<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
 def aggregate(self, pipeline, **kwargs):
 """Execute an aggregation pipeline on this collection. The aggregation can be run on a secondary if the client is connected to a replica set and its ``read_preference`` is not :attr:`PRIMARY`. :Parameters: - `pipeline`: a single command or list of aggregation commands - `session` (optional):
 a :class:`~pymongo.client_session.ClientSession`, created with :meth:`~MotorClient.start_session`. - `**kwargs`: send arbitrary parameters to the aggregate command Returns a :class:`MotorCommandCursor` that can be iterated like a cursor from :meth:`find`:: pipeline = [{'$project': {'name': {'$toUpper': '$name'}}}] cursor = collection.aggregate(pipeline) while (yield cursor.fetch_next):
 doc = cursor.next_object() print(doc) In Python 3.5 and newer, aggregation cursors can be iterated elegantly in native coroutines with `async for`:: async def f():
 async for doc in collection.aggregate(pipeline):
 print(doc) :class:`MotorCommandCursor` does not allow the ``explain`` option. To explain MongoDB's query plan for the aggregation, use :meth:`MotorDatabase.command`:: async def f():
 plan = await db.command( 'aggregate', 'COLLECTION-NAME', pipeline=[{'$project': {'x': 1}}], explain=True) print(plan) .. versionchanged:: 1.0 :meth:`aggregate` now **always** returns a cursor. .. versionchanged:: 0.5 :meth:`aggregate` now returns a cursor by default, and the cursor is returned immediately without a ``yield``. See :ref:`aggregation changes in Motor 0.5 <aggregate_changes_0_5>`. .. versionchanged:: 0.2 Added cursor support. .. _aggregate command: http://docs.mongodb.org/manual/applications/aggregation """

        cursor_class = create_class_with_framework(
            AgnosticLatentCommandCursor, self._framework, self.__module__)

        # Latent cursor that will send initial command on first "async for".
        return cursor_class(self, self._async_aggregate, pipeline,
                            **unwrap_kwargs_session(kwargs))