3. bag.py

# importing regex and nltk
import re, nltk
from nltk.corpus import stopwords
from nltk.tokenize import word_tokenize
from nltk.stem import WordNetLemmatizer
# importing Counter to get word counts for bag of words
from collections import Counter
# importing a passage from Through the Looking Glass
from looking_glass import looking_glass_text
# importing part-of-speech function for lemmatization
from part_of_speech import get_part_of_speech

# Change text to another string:
text = "I just doing math today"

cleaned = re.sub('\W+', ' ', text).lower()
tokenized = word_tokenize(cleaned)

stop_words = stopwords.words('english')
filtered = [word for word in tokenized if word not in stop_words]

normalizer = WordNetLemmatizer()
normalized = [normalizer.lemmatize(token, get_part_of_speech(token)) for token in filtered]
# Comment out the print statement below
# print(normalized)

# Define bag_of_looking_glass_words & print:
bag_of_looking_glass_words = Counter(normalized)
print(bag_of_looking_glass_words)