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FastAPIframework~10 mins

Multiple path parameters in FastAPI - Interactive Code Practice

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Practice - 5 Tasks
Answer the questions below
1fill in blank
easy

Complete the code to import the correct FastAPI class.

FastAPI
from fastapi import [1]
app = FastAPI()
Drag options to blanks, or click blank then click option'
AFastAPI
BDepends
CBody
DRequest
Attempts:
3 left
💡 Hint
Common Mistakes
Importing Request instead of FastAPI.
Importing Body instead of FastAPI.
2fill in blank
medium

Complete the code to import the Body function for request body parameters.

FastAPI
from fastapi import FastAPI, [1]
app = FastAPI()
Drag options to blanks, or click blank then click option'
APath
BDepends
CQuery
DBody
Attempts:
3 left
💡 Hint
Common Mistakes
Importing Depends instead of Body.
Importing Query or Path which are for URL parameters.
3fill in blank
hard

Fix the error in the function parameter to correctly use Body for multiple parameters.

FastAPI
from fastapi import FastAPI, Body
app = FastAPI()

@app.post("/items")
async def create_item(name: str = [1], description: str = Body(...)):
    return {"name": name, "description": description}
Drag options to blanks, or click blank then click option'
ABody(...)
BQuery(...)
CPath(...)
DDepends(...)
Attempts:
3 left
💡 Hint
Common Mistakes
Using Query or Path instead of Body for body parameters.
Not using Body(...) to mark required parameters.
4fill in blank
hard

Fill both blanks to declare two required body parameters with descriptions.

FastAPI
from fastapi import FastAPI, Body
app = FastAPI()

@app.post("/users")
async def create_user(username: str = [1], email: str = [2]):
    return {"username": username, "email": email}
Drag options to blanks, or click blank then click option'
ABody(..., description="The user's username")
BQuery(..., description="The user's username")
CBody(..., description="The user's email")
DPath(..., description="The user's email")
Attempts:
3 left
💡 Hint
Common Mistakes
Using Query or Path instead of Body for body parameters.
Omitting the description argument.
5fill in blank
hard

Fill all three blanks to declare optional body parameters with default values and descriptions.

FastAPI
from fastapi import FastAPI, Body
app = FastAPI()

@app.post("/products")
async def create_product(name: str = [1], price: float = [2], description: str = [3]):
    return {"name": name, "price": price, "description": description}
Drag options to blanks, or click blank then click option'
ABody(None, description="Product name")
BBody(0.0, description="Product price")
CBody(None, description="Product description")
DQuery(None)
Attempts:
3 left
💡 Hint
Common Mistakes
Using Query instead of Body for body parameters.
Not providing default values for optional parameters.

Practice

(1/5)
1. In FastAPI, how do you accept multiple JSON body parameters in a single endpoint function?
easy
A. Use query parameters instead of body parameters.
B. Use a single parameter with a list of dictionaries.
C. Define multiple function parameters each with a Pydantic model type.
D. Combine all parameters into a single string and parse manually.

Solution

  1. Step 1: Understand FastAPI body parameter handling

    FastAPI reads JSON body parameters by matching function argument names and types, typically Pydantic models.
  2. Step 2: Accept multiple parameters

    By defining multiple function parameters with Pydantic models, FastAPI expects each as a separate JSON object in the request body.
  3. Final Answer:

    Define multiple function parameters each with a Pydantic model type. -> Option C
  4. Quick Check:

    Multiple body parameters = multiple Pydantic model arguments [OK]
Hint: Use separate Pydantic models as function parameters for multiple bodies [OK]
Common Mistakes:
  • Trying to pass multiple JSON objects in one body without models
  • Using query parameters instead of body for complex data
  • Combining all data into one string and parsing manually
2. Which of the following is the correct syntax to declare two body parameters user and item in a FastAPI endpoint?
easy
A. async def endpoint(user: User = Body(), item: Item = Body()):
B. async def endpoint(user: User, item: Item = Query()):
C. async def endpoint(user: User, item: Item):
D. async def endpoint(user: User = Query(), item: Item = Body()):

Solution

  1. Step 1: Understand parameter declaration for multiple bodies

    FastAPI requires explicit use of Body() for multiple body parameters to distinguish them.
  2. Step 2: Check each option

    async def endpoint(user: User = Body(), item: Item = Body()): correctly uses = Body() for both parameters. async def endpoint(user: User, item: Item): misses Body(), so FastAPI treats only the first as body. Options B and D incorrectly mix Query() and Body().
  3. Final Answer:

    async def endpoint(user: User = Body(), item: Item = Body()): -> Option A
  4. Quick Check:

    Multiple bodies require = Body() [OK]
Hint: Use = Body() for each body parameter to avoid errors [OK]
Common Mistakes:
  • Omitting = Body() for multiple body parameters
  • Mixing query and body decorators incorrectly
  • Using default values without Body()
3. Given the following FastAPI endpoint, what will be the response if the client sends JSON body with {"user": {"name": "Alice"}, "item": {"id": 5}}?
from fastapi import FastAPI, Body
from pydantic import BaseModel

app = FastAPI()

class User(BaseModel):
    name: str

class Item(BaseModel):
    id: int

@app.post("/create")
async def create(user: User = Body(), item: Item = Body()):
    return {"user_name": user.name, "item_id": item.id}
medium
A. 500 Internal Server Error
B. 422 Unprocessable Entity error
C. {"user": {"name": "Alice"}, "item": {"id": 5}}
D. {"user_name": "Alice", "item_id": 5}

Solution

  1. Step 1: Understand parameter parsing

    FastAPI matches the JSON keys "user" and "item" to the parameters user and item respectively, parsing each into the corresponding Pydantic model.
  2. Step 2: Check the return statement

    The function returns a dictionary with keys "user_name" and "item_id" extracted from the parsed models, so the response JSON will contain these values.
  3. Final Answer:

    {"user_name": "Alice", "item_id": 5} -> Option D
  4. Quick Check:

    Parsed models return selected fields as response [OK]
Hint: Response keys come from return dict, not original JSON keys [OK]
Common Mistakes:
  • Expecting the entire input JSON as output
  • Confusing 422 error with correct parsing
  • Assuming server error without code issues
4. Identify the error in this FastAPI endpoint that tries to accept two body parameters user and item:
from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()

class User(BaseModel):
    name: str

class Item(BaseModel):
    id: int

@app.post("/add")
async def add(user: User, item: Item):
    return {"user": user, "item": item}
medium
A. Pydantic models cannot be used as parameters.
B. Missing = Body() for multiple body parameters causes validation error.
C. Return statement must convert models to dict before returning.
D. Endpoint must be synchronous, not async.

Solution

  1. Step 1: Check parameter declarations

    When multiple body parameters are declared, each must use = Body() to tell FastAPI to parse them from the body separately.
  2. Step 2: Analyze the return statement

    Returning Pydantic models directly is allowed; FastAPI serializes them automatically, so no error here.
  3. Final Answer:

    Missing = Body() for multiple body parameters causes validation error. -> Option B
  4. Quick Check:

    Multiple bodies require = Body() [OK]
Hint: Add = Body() for each body parameter to fix errors [OK]
Common Mistakes:
  • Omitting = Body() for multiple body parameters
  • Thinking Pydantic models can't be returned directly
  • Confusing async with sync function requirements
5. You want to create a FastAPI endpoint that accepts two body parameters: user with fields name and age, and preferences with optional color and food. Which code correctly defines the endpoint and handles missing optional fields gracefully?
hard
A. class User(BaseModel): name: str age: int class Preferences(BaseModel): color: str | None = None food: str | None = None @app.post("/profile") async def profile(user: User = Body(), preferences: Preferences = Body()): return {"user": user.dict(), "preferences": preferences.dict()}
B. class User(BaseModel): name: str age: int class Preferences(BaseModel): color: str food: str @app.post("/profile") async def profile(user: User, preferences: Preferences): return {"user": user, "preferences": preferences}
C. class User(BaseModel): name: str age: int @app.post("/profile") async def profile(user: User, preferences: dict = Body()): return {"user": user, "preferences": preferences}
D. class User(BaseModel): name: str age: int class Preferences(BaseModel): color: Optional[str] food: Optional[str] @app.post("/profile") async def profile(user: User = Body(), preferences: Preferences = Body()): return {"user": user.dict(), "preferences": preferences.dict()}

Solution

  1. Step 1: Define optional fields correctly

    Using str | None = None sets optional fields with default None, allowing missing keys without error.
  2. Step 2: Declare multiple body parameters with = Body()

    This tells FastAPI to parse both user and preferences from the JSON body separately.
  3. Step 3: Return dict representations for JSON serialization

    Calling .dict() on Pydantic models converts them to plain dicts for clean JSON output.
  4. Final Answer:

    Defines optional fields with `str | None = None`, uses `= Body()` for multiple parameters, and returns `.dict()` representations. -> Option A
  5. Quick Check:

    Optional fields + multiple bodies + dict() return = class User(BaseModel): name: str age: int class Preferences(BaseModel): color: str | None = None food: str | None = None @app.post("/profile") async def profile(user: User = Body(), preferences: Preferences = Body()): return {"user": user.dict(), "preferences": preferences.dict()} [OK]
Hint: Use field: type | None = None for optional fields [OK]
Common Mistakes:
  • Not marking optional fields with default None
  • Omitting = Body() for multiple parameters
  • Returning Pydantic models without converting to dict
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10 questions~5 mineasy hard