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Jinja is a web template engine for the Python programming language. It was created by Armin Ronacher and is licensed under a BSD License. Jinja is similar to the Django template engine, but provides Python-like expressions while ensuring that the templates are evaluated in a sandbox. It is a text-based template language and thus can be used to ...
This is the template test cases page for the sandbox of Template:Deletion process cheat sheet/Last Afd to update the examples. If there are many examples of a complicated template, later ones may break due to limits in MediaWiki; see the HTML comment "NewPP limit report" in the rendered page. You can also use Special:ExpandTemplates to examine the results of template uses. You can test how ...
For a full list of editing commands, see Help:Wikitext; For including parser functions, variables and behavior switches, see Help:Magic words; For a guide to displaying mathematical equations and formulas, see Help:Displaying a formula; For a guide to editing, see Wikipedia:Contributing to Wikipedia
Folds can be regarded as consistently replacing the structural components of a data structure with functions and values. Lists, for example, are built up in many functional languages from two primitives: any list is either an empty list, commonly called nil ([]), or is constructed by prefixing an element in front of another list, creating what is called a cons node ( Cons(X1,Cons(X2,Cons ...
Serial-position effect is the tendency of a person to recall the first and last items in a series best, and the middle items worst. [1] The term was coined by Hermann Ebbinghaus through studies he performed on himself, and refers to the finding that recall accuracy varies as a function of an item's position within a study list. [2]
The Konami Code. The Konami Code (Japanese: コナミコマンド, Konami Komando, "Konami command"), also commonly referred to as the Contra Code and sometimes the 30 Lives Code, is a cheat code that appears in many Konami video games, [1] as well as some non-Konami games.
The activation function of a node in an artificial neural network is a function that calculates the output of the node based on its individual inputs and their weights. Nontrivial problems can be solved using only a few nodes if the activation function is nonlinear .
The amount of heat entering the column from the reboiler and with the feed must equal the amount heat removed by the overhead condenser and with the products. The heat entering a distillation column is a crucial operating parameter, addition of excess or insufficient heat to the column can lead to foaming, weeping, entrainment, or flooding.