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        "author": "NetAngels",
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        "description": "mongo-profile\n=============\n\nModule **mongoprofile** contains functions and objects to retreive and parse\nthe output of MongoDB's ``\"db.system.profile.find()\"``\n\nTo get more information about MongoDB profiling, see\nhttp://www.mongodb.org/display/DOCS/Database+Profiler\n\n\nmongoprofile.MongoProfiler\n--------------------------\n\nClass `MongoProfiler` is a \"with\"-wrapper around any set of MongoDB queries.\nTypical usecase contains three steps:\n\n**Step1. Open connection**::\n\n    >>> from pymongo import Connection\n    >>> db = Connection().test\n\n**Step 2. Execute and profile queries**::\n\n    >>> profiler = MongoProfiler(db)\n    >>> with profiler:\n    ...     db.people.insert(dict(name='John', age=20))\n    ...     db.people.insert(dict(name='Mary', age=30))\n    ...     db.people.update({'name': 'John'}, {'age': 21})\n    ...     db.people.remove({'name': 'Mary'})\n    ...     list(db.people.find({'age': {'$gt': 20.0}}))\n    ...     db.people.find({'age': {'$gt': 20.0}}).count()\n\n**Step3. Get profile info**\n\nAs a result, you will get the more or less comprehensive list of dict\nsubclasses, containing all profile information, including parsed \"info\". Every\nsubclass has redefined ``__str__`` method returning the convenient presentation\nof request. See the example below to get the point::\n\n    >>> for record in profiler.get_records():\n    ...    print str(record)\n\n    test> db.people.insert({...})\n    test> db.people.insert({...})\n    test> db.people.update({ name: \"John\" }, {...})\n    test> db.people.remove({ name: \"Mary\" })\n    test> db.people.find({ $query: { age: { $gt: 20.0 } } })\n    test> db.runCommand({ count: \"people\", query: { age: { $gt: 20.0 } }, fields: null })\n\nA few more facts about record objects worth to be known:\n\n- There is a ``record.short_info()`` method returning the one-line string with\n  short information about the query.\n- Every record class is a subclass of dict, and because of that it's possible\n  to get a bunch of ordered information using calls such as\n  ``record['millis']``, ``record['ts']``, etc.\n\nMarkers\n````````\n\nThe ``MongoProfiler`` class has ``.mark(text)`` method. When ``mark`` is\ninvoked, mongodb client do the fake query to phony collection just to record\ndata in log. After the job has ended, these markers will be available as \n`'==== text ===='` records.\n\nHaving changed previous example, we get something like this.\n\nCommands::\n\n\n    >>> profiler = MongoProfiler(db)\n    >>> with profiler:\n    ...     profiler.mark('insert')\n    ...     db.people.insert(dict(name='John', age=20))\n    ...     db.people.insert(dict(name='Mary', age=30))\n    ...     profiler.mark('search')\n    ...     list(db.people.find({'age': {'$gt': 20.0}}))\n    ...     db.people.find({'age': {'$gt': 20.0}}).count()\n\n\nWill lead to the output::\n\n    '==== insert ===='\n    test> db.people.insert({...})\n    test> db.people.insert({...})\n    '==== search ===='\n    test> db.people.find({ $query: { age: { $gt: 20.0 } } })\n    test> db.runCommand({ count: \"people\", query: { age: { $gt: 20.0 } }, fields: null })\n\nDummyMongoProfiler\n-------------------\n\nIt is probable that depending on some circumstances, you want or don't want to\nspend extra resources on your query profiling. Stub ``DummyMongoProfiler``\nclass mocking ``MongoProfiler`` interface can be used for that purpose. Below\nis the usage sample with `Django-nonrel`_ in mind::\n\n    >>> from django.conf import settings\n    >>> Profiler = settings.DEBUG and MongoProfiler or DummyMongoProfiler\n    >>> profiler = Profiler(db)\n    >>> with profiler:\n    ...     ModelClass.objects.filter(...)\n    ...\n\n.. _Django-nonrel: http://www.allbuttonspressed.com/projects/django-nonrel\n\nMiscellaneous remarks\n---------------------\n\nCollection `db.system.profile` is capped with a relatively small capacity. If\nyou want to profile large amount of records at once, it is worth to extend its\nsize. The following set of commands creates capped collection of 100Mb::\n\n    > db.setProfilingLevel(0)\n    > db.system.profile.drop()\n    > db.createCollection(\"system.profile\", {capped:true, size:100*1e6})\n\nCommand ``db.system.profile.stats()`` shows you the current state of\ncollection.",
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