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Static site generators (SSGs) are software engines that use text input files (such as Markdown, reStructuredText, AsciiDoc and JSON) to generate static web pages. [1] Static sites generated by static site generators do not require a backend after site generation, making them first-class citizens on content delivery networks (CDNs).
Once a Markov chain is learned on a text corpus, it can then be used as a probabilistic text generator. [28] [29] The terms generative AI planning or generative planning were used in the 1980s and 1990s to refer to AI planning systems, especially computer-aided process planning, used to generate sequences of actions to reach a specified goal.
import random # bogosort # what happens is there is a random array that is generated by the last function # the first function checks whether the array is sorted or not # the second function repeatedly shuffles the array for as long as it remains unsorted # and that's it # happy coding => # this function checks whether or not the array is sorted def is_sorted (random_array): for i in range (1 ...
Sphinx converts reStructuredText files into HTML websites and other formats including PDF, EPub, Texinfo and man.. reStructuredText is extensible, and Sphinx exploits its extensible nature through a number of extensions – for autogenerating documentation from source code, writing mathematical notation or highlighting source code, etc.
A randomness extractor, often simply called an "extractor", is a function, which being applied to output from a weak entropy source, together with a short, uniformly random seed, generates a highly random output that appears independent from the source and uniformly distributed. [1]
Convolutional code with any code rate can be designed based on polynomial selection; [15] however, in practice, a puncturing procedure is often used to achieve the required code rate. Puncturing is a technique used to make a m/n rate code from a "basic" low-rate (e.g., 1/n) code. It is achieved by deleting of some bits in the encoder output.
The Mersenne Twister is a general-purpose pseudorandom number generator (PRNG) developed in 1997 by Makoto Matsumoto (松本 眞) and Takuji Nishimura (西村 拓士). [1] [2] Its name derives from the choice of a Mersenne prime as its period length.
A random password generator is a software program or hardware device that takes input from a random or pseudo-random number generator and automatically generates a password. Random passwords can be generated manually, using simple sources of randomness such as dice or coins , or they can be generated using a computer.