def test_single_arg_equal_calls(self):
input_single = ""
input_sequence = [""]
self.assertEqual(fit_transform(input_single),
fit_transform(input_sequence))
def test_single_arg_equal_calls():
input_single = ""
input_sequence = [""]
assert fit_transform(input_single) == fit_transform(
input_sequence
), "same single argument in iterable and as is yields different results"
def test_similar_args():
exp = [
('a', [1]),
('a', [1]),
]
res_args = one_hot_encoder.fit_transform('a', 'a')
res_list = one_hot_encoder.fit_transform(['a', 'a'])
assert exp == res_args
assert exp == res_list
def test_similar_args(self):
exp = [
('a', [1]),
('a', [1]),
]
res_args = one_hot_encoder.fit_transform('a', 'a')
res_list = one_hot_encoder.fit_transform(['a', 'a'])
self.assertEqual(exp, res_args)
self.assertEqual(exp, res_list)
def test_args():
exp = [
('a', [0, 0, 1]),
('b', [0, 1, 0]),
('c', [1, 0, 0]),
]
res_args = one_hot_encoder.fit_transform('a', 'b', 'c')
res_list = one_hot_encoder.fit_transform(['a', 'b', 'c'])
assert exp == res_args
assert exp == res_list
def test_args(self):
exp = [
('a', [0, 0, 1]),
('b', [0, 1, 0]),
('c', [1, 0, 0]),
]
res_args = one_hot_encoder.fit_transform('a', 'b', 'c')
res_list = one_hot_encoder.fit_transform(['a', 'b', 'c'])
self.assertEqual(exp, res_args)
self.assertEqual(exp, res_list)
def test_with_multiple_repeats(self):
test_word = ['first', 'second', 'first', 'second', 'first']
answer_test_words = one_hot_encoder.fit_transform(test_word)
correct_answer = [('first', [0, 1]), ('second', [1, 0]),
('first', [0, 1]), ('second', [1, 0]),
('first', [0, 1])]
self.assertEqual(correct_answer, answer_test_words)
def test_sequential_numeration(self):
input_sequence = list("abcd")
actual = [t[1] for t in fit_transform(input_sequence)]
self.assertIn([0, 0, 1, 0], actual)
self.assertNotIn([1, 0, 0, 0, 0], actual)
def test_one_city():
cities = ['Moscow']
actual = one_hot_encoder.fit_transform(cities)
expected = [
('Moscow', [1]),
]
assert actual == expected
def test_arg():
input = one_hot_encoder.fit_transform(['N', 'o'])
res = [
('N', [0, 1]),
('o', [1, 0]),
]
assert input == res
def test_ok_repeated_liberty():
cities = {'Liberty', 'Liberty', 'Liberty'}
actual = one_hot_encoder.fit_transform(cities)
expected = [
('Liberty', [1]),
]
assert actual == expected
def test_str():
"""Аргумент функции - строки."""
assert fit_transform("a", "b", "c") == [
("a", [0, 0, 1]),
("b", [0, 1, 0]),
("c", [1, 0, 0]),
]
def test_simple_list():
test_list = ['abc', 'bca', 'abc']
actual = fit_transform(test_list)
expected = [('abc', [0, 1]),
('bca', [1, 0]),
('abc', [0, 1])]
assert actual == expected
def test_list():
"""Аргумент функции - список."""
assert fit_transform(["a", "b", "c"]) == [
("a", [0, 0, 1]),
("b", [0, 1, 0]),
("c", [1, 0, 0]),
]
def test_with_one_repeat():
test_words = ['first', 'second', 'first', 'third', 'fourth']
answer_test_words = one_hot_encoder.fit_transform(test_words)
correct_answer = [('first', [0, 0, 0, 1]), ('second', [0, 0, 1, 0]),
('first', [0, 0, 0, 1]), ('third', [0, 1, 0, 0]),
('fourth', [1, 0, 0, 0])]
assert answer_test_words == correct_answer
def test_list_str():
assert fit_transform(['Moscow', 'New York', 'Moscow', 'London']) == [
('Moscow', [0, 0, 1]),
('New York', [0, 1, 0]),
('Moscow', [0, 0, 1]),
('London', [1, 0, 0]),
]
def test_single_repeated():
expected = [("8", [1]), ("8", [1]), ("8", [1])]
input_sequence = ["8"] * 3
actual = fit_transform(input_sequence)
assert (expected == actual
), "multiple entrances of same string give different encodings"
def test_ok_for_sequence_without_copy():
cities = ['Moscow', 'Liberty']
actual = one_hot_encoder.fit_transform(cities)
expected = [
('Moscow', [0, 1]),
('Liberty', [1, 0]),
]
assert actual == expected
def test_args_str():
"""Тест поведения функции, если входные аргументы - строки."""
assert fit_transform('Moscow', 'New York', 'Moscow', 'London') == [
('Moscow', [0, 0, 1]),
('New York', [0, 1, 0]),
('Moscow', [0, 0, 1]),
('London', [1, 0, 0]),
]
def test_list_int():
"""Тест поведения функции, если входной аргумент - list[int]."""
assert fit_transform([1, 2, 3, 3]) == [
(1, [0, 0, 1]),
(2, [0, 1, 0]),
(3, [1, 0, 0]),
(3, [1, 0, 0]),
]
def test_ok_two_same_cities(self):
cities = ['Moscow', 'Moscow']
actual = one_hot_encoder.fit_transform(cities)
expected = [
('Moscow', [1]),
('Moscow', [1]),
]
self.assertEqual(actual, expected)
def test_pytest_cities_without_copy():
cities = ['Moscow', 'New York', 'Moscow']
expected = [
('Moscow', [0, 1]),
('New York', [1, 0]),
('Moscow', [0, 1]),
]
assert one_hot_encoder.fit_transform(cities) == expected
def test_unique_city():
cities = ['Moscow', 'New York']
actual = one_hot_encoder.fit_transform(cities)
expected = [
('Moscow', [0, 1]),
('New York', [1, 0]),
]
assert actual == expected
def test_ok_two_diff_cities():
cities = ['Moscow', 'Perm']
actual = one_hot_encoder.fit_transform(cities)
expected = [
('Moscow', [0, 1]),
('Perm', [1, 0]),
]
assert actual == expected
def test_with_one_repeat(self):
test_words = ['first', 'second', 'first', 'third', 'fourth']
answer_test_words = one_hot_encoder.fit_transform(test_words)
correct_answer = [('first', [0, 0, 0, 1]), ('second', [0, 0, 1, 0]),
('first', [0, 0, 0, 1]), ('third', [0, 1, 0, 0]),
('fourth', [1, 0, 0, 0])]
self.assertIn(correct_answer[2], answer_test_words)
self.assertEqual(correct_answer, answer_test_words)
def test_list_float():
"""Тест поведения функции, если входные аргументы типа float."""
assert fit_transform([1.0, 2.5, 3.3, 3.7]) == [
(1.0, [0, 0, 0, 1]),
(2.5, [0, 0, 1, 0]),
(3.3, [0, 1, 0, 0]),
(3.7, [1, 0, 0, 0]),
]
def test_wrong_str(self):
cities = 'ab'
exp_transformed_cities = [
('a', [0, 1]),
('b', [0, 1]),
]
transformed_cities = fit_transform(*cities)
self.assertNotEqual(transformed_cities, exp_transformed_cities)
def test_wrong_str():
cities = 'ab'
exp_transformed_cities = [
('a', [0, 1]),
('b', [0, 1]),
]
transformed_cities = fit_transform(*cities)
assert transformed_cities != exp_transformed_cities
def test_list_str():
"""Тест поведения функции, если входным аргументом является список."""
assert fit_transform(['Moscow', 'New York', 'Moscow', 'London']) == [
('Moscow', [0, 0, 1]),
('New York', [0, 1, 0]),
('Moscow', [0, 0, 1]),
('London', [1, 0, 0]),
]
def test_ok_two_diff_cities(self):
cities = ['Moscow', 'Perm']
actual = one_hot_encoder.fit_transform(cities)
expected = [
('Moscow', [0, 1]),
('Perm', [1, 0]),
]
self.assertEqual(actual, expected)