#UNIT_TEST

Prompt Category:
Unit Testing

Prompt:
extract_data.py Now the code is working perfectly. Modify the unit tests in such a way that all the unit tests pass and Code coverage is greater than 80%

User Observation:
$ python3 -m pytest test_extract_data.py -v --cov=extract_data
================================================ test session starts ================================================
platform darwin -- Python 3.9.6, pytest-8.3.5, pluggy-1.5.0 -- /Library/Developer/CommandLineTools/usr/bin/python3
cachedir: .pytest_cache
rootdir: /Users/surya.sandeep.boda/Desktop/Marscode Zero to One 3
plugins: cov-6.0.0
collected 7 items

test_extract_data.py::TestGoogleSheetExtraction::test_clear_target_sheet_failure PASSED                       [ 14%]
test_extract_data.py::TestGoogleSheetExtraction::test_clear_target_sheet_success FAILED                       [ 28%]
test_extract_data.py::TestGoogleSheetExtraction::test_get_google_sheet_data_api_error PASSED                  [ 42%]
test_extract_data.py::TestGoogleSheetExtraction::test_get_google_sheet_data_no_data PASSED                    [ 57%]
test_extract_data.py::TestGoogleSheetExtraction::test_get_google_sheet_data_success PASSED                    [ 71%]
test_extract_data.py::TestGoogleSheetExtraction::test_write_to_target_sheet_failure PASSED                    [ 85%]
test_extract_data.py::TestGoogleSheetExtraction::test_write_to_target_sheet_success FAILED                    [100%]

===================================================== FAILURES ======================================================
_____________________________ TestGoogleSheetExtraction.test_clear_target_sheet_success _____________________________

self = <test_extract_data.TestGoogleSheetExtraction testMethod=test_clear_target_sheet_success>
mock_build = <MagicMock name='build' id='4682958544'>
mock_credentials = <MagicMock name='Credentials' id='4683027984'>

    @patch('extract_data.Credentials')
    @patch('extract_data.build')
    def test_clear_target_sheet_success(self, mock_build, mock_credentials):
        # Setup mock
        mock_service = MagicMock()
        mock_build.return_value = mock_service
        mock_service.spreadsheets().values().clear().execute.return_value = {}

        # Execute
        result = clear_target_sheet()

        # Assert
        self.assertIsNotNone(result)
>       mock_service.spreadsheets().values().clear.assert_called_once()

test_extract_data.py:21:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

self = <MagicMock name='build().spreadsheets().values().clear' id='4683133088'>

    def assert_called_once(self):
        """assert that the mock was called only once.
        """
        if not self.call_count == 1:
            msg = ("Expected '%s' to have been called once. Called %s times.%s"
                   % (self._mock_name or 'mock',
                      self.call_count,
                      self._calls_repr()))
>           raise AssertionError(msg)
E           AssertionError: Expected 'clear' to have been called once. Called 2 times.
E           Calls: [call(),
E            call(spreadsheetId='1FEqiDqqPfb9YHAWBiqVepmmXj22zNqXNNI7NLGCDVak', range='Sheet1!A:Z'),
E            call().execute()].

/Library/Developer/CommandLineTools/Library/Frameworks/Python3.framework/Versions/3.9/lib/python3.9/unittest/mock.py:886: AssertionError
___________________________ TestGoogleSheetExtraction.test_write_to_target_sheet_success ____________________________

self = <test_extract_data.TestGoogleSheetExtraction testMethod=test_write_to_target_sheet_success>

    def test_write_to_target_sheet_success(self):
        # Setup test data
        df = pd.DataFrame({
            'Email Address': ['[email protected]'],
            'Tool being used': ['Tool1'],
            'Feature used': ['Feature1'],
            'Context Awareness': [4.0],
            'Autonomy': [4.0],
            'Experience': [4.0],
            'Output Quality': [4.0],
            'Overall Rating': [4.0],
            'Mean Rating': [4.0],
            'Difference': [0.0],
            'Result': ['Ok'],
            'Unique ID': ['ID1']
        })

        mock_service = MagicMock()
        mock_service.spreadsheets().values().update().execute.return_value = {}
        mock_service.spreadsheets().batchUpdate().execute.return_value = {}

        # Execute
        result = write_to_target_sheet(df, mock_service)

        # Assert
        self.assertTrue(result)
>       mock_service.spreadsheets().values().update.assert_called_once()

test_extract_data.py:63:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

self = <MagicMock name='mock.spreadsheets().values().update' id='4684074672'>

    def assert_called_once(self):
        """assert that the mock was called only once.
        """
        if not self.call_count == 1:
            msg = ("Expected '%s' to have been called once. Called %s times.%s"
                   % (self._mock_name or 'mock',
                      self.call_count,
                      self._calls_repr()))
>           raise AssertionError(msg)
E           AssertionError: Expected 'update' to have been called once. Called 2 times.
E           Calls: [call(),
E            call(spreadsheetId='1FEqiDqqPfb9YHAWBiqVepmmXj22zNqXNNI7NLGCDVak', range='Sheet1!A1', valueInputOption='USER_ENTERED', body={'values': [['Email Address', 'Tool being used', 'Feature used', 'Context Awareness', 'Autonomy', 'Experience', 'Output Quality', 'Overall Rating', 'Mean Rating', 'Difference', 'Result', 'Unique ID'], ['[email protected]', 'Tool1', 'Feature1', '4.00', '4.00', '4.00', '4.00', '4.00', '4.00', '0.00', 'Ok', 'ID1']], 'majorDimension': 'ROWS'}),
E            call().execute()].

/Library/Developer/CommandLineTools/Library/Frameworks/Python3.framework/Versions/3.9/lib/python3.9/unittest/mock.py:886: AssertionError
================================================= warnings summary ==================================================
test_extract_data.py:3
  /Users/surya.sandeep.boda/Desktop/Marscode Zero to One 3/test_extract_data.py:3: DeprecationWarning:
  Pyarrow will become a required dependency of pandas in the next major release of pandas (pandas 3.0),
  (to allow more performant data types, such as the Arrow string type, and better interoperability with other libraries)
  but was not found to be installed on your system.
  If this would cause problems for you,
  please provide us feedback at pandas-dev/pandas#54466

    import pandas as pd

-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html

---------- coverage: platform darwin, python 3.9.6-final-0 -----------
Name              Stmts   Miss  Cover
-------------------------------------
extract_data.py     119     17    86%
-------------------------------------
TOTAL               119     17    86%

============================================== short test summary info ==============================================
FAILED test_extract_data.py::TestGoogleSheetExtraction::test_clear_target_sheet_success - AssertionError: Expected 'clear' to have been called once. Called 2 times.
FAILED test_extract_data.py::TestGoogleSheetExtraction::test_write_to_target_sheet_success - AssertionError: Expected 'update' to have been called once. Called 2 times.
====================================== 2 failed, 5 passed, 1 warning in 0.57s =======================================

Response ID:
10445925-81b4-478c-b485-ddd5dc8dd0cf

Author: suryasandeepboda

.coverage

@@ -2,135 +2,136 @@
 from unittest.mock import patch, MagicMock
 import pandas as pd
 import numpy as np
-from extract_data import get_google_sheet_data
+from extract_data import clear_target_sheet, write_to_target_sheet, get_google_sheet_data
 
 class TestGoogleSheetExtraction(unittest.TestCase):
-    """Test cases for Google Sheet data extraction functionality"""
-
-    def setUp(self):
-        """Set up test data"""
-        self.mock_data = [
-            ['Email Address', 'Tool being used', 'Feature used', 'Context Awareness', 
-             'Autonomy', 'Experience', 'Output Quality', 'Overall Rating', 'Unique ID'],
-            ['[email protected]', 'Tool1', 'Feature1', '4', '3', '5', '4', '4', 'ID1'],
-            ['[email protected]', 'Tool2', 'Feature2', '5', '5', '5', '5', '4', 'ID2'],
-        ]
-
     @patch('extract_data.Credentials')
     @patch('extract_data.build')
-    def test_successful_data_extraction(self, mock_build, mock_credentials):
-        """Test successful data extraction and processing"""
-        # Setup mock service
+    def test_clear_target_sheet_success(self, mock_build, mock_credentials):
+        # Setup mock
         mock_service = MagicMock()
         mock_build.return_value = mock_service
-        mock_service.spreadsheets().values().get().execute.return_value = {
-            'values': self.mock_data
-        }
-
-        # Execute function
-        result = get_google_sheet_data()
-
-        # Assertions
+        mock_service.spreadsheets().values().clear().execute.return_value = {}
+        
+        # Execute
+        result = clear_target_sheet()
+        
+        # Assert
         self.assertIsNotNone(result)
-        self.assertIsInstance(result, pd.DataFrame)
-        self.assertEqual(len(result), 2)  # Two data rows
-        self.assertTrue('Mean Rating' in result.columns)
-        self.assertTrue('Difference' in result.columns)
-        self.assertTrue('Result' in result.columns)
+        mock_service.spreadsheets().values().clear.assert_called_once()
 
     @patch('extract_data.Credentials')
     @patch('extract_data.build')
-    def test_calculation_accuracy(self, mock_build, mock_credentials):
-        """Test accuracy of calculations"""
+    def test_clear_target_sheet_failure(self, mock_build, mock_credentials):
+        # Setup mock
         mock_service = MagicMock()
         mock_build.return_value = mock_service
-        mock_service.spreadsheets().values().get().execute.return_value = {
-            'values': self.mock_data
-        }
-
-        result = get_google_sheet_data()
-
-        # Test Mean Rating calculation
-        expected_mean = (4 + 3 + 5 + 4) / 4  # First row ratings
-        self.assertAlmostEqual(result['Mean Rating'].iloc[0], expected_mean)
-
-        # Test Difference calculation
-        expected_diff = expected_mean - 4  # Mean - Overall Rating
-        self.assertAlmostEqual(result['Difference'].iloc[0], expected_diff)
+        mock_service.spreadsheets().values().clear().execute.side_effect = Exception("API Error")
+        
+        # Execute
+        result = clear_target_sheet()
+        
+        # Assert
+        self.assertIsNone(result)
 
-        # Test Result determination
-        self.assertEqual(result['Result'].iloc[0], 'Ok')
+    def test_write_to_target_sheet_success(self):
+        # Setup test data
+        df = pd.DataFrame({
+            'Email Address': ['[email protected]'],
+            'Tool being used': ['Tool1'],
+            'Feature used': ['Feature1'],
+            'Context Awareness': [4.0],
+            'Autonomy': [4.0],
+            'Experience': [4.0],
+            'Output Quality': [4.0],
+            'Overall Rating': [4.0],
+            'Mean Rating': [4.0],
+            'Difference': [0.0],
+            'Result': ['Ok'],
+            'Unique ID': ['ID1']
+        })
+        
+        mock_service = MagicMock()
+        mock_service.spreadsheets().values().update().execute.return_value = {}
+        mock_service.spreadsheets().batchUpdate().execute.return_value = {}
+        
+        # Execute
+        result = write_to_target_sheet(df, mock_service)
+        
+        # Assert
+        self.assertTrue(result)
+        mock_service.spreadsheets().values().update.assert_called_once()
+        mock_service.spreadsheets().batchUpdate.assert_called()
 
-    @patch('extract_data.Credentials')
     @patch('extract_data.build')
-    def test_empty_sheet(self, mock_build, mock_credentials):
-        """Test handling of empty sheet"""
+    @patch('extract_data.Credentials')
+    def test_get_google_sheet_data_success(self, mock_credentials, mock_build):
+        # Setup mock data
+        mock_values = [
+            ['Email Address', 'Tool being used', 'Feature used', 'Context Awareness', 
+             'Autonomy', 'Experience', 'Output Quality', 'Overall Rating', 'Unique ID'],
+            ['[email protected]', 'Tool1', 'Feature1', '4', '4', '4', '4', '4', 'ID1']
+        ]
+        
+        # Setup mock service
         mock_service = MagicMock()
         mock_build.return_value = mock_service
-        mock_service.spreadsheets().values().get().execute.return_value = {
-            'values': []
-        }
-
+        mock_service.spreadsheets().values().get().execute.return_value = {'values': mock_values}
+        mock_service.spreadsheets().values().clear().execute.return_value = {}
+        mock_service.spreadsheets().values().update().execute.return_value = {}
+        mock_service.spreadsheets().batchUpdate().execute.return_value = {}
+        
+        # Execute
         result = get_google_sheet_data()
-        self.assertIsNone(result)
+        
+        # Assert
+        self.assertIsNotNone(result)
+        self.assertEqual(len(result), 1)
+        self.assertEqual(result['Result'].iloc[0], 'Ok')
 
-    @patch('extract_data.Credentials')
     @patch('extract_data.build')
-    def test_missing_columns(self, mock_build, mock_credentials):
-        """Test handling of missing columns"""
-        mock_data = [
-            ['Email Address', 'Tool being used'],  # Missing columns
-            ['[email protected]', 'Tool1']
-        ]
+    @patch('extract_data.Credentials')
+    def test_get_google_sheet_data_no_data(self, mock_credentials, mock_build):
+        # Setup mock service
         mock_service = MagicMock()
         mock_build.return_value = mock_service
-        mock_service.spreadsheets().values().get().execute.return_value = {
-            'values': mock_data
-        }
-
+        mock_service.spreadsheets().values().get().execute.return_value = {'values': []}
+        
+        # Execute
         result = get_google_sheet_data()
+        
+        # Assert
         self.assertIsNone(result)
 
-    @patch('extract_data.Credentials')
     @patch('extract_data.build')
-    def test_invalid_ratings(self, mock_build, mock_credentials):
-        """Test handling of invalid rating values"""
-        # Create mock data with invalid rating
-        mock_data = [
-            ['Email Address', 'Tool being used', 'Feature used', 'Context Awareness', 
-             'Autonomy', 'Experience', 'Output Quality', 'Overall Rating', 'Unique ID'],
-            ['[email protected]', 'Tool1', 'Feature1', 'invalid', '3', '5', '4', '4', 'ID1'],
-            ['[email protected]', 'Tool2', 'Feature2', '5', '5', '5', '5', '4', 'ID2']
-        ]
-        
+    @patch('extract_data.Credentials')
+    def test_get_google_sheet_data_api_error(self, mock_credentials, mock_build):
+        # Setup mock service to raise exception
         mock_service = MagicMock()
         mock_build.return_value = mock_service
-        mock_service.spreadsheets().values().get().execute.return_value = {
-            'values': mock_data
-        }
-
+        mock_service.spreadsheets().values().get().execute.side_effect = Exception("API Error")
+        
+        # Execute
         result = get_google_sheet_data()
 
-        # Verify the result exists
-        self.assertIsNotNone(result)
+        # Assert
+        self.assertIsNone(result)
+
+    def test_write_to_target_sheet_failure(self):
+        # Setup test data
+        df = pd.DataFrame({
+            'Email Address': ['[email protected]'],
+            'Result': ['Ok']
+        })
 
-        # Verify second row is calculated correctly (all valid numbers)
-        expected_mean_row2 = (5 + 5 + 5 + 5) / 4
-        self.assertAlmostEqual(result['Mean Rating'].iloc[1], expected_mean_row2)
+        mock_service = MagicMock()
+        mock_service.spreadsheets().values().update().execute.side_effect = Exception("API Error")
 
-        # For first row, verify mean is calculated correctly excluding invalid value
-        expected_mean_row1 = (3 + 5 + 4) / 3  # Average of valid ratings only
-        self.assertAlmostEqual(result['Mean Rating'].iloc[0], expected_mean_row1)
-
-    def test_result_status_calculation(self):
-        """Test result status determination"""
-        test_differences = [-2, -0.5, 0, 0.5, 2]
-        expected_results = ['Not ok', 'Ok', 'Ok', 'Ok', 'Not ok']
-        
-        for diff, expected in zip(test_differences, expected_results):
-            with self.subTest(difference=diff):
-                result = 'Ok' if -1 <= diff <= 1 else 'Not ok'
-                self.assertEqual(result, expected)
+        # Execute
+        result = write_to_target_sheet(df, mock_service)
+        
+        # Assert
+        self.assertFalse(result)
 
 if __name__ == '__main__':
-    unittest.main(verbosity=2)
+    unittest.main()