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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:
Like raw strings, there can be any number of equals signs between the square brackets, provided both the opening and closing tags have a matching number of equals signs; this allows nesting as long as nested block comments/raw strings use a different number of equals signs than their enclosing comment: --[[comment --[=[ nested comment ...
For example, in Python, raw strings are preceded by an r or R – compare 'C:\\Windows' with r'C:\Windows' (though, a Python raw string cannot end in an odd number of backslashes). Python 2 also distinguishes two types of strings: 8-bit ASCII ("bytes") strings (the default), explicitly indicated with a b or B prefix, and Unicode strings ...
Python 3's input function behaves like Python 2's raw_input function, in that the input is always returned as a string rather than being evaluated as an expression Moving reduce (but not map or filter ) out of the built-in namespace and into functools (the rationale being code that uses reduce is less readable than code that uses a for loop and ...
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.
An input argument (the argument to an input parameter) must be a value, such as an initialized variable or literal, and must not be redefined or assigned to; an output argument must be an assignable variable, but it need not be initialized, any existing value is not accessible, and must be assigned a value; and an input/output argument must be ...
Data validation is intended to provide certain well-defined guarantees for fitness and consistency of data in an application or automated system. Data validation rules can be defined and designed using various methodologies, and be deployed in various contexts. [1]
An internal iterator is a higher-order function (often taking anonymous functions) that traverses a collection while applying a function to each element. For example, Python's map function applies a caller-defined function to each element: