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Lightweight Python JData encoder/decoder, pyjdata, [3] is available on PyPI, Debian/Ubuntu and GitHub. 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.
JSON was based on a subset of the JavaScript scripting language (specifically, Standard ECMA-262 3rd Edition—December 1999 [11]) and is commonly used with JavaScript, but it is a language-independent data format. Code for parsing and generating JSON data is readily available in many programming languages.
blob: Binary data of user-defined encoding; clob: Text data of user-defined encoding; sexp: Ordered collections of values with application-defined semantics; Each Ion type supports a null variant, indicating a lack of value while maintaining a strict type (e.g., null.int, null.struct). The Ion format permits annotations to any value in the form ...
For example, PKIX uses such notation in RFC 5912. With such notation (constraints on parameterized types using information object sets), generic ASN.1 tools/libraries can automatically encode/decode/resolve references within a document. ^ The primary format is binary, a json encoder is available. [10]
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.
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.).
For example, JSON is commonly used as a transport storage mechanism between the client and the webserver. A web scraper uses a website's URL to extract data, and stores this data for subsequent analysis. This method of web scraping enables the extraction of data in an efficient and accurate manner. [7]
JSON streaming comprises communications protocols to delimit JSON objects built upon lower-level stream-oriented protocols (such as TCP), that ensures individual JSON objects are recognized, when the server and clients use the same one (e.g. implicitly coded in). This is necessary as JSON is a non-concatenative protocol (the concatenation of ...