错误和异常#处理异常- docs.python.org

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.

我已经找到了…Else:在运行数据库查询并将这些查询的结果记录到相同风格/类型的单独数据库的情况下，构造非常有用。假设我有很多工作线程，它们都处理提交给队列的数据库查询

#in a long running loop
try:
    query = queue.get()
    conn = connect_to_db(<main db>)
    curs = conn.cursor()
    try:
        curs.execute("<some query on user input that may fail even if sanitized">)
    except DBError:
        logconn = connect_to_db(<logging db>)
        logcurs = logconn.cursor()
        logcurs.execute("<update in DB log with record of failed query")
        logcurs.close()
        logconn.close()
    else:

        #we can't put this in main try block because an error connecting
        #to the logging DB would be indistinguishable from an error in 
        #the mainquery 

        #We can't put this after the whole try: except: finally: block
        #because then we don't know if the query was successful or not

        logconn = connect_to_db(<logging db>)
        logcurs = logconn.cursor()
        logcurs.execute("<update in DB log with record of successful query")
        logcurs.close()
        logconn.close()
        #do something in response to successful query
except DBError:
    #This DBError is because of a problem with the logging database, but 
    #we can't let that crash the whole thread over what might be a
    #temporary network glitch
finally:
    curs.close()
    conn.close()
    #other cleanup if necessary like telling the queue the task is finished

当然，如果您能够区分可能抛出的异常，则不必使用这种方法，但是如果代码对成功的代码段的响应可能会抛出与成功的代码段相同的异常，并且您不能让第二个可能的异常消失，或者在成功时立即返回(在我的例子中，这会杀死线程)，那么这种方法就会派上用场。

也许它的用法是:

#debug = []

def debuglog(text, obj=None):
    " Simple little logger. "
    try:
        debug   # does global exist?
    except NameError:
        pass    # if not, don't even bother displaying
    except:
        print('Unknown cause. Debug debuglog().')
    else:
        # debug does exist.
        # Now test if you want to log this debug message
        # from caller "obj"
        try:
            if obj in debug:
                print(text)     # stdout
        except TypeError:
            print('The global "debug" flag should be an iterable.')
        except:
            print('Unknown cause. Debug debuglog().')

def myfunc():
    debuglog('Made it to myfunc()', myfunc)

debug = [myfunc,]
myfunc()

也许这对你也有帮助。

假设您的编程逻辑取决于字典中是否有具有给定键的条目。你可以使用if…来测试dict.get(key)的结果。其他的……或者你可以这样做:

try:
    val = dic[key]
except KeyError:
    do_some_stuff()
else:
    do_some_stuff_with_val(val)

PEP 380中有一个很好的try-else示例。基本上，它归结为在算法的不同部分做不同的异常处理。

大概是这样的:

try:
    do_init_stuff()
except:
    handle_init_suff_execption()
else:
    try:
        do_middle_stuff()
    except:
        handle_middle_stuff_exception()

这允许您在异常发生的地方编写异常处理代码。

下面是我喜欢使用这种模式的另一个地方:

 while data in items:
     try
        data = json.loads(data)
     except ValueError as e:
        log error
     else:
        # work on the `data`