# from code_mixed_text_toolkit.preprocessing.tokenizer import word_tokenize

# def freq_dist(corpus, word, tokenize = False, width = 10):
#   """
#     Returns number of instances and list of all instances of the target word in corpus,
#     :param corpus: the corpus in which the target words is to be searched
#     :type corpus: list or str
#     :param word: the target word
#     :type text: str
#     :param tokenize: option to tokenize the corpus or not
#     :type tokenize: bool
#     :param width: number of words/characters in the line
#     :type width: int
#     :return: number of instances and list of all instances of the target word in corpus
#     :rtype: int, list
#   """
#   if(tokenize):
#     if(type(corpus) == list):
#       corpus = ' '.join(corpus)
#       corpus = word_tokenize(corpus)
#     else:
#       corpus = word_tokenize(corpus)

#   instances = 0
#   list_instances = []
#   lwidth = width//2
#   rwidth = width - width//2
#   for i in range(0, len(corpus)):
#     if(word.lower() == corpus[i].lower()):
#       instances += 1
#       list_instances.append(corpus[(i - lwidth) if (i - lwidth) >= 0 else 0 : (i + rwidth) if (i + rwidth) <= len(corpus) else len(corpus)])

#   print("Found " + str(instances) + " instances of " + word + " in corpus.")
#   for i in list_instances:
#     print(' '.join(i))

#   return instances, list_instances