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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 ...
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.
An API specification defines these calls, meaning that it explains how to use or implement them. One purpose of APIs is to hide the internal details of how a system works, exposing only those parts a programmer will find useful and keeping them consistent even if the internal details later change.
[33] [43] In addition to building and training their model, TensorFlow can also help load the data to train the model, and deploy it using TensorFlow Serving. [44] TensorFlow provides a stable Python Application Program Interface , [45] as well as APIs without backwards compatibility guarantee for Javascript, [46] C++, [47] and Java.
The term comes from the specification for Common Lisp, which explicitly refers to the programming language feature enabling for inter-language calls as such; [citation needed] the term is also often used officially by the interpreter and compiler documentation for Haskell, [1] Rust, [2] PHP, [3] Python, and LuaJIT [4] [5]: 35 . [6]
An open API (often referred to as a public API) is a publicly available application programming interface that provides developers with programmatic access to a (possibly proprietary) software application or web service. [1] Open APIs are APIs that are published on the internet and are free to access by consumers. [2]
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.