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FastAPI is a high-performance web framework for building HTTP-based service APIs in Python 3.8+. [3] It uses Pydantic and type hints to validate, serialize and deserialize data. FastAPI also automatically generates OpenAPI documentation for APIs built with it. [4] It was first released in 2018.
HTTP Codes When using GET, POST, PUT, and DELETE, we will usually receive one of the following codes: 2xx – Success Codes 200 OK – success (most common with GET) 201 Created – request ...
For example, Python bindings are used when an extant C library, written for some purpose, is to be used from Python. Another example is libsvn which is written in C to provide an API to access the Subversion software repository. To access Subversion from within Java code, libsvnjavahl can be used, which depends on libsvn being installed and ...
In 2003, Python web frameworks were typically written against only CGI, FastCGI, mod_python, or some other custom API of a specific web server. [6] To quote PEP 333: Python currently boasts a wide variety of web application frameworks, such as Zope, Quixote, Webware, SkunkWeb, PSO, and Twisted Web -- to name just a few.
For example, the Java Database Connectivity API allows developers to query many different types of databases with the same set of functions, while the Java remote method invocation API uses the Java Remote Method Protocol to allow invocation of functions that operate remotely, but appear local to the developer.
The prefix Py-is used to show that something is related to Python. Examples of the use of this prefix in names of Python applications or libraries include Pygame, a binding of Simple DirectMedia Layer to Python (commonly used to create games); PyQt and PyGTK, which bind Qt and GTK to Python respectively; and PyPy, a Python implementation ...
The official core Java API, contained in the Android (Google), SE (OpenJDK and Oracle), MicroEJ. These packages (java.* packages) are the core Java language packages, meaning that programmers using the Java language had to use them in order to make any worthwhile use of the Java language. Optional APIs that can be downloaded separately.
CuPy is an open source library for GPU-accelerated computing with Python programming language, providing support for multi-dimensional arrays, sparse matrices, and a variety of numerical algorithms implemented on top of them. [3] CuPy shares the same API set as NumPy and SciPy, allowing it to be a drop-in replacement to run NumPy/SciPy code on GPU.