Python-ideas March 2015

python-ideas@python.org

86 participants
54 discussions

Specify number of items to allocate for array.array() constructor

by Sven Rahmann

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

4 months, 2 weeks

Implicit string literal concatenation considered harmful?

by Guido van Rossum

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

2 years, 3 months

Reprs of classes and functions

by Serhiy Storchaka

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

4 years, 11 months

Re: [Python-ideas] Top 10 Python modules that need a redesign Was: Geo coordinates conversion in stdlib

by Alexander Belopolsky

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

5 years, 2 months

Simpler Customization of Class Creation, next round

by Martin Teichmann

Hello everybody, recently I posted PEP 487, a simpler customization of class creation. For newcomers: I propose the introduction of a __init_subclass__ classmethod which initializes subclasses of a class, simplifying what metaclasses can already do. It took me a while to digest all the ideas from the list here, but well, we're not in a hurry. So, I updated PEP 487, and pushed the changes to github at https://github.com/tecki/peps/commits/master I applied the following changes: PEP 487 contained the possibility to set a namespace for subclasses. The most important usecase for this feature would be to have an OrderedDict as the class definition namespace. As Eric Snow pointed out, that will be soon standard anyways, so I took out this feature from the PEP. The implementation on PyPI now just uses an OrderedDict as a namespace, anticipating the expected changes to CPython. I also did some reading on possible usecases for PEP 487, so that it actually may be used by someone. Some Traits-like thing is a standard usecase, so I looked especially at IPython's traitlets, which are a simple example of that usecase. Currently traitlets use both __new__ and __init__ of a metaclass. So I tried to also introduce a __new_subclass__ the same way I introduced __init_subclass__. This turned out much harder than I thought, actually impossible, because it is type.__new__ that sets the method resolution order, so making super() work in a __new_subclass__ hook is a chicken-egg problem: we need the MRO to find the next base class to call, but the most basic base class is the one creating the MRO. Nick, how did you solve that problem in PEP 422? Anyhow, I think that traitlets can also be written just using __init_subclass__. There is just this weird hint in the docs that you should use __new__ for metaclasses, not __init__, a hint I never understood as the reasons when to use __new__ or __init__ are precisely the same for normal classes and metaclasses. So I think we don't miss out much when not having __new_subclass__. I also updated the implementation of PEP 487, it's still at https://pypi.python.org/pypi/metaclass Greetings Martin

5 years, 2 months

Adding rule about trailing comma.

by INADA Naoki

What about adding rule about trailing comma? Yes: foo(aaa, bbb) or foo(aaa, bbb, ) No: foo(aaa, bbb,) # except one-value tuple. or foo(aaa, bbb ) -- INADA Naoki <songofacandy(a)gmail.com>

5 years, 3 months

History on proposals for Macros?

by Matthew Rocklin

I want Python to have macros. This is obviously a hard sell. I'm willing to do some legwork to demonstrate value. What would a good proposal include? Are there good examples of failed proposals on this topic? Is the core team open to this topic? Thank you for your time, - Mathew Rocklin

5 years, 3 months

A mutable alternative to namedtuple

by Luciano Ramalho

Sometimes we need a simple class to hold some mutable attributes, provide a nice repr, support == for testing, and support iterable unpacking, so you can write: >>> p = Point(3, 4) >>> x, y = p That's very much like the classes built by namedtuple, but mutable. I propose we add to the collections module another class factory. I am calling it plainclass, but perhaps we can think of a better name. Here is how it would be used: >>> import collections >>> Point = collections.plainclass('Point', 'x y') The signature of the plainclass function would be exactly the same as namedtuple, supporting the same alternative ways of naming the attributes. The semantics of the generated Point class would be like this code: https://gist.github.com/ramalho/fd3d367e9d3b2a659faf What do you think? Cheers, Luciano PS. I am aware that there are "Namespace" classes in the standard library (e.g. [2]). They solve a different problem. [2] https://docs.python.org/3/library/argparse.html#argparse.Namespace -- Luciano Ramalho | Author of Fluent Python (O'Reilly, 2015) | http://shop.oreilly.com/product/0636920032519.do | Professor em: http://python.pro.br | Twitter: @ramalhoorg

5 years, 3 months

infinite dates: psycopg2 would support them

by Thomas Güttler

Hi, any progress on infinite datetimes? I just got the commitment from psycopg2 (lib to connect to PostgreSQL) developers, that they will support them, if python would: https://github.com/psycopg/psycopg2/issues/283#issuecomment-88016783 I can't help you with code in this context. I have never started a crowd funding campaign. Do you think it would be successful? Regards, Thomas Güttler -- http://www.thomas-guettler.de/

5 years, 3 months

Re: [Python-ideas] PEP 484: Generating test inputs from type hints

by David MacIver

(Sorry for the manual thread continuation, I wasn't previously on the mailing list) I presume 'support' could and would include a version of given() that > accessed .__annotations__. This is on my list of planned features independently of PEP 484 FWIW. It's on the long list of nice to have but minor things that didn't make it into 1.0. One of the problems is that I am for the moment somewhat committed to supporting Python 2.7 as well as Python 3 (I really wish I wasn't), or I would have probably built Hypothesis on using annotations from the beginning. To a degree though it's fortunate that I didn't given PEP 484. It doesn't look like I would be able to build the full range of features Hypothesis needs for @given using only type annotations, and 484 suggests the goal is to move to those being the only valid ones. The reason for this is that Hypothesis deliberately lets you mix strategies in with the specifiers used for annotation. So for example you can do something like: Palindromes = strategy(str).map(lambda x: x + str(reversed(x))) This is now a SearchStrategy object that still returns strings, but only ones that are palindromes. You can now do something like @given([Palindromes]) def test_this_is_a_list_of_palindromes(xs): # I'm not actually sure what interesting things you can say about a list of palindromes... So the point is that you can use a SearchStrategy deep inside the "type" signatures that Hypothesis uses, despite SearchStrategy not actually being at all type-like. (It actually used to be the case that an earlier version of SearchStrategy allowed you to test whether a value could have come from that strategy, which would have made them a bit more "type-like", but this proved to be a bad idea and the work that let me remove it was one of the best decisions I made in the design of Hypothesis) So basically I would fully intend for Hypothesis to become a consumer of types and annotations, but I don't think they can be used as a primary building block of it. (Note: I don't consider this a problem with PEP 484, which looks like a good proposal. Hypothesis's requirements are just weird and specialized and don't quite match type checking) > Of course, if every 'test_xyz' were to be > decorated with the same decorator, then the decorator could be omitted > and the fuzzing moved into the test runner. I'd be moderately against this being the primary mode of using Hypothesis, even without the above caveats. One of the things I like about Hypothesis right now is that because it just gives you Python functions it can be very unopinionated about what you're using to run your tests (even if in practice basically everyone is using unittest or pytest). However it should be relatively easy to support alongside once I've done some much needed refactoring of the core example exploration code. David

5 years, 3 months

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Python-ideas March 2015