Decorator for retrying a function N times in case some specified exception occurs.
Project description
# retry\_on\_exceptions decorator
Decorator for retrying a function N times by catching one of the specified exceptions and then retrying.
Specially useful for functions that throws errors sporadically, like ones that depends on external resources as web APIs, databases, etc.
Usage:
from retry import retry_on_exceptions
current_try = 0
@retry_on_exceptions(types=[ZeroDivisionError, KeyError], tries=3)
def test():
global current_try
current_try += 1
if current_try == 1:
return 1 / 0
elif current_try == 2:
return dict()['key']
else:
return "Got it on last try!"
if __name__ == "__main__":
print test()
The code above prints (if root logger is active and on debug level):
- Retrying function test
- Retrying function test
- Last try... and I will raise up whatever exception is raised
- Got it on last try!
Optionally, you can also specify a delay (a float in seconds), making the current thread sleep between tries:
@retry_on_exceptions(types=[urllib2.URLError], tries=3, delay=3.5)
Decorator for retrying a function N times by catching one of the specified exceptions and then retrying.
Specially useful for functions that throws errors sporadically, like ones that depends on external resources as web APIs, databases, etc.
Usage:
from retry import retry_on_exceptions
current_try = 0
@retry_on_exceptions(types=[ZeroDivisionError, KeyError], tries=3)
def test():
global current_try
current_try += 1
if current_try == 1:
return 1 / 0
elif current_try == 2:
return dict()['key']
else:
return "Got it on last try!"
if __name__ == "__main__":
print test()
The code above prints (if root logger is active and on debug level):
- Retrying function test
- Retrying function test
- Last try... and I will raise up whatever exception is raised
- Got it on last try!
Optionally, you can also specify a delay (a float in seconds), making the current thread sleep between tries:
@retry_on_exceptions(types=[urllib2.URLError], tries=3, delay=3.5)
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