Prerequisites

This is a foundational chapter with no prerequisites beyond the course prerequisite.

• Python 3.10+ installed, with working knowledge of type hints, dataclasses, and decorators
• HTTP fundamentals: familiarity with request methods (GET, POST, PUT, DELETE), status codes (200, 201, 404, 422), and JSON request/response bodies
• pip or uv package manager configured to install FastAPI and Uvicorn into a virtual environment
• Command-line comfort: ability to run development servers, execute curl commands, and read terminal output

Learning Goals

1. Create path operations with GET, POST, PUT, DELETE and proper HTTP status codes

   • Create path operations with GET, POST, PUT, DELETE and proper HTTP status codesMaster FastAPI's decorator-based routing system to map HTTP methods onto Python handler functions, selecting the correct method semantics and status codes for each type of operation in a RESTful API.
   • Define route handlers using @app.get(), @app.post(), @app.put(), and @app.delete() decorators with explicit path strings, and understand how FastAPI's order-of-declaration determines route matching priority when paths overlap
   • Extract path parameters from URL segments using Python type annotations so that FastAPI automatically parses and validates identifiers like /items/{item_id} into the correct Python type, returning a 422 response when the value cannot be coerced
   • Accept query parameters for optional filtering, pagination, and sorting by declaring function arguments with default values, and combine them with path parameters in a single handler to support URLs like /items/{item_id}?include_details=true
   • Return appropriate HTTP status codes—201 for resource creation, 204 for successful deletion with no response body, 404 for missing resources—by setting status_code in the decorator and raising HTTPException when business logic conditions fail

2. Define Pydantic models for request validation with field constraints and cust...

   • Define Pydantic models for request validation with field constraints and custom validatorsBuild structured data contracts using Pydantic's BaseModel that enforce type safety, field-level constraints, and cross-field business rules before any handler logic executes.
   • Declare request body schemas as Pydantic model classes where each field carries a Python type annotation, and observe how FastAPI automatically deserializes incoming JSON into model instances, eliminating manual json.loads() and key-checking boilerplate
   • Apply Field constraints—min_length, max_length, ge, le, pattern—to enforce domain rules at the schema level, such as ensuring a temperature parameter stays between 0.0 and 2.0 or that a model_name matches a specific regex pattern
   • Write @field_validator methods for single-field rules and @model_validator methods for cross-field logic, such as ensuring max_tokens does not exceed a model-specific ceiling or that stop_sequences is only provided when stream is False
   • Handle validation failures by interpreting FastAPI's automatic 422 error responses, which include a structured JSON body with loc, msg, and type fields pinpointing exactly which field failed and why, enabling frontend teams to render precise error messages

3. Implement dependency injection for shared resources like database connections...

   • Implement dependency injection for shared resources like database connections and configUse FastAPI's Depends() system to provide database sessions, configuration objects, and authentication state to route handlers without global variables, manual instantiation, or tightly coupled constructors.
   • Create dependency functions that yield resources with proper setup and teardown semantics using Python generators, ensuring database connections are returned to the pool and file handles are closed even when handlers raise exceptions
   • Chain dependencies hierarchically so that a route depends on get_current_user, which itself depends on verify_token, which depends on get_settings—FastAPI resolves the full dependency graph per request and caches results so each dependency executes at most once per request cycle
   • Replace class-based dependency patterns using call methods when dependencies require initialization-time configuration, such as a rate limiter that accepts max_requests and window_seconds parameters at construction but returns a callable that FastAPI invokes per request
   • Override dependencies in test suites by using app.dependency_overrides to swap production database sessions with in-memory SQLite connections or replace external API clients with mock objects, enabling isolated integration tests without environment-specific configuration

4. Configure automatic OpenAPI/Swagger documentation with response schemas and e...

   • Configure automatic OpenAPI/Swagger documentation with response schemas and examplesLeverage FastAPI's built-in OpenAPI generation to produce interactive API documentation that accurately describes every endpoint's request format, response schema, and example payloads without writing a single line of documentation manually.
   • Assign response models using the response_model parameter on route decorators to control which fields appear in API responses, stripping internal fields like hashed_password or internal_score from the serialized output while keeping them available inside your handler logic
   • Define multiple response schemas per endpoint using the responses parameter to document error cases—mapping status code 404 to a NotFoundError model and 422 to a ValidationError model—so that generated documentation shows consumers exactly what error payloads to expect
   • Add rich metadata through Field(description=..., json_schema_extra={"example": ...}) on model fields and through summary, description, and tags parameters on route decorators, transforming the auto-generated Swagger UI at /docs from a bare schema listing into a navigable, self-explanatory API reference
   • Customize the OpenAPI schema globally by passing title, version, description, and servers to the FastAPI() constructor, and group related endpoints under logical tags so that the generated documentation mirrors your API's domain structure rather than its file layout

Key Terminology