What is a Python Library?

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Why Learn Python

In recent years, Python gained so much popularity because of its simplicity that it is now considered among the fastest-growing programming languages across the globe.

In addition, Python has an extensive library ecosystem, which makes it the largest language used for the latest technologies. Whether you're using Python for machine learning, artificial intelligence, or data science, one thing is for sure: Python libraries can make a huge difference in speeding up your development process.

As a result, Python developers are in high demand across various industries, offering plentiful job opportunities and competitive salaries.

What is a Python Library?

So you've learned why you should learn Python among other programming languages.

First things first, let's talk about what a library is in programming.

In programming, a library is a pre-written code block that developers can use to optimize their tasks without writing the code from scratch.

import math

In the above code block, I import the math library. Using this math library, we can solve most of the mathematical problems without using any formulas.

Importing specific items from a library

As in the above code, we imported a Python pre-built library to use one of its methods. But we can import only the required item from the library as well. For example, if we want to find the square of a number, we can import the "sqrt" method from the library without importing the whole library.

from math import sqrt

num = 10
sqr = sqrt(num)
print(sqr)

In the above code, we can see that we only imported the "sqrt" method from the math library.

The Most Popular Python Libraries

There are over 100,000 Python Libraries that you can install and use. In this section, we'll go over the most popular Python libraries and what they are used for.

1. NumPy

NumPy is a Python library used for numerical computing in Python. It provides support for large, multidimensional arrays and matrices.

import numpy as np

# Create an array
array = np.array([1, 2, 3, 4, 5])
print(array)

2. OpenCV

OpenCV is a library of programming mainly aimed at image processing and computer vision. We will discuss more about OpenCV in the upcoming blog.

import cv2

# Read an image
image = cv2.imread('example.jpg')
cv2.imshow('Image', image)

3. TensorFlow

TensorFlow is an open-source library developed by Google for deep learning and machine learning.

import tensorflow as tf

# Create a constant tensor
hello = tf.constant('Hello, TensorFlow!')
tf.print(hello)

Conclusion

In summary, Python's library ecosystem is one of the key factors behind its fast growth among programmers. Libraries like NumPy, OpenCV, TensorFlow, and many more help developers solve common tasks efficiently.

By using these Python libraries, you can significantly boost your productivity and ensure your code is robust and consistent. Whether you're a beginner or a well-skilled developer, Python Librarians offers you the tools and resources you need to stay ahead in the IT Industry.

So, I hope you've learned something from this article about libraries and how to use them. See you in the next article!