Python-ideas February 2018

python-ideas@python.org

64 participants
35 discussions

List assignment - extended slicing inconsistency

by Alexander Heger

What little documentation I could find, providing a stride on the assignment target for a list is supposed to trigger 'advanced slicing' causing element-wise replacement - and hence requiring that the source iterable has the appropriate number of elements. >>> a = [0,1,2,3] >>> a[::2] = [4,5] >>> a [4, 1, 5, 3] >>> a[::2] = [4,5,6] Traceback (most recent call last): File "<stdin>", line 1, in <module> ValueError: attempt to assign sequence of size 3 to extended slice of size 2 This is in contrast to regular slicing (*without* a stride), allowing to replace a *range* by another sequence of arbitrary length. >>> a = [0,1,2,3] >>> a[:3] = [4] >>> a [4, 3] Issue ===== When, however, a stride of `1` is specified, advanced slicing is not triggered. >>> a = [0,1,2,3] >>> a[:3:1] = [4] >>> a [4, 3] If advanced slicing had been triggered, there should have been a ValueError instead. Expected behaviour: >>> a = [0,1,2,3] >>> a[:3:1] = [4] Traceback (most recent call last): File "<stdin>", line 1, in <module> ValueError: attempt to assign sequence of size 1 to extended slice of size 3 I think that is an inconsistency in the language that should be fixed. Why do we need this? ==================== One may want this as extra check as well so that list does not change size. Depending on implementation, it may come with performance benefits as well. One could, though, argue that you still get the same result if you do all correctly >>> a = [0,1,2,3] >>> a[:3:1] = [4,5,6] >>> a [4, 5, 6, 3] But I disagree that there should be no error when it is wrong. *Strides that are not None should always trigger advanced slicing.* Other Data Types ================ This change should also be applied to bytearray, etc., though see below. Concerns ======== It may break some code that uses advanced slicing and expects regular slicing to occur? These cases should be rare, and the error message should be clear enough to allow fixes? I assume these cases should be exceptionally rare. If the implementation relies on `slice.indices(len(seq))[2] == 1` to determine about advance slicing or not, that would require some refactoring. If it is only `slice.stride in (1, None)` then this could easily replaced by checking against None. Will there be issues with syntax consistency with other data types, in particular outside the core library? - I always found that the dynamic behaviour of lists w/r non-advanced slicing to be somewhat peculiar in the first place, though, undeniably, it can be immensely useful. - Most external data types with fixed memory such as numpy do not have this dynamic flexibility, and the behavior of regular slicing on assignment is the same as regular slicing. The proposed change would increase consistency with these other data types. More surprises ============== >>> import array >>> a[1::2] = a[3:3] Traceback (most recent call last): File "<stdin>", line 1, in <module> ValueError: attempt to assign sequence of size 0 to extended slice of size 2 whereas >>> a = [1,2,3,4,5] >>> a[1::2] = a[3:3] Traceback (most recent call last): File "<stdin>", line 1, in <module> ValueError: attempt to assign sequence of size 0 to extended slice of size 2 >>> a = bytearray(b'12345') >>> a[1::2] = a[3:3] >>> a bytearray(b'135') but numpy >>> import numpy as np >>> a = np.array([1,2,3,4,5]) >>> a[1::2] = a[3:3] Traceback (most recent call last): File "<stdin>", line 1, in <module> ValueError: could not broadcast input array from shape (0) into shape (2) and >>> import numpy as np >>> a[1:2] = a[3:3] Traceback (most recent call last): File "<stdin>", line 1, in <module> ValueError: could not broadcast input array from shape (0) into shape (1) The latter two as expected. memoryview behaves the same. Issue 2 ======= Whereas NumPy is know to behave differently as a data type with fixed memory layout, and is not part of the standard library anyway, the difference in behaviour between lists and arrays I find disconcerting. This should be resolved to a consistent behaviour. Proposal 2 ========== Arrays and bytearrays should should adopt the same advanced slicing behaviour I suggest for lists. Concerns 2 ========== This has the potential for a lot more side effects in existing code, but as before in most cases error message should be triggered. Summary ======= I find it it not acceptable as a good language design that there is a large range of behaviour on slicing in assignment target for the different native (and standard library) data type of seemingly similar kind, and that users have to figure out for each data type by testing - or at the very least remember if documented - how it behaves on slicing in assignment targets. There should be a consistent behaviour at the very least, ideally even one with a clear user interface as suggested for lists. -Alexander

3 years

Temporary variables in comprehensions

by fhsxfhsx

As far as I can see, a comprehension like alist = [f(x) for x in range(10)] is better than a for-loop for x in range(10): alist.append(f(x)) because the previous one shows every element of the list explicitly so that we don't need to handle `append` mentally. But when it comes to something like [f(x) + g(f(x)) for x in range(10)] you find you have to sacrifice some readableness if you don't want two f(x) which might slow down your code. Someone may argue that one can write [y + g(y) for y in [f(x) for x in range(10)]] but it's not as clear as to show what `y` is in a subsequent clause, not to say there'll be another temporary list built in the process. We can even replace every comprehension with map and filter, but that would face the same problems. In a word, what I'm arguing is that we need a way to assign temporary variables in a comprehension. In my opinion, code like [y + g(y) for x in range(10) **some syntax for `y=f(x)` here**] is more natural than any solution we now have. And that's why I pro the new syntax, it's clear, explicit and readable, and is nothing beyond the functionality of the present comprehensions so it's not complicated. And I hope the discussion could focus more on whether we should allow assigning temporary variables in comprehensions rather than how to solve the specific example I mentioned above.

3 years

by Sylvain MARIE

The numbers module provides very useful ABC for the 'numeric tower', able to abstract away the differences between python primitives and for example numpy primitives. I could not find any equivalent for Booleans. However numpy defines np.bool too, so being able to have an abstract Boolean class for both python bool and numpy bool would be great. Here is a version that I included in valid8 in the meantime ----------------------- class Boolean(metaclass=ABCMeta): """ An abstract base class for booleans, similar to what is available in numbers see https://docs.python.org/3.5/library/numbers.html """ __slots__ = () @abstractmethod def __bool__(self): """Return a builtin bool instance. Called for bool(self).""" @abstractmethod def __and__(self, other): """self & other""" @abstractmethod def __rand__(self, other): """other & self""" @abstractmethod def __xor__(self, other): """self ^ other""" @abstractmethod def __rxor__(self, other): """other ^ self""" @abstractmethod def __or__(self, other): """self | other""" @abstractmethod def __ror__(self, other): """other | self""" @abstractmethod def __invert__(self): """~self""" # register bool and numpy bool_ as virtual subclasses # so that issubclass(bool, Boolean) = issubclass(np.bool_, Boolean) = True Boolean.register(bool) try: import numpy as np Boolean.register(np.bool_) except ImportError: # silently escape pass --------------------------- If that topic was already discussed and settled in the past, please ignore this thread - apologies for not being able to find it. Best regards Sylvain

3 years

Why CPython is still behind in performance for some widely used patterns ?

by Pau Freixes

Hi, This mail is the consequence of a true story, a story where CPython got defeated by Javascript, Java, C# and Go. One of the teams of the company where Im working had a kind of benchmark to compare the different languages on top of their respective "official" web servers such as Node.js, Aiohttp, Dropwizard and so on. The test by itself was pretty simple and tried to test the happy path of the logic, a piece of code that fetches N rules from another system and then apply them to X whatevers also fetched from another system, something like that def filter(rule, whatever): if rule.x in whatever.x: return True rules = get_rules() whatevers = get_whatevers() for rule in rules: for whatever in whatevers: if filter(rule, whatever): cnt = cnt + 1 return cnt The performance of Python compared with the other languages was almost x10 times slower. It's true that they didn't optimize the code, but they did not for any language having for all of them the same cost in terms of iterations. Once I saw the code I proposed a pair of changes, remove the call to the filter function making it "inline" and caching the rule's attributes, something like that for rule in rules: x = rule.x for whatever in whatevers: if x in whatever.x: cnt += 1 The performance of the CPython boosted x3/x4 just doing these "silly" things. The case of the rule cache IMHO is very striking, we have plenty examples in many repositories where the caching of none local variables is a widely used pattern, why hasn't been considered a way to do it implicitly and by default? The case of the slowness to call functions in CPython is quite recurrent and looks like its an unsolved problem at all. Sure I'm missing many things, and I do not have all of the information. This mail wants to get all of this information that might help me to understand why we are here - CPython - regarding this two slow patterns. This could be considered an unimportant thing, but its more relevant than someone could expect, at least IMHO. If the default code that you can write in a language is by default slow and exists an alternative to make it faster, this language is doing something wrong. BTW: pypy looks like is immunized [1] [1] https://gist.github.com/pfreixes/d60d00761093c3bdaf29da025a004582 -- --pau

3 years

importlib: making FileFinder easier to extend

by Erik Bray

Hello, Brief problem statement: Let's say I have a custom file type (say, with extension .foo) and these .foo files are included in a package (along with other Python modules with standard extensions like .py and .so), and I want to make these .foo files importable like any other module. On its face, importlib.machinery.FileFinder makes this easy. I make a loader for my custom file type (say, FooSourceLoader), and I can use the FileFinder.path_hook helper like: sys.path_hooks.insert(0, FileFinder.path_hook((FooSourceLoader, ['.foo']))) sys.path_importer_cache.clear() Great--now I can import my .foo modules like any other Python module. However, any standard Python modules now cannot be imported. The way PathFinder sys.meta_path hook works, sys.path_hooks entries are first-come-first-serve, and furthermore FileFinder.path_hook is very promiscuous--it will take over module loading for *any* directory on sys.path, regardless what the file extensions are in that directory. So although this mechanism is provided by the stdlib, it can't really be used for this purpose without breaking imports of normal modules (and maybe it's not intended for that purpose, but the documentation is unclear). There are a number of different ways one could get around this. One might be to pass FileFinder.path_hook loaders/extension pairs for all the basic file types known by the Python interpreter. Unfortunately there's no great way to get that information. *I* know that I want to support .py, .pyc, .so etc. files, and I know which loaders to use for them. But that's really information that should belong to the Python interpreter, and not something that should be reverse-engineered. In fact, there is such a mapping provided by importlib.machinery._get_supported_file_loaders(), but this is not a publicly documented function. One could probably think of other workarounds. For example you could implement a custom sys.meta_path hook. But I think it shouldn't be necessary to go to higher levels of abstraction in order to do this--the default sys.path handler should be able to handle this use case. In order to support adding support for new file types to sys.path_hooks, I ended up implementing the following hack: ############################################################# import os import sys from importlib.abc import PathEntryFinder @PathEntryFinder.register class MetaFileFinder: """ A 'middleware', if you will, between the PathFinder sys.meta_path hook, and sys.path_hooks hooks--particularly FileFinder. The hook returned by FileFinder.path_hook is rather 'promiscuous' in that it will handle *any* directory. So if one wants to insert another FileFinder.path_hook into sys.path_hooks, that will totally take over importing for any directory, and previous path hooks will be ignored. This class provides its own sys.path_hooks hook as follows: If inserted on sys.path_hooks (it should be inserted early so that it can supersede anything else). Its find_spec method then calls each hook on sys.path_hooks after itself and, for each hook that can handle the given sys.path entry, it calls the hook to create a finder, and calls that finder's find_spec. So each sys.path_hooks entry is tried until a spec is found or all finders are exhausted. """ def __init__(self, path): if not os.path.isdir(path): raise ImportError('only directories are supported', path=path) self.path = path self._finder_cache = {} def __repr__(self): return '{}({!r})'.format(self.__class__.__name__, self.path) def find_spec(self, fullname, target=None): if not sys.path_hooks: return None for hook in sys.path_hooks: if hook is self.__class__: continue finder = None try: if hook in self._finder_cache: finder = self._finder_cache[hook] if finder is None: # We've tried this finder before and got an ImportError continue except TypeError: # The hook is unhashable pass if finder is None: try: finder = hook(self.path) except ImportError: pass try: self._finder_cache[hook] = finder except TypeError: # The hook is unhashable for some reason so we don't bother # caching it pass if finder is not None: spec = finder.find_spec(fullname, target) if spec is not None: return spec # Module spec not found through any of the finders return None def invalidate_caches(self): for finder in self._finder_cache.values(): finder.invalidate_caches() @classmethod def install(cls): sys.path_hooks.insert(0, cls) sys.path_importer_cache.clear() ############################################################# This works, for example, like: >>> MetaFileFinder.install() >>> sys.path_hooks.append(FileFinder.path_hook((SourceFileLoader, ['.foo']))) And now, .foo modules are importable, without breaking support for the built-in module types. This is still overkill though. I feel like there should instead be a way to, say, extend a sys.path_hooks hook based on FileFinder so as to be able to support loading other file types, without having to go above the default sys.meta_path hooks. A small, but related problem I noticed in the way FileFinder.path_hook is implemented, is that for almost *every directory* that gets cached in sys.path_importer_cache, a new FileFinder instance is created with its own self._loaders attribute, each containing a copy of the same list of (loader, extensions) tuples. I calculated that on one large project this alone accounted for nearly 1 MB. Not a big deal in the grand scheme of things, but still a bit overkill. ISTM it would kill two birds with one stone if FileFinder were changed, or there were a subclass thereof, that had a class attribute containing the standard loader/extension mappings. This in turn could simply be appended to in order to support new extension types. Thanks, E

3 years

PEP 468

by guido

Gesendet von Mail für Windows 10

3 years

Coming up with an alternative to PEP 505's None-aware operators

by Nick Coghlan

The recent thread on variable assignment in comprehensions has prompted me to finally share https://gist.github.com/ncoghlan/a1b0482fc1ee3c3a11fc7ae64833a315 with a wider audience (see the comments there for some notes on iterations I've already been through on the idea). == The general idea == The general idea would be to introduce a *single* statement local reference using a new keyword with a symbolic prefix: "?it" * `(?it=expr)` is a new atomic expression for an "it reference binding" (whitespace would be permitted around "?it" and "=", but PEP 8 would recommend against it in general) * subsequent subexpressions (in execution order) can reference the bound subexpression using `?it` (an "it reference") * `?it` is reset between statements, including before entering the suite within a compound statement (if you want a persistent binding, use a named variable) * for conditional expressions, put the reference binding in the conditional, as that gets executed first * to avoid ambiguity, especially in function calls (where it could be confused with keyword argument syntax), the parentheses around reference bindings are always required * unlike regular variables, you can't close over statement local references (the nested scope will get an UnboundLocalError if you try it) The core inspiration here is English pronouns (hence the choice of keyword): we don't generally define arbitrary terms in the middle of sentences, but we *do* use pronouns to refer back to concepts introduced earlier in the sentence. And while it's not an especially common practice, pronouns are sometimes even used in a sentence *before* the concept they refer to ;) If we did pursue this, then PEPs 505, 532, and 535 would all be withdrawn or rejected (with the direction being to use an it-reference instead). == Examples == `None`-aware attribute access: value = ?it.strip()[4:].upper() if (?it=var1) is not None else None `None`-aware subscript access: value = ?it[4:].upper() if (?it=var1) is not None else None `None`-coalescense: value = ?it if (?it=var1) is not None else ?it if (?it=var2) is not None else var3 `NaN`-coalescence: value = ?it if not math.isnan((?it=var1)) else ?it if not math.isnan((?that=var2)) else var3 Conditional function call: value = ?it() if (?it=calculate) is not None else default Avoiding repeated evaluation of a comprehension filter condition: filtered_values = [?it for x in keys if (?it=get_value(x)) is not None] Avoiding repeated evaluation for range and slice bounds: range((?it=calculate_start()), ?it+10) data[(?it=calculate_start()):?it+10] Avoiding repeated evaluation in chained comparisons: value if (?it=lower_bound()) <= value < ?it+tolerance else 0 Avoiding repeated evaluation in an f-string: print(f"{?it=get_value()!r} is printed in pure ASCII as {?it!a} and in Unicode as {?it}" == Possible future extensions == One possible future extension would be to pursue PEP 3150, treating the nested namespace as an it reference binding, giving: sorted_data = sorted(data, key=?it.sort_key) given ?it=: def sort_key(item): return item.attr1, item.attr2 (A potential bonus of that spelling is that it may be possible to make "given ?it=:" the syntactic keyword introducing the suite, allowing "given" itself to continue to be used as a variable name) Another possible extension would be to combine it references with `as` clauses on if statements and while loops: if (?it=pattern.match(data)) is not None as matched: ... while (?it=pattern.match(data)) is not None as matched: ... == Why not arbitrary embedded assignments? == Primarily because embedded assignments are inherently hard to read, especially in long expressions. Restricting things to one pronoun, and then pursuing PEP 3150's given clause in order to expand to multiple statement local names should help nudge folks towards breaking things up into multiple statements rather than writing ever more complex one-liners. That said, the ?-prefix notation is deliberately designed such that it *could* be used with arbitrary identifiers rather then being limited to a single specific keyword, and the explicit lack of closure support means that there wouldn't be any complex nested scope issues associated with lambda expressions, generator expressions, or container comprehensions. With that approach, "?it" would just be an idiomatic default name like "self" or "cls" rather than being a true keyword. Given arbitrary identifier support, some of the earlier examples might instead be written as: value = ?f() if (?f=calculate) is not None else default range((?start=calculate_start()), ?start+10) value if (?lower=lower_bound()) <= value < ?lower+tolerance else 0 The main practical downside to this approach is that *all* the semantic weight ends up resting on the symbolic "?" prefix, which makes it very difficult to look up as a new Python user. With a keyword embedded in the construct, there's a higher chance that folks will be able to guess the right term to search for (i.e. "python it expression" or "python it keyword"). Another downside of this more flexible option is that it likely *wouldn't* be amenable to the "if expr as name:" syntax extension, as there wouldn't be a single defined pronoun expression to bind the name to. However, the extension to PEP 3150 would allow the statement local namespace to be given an arbitrary name: sorted_data = sorted(data, key=?ns.sort_key) given ?ns=: def sort_key(item): return item.attr1, item.attr2 Cheers, Nick. -- Nick Coghlan | ncoghlan(a)gmail.com | Brisbane, Australia

3 years

Re: [Python-ideas] Coming up with an alternative to PEP 505's None-aware operators

by rymg19＠gmail.com

I don't know...to me this looks downright ugly and an awkward special case. It feels like it combines reading difficulty of inline assignment with the awkwardness of a magic word and the ugliness of using ?. Basically, every con of the other proposals combined... -- Ryan (ライアン) Yoko Shimomura, ryo (supercell/EGOIST), Hiroyuki Sawano >> everyone elsehttps://refi64.com/ On Feb 15, 2018 at 8:07 PM, <Nick Coghlan <ncoghlan(a)gmail.com>> wrote: The recent thread on variable assignment in comprehensions has prompted me to finally share https://gist.github.com/ncoghlan/a1b0482fc1ee3c3a11fc7ae64833a315 with a wider audience (see the comments there for some notes on iterations I've already been through on the idea). == The general idea == The general idea would be to introduce a *single* statement local reference using a new keyword with a symbolic prefix: "?it" * `(?it=expr)` is a new atomic expression for an "it reference binding" (whitespace would be permitted around "?it" and "=", but PEP 8 would recommend against it in general) * subsequent subexpressions (in execution order) can reference the bound subexpression using `?it` (an "it reference") * `?it` is reset between statements, including before entering the suite within a compound statement (if you want a persistent binding, use a named variable) * for conditional expressions, put the reference binding in the conditional, as that gets executed first * to avoid ambiguity, especially in function calls (where it could be confused with keyword argument syntax), the parentheses around reference bindings are always required * unlike regular variables, you can't close over statement local references (the nested scope will get an UnboundLocalError if you try it) The core inspiration here is English pronouns (hence the choice of keyword): we don't generally define arbitrary terms in the middle of sentences, but we *do* use pronouns to refer back to concepts introduced earlier in the sentence. And while it's not an especially common practice, pronouns are sometimes even used in a sentence *before* the concept they refer to ;) If we did pursue this, then PEPs 505, 532, and 535 would all be withdrawn or rejected (with the direction being to use an it-reference instead). == Examples == `None`-aware attribute access: value = ?it.strip()[4:].upper() if (?it=var1) is not None else None `None`-aware subscript access: value = ?it[4:].upper() if (?it=var1) is not None else None `None`-coalescense: value = ?it if (?it=var1) is not None else ?it if (?it=var2) is not None else var3 `NaN`-coalescence: value = ?it if not math.isnan((?it=var1)) else ?it if not math.isnan((?that=var2)) else var3 Conditional function call: value = ?it() if (?it=calculate) is not None else default Avoiding repeated evaluation of a comprehension filter condition: filtered_values = [?it for x in keys if (?it=get_value(x)) is not None] Avoiding repeated evaluation for range and slice bounds: range((?it=calculate_start()), ?it+10) data[(?it=calculate_start()):?it+10] Avoiding repeated evaluation in chained comparisons: value if (?it=lower_bound()) <= value < ?it+tolerance else 0 Avoiding repeated evaluation in an f-string: print(f"{?it=get_value()!r} is printed in pure ASCII as {?it!a} and in Unicode as {?it}" == Possible future extensions == One possible future extension would be to pursue PEP 3150, treating the nested namespace as an it reference binding, giving: sorted_data = sorted(data, key=?it.sort_key) given ?it=: def sort_key(item): return item.attr1, item.attr2 (A potential bonus of that spelling is that it may be possible to make "given ?it=:" the syntactic keyword introducing the suite, allowing "given" itself to continue to be used as a variable name) Another possible extension would be to combine it references with `as` clauses on if statements and while loops: if (?it=pattern.match(data)) is not None as matched: ... while (?it=pattern.match(data)) is not None as matched: ... == Why not arbitrary embedded assignments? == Primarily because embedded assignments are inherently hard to read, especially in long expressions. Restricting things to one pronoun, and then pursuing PEP 3150's given clause in order to expand to multiple statement local names should help nudge folks towards breaking things up into multiple statements rather than writing ever more complex one-liners. That said, the ?-prefix notation is deliberately designed such that it *could* be used with arbitrary identifiers rather then being limited to a single specific keyword, and the explicit lack of closure support means that there wouldn't be any complex nested scope issues associated with lambda expressions, generator expressions, or container comprehensions. With that approach, "?it" would just be an idiomatic default name like "self" or "cls" rather than being a true keyword. Given arbitrary identifier support, some of the earlier examples might instead be written as: value = ?f() if (?f=calculate) is not None else default range((?start=calculate_start()), ?start+10) value if (?lower=lower_bound()) <= value < ?lower+tolerance else 0 The main practical downside to this approach is that *all* the semantic weight ends up resting on the symbolic "?" prefix, which makes it very difficult to look up as a new Python user. With a keyword embedded in the construct, there's a higher chance that folks will be able to guess the right term to search for (i.e. "python it expression" or "python it keyword"). Another downside of this more flexible option is that it likely *wouldn't* be amenable to the "if expr as name:" syntax extension, as there wouldn't be a single defined pronoun expression to bind the name to. However, the extension to PEP 3150 would allow the statement local namespace to be given an arbitrary name: sorted_data = sorted(data, key=?ns.sort_key) given ?ns=: def sort_key(item): return item.attr1, item.attr2 Cheers, Nick. -- Nick Coghlan | ncoghlan(a)gmail.com | Brisbane, Australia _______________________________________________ Python-ideas mailing list Python-ideas(a)python.org https://mail.python.org/mailman/listinfo/python-ideas Code of Conduct: http://python.org/psf/codeofconduct/

3 years

(no subject)

by guido

3 years

(no subject)

by guido

3 years

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Python-ideas February 2018