def test_get_filter_results_name_includes(self):
""" Test get_filter_results using the name_includes filter in
filter_dict. """
data_file = open('data.txt', 'r')
twitter_dict = tf.process_data(data_file)
data_file.close()
actual = tf.get_filter_results(twitter_dict, ['tomCruise', \
'PerezHilton'], {'name_includes': 'tomCruise'})
expected = ['tomCruise']
self.assertEqual(actual, expected)
def test_get_filter_results_location_includes(self):
""" Test get_filter_results using the following filter in filter_dict.
"""
data_file = open('data.txt', 'r')
twitter_dict = tf.process_data(data_file)
data_file.close()
actual = tf.get_filter_results(twitter_dict, ['tomCruise', \
'PerezHilton', 'tomfan'], {'follower': 'katieH'})
expected = ['tomCruise', 'PerezHilton']
self.assertEqual(actual, expected)
import twitterverse_functions as tf
import os.path
if __name__ == '__main__':
data_filename = input('Data file: ')
while not os.path.exists(data_filename):
print("That file does not exist.")
data_filename = input('Data file: ')
data_file = open(data_filename, 'r')
data = tf.process_data(data_file)
data_file.close()
query_filename = input('Query file: ')
while not os.path.exists(query_filename):
print("That file does not exist.")
query_filename = input('Query file: ')
query_file = open(query_filename, 'r')
query = tf.process_query(query_file)
query_file.close()
search_results = tf.get_search_results(data, query['search'])
filtered_results = tf.get_filter_results(data, search_results,
query['filter'])
presented_results = tf.get_present_string(data, filtered_results,
query['present'])
print(presented_results, end="")
def disable_open(*args):
raise Exception("You must not call built-in function open!")
builtins.print = disable_print
builtins.input = disable_input
builtins.open = disable_open
import twitterverse_functions
# typecheck the twitterverse_functions.py functions
# Type check twitterverse_functions.process_data
open_data_file = our_open('small_data.txt')
result = twitterverse_functions.process_data(open_data_file)
open_data_file.close()
assert isinstance(result, dict), \
'''process_data should return a dict, but returned {0}''' \
.format(type(result))
for item in result:
assert isinstance(item, str), \
'process_data should return a dict with str keys, ' \
'but returned a dict with {0} keys'\
.format(type(item))
assert isinstance(result[item], dict), \
'process_data should return a dict with dict values, but returned ' \
'a dict with {0} values'\
.format(type(result[item]))
for key in result[item]:
assert isinstance(key, str), \
# Created by Professor/TA to test functions (created by me)
import twitterverse_functions as tf
if __name__ == '__main__':
data_filename = input('Data file: ')
data_file = open(data_filename, 'r')
data = tf.process_data(data_file)
data_file.close()
query_filename = input('Query file: ')
query_file = open(query_filename, 'r')
query = tf.process_query(query_file)
query_file.close()
search_results = tf.get_search_results(data, query['search'])
filtered_results = tf.get_filter_results(data, search_results,
query['filter'])
presented_results = tf.get_present_string(data, filtered_results,
query['present'])
print(presented_results, end="")
import twitterverse_functions as tf
f = open('small_data.txt', 'r')
d = tf.process_data(f)
print(d)
f.close()
usernames = ['tomCruise', 'katieH']
pres_dict = {'sort-by': 'username', 'format': 'long'}
print(tf.get_present_string(d, usernames, pres_dict))