def test(): setup_logging() logger = logging.getLogger(__name__) logger.info('first log message')
import os import logging import functools import json from logging_setup import setup_logging setup_logging() from pika_client.environment_variables import EnvironmentVariable from pika_client.base import Connector from pika_client.consumers import BasePubSubConsumer LOGGER = logging.getLogger(__name__) FROM_EMAIL = os.environ.get('FROM_EMAIL', '*****@*****.**') class EmailConsumer(BasePubSubConsumer): def __init__( self, service, connector, app_id='EMAIL_SERVICE', queue='emails', durable=False, exchange='notifications_x', exchange_type='topic', routing_key='notifications.email'): super().__init__( connector, app_id=app_id, queue=queue, durable=durable,
beam_tx = alib.e3d_array_beam_stage1_dense_interp(az0=0, el0=90.0, I_0=10**4.2) beam_rx = alib.e3d_array_beam_interp(az0=0, el0=90.0, I_0=10**4.5) radar.set_beam(beam_tx, 'TX') radar.set_beam(beam_rx, 'RX') #plot_scan_for_object(obj, radar, 0.0, 1.5*24.0*3600.0) #radar.set_scan(rs2) #plot_scan_for_object(obj, radar, 0.0, 12.0*3600.0) #exit() logger = logging_setup.setup_logging( term_level=logging.DEBUG, logfile=False, ) det_times = get_detections(obj, radar, 0.0, 1.0 * 24.0 * 3600.0, logger=None) #print(det_times) total_dets = len(det_times[0]["snr"]) print('total_dets: {}'.format(total_dets)) if total_dets > 0: max_snr = n.max(det_times[0]["snr"])
""" results = {} for report in reports: if report in reports_train: res = 'train' else: prediction = predictions[reports_test.index(report)] res = '{} {}'.format( 'true' if prediction == report.category else 'false', 'positive' if prediction == CATEGORY_MALICIOUS else 'negative' ) results[report.name] = res with open(os.path.join(log_dir, 'results.json'), 'w') as f: json.dump(results, f, indent=4) joblib.dump(clf, os.path.join(log_dir, 'clf.pkl')) joblib.dump(ml.vec, os.path.join(log_dir, 'vec.pkl')) joblib.dump(ml.imp, os.path.join(log_dir, 'imp.pkl')) #joblib.dump(ml.scaler, os.path.join(log_dir, 'scaler.pkl')) """ # Precision = (# correctly predicted pos) / (# predicted pos), recall = (# correctly predicted pos) / (# actual positive) # logger.info(str(classification_report(y_test, predictions, target_names=['benign', 'malware']))) if __name__ == '__main__': from logging_setup import setup_logging log_dir = setup_logging(from_file=__file__) main()
def test_log(): setup_logging() logger = logging.getLogger(__name__) logger.info('Hello message')