Lambda expression in Python doesn't work correctly

Question

I tried to make some lambda expressions. There is no any error. But it doesn't work correctly. Following is my code.

from nltk.tokenize import word_tokenize

list1 = 'gain, archive, win, success'.split(',')
list2 = 'miss, loss, gone, give up'.split(',')

def classify(s, rls):
for (f, emotion) in rls:
  if f(s):
     return emotion
return "another"

rules = [(lambda x: (i for i, j in zip(word_tokenize(x),list2) if i == j) != [], "sad"),
         (lambda x: (a for a, b in zip(word_tokenize(x),list1) if a == b) != [], "happy"),]

print classify("I win the game", rules)
print classify("I miss you", rules)

The output is

sad
sad

I have no idea what is the wrong with my code. Can someone help me !

Answer 1

Zip iterates through the lists " in parallel ", so it returns a list of tuples, where the i-th tuple contains the i-th element from each of the argument sequences or iterables. The returned list is truncated in length to the length of the shortest argument sequence. ( source )

So you were trying to check if the i-th word of the sentence matches the i-th sentiment word in the least, which I guess is not what you want. Plus, as noted by @juanpa.arrivillaga, you were checking if a generator was equal to the empty list , which is always True , for the simple reason that a generator is not a list, independently from its content.
What you want is checking if any word in the sentence is in the sentiment list.

Try changing:

lambda x: (i for i, j in zip(word_tokenize(x),list2) if i == j) != []

to:

lambda x: any(word in list2 for word in word_tokenize(x))

So overall you define rules like this:

rules = [(lambda x: any(word in list2 for word in word_tokenize(x)), "sad"),
         (lambda x: any(word in list1 for word in word_tokenize(x)), "happy")]

Also, there are white spaces in the words in sentiment lists that can make the comparison fail. Redefine them as follows:

list1 = 'gain,archive,win,success'.split(',')
list2 = 'miss,loss,gone,give up'.split(',')

Or even better use strip to remove empty spaces from beginning and end of words as general good practice when working with strings.