Mailman 3 February 2013 - 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 21 Feb '20

21 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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while conditional in list comprehension ??
by Wolfgang Maier 21 Feb '14

21 Feb '14

Dear all, I guess this is so obvious that someone must have suggested it before: in list comprehensions you can currently exclude items based on the if conditional, e.g.: [n for n in range(1,1000) if n % 4 == 0] Why not extend this filtering by allowing a while statement in addition to if, as in: [n for n in range(1,1000) while n < 400] Trivial effect, I agree, in this example since you could achieve the same by using range(1,400), but I hope you get the point. This intuitively understandable extension would provide a big speed-up for sorted lists where processing all the input is unnecessary. Consider this: some_names=["Adam", "Andrew", "Arthur", "Bob", "Caroline","Lancelot"] # a sorted list of names [n for n in some_names if n.startswith("A")] # certainly gives a list of all names starting with A, but . [n for n in some_names while n.startswith("A")] # would have saved two comparisons Best, Wolfgang

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format specifier for "not bytes"
by Daniel Holth 05 Jul '13

05 Jul '13

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

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frozenset literals
by Hua Lu 21 May '13

21 May '13

This is similar to another proposal: http://mail.python.org/pipermail/python-3000/2008-January/011798.html Anyway, I was using ast.literal_eval and attempted to use frozenset({...}) as a key in a dictionary, which failed, because frozenset isn't a literal (though putting frozenset in the environment would be a security risk). I am currently working around this with tuples, but I'd like a literal for representing frozensets as well. I also use frozensets elsewhere in the code in ways similar to Raymond's original suggestion. Perhaps something like f{...} for declaring frozenset( comprehension)? literals?

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hexdump
by anatoly techtonik 29 Apr '13

29 Apr '13

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.

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Poll about -h,--help options
by anatoly techtonik 13 Apr '13

13 Apr '13

Hi, Is it interesting to know if people expect -h to work as a --help equivalent by default? As it directly affects best practices of using Python in command line, can we run such poll on python.org? I thought that this stuff is obvious, but it appears that it is not, so I'd like to see this usability study - it will be interesting for the Python community to know itself better. -- anatoly t.

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argparse - add support for environment variables
by Miki Tebeka 27 Mar '13

27 Mar '13

Greetings, The usual way of resolving configuration is command line -> environment -> default. Currently argparse supports only command line -> default, I'd like to suggest an optional "env" keyword to add_argument that will also resolve from environment. (And also optional env dictionary to the ArgumentParser __init__ method [or to parse_args], which will default to os.environ). Example: [spam.py] parser = ArgumentParser() parser.add_argument('--spam', env='SPAM', default=7) args = parser.parse_args() print(args.spam) ./spam.py -> 7 ./spam.py --spam=12 -> 12 SPAM=9 ./spam.py -> 9 SPAM=9 ./spam.py --spam=12 -> 12 What do you think? -- Miki

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OrderedDict for kwargs and class statement namespace
by Eric Snow 02 Mar '13

02 Mar '13

Just wanted to put out some feelers for the feasibility of these two features: * have the **kwargs param be an OrderedDict rather than a dict * have class definitions happen relative to an OrderedDict by default rather than a dict, and still overridable by a metaclass's __prepare__(). Both of these will need OrderedDict in C, which is getting close (issue #16991). -eric

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range
by Wolfgang Maier 28 Feb '13

28 Feb '13

Dear all, what do you think about allowing the use of operators on ranges? I thought of things like: a = range(1,10) b = range(5,12) intersect = a & b # equivalent to intersect = range(5,10) merge = a | b # equivalent to merge = range(1,12) to make this work in more complex cases, like: a = range(1,10) b = range(12,15) merge = a | b # equivalent to sth. like range(range(1,10),range(12,15)) maybe range nesting would be desirable, but the full sequence of values of such a nested range could still be calculated on demand. Such syntax would allow for the generation of more complex sequences, and, as a side-effect, ranges could also be checked for overlap easily: if a & b: do_something() this whole idea is reminiscent, of course, of what's implemented for sets already, so like there you could think of intersect = a & b as shorthand for intersect = a.intersection(b) Opinions?

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