Top 30 Intermediate Python & FastAPI Interview Questions and Answers

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1. Question 1 of 30

   What mechanism triggers FastAPI to automatically validate and parse an incoming JSON request body against a schema?

   • aSetting the response_model argument on the route decorator
   • bUsing a Pydantic model as the type hint for a route parameter
   • cAdding an explicit validate decorator to the route handler
   • dManually calling json.loads on request.body inside the route function
   Show the answer

   Answer: b · Using a Pydantic model as the type hint for a route parameter

   FastAPI inspects function signature type hints at runtime, so using a Pydantic model as a parameter type hint automatically triggers request parsing and validation. Manually calling json.loads inside the route is a red flag that ignores this declarative mechanism, and response_model governs response serialization, not request validation.

   Read the full bite: How does FastAPI leverage Pydantic for request validation and serialization?

2. Question 2 of 30

   When building an async execution-time decorator for FastAPI, why is omitting functools.wraps on the inner wrapper considered a red flag?

   • aIt causes the wrapper to run synchronously, blocking the event loop during high-concurrency requests.
   • bIt strips the original function's metadata, which breaks FastAPI's OpenAPI schema generation and dependency injection.
   • cIt makes FastAPI treat the endpoint as synchronous, offloading it to a thread pool and skewing the timer.
   • dIt prevents the decorator from awaiting the original coroutine, leading to unhandled runtime warnings.
   Show the answer

   Answer: b · It strips the original function's metadata, which breaks FastAPI's OpenAPI schema generation and dependency injection.

   functools.wraps preserves the original function's name, signature, and metadata, which FastAPI relies on to generate OpenAPI docs and resolve dependencies; omitting it exposes the wrapper's metadata instead. Distractor A is wrong because wraps has no effect on whether code runs synchronously or blocks the event loop.

   Read the full bite: Write an async decorator that logs execution time for FastAPI

3. Question 3 of 30

   Which implementation correctly minimizes total latency when a FastAPI endpoint must fetch data from two independent external APIs?

   • aInside an async def endpoint, pass two httpx.AsyncClient coroutines to asyncio.gather and await the result.
   • bInside an async def endpoint, pass two synchronous requests.get calls to asyncio.gather and await the result.
   • cInside an async def endpoint, await an httpx.AsyncClient call to the first API, then await a second call to the other API.
   • dInside an async def endpoint, run two synchronous requests.get calls concurrently using threading.Thread.
   Show the answer

   Answer: a · Inside an async def endpoint, pass two httpx.AsyncClient coroutines to asyncio.gather and await the result.

   asyncio.gather with an async HTTP client schedules both I/O-bound coroutines concurrently on the event loop, reducing total latency to roughly the slower call. Option C is tempting because it uses async/await correctly, but sequential awaiting means the second request cannot start until the first finishes, so latencies add up.

   Read the full bite: How do you structure concurrent API calls with asyncio.gather in FastAPI?

4. Question 4 of 30

   A FastAPI endpoint declares a path parameter as item_id: int. A request arrives for /items/abc, which cannot be coerced to an integer. What happens?

   • aFastAPI returns an automatic 422 error describing the invalid value, and the endpoint function body never executes
   • bPython raises a TypeError at the point where item_id is used inside the function body
   • cFastAPI passes the string abc through unchanged, and the function must convert it manually
   • dThe server returns a 500 Internal Server Error because the type coercion crashes the process
   Show the answer

   Answer: a · FastAPI returns an automatic 422 error describing the invalid value, and the endpoint function body never executes

   FastAPI validates the coerced type before your function runs, so an uncoercible value short circuits into an automatic 422 with no handler code executing. Python itself does nothing with the int annotation at runtime, which is why expecting a TypeError or manual parsing misses the point of the hint.

   Read the full bite: How FastAPI uses type hints for validation

5. Question 5 of 30

   Which FastAPI endpoint declaration identifies a user in the URL path and accepts an optional search term after the question mark?

   • aRoute /users/{user_id}/items with user_id in path and q optional
   • bRoute /users/items with user_id and q as query arguments, q optional
   • cRoute /users/{user_id}/items/{q} with user_id and q in path, q optional
   • dRoute /users/{user_id}/items with user_id in path and q required
   Show the answer

   Answer: a · Route /users/{user_id}/items with user_id in path and q optional

   Option A correctly places the user identifier in the path template and gives q a default of None so it becomes an optional query parameter. Option B is tempting because it also makes q optional, but it omits user_id from the path so FastAPI treats it as a query parameter, violating RESTful hierarchy.

   Read the full bite: What is the difference between a path parameter and a query parameter?

6. Question 6 of 30

   An endpoint declares a query parameter as q: Optional[str] with no default value. What happens when a client omits it?

   • aFastAPI automatically assigns None as the default based solely on the Optional type hint
   • bFastAPI follows Pydantic model conventions and defaults the parameter to None
   • cFastAPI returns a 422 Unprocessable Entity error
   • dFastAPI allows the request and sets q to None because the type hint permits None
   Show the answer

   Answer: c · FastAPI returns a 422 Unprocessable Entity error

   FastAPI derives requirement from the presence or absence of a Python signature default, not from type hints, so Optional[str] without = None is still required and omitting it triggers a 422 error. Option D is a common misconception because Optional alone does not make a parameter optional in FastAPI.

   Read the full bite: How does FastAPI distinguish required optional and default query parameters

7. Question 7 of 30

   What combination of standard and code sources enables FastAPI's automatic interactive documentation?

   • aIt generates a static JSON schema at build time from explicit annotations only
   • bIt requires manually maintaining an openapi.yaml file alongside your code changes
   • cIt uses the Swagger UI standard to parse docstrings without needing type hints
   • dIt dynamically builds an OpenAPI schema from type hints, Pydantic models, decorators, and docstrings
   Show the answer

   Answer: d · It dynamically builds an OpenAPI schema from type hints, Pydantic models, decorators, and docstrings

   FastAPI dynamically generates an OpenAPI schema by extracting metadata from type hints, Pydantic models, decorators, and docstrings, so no manual schema file is required. Option B is wrong because maintaining a separate openapi.yaml by hand is unnecessary and contradicts FastAPI's design.

   Read the full bite: What standard and code elements power FastAPI's auto-generated API docs?

8. Question 8 of 30

   In Pydantic V2, how should you enforce a positive price and a regex-formatted SKU without writing custom validators?

   • aSupply the constraints through json_schema_extra so they apply at runtime validation
   • bSet price: float = Field(gt=0) and sku: str = Field(pattern=r'^ITEM-\d{5}$') on standard types
   • cUse conint(gt=0) for price and constr(pattern=r'^ITEM-\d{5}$') for SKU in the model definition
   • dAdd @field_validator methods for price and sku to check values during model validation
   Show the answer

   Answer: b · Set price: float = Field(gt=0) and sku: str = Field(pattern=r'^ITEM-\d{5}$') on standard types

   Field's built-in gt and pattern parameters enforce constraints natively without extra code, while @field_validator adds unnecessary boilerplate and ignores Pydantic V2's native capabilities.

   Read the full bite: Enforce positive price and SKU format using Pydantic Field without custom validators

9. Question 9 of 30

   You are writing a Pydantic v2 model with a name field that must be at least 3 characters. Which implementation is correct?

   • aRun the length check in the FastAPI endpoint before creating the model.
   • bUse @field_validator('name') on a classmethod that raises ValueError without returning the value.
   • cUse @field_validator('name') on a classmethod that raises ValueError and returns the value.
   • dUse @validator('name') on an instance method that sets self.name after checking.
   Show the answer

   Answer: c · Use @field_validator('name') on a classmethod that raises ValueError and returns the value.

   Pydantic v2 requires single-field validators to use @field_validator on a classmethod, raise ValueError on failure, and return the value so processing continues. Option B is tempting but wrong because omitting the return breaks the model lifecycle, and D uses the deprecated v1 pattern.

   Read the full bite: Implement a custom validator for a single Pydantic model field

10. Question 10 of 30

    A FastAPI endpoint returns a UserDB model containing password_hash. Which strategy best prevents exposing the hash while keeping the API contract explicit and maintainable?

    • aSet password_hash to None in the endpoint body before returning the UserDB instance.
    • bUse response_model_exclude={"password_hash"} on the decorator to omit the field during serialization.
    • cCreate a separate UserOut model without password_hash and set response_model=UserOut on the endpoint.
    • dCall user.model_dump(exclude={"password_hash"}) and return the raw dict from the endpoint.
    Show the answer

    Answer: c · Create a separate UserOut model without password_hash and set response_model=UserOut on the endpoint.

    A dedicated output model declaratively isolates the API contract from the database schema and prevents accidental leaks if new sensitive fields are added later. Option B is a tempting quick fix, but it keeps the sensitive field in the source model and hides the contract outside the type system, making it harder to maintain.

    Read the full bite: How do you prevent password_hash from appearing in a FastAPI response?

11. Question 11 of 30

    An Order model needs to hold a list of Product models. What is the idiomatic Pydantic way to ensure nested dictionaries are validated and coerced automatically?

    • aParse the payload with a JSON library first, then pass the resulting objects to Order to avoid nested validation overhead.
    • bAnnotate the field as list[Product] where Product subclasses BaseModel, relying on Pydantic's recursive schema resolution.
    • cDefine products as list and attach a field_validator that manually constructs Product instances from each dictionary.
    • dOverride __init__ in Order to iterate over the raw list and build Product objects before assignment.
    Show the answer

    Answer: b · Annotate the field as list[Product] where Product subclasses BaseModel, relying on Pydantic's recursive schema resolution.

    Annotating the field as list[Product] leverages Pydantic's core schema generation to recursively validate nested items and report precise error paths automatically. Overriding __init__ to manually build Product instances is a red flag because it ignores Pydantic's built-in recursive validation machinery.

    Read the full bite: Model an Order with a nested Product list in Pydantic

12. Question 12 of 30

    A FastAPI endpoint with parameters file: UploadFile and user_id: str fails when receiving multipart form-data. What is the most likely reason?

    • aFastAPI assumes both parameters come from the JSON body because they lack File() and Form() metadata.
    • bThe endpoint must use bytes instead of UploadFile to enable spooled temporary file handling.
    • cString fields in multipart requests must always be defined as Pydantic models rather than plain types.
    • dpython-multipart is not installed, so FastAPI silently falls back to JSON parsing for binary data.
    Show the answer

    Answer: a · FastAPI assumes both parameters come from the JSON body because they lack File() and Form() metadata.

    Without File() or Form() metadata, FastAPI assumes parameters arrive in the JSON body, which breaks multipart form-data parsing. Distractor A reverses the memory behavior: UploadFile spools large files, while bytes loads everything into memory.

    Read the full bite: Implement a FastAPI file upload endpoint with form data

13. Question 13 of 30

    In FastAPI, which approach best implements a reusable current-user check that preserves OpenAPI docs integration and keeps endpoints testable?

    • aDefine a get_current_user dependency that uses OAuth2PasswordBearer, validates the token, returns a User model, and inject it into routes with Depends.
    • bReturn the raw token string from a dependency and let each endpoint query the database for the user.
    • cManually read request.headers.get("Authorization") inside every endpoint and decode the JWT there.
    • dCreate a middleware that parses the Authorization header and stores the user in request.state.
    Show the answer

    Answer: a · Define a get_current_user dependency that uses OAuth2PasswordBearer, validates the token, returns a User model, and inject it into routes with Depends.

    A dedicated get_current_user dependency keeps auth explicit in the signature, auto-documents security in OpenAPI, and enables test overrides via app.dependency_overrides. Middleware hides the dependency from the docs and complicates testing.

    Read the full bite: How do you create a reusable current-user dependency in FastAPI?

14. Question 14 of 30

    In FastAPI, what is the key benefit of declaring a Response parameter to set headers and cookies rather than returning a Response subclass directly?

    • aIt allows the endpoint to read incoming request headers and cookies through the injected Response object.
    • bReturning a Response subclass directly causes FastAPI to raise a runtime validation error when response_model is declared.
    • cIt is the only way to attach multiple Set-Cookie headers in a single endpoint response.
    • dFastAPI can merge the mutated headers and cookies into the final response without bypassing automatic serialization and response_model validation.
    Show the answer

    Answer: d · FastAPI can merge the mutated headers and cookies into the final response without bypassing automatic serialization and response_model validation.

    Injecting Response lets FastAPI merge your metadata into the automatically serialized final response while preserving response_model filtering and OpenAPI docs. The injected Response object handles outgoing data only; reading incoming request headers requires the Request dependency or Header parameters, not Response.

    Read the full bite: How do you set a custom header and cookie in FastAPI?

15. Question 15 of 30

    When you assign a mock to app.dependency_overrides[get_db] in FastAPI, what happens during the test and what must you do afterward?

    • aFastAPI executes the original dependency and its sub-dependencies, then replaces the final return value with the mock, and the framework automatically resets overrides after every test.
    • bFastAPI injects the mock exclusively, bypassing the original and its sub-dependencies, and you must manually clear overrides after the test.
    • cFastAPI calls the mock but still executes the original dependency's sub-dependencies to preserve the injection chain, and overrides expire at the end of the test session.
    • dMonkeypatching the module containing the dependency is the idiomatic approach because dependency_overrides requires you to manually rebuild the dependency graph.
    Show the answer

    Answer: b · FastAPI injects the mock exclusively, bypassing the original and its sub-dependencies, and you must manually clear overrides after the test.

    FastAPI uses the replacement function exclusively and never executes the original dependency or its sub-dependencies. Option C is tempting but incorrect because sub-dependencies are fully bypassed, not preserved, and overrides persist until you manually clear them.

    Read the full bite: How would you override a FastAPI dependency during testing?

16. Question 16 of 30

    You need a FastAPI dependency that accepts roles in its constructor and validates the current user each request. Why use a callable class rather than a plain function?

    • aThe instance becomes a request-scoped singleton that stores the role list globally after the first call
    • bThe class __init__ receives configuration and sub-dependencies declaratively while __call__ handles per-request logic and OpenAPI integration
    • cCallable classes bypass automatic dependency resolution so you can instantiate them manually inside the endpoint
    • dFastAPI only inspects type annotations on class __call__ methods, not on multi-parameter functions
    Show the answer

    Answer: b · The class __init__ receives configuration and sub-dependencies declaratively while __call__ handles per-request logic and OpenAPI integration

    A callable class lets FastAPI resolve constructor sub-dependencies and configuration via __init__ while __call__ handles per-request execution and remains visible to OpenAPI. The tempting distractor wrongly claims you must manually instantiate the class inside the endpoint, which defeats automatic injection and is explicitly flagged as a red flag.

    Read the full bite: How do you use a Python class as a FastAPI dependency?

17. Question 17 of 30

    A FastAPI endpoint depends on get_session, which yields and depends on get_pool, which also yields. What teardown order is guaranteed after the endpoint runs?

    • aget_session and get_pool tear down simultaneously as parallel background tasks
    • bget_pool tears down before get_session because it was set up first
    • cTeardown order is undefined and determined by Python garbage collection
    • dget_session tears down first, then get_pool, managed by FastAPI's internal stack
    Show the answer

    Answer: d · get_session tears down first, then get_pool, managed by FastAPI's internal stack

    FastAPI uses an internal stack to ensure nested yield dependencies teardown bottom-up, so get_session closes before get_pool releases connections. Distractor A incorrectly assumes teardown mirrors setup order, which would risk resource leaks.

    Read the full bite: How does FastAPI execute setup and teardown in nested yield dependencies?

18. Question 18 of 30

    In FastAPI, a database-querying dependency is injected into both a path operation and a sub-dependency. By default, what happens during a single request?

    • aThe dependency runs twice, once per declaration, because FastAPI resolves each Depends() independently
    • bThe dependency runs fresh each time because caching must be explicitly enabled with use_cache=True
    • cThe dependency runs once and the cached value is reused only within that request's dependency tree
    • dThe dependency runs once and its cached result is shared across all concurrent requests
    Show the answer

    Answer: c · The dependency runs once and the cached value is reused only within that request's dependency tree

    FastAPI defaults to use_cache=True, so it executes the dependency once per request and reuses that cached value throughout the same request's dependency tree. Option A is a common misconception: FastAPI does not independently resolve every Depends() declaration; it avoids redundant work by caching within the request lifecycle.

    Read the full bite: How does FastAPI cache dependencies within a single request?

19. Question 19 of 30

    You need to enforce authentication on every /users endpoint while leaving /items public. What is the most maintainable FastAPI approach?

    • aAdd Depends(get_current_user) to every path operation in the users router and leave items routes bare.
    • bRegister a middleware that checks authentication before every request and bypasses /items by path.
    • cPass dependencies=[Depends(get_current_user)] to the users APIRouter and omit it from the items router, then include both in the app.
    • dApply the dependency at the app level and add conditional logic inside get_current_user to skip /items paths.
    Show the answer

    Answer: c · Pass dependencies=[Depends(get_current_user)] to the users APIRouter and omit it from the items router, then include both in the app.

    Passing dependencies to APIRouter scopes authentication to that router only while keeping other routers unaffected and preserving OpenAPI docs. Adding Depends to every route manually violates DRY and makes refactoring painful, even though it produces the same runtime behavior.

    Read the full bite: How to apply a dependency to only one FastAPI router?

20. Question 20 of 30

    Which approach best balances performance, testability, and type safety when making configuration available to FastAPI path operations?

    • aCreate a new Settings instance inside each route handler on every request
    • bCache the Settings instance with lru_cache and inject it via FastAPI dependency injection
    • cLoad configuration into an untyped dict from a JSON file accessed directly by routes
    • dImport a global Settings instance directly into route modules
    Show the answer

    Answer: b · Cache the Settings instance with lru_cache and inject it via FastAPI dependency injection

    Caching with lru_cache parses config once at startup instead of on every request, and dependency injection lets tests easily override settings. Option D is tempting but wrong because a direct global import is brittle and harder to mock than an injected dependency.

    Read the full bite: Manage dev, staging, and prod configs in a large FastAPI app

21. Question 21 of 30

    Which approach best keeps FastAPI router modules decoupled and reusable when applying a shared path prefix like /api/v1?

    • aUse relative paths in the router and apply the shared prefix via app.include_router when mounting
    • bPass the prefix argument directly to the APIRouter constructor instead of to include_router
    • cCreate custom middleware that rewrites incoming URLs to prepend the shared prefix before routing
    • dHardcode the full absolute path in every APIRouter decorator and mount the router without any prefix
    Show the answer

    Answer: a · Use relative paths in the router and apply the shared prefix via app.include_router when mounting

    Defining relative paths in APIRouter and setting the prefix in include_router keeps route definitions separate from URL composition, enabling reuse. Hardcoding full paths scatters configuration, while middleware and router-level prefix arguments add unnecessary complexity.

    Read the full bite: How do you apply a common path prefix across FastAPI routers?

22. Question 22 of 30

    You need to call a legacy synchronous database driver inside an async FastAPI endpoint. Which approach prevents the event loop from freezing?

    • aWrap the call with asyncio.create_task and await the resulting task
    • bawait the synchronous function call directly, since await yields control to the loop
    • cAdd the async keyword to the function definition and call it normally
    • dUse asyncio.to_thread to run the call in a ThreadPoolExecutor worker
    Show the answer

    Answer: d · Use asyncio.to_thread to run the call in a ThreadPoolExecutor worker

    asyncio.to_thread submits the blocking call to a ThreadPoolExecutor, letting the event loop run other coroutines while the sync IO completes in a worker thread. asyncio.create_task is tempting because it enables concurrent coroutine execution, but it does not offload synchronous work to another thread, so the blocking call would still freeze the event loop.

    Read the full bite: How do you safely execute blocking code from an async function

23. Question 23 of 30

    In a single-threaded asyncio program, how does the event loop switch execution from one Task to another?

    • aThe running Task must reach an await expression to yield control back to the loop
    • bThe loop polls the OS selector and forcibly interrupts the running Task when other I/O is ready
    • cThe loop assigns a small time slice to each Task and preempts it when the slice expires
    • dTasks automatically run in the background and the loop collects their results when they finish
    Show the answer

    Answer: a · The running Task must reach an await expression to yield control back to the loop

    Asyncio uses cooperative multitasking, so a Task only yields control at an await boundary. Option B is tempting because the loop does poll the OS selector, but it cannot forcibly interrupt a running Task—control must be yielded voluntarily.

    Read the full bite: Explain the asyncio event loop and cooperative multitasking

24. Question 24 of 30

    You call asyncio.wait on three tasks, and one of them raises an exception. What actually happens?

    • await immediately raises the exception to the caller, identical to the default behavior of gather
    • bThe failing task is silently dropped from both the done and pending sets
    • cwait does not raise the exception itself, it returns the task in the done set, and you must check each task's result or exception yourself
    • dwait cancels the other two tasks automatically as soon as one raises an exception
    Show the answer

    Answer: c · wait does not raise the exception itself, it returns the task in the done set, and you must check each task's result or exception yourself

    asyncio.wait never raises on a failed task, it just places that task in the done set, and you have to call its result or exception method yourself, which is why a failure can go unnoticed. That silent behavior is the opposite of gather's default, which propagates the first exception immediately.

    Read the full bite: asyncio.gather vs asyncio.wait

25. Question 25 of 30

    What is the primary risk of using threading.Lock inside an asyncio coroutine to guard shared state?

    • aThe lock has no effect since asyncio tasks cannot interleave on a single thread.
    • bIt safely protects the resource because locks are universal synchronization primitives.
    • cIt blocks the underlying OS thread, freezing the event loop and all other tasks.
    • dThe event loop continues scheduling other coroutines while the task waits for the lock.
    Show the answer

    Answer: c · It blocks the underlying OS thread, freezing the event loop and all other tasks.

    threading.Lock blocks the native OS thread via OS primitives, which prevents the event loop from scheduling any other coroutine. Option B is tempting because locks do protect shared state in threaded code, but inside a coroutine a threading.Lock halts the entire loop instead of yielding control.

    Read the full bite: When should you use asyncio.Lock over threading.Lock?

26. Question 26 of 30

    Why should get_db use yield instead of return when providing a database session to FastAPI endpoints?

    • aYield allows the session to be defined once globally and imported by all endpoints.
    • bYield converts the function into middleware that executes for every route automatically.
    • cYield lets FastAPI cache the session for reuse across multiple incoming requests.
    • dYield ensures cleanup logic in the finally block runs after the endpoint completes.
    Show the answer

    Answer: d · Yield ensures cleanup logic in the finally block runs after the endpoint completes.

    Using yield with a finally block guarantees the session closes after the endpoint runs, even if an exception occurs. Reusing a cached session across requests, as in option C, breaks thread safety and causes concurrency issues.

    Read the full bite: How do you use FastAPI dependency injection for database sessions?

27. Question 27 of 30

    Why does a synchronous database call inside an async FastAPI endpoint prevent other requests from progressing even when the underlying driver releases the GIL?

    • aBecause the single-threaded event loop never receives an await point during blocking socket calls, so it cannot interleave other requests
    • bBecause the database connection pool is exhausted by long-running synchronous queries, forcing subsequent requests to wait
    • cBecause synchronous socket calls hold the GIL, preventing the event loop from switching to another task until the query returns
    • dBecause releasing the GIL lets other Python threads run, but the event loop cannot migrate tasks to those threads without run_in_executor
    Show the answer

    Answer: a · Because the single-threaded event loop never receives an await point during blocking socket calls, so it cannot interleave other requests

    The event loop requires await points to switch tasks, which synchronous database calls never yield, so the thread blocks even if the GIL is released. Distractor D is tempting because it sounds like the GIL is the culprit, but the card explicitly notes that synchronous I/O blocks the loop despite releasing the GIL.

    Read the full bite: Why synchronous DB libraries block async FastAPI endpoints and correct SQLAlchemy usage

28. Question 28 of 30

    When implementing a PATCH endpoint for partial SQLAlchemy updates, which approach prevents omitted JSON fields from overwriting existing database values?

    • aLoad the existing record, dump the update schema with exclude_unset=True, and apply fields with setattr
    • bReuse the creation schema and call model_dump without exclude_unset=True
    • cExecute a Core update statement directly against the table without loading the instance
    • dConstruct a new ORM instance from the payload and merge it into the session
    Show the answer

    Answer: a · Load the existing record, dump the update schema with exclude_unset=True, and apply fields with setattr

    Using exclude_unset=True strips keys the client omitted, so setattr only modifies the fields actually provided. Option B is tempting because it uses the same dump pattern, but without exclude_unset=True missing fields become None and clobber existing data.

    Read the full bite: Implement a PATCH endpoint for partial SQLAlchemy updates

29. Question 29 of 30

    Why does a Motor or Beanie integration not need a per-request session object the way SQLAlchemy's AsyncSession does?

    • aFastAPI automatically opens a session for every NoSQL request
    • bBeanie disables connection pooling entirely for safety
    • cMongoDB is single-threaded so only one connection is ever used
    • dMotor's client maintains an internal connection pool and operations are awaited directly, with no unit-of-work or identity map to scope per request
    Show the answer

    Answer: d · Motor's client maintains an internal connection pool and operations are awaited directly, with no unit-of-work or identity map to scope per request

    Motor's client pools connections globally and Beanie awaits queries directly, so there is no SQLAlchemy-style session lifecycle to manage. MongoDB is not single-threaded, so that option is a misconception.

    Read the full bite: MongoDB async ODM vs SQLAlchemy sessions

30. Question 30 of 30

    Which step must occur inside the POST /token endpoint before returning an access token?

    • aThe submitted password is verified against a stored hash using a library like pwdlib
    • bThe get_current_user function decodes the JWT sub claim to identify the user
    • cThe OAuth2PasswordBearer dependency validates the Authorization header
    • dA server-side session is created to track the authenticated client state
    Show the answer

    Answer: a · The submitted password is verified against a stored hash using a library like pwdlib

    The token endpoint must verify the submitted password against a stored hash before issuing a JWT. Creating a server-side session is wrong because this flow is stateless, and get_current_user is used on subsequent protected routes, not during token creation.

    Read the full bite: Implement OAuth2 Password Flow in FastAPI