Esempi in Python per execute_task_2

Esempio n. 1

File: task_2_test.py Progetto: bgrana/sports_popularity_pipeline

def test_product_type():
    df = pd.DataFrame([['0', '10:00:00', 'dev1', 1234, '1', 'DE', 'program1', 'S1', 'E1', 'horror', 'svod'], \
        ['0', '10:00:00', 'dev2', 1234, '1', 'DE', 'program1', 'S1', 'E1', 'horror', 'tvod'], \
        ['0', '10:00:00', 'dev1', 1234, '2', 'SE', 'program1', 'S1', 'E1', 'horror', 'svod']], columns=cols)
    res = task_2.execute_task_2(df)

    # Product type should be 'svod' as it is the most repeated one among viewers of 'program1'
    assert res['product_type'][0] == 'svod'

Esempio n. 2

File: task_2_test.py Progetto: bgrana/sports_popularity_pipeline

def test_content_count():
    df = pd.DataFrame([['0', '10:00:00', 'dev1', 1234, '1', 'DE', 'program1', 'S1', 'E1', 'horror', 'svod'], \
        ['0', '10:00:00', 'dev1', 1234, '1', 'DE', 'program1', 'S1', 'E1', 'horror', 'svod'], \
        ['0', '10:00:00', 'dev1', 1234, '2', 'SE', 'program1', 'S1', 'E1', 'horror', 'svod']], columns=cols)
    res = task_2.execute_task_2(df)

    # Content count should be 3 as there are 3 visualizations of 'program1'
    assert res['content_count'][0] == 3

Esempio n. 3

File: task_2_test.py Progetto: bgrana/sports_popularity_pipeline

def test_country_code():
    df = pd.DataFrame([['0', '10:00:00', 'dev1', 1234, '1', 'DE', 'program1', 'S1', 'E1', 'horror', 'svod'], \
        ['0', '10:00:00', 'dev1', 1234, '1', 'DE', 'program1', 'S1', 'E1', 'horror', 'svod'], \
        ['0', '10:00:00', 'dev1', 1234, '2', 'SE', 'program1', 'S1', 'E1', 'horror', 'svod']], columns=cols)
    res = task_2.execute_task_2(df)

    # Country code should be 'DE' as it is the most repeated one among viewers of 'program1'
    assert res['country_code'][0] == 'DE'

Esempio n. 4

File: task_2_test.py Progetto: bgrana/sports_popularity_pipeline

def test_unique_users():
    df = pd.DataFrame([['0', '10:00:00', 'dev1', 1234, '1', 'DE', 'program1', 'S1', 'E1', 'horror', 'svod'], \
        ['0', '10:00:00', 'dev1', 1234, '1', 'DE', 'program1', 'S1', 'E1', 'horror', 'svod'], \
        ['0', '10:00:00', 'dev1', 1234, '2', 'SE', 'program1', 'S1', 'E1', 'horror', 'svod']], columns=cols)
    res = task_2.execute_task_2(df)

    # Number of users should be 2 as 2 users watched 'program1'
    assert res['unique_users'][0] == 2

Esempio n. 5

File: task_2_test.py Progetto: bgrana/sports_popularity_pipeline

def test_content_ordered_by_unique_users():
    df = pd.DataFrame([['0', '10:00:00', 'dev1', 1234, '1', 'DE', 'program1', 'S1', 'E1', 'horror', 'svod'], \
        ['0', '10:00:00', 'dev2', 1234, '1', 'DE', 'program2', 'S1', 'E1', 'horror', 'svod'], \
        ['0', '10:00:00', 'dev1', 1234, '2', 'SE', 'program2', 'S1', 'E1', 'horror', 'svod']], columns=cols)
    res = task_2.execute_task_2(df)

    # 'program2' should be the most viewed and 'program1' the second most viewed
    assert res.index[0] == 'program2'
    assert res.index[1] == 'program1'