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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 ...
JSON Schema specifies a JSON-based format to define the structure of JSON data for validation, documentation, and interaction control. It provides a contract for the JSON data required by a given application and how that data can be modified. [ 29 ]
The binary file can store some information that cannot be captured in the XML or JSON file formats. The array, set and dictionary binary types are made up of pointers - the objref and keyref entries - that index into an object table in the file. This means that binary plists can capture the fact that - for example - a separate array and ...
Google Dictionary is an online dictionary service of Google that can be accessed with the "define" operator and other similar phrases [note 1] in Google Search. [2] It is also available in Google Translate and as a Google Chrome extension. The dictionary content is licensed from Oxford University Press's Oxford Languages. [3]
dictc (DICT Client) [11] client for Windows written in Delphi. dict.org's own client (part of the dictd [7] package) dictem, [12] for the Emacs text editor; Dictionary, an application included with Mac OS X. Online dictionaries can be accessed by setting it as the helper for 'dict://' URI schemes. Fantasdic; GNOME Dictionary, comes with GNOME
An empty dictionary is encoded as de. A dictionary with keys "wiki" → "bencode" and "meaning" → 42 is encoded as d4:wiki7:bencode7:meaningi42ee. There are no restrictions on the types of values stored within lists and dictionaries; they may contain other lists and dictionaries, allowing for arbitrarily complex data structures.
In some domains, a few dozen different source and target schema (proprietary data formats) may exist. An "exchange" or "interchange format" is often developed for a single domain, and then necessary routines (mappings) are written to (indirectly) transform/translate each and every source schema to each and every target schema by using the interchange format as an intermediate step.
This makes accessing data in these formats much faster than data in formats requiring more extensive processing, such as JSON, CSV, and in many cases Protocol Buffers. Compared to other serialization formats however, the handling of FlatBuffers requires usually more code, and some operations are not possible (like some mutation operations).