Python

Build one 'sales data API server' across 5 real stages: discount-calculation logic → a FastAPI REST API → pandas data analysis → dependency management → testing/deployment. Learn to read and review AI-written Python code.

Stages

1. Build a sales-data API server · Step 1 discount logic

   ~80 minSubscription needed

   Write the core discount-calculation logic with functions, type hints, and f-strings. This project builds one real API server across 5 lessons — start by reading an AI-written script from the top.

2. Build a sales-data API server · Step 2 REST API

   ~110 minSubscription needed

   Wrap the Step 1 discount logic in a real FastAPI endpoint. Read how Pydantic models validate requests and serialize responses, and diagnose the common 422 error.

3. Build a sales-data API server · Step 3 data analysis

   ~110 minSubscription needed

   Analyze the sales data managed by the Step 2 API with pandas. Learn to confirm whether AI-proposed data-processing code actually produces the intended result.

4. Build a sales-data API server · Step 4 dependency management

   ~90 minSubscription needed

   Consolidate the packages the API server and analysis script both need. Diagnose version conflicts and dependency issues, and learn to describe them precisely to an AI.

5. Build a sales-data API server · Step 5 testing/deployment

   ~110 minSubscription needed

   Test the Step 1 discount logic with pytest and deploy the Step 2 API with Docker — the wrap-up lesson for this 5-step project.