Logging and timing tests for Python functions.
pip install function_log
from function_log import log_this, show_log, time_log, time_this
Logging decorator - Logs function name, args, kwargs, first encountered error, function time and execution time to 'filename_log.json' if log file exists. If log file does not exist, it creates one
@log_this
def function_A():
import time
time.sleep(1)
@log_this
def function_B():
import time
time.sleep(1)
>>> function_A()
>>> [Logged function_A in path/to/file_log.json]
>>> function_B()
>>> [Logged function_B in path/to/file_log.json]
Returns current log file contents. If errors argument is True, returns only log file contents with encountered errors
>>> log = show_log()
>>> 0 - {'name': 'function_A', 'args': [], 'kwargs': {}, 'error': None, 'timer': 1.0011684894561768, 'timestamp': '2018/1/21 - 16:46:21'}
1 - {'name': 'function_B', 'args': [], 'kwargs': {}, 'error': None, 'timer': 1.000422716140747, 'timestamp': '2018/1/21 - 16:51:36'}
>>> log
>>> [{'name': 'function_A', 'args': [], 'kwargs': {}, 'error': None, 'timer': 1.0011684894561768, 'timestamp': '2018/1/21 - 16:46:21'},
{'name': 'function_B', 'args': [], 'kwargs': {}, 'error': None, 'timer': 1.000422716140747, 'timestamp': '2018/1/21 - 16:51:36'}]
Calculates mean time of each function and returns a dictionary of functions with function time and number of function iterations. If sort argument is True, returns a sorted dictionary of functions from fastest to slowest
>>> function_times = time_log()
>>> function_A: [1.000795602798462, 1]
function_B: [1.000351905822754, 1]
>>> function_times
>>> {'function_A': [1.000795602798462, 1], 'function_B': [1.000351905822754, 1]}
>>> sorted_function_times = time_log(True)
>>> function_B: [1.000351905822754, 1]
function_A: [1.000795602798462, 1]
>>> function_times
>>> {'function_B': [1.000351905822754, 1], 'function_A': [1.000795602798462, 1]}
Timing function - prints function time without logging -- /time_this(times to execute function, function, *args, **kwargs)/
def function_A(a,b):
a**b
>>> function_A_time = time_this(10,function_A,100,10000)
>>> ### Calculating Average Function Time ###
[Executed: 10 - Average Time: 0.0006852515631798894]
>>> function_A_time
>>> 0.0006852515631798894