如何使用pickle保存dict(或任何其他Python对象)?

我已经浏览了Python文档提供的信息，但我还是有点困惑。有人可以发布一个示例代码，编写一个新文件，然后使用pickle将字典转储到其中吗?

当前回答

一般来说，除非字典中只有简单的对象，如字符串和整数，否则pickle字典将会失败。

Python 2.7.9 (default, Dec 11 2014, 01:21:43) 
[GCC 4.2.1 Compatible Apple Clang 4.1 ((tags/Apple/clang-421.11.66))] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> from numpy import *
>>> type(globals())     
<type 'dict'>
>>> import pickle
>>> pik = pickle.dumps(globals())
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/pickle.py", line 1374, in dumps
    Pickler(file, protocol).dump(obj)
  File "/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/pickle.py", line 224, in dump
    self.save(obj)
  File "/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/pickle.py", line 286, in save
    f(self, obj) # Call unbound method with explicit self
  File "/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/pickle.py", line 649, in save_dict
    self._batch_setitems(obj.iteritems())
  File "/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/pickle.py", line 663, in _batch_setitems
    save(v)
  File "/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/pickle.py", line 306, in save
    rv = reduce(self.proto)
  File "/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/copy_reg.py", line 70, in _reduce_ex
    raise TypeError, "can't pickle %s objects" % base.__name__
TypeError: can't pickle module objects
>>>

即使是一个非常简单的字典也经常会失败。这取决于内容。

>>> d = {'x': lambda x:x}
>>> pik = pickle.dumps(d)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/pickle.py", line 1374, in dumps
    Pickler(file, protocol).dump(obj)
  File "/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/pickle.py", line 224, in dump
    self.save(obj)
  File "/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/pickle.py", line 286, in save
    f(self, obj) # Call unbound method with explicit self
  File "/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/pickle.py", line 649, in save_dict
    self._batch_setitems(obj.iteritems())
  File "/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/pickle.py", line 663, in _batch_setitems
    save(v)
  File "/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/pickle.py", line 286, in save
    f(self, obj) # Call unbound method with explicit self
  File "/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/pickle.py", line 748, in save_global
    (obj, module, name))
pickle.PicklingError: Can't pickle <function <lambda> at 0x102178668>: it's not found as __main__.<lambda>

然而，如果你使用一个更好的序列化器，如dill或cloudpickle，那么大多数字典都可以被pickle:

>>> import dill
>>> pik = dill.dumps(d)

或者如果你想保存你的字典到一个文件…

>>> with open('save.pik', 'w') as f:
...   dill.dump(globals(), f)
...

后一个例子与这里发布的任何其他好的答案是一样的(除了忽略了字典内容的可选择性之外，这些答案都是好的)。

2015-06-08 22:35:56

其他回答

如果你只是想把字典存储在一个文件中，可以像这样使用pickle

import pickle

a = {'hello': 'world'}

with open('filename.pickle', 'wb') as handle:
    pickle.dump(a, handle)

with open('filename.pickle', 'rb') as handle:
    b = pickle.load(handle)

如果您想在多个文件中保存和恢复多个字典缓存和存储更复杂的数据，使用anycache。泡菜周围的其他东西它都有

from anycache import anycache

@anycache(cachedir='path/to/files')
def myfunc(hello):
    return {'hello', hello}

的参数来存储不同的myfunc结果不同的文件在cachedir并重新加载它们。

有关更多详细信息，请参阅文档。

2017-11-19 20:49:09

import pickle

dictobj = {'Jack' : 123, 'John' : 456}

filename = "/foldername/filestore"

fileobj = open(filename, 'wb')

pickle.dump(dictobj, fileobj)

fileobj.close()

2013-12-05 12:40:49

>>> import pickle
>>> with open("/tmp/picklefile", "wb") as f:
...     pickle.dump({}, f)
...

通常情况下，最好使用cPickle实现

>>> import cPickle as pickle
>>> help(pickle.dump)
Help on built-in function dump in module cPickle:

dump(...)
    dump(obj, file, protocol=0) -- Write an object in pickle format to the given file.

    See the Pickler docstring for the meaning of optional argument proto.

2012-06-27 02:16:23

import pickle

your_data = {'foo': 'bar'}

# Store data (serialize)
with open('filename.pickle', 'wb') as handle:
    pickle.dump(your_data, handle, protocol=pickle.HIGHEST_PROTOCOL)

# Load data (deserialize)
with open('filename.pickle', 'rb') as handle:
    unserialized_data = pickle.load(handle)

print(your_data == unserialized_data)

HIGHEST_PROTOCOL的优点是文件变得更小。这使得解腌有时要快得多。

重要提示:pickle的最大文件大小约为2GB。

替代方法

import mpu
your_data = {'foo': 'bar'}
mpu.io.write('filename.pickle', data)
unserialized_data = mpu.io.read('filename.pickle')

选择格式

CSV:超简单格式(读写) JSON:适合编写人类可读的数据;非常常用(读和写) YAML: YAML是JSON的超集，但更容易阅读(读写，JSON和YAML的比较) pickle: Python序列化格式(读和写) MessagePack (Python包):更紧凑的表示(读和写) HDF5 (Python包):适合矩阵(读和写) XML:也存在*叹*(读和写)

对于您的应用程序，以下内容可能很重要:

其他编程语言的支持读写能力紧凑性(文件大小)

请参见:数据序列化格式的比较

如果您正在寻找一种创建配置文件的方法，您可能想要阅读我的简短文章Python中的配置文件

2015-10-20 19:49:21