Acceso asíncrono a MongoDB con Motor
Conecte FastAPI a MongoDB mediante el driver asíncrono Motor y gestione el ciclo de vida de las conexiones durante el lifespan de la aplicación.
Acceso asíncrono a MongoDB con Motor es una lección gratuita de FastAPI Backend Development Bootcamp en CoddyKit. Esta es la lección 1 de 4. Puedes leer la lección completa abajo gratuitamente — luego la practicas en el navegador con un editor de código integrado y un tutor de IA 24/7. Forma parte de la ruta de aprendizaje de FastAPI Backend Development Bootcamp, y tu progreso se sincroniza en la web y la app de CoddyKit. El curso de FastAPI Backend Development Bootcamp incluye 4 lecciones en total.
Partes de esta lección aún no han sido traducidas y se muestran en inglés.
Why Motor for Async MongoDB
FastAPI is an async framework. If you talk to MongoDB with a blocking driver like pymongo, every database call freezes the event loop and kills concurrency.
Motor is MongoDB's official async driver. It wraps PyMongo and exposes coroutine-based methods you can await, so the event loop stays free to handle other requests while a query is in flight.
motor.motor_asyncio.AsyncIOMotorClient— the async client.- Every I/O call (
find_one,insert_one, ...) returns an awaitable. - Higher-level ODMs like Beanie are built on top of Motor.
Installing the Driver
Install Motor and its peer dependency. Motor pulls in a compatible PyMongo automatically.
motor— async driver.fastapianduvicorn— the web layer.
For Beanie integration later you would also add beanie, but Motor alone is enough to read and write documents directly.
pip install motor fastapi uvicorn
# motor brings in a compatible pymongo wheel
# verify the install
python -c "import motor; print(motor.version)"Creating an Async Client
You create a single AsyncIOMotorClient for the whole application. The client manages an internal connection pool, so you should never create a new client per request.
Indexing into the client gives you a database, and indexing into that gives you a collection. None of this opens a socket yet — connections are established lazily on the first real operation.
from motor.motor_asyncio import AsyncIOMotorClient
client = AsyncIOMotorClient("mongodb://localhost:27017")
database = client["shop"]
products = database["products"]
# Equivalent attribute-style access
# database = client.shop
# products = database.productsAwaiting Your First Query
Because every Motor I/O method is a coroutine, you must await it inside an async function. Forgetting await returns an unresolved coroutine object, not your data.
insert_one returns an InsertOneResult whose inserted_id is the generated ObjectId. find_one returns the matching document as a plain dict, or None.
import asyncio
from motor.motor_asyncio import AsyncIOMotorClient
async def main():
client = AsyncIOMotorClient("mongodb://localhost:27017")
products = client["shop"]["products"]
result = await products.insert_one({"name": "Keyboard", "price": 49})
print("inserted id:", result.inserted_id)
doc = await products.find_one({"name": "Keyboard"})
print(doc)
asyncio.run(main())The Connection Lifecycle Problem
Where should the client live? Options that look tempting but are wrong:
- A new client inside each route — exhausts connections and is slow.
- A module-level client created at import time — connects before the app is ready and is hard to close cleanly.
The right place is the app's lifespan: open the client when the server starts, store it, and close it when the server shuts down. This guarantees one pooled client per process and a clean teardown.
The Lifespan Context Manager
Modern FastAPI uses an async context manager passed as lifespan. Code before yield runs on startup; code after yield runs on shutdown.
Store shared resources on app.state so any route can reach them. Calling client.close() on shutdown returns pooled sockets to the OS gracefully.
from contextlib import asynccontextmanager
from fastapi import FastAPI
from motor.motor_asyncio import AsyncIOMotorClient
@asynccontextmanager
async def lifespan(app: FastAPI):
app.state.mongo = AsyncIOMotorClient("mongodb://localhost:27017")
app.state.db = app.state.mongo["shop"]
yield
app.state.mongo.close()
app = FastAPI(lifespan=lifespan)Verifying the Connection on Startup
The client connects lazily, so a wrong host won't fail until the first query. To fail fast at boot, send a lightweight ping command during startup.
If the ping raises, the server crashes immediately with a clear error instead of silently serving 500s later.
from contextlib import asynccontextmanager
from fastapi import FastAPI
from motor.motor_asyncio import AsyncIOMotorClient
@asynccontextmanager
async def lifespan(app: FastAPI):
client = AsyncIOMotorClient("mongodb://localhost:27017")
await client.admin.command("ping") # raises if unreachable
app.state.db = client["shop"]
app.state.mongo = client
yield
client.close()
app = FastAPI(lifespan=lifespan)Injecting the Database into Routes
Reaching into request.app.state directly works but couples routes to global state. A cleaner pattern is a small dependency that returns the database handle.
This keeps routes testable — in tests you can override the dependency to point at a throwaway database.
from fastapi import Depends, Request
from motor.motor_asyncio import AsyncIOMotorDatabase
def get_db(request: Request) -> AsyncIOMotorDatabase:
return request.app.state.db
@app.get("/products/{name}")
async def get_product(name: str, db: AsyncIOMotorDatabase = Depends(get_db)):
doc = await db["products"].find_one({"name": name})
return doc or {"error": "not found"}Serializing the ObjectId
MongoDB documents carry an _id field of type ObjectId, which is not JSON serializable. Returning a raw document from a route triggers a serialization error.
Convert _id to a string before returning, or map it into a Pydantic model. A simple helper keeps your routes clean.
def serialize(doc: dict) -> dict:
if doc and "_id" in doc:
doc["id"] = str(doc["_id"])
del doc["_id"]
return doc
# Usage inside a route:
# raw = await db["products"].find_one({"name": name})
# return serialize(raw)
print(serialize({"_id": "507f1f77bcf86cd799439011", "name": "Mouse"}))Iterating Cursors Asynchronously
find() returns an async cursor, not a list. You consume it with async for, or materialize it with to_list().
await cursor.to_list(length=100)— load up to 100 docs at once.async for doc in cursor:— stream documents one at a time, ideal for large result sets.
from fastapi import Depends
from motor.motor_asyncio import AsyncIOMotorDatabase
@app.get("/products")
async def list_products(db: AsyncIOMotorDatabase = Depends(get_db)):
cursor = db["products"].find({"price": {"$lt": 100}})
return await cursor.to_list(length=50)
# Streaming alternative:
# async for doc in cursor:
# process(doc)Configuring the Pool and Timeouts
The client constructor accepts tuning options. Read them from environment variables so the same code works across dev and production.
maxPoolSize— cap on concurrent connections.serverSelectionTimeoutMS— how long to wait before declaring the server unreachable.
Loading the URI from the environment also keeps credentials out of source control.
import os
from motor.motor_asyncio import AsyncIOMotorClient
def make_client() -> AsyncIOMotorClient:
uri = os.environ.get("MONGODB_URI", "mongodb://localhost:27017")
return AsyncIOMotorClient(
uri,
maxPoolSize=20,
serverSelectionTimeoutMS=5000,
)Quick Check
Where should the AsyncIOMotorClient be created and destroyed in a FastAPI app?
Recap
You connected FastAPI to MongoDB with the async Motor driver:
- Motor exposes awaitable methods so MongoDB I/O never blocks the event loop.
- Create one
AsyncIOMotorClientper process — it owns a connection pool. - Open and close the client in the lifespan context manager, and
pingon startup to fail fast. - Expose the database through a
Dependsdependency for clean, testable routes. - Convert
_id(anObjectId) to a string before returning JSON. - Consume
find()cursors withto_list()orasync for, and tunemaxPoolSizeand timeouts from environment variables.
This Motor foundation is exactly what Beanie builds on next.
Preguntas frecuentes
¿La lección «Acceso asíncrono a MongoDB con Motor» es gratis?
Sí — el texto completo de «Acceso asíncrono a MongoDB con Motor» es gratis para leer aquí en la web. Para practicarla de forma interactiva (editor de código integrado y tutor de IA 24/7) y desbloquear el resto del curso de FastAPI Backend Development Bootcamp, actualiza a CoddyKit PRO. El curso de FastAPI Backend Development Bootcamp incluye 4 lecciones en total.
¿Qué aprenderé en «Acceso asíncrono a MongoDB con Motor»?
Conecte FastAPI a MongoDB mediante el driver asíncrono Motor y gestione el ciclo de vida de las conexiones durante el lifespan de la aplicación. Practicas FastAPI Backend Development Bootcamp con código real que ejecutas directamente en el navegador, y un tutor de IA 24/7 responde tus preguntas mientras trabajas en la lección.
¿Necesito experiencia previa para empezar FastAPI Backend Development Bootcamp?
No se requiere experiencia previa. FastAPI Backend Development Bootcamp en CoddyKit está estructurado para principiantes hasta estudiantes avanzados, así que puedes empezar aquí o desde el inicio y avanzar a tu ritmo. Esta es la lección 1 de 4.
¿Cuánto tiempo toma la lección «Acceso asíncrono a MongoDB con Motor»?
La mayoría de las lecciones de CoddyKit toman alrededor de 5–10 minutos. Cada una es compacta e interactiva, así que avanzas constantemente y retomas exactamente por donde dejaste en la web y la app.
¿Puedo escribir y ejecutar código en esta lección de FastAPI Backend Development Bootcamp?
Sí. Cada lección de FastAPI Backend Development Bootcamp incluye un editor de código integrado, así que escribes y ejecutas código real directamente en tu navegador y obtienes retroalimentación instantánea de IA — sin configuración local necesaria.
Todas las lecciones de este curso
- Acceso asíncrono a MongoDB con Motor
- Modelado de documentos con el ODM Beanie
- Pipelines de agregación y consultas complejas
- Evolución de esquemas y migraciones de documentos