Nrthugu

My script produces data in the following format:

dictionary = {

 (.. 42 values: None, 1 or 2 ..): {

  0: 0.4356, # ints as keys, floats as values

  1: 0.2355,

  2: 0.4352,

  ...

  6: 0.6794

 },

 ...

}

where:

• 
  (.. 42 values: None, 1 or 2 ..) is a game state


• inner dict stores calculated values of actions which are possible in that state

The problem is that the state space is very big (millions of states), so the whole data stucture cannot be stored in memory. That's why I'm looking for a database engine which would fit my needs and I could use with Python. I need to get the list of actions and their values in the given state (previously mentioned tuple of 42 values) and to modify value of given action in given state.

Check out ZODB: http://www.zodb.org/en/latest/

It's natve object DB for Python that supports transactions, caching, pluggable layers, pack operations (for keeping history) and BLOBs.

You can use a key-value cache solution. A good one is Redis. It`s very fast and simple, written on the C and more over than just a key value cache. Integration with python just several lines of code. The redis is also can be scaled very easy for the really big data. I worked in the game industry and understand what I am talking about.

Also, as already mentioned here, you can use more complex solution, not a cache, the database PostgresSQL. Now it supports a JSON binary format field - JSONB. I think the best python database ORM is the SQLAlchemy. It supports PostgresSQL out of the box. I will use this one in my code block. For example, you have a table

class MobTable(db.Model):

    tablename = 'mobs'



    id = db.Column(db.Integer, primary_key=True)

    stats = db.Column(JSONB, index=True, default={})

If your have a mob with such json stats

{

    id: 1,

    title: 'UglyOrk',

    resists: {cold: 13}

}

You can search all mobs with the not null cold resists

expr = MobTable.stats[("resists", "cold")]

q = (session.query(MobTable.id, expr.label("cold_protected"))

    .filter(expr != None)

    .all()) 

I recommend you use HD5f. It's a data base format that works perfectly with Python (it is specifically developed for Python) and stores the data in binary format. This reduces the size of the data to be stored a great extent! More importantly it gives you the ability of random access which I believe serves for your purposes. Also, if you do not use any compression method you will retrieve the data with the highest possible speed.

You can also store it as JSONB in PostgreSQL DB.

For connecting with PostgreSQL you can use psycopg2, which is compliant with Python Database API Specification v2.0.