Category Encoder - fit partial

CategoryEncoder.py

from collections.abc import Iterable

class CategoryEncoder(object):
    """
    Once fit method is called, sklearn.preprocessing.LabelEncoder cannot encode new categories. 
    In this category encoder, fit can be called any number times. It encodes categories which it has not seen before,
    without changing the encoding of existing categories. 
    
    Usually the first category has encoded value of zero. We can override it with value 'start'
    """
    mapping = {}
    start = 0
    
    def __init__(self, start=0):
        self.start = start
        
    def fit(self, l):
        if not isinstance(l, Iterable):
            l = [l]
        for o in l:
            if o not in self.mapping.keys():
                self.mapping[o] = len(self.mapping.keys()) + self.start
        return self
                
    def transform(self, l):
        if isinstance(l, Iterable):
            return [self.mapping.get(o,-1) for o in l]
        else:
            return self.mapping.get(l,-1)
    
    def fit_transform(self,l):
        self.fit(l)
        return self.transform(l)