def counter_on_all_words(self):
with tempfile.TemporaryFile() as tmpfile:
# Clean each tweet and write it out to the temporary file, with
# a trailing newline
for tweet in self.tweet_iterable:
for word in utils.clean_tweet(tweet).split(" "):
tmpfile.write(word + "\n")
# Make sure that the file is at the beginning and then create a
# Counter from it to get the unique items
tmpfile.seek(0)
count_container = Counter(tmpfile.read().splitlines())
sorted_count_dictionary = OrderedDict(sorted(count_container.items(),
key=itemgetter(0)))
return sorted_count_dictionary.items()
def count_unique(self):
"""
This is the function documentation
"""
count_container = Counter()
for tweet in self.tweet_iterable:
# Encapsulte tweet in string call and return strip to
# escape any strange characters
count_container = count_container + \
Counter(utils.clean_tweet(tweet).split(" "))
sorted_count_dictionary = OrderedDict(sorted(count_container.items(),
key=itemgetter(0)))
# Remove edge cases of blank string or space string
sorted_count_dictionary.pop(' ', None)
sorted_count_dictionary.pop('', None)
return sorted_count_dictionary
def populate_median_list(self):
for dirty_tweet in self.tweet_iterable:
tweet = utils.clean_tweet(dirty_tweet)
self.append_to_unique_word_list(tweet)
current_number_of_tweets = len(self.num_unique_words_sorted)
# Condition if odd amount
if current_number_of_tweets % 2:
index = current_number_of_tweets / 2
self.median_list.append(self.num_unique_words_sorted[index])
# Condition if even amount
else:
left_index = (current_number_of_tweets / 2) - 1
right_index = current_number_of_tweets / 2
average_of_medians = self.format_to_two_decimal(
(self.num_unique_words_sorted[left_index] +
self.num_unique_words_sorted[right_index]) / 2.0)
self.median_list.append(average_of_medians)
return self.median_list
