def mock_stats(mock_config):
'''
Mock Datadog authentication and stats management
'''
from shipit_static_analysis import stats
# Configure Datadog with a dummy token
# and an ultra fast flushing cycle
stats.auth('test_token')
stats.api.stop()
stats.api.start(flush_interval=0.001)
assert not stats.api._disabled
assert stats.api._is_auto_flushing
class MemoryReporter(object):
'''
A reporting class that reports to memory for testing.
Used in datadog unit tests:
https://github.com/DataDog/datadogpy/blob/master/tests/unit/threadstats/test_threadstats.py
'''
def __init__(self, api):
self.metrics = []
self.events = []
self.api = api
def flush_metrics(self, metrics):
self.metrics += metrics
def flush_events(self, events):
self.events += events
def flush(self):
# Helper for unit tests to force flush
self.api.flush(time.time() + 20)
def get_metrics(self, metric_name):
return list(
itertools.chain(*[[[t, point * m['interval']]
for t, point in m['points']]
for m in self.metrics
if m['metric'] == metric_name]))
# Gives reporter access to unit tests to access metrics
stats.api.reporter = MemoryReporter(stats.api)
yield stats.api.reporter
def main(
phabricator,
mozreview,
cache_root,
taskcluster_secret,
taskcluster_client_id,
taskcluster_access_token,
):
assert (phabricator is None) ^ (mozreview is None), \
'Specify a phabricator XOR mozreview parameters'
secrets = get_secrets(
taskcluster_secret,
config.PROJECT_NAME,
required=(
'APP_CHANNEL',
'REPORTERS',
'ANALYZERS',
),
existing={
'APP_CHANNEL': 'development',
'REPORTERS': [],
'ANALYZERS': [
'clang-tidy',
],
},
taskcluster_client_id=taskcluster_client_id,
taskcluster_access_token=taskcluster_access_token,
)
init_logger(
config.PROJECT_NAME,
PAPERTRAIL_HOST=secrets.get('PAPERTRAIL_HOST'),
PAPERTRAIL_PORT=secrets.get('PAPERTRAIL_PORT'),
SENTRY_DSN=secrets.get('SENTRY_DSN'),
MOZDEF=secrets.get('MOZDEF'),
)
# Setup settings before stats
settings.setup(secrets['APP_CHANNEL'])
# Setup statistics
datadog_api_key = secrets.get('DATADOG_API_KEY')
if datadog_api_key:
stats.auth(datadog_api_key)
# Load reporters
reporters = get_reporters(
secrets['REPORTERS'],
taskcluster_client_id,
taskcluster_access_token,
)
# Load revisions
revisions = []
if phabricator:
# Only one phabricator revision at a time
api = reporters.get('phabricator')
assert api is not None, \
'Cannot use a phabricator revision without a phabricator reporter'
revisions.append(PhabricatorRevision(phabricator, api))
if mozreview:
# Multiple mozreview revisions are possible
revisions += [MozReviewRevision(r) for r in mozreview.split(' ')]
w = Workflow(cache_root, reporters, secrets['ANALYZERS'])
for revision in revisions:
try:
w.run(revision)
except Exception as e:
# Log errors to papertrail
logger.error(
'Static analysis failure',
revision=revision,
error=e,
)