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  2. Comparison of data-serialization formats - Wikipedia

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

    Comma-separated values (CSV) RFC author: Yakov Shafranovich — Myriad informal variants RFC 4180 (among others) No Yes No No No No Common Data Representation (CDR) Object Management Group — Yes General Inter-ORB Protocol: Yes No Yes Yes Ada, C, C++, Java, Cobol, Lisp, Python, Ruby, Smalltalk — D-Bus Message Protocol freedesktop.org — Yes ...

  3. 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 ...

  4. Smile (data interchange format) - Wikipedia

    en.wikipedia.org/wiki/Smile_(data_interchange...

    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.

  5. 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.

  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. 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).

  8. OpenRefine - Wikipedia

    en.wikipedia.org/wiki/OpenRefine

    Transformation of data: converting values to other formats, normalizing and denormalizing. Parsing data from web sites: OpenRefine has a URL fetch feature and jsoup HTML parser and DOM engine. [9] Adding data to dataset by fetching it from web services (i.e. returning JSON). [10] For example, can be used for geocoding addresses to geographic ...

  9. Tab-separated values - Wikipedia

    en.wikipedia.org/wiki/Tab-separated_values

    Tab-separated values (TSV) is a simple, text-based file format for storing tabular data. [3] Records are separated by newlines , and values within a record are separated by tab characters . The TSV format is thus a delimiter-separated values format, similar to comma-separated values .