Python Class Error Handling
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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
Python Exception Class
of complaint you get while you are still learning Python: >>> while True print('Hello world') python exception message File "
Python Exception Stack Trace
‘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 python custom exception at the function print(), 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 python print exception will soon learn how to handle them in 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 "
Pages Local Site Map ------------------------ Rename Page Delete Page ------------------------ ------------------------ Remove Spam Revert to this revision ------------------------ SlideShow User Login Handling Exceptions The simplest way to handle exceptions is with a "try-except" block: 1 (x,y) = (5,0) 2 try: 3 z = x/y 4 except ZeroDivisionError: 5 print "divide by zero" If
Syntax For Generic Except Clause In Python
you wanted to examine the exception from code, you could have: 1 (x,y) = python try without except (5,0) 2 try: 3 z = x/y 4 except ZeroDivisionError as e: 5 z = e # representation: " 0x817426c>" 6 print z # output: "integer division or modulo by zero" General Error Catching Sometimes, you want to catch all errors that could possibly be generated, but usually you don't.In most cases, you want https://docs.python.org/3/tutorial/errors.html to be as specific as possible (CatchWhatYouCanHandle). In the first example above, if you were using a catch-all exception clause and a user presses Ctrl-C, generating a KeyboardInterrupt, you don't want the program to print "divide by zero". However, there are some situations where it's best to catch all errors. For example, suppose you are writing an extension module to a web service. You want the error information to output the https://wiki.python.org/moin/HandlingExceptions output web page, and the server to continue to run, if at all possible. But you have no idea what kind of errors you might have put in your code. In situations like these, you may want to code something like this: 1 import sys 2 try: 3 untrusted.execute() 4 except: # catch *all* exceptions 5 e = sys.exc_info()[0] 6 write_to_page( " Error: %sPython Try Except Else
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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 object being iterated over. This creates an iterator for the object, capable of returning the contents of the object in sequence. For the call to iter() to succeed, the object must either support the iteration protocol (by defining __iter__()) or the sequence protocol (by defining __getitem__()). As it happens, both the __iter__() and __getitem__() functions are required to raise an exception when the items to ite