Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Full Stack FastAPI, React, and MongoDB

You're reading from   Full Stack FastAPI, React, and MongoDB Build Python web applications with the FARM stack

Arrow left icon
Product type Paperback
Published in Sep 2022
Publisher Packt
ISBN-13 9781803231822
Length 336 pages
Edition 1st Edition
Languages
Tools
Arrow right icon
Author (1):
Arrow left icon
Marko Aleksendrić Marko Aleksendrić
Author Profile Icon Marko Aleksendrić
Marko Aleksendrić
Arrow right icon
View More author details
Toc

Table of Contents (17) Chapters Close

Preface 1. Part 1 – Introduction to the FARM Stack and the Components FREE CHAPTER
2. Chapter 1: Web Development and the FARM Stack 3. Chapter 2: Setting Up the Document Store with MongoDB 4. Chapter 3: Getting Started with FastAPI 5. Chapter 4: Setting Up a React Workflow 6. Part 2 – Parts of the Stack Working Together
7. Chapter 5: Building the Backend for Our Application 8. Chapter 6: Building the Frontend of the Application 9. Chapter 7: Authentication and Authorization 10. Part 3 – Deployment and Final Thoughts
11. Chapter 8: Server-Side Rendering and Image Processing with FastAPI and Next.js 12. Chapter 9: Building a Data Visualization App with the FARM Stack 13. Chapter 10: Caching with Redis and Deployment on Ubuntu (DigitalOcean) and Netlify 14. Chapter 11: Useful Resources and Project Ideas 15. Index 16. Other Books You May Enjoy

Aggregation framework

In the following pages, we will try to provide a brief introduction to the MongoDB aggregation framework, what it is, what benefits it offers, and why it is regarded as one of the strongest selling points of the MongoDB ecosystem.

Centered around the concept of a pipeline (something that you might be familiar with if you have done some analytics or if you have ever connected a few commands in Linux), the aggregation framework is, at its simplest, an alternative way to retrieve sets of documents from a collection; it is similar to the find method that we already used extensively but with the additional benefit of the possibility of data processing in different stages or steps.

With the aggregation pipeline, we basically pull documents from a MongoDB collection and feed them sequentially to various stages of the pipeline where each stage output is fed to the next stage’s input until the final set of documents is returned. Each stage performs some data...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at €18.99/month. Cancel anytime