NumPy Frombuffer Function

Introduction

NumPy frombuffer() function is used to create a numpy array from a specified buffer. The buffer represents an object that exposes a buffer interface. This function interprets the buffer as a one-dimensional array. In this lab tutorial, we will cover the steps involved in using the frombuffer() function of the NumPy library.

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Skills Graph

Import the required libraries

We start by importing the required libraries, i.e., numpy which provides support for array operations, and ctypes to get a predefined buffer.

import numpy as np
import ctypes

Get a predefined buffer

We will get the ctypes predefined buffer using the create_string_buffer() method. This method creates a mutable buffer initialized with the specified string.

buffer = ctypes.create_string_buffer(b'Welcome to this tutorial!')

Create a numpy array from the buffer

We can now create a numpy array using the frombuffer() method. Here, we use the dtype parameter to specify the data type of the elements in the numpy array. The count parameter is used to set the number of items to read from the buffer.

np_array = np.frombuffer(buffer, dtype='S1', count=-1)

Print the numpy array

We can now print the numpy array we created in the previous step using the print() function.

print(np_array)

Print the data type of the numpy array

We can print the data type of the numpy array using the type() function.

print(type(np_array))

Summary

In this lab tutorial, we learned how to create a numpy array from a buffer using the frombuffer() method of the NumPy library. We also learned how to specify the data type of the elements in the numpy array using the dtype parameter and how to set the number of items to read from the buffer using the count parameter. The frombuffer() method is an efficient way of creating numpy arrays from a buffer-like object.