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...iterables with close() methods. (Note: the application must invoke the start_response() callable before the iterable yields its first body string, so that the server can send the headers before any body content. However, this invocation may be performed by the iterable's first iteration, so servers must not assume that start_response() has been called before they begin iterating over the iterable.) Finally, servers and gateways must not directly use any other attributes of the iterable returned...
...iterating through asynchronous iterators is proposed: async for TARGET in ITER: BLOCK else: BLOCK2 which is semantically equivalent to: iter = (ITER) iter = type(iter).__aiter__(iter) running = True while running: try: TARGET = await type(iter).__anext__(iter) except StopAsyncIteration: running = False else: BLOCK else: BLOCK2 It is a TypeError to pass a regular iterable without __aiter__ method to async for. It is a SyntaxError to use async f...
...iterator should not assume the entire iterator will be consumed, as it may be closed early by the server. (Note: the application must invoke the start_response() callable before the iterable yields its first body bytestring, so that the server can send the headers before any body content. However, this invocation may be performed by the iterable's first iteration, so servers must not assume that start_response() has been called before they begin iterating over the iterable.) Finally, servers an...
...iteration can begin. (Actually, the length of the step argument isn't needed until the second element is returned.) A pseudo-implementation (using only the stop argument, and assuming that it is iterable) is: def xrange(stop): i = 0 for x in stop: yield i i += 1 Testing whether to use int() or lazy iteration could be done by checking for an __iter__ attribute. (This example assumes the presence of generators, but could easily have been implemented as a plain iterator ...
...Iterable The base class for classes defining __iter__. The __iter__ method should always return an instance of Iterator (see below). The abstract __iter__ method returns an empty iterator. Iterator The base class for classes defining __next__. This derives from Iterable. The abstract __next__ method raises StopIteration. The concrete __iter__ method returns self. Note the distinction between Iterable and Iterator: an Iterable can be iterated over, i.e. supports the __iter__ methods; an Ite...
...iterator. If the sent value is None, the iterator's __next__() method is called. If the sent value is not None, the iterator's send() method is called. If the call raises StopIteration, the delegating generator is resumed. Any other exception is propagated to the delegating generator. Exceptions other than GeneratorExit thrown into the delegating generator are passed to the throw() method of the iterator. If the call raises StopIteration, the delegating generator is resumed. Any other except...
...iter__ method, then it could be annotated by a union type: class OldIterable(Sized, Protocol[T]): def __getitem__(self, item: int) -> T: ... CompatIterable = Union[Iterable[T], OldIterable[T]] class A: def __iter__(self) -> Iterator[str]: ... class B: def __len__(self) -> int: ... def __getitem__(self, item: int) -> str: ... def iterate(it: CompatIterable[str]) -> None: ... iterate(A()) # OK iterate(B()) # OK Since there is a reasonable alternative for ...
...Iteration PEP:212 Title:Loop Counter Iteration Author:nowonder at nowonder.de (Peter Schneider-Kamp) Status:Rejected Type:Standards Track Created:22-Aug-2000 Python-Version:2.1 Post-History: Contents Rejection Notice Introduction Motivation Loop counter iteration The Proposed Solutions Non-reserved keyword indexing Built-in functions indices and irange Methods for sequence objects Implementations Backward Compatibility Issues Copyright References Rejection Notice This PEP h...
...itertools module as itertools.izip(). This function provides lazy behavior, consuming single elements and producing a single tuple on each pass. The "just-in-time" style saves memory and runs faster than its list based counterpart, zip(). The itertools module also added itertools.repeat() and itertools.chain(). These tools can be used together to pad sequences with None (to match the behavior of map(None, seqn)): zip(firstseq, chain(secondseq, repeat(None))) References [1]http://doc...
...iterators, and StopIteration The proposal does not change the relationship between generators and iterators: a generator object is still an iterator, and not all iterators are generators. Generators have additional methods that iterators don't have, like send and throw. All this is unchanged. Nothing changes for generator users -- only authors of generator functions may have to learn something new. (This includes authors of generator expressions that depend on early termination of the iterat...
...itertools.ifilter() and itertools.imap(). In contrast, the utility of other itertools will be enhanced by generator expressions: dotproduct = sum(x*y for x,y in itertools.izip(x_vector, y_vector)) Having a syntax similar to list comprehensions also makes it easy to convert existing code into a generator expression when scaling up application. Early timings showed that generators had a significant performance advantage over list comprehensions. However, the latter were highly optimized for Py...
...iterator object is returned; this conforms to the iterator protocol, so in particular can be used in for-loops in a natural way. Note that when the intent is clear from context, the unqualified name "generator" may be used to refer either to a generator-function or a generator-iterator. Each time the .next() method of a generator-iterator is invoked, the code in the body of the generator-function is executed until a yield or return statement (see below) is encountered, or until the end of the b...
...iterable unpacking operator features unnecessary restrictions that can harm readability. Unpacking multiple times has an obvious rationale. When you want to unpack several iterables into a function definition or follow an unpack with more positional arguments, the most natural way would be to write: function(**kw_arguments, **more_arguments) function(*arguments, argument) Simple examples where this is useful are print and str.format. Instead, you could be forced to write: kwargs = dict(kw_a...
...iterators/generators instantiated elsewhere should typically not be littered with close calls. The rare case of code that has acquired ownership of and need to properly deal with all of iterators, generators and generators acquiring resources that need timely release, is easily solved: if hasattr(iterator, 'close'): iterator.close() Open Issues Definitive semantics ought to be chosen. Currently Guido favors Exception Semantics. If the generator yields a value instead of terminating, or...
...iterator11273 argtools10869 Notes: as reported by Dinu Gherman's pycount -- ie. this is lines of real code, not counting blanks, comments, or docstrings (but counting literal strings, such as help and usage text) ie. with all explicit help text removed. For ArgParser and argtools, this is just a big literal string, since these libraries don't do automatic help generation. For Optik, this just means removing the help parameter ...
...iteration. Thread: "Parallel iteration syntax", https://mail.python.org/pipermail/python-3000/2006-March/000210.html Strings will stay iterable. Thread: "Making strings non-iterable", https://mail.python.org/pipermail/python-3000/2006-April/000759.html There will be no syntax to sort the result of a generator expression or list comprehension. sorted() covers all use cases. Thread: "Adding sorting to generator comprehension", https://mail.python.org/pipermail/python-3000/2006-April/001295...
...iterator): for VAR in iterator: yield EXPR a = list(genexpr(iter(ITERABLE))) Let's add a simple assignment expression. Original code: def f(): a = [TARGET := EXPR for VAR in ITERABLE] Translation: def f(): if False: TARGET = None # Dead code to ensure TARGET is a local variable def genexpr(iterator): nonlocal TARGET for VAR in iterator: TARGET = EXPR yield TARGET a = list(genexpr(iter(ITERABLE))) ...
...itervalues(): for key, value in d.items(): --> for key, value in d.iteritems(): Contra-indications: If you need a list, do not change the return type: def getids(): return d.keys() Some dictionary-like objects may not define iter methods: for k in dictlike.keys(): Iterators do not support slicing, sorting or other operations: k = d.keys(); j = k[:] Dictionary iterators prohibit modifying the dictionary: for k in d.keys(): del[k] stat Methods Replac...
...iterdir(). However, iterX() functions in Python (mostly found in Python 2) tend to be simple iterator equivalents of their non-iterator counterparts. For example, dict.iterkeys() is just an iterator version of dict.keys(), but the objects returned are identical. In scandir()'s case, however, the return values are quite different objects (DirEntry objects vs filename strings), so this should probably be reflected by a difference in name -- hence scandir(). See some relevant discussion on python-d...
...iterators, which resumes the generator and sends a value that becomes the result of the current yield-expression. The send() method returns the next value yielded by the generator, or raises StopIteration if the generator exits without yielding another value. Add a new throw() method for generator-iterators, which raises an exception at the point where the generator was paused, and which returns the next value yielded by the generator, raising StopIteration if the generator exits without yieldi...