Exception handling is often not handled correctly in software, especially when there are multiple sources of exceptions; data flow analysis of 5 million lines of Java code found over 1300 exception handling defects.[15] Citing multiple prior studies by others (1999–2004) and their own results, Weimer and Necula wrote that a significant problem with exceptions is that
Compared to conditionals, programming by Exception is slow. You can use the timeit module (or the IPython %timeit magic function) to run comparative performance benchmarks. https://en.wikipedia.org/wiki/Coding_by_exception : https://en.wikipedia.org/wiki/Exception_handling#Criticism : they "create hidden control-flow paths that are difficult for programmers to reason about".[15]:8:27
Go was initially released with exception handling explicitly omitted,
** advise using only for unrecoverable errors that should halt the entire
with the developers arguing that it obfuscated control flow.[16] Later, the exception-like panic/recover mechanism was added to the language, which the Go authors process.[17][18][19][20] **
Exceptions, as unstructured flow, increase the risk of resource leaks
(such as escaping a section locked by a mutex, or one temporarily holding a
file open) or inconsistent state. There are various techniques for resource
management in the presence of exceptions, most commonly combining the
dispose pattern with some form of unwind protection (like a finally
clause), which automatically releases the resource when control exits a
section of code.
[Emphasis added]
Neither of these documents advise against using Exceptions for control flow:
- https://docs.python.org/3/tutorial/errors.html#exceptions
- https://docs.python.org/3/library/exceptions.html
One alternative to Exceptions is to return a (value, err) tuple and have
conditionals for each possible value of err.
(value, err) = func()
if err is not None:
# [...]
On Tue, Oct 13, 2020 at 1:10 PM Wes Turner
Exception.args holds the arguments passed to the exception.
You could add type checking with dataclass, or you can just access Exception.args or sys.exc_info().args:
```python class Exception2(Exception): pass
try: raise Exception2('error str', dict(a='1', b=2)) except Exception2 as e: print(('args', e.args)) assert e.args[0] == 'error str' assert e.args[1] == dict(a='1', b=2)
import sys type_, value, traceback = sys.exc_info() assert value.args[0] == 'error str' assert value.args[1] == dict(a='1', b=2)
# ('args', ('error str', {'a': '1', 'b': 2})) ```
On Tue, Oct 13, 2020 at 12:56 PM David Mertz
wrote: On Tue, Oct 13, 2020 at 6:18 AM Steven D'Aprano
wrote: I don't think that a two line class (perhaps a couple of extra lines if you give it a docstring) justifies the name "boilerplate":
class MySpecialException(Exception): pass
I think that in 22 years of using Python, I have never written an exception that took more than these two lines of code.
Heck, I even have my memory jogged of string exceptions reading this. When did those go away fully, 1.5.2? 2.1?
I DID in the discussion, immediately think of making an exception a dataclass, as someone else replied with. I guess if you want cargo in your exception, that's a pretty good way to do it. But really the ONLY thing I ever want in an exception is an inheritance tree. An exception feels like a really unnatural way to pass around data (that said, there are a few exceptions written by other libraries where some attribute or another is useful in my except blocks. Perhaps I should consider that, beyond inspecting the traceback when needed.
If you really want a snazzy highly-parameterized exception, write it yourself as a class factory. I won't particularly like the antipattern, but it's available now.
if some_bad_thing: raise ExceptionMaker("BadStuffErrror", details, plus, more_details)
Implementation of 'ExceptionMaker' left to readers. But it's possible to write once.
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