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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 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 ...
JSON Pointer [10] defines a string syntax for identifying a single value within a given JSON value of known structure. 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 ...
Dask Bag is used to parallelize computation of semi-structured or unstructured data, such as JSON records, text data, log files or user-defined Python objects using operations such as filter, fold, map and groupby. Dask Bags can be created from an existing Python iterable or can load data directly from text files and binary files in the Avro ...
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] JSON Schema is based on the concepts from XML Schema (XSD) but is JSON-based. As in XSD, the same ...
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 ...
ArangoDB is a transactional native multi-model database supporting two major NoSQL data models (graph and document [1]) with one query language. Written in C++ and optimized for in-memory computing. In addition ArangoDB integrated RocksDB for persistent storage. ArangoDB supports Java, JavaScript, Python, PHP, NodeJS, C++ and Elixir.
The most distinctive feature is the Client and Server Module. The Server Module enables the Python code for business logic, executed as a server-side session. The Client Module executes the JavaScript code within a browser. It is possible to exchange data between the two. [4] Application Builder is strongly influenced by Delphi visual designer. [5]