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Python Exception Message

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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 "", line https://jeffknupp.com/blog/2013/02/06/write-cleaner-python-use-exceptions/ 1 while True print 'Hello world' ^ SyntaxError: invalid syntax The parser repeats the offending line and displays a little ‘arrow' pointing at the earliest point in the line where the error was detected. The error is caused by (or at least detected at) the token preceding the arrow: in the example, the error is detected at the keyword print, python raise since a colon (':') is missing before it. File name and line number are printed so you know where to look in case the input came from a script. 8.2. Exceptions¶ Even if a statement or expression is syntactically correct, it may cause an error when an attempt is made to execute it. Errors detected during execution are called exceptions and are not unconditionally fatal: you will soon learn how to handle them in python raise argument Python programs. Most exceptions are not handled by programs, however, and result in error messages as shown here: >>> 10 * (1/0) Traceback (most recent call last): File "", line 1, in ZeroDivisionError: integer division or modulo by zero >>> 4 + spam*3 Traceback (most recent call last): File "", line 1, in NameError: name 'spam' is not defined >>> '2' + 2 Traceback (most recent call last): File "", line 1, in TypeError: cannot concatenate 'str' and 'int' objects The last line of the error message indicates what happened. Exceptions come in different types, and the type is printed as part of the message: the types in the example are ZeroDivisionError, NameError and TypeError. The string printed as the exception type is the name of the built-in exception that occurred. This is true for all built-in exceptions, but need not be true for user-defined exceptions (although it is a useful convention). Standard exception names are built-in identifiers (not reserved keywords). The rest of the line provides detail based on the type of exception and what caused it. The preceding part of the error message shows the context where the exception happened, in the form of a stack traceback. In general it contains a stack traceback listing source lines; however, it will not display lines read from standard inpu

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

 

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