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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.
The Simplified Wrapper and Interface Generator (SWIG) is an open-source software tool used to connect computer programs or libraries written in C or C++ with scripting languages such as Lua, Perl, PHP, Python, R, Ruby, Tcl, and other language implementations like C#, Java, JavaScript, Go, D, OCaml, Octave, Scilab and Scheme.
It is used to parse source code into concrete syntax trees usable in compilers, interpreters, text editors, and static analyzers. [ 1 ] [ 2 ] It is specialized for use in text editors, as it supports incremental parsing for updating parse trees while code is edited in real time, [ 3 ] and provides a built-in S-expression query system for ...
T4 Template/Text File: Any text format such as XML, XAML, C# files or just plain text files. Umple: Umple, Java, Javascript, PHP Active Tier Umple code embedding one or more of Java, Python, C++, PHP or Ruby Pure Umple code describing associations, patterns, state machines, etc.
However, a generator is an object with persistent state, which can repeatedly enter and leave the same scope. A generator call can then be used in place of a list, or other structure whose elements will be iterated over. Whenever the for loop in the example requires the next item, the generator is called, and yields the next item.
An example of a Python generator returning an iterator for the Fibonacci numbers using Python's yield statement follows: def fibonacci ( limit ): a , b = 0 , 1 for _ in range ( limit ): yield a a , b = b , a + b for number in fibonacci ( 100 ): # The generator constructs an iterator print ( number )
The C language does not have collections or a foreach construct. However, it has several standard data structures that can be used as collections, and foreach can be made easily with a macro.
In Python, functions are first-class objects, just like strings, numbers, lists etc. This feature eliminates the need to write a function object in many cases. Any object with a __call__() method can be called using function-call syntax. An example is this accumulator class (based on Paul Graham's study on programming language syntax and ...