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  2. Python syntax and semantics - Wikipedia

    en.wikipedia.org/wiki/Python_syntax_and_semantics

    For example, one could define a dictionary having a string "toast" mapped to the integer 42 or vice versa. The keys in a dictionary must be of an immutable Python type, such as an integer or a string, because under the hood they are implemented via a hash function. This makes for much faster lookup times, but requires keys not change.

  3. Approximate string matching - Wikipedia

    en.wikipedia.org/wiki/Approximate_string_matching

    The closeness of a match is measured in terms of the number of primitive operations necessary to convert the string into an exact match. This number is called the edit distance between the string and the pattern. The usual primitive operations are: [1] insertion: cot → coat; deletion: coat → cot

  4. String metric - Wikipedia

    en.wikipedia.org/wiki/String_metric

    The most widely known string metric is a rudimentary one called the Levenshtein distance (also known as edit distance). [2] It operates between two input strings, returning a number equivalent to the number of substitutions and deletions needed in order to transform one input string into another.

  5. Python (programming language) - Wikipedia

    en.wikipedia.org/wiki/Python_(programming_language)

    Python uses the + operator for string concatenation. Python uses the * operator for duplicating a string a specified number of times. The @ infix operator is intended to be used by libraries such as NumPy for matrix multiplication. [104] [105] The syntax :=, called the "walrus operator", was introduced in Python 3.8. It assigns values to ...

  6. Levenshtein distance - Wikipedia

    en.wikipedia.org/wiki/Levenshtein_distance

    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.

  7. String-searching algorithm - Wikipedia

    en.wikipedia.org/wiki/String-searching_algorithm

    A string-searching algorithm, sometimes called string-matching algorithm, is an algorithm that searches a body of text for portions that match by pattern. A basic example of string searching is when the pattern and the searched text are arrays of elements of an alphabet ( finite set ) Σ.

  8. Pattern matching - Wikipedia

    en.wikipedia.org/wiki/Pattern_matching

    Here, the first n is a single variable pattern, which will match absolutely any argument and bind it to name n to be used in the rest of the definition. In Haskell (unlike at least Hope ), patterns are tried in order so the first definition still applies in the very specific case of the input being 0, while for any other argument the function ...

  9. String interpolation - Wikipedia

    en.wikipedia.org/wiki/String_interpolation

    There are two main types of variable-expanding algorithms for variable interpolation: [3] Replace and expand placeholders: creating a new string from the original one, by find–replace operations. Find variable reference (placeholder), replace it by its variable value. This algorithm offers no cache strategy.

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