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  2. Comparison of data-serialization formats - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_data...

    (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 ...

  3. Comparison of code generation tools - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_code...

    Well-formed output language code fragments Any programming language (proven for C, C++, Java, C#, PHP, COBOL) gSOAP: C / C++ WSDL specifications C / C++ code that can be used to communicate with WebServices. XML with the definitions obtained. Microsoft Visual Studio LightSwitch: C# / VB.NET Active Tier Database schema

  4. Serialization - Wikipedia

    en.wikipedia.org/wiki/Serialization

    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 ...

  5. Ion (serialization format) - Wikipedia

    en.wikipedia.org/wiki/Ion_(Serialization_format)

    As a superset of JSON, Ion includes the following data types null: An empty value; bool: Boolean values; string: Unicode text literals; list: Ordered heterogeneous collection of Ion values; struct: Unordered collection of key/value pairs; The nebulous JSON 'number' type is strictly defined in Ion to be one of int: Signed integers of arbitrary size

  6. Machine-readable medium and data - Wikipedia

    en.wikipedia.org/wiki/Machine-readable_medium...

    Machine-readable data may be classified into two groups: human-readable data that is marked up so that it can also be read by machines (e.g. microformats, RDFa, HTML), and data file formats intended principally for processing by machines (CSV, RDF, XML, JSON). These formats are only machine readable if the data contained within them is formally ...

  7. Comma-separated values - Wikipedia

    en.wikipedia.org/wiki/Comma-separated_values

    Comma-separated values (CSV) is a text file format that uses commas to separate values, and newlines to separate records. A CSV file stores tabular data (numbers and text) in plain text, where each line of the file typically represents one data record. Each record consists of the same number of fields, and these are separated by commas in the ...

  8. Protocol Buffers - Wikipedia

    en.wikipedia.org/wiki/Protocol_Buffers

    A schema for a particular use of protocol buffers associates data types with field names, using integers to identify each field. (The protocol buffer data contains only the numbers, not the field names, providing some bandwidth/storage savings compared with systems that include the field names in the data.)

  9. FlatBuffers - Wikipedia

    en.wikipedia.org/wiki/FlatBuffers

    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).