Prerequisites: Decorators in Python, Logging in Python
Logging helps you to keep track of the program/application you run. It stores the outputs/errors/messages/exceptions anything you want to store. Program executions can be debugged with the help of print statements during the runtime of code. But the code is not elegant and not a good practice. Logging is a standard process an application to follow to store the process in a log file that would help to analyze/debug in the future/unexpected situations.
Logging for exceptions
For a logger, we have different levels of logging a message. As the article is limited to exception logging, we will go with the ‘INFO’ level log message which helps us to check if the code is working as expected. If there is an exception, it will store exception into the log file using logger object logger.exception(“some exception raised”)
Below is the implementation.
import logging from functools import wraps def create_logger(): #create a logger object logger = logging.getLogger('exc_logger') logger.setLevel(logging.INFO) #create a file to store all the # logged exceptions logfile = logging.FileHandler('exc_logger.log') fmt = '%(asctime)s - %(name)s - %(levelname)s - %(message)s' formatter = logging.Formatter(fmt) logfile.setFormatter(formatter) logger.addHandler(logfile) return logger logger = create_logger() # you will find a log file # created in a given path print(logger) def exception(logger): # logger is the logging object # exception is the decorator objects # that logs every exception into log file def decorator(func): @wraps(func) def wrapper(*args, **kwargs): try: return func(*args, **kwargs) except: issue = "exception in "+func.__name__+"\n" issue = issue+"-------------------------\ ------------------------------------------------\n" logger.exception(issue) raise return wrapper return decorator @exception(logger) def divideStrByInt(): return "krishna"/7 # Driver Code if __name__ == '__main__': divideStrByInt() |
Output:
