Until now error messages haven't been more than mentioned, but if you have
tried out the examples you have probably seen some. There are (at least) two
distinguishable kinds of errors: syntax errors and exceptions.
Syntax Errors
Syntax errors, also known as parsing errors, are perhaps the most common kind
of complaint you get while you are still learning Python:
>>> while True print 'Hello world'
File "<stdin>", line 1, in ?
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,
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.
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 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 "<stdin>", line 1, in ?
ZeroDivisionError: integer division or modulo by zero
>>> 4 + spam*3
Traceback (most recent call last):
File "<stdin>", line 1, in ?
NameError: name 'spam' is not defined
>>> '2' + 2
Traceback (most recent call last):
File "<stdin>", 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 input.
Handling Exceptions
It is possible to write programs that handle selected exceptions. Look at the
following example, which asks the user for input until a valid integer has been
entered, but allows the user to interrupt the program (using Control-C
or whatever the operating system supports); note that a user-generated
interruption is signalled by raising the KeyboardInterrupt
exception.
>>> while True:
... try:
... x = int(raw_input("Please enter a number: "))
... break
... except ValueError:
... print "Oops! That was no valid number. Try again..."
...
The try statement works as follows.
First, the try clause (the statement(s) between the
try and except keywords)
is executed.
If no exception occurs, the except clause is skipped and
execution of the try statement is finished.
If an exception occurs during execution of the try clause, the rest of
the clause is skipped. Then if its type matches the exception named after
the except keyword, the except clause is executed,
and then execution continues after the try
statement.
If an exception occurs which does not match the exception named in the
except clause, it is passed on to outer try
statements; if no handler is found, it is an unhandled exception
and execution stops with a message as shown above.
A try statement may have more than one except
clause, to specify handlers for different exceptions. At most one handler will
be executed. Handlers only handle exceptions that occur in the corresponding try
clause, not in other handlers of the same try
statement. An except clause may name multiple exceptions as a parenthesized
tuple, for example:
The last except clause may omit the exception name(s), to serve as a
wildcard. Use this with extreme caution, since it is easy to mask a real
programming error in this way! It can also be used to print an error message and
then re-raise the exception (allowing a caller to handle the exception as well):
import sys
try:
f = open('myfile.txt')
s = f.readline()
i = int(s.strip())
except IOError, (errno, strerror):
print "I/O error(%s): %s" % (errno, strerror)
except ValueError:
print "Could not convert data to an integer."
except:
print "Unexpected error:", sys.exc_info()[0]
raise
The try ... except
statement has an optional else clause, which, when present, must follow
all except clauses. It is useful for code that must be executed if the try
clause does not raise an exception. For example:
for arg in sys.argv[1:]:
try:
f = open(arg, 'r')
except IOError:
print 'cannot open', arg
else:
print arg, 'has', len(f.readlines()), 'lines'
f.close()
The use of the else clause is better than adding
additional code to the try clause because it avoids
accidentally catching an exception that wasn't raised by the code being
protected by the try ... except
statement.
When an exception occurs, it may have an associated value, also known as the
exception's argument. The presence and type of the argument depend on
the exception type.
The except clause may specify a variable after the exception name (or tuple).
The variable is bound to an exception instance with the arguments stored in
instance.args. For convenience, the exception instance defines
__getitem__ and __str__ so the
arguments can be accessed or printed directly without having to reference
.args.
But use of .args is discouraged. Instead, the preferred use is
to pass a single argument to an exception (which can be a tuple if multiple
arguments are needed) and have it bound to the message attribute.
One may also instantiate an exception first before raising it and add any
attributes to it as desired.
>>> try:
... raise Exception('spam', 'eggs')
... except Exception, inst:
... print type(inst) # the exception instance
... print inst.args # arguments stored in .args
... print inst # __str__ allows args to printed directly
... x, y = inst # __getitem__ allows args to be unpacked directly
... print 'x =', x
... print 'y =', y
...
<type 'exceptions.Exception'>
('spam', 'eggs')
('spam', 'eggs')
x = spam
y = eggs
If an exception has an argument, it is printed as the last part (`detail') of
the message for unhandled exceptions.
Exception handlers don't just handle exceptions if they occur immediately in
the try clause, but also if they occur inside functions that are called (even
indirectly) in the try clause. For example:
>>> def this_fails():
... x = 1/0
...
>>> try:
... this_fails()
... except ZeroDivisionError, detail:
... print 'Handling run-time error:', detail
...
Handling run-time error: integer division or modulo by zero
Raising Exceptions
The raise statement allows the programmer to force a
specified exception to occur. For example:
>>> raise NameError, 'HiThere'
Traceback (most recent call last):
File "<stdin>", line 1, in ?
NameError: HiThere
The first argument to raise names the exception to
be raised. The optional second argument specifies the exception's argument.
Alternatively, the above could be written as raise NameError('HiThere').
Either form works fine, but there seems to be a growing stylistic preference for
the latter.
If you need to determine whether an exception was raised but don't intend to
handle it, a simpler form of the raise statement allows
you to re-raise the exception:
Programs may name their own exceptions by creating a new exception class.
Exceptions should typically be derived from the Exception
class, either directly or indirectly. For example:
In this example, the default __init__ of
Exception has been overridden. The new behavior simply
creates the value attribute. This replaces the default behavior of
creating the args attribute.
Exception classes can be defined which do anything any other class can do,
but are usually kept simple, often only offering a number of attributes that
allow information about the error to be extracted by handlers for the exception.
When creating a module that can raise several distinct errors, a common practice
is to create a base class for exceptions defined by that module, and subclass
that to create specific exception classes for different error conditions:
class Error(Exception):
"""Base class for exceptions in this module."""
pass
class InputError(Error):
"""Exception raised for errors in the input.
Attributes:
expression -- input expression in which the error occurred
message -- explanation of the error
"""
def __init__(self, expression, message):
self.expression = expression
self.message = message
class TransitionError(Error):
"""Raised when an operation attempts a state transition that's not
allowed.
Attributes:
previous -- state at beginning of transition
next -- attempted new state
message -- explanation of why the specific transition is not allowed
"""
def __init__(self, previous, next, message):
self.previous = previous
self.next = next
self.message = message
Most exceptions are defined with names that end in ``Error,'' similar to the
naming of the standard exceptions.
Many standard modules define their own exceptions to report errors that may
occur in functions they define.
``Classes.''
Defining Clean-up Actions
The try statement has another optional clause which
is intended to define clean-up actions that must be executed under all
circumstances. For example:
A finally clause is always executed before leaving the
try statement, whether an exception has occurred or
not. When an exception has occurred in the try clause
and has not been handled by an except clause (or it has
occurred in a except or else
clause), it is re-raised after the finally clause has
been executed. The finally clause is also executed ``on
the way out'' when any other clause of the try
statement is left via a break,
continue or return statement. A more complicated
example (having except and finally
clauses in the same try statement works as of Python
2.5):
>>> def divide(x, y):
... try:
... result = x / y
... except ZeroDivisionError:
... print "division by zero!"
... else:
... print "result is", result
... finally:
... print "executing finally clause"
...
>>> divide(2, 1)
result is 2
executing finally clause
>>> divide(2, 0)
division by zero!
executing finally clause
>>> divide("2", "1")
executing finally clause
Traceback (most recent call last):
File "<stdin>", line 1, in ?
File "<stdin>", line 3, in divide
TypeError: unsupported operand type(s) for /: 'str' and 'str'
As you can see, the finally clause is executed in
any event. The TypeError raised by dividing two
strings is not handled by the except clause and
therefore re-raised after the finally clauses has been
executed.
In real world applications, the finally clause is
useful for releasing external resources (such as files or network connections),
regardless of whether the use of the resource was successful.
Predefined Clean-up Actions
Some objects define standard clean-up actions to be undertaken when the
object is no longer needed, regardless of whether or not the operation using the
object succeeded or failed. Look at the following example, which tries to open a
file and print its contents to the screen.
for line in open("myfile.txt"):
print line
The problem with this code is that it leaves the file open for an
indeterminate amount of time after the code has finished executing. This is not
an issue in simple scripts, but can be a problem for larger applications. The
with statement allows objects like files to be used in
a way that ensures they are always cleaned up promptly and correctly.
with open("myfile.txt") as f:
for line in f:
print line
After the statement is executed, the file f is always closed, even
if a problem was encountered while processing the lines. Other objects which
provide predefined clean-up actions will indicate this in their documentation.
Note: Since with
is a new language keyword, it must be enabled by executing from __future__
import with_statement in Python 2.5. From 2.6 on, it will always be
enabled.
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