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'))

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'))

import pickle

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

filename = "/foldername/filestore"

fileobj = open(filename, 'wb')

pickle.dump(dictobj, fileobj)

fileobj.close()

# 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"}

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

如果你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