我遇到了泡菜问题,代码就是:
import cPickle
class A(object):
def __init__(self):
self.a = 1
def methoda(self):
print(self.a)
class B(object):
def __init__(self):
self.b = 2
a = A()
self.b_a = a.methoda
def methodb(self):
print(self.b)
if __name__ == '__main__':
b = B()
with open('best_model1.pkl', 'w') as f:
cPickle.dump(b, f)
错误是:
文件" /usr/lib/python2.7/copy_reg.py",第70行,在_reduce_ex中 引发TypeError,"不能腌制%s对象" %base。名称 TypeError:无法腌制instancemethod对象
答案 0 :(得分:3)
如果您使用dill
代替cPickle
,则可以。
>>> import dill
>>>
>>> class A(object):
... def __init__(self):
... self.a = 1
... def methods(self):
... print(self.a)
...
>>>
>>> class B(object):
... def __init__(self):
... self.b = 2
... a = A()
... self.b_a = a.methods
... def methodb(self):
... print(self.b)
...
>>> b = B()
>>> b_ = dill.dumps(b)
>>> _b = dill.loads(b_)
>>> _b.methodb()
2
>>>
另见: Can't pickle <type 'instancemethod'> when using python's multiprocessing Pool.map()
答案 1 :(得分:0)
此外,当安装莳萝时,泡菜可以使用,但照常不能使用cPickle。
import cPickle, pickle
class A(object):
def __init__(self):
self.a = 1
def methoda(self):
print(self.a)
class B(object):
def __init__(self):
self.b = 2
a = A()
self.b_a = a.methoda
def methodb(self):
print(self.b)
# try using cPickle
try:
c = cPickle.dumps(b)
d = cPickle.loads(c)
except Exception as err:
print('Unable to use cPickle (%s)'%err)
else:
print('Using cPickle was successful')
print(b)
print(d)
# try using pickle
try:
c = pickle.dumps(b)
d = pickle.loads(c)
except Exception as err:
print('Unable to use pickle (%s)'%err)
else:
print('Using pickle was successful')
print(b)
print(d)
>>> Unable to use cPickle (can't pickle instancemethod objects)
>>> Using pickle was successful
>>> <__main__.B object at 0x10e9b84d0>
>>> <__main__.B object at 0x13df07190>
无论出于何种原因,cPickle都不只是酱菜的C版本快100倍,而是有一些差异