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Here's a little interesting story about using MongoKit to quickly draw items from a MongoDB

So I had a piece of code that was doing a big batch update. It was slow. It took about 0.5 seconds per user and I sometimes had a lot of users to run it for.

The code looked something like this:

 for play in db.PlayedQuestion.find({'user.$id': user._id}):
    if play.winner == user:
         bla()
    elif play.draw:
         ble()
    else:
         blu()

Because the model PlayedQuestion contains DBRefs MongoKit will automatically look them up for every iteration in the main loop. Individually very fast (thank you indexes) but because of the number of operations very slow in total. Here's how to make it much faster:

   for play in db.PlayedQuestion.collection.find({'user.$id': user._id}):

The problem with this is that you get dict instances for each which is more awkward to work with. I.e. instead of `play.winner` you have use `play['winner'].id`. Here's my solution that makes this a lot easier:

class dict_plus(dict):

  def __init__(self, *args, **kwargs):
       if 'collection' in kwargs:  # excess we don't need
           kwargs.pop('collection')
       dict.__init__(self, *args, **kwargs)
       self._wrap_internal_dicts()

   def _wrap_internal_dicts(self):
       for key, value in self.items():
           if isinstance(value, dict):
               self[key] = dict_plus(value)

   def __getattr__(self, key):
       if key.startswith('__'):
           raise AttributeError(key)
       return self[key]

  ...

 for play in db.PlayedQuestion.collection.find({'user.$id': user._id}):
    play = dict_plus(play)
    if play.winner.id == user._id:
         bla()
    elif play.draw:
         ble()
    else:
         blu()

Now, the whole thing takes 0.01 seconds instead of 0.5. 50 times faster!!

Because this took me a long time to figure out I thought I'd share it with people in case other people get stuck on the same problem.

The problem is that Mongoose doesn't support DBRefs. A DBRef is just a little sub structure with a two keys: $ref and $id where $id is an ObjectId instance. Here's what it might look like on the mongodb shell:

> db.questions.findOne();
{
       "_id" : ObjectId("4d64322a6da68156b8000001"),
       "author" : {
               "$ref" : "users",
               "$id" : ObjectId("4d584fb86da681668b000000")
       },
       "text" : "Foo?",
       ...
       "answer" : "Bar"
       "genre" : {
               "$ref" : "question_genres",
               "$id" : ObjectId("4d64322a6da68156b8000000")
       }
}

DBRefs are very convenient because various wrappers on drivers can do automatic cross-fetching based on this. For example, with MongoKit I can do this:

for question in db.Question.find():
   print question.author.first_name

If we didn't have DBRefs you'd have to do this:

for question in db.Question.find():
   author = db.Authors.findOne({'_id': question.author})
   print author.first_name

This is a summary about the MongoUK conference held today here in London. It was great! Unlike other commercial conferences this one actually cost money but it was only about $50 and although there were free coffee cups, stickers and stuff this didn't feel at all like they were trying to sell themselves. The focus was on the technology. Great!

As often with these things, you realise that you have actually grasped a couple of things quite well now but it's also humbling in that there is so much you haven't grasped that other people are way ahead of you in.

What I learned

MongoKit is a Python wrapper on top of pymongo that adds structure and validation and some other bits and pieces. It's like an ORM but not for an SQL database but for a document store like MongoDB. It's a great piece of code because it's thin. It's very careful not to molly cuddle you and your access to the source. What I discovered was that I was doing an advanced query and with the results they we instantiated as class instances and later turned into JSON for the HTTP response. Bad idea. I don't need them to be objects really so with MongoKit it's possible to go straight to the source and that's what I did.

With few very simple changes I managed to make my restful API app almost 10 times faster!!

Read the whole story here

At Euro DjangoCon I met lots of people and talked a lot about MongoDB as the backend. I even did a presentation on the subject which led to a lot of people asking me more questions about MongoDB.

I did mention to some people that one of the drawbacks of using MongoDB which doesn't have transactions is that you have to create and destroy the collections (like SQL tables) each time for every single test runs. I thought this was slow. It's not

Today I've been doing some more profiling and testing and debugging and I can conclude that it's not a problem. Creating the database has a slight delay but it's something you only have to do once and actually it's very fast. Here's how I tear down the collections in between each test:

class BaseTest(TestCase):

   def tearDown(self):
       for name in self.database.collection_names():
           if name not in ('system.indexes',):
               self.database.drop_collection(name)

For example, running test of one of my apps looks like this:

$ ./manage.py test myapp
...........lots.............
----------------------------------------------------------------------
Ran 55 tests in 3.024s

So, don't fear writing lots of individual unit tests. MongoDB will not slow you down.