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FlatBuffers can be used in software written in C++, C#, C, Go, Java, JavaScript, Kotlin, Lobster, Lua, PHP, Python, Rust, Swift, and TypeScript. The schema compiler runs on Android , Microsoft Windows , macOS , and Linux , [ 3 ] but games and other programs use FlatBuffers for serialization work on many other operating systems as well ...
The Function constructor can be used to trigger execution of JavaScript code contained in a string as if it were native JavaScript. So, for example, the statement alert() is equivalent to Function("alert()")().
^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.
Flow diagram. In computing, serialization (or serialisation, also referred to as pickling in Python) is the process of translating a data structure or object state into a format that can be stored (e.g. files in secondary storage devices, data buffers in primary storage devices) or transmitted (e.g. data streams over computer networks) and reconstructed later (possibly in a different computer ...
For example, if the value of the eighth bit is not preserved, the program might interpret a byte value above 127 as a flag telling it to perform some function. It is often desirable, however, to be able to send non-textual data through text-based systems, such as when one might attach an image file to an e-mail message.
YAML (/ ˈ j æ m əl /, rhymes with camel [4]) was first proposed by Clark Evans in 2001, [15] who designed it together with Ingy döt Net [16] and Oren Ben-Kiki. [16]Originally YAML was said to mean Yet Another Markup Language, [17] because it was released in an era that saw a proliferation of markup languages for presentation and connectivity (HTML, XML, SGML, etc.).
Base64 can be used to transmit and store text that might otherwise cause delimiter collision; Base64 is used to encode character strings in LDAP Data Interchange Format files; Base64 is often used to embed binary data in an XML file, using a syntax similar to <data encoding="base64">…</data> e.g. favicons in Firefox's exported bookmarks.html.
It can convert a wide range of complex data structures, including dict, array, numpy ndarray, into JData representations and export the data as JSON or UBJSON files. The BJData Python module, pybj, [4] enabling reading/writing BJData/UBJSON files, is also available on PyPI, Debian/Ubuntu and GitHub.