What is numpy.load() in Python?
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Overview
The numpy.load() is used to load arrays or pickled objects from files with .npy , and .npz extensions to volatile memory or program.
Pickling is a process in which Python objects are converted into streams of bytes to store data in file. Therefore, it results in a packed object.
Syntax
numpy.load(file, mmap_mode=None, allow_pickle=False, fix_imports=True,encoding='ASCII')
Parameters
It takes the following argument values:
- file : This is the file to read. It can be either a pathlib.Path or a file-like object or a string.
- mmap_mode : The default value of this parameter is None . Other possible values are ‘+’ , ‘r’ , ‘w+’ , and ‘c’ . It follows the specified memory mapping mode when set to any of these values.
- allow_pickle : When set to True , it will allow reading pickle arrays from .npy and .npz files. The default value of this parameter is False .
- fix_imports : This parameter is useful when we load pickles generated from the older versions of Python. The default value of this parameter is True .
- encoding : It is used to select the pickle file reading encoding scheme. The default value of this parameter is ‘ASCII’ .
Return value
It returns the data stored in the files as an array, tuple, dict, and so on.
Exception
It also raises the following exceptions.
- OSError : It returns this error when the file is inaccessible or unreadable.
- UnpicklingError : It returns this error if allow_pickle is set, but the file cannot be loaded in the program.
- ValueError : It returns this error when a specified file contains an array type object, but allow_pickle is set to False .
Example
In the code snippet below, let’s look at how the load() function loads an array or pickle file from memory.