Python Raise Argument Error
Contents |
here for a quick overview of the site Help Center Detailed answers to any questions you might have Meta Discuss the python argparse argumenterror workings and policies of this site About Us Learn more about Stack python raise valueerror Overflow the company Business Learn more about hiring developers or posting ads with us Stack Overflow Questions Jobs
Python Exception Message
Documentation Tags Users Badges Ask Question x Dismiss Join the Stack Overflow Community Stack Overflow is a community of 6.2 million programmers, just like you, helping each other. Join them;
Python Custom Exception
it only takes a minute: Sign up Which exception should I raise on bad/illegal argument combinations in Python? up vote 236 down vote favorite 26 I was wondering about the best practices for indicating invalid argument combinations in Python. I've come across a few situations where you have a function like so: def import_to_orm(name, save=False, recurse=False): """ :param name: python exception stack trace Name of some external entity to import. :param save: Save the ORM object before returning. :param recurse: Attempt to import associated objects as well. Because you need the original object to have a key to relate to, save must be `True` for recurse to be `True`. :raise BadValueError: If `recurse and not save`. :return: The ORM object. """ pass The only annoyance with this is that every package has its own, usually slightly differing BadValueError. I know that in Java there exists java.lang.IllegalArgumentException -- is it well understood that everybody will be creating their own BadValueErrors in Python or is there another, preferred method? python exception arguments share|improve this question edited Nov 2 '11 at 19:26 sth 128k33204309 asked Nov 1 '08 at 23:02 cdleary 27.4k40130178 add a comment| 4 Answers 4 active oldest votes up vote 245 down vote accepted I would just raise ValueError, unless you need a more specific exception.. def import_to_orm(name, save=False, recurse=False): if recurse and not save: raise ValueError("save must be True if recurse is True") There's really no point in doin
This module never needs to be imported explicitly: the exceptions are provided in the built-in namespace as well
What Is The Argument Of An Exception In Python Quiz
as the exceptions module. For class exceptions, in a python catch multiple exceptions try statement with an except clause that mentions a particular class, that clause also sys exc_info handles any exception classes derived from that class (but not exception classes from which it is derived). Two exception classes that are not related via subclassing http://stackoverflow.com/questions/256222/which-exception-should-i-raise-on-bad-illegal-argument-combinations-in-python are never equivalent, even if they have the same name. The built-in exceptions listed below can be generated by the interpreter or built-in functions. Except where mentioned, they have an "associated value" indicating the detailed cause of the error. This may be a string or a tuple containing several items of information https://docs.python.org/2/library/exceptions.html (e.g., an error code and a string explaining the code). The associated value is the second argument to the raise statement. If the exception class is derived from the standard root class BaseException, the associated value is present as the exception instance's args attribute. User code can raise built-in exceptions. This can be used to test an exception handler or to report an error condition "just like" the situation in which the interpreter raises the same exception; but beware that there is nothing to prevent user code from raising an inappropriate error. The built-in exception classes can be subclassed to define new exceptions; programmers are encouraged to derive new exceptions from the Exception class or one of its subclasses, and not from BaseException. More information on defining exceptions is available in the Python Tutorial under User-defined Exceptions. The following exceptions are only used as base classes for other exceptions
you have probably seen some. There are (at least) two distinguishable kinds of errors: syntax errors and exceptions. 8.1. Syntax Errors¶ Syntax errors, also known as parsing errors, are perhaps the most common kind of complaint you get https://docs.python.org/2.7/tutorial/errors.html while you are still learning Python: >>> while True print 'Hello world' File "
Cleaner Python: Use Exceptions Many programmers have had it drilled into their head that exceptions, in any language, should only be used in truly exceptional cases. They're wrong. The Python community's approach to exceptions leads to cleaner code that's easier to read. And that's without the monstrous hit to performance commonly associated with exceptions in other languages. EDIT: Updated with more useful exception idioms Using exceptions to write cleaner code? When I talk about "using exceptions", I'm specifically not referring to creating some crazy exception hierarchy for your package and raising exceptions at every possible opportunity. That will most certainly lead to unmaintainable and difficult to understand code. This notion has been widely discussed and is well summarized on Joel Spolsky's blog. Note: Python avoids much of the tension of the "error codes vs exceptions" argument. Between the ability to return multiple values from a function and the ability to return values of different types (e.g. None or something similar in the error case) the argument is moot. But this is besides the point. The style of exception usage I'm advocating is quite different. In short: take advantage of Python built-ins and standard library modules that already throw exceptions. Exceptions are built in to Python at the lowest levels. In fact, I guarantee your code is already using exceptions, even if not explicitly. Intermezzo: How the for statement works Any time you use for to iterate over an iterable (basically, all sequence types and anything that defines __iter__() or __getitem__()), it needs to know when to stop iterating. Take a look at the code below: words = ['exceptions', 'are', 'useful'] for word in words: print(word) How does for know when it's reached the last element in words and should stop trying to get more items? The answer may surprise you: the list raises a StopIteration exception. In fact, all iterables follow this pattern. When a for statement is first evaluated, it calls iter() on the objec