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Trackback as a string

When Python encounters an error, it produces an error message called trackback. The trackback includes the error message, the line number of the line that caused the error, and the sequence of the functions calls that led to the error. This sequence of calls is called the call stack.

def spam():
    bacon()

def bacon():
    raise Exception('This is the error message.')

spam()

return:

Traceback (most recent call last):
  File "c:\Users\sol.rosca\Cloud\Cours\Programmation\Python\Python-Automate-the-boring-stuff\02.py", line 7, in <module>
    spam()
  File "c:\Users\sol.rosca\Cloud\Cours\Programmation\Python\Python-Automate-the-boring-stuff\02.py", line 2, in spam
    bacon()
  File "c:\Users\sol.rosca\Cloud\Cours\Programmation\Python\Python-Automate-the-boring-stuff\02.py", line 5, in bacon
    raise Exception('This is the error message.')
Exception: This is the error message.

Here we can see that the error happened on line 5, in the bacon() function. This particular call to bacon() canme from line 2, in the spam() function, which in turn was called on line 7.

The traceback is displayed by Python whenever a raised exception goes unhandled. But we can also obtain it as a string by calling the traceback.format_exec(). This function is useful if you want the information from an exception but also want an except statement to gracefully handle the exception. You will need to import Python’s traceback module before calling this function. For example, instead of crashing your program right when an exception occurs, you can write the traceback information to a log file and keep your program tunning. You can look at the log file later, when you’re ready to debug your program.

>>> import traceback 
>>> try:
         raise Exception('This is the error message.') 
except:
        errorFile = open('errorInfo.txt', 'w')
        errorFile.write(traceback.format_exc())         
        errorFile.close()         
        print('The traceback info was written to errorInfo.txt.')

116 
The traceback info was written to errorInfo.txt

Assert

Sanity check to make sure your code isn’t doing something obviously wrong. If the assert fails, then assertionError exception is raised.

>>> a = 22
>>> assert a == 22, '\'a\' doit valoir 22'
>>>
>>> a = 15
>>> assert a == 22, '\'a\' doit valoir 22'

return:

Traceback (most recent call last):
  File "c:\Users\sol.rosca\Cloud\Cours\Programmation\Python\Python-Automate-the-boring-stuff\02Assert\00.py", line 5, in <module>
    assert a == 22, '\'a\' doit valoir 22'
AssertionError: 'a' doit valoir 22

Logging & debugging

Le module logging permet de debugger facilement et d’éviter l’utilisation intempestive de print pour vérifier des valeurs.

import logging
logging.basicConfig(level=logging.DEBUG, format=' %(asctime)s - %(levelname)s - %(message)s')

logging.debug('Start of program')

def factorial(n):
    logging.debug('Start of factorial {}'.format(n))
    total = 1
    for i in range(1, n+1):
        total *= i
        logging.debug('i is {}, total is {}'.format(i, total))
    logging.debug('End of factorial({})'.format(n))
    return total

print(factorial(5))
logging.debug('End of program')

Don’t debug with print()

Taper import logging et logging.basicConfig(level=logging.DEBUG, format=' %(asctime)s - %(levelname)s - %(message)s') est peut-être vite fait chiant mais il permet de pas devoir “chasser” les print() de test une fois le programme débuggé. Aussi grace au call logging.disable(logging.CRITICAL) on peut désactiver les logs et avoir un affichage clair tout en gardant les point de check qui peuvent être utile plus tard.

Logging to a file

A la place d’afficher toutes ces informations dans la console, on peut les envoyer directement dans un fichier txt (ou log) grace à un paramètre de la fonction logging.basicConfig()

import logging
logging.basicConfig(filename='myProgramLog.txt', level=logging.DEBUG, format=' %(asctime)s - %(levelname)s - %(message)s')