Skip to content

Instantly share code, notes, and snippets.

@alialavia
Last active July 3, 2018 01:10
Show Gist options
  • Save alialavia/4c7ddc9f9bfc6958d60850887ec21665 to your computer and use it in GitHub Desktop.
Save alialavia/4c7ddc9f9bfc6958d60850887ec21665 to your computer and use it in GitHub Desktop.
"""
To evaluate the good or bad score of a tweet, we count the number of good and
bad words in it.
if a word is good, increase the value of good_words by one
else if a word is bad, increase the value of bad_words by one
if good_words > bad_words then it's a good tweet otherwise it's a bad tweet
"""
tweet_string = "Thanks to the historic TAX CUTS that I signed into law, your paychecks are going way UP, your taxes are going way DOWN, and America is once again OPEN FOR BUSINESS!"
tweet_words = tweet_string.split()
number_of_words = len(tweet_words)
number_of_good_words = 0
number_of_bad_words = 0
good_words = ["Thanks", "historic", "paychecks"]
bad_words = ["taxes"]
# Iterate through the words in the tweet string
for w in tweet_words:
print(w)
if w in good_words:
number_of_good_words += 1 # same as writing number_of_good_words = number_of_good_words + 1
elif w in bad_words:
number_of_bad_words += 1
print ("There are " + str(number_of_good_words) + " good words in this tweet")
print ("There are " + str(number_of_bad_words) + " bad words in this tweet")
if number_of_good_words > number_of_bad_words:
print ("What a presidential thing to say! HUGE!")
else:
print ("Surely you're joking, Mr. Trump! SAD!")
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment