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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.
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:
Porting programs can be problematic because a word not reserved by one system or compiler might be reserved by another. Because reserved words cannot be used as identifiers, users may choose deliberate misspellings of reserved words as identifiers instead, such as clazz for Java variables of type Class. [1]
By mathematical analogy, a metasyntactic variable is a word that is a variable for other words, just as in algebra letters are used as variables for numbers. [ 1 ] Metasyntactic variables are used to name entities such as variables, functions, and commands whose exact identity is unimportant and serve only to demonstrate a concept, which is ...
As the user types a variable name, the feature also makes suggestions to complete the variable as they are typed. IntelliSense continues to show parameters, highlighting the pertinent one, as the user types. The user can "force" IntelliSense to show its pop-up list without context by using Ctrl+J or Ctrl+Space.
If a variable is only referenced by a single identifier, that identifier can simply be called the name of the variable; otherwise, we can speak of it as one of the names of the variable. For instance, in the previous example the identifier "total_count" is the name of the variable in question, and "r" is another name of the same variable.
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In information theory, linguistics, and computer science, the Levenshtein distance is a string metric for measuring the difference between two sequences. The Levenshtein distance between two words is the minimum number of single-character edits (insertions, deletions or substitutions) required to change one word into the other.