Top 10 Python Libraries You Must Know In 2021

What is Python?

Python is a widely-used programming language. In recent days the demand for python programmers has been increasing. Python supports procedure-oriented as well as object-oriented programming. Python is a minimalist language.

Why we need Python and its libraries?

There are lots of advantages of using Python language, few of them are simple to use, its free, Compatibility, and availability of open-source libraries. It also helps in the analysis of large number data through it high-performance libraries and tools. Python is widely considered as the preferred language for learning Machine Learning. Now let’s talk about python Libraries, through these libraries data handling capacity and data manipulation is great. Python Libraries allow you to think like a programmer and not wasting your time with confusing syntax. Now it’s time to know the top 10 python libraries one by one.

Matplotlib
Numpy
Pillow
Requests
OpenCV Python
Theano
Keras
Tensor Flow
Fire
Arrow

1. Matplotlib

Matplotlib is one of the most popular python libraries for the data visualization method. This library is used to write 2-dimensional graphs and plots. This library helps us to build multiple plots and axes at a time as shown in the figure.

Features of Matplotlib:

Matplotlib can create quality figures that are really good for publication. The figures which you create with Matplotlib are available in hardcopy formats and you can access them through different platforms.
You can also integrate third-party packages with Matplotlib libraries such as basemap, seaborne and many more.
Matplotlib library is available with many python tool kits namely Scripts, shells of ipython and many jupyter notebooks.
Matplotlib developer community is very active to help you with any of inquiries related to this library.
The important thing with this library is that you can easily find any bugs or tickets and this tickets will be available in the issue finding system from GitHub. This is an official page for Matplotlib.

2. Numpy

Numpy is a one of the popular array-processing package. It provides good support for different kind of arrays as well as for matrices. This library provides variety of tools to manage arrays and matrices. It is very fast and efficient library to use.

Features of Numpy:

Array of Numpy offer latest and advanced mathematical implementation on large amount of data. Numpy makes the execution of these projects easier to use and hassle free.
Numpy library has come with advanced usages such as logical shape manipulation, Fourier discrete data transfer, linear algebra support and etc.
This library allows user to correct or change the all kinds of dimensional array shapes using Numpy library. These libraries enable us to generate new arrays and delete the existing arrays.
You can easily integrate Numpy with different programming languages such C, C++ and C#.
Numpy provides functionalities that are comparable with MATLAB.

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3. Pillow

Pillow is a subsection of PIL or Python Image Library. Initially it was completely available with Python Image codes and structure. But after many years of research, it has come with more friendly and better way of coding. Python community says Pillow is actually a modern version of PIL. Pillow library is useful when you are working with Images or any type of Image formats.

Features of Pillow:

Pillow library cannot only open or save your images, but it also influences the environment of images as well.
Pillow supports lot of file types such as PDF, WebP, PNG, JPEG, GIF, BMP and many more.
Pillow library helps you create Thumbnail for an image easily. Now a day, Thumbnail has become valuable aspect of your image.
Pillow supports many filter files such as FIND_EDGES, FILTERS, and SMOOTH, BLUR, CONTOUR, SHARPEN and DETAIL.
Pillow community is always active to answer all your enquires related to library. That is more commendable.

4. Requests

Request is one of the rich and important HTTP libraries. This library released under Apache 2.0 focused on making HTTP more effective and user-friendly way. This library is useful for beginners as it allows the most common method of HTTP. By using this library you can perform many tasks like customizing, inspection of codes, authorization and configuration of HTTP methods.

Features of Requests:

It is an easy library with lot of features that allow you to address custom header, SSL certificate verifications and sweep parameters towards URL’s.
By using basic python dictionaries with this library, you can perform tasks such adding headers, footers, add parameters and formatting data
Request library allows you to upload multiple files at a time. It provides faster and efficient environment for the users.
Request library also supports HTTP proxy method and Allows users to access route file or page.
Request library has multiple features such as value cookies, Unicode response bodies, thread safety, connection pooling and many more.

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5. OpenCV Python

OpenCV Python or Open source computer vision python library is a famous library for all kind of face recognition or image processing. This library manages all type of functions with related to instant computer visions. OpenCv library has no proper documentation so it is very hard to learn. However it has come with many prewritten inbuilt functions and methods which help you to learn image processing easily.

Features of OpenCV:

Computer vision allows you to rebuild, interrupt and comprehend 3D environment.
OpenCV library is best image processing package that allows you to read and write at the same time.
This package allows you to diagnose special objects in any video or image. Objects such as face, trees, house etc.
You can also capture any type of video and monitor movement and background properties etc.
OpenCV is more compatible with operating systems such as Windows, Mac, Linux, open BSD and many more.

6. Theano

Theano is python library and compiler for computer program or an optimizing compiler. It supports to perform many mathematical declarations such as analyze, describe, optimize and many more. Theano supports best use of multi-dimensional arrays. But while working with Theano package you hardly have to focus on perfection of project.

Features of Theano:

Theano’s interfaces are similar with Numpy library. So while using Theano, numpy.ndarrays are also available internally.
Theano works well with many GPUs. It can also help you to execute one or more dimensional inputs at a time.
Theano also tries to avoid bugs or issues while working with expressions. You can work with expressions seamlessly without wasting time.
Computation of data-intensive application is easier and faster with Theano.
This library consists of many useful tools that are useful to identify and testify dangerous bugs or tickets and also serious kind of issues.

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7. Keras

Keras is an ideal library for those who want to pursue their career in deep Neural Networks. Keras is an Open Source neural network library but it is written in Python. It has effective inspection policy over networking data. Keras has features like user-friendly and modular functionality.

Features of Keras:

Keras is one of the most powerful neural network libraries. It is capable of running in many platforms like Microsoft Cognitive, PaidML, Tensor Flow and many other platforms.
This library has many features that supports for Neural Networking. Few of them are functions, layers, optimize and many more.
Keras features also allow users to work with many image and text related documents.
This library does not support only neural networking but also convolutional and re-current neural network environment.
Using Keras you can also build deep models for Smartphones like Android and IOS or java virtual machines.

8. Tensor Flow

Tensor Flow is a free and open source library mainly used for machine learning. It is very easy to learn and handful collections of useful tools. This library is not limited to machine learning only you can also use it for data flow and other programming differentiable. It’s very easy to use if you are using Colab Notebooks on any available browser.

Features of Tensor Flow:

Tensor Flow has feature of eager execution, this allows user to create and manipulate machine learning models and easy to debug.
This library uses high performance API’s such as Keras. It offers agile iteration for machine learning models.
With the help of Tensor Flow library you can easily move Machine learning models to any clouds or on any devices.
Tensor flow has come with easy learn architecture. You can easily learn coding and execution of machine learning models.
This library has solutions for all type of machine learning issues. You can easily debug and run the program.

9. Fire

Fire is an open source library. It can generate command-line interfaces (CLI’s). Even to generate CLI’s you must be aware of few coding lines. Fire is most powerful tool, which can derive CLI’s from any python objects. It is mostly used by Google to create command line interfaces and different experiment management tools.

Features of Fire:

Fire can work many python objects such as Modules, objects, classes, lists, Dictionaries and many more.
The CLI’s that are generated using Fire are adaptable to bring any changes to your code. You can change the code anytime.
It is very simple library. It allows user to write and send commands at any instances when you call fire().
The CLI’s come in complete form with an automated help pages and completion of the tab with interactive systems.
Fire comes with a linear output. Once you using Fire no need of using docstrings as well.

10. Arrow

Arrow is a simplest and practical python library. It is friendly library that works with dates and time. Arrow has come up with smart API’s. This API’s supports many general schemes. Beginners with basic coding knowledge can work pretty well with Arrow.

Features of Arrow:

Arrow library can remove, Change or generate date and time. It executes the quick updates of dates and times and plugging gaps.
It supports different versions of python for example, Versions 2.7, 3.5, 3.6, 3.7 and 3.8.
You can easily create general input scenarios using Arrow library. Arrow creates most simple creational methods.
You can easily convert time zones using Arrow. It offers timestamp as a general property. You can also extend this library for further use.
Arrow easily eliminates and resolve strings within a natural process. It’s a time sensitive library and set to UTC by default.

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Name of library	Meaning	Advantages	Disadvantages
Matplotlib	Used to write graphs and plots	Data visualization is possible	Making plots interaction would be laborious task
Numpy	It is popular array-processing library	Supports different kind of arrays and matrices	Require Contiguous memory allocation
Pillow	It is a python Image library	It is useful for working with Images and Image formats	Modification takes lot of time
Request	It is rich and important HTTP library	Customizing, Inspection, authorizing and configuration	Increase in Security cost if the traffic increases
OpenCV python	It is an open source computer vision library	Face recognition and image processing is possible	No proper documentations to learn
Theano	Theano is an optimizing compiler	Supports mathematical declarations such as analyze, describe code	Hard to have project perfection
Keras	It is an ideal library for neural network learning	User-friendly and modular functionality	Does not offer intuitive support
Tensor Flow	Mainly used for Machine learning	Easy to learn and handful collections of useful tools	Not support for Windows
Fire	It generates command-line interfaces	Used by Google to create command line interfaces	Takes much time in changing the codes
Arrow	Used in creating Date and time formats	It supports all versions of python software and easily convert time zones	Its a time sensitive library

Python libraries play a vital role in the programmers’ career. These libraries are widely used in data science, machine learning, deep learning or any other programming world. I hope this article is useful for those who want to be a python programmer and community as well.

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