Convenience facilities for managing exceptions.
Project description
Convenience facilities for managing exceptions.
Latest release 20221228: Get warning etc from cs.gimmicks, breaks circular import with cs.logutils.
Function exc_fold(*da, **dkw)
Decorator to catch specific exception types and return a defined default value.
Function logexc(func)
Decorator to log exceptions and reraise.
Function logexc_gen(genfunc)
Decorator to log exceptions and reraise for generators.
Function LogExceptions(conceal=False)
Wrapper for NoExceptions
which reports exceptions and optionally
suppresses them.
Function noexc(func)
Decorator to wrap a function which should never raise an exception. Instead, any raised exception is attempted to be logged.
A significant side effect is of course that if the function raises an
exception it now returns None
.
My primary use case is actually to wrap logging functions,
which I have had abort otherwise sensible code.
Function noexc_gen(func)
Decorator to wrap a generator which should never raise an exception. Instead, any raised exception is attempted to be logged and iteration ends.
My primary use case is wrapping generators chained in a pipeline, as in cs.later.Later.pipeline.
Class NoExceptions
A context manager to catch all exceptions and log them.
Arguably this should be a bare try...except but that's syntacticly
noisy and separates the catch from the top.
For simple function calls return_exc_info()
is probably better.
Method NoExceptions.__init__(self, handler)
:
Initialise the NoExceptions
context manager.
The handler
is a callable which
expects (exc_type,exc_value,traceback)
and returns True
or False
for the __exit__
method of the manager.
If handler
is None
, the __exit__
method
always returns True
, suppressing any exception.
Function return_exc_info(func, *args, **kwargs)
Run the supplied function and arguments.
Return (func_return, None)
in the case of successful operation
and (None, exc_info)
in the case of an exception.
exc_info
is a 3-tuple of (exc_type, exc_value, exc_traceback)
as returned by sys.exc_info()
.
If you need to protect a whole suite and would rather not move it
into its own function, consider the NoExceptions context manager.
Function returns_exc_info(func)
Decorator function to wrap functions whose exceptions should be caught, such as inside event loops or worker threads.
It causes a function to return (func_return, None)
in the case of successful operation
and (None, exc_info)
in the case of an exception.
exc_info
is a 3-tuple of (exc_type, exc_value, exc_traceback)
as returned by sys.exc_info()
.
Function safe_property(func)
Substitute for @property which lets AttributeErrors escape as RuntimeErrors.
Function transmute(*da, **dkw)
Decorator to transmute an inner exception to another exception type.
The motivating use case is properties in a class with a
__getattr__
method;
if some inner operation of the property function raises AttributeError
then the property is bypassed in favour of __getattr__
.
Confusion ensues.
In principle this can be an issue with any exception raised from "deeper" in the call chain, which can be mistaken for a "shallow" exception raised by the function itself.
Function unattributable(func)
Decorator to transmute AttributeError
into a RuntimeError
.
Function unimplemented(func)
Decorator for stub methods that must be implemented by a stub class.
Release Log
Release 20221228: Get warning etc from cs.gimmicks, breaks circular import with cs.logutils.
Release 20221207: @unattributable: bugfix decorator construction to accomodate callable() @decorator precheck.
Release 20210123: @transmute: refactor to raise chained exceptions in Python 3+.
Release 20190812: LogExceptions: drop stack trace noise.
Release 20190220: New decorator @exc_fold to catch particular exceptions, log an error and return a defined value.
Release 20190101: @logexc: handle missing func.name.
Release 20170904: Minor updates, improved docstring.
Release 20160828:
- @unattributable and @safe_property decorators, used to protect properties from inner AttributeErrors.
- Improved exception practices.
Release 20150118: metadata updates
Release 20150110: Initial distinfo for pypi release.
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