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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.
Arbitrary-length heterogenous arrays with end-marker Arbitrary-length key/value pairs with end-marker Structured Data eXchange Formats (SDXF) Big-endian signed 24-bit or 32-bit integer Big-endian IEEE double Either UTF-8 or ISO 8859-1 encoded List of elements with identical ID and size, preceded by array header with int16 length
Property list files use the filename extension.plist, and thus are often referred to as p-list files. Property list files are often used to store a user's settings. They are also used to store information about bundles and applications , a task served by the resource fork in the old Mac OS.
Certain JSON implementations only accept JSON texts representing an object or an array. For interoperability, applications interchanging JSON should transmit messages that are objects or arrays. The specifications allow JSON objects that contain multiple members with the same name.
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 ...
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).
The Portable Format for Analytics (PFA) is a JSON-based predictive model interchange format conceived and developed by Jim Pivarski. [citation needed] PFA provides a way for analytic applications to describe and exchange predictive models produced by analytics and machine learning algorithms.
Support for JSON and plain-text transformation was added in later updates to the XSLT 1.0 specification. As of August 2022, the most recent stable version of the language is XSLT 3.0, which achieved Recommendation status in June 2017. XSLT 3.0 implementations support Java, .NET, C/C++, Python, PHP and NodeJS.