Deepen your FastAPI vocabulary — lifespan context managers, test overrides, background tasks, and response shaping.
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At standup, a backend developer explains the lifespan context manager in FastAPI. Which description is correct?
The lifespan parameter (FastAPI 0.93+) accepts an @asynccontextmanager function. Code before yield runs on application startup (e.g. connecting to a database, loading ML models); code after yield runs on shutdown (e.g. closing connections). It replaces the deprecated @app.on_event("startup") decorator with a cleaner, testable pattern.
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In a PR review, a teammate uses dependency overrides in tests. What is the correct explanation?
app.dependency_overrides is a dict on the FastAPI app instance. Setting app.dependency_overrides[get_db] = get_test_db tells FastAPI to inject get_test_db wherever get_db is declared as a dependency, for the lifetime of the TestClient. It works with both sync and async dependencies and requires no patching of production code.
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An incident involves a slow endpoint that is blocking the event loop. A teammate suggests BackgroundTasks. What is correct?
BackgroundTasks run the added functions after the HTTP response has been sent to the client. They run in the same event loop thread (async functions) or in a thread pool (sync functions). They are suitable for lightweight I/O work like sending emails or writing audit logs. For CPU-bound or long-running work, use a proper task queue like Celery, ARQ, or Dramatiq.
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In a design review, the team discusses response_model_exclude and response_model_include. What is correct?
response_model_exclude and response_model_include are per-endpoint parameters (on @app.get, @app.post, etc.) that filter the serialised response without modifying the Pydantic model itself. exclude blacklists fields; include whitelists fields. Both accept a set of field names or a nested dict for nested model filtering.
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In a code review, a developer creates a custom Request class in FastAPI. What is the correct approach?
FastAPI (via Starlette) supports custom Request classes. Subclass fastapi.Request, add your properties (e.g. lazy-parse a JWT into a tenant ID), then pass request_class=MyRequest to the FastAPI() constructor. Type-annotate path operation parameters with request: MyRequest to get your custom class injected. This avoids boilerplate dependency functions for request-level concerns.
What does the "FastAPI Advanced Patterns Vocabulary" vocabulary exercise cover?
This exercise tests real IT vocabulary related to fastapi advanced patterns vocabulary through 5 multiple-choice questions, each built from realistic workplace sentences rather than abstract definitions.
Is this vocabulary exercise free to use?
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How many questions does this exercise have?
This exercise has 5 questions. Each one shows a real-world sentence or scenario with multiple-choice options and an explanation once you answer.
What happens after I answer a question?
You'll see immediate feedback showing whether your answer was correct, along with a short explanation of why — then a button to move to the next question, and a full results screen at the end.
Can I retry the exercise if I get questions wrong?
Yes. Once you reach the results screen, click "Try again" to reset your answers and go through the exercise from the start as many times as you like.
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No account is needed. Your answers are scored in your browser during the session — nothing is saved to a server, so you can jump straight in.
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No — progress within an exercise resets if you navigate away or reload. Each exercise is short enough to complete in a few minutes in one sitting.
Are these vocabulary exercises connected to other topics?
Yes — browse the full vocabulary exercises hub to find related modules covering adjacent IT topics and roles.
How is this different from reading a glossary or blog article?
Exercises like this one are active recall drills — you have to choose the correct term or phrasing yourself, which builds retention faster than passively reading a definition.
Where can I find more vocabulary exercises?
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