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10 things you will learn
- Read and understand the requirements of an OpenAPI specification
- How to build an API with FastAPI
- Model data validation schemas using Pydantic
- Use FastAPI's Dependency Injection system to handle common query parameters
- Write custom middleware
- Data modelling with SQLAlchemy
- Manage database migrations using Alembic
- API testing with pytest and schemathesis
- Dockerize your application and run with docker-compose
- Deploy with Render
Course Curriculum (in progress)
Welcome!
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Introduction to the project
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Building an API with FastAPI
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- Implementing API endpoints (14:18)
- Capturing and validating URL query and path parameters; setting response status codes (18:34)
- Modelling validation schemas with Pydantic (22:45)
- Hooking the Pydantic models with the endpoints to validate request and response payloads (11:27)
- Fine-tuning Pydantic schemas for OpenAPI compatibility (14:21)
Adding the data layer with SQLAlchemy
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- What is SQLAlchemy? (6:03)
- Introducing the database design (3:03)
- Setting up SQLAlchemy and Alembic (5:12)
- Creating SQLAlchemy's base declarative class (6:36)
- Modelling the database with SQLAlchemy (20:07)
- Running migrations with Alembic (14:10)
- Inserting records with SQLAlchemy (11:25)
- Running your first query with SQLAlchemy (3:25)
- Adding Dataclass super powers to SQLAlchemy models (3:52)
- Running WHERE and COUNT queries with SQLAlchemy (5:12)
- Running complex queries with SQLAlchemy (2:59)
- Updating records with SQLAlchemy (3:13)
- Deleting records with SQLAlchemy (1:24)
- Avoid glitches with SQLite (2:54)
- SQLAlchemy assignment (1:30)
Integrating SQLAlchemy with the API layer
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Testing with the Swagger UI and tracing errors in FastAPI
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Updating jobs
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Adding the Candidates API
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