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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 ...
cross-platform (Python) 2.1.1 BSD: Kid (templating language) Ryan Tomayko cross-platform (Python) 0.9.6 2006-12-20 Mako: Michael Bayer cross-platform (Python) 1.1.2 2020-03-01 MIT License: MATLAB: The MathWorks, Inc. Windows, macOS, Linux 1984 9.5 2018-09-12 Proprietary: M-Power: mrc cross-platform (Java) 2004 Proprietary: Microsoft Visual ...
Python. The use of the triple-quotes to comment-out lines of source, does not actually form a comment. [19] The enclosed text becomes a string literal, which Python usually ignores (except when it is the first statement in the body of a module, class or function; see docstring). Elixir
Comparison of Java and .NET platforms ALGOL 58's influence on ALGOL 60; ALGOL 60: Comparisons with other languages; Comparison of ALGOL 68 and C++; ALGOL 68: Comparisons with other languages; Compatibility of C and C++; Comparison of Pascal and Borland Delphi; Comparison of Object Pascal and C; Comparison of Pascal and C; Comparison of Java and C++
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:
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.
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