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This template generates a test case for two or more templates. Each template is called with the same parameters, and the test case can be displayed in various different formats. All parameters passed to this template are passed through to the test-case templates, with the exception of parameters starting with an underscore character ...
If this case is an appeal, name the court from which the appeal immediately came. Link the name if possible. If the case at the lower court has its own article, that case can be linked in parentheses after the name of the court. More complicated or longer histories can use the prior actions field alongside this field or instead of it. String ...
Template:Test case nowiki, for templates with complex invocations; Template:Collapsible test case, to collapse test cases when the main and sandbox templates produce the same result; Note that all of these templates can produce collapsible test cases, but Template:Collapsible test case has this feature turned on by default. For detailed ...
Object storage (also known as object-based storage [1] or blob storage) is a computer data storage approach that manages data as "blobs" or "objects", as opposed to other storage architectures like file systems, which manage data as a file hierarchy, and block storage, which manages data as blocks within sectors and tracks. [2]
The blob URI scheme, also known as an object URL, is a Uniform Resource Identifier (URI) ...
The Mustache template does nothing but reference methods in the (input data) view. [3] All the logic, decisions, and code is contained in this view, and all the markup (ex. output XML) is contained in the template. In a model–view–presenter (MVP) context: input data is from MVP-presenter, and the Mustache template is the MVP-view.
^The current default format is binary. ^ The "classic" format is plain text, and an XML format is also supported. ^ Theoretically possible due to abstraction, but no implementation is included.
Informally, a blob is a region of an image in which some properties are constant or approximately constant; all the points in a blob can be considered in some sense to be similar to each other. The most common method for blob detection is by using convolution.