def get_two_metrics(output_directory, resource_path, rules):
metrics = [
Metric('MetricOne', 'TestOne.csv', 'HostnameOne', output_directory,
resource_path, 'MetricOne', None, None, rules, None, None),
Metric('MetricTwo', 'TestTwo.csv', 'HostnameOne', output_directory,
resource_path, 'MetricTwo', None, None, rules, None, None)
]
return metrics
def initialize_metric(section, infile_list, hostname, output_directory, resource_path, label, ts_start, ts_end, rule_strings, important_sub_metrics, other_options):
"""
Initialize appropriate metric based on type of metric.
:param: section: config section name or auto discovered metric type
:param: infile_list: list of input log files for the metric
:param: hostname: hostname associated with the logs origin
:param: output_directory: report location
:param: resource_path: resource path for report
:param: label: label for config section or auto discovered metric type
:param: ts_start: start time for analysis
:param: ts_end: end time for analysis
:param: rule_strings: list of slas
:param: important_sub_metrics: list of important sub metrics
:param: other_options: kwargs
:return: metric object
"""
bin_path = os.path.abspath(os.path.join(os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))),'bin'))
metric = None
metric_type = section.split('-')[0]
if metric_type in metric_classes:
if 'SAR' in metric_type:
metric = metric_classes['SAR'](section, infile_list, hostname, output_directory, resource_path, label, ts_start, ts_end, rule_strings, important_sub_metrics, **other_options)
else:
metric = metric_classes[metric_type](section, infile_list, hostname, output_directory, resource_path, label, ts_start, ts_end, rule_strings, important_sub_metrics, **other_options)
else:
metric = Metric(section, infile_list, hostname, output_directory, resource_path, label, ts_start, ts_end, rule_strings, important_sub_metrics, **other_options)
metric.bin_path = bin_path
return metric
def test_metrics_with_summary_with_partial_error():
"""
Tests to verify that metric reports are generated for OK metrics if there are some metrics that are in error. Also a summary report should be created.
"""
global output_directory
global input_log_directory
global resource_path
rules = {}
metrics = get_two_metrics(output_directory, resource_path, rules)
files_list = [
os.path.join(input_log_directory, 'a.csv'),
os.path.join(input_log_directory, 'b.csv')
]
for metric in metrics:
metric.csv_files = files_list
metric.stats_files = files_list
metric.timeseries_csv_list = files_list
metric.important_stats_files = files_list
metric.percentiles_files = files_list
metrics.append(
Metric('MetricThree', 'TestThree.csv', 'HostnameOne', output_directory,
resource_path, 'MetricThree', None, None, rules, None, None))
aggregate_metrics = []
correlated_plots = []
rpt = Report(None,
output_directory,
resource_directory,
resource_path,
metrics + aggregate_metrics,
correlated_plots=correlated_plots)
rpt.generate()
assert naarad.utils.is_valid_file(
os.path.join(output_directory, 'MetricOne_report.html'))
assert naarad.utils.is_valid_file(
os.path.join(output_directory, 'MetricTwo_report.html'))
assert not naarad.utils.is_valid_file(
os.path.join(output_directory, 'MetricThree_report.html'))
assert naarad.utils.is_valid_file(
os.path.join(output_directory, 'report.html'))
assert naarad.utils.is_valid_file(
os.path.join(output_directory, 'summary_report.html'))
os.system('rm -rf tmp_report_test/*.*')
os.system('rm -rf tmp_report_test/resources/*.*')
