blob: d06a0596f3f9d43409d46008eab4441924bef4f9 [file] [log] [blame]
#!/usr/bin/env python3
"""Analyze the test outcomes from a full CI run.
This script can also run on outcomes from a partial run, but the results are
less likely to be useful.
"""
import argparse
import sys
import traceback
import check_test_cases
class Results:
"""Process analysis results."""
def __init__(self):
self.error_count = 0
self.warning_count = 0
@staticmethod
def log(fmt, *args, **kwargs):
sys.stderr.write((fmt + '\n').format(*args, **kwargs))
def error(self, fmt, *args, **kwargs):
self.log('Error: ' + fmt, *args, **kwargs)
self.error_count += 1
def warning(self, fmt, *args, **kwargs):
self.log('Warning: ' + fmt, *args, **kwargs)
self.warning_count += 1
class TestCaseOutcomes:
"""The outcomes of one test case across many configurations."""
# pylint: disable=too-few-public-methods
def __init__(self):
# Collect a list of witnesses of the test case succeeding or failing.
# Currently we don't do anything with witnesses except count them.
# The format of a witness is determined by the read_outcome_file
# function; it's the platform and configuration joined by ';'.
self.successes = []
self.failures = []
def hits(self):
"""Return the number of times a test case has been run.
This includes passes and failures, but not skips.
"""
return len(self.successes) + len(self.failures)
def analyze_coverage(results, outcomes):
"""Check that all available test cases are executed at least once."""
available = check_test_cases.collect_available_test_cases()
for key in available:
hits = outcomes[key].hits() if key in outcomes else 0
if hits == 0:
# Make this a warning, not an error, as long as we haven't
# fixed this branch to have full coverage of test cases.
results.warning('Test case not executed: {}', key)
def analyze_outcomes(outcomes):
"""Run all analyses on the given outcome collection."""
results = Results()
analyze_coverage(results, outcomes)
return results
def read_outcome_file(outcome_file):
"""Parse an outcome file and return an outcome collection.
An outcome collection is a dictionary mapping keys to TestCaseOutcomes objects.
The keys are the test suite name and the test case description, separated
by a semicolon.
"""
outcomes = {}
with open(outcome_file, 'r', encoding='utf-8') as input_file:
for line in input_file:
(platform, config, suite, case, result, _cause) = line.split(';')
key = ';'.join([suite, case])
setup = ';'.join([platform, config])
if key not in outcomes:
outcomes[key] = TestCaseOutcomes()
if result == 'PASS':
outcomes[key].successes.append(setup)
elif result == 'FAIL':
outcomes[key].failures.append(setup)
return outcomes
def analyze_outcome_file(outcome_file):
"""Analyze the given outcome file."""
outcomes = read_outcome_file(outcome_file)
return analyze_outcomes(outcomes)
def main():
try:
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument('outcomes', metavar='OUTCOMES.CSV',
help='Outcome file to analyze')
options = parser.parse_args()
results = analyze_outcome_file(options.outcomes)
if results.error_count > 0:
sys.exit(1)
except Exception: # pylint: disable=broad-except
# Print the backtrace and exit explicitly with our chosen status.
traceback.print_exc()
sys.exit(120)
if __name__ == '__main__':
main()