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.. currentmodule:: motor.motor_asyncio

Tutorial: Using Motor With :mod:`asyncio`

.. testsetup:: before-inserting-2000-docs

  import pymongo
  import motor.motor_asyncio
  import asyncio
  client = motor.motor_asyncio.AsyncIOMotorClient()
  db = client.test_database


.. testsetup:: after-inserting-2000-docs

  import pymongo
  import motor.motor_asyncio
  import asyncio
  client = motor.motor_asyncio.AsyncIOMotorClient()
  db = client.test_database
  pymongo.MongoClient().test_database.test_collection.insert_many(
      [{'i': i} for i in range(2000)])


.. testcleanup:: *

  import pymongo
  pymongo.MongoClient().test_database.test_collection.delete_many({})

A guide to using MongoDB and asyncio with Motor.

Contents

Tutorial Prerequisites

You can learn about MongoDB with the MongoDB Tutorial before you learn Motor.

Using Python 3.5 or later, do:

$ python3 -m pip install motor

This tutorial assumes that a MongoDB instance is running on the default host and port. Assuming you have downloaded and installed MongoDB, you can start it like so:

$ mongod

Object Hierarchy

Motor, like PyMongo, represents data with a 4-level object hierarchy:

Creating a Client

You typically create a single instance of :class:`~motor.motor_asyncio.AsyncIOMotorClient` at the time your application starts up.

>>> import motor.motor_asyncio
>>> client = motor.motor_asyncio.AsyncIOMotorClient()

This connects to a mongod listening on the default host and port. You can specify the host and port like:

>>> client = motor.motor_asyncio.AsyncIOMotorClient('localhost', 27017)

Motor also supports connection URIs:

>>> client = motor.motor_asyncio.AsyncIOMotorClient('mongodb://localhost:27017')

Connect to a replica set like:

>>> client = motor.motor_asyncio.AsyncIOMotorClient('mongodb://host1,host2/?replicaSet=my-replicaset-name')

Getting a Database

A single instance of MongoDB can support multiple independent databases. From an open client, you can get a reference to a particular database with dot-notation or bracket-notation:

>>> db = client.test_database
>>> db = client['test_database']

Creating a reference to a database does no I/O and does not require an await expression.

Getting a Collection

A collection is a group of documents stored in MongoDB, and can be thought of as roughly the equivalent of a table in a relational database. Getting a collection in Motor works the same as getting a database:

>>> collection = db.test_collection
>>> collection = db['test_collection']

Just like getting a reference to a database, getting a reference to a collection does no I/O and doesn't require an await expression.

Inserting a Document

As in PyMongo, Motor represents MongoDB documents with Python dictionaries. To store a document in MongoDB, call :meth:`~AsyncIOMotorCollection.insert_one` in an await expression:

>>> async def do_insert():
...     document = {'key': 'value'}
...     result = await db.test_collection.insert_one(document)
...     print('result %s' % repr(result.inserted_id))
...
>>>
>>> import asyncio
>>> loop = client.get_io_loop()
>>> loop.run_until_complete(do_insert())
result ObjectId('...')
.. mongodoc:: insert


>>> # Clean up from previous insert
>>> pymongo.MongoClient().test_database.test_collection.delete_many({})
<pymongo.results.DeleteResult ...>

Insert documents in large batches with :meth:`~AsyncIOMotorCollection.insert_many`:

>>> async def do_insert():
...     result = await db.test_collection.insert_many(
...         [{'i': i} for i in range(2000)])
...     print('inserted %d docs' % (len(result.inserted_ids),))
...
>>> loop = client.get_io_loop()
>>> loop.run_until_complete(do_insert())
inserted 2000 docs

Getting a Single Document With find_one

Use :meth:`~motor.motor_asyncio.AsyncIOMotorCollection.find_one` to get the first document that matches a query. For example, to get a document where the value for key "i" is less than 1:

>>> async def do_find_one():
...     document = await db.test_collection.find_one({'i': {'$lt': 1}})
...     pprint.pprint(document)
...
>>> loop = client.get_io_loop()
>>> loop.run_until_complete(do_find_one())
{'_id': ObjectId('...'), 'i': 0}

The result is a dictionary matching the one that we inserted previously.

Note

The returned document contains an "_id", which was automatically added on insert.

.. mongodoc:: find

Querying for More Than One Document

Use :meth:`~motor.motor_asyncio.AsyncIOMotorCollection.find` to query for a set of documents. :meth:`~motor.motor_asyncio.AsyncIOMotorCollection.find` does no I/O and does not require an await expression. It merely creates an :class:`~motor.motor_asyncio.AsyncIOMotorCursor` instance. The query is actually executed on the server when you call :meth:`~motor.motor_asyncio.AsyncIOMotorCursor.to_list` or execute an async for loop.

To find all documents with "i" less than 5:

>>> async def do_find():
...     cursor = db.test_collection.find({'i': {'$lt': 5}}).sort('i')
...     for document in await cursor.to_list(length=100):
...         pprint.pprint(document)
...
>>> loop = client.get_io_loop()
>>> loop.run_until_complete(do_find())
{'_id': ObjectId('...'), 'i': 0}
{'_id': ObjectId('...'), 'i': 1}
{'_id': ObjectId('...'), 'i': 2}
{'_id': ObjectId('...'), 'i': 3}
{'_id': ObjectId('...'), 'i': 4}

A length argument is required when you call to_list to prevent Motor from buffering an unlimited number of documents.

async for

You can handle one document at a time in an async for loop:

>>> async def do_find():
...     c = db.test_collection
...     async for document in c.find({'i': {'$lt': 2}}):
...         pprint.pprint(document)
...
>>> loop = client.get_io_loop()
>>> loop.run_until_complete(do_find())
{'_id': ObjectId('...'), 'i': 0}
{'_id': ObjectId('...'), 'i': 1}

You can apply a sort, limit, or skip to a query before you begin iterating:

>>> async def do_find():
...     cursor = db.test_collection.find({'i': {'$lt': 4}})
...     # Modify the query before iterating
...     cursor.sort('i', -1).skip(1).limit(2)
...     async for document in cursor:
...         pprint.pprint(document)
...
>>> loop = client.get_io_loop()
>>> loop.run_until_complete(do_find())
{'_id': ObjectId('...'), 'i': 2}
{'_id': ObjectId('...'), 'i': 1}

The cursor does not actually retrieve each document from the server individually; it gets documents efficiently in large batches.

Counting Documents

Use :meth:`~motor.motor_asyncio.AsyncIOMotorCollection.count_documents` to determine the number of documents in a collection, or the number of documents that match a query:

>>> async def do_count():
...     n = await db.test_collection.count_documents({})
...     print('%s documents in collection' % n)
...     n = await db.test_collection.count_documents({'i': {'$gt': 1000}})
...     print('%s documents where i > 1000' % n)
...
>>> loop = client.get_io_loop()
>>> loop.run_until_complete(do_count())
2000 documents in collection
999 documents where i > 1000

Updating Documents

:meth:`~motor.motor_asyncio.AsyncIOMotorCollection.replace_one` changes a document. It requires two parameters: a query that specifies which document to replace, and a replacement document. The query follows the same syntax as for :meth:`find` or :meth:`find_one`. To replace a document:

>>> async def do_replace():
...     coll = db.test_collection
...     old_document = await coll.find_one({'i': 50})
...     print('found document: %s' % pprint.pformat(old_document))
...     _id = old_document['_id']
...     result = await coll.replace_one({'_id': _id}, {'key': 'value'})
...     print('replaced %s document' % result.modified_count)
...     new_document = await coll.find_one({'_id': _id})
...     print('document is now %s' % pprint.pformat(new_document))
...
>>> loop = client.get_io_loop()
>>> loop.run_until_complete(do_replace())
found document: {'_id': ObjectId('...'), 'i': 50}
replaced 1 document
document is now {'_id': ObjectId('...'), 'key': 'value'}

You can see that :meth:`replace_one` replaced everything in the old document except its _id with the new document.

Use :meth:`~motor.motor_asyncio.AsyncIOMotorCollection.update_one` with MongoDB's modifier operators to update part of a document and leave the rest intact. We'll find the document whose "i" is 51 and use the $set operator to set "key" to "value":

>>> async def do_update():
...     coll = db.test_collection
...     result = await coll.update_one({'i': 51}, {'$set': {'key': 'value'}})
...     print('updated %s document' % result.modified_count)
...     new_document = await coll.find_one({'i': 51})
...     print('document is now %s' % pprint.pformat(new_document))
...
>>> loop = client.get_io_loop()
>>> loop.run_until_complete(do_update())
updated 1 document
document is now {'_id': ObjectId('...'), 'i': 51, 'key': 'value'}

"key" is set to "value" and "i" is still 51.

:meth:`update_one` only affects the first document it finds, you can update all of them with :meth:`update_many`:

await coll.update_many({'i': {'$gt': 100}},
                       {'$set': {'key': 'value'}})

.. mongodoc:: update

Deleting Documents

:meth:`~motor.motor_asyncio.AsyncIOMotorCollection.delete_many` takes a query with the same syntax as :meth:`~motor.motor_asyncio.AsyncIOMotorCollection.find`. :meth:`delete_many` immediately removes all matching documents.

>>> async def do_delete_many():
...     coll = db.test_collection
...     n = await coll.count_documents({})
...     print('%s documents before calling delete_many()' % n)
...     result = await db.test_collection.delete_many({'i': {'$gte': 1000}})
...     print('%s documents after' % (await coll.count_documents({})))
...
>>> loop = client.get_io_loop()
>>> loop.run_until_complete(do_delete_many())
2000 documents before calling delete_many()
1000 documents after
.. mongodoc:: remove

Commands

All operations on MongoDB are implemented internally as commands. Run them using the :meth:`~motor.motor_asyncio.AsyncIOMotorDatabase.command` method on :class:`~motor.motor_asyncio.AsyncIOMotorDatabase`:

.. doctest:: after-inserting-2000-docs

>>> from bson import SON
>>> async def use_distinct_command():
...     response = await db.command(SON([("distinct", "test_collection"),
...                                      ("key", "i")]))
...
>>> loop = client.get_io_loop()
>>> loop.run_until_complete(use_distinct_command())

Since the order of command parameters matters, don't use a Python dict to pass the command's parameters. Instead, make a habit of using :class:`bson.SON`, from the bson module included with PyMongo.

Many commands have special helper methods, such as :meth:`~motor.motor_asyncio.AsyncIOMotorDatabase.create_collection` or :meth:`~motor.motor_asyncio.AsyncIOMotorCollection.aggregate`, but these are just conveniences atop the basic :meth:`command` method.

.. mongodoc:: commands

A Web Application With aiohttp

Let us create a web application using aiohttp, a popular HTTP package for asyncio. Install it with:

python3 -m pip install aiohttp

We are going to make a trivial web site with two pages served from MongoDB. To begin:

.. literalinclude:: examples/aiohttp_example.py
  :language: python3
  :start-after: setup-start
  :end-before: setup-end

The AsyncIOMotorClient constructor does not actually connect to MongoDB. The client connects on demand, when you attempt the first operation. We create it and assign the "test" database's handle to db.

The setup_db coroutine drops the "pages" collection (plainly, this code is for demonstration purposes), then inserts two documents. Each document's page name is its unique id, and the "body" field is a simple HTML page. Finally, setup_db returns the database handle.

We'll use the setup_db coroutine soon. First, we need a request handler that serves pages from the data we stored in MongoDB.

.. literalinclude:: examples/aiohttp_example.py
  :language: python3
  :start-after: handler-start
  :end-before: handler-end

We start the server by running setup_db and passing the database handle to an :class:`aiohttp.web.Application`:

.. literalinclude:: examples/aiohttp_example.py
  :language: python3
  :start-after: main-start
  :end-before: main-end

Note that it is a common mistake to create a new client object for every request; this comes at a dire performance cost. Create the client when your application starts and reuse that one client for the lifetime of the process. You can maintain the client by storing a database handle from the client on your application object, as shown in this example.

Visit localhost:8080/pages/page-one and the server responds "Hello!". At localhost:8080/pages/page-two it responds "Goodbye." At other URLs it returns a 404.

The complete code is in the Motor repository in examples/aiohttp_example.py.

See also the :doc:`examples/aiohttp_gridfs_example`.

Further Reading

The handful of classes and methods introduced here are sufficient for daily tasks. The API documentation for :class:`~motor.motor_asyncio.AsyncIOMotorClient`, :class:`~motor.motor_asyncio.AsyncIOMotorDatabase`, :class:`~motor.motor_asyncio.AsyncIOMotorCollection`, and :class:`~motor.motor_asyncio.AsyncIOMotorCursor` provides a reference to Motor's complete feature set.

Learning to use the MongoDB driver is just the beginning, of course. For in-depth instruction in MongoDB itself, see The MongoDB Manual.