def setup_logging():
"""
Setup the correct logging verbosity and file handlers.
We also add a logger for Sentry in case it has been set in the environment.
Sentry allows us to centrally collect error logging during development.
"""
if os.environ.get("SENTRY_SDK_URL"):
import sentry_sdk
sentry_sdk.init(os.environ.get("SENTRY_SDK_URL"))
# Configuration for which we need access to both settings and logging singletons should happen here
logging.verbosity = settings.config.getint("general", "log_verbosity")
logging.logger.setLevel(settings.config.get("general", "log_level"))
os.environ['TF_CPP_MIN_LOG_LEVEL'] = settings.config.get(
"machine_learning", "tensorflow_log_level")
# Log Handlers
log_file = settings.config.get("general", "log_file")
if os.path.exists(os.path.dirname(log_file)):
logging.add_file_handler(log_file)
else:
logging.logger.warning(
'log directory for log file %s does not exist, check your settings! Only logging to stdout',
log_file)
def setup_logging():
if os.environ.get("SENTRY_SDK_URL"):
import sentry_sdk
sentry_sdk.init(os.environ.get("SENTRY_SDK_URL"))
# Configuration for which we need access to both settings and logging singletons should happen here
logging.verbosity = settings.config.getint("general", "log_verbosity")
logging.logger.setLevel(settings.config.get("general", "log_level"))
os.environ['TF_CPP_MIN_LOG_LEVEL'] = settings.config.get(
"machine_learning", "tensorflow_log_level")
# Log Handlers
log_file = settings.config.get("general", "log_file")
if os.path.exists(os.path.dirname(log_file)):
logging.add_file_handler(log_file)
else:
logging.logger.warning(
"log directory for log file %s does not exist, check your settings! Only logging "
+ "to stdout.", log_file)
pattern=test_filename)
unittest.TextTestRunner(verbosity=settings.config.getint(
"general", "log_verbosity")).run(suite)
sys.exit()
# Configuration for which we need access to both settings and logging singletons should happen here
logging.verbosity = settings.config.getint("general", "log_verbosity")
logging.logger.setLevel(settings.config.get("general", "log_level"))
os.environ['TF_CPP_MIN_LOG_LEVEL'] = settings.config.get(
"machine_learning", "tensorflow_log_level")
# Log Handlers
LOG_FILE = settings.config.get("general", "log_file")
if os.path.exists(os.path.dirname(LOG_FILE)):
logging.add_file_handler(LOG_FILE)
else:
logging.logger.warning(
"log directory for log file %s does not exist, check your settings! Only logging to stdout.",
LOG_FILE)
logging.logger.info("outliers.py started - contact: [email protected]")
logging.logger.info("run mode: " + settings.args.run_mode)
logging.print_generic_intro("initializing")
logging.logger.info("loaded " + str(len(settings.loaded_config_paths)) +
" configuration files")
if settings.failed_config_paths:
logging.logger.warning("failed to load " +
str(len(settings.failed_config_paths)) +
from analyzers import beaconing_generic
##############
# Entrypoint #
##############
# Configuration for which we need access to both settings and logging singletons should happen here
logging.verbosity = settings.config.getint("general", "log_verbosity")
logging.logger.setLevel(settings.config.get("general", "log_level"))
os.environ['TF_CPP_MIN_LOG_LEVEL'] = settings.config.get(
"machine_learning", "tensorflow_log_level")
# Log Handlers
log_file = settings.config.get("general", "log_file")
if os.path.exists(os.path.dirname(log_file)):
logging.add_file_handler(log_file)
else:
logging.logger.warning(
"log directory for log file " + log_file +
" does not exist, check your settings! Only logging to stdout.")
logging.logger.info("outliers.py started - contact: [email protected]")
logging.logger.info("run mode: " + settings.args.run_mode)
logging.print_generic_intro("initializing")
def perform_analysis():
test_generic.perform_analysis()
beaconing_generic.perform_analysis()
metrics_generic.perform_analysis()
simplequery_generic.perform_analysis()
