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  2. Python syntax and semantics - Wikipedia

    en.wikipedia.org/wiki/Python_syntax_and_semantics

    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:

  3. Lazy initialization - Wikipedia

    en.wikipedia.org/wiki/Lazy_initialization

    Using a factory method to create instances of a class (factory method pattern) Storing the instances in a map, and returning the same instance to each request for an instance with same parameters (multiton pattern) Using lazy initialization to instantiate the object the first time it is requested (lazy initialization pattern)

  4. Fold (higher-order function) - Wikipedia

    en.wikipedia.org/wiki/Fold_(higher-order_function)

    The extraneous intermediate list structure can be eliminated with the continuation-passing style technique, foldr f z xs == foldl (\ k x-> k. f x) id xs z; similarly, foldl f z xs == foldr (\ x k-> k. flip f x) id xs z ( flip is only needed in languages like Haskell with its flipped order of arguments to the combining function of foldl unlike e ...

  5. Lazy evaluation - Wikipedia

    en.wikipedia.org/wiki/Lazy_evaluation

    In Python 3.x the range() function [28] returns a generator which computes elements of the list on demand. Elements are only generated when they are needed (e.g., when print(r[3]) is evaluated in the following example), so this is an example of lazy or deferred evaluation:

  6. Fixed-point combinator - Wikipedia

    en.wikipedia.org/wiki/Fixed-point_combinator

    (Here we use the standard notations and conventions of lambda calculus: Y is a function that takes one argument f and returns the entire expression following the first period; the expression . ( ) denotes a function that takes one argument x, thought of as a function, and returns the expression ( ), where ( ) denotes x applied to itself ...

  7. Divisor summatory function - Wikipedia

    en.wikipedia.org/wiki/Divisor_summatory_function

    This quantity can be visualized as the count of the number of lattice points fenced off by a hyperbolic surface in k dimensions. Thus, for k = 2, D(x) = D 2 (x) counts the number of points on a square lattice bounded on the left by the vertical-axis, on the bottom by the horizontal-axis, and to the upper-right by the hyperbola jk = x.

  8. Subset sum problem - Wikipedia

    en.wikipedia.org/wiki/Subset_sum_problem

    The subset sum problem (SSP) is a decision problem in computer science.In its most general formulation, there is a multiset of integers and a target-sum , and the question is to decide whether any subset of the integers sum to precisely . [1]

  9. Maximum subarray problem - Wikipedia

    en.wikipedia.org/wiki/Maximum_subarray_problem

    Each possible contiguous sub-array is represented by a point on a colored line. That point's y-coordinate represents the sum of the sample. Its x-coordinate represents the end of the sample, and the leftmost point on that colored line represents the start of the sample. In this case, the array from which samples are taken is [2, 3, -1, -20, 5, 10].