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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:
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.
DDL—Data Definition Language; DDoS—Distributed Denial of Service; DDR—Double Data Rate; DEC—Digital Equipment Corporation; DES—Data Encryption Standard; dev—development; DFA—Deterministic Finite Automaton; DFD—Data Flow Diagram; DFS—Depth-First Search; DFS—Distributed File System; DGD—Dworkin's Game Driver
Pages in category "Articles with example Python (programming language) code" The following 200 pages are in this category, out of approximately 201 total. This list may not reflect recent changes. (previous page)
Languages with an explicit return statement create the possibility of multiple return statements in the same function. Whether or not that is a good thing is controversial. Strong adherents of structured programming make sure each function has a single entry and a single exit (SESE).
The term closure is often used as a synonym for anonymous function, though strictly, an anonymous function is a function literal without a name, while a closure is an instance of a function, a value, whose non-local variables have been bound either to values or to storage locations (depending on the language; see the lexical environment section below).
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]
Pandas (styled as pandas) is a software library written for the Python programming language for data manipulation and analysis.In particular, it offers data structures and operations for manipulating numerical tables and time series.