The ndarray objects can be saved to and loaded from the disk files. The IO functions available are −

• load() and save() functions handle /numPy binary files (with npy extension)

• loadtxt() and savetxt() functions handle normal text files

NumPy introduces a simple file format for ndarray objects. This .npy file stores data, shape, dtype and other information required to reconstruct the ndarray in a disk file such that the array is correctly retrieved even if the file is on another machine with different architecture.

numpy.save()

The numpy.save() file stores the input array in a disk file with npy extension.

import numpy as np 
a = np.array([1,2,3,4,5]) 
np.save(''outfile'',a)

To reconstruct array from outfile.npy, use load() function.

import numpy as np 
b = np.load(''outfile.npy'') 
print b 

It will produce the following output −

array([1, 2, 3, 4, 5])

The save() and load() functions accept an additional Boolean parameter allow_pickles. A pickle in Python is used to serialize and de-serialize objects before saving to or reading from a disk file.

savetxt()

The storage and retrieval of array data in simple text file format is done with savetxt() and loadtxt() functions.

Example

import numpy as np 

a = np.array([1,2,3,4,5]) 
np.savetxt(''out.txt'',a) 
b = np.loadtxt(''out.txt'') 
print b 

It will produce the following output −

[ 1.  2.  3.  4.  5.] 

The savetxt() and loadtxt() functions accept additional optional parameters such as header, footer, and delimiter.