如何使用 pickle 保存字典（或任何其他 Python 对象）？

Question

我已经查看了Python docs 提供的信息，但我仍然有点困惑。有人可以发布示例代码来编写一个新文件，然后使用 pickle 将字典转储到其中吗？

Answer 1

试试这个：

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)

上述解决方案没有特定于dict 对象的内容。这种相同的方法将适用于许多 Python 对象，包括任意类的实例和任意复杂的数据结构嵌套。例如，将第二行替换为以下行：

import datetime
today = datetime.datetime.now()
a = [{'hello': 'world'}, 1, 2.3333, 4, True, "x", 
     ("y", [[["z"], "y"], "x"]), {'today', today}]

也会产生True的结果。

某些对象由于其性质而不能腌制。例如，pickle 包含打开文件句柄的结构是没有意义的。

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)

HIGHEST_PROTOCOL 的优点是文件变小了。这使得解酸有时更快。

重要提示：pickle的最大文件大小约为2GB。

另一种方式

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

替代格式

• CSV：超级简单的格式 (read & write)
• JSON：非常适合编写人类可读的数据；很常用 (read & write)
• YAML：YAML 是 JSON 的超集，但更易于阅读（read & write、comparison of JSON and YAML）
• pickle：一种 Python 序列化格式 (read & write)
• MessagePack (Python package)：更紧凑的表示 (read & write)
• HDF5 (Python package)：非常适合矩阵 (read & write)
• XML: 也存在 *sigh* (read & write)

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/写性能
• 紧凑性（文件大小）

另请参阅：Comparison of data serialization formats

如果您正在寻找一种制作配置文件的方法，您可能想阅读我的短文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

一般来说，酸洗 dict 会失败，除非你只有简单的对象，比如字符串和整数。

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
>>> 

即使是真的简单的dict 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>

但是，如果您使用更好的序列化程序，例如 dill 或 cloudpickle，那么大多数字典都可以腌制：

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

或者，如果您想将 dict 保存到文件中...

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

后一个示例与此处发布的任何其他好答案相同（除了忽略 dict 内容的可挑选性之外，这很好）。

Answer 5

将 Python 数据（例如字典）转储到 pickle 文件的简单方法。

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)
... 

通常最好使用 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.

Answer 7

如果您只想将字典存储在单个文件中，请像这样使用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。 它可以完成您在 pickle 周围所需的所有其他东西

from anycache import anycache

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

Anycache 根据参数存储不同的myfunc 结果 cachedir 中的不同文件并重新加载它们。

更多详情请参阅documentation。

Answer 8

import pickle

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

filename = "/foldername/filestore"

fileobj = open(filename, 'wb')

pickle.dump(dictobj, fileobj)

fileobj.close()

Answer 9

仅供参考，Pandas 现在有一种保存泡菜的方法。

我觉得这更容易。

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

Answer 10

如果您想在不打开文件的情况下在一行中处理写入或读取：

  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

我发现腌制令人困惑（可能是因为我很厚）。不过，我发现这是可行的：

myDictionaryString=str(myDictionary)

然后您可以将其写入文本文件。我放弃了尝试使用 pickle，因为我收到错误告诉我将整数写入 .dat 文件。我很抱歉没有使用泡菜。