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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 situations where they are commonly used. [39] Apart from XML, examples could include CSV and supersets of JSON.
Concatenated JSON works with pretty-printed JSON but requires more effort and complexity to parse. It doesn't work well with traditional line-oriented tools. Concatenated JSON streaming is a superset of line-delimited JSON streaming. Length-prefixed JSON works with pretty-printed JSON.
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 ...
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).
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 ...
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 - you can use it to slice and filter and map and transform structured data.
By default, a Pandas index is a series of integers ascending from 0, similar to the indices of Python arrays. However, indices can use any NumPy data type, including floating point, timestamps, or strings. [4]: 112 Pandas' syntax for mapping index values to relevant data is the same syntax Python uses to map dictionary keys to values.
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.