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Fixed scrapper test

This commit is contained in:
Alberto Soutullo 2024-03-07 11:37:33 +01:00
parent 4cb8ed0911
commit 23e22d8073
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GPG Key ID: A7CAC0D8343B0387
1 changed files with 12 additions and 12 deletions
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24
src/metrics/tests/test_scrapper.py
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@ -38,7 +38,7 @@ class TestScrapper(unittest.TestCase):
test_scrapper.query_and_dump_metrics()
expected_data = {
'Unix Timestamp': pd.to_datetime(
'Time': pd.to_datetime(
['1970-01-01 00:00:01', '1970-01-01 00:00:02', '1970-01-01 00:00:03',
'1970-01-01 00:00:04', '1970-01-01 00:00:05']),
'nodes-1': [5] * 5
@ -48,7 +48,7 @@ class TestScrapper(unittest.TestCase):
result = pd.read_csv('test_results/metric1.csv')
# Convert data type since it is lost when reading from a file
result['Unix Timestamp'] = pd.to_datetime(result['Unix Timestamp'])
result['Time'] = pd.to_datetime(result['Time'])
self.assertTrue(result.equals(expected_df))
@ -71,7 +71,7 @@ class TestScrapper(unittest.TestCase):
test_scrapper.query_and_dump_metrics()
expected_data = {
'Unix Timestamp': pd.to_datetime(
'Time': pd.to_datetime(
['1970-01-01 00:00:01', '1970-01-01 00:00:02', '1970-01-01 00:00:03',
'1970-01-01 00:00:04', '1970-01-01 00:00:05']),
'nodes-1': [5] * 5,
@ -81,7 +81,7 @@ class TestScrapper(unittest.TestCase):
result = pd.read_csv('test_results/metric1.csv')
# Convert data type since it is lost when reading from a file
result['Unix Timestamp'] = pd.to_datetime(result['Unix Timestamp'])
result['Time'] = pd.to_datetime(result['Time'])
self.assertTrue(result.equals(expected_df))
@ -104,7 +104,7 @@ class TestScrapper(unittest.TestCase):
test_scrapper.query_and_dump_metrics()
expected_data = {
'Unix Timestamp': pd.to_datetime(
'Time': pd.to_datetime(
['1970-01-01 00:00:01', '1970-01-01 00:00:02', '1970-01-01 00:00:03',
'1970-01-01 00:00:04', '1970-01-01 00:00:05']),
'nodes-1': [5] * 5,
@ -114,7 +114,7 @@ class TestScrapper(unittest.TestCase):
result = pd.read_csv('test_results/metric1.csv')
# Convert data type since it is lost when reading from a file
result['Unix Timestamp'] = pd.to_datetime(result['Unix Timestamp'])
result['Time'] = pd.to_datetime(result['Time'])
self.assertTrue(result.equals(expected_df))
@ -145,7 +145,7 @@ class TestScrapper(unittest.TestCase):
test_scrapper.query_and_dump_metrics()
expected_data_1 = {
'Unix Timestamp': pd.to_datetime(
'Time': pd.to_datetime(
['1970-01-01 00:00:01', '1970-01-01 00:00:02', '1970-01-01 00:00:03',
'1970-01-01 00:00:04', '1970-01-01 00:00:05']),
'nodes-1': [5] * 5,
@ -154,7 +154,7 @@ class TestScrapper(unittest.TestCase):
expected_df1 = pd.DataFrame(expected_data_1)
expected_data_2 = {
'Unix Timestamp': pd.to_datetime(
'Time': pd.to_datetime(
['1970-01-01 00:00:01', '1970-01-01 00:00:02', '1970-01-01 00:00:03',
'1970-01-01 00:00:04', '1970-01-01 00:00:05']),
'nodes-1_out': [5] * 5,
@ -164,13 +164,13 @@ class TestScrapper(unittest.TestCase):
result1 = pd.read_csv('test_results/metric1.csv')
# Convert data type since it is lost when reading from a file
result1['Unix Timestamp'] = pd.to_datetime(result1['Unix Timestamp'])
result1['Time'] = pd.to_datetime(result1['Time'])
self.assertTrue(result1.equals(expected_df1))
result2 = pd.read_csv('test_results/metric2[$__rate_interval]).csv')
# Convert data type since it is lost when reading from a file
result2['Unix Timestamp'] = pd.to_datetime(result2['Unix Timestamp'])
result2['Time'] = pd.to_datetime(result2['Time'])
self.assertTrue(result2.equals(expected_df2))
@ -263,7 +263,7 @@ class TestScrapper(unittest.TestCase):
test_scrapper._dump_data('metric1', 'instance', data)
expected_data = {
'Unix Timestamp': pd.to_datetime(
'Time': pd.to_datetime(
['1970-01-01 00:00:01', '1970-01-01 00:00:02', '1970-01-01 00:00:03',
'1970-01-01 00:00:04', '1970-01-01 00:00:05']),
'nodes-1': [5] * 5
@ -272,7 +272,7 @@ class TestScrapper(unittest.TestCase):
result = pd.read_csv('test_results/metric1.csv')
# Convert data type since it is lost when reading from a file
result['Unix Timestamp'] = pd.to_datetime(result['Unix Timestamp'])
result['Time'] = pd.to_datetime(result['Time'])
self.assertTrue(result.equals(expected_df))