mongo-profile 0.3

MongoDB profile helper

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.mongoprofile

Class mongoprofile 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:

>>> with mongoprofile(db) as profile:
...     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 profile:
...    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.

mongoprofile.Profile

When your code runs with mongoprofile(db) as profile:, new mongoprofile.Profile instance is created.

The Profile class itself is a subclass of list, so you can handle profile variable appropriately. Moreover, there is an additional .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:

>>> with mongoprofile(db) as profile:
...     profile.mark('insert')
...     db.people.insert(dict(name='John', age=20))
...     db.people.insert(dict(name='Mary', age=30))
...     profile.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 })

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() get the information about the current state of collection.