最近学习了python的错误处理和几种测试方法
1 try except
可以通过try except方式捕捉异常
try:
print('try...')
r = 10/0
print('result is :', r)
except ZeroDiversionError as e:
print('except is :', e)
finally:
print('finally ...')
print('END')
可以捕捉不同类型的错误，编写多个except
try:
print('try...')
r = 10/int('a')
print('result is: ', r)
except ValueError as e:
print('ValueError : ', e)
except ZeroDiversionError as e:
print('ZeroDivisionError is : ', e)
finally:
print('finally ...')
print('END')
try except同样支持else结构
try:
print('try... ')
r = 10/int('2')
print('result is : ', r)
except ValueError as e:
print('ValueError : ', e)
except ZeroDivisionError as e:
print('ZeroDivisionError is : ', e)
else:
print('no error')
finally:
print('finally ...')
print('END')
某个函数调用出现异常，在上层同样可以捕获到
def foo(s):
return 10/int(s)
def bar(s):
return foo(s) * 2
def main():
try:
bar('0')
except Exception as e:
print('Exception is : ', e)
finally:
print('finally...')
main()
2 logging
python 提供打日志方式输出异常，并且不会因为出现异常导致程序中断
import logging
def foo(s):
return 10/int(s)
def bar(s):
return foo(s) * 2
def main():
try:
bar('0')
except Exception as e:
logging.exception(e)
main()
print('END')
如果想要将异常处理的更细致，可以自定义一个异常类，继承于几种错误类，如ValueError等，在可能出现问题的地方将错误抛出来
class FooError(ValueError):
pass
def foo(s):
n = int(s)
if n == 0:
raise FooError('invalid error is : %s' %s)
return 10/n
foo('0')
错误可以一层一层向上抛，直到有上层能处理这个错误为止
def foo(s):
n = int(s)
if n==0:
raise ValueError('invalid error is: %s' %s)
return 10/n
def bar():
try:
foo('0')
except ValueError as e:
print('ValueError')
raise
bar()
logging可以设置不同的级别,通过basicConfig可以设置
import logging
logging.basicConfig(level=logging.INFO)
def foo(s):
n = int(s)
return 10/n
def main():
m = foo('0')
logging.info('n is : %d' %m)
main()
3 断言assert
大部分语言都支持assert，python也一样，在可能出错的地方写assert，会在异常出现时使程序终止
def foo(s):
n = int(s)
assert n != 0 ,'n is zero'
return 10/n
def main():
foo('0')
main()
4 pdb调试和set_trace
pdb调试用 python -m pdb 文件名.py, 单步执行敲n,退出为q
python 可以在代码里设置断点，在程序自动执行到断点位置暂停,暂停在set_trace的代码行
import pdb
def foo(s):
n = int(s)
pdb.set_trace()
return 10/n
def main():
m = foo('0')
main()
5 单元测试
先实现一个自己定义的Dict类，将文件保存为mydict.py
class Dict(dict):
def __init__(self, **kw):
super(Dict, self).__init__(**kw)
def __getattr__(self, key):
try:
return self[key]
except Exception as e:
raise AttributeError('AttributeError is :%s', e)
def __setattr__(self, key, value):
self[key] = value
python 提供了单元测试的类，开发者可以继承unittest.Test实现特定的测试类,下面实现Dict的单元测试类，保存为unittestdict.py
import unittest
from mydict import Dict
class TestDict(unittest.TestCase):
def setUp(self):
print('setUp...')
def tearDown(self):
print('tear Down...')
def test_init(self):
d = Dict(a='testa', b = 1)
self.assertEqual(d.a, 'testa')
self.assertEqual(d.b, 1)
self.assertTrue(isinstance(d, dict))
def test_key(self):
d = Dict()
d['name'] = 'hmm'
self.assertEqual(d.name, 'hmm')
def test_attr(self):
d = Dict()
d.name = 'hmm'
self.assertEqual(d['name'], 'hmm')
self.assertTrue('name' in d)
def test_attrerror(self):
d = Dict()
with self.assertRaises(AttributeError):
value = d.empty
def test_keyerror(self):
d = Dict()
with self.assertRaises(AttributeError):
value = d['empty']
if __name__ == '__main__':
unittest.main()
运行unittest.py可以检测mydict中Dict类是否有错误
6 文档测试
文档测试在代码中按照特定格式编写python输入和期待的输出，通过python提供的文档测试类，实现测试代码的目的
class Dict(dict):
'''
>>> d1 = Dict()
>>> d1['x'] = 100
>>> d1.x
100
>>> d1.y = 200
>>> d1['y']
200
>>> d2=Dict(a=1,b=2,c='m')
>>> d2.c
'm'
'''
def __init__(self, **kw):
super(Dict,self).__init__(**kw)
def __getattr__(self,key):
try:
return self[key]
except KeyError:
raise AttributeError('AttributeError key is %s' %key)
def __setattr__(self,key,value):
self[key] = value
if __name__ == '__main__':
import doctest
doctest.testmod()
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