NLP | Storing Conditional Frequency Distribution in Redis

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The nltk.probability.ConditionalFreqDist class is a container for FreqDist instances, with one FreqDist per condition. It is used to count frequencies that are dependent on another condition, such as another word or a class label. It is being used here to create an API-compatible class on top of Redis using the RedisHashFreqDist .
In the code given below, a RedisConditionalHashFreqDist class that extends nltk.probability.ConditionalFreqDist and overrides the __getitem__() method. Override __getitem__() so as to create an instance of RedisHashFreqDist instead of a FreqDist.

Code :

from nltk.probability import ConditionalFreqDist 
from rediscollections import encode_key 
  
class RedisConditionalHashFreqDist(ConditionalFreqDist): 
    def __init__(self, r, name, cond_samples = None): 
        self._r = r 
        self._name = name 
        ConditionalFreqDist.__init__(self, cond_samples) 
          
        for key in self._r.keys(encode_key('% s:*' % name)): 
            condition = key.split(':')[1] 
            # calls self.__getitem__(condition) 
            self[condition]  
              
    def __getitem__(self, condition): 
        if condition not in self._fdists: 
            key = '% s:% s' % (self._name, condition) 
            val = RedisHashFreqDist(self._r, key) 
            super(RedisConditionalHashFreqDist, self).__setitem__( 
                    condition, val) 
        return super( 
                RedisConditionalHashFreqDist, self).__getitem__(condition) 
    def clear(self): 
        for fdist in self.values(): 
            fdist.clear() 

An instance of this class can be created by passing in a Redis connection and a base name. After that, it works just like a ConditionalFreqDist as shown in the code below :
Code :

from redis import Redis 
from redisprob import RedisConditionalHashFreqDist 
  
r = Redis() 
rchfd = RedisConditionalHashFreqDist(r, 'condhash') 
  
print (rchfd.N()) 
  
print (rchfd.conditions()) 
  
rchfd['cond1']['foo'] += 1
  
print (rchfd.N()) 
  
print (rchfd['cond1']['foo']) 
  
print (rchfd.conditions()) 
  
rchfd.clear()

Output :

0
[]
1
1
['cond1']

How it works ?

The RedisConditionalHashFreqDist uses name prefixes to reference RedisHashFreqDist instances.
The name passed into the RedisConditionalHashFreqDist is a base name that is combined with each condition to create a unique name for each RedisHashFreqDist.
For example, if the base name of the RedisConditionalHashFreqDist is ‘condhash’, and the condition is ‘cond1’, then the final name for the RedisHashFreqDist is ‘condhash:cond1’.
This naming pattern is used at initialization to find all the existing hash maps using the keys command.
By searching for all keys matching ‘condhash:*’, user can identify all the existing conditions and create an instance of RedisHashFreqDist for each.
Combining strings with colons is a common naming convention for Redis keys as a way to define namespaces.
Each RedisConditionalHashFreqDist instance defines a single namespace of hash maps.

RedisConditionalHashFreqDist also defines a clear() method. This is a helper method that calls clear() on all the internal RedisHashFreqDist instances. The clear() method is not defined in ConditionalFreqDist.