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authorScott <[email protected]>2022-01-17 20:30:08 -0800
committerScott <[email protected]>2022-01-17 20:30:08 -0800
commit142ec2f33945b549fbc9c2decd179cc0581cb55c (patch)
tree88eb2eaf38fc137ccb3e43b9647211eae3c0443a /logging_utils.py
parentff0c10dff77a141bfebcce592eef34d6b065bfa9 (diff)
Creates a function_utils and pull a function_identifer method into
it.
Diffstat (limited to 'logging_utils.py')
-rw-r--r--logging_utils.py29
1 files changed, 4 insertions, 25 deletions
diff --git a/logging_utils.py b/logging_utils.py
index ddea102..c04d76d 100644
--- a/logging_utils.py
+++ b/logging_utils.py
@@ -159,29 +159,6 @@ built_in_print = print
logging_initialized = False
-def function_identifier(f: Callable) -> str:
- """
- Given a callable function, return a string that identifies it.
- Usually that string is just __module__:__name__ but there's a
- corner case: when __module__ is __main__ (i.e. the callable is
- defined in the same module as __main__). In this case,
- f.__module__ returns "__main__" instead of the file that it is
- defined in. Work around this using pathlib.Path (see below).
-
- >>> function_identifier(function_identifier)
- 'logging_utils:function_identifier'
-
- """
- if f.__module__ == '__main__':
- from pathlib import Path
- import __main__
- module = __main__.__file__
- module = Path(module).stem
- return f'{module}:{f.__name__}'
- else:
- return f'{f.__module__}:{f.__name__}'
-
-
# A map from logging_callsite_id -> count of logged messages.
squelched_logging_counts: Mapping[str, int] = {}
@@ -200,7 +177,8 @@ def squelch_repeated_log_messages(squelch_after_n_repeats: int) -> Callable:
"""
def squelch_logging_wrapper(f: Callable):
- identifier = function_identifier(f)
+ import function_utils
+ identifier = function_utils.function_identifier(f)
squelched_logging_counts[identifier] = squelch_after_n_repeats
return f
return squelch_logging_wrapper
@@ -334,7 +312,8 @@ def logging_is_probabilistic(probability_of_logging: float) -> Callable:
"""
def probabilistic_logging_wrapper(f: Callable):
- identifier = function_identifier(f)
+ import function_utils
+ identifier = function_utils.function_identifier(f)
probabilistic_logging_levels[identifier] = probability_of_logging
return f
return probabilistic_logging_wrapper