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>>> from pymongo import MongoClient
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>>> db = MongoClient().aggregation_example
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>>> db.things.insert({"x": 1, "tags": ["dog", "cat"]})
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>>> db.things.insert({"x": 2, "tags": ["cat"]})
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>>> db.things.insert({"x": 2, "tags": ["mouse", "cat", "dog"]})
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>>> db.things.insert({"x": 3, "tags": []})
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>>> result = db.things.insert_many([{"x": 1, "tags": ["dog", "cat"]},
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... {"x": 2, "tags": ["cat"]},
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... {"x": 2, "tags": ["mouse", "cat", "dog"]},
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... {"x": 3, "tags": []}])
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>>> result.inserted_ids
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[ObjectId('...'), ObjectId('...'), ObjectId('...'), ObjectId('...')]
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.. _aggregate-examples:
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Aggregation Framework
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---------------------
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aggregate requires server version **>= 2.1.0**. The PyMongo
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:meth:`~pymongo.collection.Collection.aggregate` helper requires
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PyMongo version **>= 2.3**.
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aggregate requires server version **>= 2.1.0**.
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>>> from bson.son import SON
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>>> db.things.aggregate([
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... {"$unwind": "$tags"},
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... {"$group": {"_id": "$tags", "count": {"$sum": 1}}},
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... {"$sort": SON([("count", -1), ("_id", -1)])}
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{u'ok': 1.0, u'result': [{u'count': 3, u'_id': u'cat'}, {u'count': 2, u'_id': u'dog'}, {u'count': 1, u'_id': u'mouse'}]}
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... {"$unwind": "$tags"},
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... {"$group": {"_id": "$tags", "count": {"$sum": 1}}},
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... {"$sort": SON([("count", -1), ("_id", -1)])}
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>>> list(db.things.aggregate(pipeline))
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[{u'count': 3, u'_id': u'cat'}, {u'count': 2, u'_id': u'dog'}, {u'count': 1, u'_id': u'mouse'}]
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To run an explain plan for this aggregation use the
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:meth:`~pymongo.database.Database.command` method::
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>>> db.command('aggregate', 'things', pipeline=pipeline, explain=True)
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{u'ok': 1.0, u'stages': [...]}
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As well as simple aggregations the aggregation framework provides projection
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capabilities to reshape the returned data. Using projections and aggregation,
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Another option for aggregation is to use the map reduce framework. Here we
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will define **map** and **reduce** functions to also count he number of
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will define **map** and **reduce** functions to also count the number of
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occurrences for each tag in the ``tags`` array, across the entire collection.
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Our **map** function just emits a single `(key, 1)` pair for each tag in
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.. note:: Doesn't work with sharded MongoDB configurations, use aggregation or
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map/reduce instead of group().
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Here we are doing a simple group and count of the occurrences ``x`` values:
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Here we are doing a simple group and count of the occurrences of ``x`` values:
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>>> from bson.code import Code
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>>> reducer = Code("""
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... function(obj, prev){
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... prev.count++;
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>>> from bson.son import SON
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>>> results = db.things.group(key={"x":1}, condition={}, initial={"count": 0}, reduce=reducer)
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>>> for doc in results:
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doc/examples/aggregation.rst
