwriter(opts.encoding)(sys.stdout.buffer) What I want to be able to put there instead is: sys.stdout.set_encoding (opts.encoding) The former I found on the internet -- there is zero probability I could have figured that out from the Python docs. It is obscure to anyone (who has like me generally only needed to deal with .encode() and .decode()) who hasn't encountered it before or dealt much with the codecs module. It is excessively complex for what is conceptually a simple and straight-forward operation. It requires the import of the codecs module in programs that other- wise don't need it [*2], and the reading of the codecs docs (not a shining example of clarity themselves) to understand it. In short it is butt ugly relative to what I generally get in Python. Would it be feasible to provide something like .set_encoding() on textio streams? (Or make .encoding a writeable property?; it seems to intentionally be non-writeable for some reason but is that reason really unavoidable?) If doing this for textio in general is too hard, then what about encapsulating the codecs stuff above in a sys.set_encoding() function? Needing to change the encoding of a sys.std* stream is not an uncommon need and a user should not have to go through the codecs dance above to do so IMO. ---- [*1] There are other ways to change stdout's encoding but they all have problems AFAICT. PYTHONIOENCODING can't easily be changed dynamically within program. Reopening stdout as binary, or using the binary interface to text stdout, requires a explicit encode call at each write site. Overloading print() is obscure because it requires reader to notice print was overloaded. [*2] I don't mean the actual import of the codecs module which occurs anyway; I mean the extra visual and cognitive noise introduced by the presence of the import statement in the source.

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Better support for finalization with weakrefs
by Richard Oudkerk Aug. 2, 2012

Aug. 2, 2012

I would like to see better support for the use of weakrefs callbacks for object finalization. The current issues with weakref callbacks include: 1. They are rather low level, and working out how to use them correctly requires a bit of head scratching. One must find somewhere to store the weakref till after the referent is dead, and without accidentally keeping the referent alive. Then one must ensure that the callback frees the weakref (without leaving any remnant ref-cycles). When it is an option, using a __del__ method is far less hassle. 2. Callbacks invoked during interpreter shutdown are troublesome. For instance they can throw exceptions because module globals have been replaced by None. 3. Sometimes you want the callback to be called at program exit even if the referent is still alive. 4. Exceptions thrown in callbacks do not produce a traceback. This can make debugging rather awkward. (Maybe this is because printing tracebacks is problematic during interpreter shutdown?) (Note that problems 2-4 also apply to using __del__ methods.) If possible I would like to see the weakref module provide a finalize class to address these issues. Trivial usage might be >>> class Kenny: pass ... >>> kenny = Kenny() >>> finalize(kenny, print, "you killed kenny!") <finalize.finalize object at 0xffed4f2c> >>> del kenny you killed kenny! Prototype at https://gist.github.com/3208245 Cheers, Richard

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