FastAPI has Ruined Flask Forever for Me

What do you like best about being a data scientist? It’s definitely modeling and fine-tuning for optimal results. But what does it mean to be a good model if it’s never used or never deployed?

To produce a machine learning model, the typical approach is to wrap it in a REST API and use it as a microservice. One of the most widely used frameworks for creating APIs is Flask.

The main reason Flask is widely used is its simplicity. In general, we only use the API to model predictions, so we don’t need a complex architecture (example: Django). Another reason is that Flask is written in Python, which is the language used to do machine learning modeling in general, so we are familiar with it.

However, if you want to create a REST API with clear, static, inputs that are validated, you must include several different packages from several third parties that do not cooperate with each other. And you have to create custom code to get everything running.

This is what caused me to look for alternatives for my needs, where finally I found a framework called FastAPI and it became my new favorite framework. Here are the reasons why I like to use FastAPI.

#machine-learning #python #flask #web-development

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FastAPI has Ruined Flask Forever for Me
Steve  Kunde

Steve Kunde

1592723950

Download a Flask template ready to plug in your business logic

Let’s assume after lots of hard work you have your machine learning model running the way it should. This model could be one which responds to a user’s request to classify a tweet sentiment or identify objects in an image or recommend a product or some other algorithm unique to your needs. You would now like to quickly deploy this model. The article below is an explanation of the template that I have created to get you up and running quickly.

#flask-framework #flask-python-appengine #flask-sqlalchemy #marshmallow #flask #programming

FastAPI has Ruined Flask Forever for Me

What do you like best about being a data scientist? It’s definitely modeling and fine-tuning for optimal results. But what does it mean to be a good model if it’s never used or never deployed?

To produce a machine learning model, the typical approach is to wrap it in a REST API and use it as a microservice. One of the most widely used frameworks for creating APIs is Flask.

The main reason Flask is widely used is its simplicity. In general, we only use the API to model predictions, so we don’t need a complex architecture (example: Django). Another reason is that Flask is written in Python, which is the language used to do machine learning modeling in general, so we are familiar with it.

However, if you want to create a REST API with clear, static, inputs that are validated, you must include several different packages from several third parties that do not cooperate with each other. And you have to create custom code to get everything running.

This is what caused me to look for alternatives for my needs, where finally I found a framework called FastAPI and it became my new favorite framework. Here are the reasons why I like to use FastAPI.

#machine-learning #python #flask #web-development

Web development with python and flask: part 3

In this part of the series, we will be taking a look at the HTTP protocol, request/response objects, their application in flask, properties, and their related methods. We will take steps to import it from the flask module, use its properties, and look at some of its related usages

Web applications implement one of the internet data and message exchange architectures that is based on HTTP protocol. The HTTP protocol is just one of the many application layers of TCP/IP. The TCP/IP(Transmission Control Protocol/Internet Protocol) is used as a standard for transmitting data over networks. In simple terms, HTTP has rules, properties, and methods that implement the transmission of messages in form of hyperlinks over the communication structures enforced by the TCP/IP.

.You must know that the internet is based on connected physical computational devices over either copper wires, fiber optical cables, wireless, and other media to form data transmission and retrieval systems across the globe. Trust me, that is a whole career field in itself and we are not interested in its elaborate ramblings in this post.

#flask #web developemnt #flask #flask requests #webdevelopment

Adrienne  Hane

Adrienne Hane

1597284513

Migrate From Flask to FastAPI Smoothly

By reading this piece, you will learn about the fundamental concepts behind FastAPI and the steps involved in transitioning from Flask to FastAPI. Side by side comparisons will be provided for your references. At the end of this tutorial, you should be able to migrate your Flask server entirely into aFastAPI server. For your information, FastAPI framework is:

“… a modern, fast (high-performance), web framework for building APIs with Python 3.6+ based on standard Python type hints.”

The official documentation outlines the following key features for FastAPI (Estimation is based on tests on an internal development team, building production applications.):

  • Fast: Very high performance, on par with NodeJS and Go.
  • Fast to code: Increase the speed to develop features by about 200% to 300%.
  • Fewer bugs: Reduce about 40% of human (developer) induced errors.
  • Intuitive: Great editor support. Completion everywhere. Less time debugging.
  • Easy: Designed to be easy to use and learn. Less time reading docs.
  • Short: Minimize code duplication. Multiple features from each parameter declaration. Fewer bugs.
  • Robust: Get production-ready code. With automatic interactive documentation.
  • Standards-based: Based on (and fully compatible with) the open standards for APIs: OpenAPI (previously known as Swagger) and JSON Schema.

#flask #devops #fastapi #python

How to Use FastAPI to Recreate the Flask

« FastAPI» articles. Flask has been around longer and is geared towards small web apps. One thing Flask has is a great beginner tutorial for building a simple app where users can register, log in, and create posts. FastAPI has good documentation for building APIs, but it’s lacking a simple tutorial for a basic app like the Flask example.

I’m in the process of learning both frameworks, so I decided it would be a good exercise to recreate the Flask tutorial app using FastAPI.

#fastapi #flask #python