如何使用 pickle 保存字典（或任何其他 Python 对象）？

Question

I have looked through the information that the Python docs give, but I'm still a little confused. Could somebody post sample code that would write a new file then use pickle to dump a dictionary into it?

Answer 1

Try this:

import pickle

a = {'hello': 'world'}

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

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

print a == b

Answer 2

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)

The advantage of HIGHEST_PROTOCOL is that files get smaller. This makes unpickling sometimes much faster.

Important notice : The maximum file size of pickle is about 2GB.

Alternative way

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

Alternative Formats

• CSV: Super simple format ( read & write )
• JSON: Nice for writing human-readable data; VERY commonly used ( read & write )
• YAML: YAML is a superset of JSON, but easier to read ( read & write , comparison of JSON and YAML )
• pickle: A Python serialization format ( read & write )
• MessagePack ( Python package ): More compact representation ( read & write )
• HDF5 ( Python package ): Nice for matrices ( read & write )
• XML: exists too *sigh* ( read & write )

For your application, the following might be important:

• Support by other programming languages
• Reading / writing performance
• Compactness (file size)

See also: Comparison of data serialization formats

In case you are rather looking for a way to make configuration files, you might want to read my short article Configuration files in Python

Answer 3

# Save a dictionary into a pickle file.
import pickle

favorite_color = {"lion": "yellow", "kitty": "red"}  # create a dictionary
pickle.dump(favorite_color, open("save.p", "wb"))  # save it into a file named save.p

# -------------------------------------------------------------
# Load the dictionary back from the pickle file.
import pickle

favorite_color = pickle.load(open("save.p", "rb"))
# favorite_color is now {"lion": "yellow", "kitty": "red"}

Answer 4

In general, pickling a dict will fail unless you have only simple objects in it, like strings and integers.

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
>>> 

Even a really simple dict will often fail. It just depends on the contents.

>>> 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>

However, if you use a better serializer like dill or cloudpickle , then most dictionaries can be pickled:

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

Or if you want to save your dict to a file...

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

The latter example is identical to any of the other good answers posted here (which aside from neglecting the picklability of the contents of the dict are good).

Answer 5

Simple way to dump a Python data (eg dictionary) to a pickle file.

import pickle

your_dictionary = {}

pickle.dump(your_dictionary, open('pickle_file_name.p', 'wb'))

Answer 6

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

normally it's preferable to use the cPickle implementation

>>> 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.

Answer 7

If you just want to store the dict in a single file, use pickle like that

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)

If you want to save and restore multiple dictionaries in multiple files for caching and store more complex data, use anycache . It does all the other stuff you need around pickle

from anycache import anycache

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

Anycache stores the different myfunc results depending on the arguments to different files in cachedir and reloads them.

See the documentation for any further details.

Answer 8

import pickle

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

filename = "/foldername/filestore"

fileobj = open(filename, 'wb')

pickle.dump(dictobj, fileobj)

fileobj.close()

Answer 9

FYI, Pandas has a method to save pickles now.

I find it easier.

pd.to_pickle(object_to_save,'/temp/saved_pkl.pickle' )

Answer 10

If you want to handle writing or reading in one line without file opening:

  import joblib

  my_dict = {'hello': 'world'}

  joblib.dump(my_dict, "my_dict.pickle") # write pickle file
  my_dict_loaded = joblib.load("my_dict.pickle") # read pickle file

Answer 11

I've found pickling confusing (possibly because I'm thick). I found that this works, though:

myDictionaryString=str(myDictionary)

Which you can then write to a text file. I gave up trying to use pickle as I was getting errors telling me to write integers to a .dat file. I apologise for not using pickle.