Flask vs Django: Which Python Framework is best for Machine Learning app?

flask vs django

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You’ve developed a Machine Learning model. Now you want to deploy it on the web and you are confused between the Flask vs Django. You want to take input from the user and do the process and provide the result using the built model in real-time.

Either this or you may want to build the model taking data from the user. And now you’re looking for the better python framework to use.

We have done the Flask vs Django comparison for you and which framework has come on the top, let us see.

While both are good alternative web frameworks for each other, both can always not be a good choice. You have to select one which would be helpful for your ML application. Now we will compare Django vs Flask using some important and necessary parameters.

Flask vs Django Comparison

flask vs django

Flask vs Django: Simplicity and Flexibility

Python framework Flask is focused on simplicity and minimality. So, it gives the developer the freedom he/she needs to choose modules. Django, on the other hand, gives a lot more batteries or features which you won’t even require. Developers need to build the application around the batteries provided in the Django while it is not the case with the Flask.

Development speed

As I said Django provides batteries, a user can develop their applications around it. It improves the speed of development. Flask on the other hand also is good for the speed as the developer can create an application in a short time because of its simplicity.

flask vs django

Size of the project

For any other web application, Django is more preferable by most people. But for Machine Learning application, Flask is preferred by the developers. The reason behind this approach is the freedom to use any module. It is possible to use Django, but for ML application, Flask is better. You can use try Django for small-sized ML app, but for bigger ML project, I would recommend you Flask.

Availability of Add-ons

Django is more mature than Flask, because of its earlier release in 2005 compared to Flask in 2010. The add-ons, extensions are more in Django. Flask is younger that’s why it has little options. Still, Flask is more useful for ML app and is used by most.


For general web applications, such as full-stack websites, Django has a wider community. Flask has the number of developers which have worked on Machine Learning web applications.

Flask vs Django: Conclusion

The thing is, for most of the general web applications, Django is a wise choice because of the availability of the add-ons and features. As for Machine Learning, Flask should be your first priority.

Simplicity and Flexibility SimplerHard
Development speed SlowFast
Size of the project For bigger ML project For small ML project
Availability of Add-ons LessMore
Community SmallWider

Also Read: Flask SQLAlchemy Tutorial: Login System with Python

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