Metadata-Version: 1.0
Name: mongo-profile
Version: 0.4.1
Summary: MongoDB profile helper
Home-page: http://github.com/NetAngels/mongo-profile
Author: NetAngels
Author-email: info@netangels.ru
License: BSD License
Description: mongo-profile
        =============
        
        Module **mongoprofile** contains functions and objects to retreive and parse
        the output of MongoDB's ``"db.system.profile.find()"``
        
        To get more information about MongoDB profiling, see
        http://www.mongodb.org/display/DOCS/Database+Profiler
        
        
        mongoprofile.MongoProfiler
        --------------------------
        
        Class `MongoProfiler` is a "with"-wrapper around any set of MongoDB queries.
        Typical usecase contains three steps:
        
        **Step1. Open connection**::
        
            >>> from pymongo import Connection
            >>> db = Connection().test
        
        **Step 2. Execute and profile queries**::
        
            >>> profiler = MongoProfiler(db)
            >>> with profiler:
            ...     db.people.insert(dict(name='John', age=20))
            ...     db.people.insert(dict(name='Mary', age=30))
            ...     db.people.update({'name': 'John'}, {'age': 21})
            ...     db.people.remove({'name': 'Mary'})
            ...     list(db.people.find({'age': {'$gt': 20.0}}))
            ...     db.people.find({'age': {'$gt': 20.0}}).count()
        
        **Step3. Get profile info**
        
        As a result, you will get the more or less comprehensive list of dict
        subclasses, containing all profile information, including parsed "info". Every
        subclass has redefined ``__str__`` method returning the convenient presentation
        of request. See the example below to get the point::
        
            >>> for record in profiler.get_records():
            ...    print str(record)
        
            test> db.people.insert({...})
            test> db.people.insert({...})
            test> db.people.update({ name: "John" }, {...})
            test> db.people.remove({ name: "Mary" })
            test> db.people.find({ $query: { age: { $gt: 20.0 } } })
            test> db.runCommand({ count: "people", query: { age: { $gt: 20.0 } }, fields: null })
        
        A few more facts about record objects worth to be known:
        
        - There is a ``record.short_info()`` method returning the one-line string with
          short information about the query.
        - Every record class is a subclass of dict, and because of that it's possible
          to get a bunch of ordered information using calls such as
          ``record['millis']``, ``record['ts']``, etc.
        
        Markers
        ````````
        
        The ``MongoProfiler`` class has ``.mark(text)`` method. When ``mark`` is
        invoked, mongodb client do the fake query to phony collection just to record
        data in log. After the job has ended, these markers will be available as 
        `'==== text ===='` records.
        
        Having changed previous example, we get something like this.
        
        Commands::
        
        
            >>> profiler = MongoProfiler(db)
            >>> with profiler:
            ...     profiler.mark('insert')
            ...     db.people.insert(dict(name='John', age=20))
            ...     db.people.insert(dict(name='Mary', age=30))
            ...     profiler.mark('search')
            ...     list(db.people.find({'age': {'$gt': 20.0}}))
            ...     db.people.find({'age': {'$gt': 20.0}}).count()
        
        
        Will lead to the output::
        
            '==== insert ===='
            test> db.people.insert({...})
            test> db.people.insert({...})
            '==== search ===='
            test> db.people.find({ $query: { age: { $gt: 20.0 } } })
            test> db.runCommand({ count: "people", query: { age: { $gt: 20.0 } }, fields: null })
        
        DummyMongoProfiler
        -------------------
        
        It is probable that depending on some circumstances, you want or don't want to
        spend extra resources on your query profiling. Stub ``DummyMongoProfiler``
        class mocking ``MongoProfiler`` interface can be used for that purpose. Below
        is the usage sample with `Django-nonrel`_ in mind::
        
            >>> from django.conf import settings
            >>> Profiler = settings.DEBUG and MongoProfiler or DummyMongoProfiler
            >>> profiler = Profiler(db)
            >>> with profiler:
            ...     ModelClass.objects.filter(...)
            ...
        
        .. _Django-nonrel: http://www.allbuttonspressed.com/projects/django-nonrel
        
        Miscellaneous remarks
        ---------------------
        
        Collection `db.system.profile` is capped with a relatively small capacity. If
        you want to profile large amount of records at once, it is worth to extend its
        size. The following set of commands creates capped collection of 100Mb::
        
            > db.setProfilingLevel(0)
            > db.system.profile.drop()
            > db.createCollection("system.profile", {capped:true, size:100*1e6})
        
        Command ``db.system.profile.stats()`` shows you the current state of
        collection.
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Database
