test_extract_dataframe.py

import unittest
import pandas as pd
import sys
import os

sys.path.append(os.path.abspath(os.path.join("../Twitter-Data-Analysis/")))

from extract_dataframe import read_json
from extract_dataframe import TweetDfExtractor
# For unit testing the data reading and processing codes,
# we will need about 5 tweet samples.
# Create a sample not more than 10 tweets and place it in a json file.
# Provide the path to the samples tweets file you created below
# put here the path to where you placed the file e.g. ./sampletweets.json.
sampletweetsjsonfile = "./tests/sample_global.json"
_, tweet_list = read_json(sampletweetsjsonfile)

columns = [
    "created_at",
    "source",
    "original_text",
    "clean_text",
    "sentiment",
    "polarity",
    "subjectivity",
    "lang",
    "favorite_count",
    "retweet_count",
    "original_author",
    "screen_count",
    "followers_count",
    "friends_count",
    "possibly_sensitive",
    "hashtags",
    "user_mentions",
    "place",
    "place_coord_boundaries",
]


class TestTweetDfExtractor(unittest.TestCase):
    """
                A class for unit-testing function in the fix_clean_tweets_dataframe.py file
                Args:
        -----
                        unittest.TestCase this allows the new class to inherit
                        from the unittest module
        """

    def setUp(self) -> pd.DataFrame:
        self.df = TweetDfExtractor(tweet_list[:5])
        # tweet_df = self.df.get_tweet_df()

    def test_find_statuses_count(self):
        self.assertEqual(
            self.df.find_statuses_count(), [8097, 5831, 1627, 1627, 18958]
        )

    def test_find_full_text(self):
        text = [
            "RT @i_ameztoy Extra random image I Lets focus in one very specific zone of the western coast gt Longjing District Taichung #City #Ta",
            "RT @IndoPac_Info #Chinas media explains the military reasons for each area of the drills in the #Taiwan Strait Read the labels in the pi",
            "China even cut off communication they dont anwer phonecalls from the US But here clown @ZelenskyyUa enters the stage to ask #XiJinping to change Putins mind",
            "Putin to #XiJinping I told you my friend Taiwan will be a vassal state including nukes much like the Ukrainian model I warned you But it took Pelosi to open Chinas eyes",
            "RT @ChinaUncensored I’m sorry I thought Taiwan was an independent country because it had its own government currency military travel d"
        ]
        self.assertEqual(self.df.find_clean_text(), text)

    def test_find_sentiments(self):
        self.assertEqual(
            self.df.find_sentiments(self.df.find_full_text()),
            (
                [-0.125, -0.1, 0.0, 0.1, -6.938893903907228e-18],
                [0.190625, 0.1, 0.0, 0.35, 0.55625],
                ['negative', 'negative', 'neutral', 'positive', 'negative']
            ),
        )

    def test_find_screen_name(self):
        name = ['i_ameztoy', 'ZIisq', 'Fin21Free',
                'Fin21Free', 'VizziniDolores']
        self.assertEqual(self.df.find_screen_name(), name)

    def test_find_followers_count(self):
        f_count = [20497, 65, 85, 85, 910]
        self.assertEqual(self.df.find_followers_count(), f_count)

    def test_find_friends_count(self):
        friends_count = [2621, 272, 392, 392, 2608]
        self.assertEqual(self.df.find_friends_count(), friends_count)

    def test_find_is_sensitive(self):
        self.assertEqual(self.df.is_sensitive(), [
                         None, None, None, None, None])

    def test_find_hashtags(self):
        self.assertEqual(self.df.find_hashtags(), ['City++++', 'China++++Taiwan++++', 'XiJinping++++', 'XiJinping++++', ''])

    def test_find_mentions(self):
        self.assertEqual(self.df.find_mentions(), ['i_ameztoy++++', 'IndoPac_Info++++', 'ZelenskyyUa++++', '', 'ChinaUncensored++++'])


if __name__ == "__main__":
    unittest.main()