From Python scripts to APIs running in production
Mastering APIs with Python takes you from your first requests.get() to a deployed system on AWS. You build six portfolio projects along the way, and two of them end up live at a URL a recruiter can click.
Pay once, keep it forever. 30-day money-back guarantee.
What you'll ship
Six projects you build and keep
Real applications for your portfolio, not todo apps. Two of them deploy to a live URL you can put on a CV.
Production Weather CLI
Ch 13A command-line tool that retries failed calls, validates messy input, and logs the way production code does.
Spotify Music Time Machine
Ch 14–20A full web app with Spotify login, your listening history stored in a database, deployed and live on the internet.
Enterprise Music Platform
Ch 24–25The same app rebuilt on PostgreSQL with connection pooling, the upgrade that real traffic forces on you.
News Aggregator API
Ch 26Your own REST API built with FastAPI, with authentication, rate limiting, and docs that generate themselves.
Cloud-Native News Service
Ch 27–29That API running on AWS inside Docker, shipped automatically by a pipeline every time you push.
Multi-Source Analytics Platform
Ch 30Async workers pulling many APIs at once behind a microservices architecture on AWS.
What's inside
From first request to production
Thirty chapters in four parts, building toward six portfolio projects you can show.
Foundations & Core Skills
How modern applications talk to each other. Your first API call, JSON, authentication, API keys, error handling, and validation. Ends with a production-ready weather CLI: retries, logging, and input validation included.
Part II · Ch 14–20Full-Stack Integration
OAuth 2.0, databases with SQLite, and Flask. You build the Spotify Music Time Machine: a real web app with login, stored listening history, a dashboard, a test suite, and a live deployed URL.
Parts III & IV · Ch 21–30Professional & Production
Webhooks, async, file uploads, PostgreSQL, and building your own REST API with FastAPI. Then the part most books skip: Docker, AWS deployment, CI/CD, and production operations, ending in a multi-source analytics platform.
Who is this for?
Most Python learners can follow tutorials. Fewer know how to turn API code into systems that handle errors, store data, pass tests, and survive deployment. So if you can write basic Python and you want to cross the gap between tutorials and production work, with a portfolio that backs you up in interviews, this is for you. Every architectural decision is taught the way you would defend it to a hiring manager, so you can explain your choices instead of just running the code. Already working as a developer? Skim the first two setup chapters and start at Chapter 3.
A good fit if you
- Know basic Python and want to build things that survive contact with the real internet
- Want portfolio projects with OAuth, databases, testing, and cloud deployment, not todo apps
Not a fit if you
- Have never written Python before (learn the basics first, then come back)
- Want a frontend or data-science curriculum; this is backend and APIs throughout
The author
Written and supported by one developer.
I'm Simon O'Connor, an Irish software developer. I spent a year and a half writing this book and building every project in it myself, shaping the explanations around the problems people actually hit when they move beyond small Python scripts.
Tutorials usually stop once the code works once. Professional work starts after that: handling errors, protecting credentials, storing state, testing behaviour, and deploying safely. The book teaches that part, from your first API call to a production capstone on AWS.
I answer every support email personally, and every purchase comes with a 30-day money-back guarantee. If you get stuck, you're dealing with the person who wrote the code.
Simon O'Connor
Author, Mastering APIs with Python
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