When creating a Python app, you have two options: FastAPI vs Flask. Discover here which one you should choose for your project.
首先是 FastAPI 采用了和 Flask 类似的装饰器路由,很容易让人联想到 Flask。 二是FastAPI 没有给它的项目构成做足够的说明。如果 FastAPI 在其介绍的第一句就加上「based on Starlette and Pydantic」而不是放到 Requirements 部分才提及,这样也许会让Starlette和Pydantic获得更多应有的关注,也就不会有这么多人拿 Fl...
上图的性能对比基准是基于每秒响应数,每个请求20个查询,明显看出 FastApi 接口响应速度比 Flask 快很多。 1).Flask 部署方式 由于Flask 本身是不支持异步编码,所以它一般的部署方式和同步的框架Django是一样的,都是用 uwsgi 部署。 2).FastApi部署方式 FastAPI 是个异步框架,所以它是支持 async/await 异步编程语法...
then, if the data exceeds 1MB in size, writing the file to temporary directory, then reading the file from temporary directory (using file.read()) and finally, writing the file to a permanent directory—is what makes uploading file slow compared to using Flask framework, as OP...
选择它的起因是 flask 用腻了,尝试一下新东西。另外,我最看重的是它的异步支持:FastAPI 支持异步编程,可以利用 Python 3.7+ 的async和await关键字来编写异步代码,从而提高性能。当然,承载其网络服务的是 python 的另一个 ASGI(Asynchronous Server Gateway Interface) 模块,称为unicorn,我需要再弄懂一些才能写写它...
Performance:Since the FastAPI has its main focus on high performance we can say it is the fastest framework among all of them, Flask is also a high-performance API because of its micro-framework feature and gives higher performance than Django. ...
PerformanceKnown for high performance due to its asynchronous natureIt is efficient but can be slightly slower than FastAPI and Flask due to its monolithic nature.Offers commendable performance, especially for lightweight applications Learning CurveModerate, especially for those familiar with Python-type ...
gunicorn api.performance_test:app -b localhost:8001-k uvicorn.workers.UvicornWorker --workers1 The resonse body of a get tohttp://localhost:8001/delay/0.0/0.0is consistently something like: {"delays": [0.0,0.0],"total_time_taken":"0:00:00.057946","times": ["0:00:00.0003...
Fast: Very high performance, on par withNodeJSandGo(thanks to Starlette and Pydantic).One of the fastest Python frameworks available. Fast to code: Increase the speed to develop features by about 200% to 300%. * Fewer bugs: Reduce about 40% of human (developer) induced errors. * ...
while UtilMeta Python Framework uses a more concise declarative ORM Schema for Django and other future-supporting ORMs like sqlachemy and Peewee to build RESTful APIs more efficiently, and supports not only Django but all Python mainstream frameworks like Django, Flask, Starlette, FastAPI, Sanic,...