Why query parameters filter data in FastAPI - Performance Evidence

Performance: Why query parameters filter data

MEDIUM IMPACT

This affects server response time and network payload size by controlling how much data is sent to the client.

Filtering data on the server before sending to the client

FastAPI

from fastapi import FastAPI, Query
app = FastAPI()

items = [{"id": i, "value": f"Item {i}"} for i in range(1000)]

@app.get("/items")
def read_items(min_id: int = Query(0)):
    filtered = [item for item in items if item["id"] >= min_id]
    return filtered

Filters data on server using query parameter, sending only needed items to client.

📈 Performance GainReduces payload size and response time, improving LCP and user experience.

Filtering data on the server before sending to the client

FastAPI

from fastapi import FastAPI
app = FastAPI()

items = [{"id": i, "value": f"Item {i}"} for i in range(1000)]

@app.get("/items")
def read_items():
    return items

Returns all 1000 items regardless of client needs, causing large payload and slow response.

📉 Performance CostBlocks rendering longer due to large JSON payload; increases LCP by hundreds of milliseconds.

Performance Comparison

Pattern	DOM Operations	Reflows	Paint Cost	Verdict
No filtering (all data sent)	Minimal DOM nodes (depends on client)	0 reflows from server data	High paint cost due to large data	[X] Bad
Server-side filtering with query params	Minimal DOM nodes (only filtered data)	0 reflows from server data	Lower paint cost due to smaller data	[OK] Good

Rendering Pipeline

Query parameters affect the server response size, which impacts network transfer and browser rendering time.

→Network Transfer

→HTML/JSON Parsing

→Rendering

⚠️ BottleneckNetwork Transfer and Parsing large payloads

Core Web Vital Affected

LCP

This affects server response time and network payload size by controlling how much data is sent to the client.

Optimization Tips

1Always filter data on the server using query parameters to reduce payload size.

2Smaller payloads improve network transfer time and browser rendering speed.

3Reducing data sent improves Largest Contentful Paint (LCP) for better user experience.

Performance Quiz - 3 Questions

How do query parameters improve performance when filtering data in FastAPI?

A They increase the server load by sending all data to the client.

B They reduce the amount of data sent over the network by filtering on the server.

C They delay the response by adding extra processing on the client.

D They have no effect on performance.

DevTools: Network

How to check: Open DevTools, go to Network tab, filter for the API request, and inspect the response size and timing.

What to look for: Look for smaller response payload size and faster response time when using query parameters.

Practice

1. What is the main purpose of query parameters in a FastAPI endpoint?

easy

A. To filter or customize the data returned by the API

B. To define the HTTP method used by the endpoint

C. To specify the database connection details

D. To set the server port number

Solution

1. Step 1: Understand what query parameters do

   Query parameters are used to send extra information in the URL to control what data the API returns.

2. Step 2: Identify the purpose in FastAPI

   In FastAPI, query parameters let users filter or customize the response without changing the endpoint itself.

3. Final Answer:

   To filter or customize the data returned by the API -> Option A

4. Quick Check:

   Query parameters = filter/customize data [OK]

Hint: Query parameters control what data you get back [OK]

Common Mistakes:

• Confusing query parameters with HTTP methods
• Thinking query parameters set server or database settings
• Assuming query parameters change endpoint URLs

2. Which of the following is the correct way to declare an optional query parameter named category in FastAPI?

easy

A. def read_items(category: str):

B. def read_items(category: str = None):

C. def read_items(category):

D. def read_items(category: int = 0):

Solution

1. Step 1: Recall how to declare optional query parameters

   In FastAPI, optional query parameters are declared by giving a default value, often None.

2. Step 2: Check the options for correct syntax

   def read_items(category: str = None): uses category: str = None, which means the parameter is optional and of type string.

3. Final Answer:

   def read_items(category: str = None): -> Option B

4. Quick Check:

   Optional query param = default None [OK]

Hint: Optional query params have default values like None [OK]

Common Mistakes:

• Not providing a default value for optional parameters
• Using wrong data types for query parameters
• Omitting type annotations

3. Given this FastAPI endpoint:

from fastapi import FastAPI
app = FastAPI()

items = [
  {"name": "apple", "category": "fruit"},
  {"name": "carrot", "category": "vegetable"}
]

@app.get("/items")
async def read_items(category: str = None):
    if category:
        return [item for item in items if item["category"] == category]
    return items

What will be the output of a GET request to /items?category=fruit?

medium

A. [{"name": "apple", "category": "fruit"}]

B. [{"name": "carrot", "category": "vegetable"}]

C. []

D. [{"name": "apple", "category": "fruit"}, {"name": "carrot", "category": "vegetable"}]

Solution

1. Step 1: Understand the query parameter usage

   The endpoint checks if category is given, then filters items matching that category.

2. Step 2: Apply the filter for category='fruit'

   Only the item with category 'fruit' is the apple, so the returned list contains only that item.

3. Final Answer:

   [{"name": "apple", "category": "fruit"}] -> Option A

4. Quick Check:

   Filter by category 'fruit' returns apple [OK]

Hint: Filter returns only items matching query parameter value [OK]

Common Mistakes:

• Returning all items ignoring the filter
• Returning empty list when filter matches
• Confusing category values

4. Identify the error in this FastAPI endpoint that tries to filter items by a query parameter color:

from fastapi import FastAPI
app = FastAPI()

items = [
  {"name": "shirt", "color": "blue"},
  {"name": "pants", "color": "black"}
]

@app.get("/items")
def read_items(color):
    return [item for item in items if item["color"] == color]

medium

A. The items list is empty

B. The list comprehension syntax is incorrect

C. The endpoint should use POST instead of GET

D. The query parameter 'color' is missing a type annotation and default value

Solution

1. Step 1: Check function parameter declaration

   The parameter 'color' lacks a type annotation and default value, so FastAPI treats it as a required path parameter, causing errors.

2. Step 2: Correct declaration for query parameter

   Adding a type (e.g., str) and a default (e.g., None) makes it an optional query parameter, fixing the error.

3. Final Answer:

   The query parameter 'color' is missing a type annotation and default value -> Option D

4. Quick Check:

   Query params need type and default [OK]

Hint: Query params must have type and default to work [OK]

Common Mistakes:

• Omitting type annotations for query parameters
• Confusing query parameters with path parameters
• Using wrong HTTP methods for filtering

5. You want to create a FastAPI endpoint that returns products filtered by optional query parameters category and max_price. Which code snippet correctly implements this filtering?

hard

A. async def get_products(category: str, max_price: float):
return products

B. async def get_products(category, max_price):
return [p for p in products if p['category'] == category and p['price'] <= max_price]

C. async def get_products(category: str = None, max_price: float = None):
filtered = products
if category:
filtered = [p for p in filtered if p['category'] == category]
if max_price is not None:
filtered = [p for p in filtered if p['price'] <= max_price]
return filtered

D. async def get_products():
return products

Solution

1. Step 1: Understand optional query parameters usage

   Both category and max_price are optional, so they need default values (None) to allow filtering only when provided.

2. Step 2: Check filtering logic

   async def get_products(category: str = None, max_price: float = None): filtered = products if category: filtered = [p for p in filtered if p['category'] == category] if max_price is not None: filtered = [p for p in filtered if p['price'] <= max_price] return filtered filters products step-by-step, applying each filter only if the parameter is given, which is correct and safe.

3. Final Answer:

   async def get_products(category: str = None, max_price: float = None): filtered = products if category: filtered = [p for p in filtered if p['category'] == category] if max_price is not None: filtered = [p for p in filtered if p['price'] <= max_price] return filtered -> Option C

4. Quick Check:

   Optional filters with defaults and conditions = correct [OK]

Hint: Use defaults None and conditionally filter inside function [OK]

Common Mistakes:

• Not providing default values for optional parameters
• Filtering without checking if parameters exist
• Returning unfiltered data ignoring query parameters