Async database queries in FastAPI - Step-by-Step Execution

Concept Flow - Async database queries

Start API request

↓

Call async DB query function

↓

Await DB response

↓

DB processes query asynchronously

↓

Return data to API

↓

Send response to client

↓

End request

This flow shows how an async database query is called and awaited in FastAPI, allowing the server to handle other tasks while waiting for the database.

Execution Sample

FastAPI

from fastapi import FastAPI
from databases import Database

app = FastAPI()
db = Database('sqlite:///test.db')

@app.on_event("startup")
async def startup():
    await db.connect()

@app.on_event("shutdown")
async def shutdown():
    await db.disconnect()

@app.get('/items/{id}')
async def read_item(id: int):
    query = 'SELECT * FROM items WHERE id = :id'
    return await db.fetch_one(query=query, values={'id': id})

This code defines an async FastAPI endpoint that queries a database asynchronously for an item by id.

Execution Table

Step	Action	Awaited?	DB Query Sent	DB Response Received	API Response Sent
1	API receives GET /items/5	No	No	No	No
2	Call read_item(5)	Yes	No	No	No
3	Await db.fetch_one(query, values)	Yes	Yes	No	No
4	DB processes query asynchronously	Yes	Yes	Yes	No
5	Await completes with data	No	Yes	Yes	No
6	Return data from read_item	No	Yes	Yes	Yes
7	API sends response to client	No	Yes	Yes	Yes
8	Request handling complete	No	Yes	Yes	Yes

💡 Request ends after sending API response with data from async DB query.

Variable Tracker

Variable	Start	After Step 3	After Step 5	Final
id	undefined	5	5	5
query	undefined	SELECT * FROM items WHERE id = :id	SELECT * FROM items WHERE id = :id	SELECT * FROM items WHERE id = :id
db_response	undefined	awaiting	{'id': 5, 'name': 'Item 5'}	{'id': 5, 'name': 'Item 5'}
api_response	undefined	undefined	undefined	{'id': 5, 'name': 'Item 5'}

Key Moments - 3 Insights

Why do we use 'await' before the database query?

Because the database query is asynchronous, 'await' pauses the function until the data is ready, as shown in execution_table step 3 and 5.

What happens if we don't use 'await' on the async DB call?

The function would return a coroutine object instead of actual data, so the API response would be incorrect. See step 5 where awaiting completes with data.

Does the server block other requests while waiting for the DB?

No, because the async call allows the server to handle other tasks during the wait, as the DB processes query asynchronously in step 4.

Visual Quiz - 3 Questions

Look at the execution table, at which step is the database query actually sent?

A Step 3

B Step 2

C Step 5

D Step 1

💡 Hint

Check the 'DB Query Sent' column in the execution_table.

According to variable_tracker, what is the value of 'db_response' after step 5?

A 'awaiting'

B {'id': 5, 'name': 'Item 5'}

C undefined

D 5

💡 Hint

Look at the 'db_response' row and 'After Step 5' column in variable_tracker.

If we remove 'await' before db.fetch_one, what will happen to the API response?

A It will cause a syntax error

B It will return the actual data immediately

C It will return a coroutine object, not the data

D It will block the server until data arrives

💡 Hint

Refer to key_moments about the importance of 'await' and execution_table step 5.

Concept Snapshot

Async database queries in FastAPI:
- Use async def for endpoint functions
- Use 'await' to pause until DB query completes
- DB queries run without blocking server
- Return awaited data as API response
- Enables handling many requests efficiently

Full Transcript

This visual execution trace shows how FastAPI handles async database queries. When the API receives a request, it calls an async function that sends a query to the database using 'await'. The server does not block but waits asynchronously for the database to respond. Once the data arrives, the function returns it, and the API sends the response to the client. Variables like 'db_response' change from 'awaiting' to actual data after the await completes. Key points include the necessity of 'await' to get real data and how async queries improve server responsiveness.