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The decorator pattern is a design pattern used in statically-typed object-oriented programming languages to allow functionality to be added to objects at run time; Python decorators add functionality to functions and methods at definition time, and thus are a higher-level construct than decorator-pattern classes.
The Decorator Pattern (or an implementation of this design pattern in Python - as the above example) should not be confused with Python Decorators, a language feature of Python. They are different things. Second to the Python Wiki: The Decorator Pattern is a pattern described in the Design Patterns Book.
The eval() vs. exec() built-in functions (in Python 2, exec is a statement); the former is for expressions, the latter is for statements; Statements cannot be a part of an expression—so list and other comprehensions or lambda expressions, all being expressions, cannot contain statements.
The Zen of Python is a collection of 19 "guiding principles" for writing computer programs that influence the design of the Python programming language. [1] Python code that aligns with these principles is often referred to as "Pythonic". [2] Software engineer Tim Peters wrote this set of principles and posted it on the Python mailing list in ...
Decorator can refer to: A house painter and decorator; Interior design; Decorator pattern in object-oriented programming; Function decorators, in Python;
Python's runtime does not restrict access to such attributes, the mangling only prevents name collisions if a derived class defines an attribute with the same name. On encountering name mangled attributes, Python transforms these names by prepending a single underscore and the name of the enclosing class, for example: >>>
In lisps and lambda calculus, functions are generally first-class citizens. Loosely, this means that functions can be inputs and outputs for other functions. This can simplify the definition of some functions. For example, writing a function to output the first n square numbers in Racket can be done accordingly:
Mojo was created for an easy transition from Python. The language has syntax similar to Python's, with inferred static typing, [25] and allows users to import Python modules. [26] It uses LLVM and MLIR as its compilation backend. [7] [27] [28] The language also intends to add a foreign function interface to call C/C++ and Python