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In Python, a generator can be thought of as an iterator that contains a frozen stack frame. Whenever next() is called on the iterator, Python resumes the frozen frame, which executes normally until the next yield statement is reached. The generator's frame is then frozen again, and the yielded value is returned to the caller.
In Python, a generator is an iterator constructor: a function that returns an iterator. An example of a Python generator returning an iterator for the Fibonacci numbers using Python's yield statement follows:
Python 2.5 implements better support for coroutine-like functionality, based on extended generators ; Python 3.3 improves this ability, by supporting delegating to a subgenerator ; Python 3.4 introduces a comprehensive asynchronous I/O framework as standardized in PEP 3156, which includes coroutines that leverage subgenerator delegation
A distinctive feature of CLU iterators is that they are implemented as coroutines, with each value being provided to the caller via a yield statement. Iterators like those in CLU are now a common feature of many modern languages, such as C#, Ruby, and Python, though recently they are often referred to as generators.
In Python 3, filter was changed to return an iterator rather than a list. [13] The complementary functionality, returning an iterator over elements for which the predicate is false, is also available in the standard library as filterfalse in the itertools module. Ruby: enum.find_all {block} enum.select {block} enum is an Enumeration Rust ...
The loop calls the Iterator::next method on the iterator before executing the loop body. If Iterator::next returns Some(_), the value inside is assigned to the pattern and the loop body is executed; if it returns None, the loop is terminated.
In programming language theory, lazy evaluation, or call-by-need, [1] is an evaluation strategy which delays the evaluation of an expression until its value is needed (non-strict evaluation) and which avoids repeated evaluations (by the use of sharing).
Python sets are very much like mathematical sets, and support operations like set intersection and union. Python also features a frozenset class for immutable sets, see Collection types. Dictionaries (class dict) are mutable mappings tying keys and corresponding values. Python has special syntax to create dictionaries ({key: value})