Building APIs with Python Course

Lesson 1 • Python Syntax and Data Types

Review core Python syntax, variables, and built-in data types used in API logic. Mastery here underpins all request and response handling later.

Lesson 2 • Setting Up the Development Environment

Configure Python, virtual environments, and package managers for API projects. Proper setup prevents dependency conflicts throughout the course.

Lesson 3 • Functions and Modules

Define reusable functions and organise code into modules and packages. Modular design is the structural backbone of any API codebase.

Lesson 4 • Working with JSON and Files

Parse, serialise, and manipulate JSON data and read configuration files. JSON is the primary data format exchanged in REST APIs.

Lesson 1 • Testing APIs with Client Tools

Use HTTP client tools to send requests and inspect responses before writing code. Hands-on testing builds intuition for API behaviour.

Lesson 2 • REST Architectural Principles

Define the six REST constraints and explain how they shape API design decisions. Understanding REST guides every endpoint and resource decision made later.

Lesson 3 • Designing RESTful Endpoints

Apply naming conventions, HTTP verbs, and resource hierarchies to design clean endpoints. Good endpoint design reduces client confusion and maintenance cost.

Lesson 1 • Error Handling in Flask

Register error handlers for HTTP errors and unhandled exceptions. Centralised error handling ensures consistent error responses across all routes.

Lesson 2 • Flask Application Structure

Initialise a Flask app, understand the application factory pattern, and organise project files. Proper structure scales cleanly as the API grows.

Lesson 3 • Request Parsing and Validation

Extract and validate data from request bodies, query strings, and headers. Input validation prevents bad data from reaching business logic.

Lesson 4 • Routing and URL Rules

Define routes using decorators and handle dynamic URL segments. Routes map HTTP requests to Python functions that return responses.

Lesson 1 • Request Bodies with Pydantic

Define request schemas using Pydantic models for automatic parsing and validation. Pydantic eliminates manual validation boilerplate and provides clear error messages.

Lesson 2 • Path and Query Parameters

Declare typed path and query parameters with automatic validation and documentation. FastAPI infers validation rules directly from Python type hints.

Lesson 3 • Response Models and Status Codes

Specify response models to filter output fields and document return shapes. Explicit response models enforce API contracts and improve generated documentation.

Lesson 4 • Dependency Injection in FastAPI

Use FastAPI's Depends system to share logic like auth checks and DB sessions. Dependency injection keeps route functions thin and testable.

Lesson 1 • CRUD Operations with ORM

Implement create, read, update, and delete operations using SQLAlchemy query API. These operations form the core data layer of any REST API.

Lesson 2 • Database Migrations with Alembic

Use Alembic to version-control schema changes without data loss. Migrations are essential for evolving production database schemas safely.

Lesson 3 • Relational Database Fundamentals

Review tables, relationships, primary keys, and foreign keys as they apply to API data models. Database design decisions directly shape API resource structure.

Lesson 4 • Serialisation and Data Transfer Objects

Convert ORM model instances to JSON-serialisable dictionaries or Pydantic schemas. Serialisation decouples the database layer from the API response layer.

Lesson 1 • Authentication Concepts and Strategies

Compare session-based, token-based, and API key authentication models. Choosing the right strategy depends on client type and security requirements.

Lesson 2 • Implementing JWT Authentication

Generate, sign, and verify JSON Web Tokens to authenticate API requests. JWTs enable stateless authentication suitable for distributed API deployments.

Lesson 3 • Password Hashing and Storage

Hash passwords with bcrypt and validate them during login without storing plaintext. Secure password storage is a non-negotiable security baseline.

Lesson 4 • Protecting Routes with Middleware

Apply authentication middleware and decorators to restrict access to protected routes. Middleware enforces auth consistently without duplicating logic in each route.

Lesson 1 • Test Coverage and CI Integration

Measure test coverage with pytest-cov and run tests automatically in a CI pipeline. Coverage metrics and automation prevent regressions from reaching production.

Lesson 2 • Testing Fundamentals with pytest

Set up pytest, write test functions, and use assertions to verify behaviour. A solid testing foundation enables confident refactoring throughout the project.

Lesson 3 • Integration Testing with Test Clients

Use Flask and FastAPI test clients to send HTTP requests against a live app. Integration tests verify that routes, middleware, and database layers work together.

Lesson 4 • Unit Testing API Logic

Isolate and test individual functions, validators, and service layer methods. Unit tests catch logic errors early without requiring a running server.

Lesson 1 • Performance and Security Hardening

Apply rate limiting, CORS policies, and response caching to harden production APIs. These measures protect against abuse and improve response times under load.

Lesson 2 • Containerising APIs with Docker

Write Dockerfiles and docker-compose files to package APIs as portable containers. Containers eliminate environment inconsistencies between development and production.

Lesson 3 • API Documentation with OpenAPI

Write and enhance OpenAPI specifications to produce developer-friendly API docs. Good documentation reduces integration time for API consumers.

Lesson 4 • Deploying to Cloud Platforms

Deploy containerised APIs to cloud platforms using managed services and CI/CD pipelines. Cloud deployment makes APIs accessible, scalable, and maintainable.