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Add tests for QuantumProvenanceGraph cli
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@eigerx
eigerx committed Jul 30, 2024
1 parent 0920c14 commit 94c8ff2
Showing 1 changed file with 334 additions and 0 deletions.
334 changes: 334 additions & 0 deletions tests/test_cliCmdReport.py
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Original file line number Diff line number Diff line change
Expand Up @@ -34,6 +34,7 @@
from lsst.ctrl.mpexec.cli.pipetask import cli as pipetask_cli
from lsst.daf.butler.cli.utils import LogCliRunner, clickResultMsg
from lsst.daf.butler.tests.utils import makeTestTempDir, removeTestTempDir
from lsst.pipe.base.quantum_provenance_graph import DatasetTypeSummary, Summary, TaskSummary
from lsst.pipe.base.tests.simpleQGraph import makeSimpleQGraph
from lsst.pipe.base.tests.util import check_output_run
from yaml.loader import SafeLoader
Expand Down Expand Up @@ -102,6 +103,339 @@ def test_report(self):
self.assertIn("Expected", result_hr.stdout)
self.assertIn("Succeeded", result_hr.stdout)

# Test cli for the QPG
result_v2_show_err = self.runner.invoke(
pipetask_cli,
["report", self.root, graph_uri, "--no-logs", "--show-errors", "--force-v2"],
input="no",
)

# Check that we can read from the command line
self.assertEqual(result_v2_show_err.exit_code, 0, clickResultMsg(result_v2_show_err))

# Check that we get string output
self.assertIsInstance(result_v2_show_err.stdout, str)

# Check that task0 and the quanta for task0 exist in the string
self.assertIn("task0", result_v2_show_err.stdout)
self.assertIn("Not Attempted", result_v2_show_err.stdout)
self.assertIn("Successful", result_v2_show_err.stdout)
self.assertIn("Blocked", result_v2_show_err.stdout)
self.assertIn("Failed", result_v2_show_err.stdout)
self.assertIn("Wonky", result_v2_show_err.stdout)
self.assertIn("TOTAL", result_v2_show_err.stdout)
self.assertIn("EXPECTED", result_v2_show_err.stdout)

# Check that title from --show-errors appears
self.assertIn("Unsuccessful Datasets", result_v2_show_err.stdout)

# Check that the full output option works
test_filename_v2 = os.path.join(self.root, "report_test.json")
result_v2_full = self.runner.invoke(
pipetask_cli,
[
"report",
self.root,
graph_uri,
"--no-logs",
"--full-output-filename",
test_filename_v2,
"--force-v2",
],
input="no",
)

self.assertEqual(result.exit_code, 0, clickResultMsg(result_v2_full))

with open(test_filename_v2) as f:
output = f.read()
model = Summary.model_validate_json(output)
self.assertDictEqual(
model.tasks,
{
"task0": TaskSummary(
n_successful=0,
n_blocked=0,
n_not_attempted=1,
n_expected=1,
failed_quanta=[],
recovered_quanta=[],
wonky_quanta=[],
n_wonky=0,
n_failed=0,
),
"task1": TaskSummary(
n_successful=0,
n_blocked=0,
n_not_attempted=1,
n_expected=1,
failed_quanta=[],
recovered_quanta=[],
wonky_quanta=[],
n_wonky=0,
n_failed=0,
),
"task2": TaskSummary(
n_successful=0,
n_blocked=0,
n_not_attempted=1,
n_expected=1,
failed_quanta=[],
recovered_quanta=[],
wonky_quanta=[],
n_wonky=0,
n_failed=0,
),
"task3": TaskSummary(
n_successful=0,
n_blocked=0,
n_not_attempted=1,
n_expected=1,
failed_quanta=[],
recovered_quanta=[],
wonky_quanta=[],
n_wonky=0,
n_failed=0,
),
"task4": TaskSummary(
n_successful=0,
n_blocked=0,
n_not_attempted=1,
n_expected=1,
failed_quanta=[],
recovered_quanta=[],
wonky_quanta=[],
n_wonky=0,
n_failed=0,
),
},
)
self.assertDictEqual(
model.datasets,
{
"add_dataset1": DatasetTypeSummary(
producer="task0",
n_published=0,
n_unpublished=0,
n_predicted_only=0,
n_expected=1,
cursed_datasets=[],
unsuccessful_datasets=[{"instrument": "INSTR", "detector": 0}],
n_cursed=0,
n_unsuccessful=1,
),
"add2_dataset1": DatasetTypeSummary(
producer="task0",
n_published=0,
n_unpublished=0,
n_predicted_only=0,
n_expected=1,
cursed_datasets=[],
unsuccessful_datasets=[{"instrument": "INSTR", "detector": 0}],
n_cursed=0,
n_unsuccessful=1,
),
"task0_metadata": DatasetTypeSummary(
producer="task0",
n_published=0,
n_unpublished=0,
n_predicted_only=0,
n_expected=1,
cursed_datasets=[],
unsuccessful_datasets=[{"instrument": "INSTR", "detector": 0}],
n_cursed=0,
n_unsuccessful=1,
),
"task0_log": DatasetTypeSummary(
producer="task0",
n_published=0,
n_unpublished=0,
n_predicted_only=0,
n_expected=1,
cursed_datasets=[],
unsuccessful_datasets=[{"instrument": "INSTR", "detector": 0}],
n_cursed=0,
n_unsuccessful=1,
),
"add_dataset2": DatasetTypeSummary(
producer="task1",
n_published=0,
n_unpublished=0,
n_predicted_only=0,
n_expected=1,
cursed_datasets=[],
unsuccessful_datasets=[{"instrument": "INSTR", "detector": 0}],
n_cursed=0,
n_unsuccessful=1,
),
"add2_dataset2": DatasetTypeSummary(
producer="task1",
n_published=0,
n_unpublished=0,
n_predicted_only=0,
n_expected=1,
cursed_datasets=[],
unsuccessful_datasets=[{"instrument": "INSTR", "detector": 0}],
n_cursed=0,
n_unsuccessful=1,
),
"task1_metadata": DatasetTypeSummary(
producer="task1",
n_published=0,
n_unpublished=0,
n_predicted_only=0,
n_expected=1,
cursed_datasets=[],
unsuccessful_datasets=[{"instrument": "INSTR", "detector": 0}],
n_cursed=0,
n_unsuccessful=1,
),
"task1_log": DatasetTypeSummary(
producer="task1",
n_published=0,
n_unpublished=0,
n_predicted_only=0,
n_expected=1,
cursed_datasets=[],
unsuccessful_datasets=[{"instrument": "INSTR", "detector": 0}],
n_cursed=0,
n_unsuccessful=1,
),
"add_dataset3": DatasetTypeSummary(
producer="task2",
n_published=0,
n_unpublished=0,
n_predicted_only=0,
n_expected=1,
cursed_datasets=[],
unsuccessful_datasets=[{"instrument": "INSTR", "detector": 0}],
n_cursed=0,
n_unsuccessful=1,
),
"add2_dataset3": DatasetTypeSummary(
producer="task2",
n_published=0,
n_unpublished=0,
n_predicted_only=0,
n_expected=1,
cursed_datasets=[],
unsuccessful_datasets=[{"instrument": "INSTR", "detector": 0}],
n_cursed=0,
n_unsuccessful=1,
),
"task2_metadata": DatasetTypeSummary(
producer="task2",
n_published=0,
n_unpublished=0,
n_predicted_only=0,
n_expected=1,
cursed_datasets=[],
unsuccessful_datasets=[{"instrument": "INSTR", "detector": 0}],
n_cursed=0,
n_unsuccessful=1,
),
"task2_log": DatasetTypeSummary(
producer="task2",
n_published=0,
n_unpublished=0,
n_predicted_only=0,
n_expected=1,
cursed_datasets=[],
unsuccessful_datasets=[{"instrument": "INSTR", "detector": 0}],
n_cursed=0,
n_unsuccessful=1,
),
"add_dataset4": DatasetTypeSummary(
producer="task3",
n_published=0,
n_unpublished=0,
n_predicted_only=0,
n_expected=1,
cursed_datasets=[],
unsuccessful_datasets=[{"instrument": "INSTR", "detector": 0}],
n_cursed=0,
n_unsuccessful=1,
),
"add2_dataset4": DatasetTypeSummary(
producer="task3",
n_published=0,
n_unpublished=0,
n_predicted_only=0,
n_expected=1,
cursed_datasets=[],
unsuccessful_datasets=[{"instrument": "INSTR", "detector": 0}],
n_cursed=0,
n_unsuccessful=1,
),
"task3_metadata": DatasetTypeSummary(
producer="task3",
n_published=0,
n_unpublished=0,
n_predicted_only=0,
n_expected=1,
cursed_datasets=[],
unsuccessful_datasets=[{"instrument": "INSTR", "detector": 0}],
n_cursed=0,
n_unsuccessful=1,
),
"task3_log": DatasetTypeSummary(
producer="task3",
n_published=0,
n_unpublished=0,
n_predicted_only=0,
n_expected=1,
cursed_datasets=[],
unsuccessful_datasets=[{"instrument": "INSTR", "detector": 0}],
n_cursed=0,
n_unsuccessful=1,
),
"add_dataset5": DatasetTypeSummary(
producer="task4",
n_published=0,
n_unpublished=0,
n_predicted_only=0,
n_expected=1,
cursed_datasets=[],
unsuccessful_datasets=[{"instrument": "INSTR", "detector": 0}],
n_cursed=0,
n_unsuccessful=1,
),
"add2_dataset5": DatasetTypeSummary(
producer="task4",
n_published=0,
n_unpublished=0,
n_predicted_only=0,
n_expected=1,
cursed_datasets=[],
unsuccessful_datasets=[{"instrument": "INSTR", "detector": 0}],
n_cursed=0,
n_unsuccessful=1,
),
"task4_metadata": DatasetTypeSummary(
producer="task4",
n_published=0,
n_unpublished=0,
n_predicted_only=0,
n_expected=1,
cursed_datasets=[],
unsuccessful_datasets=[{"instrument": "INSTR", "detector": 0}],
n_cursed=0,
n_unsuccessful=1,
),
"task4_log": DatasetTypeSummary(
producer="task4",
n_published=0,
n_unpublished=0,
n_predicted_only=0,
n_expected=1,
cursed_datasets=[],
unsuccessful_datasets=[{"instrument": "INSTR", "detector": 0}],
n_cursed=0,
n_unsuccessful=1,
),
},
)


if __name__ == "__main__":
unittest.main()

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