search
HomeBackend DevelopmentPython TutorialFastAPI: The best choice for fast API development with Python

FastAPI: 使用Python进行快速API开发的最佳选择

FastAPI: The best choice for rapid API development using Python

Introduction:
In modern software development, building stable and efficient APIs is very important. important part. Choosing a framework that can quickly build APIs is crucial to the development efficiency and performance optimization of the project. In the Python world, FastAPI is a highly respected framework that provides concise syntax and powerful functions, allowing developers to quickly build high-performance APIs.

FastAPI Introduction:
FastAPI is an asynchronous programming framework based on Python 3.7. It uses the standard Python type hinting function (jsontype hinting) to implement static type checking, and makes full use of asyncio introduced in Python 3.7. await and async/await syntax. Thanks to the async/await syntax, FastAPI's performance is excellent and comparable to Node.js. FastAPI also has a strong documentation that allows developers to easily build, test and deploy APIs.

Use an example to demonstrate the superiority of FastAPI:
Suppose we are building a movie information API, and we hope to obtain detailed information about the movie based on the movie ID. First, we need to install FastAPI:

pip install fastapi

Then, we can create a file named main.py and import the required modules and libraries:

from fastapi import FastAPI

# 创建 FastAPI 实例
app = FastAPI()

# 创建 API 路由
@app.get("/movie/{movie_id}")
async def get_movie(movie_id: int):
    # 查询电影信息的代码
    movie_info = await get_movie_info(movie_id)
    return movie_info

# 运行 FastAPI
if __name__ == "__main__":
    import uvicorn
    uvicorn.run(app, host="127.0.0.1", port=8000)

In the above code, we first import the FastAPI module and create a FastAPI instance. We then define an API route for GET requests using the @app.get decorator, which can accept a movie_id parameter. In the routing processing function, we use the await keyword to asynchronously obtain movie information and return it to the client.

Next, we use the uvicorn library to run the FastAPI server. Just run python main.py to start the server and listen for requests under the 127.0.0.1:8000 address.

Features of FastAPI:

  1. High performance: FastAPI is built on asyncio, taking advantage of the asynchronous programming capabilities provided by Python 3.7. Its processing speed is very fast and comparable to other high-performance frameworks.
  2. Static type checking: FastAPI uses Python type hinting (jsontype hinting) to implement static type checking, which can detect type errors during the coding phase and avoid errors at runtime.
  3. Automatically generate documentation: FastAPI provides a powerful document that can automatically generate interface documentation. Simply visit the /docs or /redoc routes to view the details of the API.
  4. Support asynchronous: FastAPI makes full use of Python's asynchronous programming capabilities and uses the await keyword to handle asynchronous tasks and improve efficiency.
  5. Safe and reliable: FastAPI supports token-based authentication, data verification, CORS (cross-domain resource sharing) and other security functions, providing strong protection for API developers.
  6. Rich ecosystem: FastAPI benefits from the huge ecosystem of the Python community and can be integrated with many libraries and tools, such as SQLAlchemy, MongoDB, Jinja2, etc.

Conclusion:
FastAPI As a rapid API development framework, it provides simple and easy-to-use syntax, excellent performance and complete documentation, allowing developers to quickly build efficient and stable API. At the same time, it also makes full use of Python's asynchronous programming capabilities, making it possible to handle concurrent requests. Therefore, if you need a high-performance API development framework, FastAPI is definitely a good choice.

Reference link:

  • FastAPI official documentation: https://fastapi.tiangolo.com/
  • FastAPI GitHub repository: https://github.com/ tiangolo/fastapi

The above is the detailed content of FastAPI: The best choice for fast API development with Python. For more information, please follow other related articles on the PHP Chinese website!

Statement
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn
What are some common operations that can be performed on Python arrays?What are some common operations that can be performed on Python arrays?Apr 26, 2025 am 12:22 AM

Pythonarrayssupportvariousoperations:1)Slicingextractssubsets,2)Appending/Extendingaddselements,3)Insertingplaceselementsatspecificpositions,4)Removingdeleteselements,5)Sorting/Reversingchangesorder,and6)Listcomprehensionscreatenewlistsbasedonexistin

In what types of applications are NumPy arrays commonly used?In what types of applications are NumPy arrays commonly used?Apr 26, 2025 am 12:13 AM

NumPyarraysareessentialforapplicationsrequiringefficientnumericalcomputationsanddatamanipulation.Theyarecrucialindatascience,machinelearning,physics,engineering,andfinanceduetotheirabilitytohandlelarge-scaledataefficiently.Forexample,infinancialanaly

When would you choose to use an array over a list in Python?When would you choose to use an array over a list in Python?Apr 26, 2025 am 12:12 AM

Useanarray.arrayoveralistinPythonwhendealingwithhomogeneousdata,performance-criticalcode,orinterfacingwithCcode.1)HomogeneousData:Arrayssavememorywithtypedelements.2)Performance-CriticalCode:Arraysofferbetterperformancefornumericaloperations.3)Interf

Are all list operations supported by arrays, and vice versa? Why or why not?Are all list operations supported by arrays, and vice versa? Why or why not?Apr 26, 2025 am 12:05 AM

No,notalllistoperationsaresupportedbyarrays,andviceversa.1)Arraysdonotsupportdynamicoperationslikeappendorinsertwithoutresizing,whichimpactsperformance.2)Listsdonotguaranteeconstanttimecomplexityfordirectaccesslikearraysdo.

How do you access elements in a Python list?How do you access elements in a Python list?Apr 26, 2025 am 12:03 AM

ToaccesselementsinaPythonlist,useindexing,negativeindexing,slicing,oriteration.1)Indexingstartsat0.2)Negativeindexingaccessesfromtheend.3)Slicingextractsportions.4)Iterationusesforloopsorenumerate.AlwayschecklistlengthtoavoidIndexError.

How are arrays used in scientific computing with Python?How are arrays used in scientific computing with Python?Apr 25, 2025 am 12:28 AM

ArraysinPython,especiallyviaNumPy,arecrucialinscientificcomputingfortheirefficiencyandversatility.1)Theyareusedfornumericaloperations,dataanalysis,andmachinelearning.2)NumPy'simplementationinCensuresfasteroperationsthanPythonlists.3)Arraysenablequick

How do you handle different Python versions on the same system?How do you handle different Python versions on the same system?Apr 25, 2025 am 12:24 AM

You can manage different Python versions by using pyenv, venv and Anaconda. 1) Use pyenv to manage multiple Python versions: install pyenv, set global and local versions. 2) Use venv to create a virtual environment to isolate project dependencies. 3) Use Anaconda to manage Python versions in your data science project. 4) Keep the system Python for system-level tasks. Through these tools and strategies, you can effectively manage different versions of Python to ensure the smooth running of the project.

What are some advantages of using NumPy arrays over standard Python arrays?What are some advantages of using NumPy arrays over standard Python arrays?Apr 25, 2025 am 12:21 AM

NumPyarrayshaveseveraladvantagesoverstandardPythonarrays:1)TheyaremuchfasterduetoC-basedimplementation,2)Theyaremorememory-efficient,especiallywithlargedatasets,and3)Theyofferoptimized,vectorizedfunctionsformathematicalandstatisticaloperations,making

See all articles

Hot AI Tools

Undresser.AI Undress

Undresser.AI Undress

AI-powered app for creating realistic nude photos

AI Clothes Remover

AI Clothes Remover

Online AI tool for removing clothes from photos.

Undress AI Tool

Undress AI Tool

Undress images for free

Clothoff.io

Clothoff.io

AI clothes remover

Video Face Swap

Video Face Swap

Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Tools

DVWA

DVWA

Damn Vulnerable Web App (DVWA) is a PHP/MySQL web application that is very vulnerable. Its main goals are to be an aid for security professionals to test their skills and tools in a legal environment, to help web developers better understand the process of securing web applications, and to help teachers/students teach/learn in a classroom environment Web application security. The goal of DVWA is to practice some of the most common web vulnerabilities through a simple and straightforward interface, with varying degrees of difficulty. Please note that this software

WebStorm Mac version

WebStorm Mac version

Useful JavaScript development tools

Atom editor mac version download

Atom editor mac version download

The most popular open source editor

EditPlus Chinese cracked version

EditPlus Chinese cracked version

Small size, syntax highlighting, does not support code prompt function

MinGW - Minimalist GNU for Windows

MinGW - Minimalist GNU for Windows

This project is in the process of being migrated to osdn.net/projects/mingw, you can continue to follow us there. MinGW: A native Windows port of the GNU Compiler Collection (GCC), freely distributable import libraries and header files for building native Windows applications; includes extensions to the MSVC runtime to support C99 functionality. All MinGW software can run on 64-bit Windows platforms.