You're reading from Mastering Flask Web and API Development Build and deploy production-ready Flask apps seamlessly across web, APIs, and mobile platforms

Product type Paperback

Published in Aug 2024

Publisher Packt

ISBN-13 9781837633227

Length 494 pages

Edition 1st Edition

Languages

Python

Tools

Flask

Concepts

Big Data

Author (1):

Sherwin John C. Tragura

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Table of Contents (18) Chapters

Preface

1. Part 1:Learning the Flask 3.x Framework

2. Chapter 1: A Deep Dive into the Flask Framework FREE CHAPTER

3. Chapter 2: Adding Advanced Core Features

4. Chapter 3: Creating REST Web Services

5. Chapter 4: Utilizing Flask Extensions

6. Part 2:Building Advanced Flask 3.x Applications

7. Chapter 5: Building Asynchronous Transactions

8. Chapter 6: Developing Computational and Scientific Applications

9. Chapter 7: Using Non-Relational Data Storage

10. Chapter 8: Building Workflows with Flask

11. Chapter 9: Securing Flask Applications

12. Part 3:Testing, Deploying, and Building Enterprise-Grade Applications

13. Chapter 10: Creating Test Cases for Flask

14. Chapter 11: Deploying Flask Applications

15. Chapter 12: Integrating Flask with Other Tools and Frameworks

16. Index

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Summary

There are lots of NoSQL databases that can store non-relational data for big data applications built with Flask 3.x. Flask can PUT, GET, and SCAN data in HBase using HDFS, access the Cassandra database, execute HGET an HSET with Redis, perform CRUD operations in Couchbase and MongoDB, and manage nodes with Neo4J. Although there are changes in some support modules, such as in flask-mongoengine, because of the transformations in the Flask internal modules (for example, the removal of flask.json), Flask can still adapt to other Python module extensions and workarounds to connect to and manage its data, such as using the FastAPI-compatible Redis OM.

In general, this chapter showcased Flask’s compatibility with almost all the efficient, popular, and widely used NoSQL databases. It is also a Python framework that’s fit for building big data applications for many enterprises and scientific development because it supports many NoSQL storages.

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