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JSON is promoted as a low-overhead alternative to XML as both of these formats have widespread support for creation, reading, and decoding in the real-world ...
RDFLib is a Python library for working with RDF, [2] a simple yet powerful language for representing information. This library contains parsers/serializers for almost all of the known RDF serializations, such as RDF/XML, Turtle, N-Triples, & JSON-LD, many of which are now supported in their updated form (e.g. Turtle 1.1).
Modules work over JSON and standard output and can be written in any language. Uses YAML to express reusable descriptions of systems. ... It is written in Python and ...
JSONiq [11] is a query and transformation language for JSON. XPath 3.1 [12] is an expression language that allows the processing of values conforming to the XDM [13] data model. The version 3.1 of XPath supports JSON as well as XML. jq is like sed for JSON data – it can be used to slice and filter and map and transform structured data.
JSON: No Smile Format Specification: Yes No Yes Partial (JSON Schema Proposal, other JSON schemas/IDLs) Partial (via JSON APIs implemented with Smile backend, on Jackson, Python) — SOAP: W3C: XML: Yes W3C Recommendations: SOAP/1.1 SOAP/1.2: Partial (Efficient XML Interchange, Binary XML, Fast Infoset, MTOM, XSD base64 data) Yes Built-in id ...
While JSON is the most common format, it is possible to forgo some features (like storing images and metadata), and save notebooks as markdown documents using extensions like Jupytext. [24] Jupytext is often used in conjunction with version control to make diffing and merging of notebooks simpler.
The Language Server Protocol (LSP) is an open, JSON-RPC-based protocol for use between source code editors or integrated development environments (IDEs) and servers that provide "language intelligence tools": [1] programming language-specific features like code completion, syntax highlighting and marking of warnings and errors, as well as refactoring routines.
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 ...