Differences between Motor and PyMongo¶
Important
This page describes using Motor with Tornado. Beginning in version 0.5 Motor can also integrate with asyncio instead of Tornado.
Major differences¶
Connecting to MongoDB¶
Motor provides a single client class, MotorClient
. Unlike PyMongo’s
MongoClient
, Motor’s client class does
not begin connecting in the background when it is instantiated. Instead it
connects on demand, when you first attempt an operation.
Coroutines¶
Motor supports nearly every method PyMongo does, but Motor methods that do network I/O are coroutines. See Tutorial: Using Motor With Tornado.
Threading and forking¶
Multithreading and forking are not supported; Motor is intended to be used in a single-threaded Tornado application. See Tornado’s documentation on running Tornado in production to take advantage of multiple cores.
Minor differences¶
GridFS¶
File-like
PyMongo’s
GridIn
andGridOut
strive to act like Python’s built-in file objects, so they can be passed to many functions that expect files. But the I/O methods ofMotorGridIn
andMotorGridOut
are asynchronous, so they cannot obey the file API and aren’t suitable in the same circumstances as files.Setting properties
In PyMongo, you can set arbitrary attributes on a
GridIn
and they’re stored as metadata on the server, even after theGridIn
is closed:fs = gridfs.GridFSBucket(db) grid_in = fs.open_upload_stream('test_file') grid_in.close() grid_in.my_field = 'my_value' # Sends update to server.
Updating metadata on a
MotorGridIn
is asynchronous, so the API is different:async def f(): fs = motor.motor_tornado.MotorGridFSBucket(db) grid_in = fs.open_upload_stream('test_file') await grid_in.close() # Sends update to server. await grid_in.set('my_field', 'my_value')
See also
is_locked¶
In PyMongo is_locked
is a property of
MongoClient
. Since determining whether the
server has been fsyncLocked requires I/O, Motor has no such convenience method.
The equivalent in Motor is:
result = await client.admin.current_op()
locked = bool(result.get('fsyncLock', None))
system_js¶
PyMongo supports Javascript procedures stored in MongoDB with syntax like:
>>> db.system_js.my_func = 'function(x) { return x * x; }'
>>> db.system_js.my_func(2)
4.0
Motor does not.
Cursor slicing¶
In PyMongo, the following raises an IndexError
if the collection has fewer
than 101 documents:
# Can raise IndexError.
doc = db.collection.find()[100]
In Motor, however, no exception is raised. The query simply has no results:
async def f():
cursor = db.collection.find()[100]
# Iterates zero or one times.
async for doc in cursor:
print(doc)
The difference arises because the PyMongo Cursor
’s
slicing operator blocks until it has queried the MongoDB server, and determines
if a document exists at the desired offset; Motor simply returns a new
MotorCursor
with a skip and limit applied.
Creating a collection¶
There are two ways to create a capped collection using PyMongo:
# Typical:
db.create_collection(
'collection1',
capped=True,
size=1000)
# Unusual:
collection = Collection(
db,
'collection2',
capped=True,
size=1000)
Motor can’t do I/O in a constructor, so the unusual style is prohibited and only the typical style is allowed:
async def f():
await db.create_collection(
'collection1',
capped=True,
size=1000)