Delogger is a Python package that makes easy use of decided logging.
- It behaves like normal logging.
- Non-blocking logging using QueueHandler.
To install Delogger, use pip.
pip install delogger
from delogger.presets.debug import logger
if __name__ == "__main__":
logger.debug("debug msg")
logger.info("info msg")
logger.warning("warn msg")
logger.error("error msg")
logger.critical("critical msg")Output
File output (./log/20201010_164622.log)
2020-10-10 16:46:22.050 DEBUG debug_preset.py:4 <module> debug msg
2020-10-10 16:46:22.050 INFO debug_preset.py:5 <module> info msg
2020-10-10 16:46:22.051 WARN debug_preset.py:6 <module> warn msg
2020-10-10 16:46:22.051 ERROR debug_preset.py:7 <module> error msg
2020-10-10 16:46:22.051 CRIT debug_preset.py:8 <module> critical msg
and more samples
debug: Output color debug log and save log file.debug_stream: Output color debug log.output: Save log file and notify to slack.profiler: Same debug preset and seted profiles decorator.
CountRotatingFileMode: Backup count rotating.TimedRotatingFileMode: Same logging.handlers.TimedRotatingFileHandler.SlackWebhookMode: Log to slack. (Incomming webhook)SlackTokenMode: Log to slack. (token key)StreamColorDebugMode: Output color log. (debug and above)StreamDebugMode: Output noncolor log. (debug and above)StreamInfoMode: Output noncolor log. (info and above)PropagateMode: Set Setropagate true.
DELOGGER_NAME: logger name for presets.DELOGGER_FILEPATH: output log filepath for presets.DELOGGER_SLACK_WEBHOOK: send slack for presets.
Inject decorator into logger.
DEBUG 21:00:00 debug_log.py:32 START test args=('test',) kwargs={}
DEBUG 21:00:01 debug_log.py:39 END test return=value
Required line_profiler package.
DEBUG 21:38:22 line_profile.py:28 line_profiler result
Timer unit: 1e-06 s
Total time: 6.4e-05 s
File: test.py
Function: test at line 6
Line # Hits Time Per Hit % Time Line Contents
==============================================================
6 @logger.line_profile
7 def test(arg1):
8 101 43.0 0.4 67.2 for i in range(100):
9 100 21.0 0.2 32.8 pass
10 1 0.0 0.0 0.0 return i
Required memory_profiler package.
DEBUG 21:40:31 memory_profile.py:25 memory_profiler result
Filename: test.py
Line # Mem usage Increment Line Contents
================================================
6 37.96 MiB 37.96 MiB @logger.memory_profile
7 def test(arg1):
8 45.43 MiB 7.47 MiB a = [0] * 1000 * 1000
9 45.43 MiB 0.00 MiB for i in range(100):
10 45.43 MiB 0.00 MiB pass
11 45.43 MiB 0.00 MiB return i
Required line_profiler and memory_profiler package.
DEBUG 21:41:08 line_memory_profile.py:70 line, memory profiler result
Timer unit: 1e-06 s
Total time: 0.004421 s
File: test.py
Function: test at line 6
Line # Hits Time Per Hit % Time Mem usage Increment Line Contents
=========================================================================================
6 37.96 MiB 37.96 MiB @logger.line_memory_profile
7 def test(arg1):
8 1 4355.0 4355.0 98.5 45.43 MiB 7.47 MiB a = [0] * 1000 * 1000
9 101 33.0 0.3 0.7 45.43 MiB 0.00 MiB for i in range(100):
10 100 32.0 0.3 0.7 45.43 MiB 0.00 MiB pass
11 1 1.0 1.0 0.0 45.43 MiB 0.00 MiB return i
- It can adjust the timing of profile output
Required line_profiler package.
DEBUG 21:45:55 line_profile.py:67 line_profiler_stats result
Timer unit: 1e-06 s
Total time: 0.009081 s
File: test.py
Function: test at line 6
Line # Hits Time Per Hit % Time Line Contents
==============================================================
6 @logger.add_line_profile
7 def test(arg1):
8 2 8957.0 4478.5 98.6 a = [0] * 1000 * 1000
9 202 71.0 0.4 0.8 for i in range(100):
10 200 52.0 0.3 0.6 pass
11 2 1.0 0.5 0.0 return i