(mongopy)

a simple memory store for storing schemaless data (taking cues from MongoDB)

TODO

I'm going to mirror the api of MongoDB, except maintain internal python data structures to store the data in memory. I forsee adding a disk option that is dynamic and models MongoDB even more by offering (safe=True) for editing data. I would like to use asyncronous jobs to write to disk when times are convenient, but give overrideable access to the user.

Description

Anyone even considering this package is going to already enjoy MongoDB and the coders at 10gen.com. I really enjoy it too, but sometimes I just need a better storage system for quick, fast access to things I don't necessarily want to write to disk.

That will be a typical use for this application. Someone who wants to have a memory solution that's quick to instantiate and has the beginnings of a beautiful interface that is modeled after MongoDB.

Usage

Instantiation:

>>> from mongopy import MongoPy
>>> db = MongoPy()

Inserting:

>>> db.insert({'name': 'David', 'level': 6})
u'8491991710235950406'
>>> db.insert({'name': 'Goliath', 'level': 0})
u'15400048366191294602'

Finding:

>>> db.find()
[{'_id': u'8491991710235950406', 'name': 'David', 'level': 6}, {'_id': u'15400048366191294602', 'name': 'Goliath', 'level': 0}]
>>> db.find_one({'_id': '8491991710235950406'})
{'_id': u'8491991710235950406', 'name': 'David', 'level': 6}
>>> db.find_one({'_id': '15400048366191294602'})
{'_id': u'15400048366191294602', 'name': 'Goliath', 'level': 0}

>>> db.find({'level': {'$in': [0,1,2,3]}})
[{'_id': u'15400048366191294602', 'name': 'Goliath', 'level': 0}]
>>> db.find({'level': {'$lte': [7]}})
[{'_id': u'8491991710235950406', 'name': 'David', 'level': 6}, {'_id': u'15400048366191294602', 'name': 'Goliath', 'level': 0}]
>>> db.find_one({'level': {'$gt': 4}})
{'_id': u'8491991710235950406', 'name': 'David', 'level': 6}

Updating:

>>> db.update({'name': 'David'}, {'level': {'$inc': 1}})
>>> db.update({'_id': u'15400048366191294602'}, {'level': {'$unset': 1}})
>>> db.find()
[{'_id': u'8491991710235950406', 'name': 'David', 'level': 7}, {'_id': u'15400048366191294602', 'name': 'Goliath'}]

Deleting:

>>> db.delete({'name': 'Goliath'})
1
>>> db.find_one({'name': 'Goliath'})
>>>

Basic Indexing:

>>> db.ensure_index('name')
True
>>> db._indexes['name']
{'Goliath': {'_id': u'7220570962932597029', 'name': 'Goliath', 'level': 0}, 'David': {'_id': u'12745564493724871612', 'name': 'David', 'level': 6}}