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In Python, functions are first-class objects that can be created and passed around dynamically. Python's limited support for anonymous functions is the lambda construct. An example is the anonymous function which squares its input, called with the argument of 5:
This leads to duplicating some functionality. For example: List comprehensions vs. for-loops; Conditional expressions vs. if blocks; The eval() vs. exec() built-in functions (in Python 2, exec is a statement); the former is for expressions, the latter is for statements
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A built-in function, or builtin function, or intrinsic function, is a function for which the compiler generates code at compile time or provides in a way other than for other functions. [23] A built-in function does not need to be defined like other functions since it is built in to the programming language. [24]
In Python, if a name is intended to be "private", it is prefixed by one or two underscores. Private variables are enforced in Python only by convention. Names can also be suffixed with an underscore to prevent conflict with Python keywords. Prefixing with double underscores changes behaviour in classes with regard to name mangling.
The linker needs a great deal of information on each program entity. For example, to correctly link a function it needs its name, the number of arguments and their types, and so on. The simple programming languages of the 1970s, like C, only distinguished subroutines by their name, ignoring other information including parameter and return types.
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 ...
defines a primary function simpleFun that implicitly applies custom subfunction myCustomFun to each element of an array using built-in function arrayfun. Alternatively, it may be desirable to abstract the mechanisms of the array storage container from the user by defining a custom object-oriented MATLAB implementation of the Iterator Pattern.