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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. The BJData Python module, pybj, [4] enabling reading/writing BJData/UBJSON files, is also available on PyPI, Debian/Ubuntu and GitHub.
CBOR encoded data is seen as a stream of data items. Each data item consists of a header byte containing a 3-bit type and 5-bit short count. This is followed by an optional extended count (if the short count is in the range 24–27), and an optional payload. For types 0, 1, and 7, there is no payload; the count is the value. For types 2 (byte ...
Trino is an open-source distributed SQL query engine designed to query large data sets distributed over one or more heterogeneous data sources. [1] Trino can query data lakes that contain a variety of file formats such as simple row-oriented CSV and JSON data files to more performant open column-oriented data file formats like ORC or Parquet [2] [3] residing on different storage systems like ...
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 ...
JSON-RPC works by sending a request to a server implementing this protocol. The client in that case is typically software intending to call a single method of a remote system. Multiple input parameters can be passed to the remote method as an array or object, whereas the method itself can return multiple output data as well.
BSON (/ ˈ b iː s ə n / [2]) is a computer data interchange format. The name "BSON" is based on the term JSON and stands for "Binary JSON". [2] It is a binary form for representing simple or complex data structures including associative arrays (also known as name-value pairs), integer indexed arrays, and a suite of fundamental scalar types.
The Portable Format for Analytics (PFA) is a JSON-based predictive model interchange format conceived and developed by Jim Pivarski. [citation needed] PFA provides a way for analytic applications to describe and exchange predictive models produced by analytics and machine learning algorithms.
The glTF format stores data primarily in JSON. The JSON may also contain blobs of binary data known as buffers, and refer to external files, for storing mesh data, images, etc. [7] The binary .glb format also contains JSON text, but serialized with binary chunk headers to allow blobs to be directly appended to the file.