Python-ideas September 2015

python-ideas@python.org

107 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

8 months, 1 week

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, 7 months

proposal: "python -m foo" should bind sys.modules['foo']

by Cameron Simpson

Hello all, This is a writeup of a proposal I floated here: https://mail.python.org/pipermail/python-list/2015-August/694905.html last Sunday. If the response is positive I wish to write a PEP. Briefly, it is a natural expectation in users that the command: python -m module_name ... used to invoke modules in "main program" mode on the command line imported the module as "module_name". It does not, it imports it as "__main__". An import within the program of "module_name" makes a new instance of the module, which causes cognitive dissonance and has the side effect that now the program has two instances of the module. What I propose is that the above command line _should_ bind sys.modules['module_name'] as well as binding '__main__' as it does currently. I'm proposing that the python -m option have this effect (python pseudocode): % python -m module.name ... runs: # pseudocode, with values hardwired for clarity import sys M = new_empty_module(name='__main__', qualname='module.name') sys.modules['__main__'] = M sys.modules['module.name'] = M # load the module code from wherever (not necessarily a file - CPython # already must do this phase) M.execfile('/path/to/module/name.py') Specificly, this would have the following two changes to current practice: 1) the module is imported _once_, and bound to both its canonical name and also to __main__. 2) imported modules acquire a new attribute __qualname__ (analogous to the recent __qualname__ on functions). This is always the conanoical name of the module as resolved by the importer. For most modules __name__ will be the same as __qualname__, but for the "main" module __name__ will be '__main__'. This change has the following advantages: The current standard boilerplate: if __name__ == '__main__': ... invoke "main program" here ... continues to work unchanged. Importantly, if the program then issues "import module_name", it is already there and the existing instance is found and used. The thread referenced above outlines my most recent encounter with this and the trouble it caused me. Followup messages include some support for this proposed change, and some criticism. The critiquing article included some workarounds for this multiple module situation, but they were (1) somewhat dependent on modules coming from a file pathname and (2) cumbersome and require every end user to adopt these changes if affected by the situation. I'd like to avoid that. Cheers, Cameron Simpson <cs(a)zip.com.au> The reasonable man adapts himself to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore all progress depends on the unreasonable man. - George Bernard Shaw

3 years, 9 months

solving multi-core Python

by Eric Snow

tl;dr Let's exploit multiple cores by fixing up subinterpreters, exposing them in Python, and adding a mechanism to safely share objects between them. This proposal is meant to be a shot over the bow, so to speak. I plan on putting together a more complete PEP some time in the future, with content that is more refined along with references to the appropriate online resources. Feedback appreciated! Offers to help even more so! :) -eric -------- Python's multi-core story is murky at best. Not only can we be more clear on the matter, we can improve Python's support. The result of any effort must make multi-core (i.e. parallelism) support in Python obvious, unmistakable, and undeniable (and keep it Pythonic). Currently we have several concurrency models represented via threading, multiprocessing, asyncio, concurrent.futures (plus others in the cheeseshop). However, in CPython the GIL means that we don't have parallelism, except through multiprocessing which requires trade-offs. (See Dave Beazley's talk at PyCon US 2015.) This is a situation I'd like us to solve once and for all for a couple of reasons. Firstly, it is a technical roadblock for some Python developers, though I don't see that as a huge factor. Regardless, secondly, it is especially a turnoff to folks looking into Python and ultimately a PR issue. The solution boils down to natively supporting multiple cores in Python code. This is not a new topic. For a long time many have clamored for death to the GIL. Several attempts have been made over the years and failed to do it without sacrificing single-threaded performance. Furthermore, removing the GIL is perhaps an obvious solution but not the only one. Others include Trent Nelson's PyParallels, STM, and other Python implementations.. Proposal ======= In some personal correspondence Nick Coghlan, he summarized my preferred approach as "the data storage separation of multiprocessing, with the low message passing overhead of threading". For Python 3.6: * expose subinterpreters to Python in a new stdlib module: "subinterpreters" * add a new SubinterpreterExecutor to concurrent.futures * add a queue.Queue-like type that will be used to explicitly share objects between subinterpreters This is less simple than it might sound, but presents what I consider the best option for getting a meaningful improvement into Python 3.6. Also, I'm not convinced that the word "subinterpreter" properly conveys the intent, for which subinterpreters is only part of the picture. So I'm open to a better name. Influences ======== Note that I'm drawing quite a bit of inspiration from elsewhere. The idea of using subinterpreters to get this (more) efficient isolated execution is not my own (I heard it from Nick). I have also spent quite a bit of time and effort researching for this proposal. As part of that, a number of people have provided invaluable insight and encouragement as I've prepared, including Guido, Nick, Brett Cannon, Barry Warsaw, and Larry Hastings. Additionally, Hoare's "Communicating Sequential Processes" (CSP) has been a big influence on this proposal. FYI, CSP is also the inspiration for Go's concurrency model (e.g. goroutines, channels, select). Dr. Sarah Mount, who has expertise in this area, has been kind enough to agree to collaborate and even co-author the PEP that I hope comes out of this proposal. My interest in this improvement has been building for several years. Recent events, including this year's language summit, have driven me to push for something concrete in Python 3.6. The subinterpreter Module ===================== The subinterpreters module would look something like this (a la threading/multiprocessing): settrace() setprofile() stack_size() active_count() enumerate() get_ident() current_subinterpreter() Subinterpreter(...) id is_alive() running() -> Task or None run(...) -> Task # wrapper around PyRun_*, auto-calls Task.start() destroy() Task(...) # analogous to a CSP process id exception() # other stuff? # for compatibility with threading.Thread: name ident is_alive() start() run() join() Channel(...) # shared by passing as an arg to the subinterpreter-running func # this API is a bit uncooked still... pop() push() poison() # maybe select() # maybe Note that Channel objects will necessarily be shared in common between subinterpreters (where bound). This sharing will happen when the one or more of the parameters to the function passed to Task() is a Channel. Thus the channel would be open to the (sub)interpreter calling Task() (or Subinterpreter.run()) and to the new subinterpreter. Also, other channels could be fed into such a shared channel, whereby those channels would then likewise be shared between the interpreters. I don't know yet if this module should include *all* the essential pieces to implement a complete CSP library. Given the inspiration that CSP is providing, it may make sense to support it fully. It would be interesting then if the implementation here allowed the (complete?) formalisms provided by CSP (thus, e.g. rigorous proofs of concurrent system models). I expect there will also be a _subinterpreters module with low-level implementation-specific details. Related Ideas and Details Under Consideration ==================================== Some of these are details that need to be sorted out. Some are secondary ideas that may be appropriate to address in this proposal or may need to be tabled. I have some others but these should be sufficient to demonstrate the range of points to consider. * further coalesce the (concurrency/parallelism) abstractions between threading, multiprocessing, asyncio, and this proposal * only allow one running Task at a time per subinterpreter * disallow threading within subinterpreters (with legacy support in C) + ignore/remove the GIL within subinterpreters (since they would be single-threaded) * use the GIL only in the main interpreter and for interaction between subinterpreters (and a "Local Interpreter Lock" for within a subinterpreter) * disallow forking within subinterpreters * only allow passing plain functions to Task() and Subinterpreter.run() (exclude closures, other callables) * object ownership model + read-only in all but 1 subinterpreter + RW in all subinterpreters + only allow 1 subinterpreter to have any refcounts to an object (except for channels) * only allow immutable objects to be shared between subinterpreters * for better immutability, move object ref counts into a separate table * freeze (new machinery or memcopy or something) objects to make them (at least temporarily) immutable * expose a more complete CSP implementation in the stdlib (or make the subinterpreters module more compliant) * treat the main interpreter differently than subinterpreters (or treat it exactly the same) * add subinterpreter support to asyncio (the interplay between them could be interesting) Key Dependencies ================ There are a few related tasks/projects that will likely need to be resolved before subinterpreters in CPython can be used in the proposed manner. The proposal could implemented either way, but it will help the multi-core effort if these are addressed first. * fixes to subinterpreter support (there are a couple individuals who should be able to provide the necessary insight) * PEP 432 (will simplify several key implementation details) * improvements to isolation between subinterpreters (file descriptors, env vars, others) Beyond those, the scale and technical scope of this project means that I am unlikely to be able to do all the work myself to land this in Python 3.6 (though I'd still give it my best shot). That will require the involvement of various experts. I expect that the project is divisible into multiple mostly independent pieces, so that will help. Python Implementations =================== They can correct me if I'm wrong, but from what I understand both Jython and IronPython already have subinterpreter support. I'll be soliciting feedback from the different Python implementors about subinterpreter support. C Extension Modules ================= Subinterpreters already isolate extension modules (and built-in modules, including sys). PEP 384 provides some help too. However, global state in C can easily leak data between subinterpreters, breaking the desired data isolation. This is something that will need to be addressed as part of the effort.

4 years, 5 months

Add appdirs module to stdlib

by Philipp A.

When defining a place for config files, cache files, and so on, people usually hack around in a OS-dependent, misinformed, and therefore wrong way. Thanks to the tempfile API we at least don’t see people hardcoding /tmp/ too much. There is a beautiful little module that does things right and is easy to use: appdirs <https://pypi.python.org/pypi/appdirs> TI think this is a *really* good candidate for the stdlib since this functionality is useful for everything that needs a cache or config (so not only GUI and CLI applications, but also scripts that download and cache stuff from the internet for faster re-running) probably we should build the API around pathlib, since i found myself not touching os.path with a barge pole since pathlib exists. i’ll write a PEP about this soon :)

5 years

Binary f-strings

by Eric V. Smith

Now that f-strings are in the 3.6 branch, I'd like to turn my attention to binary f-strings (fb'' or bf''). The idea is that: >>> bf'datestamp:{datetime.datetime.now():%Y%m%d}\r\n' Might be translated as: >>> (b'datestamp:' + ... bytes(format(datetime.datetime.now(), ... str(b'%Y%m%d', 'ascii')), ... 'ascii') + ... b'\r\n') Which would result in: b'datestamp:20150927\r\n' The only real question is: what encoding to use for the second parameter to bytes()? Since an object must return unicode from __format__(), I need to convert that to bytes in order to join everything together. But how? Here I suggest 'ascii'. Unfortunately, this would give an error if __format__ returned anything with a char greater than 127. I think we've learned that an API that only raises an exception with certain specific inputs is fragile. Guido has suggested using 'utf-8' as the encoding. That has some appeal, but if we're designing this for wire protocols, not all protocols will be using utf-8. Another idea would be to extend the "conversion char" from just 's', 'r', or 'a', which don't make much sense for bytes, to instead be a string that specifies the encoding. The default could be ascii, and if you want to specify something else: bf'datestamp:{datetime.datetime.now()!utf-8:%Y%m%d}\r\n' That would work for any encoding that doesn't have ':', '{', or '}' in the encoding name. Which seems like a reasonable restriction. And I might be over-generalizing here, but you'd presumably want to make the encoding a non-constant: bf'datestamp:{datetime.datetime.now()!{encoding}:%Y%m%d}\r\n' I think my initial proposal will be to use 'ascii', and not support any conversion characters at all for fb-strings, not even 's', 'r', and 'a'. In the future, if we want to support encodings other than 'ascii', we could then add !conversions mapping to encodings. My reasoning for using 'ascii' is that 'utf-8' could easily be an error for non-utf-8 protocols. And by using 'ascii', at least we'd give a runtime error and not put possibly bogus data into the resulting binary string. Granted, the tradeoff is that we now have a case where whether or not the code raises an exception is dependent upon the values being formatted. If 'ascii' is the default, we could later switch to 'utf-8', but we couldn't go the other way. The only place this is likely to be a problem is when formatting unicode string values. No other built-in type is going to have a non-ascii compatible character in its __format__, unless you do tricky things with datetime format_specs. Of course user-defined types can return any unicode chars from __format__. Once we make a decision, I can apply the same logic to b''.format(), if that's desirable. I'm open to suggestions on this. Thanks for reading. -- Eric.

5 years

Pre-PEP Adding A Secrets Module To The Standard Library

by Steven D'Aprano

Following on to the discussions about changing the default random number generator, I would like to propose an alternative: adding a secrets module to the standard library. Attached is a draft PEP. Feedback is requested. (I'm going to only be intermittently at the keyboard for the next day or so, so my responses may be rather slow.) -- Steve

5 years

Non-English names in the turtle module (with Spanish example)

by Al Sweigart

I've created a prototype for how we could add foreign language names to the turtle.py module and erase the language barrier for non-English schoolkids. The Tortuga module has the same functionality as You can test it out by running "pip install tortuga" https://pypi.python.org/pypi/Tortuga Since Python 2 doesn't have simpledialog, I used the PyMsgBox pure-python module for the input boxes. This code is small enough that it could be added into turtle.py. (It's just used for simple tkinter dialog boxes.) Check out the diff between Tortuga and turtle.py here: https://www.diffchecker.com/2xmbrkhk This file can be easily adapted to support multiple programming languages. Thoughts? Suggestions? -Al

5 years

PEP 505 (None coalescing operators) thoughts

by Jeff Hardy

TL;DR: +1 for the idea -1 on the propagating member-access or index operators +1 on spelling it "or?" C# has had null-coalescing since about 2005, and it's one feature I miss in every other language that I use. I view null/None as a necessary evil, so getting rid of them as soon possible is a good thing in my book. Nearly every bit of Python I've ever written would have benefitted from it, if just to get rid of the "x if x is not None else []" mess. That said, I think the other (propagating) operators are a mistake, and I think they were a mistake in C# as well. I'm not I've ever had a situation where I wished they existed, in any language. Better to get rid of the Nones as soon as possible than bring them along. It's worth reading the C# design team's notes and subsequent discussion on the associativity of "?." [1] since it goes around and around with no really good answer and no particularly intuitive behaviour. Rather than worry about that, I'd prefer to see just the basic None-coalescing added. I like Alessio's suggestion of "or?" (which seems like it should be read in a calm but threatening tone, a la Liam Neeson). It just seems more Pythonic; ?? is fine in C# but seems punctuation-heavy for Python. It does mean the ?= and ?. and ?[] are probably out, and I'm OK with that. - Jeff [1] https://roslyn.codeplex.com/discussions/543895

5 years

secrets module -- secret.keeper?

by Jim J. Jewett

Will the secrets module offer any building blocks to actually protect a secret? e.g., an easy way to encrypt a file with a given password? an encrypted datastore? a getpass that works even in IDLE? -jJ

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Python-ideas September 2015