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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.
There are subtle differences and distinctions in the use of the terms "generator" and "iterator", which vary between authors and languages. [5] 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 ...
Python 3.0, released in 2008, was a major revision not completely backward-compatible with earlier versions. Python 2.7.18, released in 2020, was the last release of Python 2. [36] Python consistently ranks as one of the most popular programming languages, and has gained widespread use in the machine learning community. [37] [38] [39] [40]
A further option invokes with-hash-table-iterator, an iterator-creating macro, the processing of which is intended to be driven by the caller. ( with-hash-table-iterator ( entry-generator phone-book ) ( loop do ( multiple-value-bind ( has-entry key value ) ( entry-generator ) ( if has-entry ( format T "~&~s => ~s" key value ) ( loop-finish )))))
In Python 3.x the range() function [28] returns a generator which computes elements of the list on demand. Elements are only generated when they are needed (e.g., when print(r[3]) is evaluated in the following example), so this is an example of lazy or deferred evaluation:
For brevity, these words will have the specified meanings in the following tables (unless noted to be part of language syntax): funcN A function.
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 ( PEP 380 ) Python 3.4 introduces a comprehensive asynchronous I/O framework as standardized in PEP 3156 , which includes coroutines that leverage subgenerator delegation
In Python terminology, the definition of a coroutine is a generator function, while an instance of it is a generator iterator, and thus a finally clause in a generator function becomes a finalizer in generator iterators instantiated from this function.