NumPy save() Method | Save Array to a File Last Updated : 11 Jul, 2025 Comments Improve Suggest changes Like Article Like Report The NumPy save() method is used to store the input array in a binary file with the 'npy extension' (.npy). Example: Python3 import numpy as np a = np.arange(5) np.save('array_file', a) SyntaxSyntax: numpy.save(file, arr, allow_pickle=True, fix_imports=True) Parameters: file: File or filename to which the data is saved. If the file is a string or Path, a .npy extension will be appended to the file name if it does not already have one. If the file is a file object, then the filename is unchanged. allow_pickle : Allow saving object arrays using Python pickles. Reasons for disallowing pickles include security (loading pickled data can execute arbitrary code) and portability (pickled objects may not be loadable on different Python installations). Default: True fix_imports : Only useful in forcing objects in object arrays on Python 3 to be pickled in a Python 2 compatible way. arr : Array data to be saved. Returns: Stores the input array in a disk file with '.npy' extension. ExamplesLet's understand the workings of numpy.save() method in these Python code and know how to use save() method of NumPy library. To use numpy.save() function, you just need to pass the file name and array in the function. Example 1 Python3 # Python program explaining # save() function import numpy as geek a = geek.arange(5) # a is printed. print("a is:") print(a) # the array is saved in the file geekfile.npy geek.save('geekfile', a) print("the array is saved in the file geekfile.npy") Output : a is: [0 1 2 3 4] the array is saved in the file geekfile.npy Example 2 Python3 # Python program explaining # save() function import numpy as geek # the array is loaded into b b = geek.load('geekfile.npy') print("b is:") print(b) # b is printed from geekfile.npy print("b is printed from geekfile.npy") Output : b is: [0 1 2 3 4] b is printed from geekfile.npy Comment More info A ArkadipGhosh Follow Improve Article Tags : Python Python-numpy Python numpy-io Explore Python FundamentalsPython Introduction 3 min read Input and Output in Python 4 min read Python Variables 5 min read Python Operators 5 min read Python Keywords 2 min read Python Data Types 7 min read Conditional Statements in Python 3 min read Loops in Python - For, While and Nested Loops 6 min read Python Functions 5 min read Recursion in Python 4 min read Python Lambda Functions 5 min read Python Data StructuresPython String 5 min read Python Lists 4 min read Python Tuples 4 min read Python Dictionary 3 min read Python Sets 6 min read Python Arrays 7 min read List Comprehension in Python 4 min read Advanced PythonPython OOP Concepts 11 min read Python Exception Handling 5 min read File Handling in Python 4 min read Python Database Tutorial 4 min read Python MongoDB Tutorial 2 min read Python MySQL 9 min read Python Packages 12 min read Python Modules 7 min read Python DSA Libraries 15 min read List of Python GUI Library and Packages 3 min read Data Science with PythonNumPy Tutorial - Python Library 3 min read Pandas Tutorial 6 min read Matplotlib Tutorial 5 min read Python Seaborn Tutorial 15+ min read StatsModel Library- Tutorial 4 min read Learning Model Building in Scikit-learn 8 min read TensorFlow Tutorial 2 min read PyTorch Tutorial 7 min read Web Development with PythonFlask Tutorial 8 min read Django Tutorial | Learn Django Framework 7 min read Django ORM - Inserting, Updating & Deleting Data 4 min read Templating With Jinja2 in Flask 6 min read Django Templates 7 min read Python | Build a REST API using Flask 3 min read How to Create a basic API using Django Rest Framework ? 4 min read Python PracticePython Quiz 3 min read Python Coding Practice 1 min read Python Interview Questions and Answers 15+ min read Like