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  2. Lazy evaluation - Wikipedia

    en.wikipedia.org/wiki/Lazy_evaluation

    Lazy evaluation can also lead to reduction in memory footprint, since values are created when needed. [19] In practice, lazy evaluation may cause significant performance issues compared to eager evaluation. For example, on modern computer architectures, delaying a computation and performing it later is slower than performing it immediately.

  3. Dask (software) - Wikipedia

    en.wikipedia.org/wiki/Dask_(software)

    Python functions decorated with Dask delayed adopt a lazy evaluation strategy by deferring execution and generating a task graph with the function and its arguments. The Python function will only execute when .compute is invoked. Dask delayed can be used as a function dask.delayed or as a decorator @dask.delayed.

  4. Comparison of programming languages (list comprehension)

    en.wikipedia.org/wiki/Comparison_of_programming...

    Python uses the following syntax to express list comprehensions over finite lists: S = [ 2 * x for x in range ( 100 ) if x ** 2 > 3 ] A generator expression may be used in Python versions >= 2.4 which gives lazy evaluation over its input, and can be used with generators to iterate over 'infinite' input such as the count generator function which ...

  5. Strict programming language - Wikipedia

    en.wikipedia.org/wiki/Strict_programming_language

    Strict programming languages are often associated with eager evaluation, and non-strict languages with lazy evaluation, but other evaluation strategies are possible in each case. [ citation needed ] The terms "eager programming language" and "lazy programming language" are often used as synonyms for "strict programming language" and "non-strict ...

  6. Comparison of functional programming languages - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_functional...

    Lazy evaluation Typing Abstract data types Algebraic data types Data is immutable Type classes Garbage collection First appeared Common Lisp: No [1] Simulated with thunks [2] Dynamic [3] Yes [4] Extension [5] No [6]? Yes: 1984 Scheme: No [7] Yes [8] Dynamic [7] Yes [9] Simulated with thunks [10] No [11] No: Yes: 1975 Racket: No: Default in Lazy ...

  7. Lazy initialization - Wikipedia

    en.wikipedia.org/wiki/Lazy_initialization

    In computer programming, lazy initialization is the tactic of delaying the creation of an object, the calculation of a value, or some other expensive process until the first time it is needed. It is a kind of lazy evaluation that refers specifically to the instantiation of objects or other resources.

  8. 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:

  9. Futures and promises - Wikipedia

    en.wikipedia.org/wiki/Futures_and_promises

    A lazy future is a future that deterministically has lazy evaluation semantics: the computation of the future's value starts when the value is first needed, as in call by need. Lazy futures are of use in languages which evaluation strategy is by default not lazy.