4 ms·

Here is the greatest inconvenience of Python exceptions for me. Say you have to try 10 different methods, and you only need one to work. Then you have to write

by sslnx 8y ago

Here is the greatest inconvenience of Python exceptions for me. Say you have to try 10 different methods, and you only need one to work. Then you have to write 10 try...except blocks so that each next block is indented relative to previous. This creates unreadable code and does not scale for say 100 methods. The solution that came to mind is labeling try blocks and referring them in except blocks. For example: try as method1: method1() except@method1 try as method2: method2() except@method2 try as method3: method3() except@method3: raise NoMethodWorked()

jhayward 8y ago
You probably want to look in to try-except-else patterns.
deaddodo 8y ago
Who.....codes like this? Use a method dispatch instead, and have the dispatcher worry about throwing the exception: try: DispatchController.dispatch() except: raise DispatchFailed() And/or use a lookup table. Especially since methods, classes, decorators, etc are all first class citizens in Python.
akubera 8y ago
I can't think of a single time I've needed a large collection of "backup" methods in case of a chain of failures; I can't even think of an example which could scale to 100. Anyways, this solution does scale: methods = [method1, method2, method3, method4] for method in methods: try: method() except Exception: pass else: break else: raise NoMethodWorked() You can even pair specific exceptions to each method: methods = [(method1, TypeError), (method2, KeyError)] for m, e in methods: try: m() except e: ... But the whole thing really sounds like you're trying to do too much with one function and you really should rethink the whole structure of your code.
- sslnx 8y ago
  This is really helpful. Thank you.
CodeMage 8y ago
There are several solutions that occured to me off the top of my head, here's the simplest one: try: method1() return except Exception: # or a more specific exception type pass # try the next method try: method2() return except Exception: pass # ... try: method10() except Exception: raise NoMethodWorked() Seriously, there are so many ways to solve this in a readable, maintainable way, without resorting to introducing weird new syntax.

by sslnx 8y ago

jhayward 8y ago

You probably want to look in to try-except-else patterns.

deaddodo 8y ago

Who.....codes like this? Use a method dispatch instead, and have the dispatcher worry about throwing the exception: try: DispatchController.dispatch() except: raise DispatchFailed() And/or use a lookup table. Especially since methods, classes, decorators, etc are all first class citizens in Python.

akubera 8y ago

I can't think of a single time I've needed a large collection of "backup" methods in case of a chain of failures; I can't even think of an example which could scale to 100. Anyways, this solution does scale: methods = [method1, method2, method3, method4] for method in methods: try: method() except Exception: pass else: break else: raise NoMethodWorked() You can even pair specific exceptions to each method: methods = [(method1, TypeError), (method2, KeyError)] for m, e in methods: try: m() except e: ... But the whole thing really sounds like you're trying to do too much with one function and you really should rethink the whole structure of your code.

sslnx 8y ago
This is really helpful. Thank you.

CodeMage 8y ago

There are several solutions that occured to me off the top of my head, here's the simplest one: try: method1() return except Exception: # or a more specific exception type pass # try the next method try: method2() return except Exception: pass # ... try: method10() except Exception: raise NoMethodWorked() Seriously, there are so many ways to solve this in a readable, maintainable way, without resorting to introducing weird new syntax.