b00e0d2a7e
This patch backports all of the recent changes to the release branch. This will get the CI functioning again. This backport also includes a couple refactorings, but those will probably end up being necessary for backporting future patches. They are relatively safe because they have already been extensively tested on main and only impact the CI.
76 lines
2.8 KiB
Python
76 lines
2.8 KiB
Python
# Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
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# See https://llvm.org/LICENSE.txt for license information.
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# SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
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"""Tests for metrics.py"""
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from dataclasses import dataclass
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import requests
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import unittest
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import unittest.mock
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import metrics
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class TestMetrics(unittest.TestCase):
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def test_upload_gauge_metric(self):
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"""Test that we can upload a gauge metric correctly.
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Also verify that we pass around parameters like API keys and user IDs
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correctly to the HTTP POST request.
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"""
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test_metrics = [metrics.GaugeMetric("gauge_test", 5, 1000)]
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return_value = requests.Response()
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return_value.status_code = 204
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with unittest.mock.patch(
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"requests.post", return_value=return_value
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) as post_mock:
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metrics.upload_metrics(test_metrics, "test_userid", "test_api_key")
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self.assertSequenceEqual(post_mock.call_args.args, [metrics.GRAFANA_URL])
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self.assertEqual(
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post_mock.call_args.kwargs["data"], "gauge_test value=5 1000"
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)
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self.assertEqual(
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post_mock.call_args.kwargs["auth"], ("test_userid", "test_api_key")
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)
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def test_upload_job_metric(self):
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"""Test that we can upload a job metric correctly."""
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test_metrics = [
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metrics.JobMetrics("test_job", 5, 10, 1, 1000, 7, "test_workflow")
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]
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return_value = requests.Response()
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return_value.status_code = 204
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with unittest.mock.patch(
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"requests.post", return_value=return_value
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) as post_mock:
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metrics.upload_metrics(test_metrics, "test_userid", "test_aoi_key")
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self.assertEqual(
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post_mock.call_args.kwargs["data"],
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"test_job queue_time=5,run_time=10,status=1 1000",
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)
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def test_upload_unknown_metric(self):
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"""Test we report an error if we encounter an unknown metric type."""
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@dataclass
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class FakeMetric:
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fake_data: str
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test_metrics = [FakeMetric("test")]
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with self.assertRaises(ValueError):
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metrics.upload_metrics(test_metrics, "test_userid", "test_api_key")
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def test_bad_response_code(self):
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"""Test that we gracefully handle HTTP response errors."""
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test_metrics = [metrics.GaugeMetric("gauge_test", 5, 1000)]
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return_value = requests.Response()
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return_value.status_code = 403
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# Just assert that we continue running here and do not raise anything.
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with unittest.mock.patch("requests.post", return_value=return_value) as _:
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metrics.upload_metrics(test_metrics, "test_userid", "test_api_key")
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if __name__ == "__main__":
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unittest.main()
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