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In computing, a device or software program is said to be agnostic or data agnostic if the method or format of data transmission is irrelevant to the device or program's function. This means that the device or program can receive data in multiple formats or from multiple sources, and still process that data effectively.
For software to be considered cross-platform, it must function on more than one computer architecture or OS. Developing such software can be a time-consuming task because different OSs have different application programming interfaces (API). Software written for one OS may not automatically work on all architectures that OS supports.
Language-agnostic programming or scripting (also called language-neutral, language-independent, or cross-language) is a software paradigm in which no particular language is promoted. In introductory instruction, the term refers to teaching principles rather than language features. [ 1 ]
Conda is an open-source, [2] cross-platform, [3] language-agnostic package manager and environment management system. It was originally developed to solve package management challenges faced by Python data scientists, and today is a popular package manager for Python and R.
Mongrel2 is described as language agnostic, meaning it does not prefer any specific programming language over another.The server's documentation says: The term 'language agnostic' came from people who read about Mongrel2 in the early days, and it means that Mongrel2 does not try to promote any one language over any others.
Apache Arrow is a language-agnostic software framework for developing data analytics applications that process columnar data.It contains a standardized column-oriented memory format that is able to represent flat and hierarchical data for efficient analytic operations on modern CPU and GPU hardware.
Schema-agnosticism is the property of a database of mapping a query issued with the user terminology and structure, automatically mapping it to the dataset vocabulary. The increase in the size and in the semantic heterogeneity of database schemas bring new requirements for users querying and searching structured data .
LIS's are language-agnostic; they mitigate the risk that a certain language binding might reduce compatibility with other languages. An ideal LIS allows the language bindings to take advantage of features of a programming language uncompromisingly.