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String functions are used in computer programming languages to manipulate a string or query information about a string (some do both).. Most programming languages that have a string datatype will have some string functions although there may be other low-level ways within each language to handle strings directly.
Introduced in Python 2.2 as an optional feature and finalized in version 2.3, generators are Python's mechanism for lazy evaluation of a function that would otherwise return a space-prohibitive or computationally intensive list. This is an example to lazily generate the prime numbers:
[52] [53] While Python 2.7 and older versions are officially unsupported, a different unofficial Python implementation, PyPy, continues to support Python 2, i.e. "2.7.18+" (plus 3.10), with the plus meaning (at least some) "backported security updates". [54] Python 3.0 was released on 3 December 2008, with some new semantics and changed syntax.
The enclosed text becomes a string literal, which Python usually ignores (except when it is the first statement in the body of a module, class or function; see docstring). Elixir. The above trick used in Python also works in Elixir, but the compiler will throw a warning if it spots this.
The first stage is the token generation, or lexical analysis, by which the input character stream is split into meaningful symbols defined by a grammar of regular expressions. For example, a calculator program would look at an input such as " 12 * (3 + 4)^2 " and split it into the tokens 12 , * , ( , 3 , + , 4 , ) , ^ , 2 , each of which is a ...
Beyond syntactic requirements of C/C++, implicit concatenation is a form of syntactic sugar, making it simpler to split string literals across several lines, avoiding the need for line continuation (via backslashes) and allowing one to add comments to parts of strings. For example, in Python, one can comment a regular expression in this way: [21]
As a more general class of examples, an algorithm on a tree can be decomposed into its behavior on a value and its behavior on children, and can be split up into two mutually recursive functions, one specifying the behavior on a tree, calling the forest function for the forest of children, and one specifying the behavior on a forest, calling ...
Callable units provide a powerful programming tool. [2] The primary purpose is to allow for the decomposition of a large and/or complicated problem into chunks that have relatively low cognitive load and to assign the chunks meaningful names (unless they are anonymous). Judicious application can reduce the cost of developing and maintaining ...