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JSON: No Smile Format Specification: Yes No Yes Partial (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 ...
JSON (JavaScript Object Notation, pronounced / ˈ dʒ eɪ s ən / or / ˈ dʒ eɪ ˌ s ɒ n /) is an open standard file format and data interchange format that uses human-readable text to store and transmit data objects consisting of name–value pairs and arrays (or other serializable values).
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
Since XML files, however, are not the most space-efficient means of storage, Mac OS X 10.2 introduced a new format where property list files are stored as binary files. Starting with Mac OS X 10.4, this is the default format for preference files. In Mac OS X 10.7, support for reading and writing files in JSON format was introduced. JSON and ...
Protocol Buffers (Protobuf) is a free and open-source cross-platform data format used to serialize structured data. It is useful in developing programs that communicate with each other over a network or for storing data.
Concatenated JSON isn't a new format, it's simply a name for streaming multiple JSON objects without any delimiters. The advantage of this format is that it can handle JSON objects that have been formatted with embedded newline characters, e.g., pretty-printed for human readability. For example, these two inputs are both valid and produce the ...
FlatBuffers is a free software library implementing a serialization format similar to Protocol Buffers, Thrift, Apache Avro, SBE, and Cap'n Proto, primarily written by Wouter van Oortmerssen and open-sourced by Google. It supports “zero-copy” deserialization, so that accessing the serialized data does not require first copying it into a ...
Pandas is built around data structures called Series and DataFrames. Data for these collections can be imported from various file formats such as comma-separated values, JSON, Parquet, SQL database tables or queries, and Microsoft Excel. [8] A Series is a 1-dimensional data structure built on top of NumPy's array.