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Types can be read and compared—types are instances of type. The attributes of an object can be extracted as a dictionary. Operators can be overloaded in Python by defining special member functions—for instance, defining a method named __add__ on a class permits one to use the + operator on objects of that class.
JSON is promoted as a low-overhead alternative to XML as both of these formats have widespread support for creation, reading, and decoding in the real-world situations where they are commonly used. [39] Apart from XML, examples could include CSV and supersets of JSON.
OpenML: [493] Web platform with Python, R, Java, and other APIs for downloading hundreds of machine learning datasets, evaluating algorithms on datasets, and benchmarking algorithm performance against dozens of other algorithms.
Control options for the current connection and list of hop-by-hop response fields. [13] Must not be used with HTTP/2. [14] Connection: close: Permanent RFC 9110: Content-Disposition [51] An opportunity to raise a "File Download" dialogue box for a known MIME type with binary format or suggest a filename for dynamic content.
Support for JSON and plain-text transformation was added in later updates to the XSLT 1.0 specification. As of August 2022, the most recent stable version of the language is XSLT 3.0, which achieved Recommendation status in June 2017. XSLT 3.0 implementations support Java, .NET, C/C++, Python, PHP and NodeJS.
FlatBuffers can be used in software written in C++, C#, C, Go, Java, JavaScript, Kotlin, Lobster, Lua, PHP, Python, Rust, Swift, and TypeScript. The schema compiler runs on Android , Microsoft Windows , macOS , and Linux , [ 3 ] but games and other programs use FlatBuffers for serialization work on many other operating systems as well ...
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.
MicroPython consists of a Python compiler to bytecode and a runtime interpreter of that bytecode. The user is presented with an interactive prompt (the REPL) to execute supported commands immediately. Included are a selection of core Python libraries; MicroPython includes modules which give the programmer access to low-level hardware. [4]