def test_megaquery_not_detectably_malformed():
exp = Experiment('slug', '2019-01-01', 8)
tl = TimeLimits.for_ts(first_enrollment_date='2019-01-01',
last_date_full_data='2019-03-01',
time_series_period='weekly',
num_dates_enrollment=8)
sql = exp.build_query(
metric_list=[
m for m in mad.__dict__.values() if isinstance(m, mad.Metric)
],
time_limits=tl,
enrollments_query_type='normandy',
)
sql_lint(sql)
def test_query_not_detectably_malformed():
exp = Experiment('slug', '2019-01-01', 8)
tl = TimeLimits.for_ts(
first_enrollment_date='2019-01-01',
last_date_full_data='2019-03-01',
time_series_period='weekly',
num_dates_enrollment=8
)
sql = exp.build_query(
metric_list=[],
time_limits=tl,
enrollments_query_type='normandy',
)
sql_lint(sql)
def test_query_not_detectably_malformed():
exp = Experiment('slug', '2019-01-01', 8)
tl = TimeLimits.for_ts(first_enrollment_date='2019-01-01',
last_date_full_data='2019-03-01',
time_series_period='weekly',
num_dates_enrollment=8)
sql = exp.build_query(
metric_list=[],
time_limits=tl,
enrollments_query_type='normandy',
)
# This query is actually slightly malformed, due to a trailing comma.
# We should add a metric here if the linter ever improves.
sql_lint(sql)
def dry_run_query(exp_path):
report = validate_schema(op.join(exp_path, "report.json"))
metric_list = _make_metric_list(report)
exp = Experiment(experiment_slug=report["experiment_slug"],
start_date=report["start_date"],
num_dates_enrollment=report["num_dates_enrollment"])
# create an archive of the sql generating analysis
time_limits = TimeLimits.for_single_analysis_window(
first_enrollment_date=report['start_date'],
last_date_full_data=report['last_date_full_data'],
analysis_start_days=report['analysis_start_days'],
analysis_length_dates=report['analysis_length_days'],
num_dates_enrollment=report['num_dates_enrollment'])
query = exp.build_query(metric_list=metric_list,
time_limits=time_limits,
enrollments_query_type='normandy')
return query