Coverage for dynasor/logging_tools.py: 100%

1""" This module contains functions and variables to control dynasor's logging 

2 

3* `logger` - the module logger 

4""" 

5 

6import logging 

7import sys 

8 

9import numba 

10 

11 

12# This is the root logger of dynasor. 

13logger = logging.getLogger('dynasor') 

14 

15# Will process all levels of INFO or higher. This sets the default level. 

16logger.setLevel(logging.INFO) 

17 

18# If you know what you are doing you may set this to True. 

19logger.propagate = False 

20 

21# The dynasor logger will collect events from children and the default behavior 

22# is to print it directly to stdout. 

23ch = logging.StreamHandler(sys.stdout) 

24ch.setFormatter(logging.Formatter( 

25 r'%(levelname)s %(asctime)s: %(message)s', datefmt='%Y-%m-%d %H:%M:%S')) 

26logger.addHandler(ch) 

27 

28 

29def set_logging_level(level: str) -> None: 

30 """ 

31 Alters the logging verbosity logging is handled. 

32 

33 Possible values from least to most verbose: 

34 `CRITICAL`, `ERROR`, `WARNING`, `INFO`, `DEBUG`. 

35 

36 Parameters 

37 ---------- 

38 level 

39 Verbosity level; see `Python logging library 

40 <https://docs.python.org/3/library/logging.html>`_ for details. 

41 """ 

42 logger.setLevel(level) 

43 

44 

45_has_checked_numba_threading_layer = False 

46 

47 

48def warn_if_numba_threading_layer_is_slow() -> None: 

49 """ 

50 Emit a one-time warning if Numba has fallen back to the ``workqueue`` 

51 threading layer, which is available everywhere but not tuned for 

52 performance; installing `TBB <https://pypi.org/project/tbb/>`_ (``pip 

53 install tbb``) lets Numba pick a faster, fork-safe layer instead. 

54 

55 Numba only selects its threading layer lazily, the first time a 

56 parallel (``@numba.njit(parallel=True)``) kernel actually runs, so this 

57 is a no-op until that has happened at least once; call it right after 

58 such a kernel has run. 

59 """ 

60 global _has_checked_numba_threading_layer 

61 if _has_checked_numba_threading_layer: 

62 return 

63 try: 

64 layer = numba.threading_layer() 

65 except ValueError: 

66 # Threading layer not yet initialized; nothing to check yet. 

67 return 

68 _has_checked_numba_threading_layer = True 

69 if layer == 'workqueue': 

70 logger.warning( 

71 'Numba is using the "workqueue" threading layer, which is slower ' 

72 'than the alternatives; install TBB (`pip install tbb`) for ' 

73 'faster parallel CPU kernels.' 

74 )