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The major changes in this release include 1) the serialization order of N-D array elements changes from column-major to row-major, 2) _ArrayData_ construct for complex N-D array changes from a 1-D vector to a two-row matrix, 3) support non-string valued keys in the hash data JSON representation, and 4) add a new _ByteStream_ object to serialize ...
(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/ref, XPointer, XPath: WSDL, XML schema: DOM, SAX, XQuery ...
Smile is a computer data interchange format based on JSON.It can also be considered a binary serialization of the generic JSON data model, which means tools that operate on JSON may be used with Smile as well, as long as a proper encoder/decoder exists for the tool.
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 ]
FlatBuffers can be used in software written in C++, C#, C, Go, Java, JavaScript, Kotlin, Lobster, Lua, PHP, Python, Rust, Swift, and TypeScript. The schema compiler runs on Android , Microsoft Windows , macOS , and Linux , [ 3 ] but games and other programs use FlatBuffers for serialization work on many other operating systems as well ...
MessagePack is more compact than JSON, but imposes limitations on array and integer sizes.On the other hand, it allows binary data and non-UTF-8 encoded strings. In JSON, map keys have to be strings, but in MessagePack there is no such limitation and any type can be a map key, including types like maps and arrays, and, like YAML, numbers.
share their code, data and models as reusable Python components and automation actions [3] with unified JSON API, JSON meta information, and a UID based on FAIR principles [2] assemble portable workflows from shared components (such as multi-objective autotuning and Design space exploration [4])
Titus (Python 2.x) - Titus is a complete, independent implementation of PFA in pure Python. It focuses on model development, so it includes model producers and PFA manipulation tools in addition to runtime execution. Currently, it works for Python 2. [4] Titus 2 (Python 3.x) - Titus 2 is a fork of Titus which supports PFA implementation for ...