Lemmatization is the process of converting words (e.g. in a sentence) to their stemming while respecting their context. For example, the sentence “You are not better than me” would become “You be not good than me”. This is useful when dealing with NLP preprocessing, for example to train doc2vec models. The python module nltk.stem contains a class called WordNetLemmatizer. In order to use it, one must provide both the word and its part-of-speech tag (adjective, noun, verb, …) because lemmatization is highly dependent on context. Read More
If you want to calculate a set containing all subsets of set (also called power set) you could either choose an recursive approach or try this iterative approach which is faster than the recursive one.
def get_subsets(fullset): listrep = list(fullset) subsets =  for i in range(2**len(listrep)): subset =  for k in range(len(listrep)): if i & 1<<k: subset.append(listrep[k]) subsets.append(subset) return subsets subsets = get_subsets(set([1,2,3,4])) print(subsets) print(len(subsets))
You can also find a shorter version at the end of the article, but to understand the principle the algorithm above is more suitable.