MongoDB and Python: Powerful and Scalable Data Storage

By Orion Loopman

This is a practical, example-driven guide to mastering MongoDB with Python for building scalable, maintainable applications. You'll begin with the essentials-the document model, collections, and drivers-then quickly move into real-world design and performance considerations: schema modeling (embedding vs. referencing), indexing strategies, and building efficient aggregation pipelines.Through clear, runnable examples, you'll learn how to:
Implement CRUD operations, complex aggregations, geospatial and text queries, GridFS for binary data, and multi-document transactions.
Apply async programming with Motor to handle high-concurrency Python applications.
Diagnose and tune slow queries with proven indexing workflows.
Dedicated chapters cover operational best practices: backups, monitoring, security hardening, and scaling with replication and sharding. You'll also walk through deploying a sample web API (built with a popular Python framework) to MongoDB Atlas, demonstrating schema design, query optimization, and production readiness.
Inside the book:
Hands-on examples with PyMongo and Motor
A complete web API project showcasing schema and performance tuning
Checklists for backup, monitoring, and access control in production
Recipes for profiling queries and selecting the right indexes
By the end, you'll have the skills and confidence to design robust data models, write efficient queries, and run MongoDB-powered Python applications that scale seamlessly from prototype to production.
Build smarter apps with MongoDB. Write them faster in Python.

• Format: Paperback
• Language: English
• ISBN: B0FTMJ5J3G
• ISBN13: 9798268055535
• Release Date: October 2025
• Publisher: Independently Published
• Length: 248 Pages
• Weight: 0.96 lbs.
• Dimensions: 0.5" x 7.0" x 10.0"