Python：通过 numpy.save 保存字典
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Python : save dictionaries through numpy.save
提问by ramu
I have a large data set (millions of rows) in memory, in the form of numpy arraysand dictionaries.
我在内存中有一个大数据集（数百万行），以numpy 数组和字典的形式。
Once this data is constructed I want to store them into files; so, later I can load these files into memory quickly, without reconstructing this data from the scratch once again.
一旦构建了这些数据，我想将它们存储到文件中；因此，稍后我可以将这些文件快速加载到内存中，而无需再次从头开始重建这些数据。
np.saveand np.loadfunctions does the job smoothly for numpy arrays.
But I am facing problems with dict objects.
np.save和np.load函数可以顺利完成 numpy 数组的工作。
但我面临着 dict 对象的问题。
See below sample. d2 is the dictionary which was loaded from the file. See #out[28] it has been loaded into d2 as a numpy array, not as a dict.So further dict operations such as get are not working.
请参阅下面的示例。d2 是从文件加载的字典。参见 #out[28] 它已作为 numpy 数组而不是 dict 加载到 d2 中。因此，诸如 get 之类的进一步 dict 操作不起作用。
Is there a way to load the data from the file as dict (instead of numpy array) ?
有没有办法从文件中加载数据作为 dict （而不是 numpy 数组）？
In [25]: d1={'key1':[5,10], 'key2':[50,100]}
In [26]: np.save("d1.npy", d1)
In [27]: d2=np.load("d1.npy")
In [28]: d2
Out[28]: array({'key2': [50, 100], 'key1': [5, 10]}, dtype=object)
In [30]: d1.get('key1') #original dict before saving into file
Out[30]: [5, 10]
In [31]: d2.get('key2') #dictionary loaded from the file
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-31-23e02e45bf22> in <module>()
----> 1 d2.get('key2')
AttributeError: 'numpy.ndarray' object has no attribute 'get'
回答by Kennet Celeste
It's a structured array. Use d2.item()to retrieve the actual dict object first:
这是一个结构化数组。用于d2.item()首先检索实际的 dict 对象：
import numpy as np
d1={'key1':[5,10], 'key2':[50,100]}
np.save("d1.npy", d1)
d2=np.load("d1.npy")
print d1.get('key1')
print d2.item().get('key2')
result:
结果：
[5, 10]
[50, 100]
回答by Kh40tiK
picklemodule can be used. Example code:
可以使用pickle模块。示例代码：
from six.moves import cPickle as pickle #for performance
from __future__ import print_function
import numpy as np
def save_dict(di_, filename_):
with open(filename_, 'wb') as f:
pickle.dump(di_, f)
def load_dict(filename_):
with open(filename_, 'rb') as f:
ret_di = pickle.load(f)
return ret_di
if __name__ == '__main__':
g_data = {
'm':np.random.rand(4,4),
'n':np.random.rand(2,2,2)
}
save_dict(g_data, './data.pkl')
g_data2 = load_dict('./data.pkl')
print(g_data['m'] == g_data2['m'])
print(g_data['n'] == g_data2['n'])
You may also save multiple python objects in a single pickled file. Each pickle.loadcall will load a single object in that case.
您还可以在单个腌制文件中保存多个 python 对象。pickle.load在这种情况下，每次调用都会加载一个对象。
