Best Python Libraries for your next project


Today’s tutorial we will discuss some of best python libraries that you can use in your next python project. Python Libraries and Packages are a set of useful modules and functions that minimize the need to write code for our project. There are thousands of python libraries and packages ready to ease developers’ regular programming needs.

1- PyTorch

Pytorch is open source library, it basically a replacement of library Numpy and it equipped with higher-level functionality for building deep neural network. You still can use other language such as scipy, Cython, and numpy which help to extend PyTorch when required. Many organization including facebook, twitter, Nvidia, uber and other organization using Pytorch for rapid prototyping in research and to train deep learning models.


2- Requests

Requests is one of the famous Python library which is licensed under Apache2 and written in Python. This library help humans to interact with the languages. With Request library, you don’t need to add query, string manually to your URL’s or form-encode your POST data. You can send HTTP request to server using Request library and you can add form data, content like header, multi-part files, etc.


3- PyFlux

Pyflux is a python library which is used to predict and analysis time series. It is developed by Ross Taylor, this library have many options for interface and contain many new classes of model types. Pyflux allow users to implement many modern time series models like GARCH and predict the nature that how it will react in future.


4- Pillow

Pillow is actually a fork of PIL – Python Image Library. At first, pillow was mainly based on the PIL code-structure. But later, it transformed into something more friendly and better. Experts say Pillow is actually a modern version of PIL. However, pillow is your trusted company while working with images or any type of image format.


5- Zappa

Zappa is one of best python package which is created by Miserlou, it so easy to build and implement server-less application on API Gateway and Amazon Web Services Lambda. Since AWS handling the horizontal scaling automatically, so no request going to be time out. With Zappa, you can update your code in single line with Zappa.


6- Scrappy

Scrappy is widely used Python web scraping library. It is used for creating crawling programs. Initially, it was designed for scraping, like its name indicate but now it used for many purposes including data mining, automated testing, etc. scrapy is open-source and must have library.


7- Pendulum

Pendulum is a python package which is used to determine pendulum. It make life a lot of easier when it comes to work with date and time. You code will still work if you replace every elements of DateTime. With Pendulum, you can parse DateTime, and display datetime with time zone. So basically Pendulum is improved version of Arrow library and it have all the handy methods like rounding, truncating, converting, parsing, formatting, and arithmetic.


8- Theano

It a Python deep learning library, which is used to optimize, define and evaluate mathematical numerical equations and multi-dimensional array. It is developed by machine learning group, so basically, Theano is a compiler for mathematical expression and it provide tight integration with Numpy and it provide a speedy and stability optimization.


9- Numpy

Numpy is a popular array – processing package of Python. It provides good support for different dimensional array objects as well as for matrices. Numpy is not only confined to providing arrays only, but it also provides a variety of tools to manage these arrays. It is fast, efficient, and really good for managing matrice and arrays.


10- Arrow

Arrow is a famous human-friendly Python library which offers sensible features like creating, formatting, manipulating and converting dates, times, and timestamps. It support python 2 and 3 and it is an alternative of datetime but provide rich features with nicer interface.


11- OpenCV

OpenCV, a.k.a Open Source Computer Vision is a python package for image processing. It monitors overall functions that are focused on instant computer vision. Although OpenCV has no proper documentation, according to many developers, it is one of the hardest libraries to learn. However, it does provide many inbuilt functions through which you learn Computer vision easily.


12- TensorFlow

If you are currently working on a machine learning project in Python, then you may have heard about this popular open source library known as TensorFlow. TensorFlow works like a computational library for writing new algorithms that involve a large number of tensor operations, since neural networks can be easily expressed as computational graphs they can be implemented using TensorFlow as a series of operations on Tensors. Plus, tensors are N-dimensional matrices which represent your data.


13- Dash

Dash, announced this year, is an open source library for building web applications, especially those that make good use of data visualization, in pure Python.
It is built on top of Flask, Plotly.js and React, and provides abstractions that free you from having to learn those frameworks and let you become productive quickly.


14- Pipenv

With Pipenv, you specify all your dependencies in a Pipfile — which is normally built by using commands for adding, removing, or updating dependencies.
The tool can generate a Pipfile.lock file, enabling your builds to be deterministic, helping you avoid those difficult to catch bugs because of some obscure dependency that you didn’t even think you needed.



As a die-hard Python fan who usually interacts with APIs, you are probably familiar with the requests library. However, requests will do no good for you if you are using the async paradigm, which is increasingly common in high performance modern applications.


16- Modin

Modin’s motto is to Scale your Pandas workflow by changing a single line of code, and it really is that simple. Just install Modin, change your import statements and reap the benefits of up to 4x speed up on modern laptops with multi-core processors.


17- SciPy

SciPy is a machine learning library for application developers and engineers. However, you still need to know the difference between SciPy library and SciPy stack. SciPy library contains modules for optimization, linear algebra, integration, and statistics.


18- Fire

Fire is an open-source python library. It can automatically generate CLIs (command-line interfaces). Even to do so, you will be just needing a few lines of code. Fire is a powerful library that can derive CLIs from literally any python objects. It is used by Google as well to create a command line and different experiment management tools as well.


19- Luminoth

Luminoth is a python built toolkit – dedicated for computer vision. It is an alpha quality release, and the last version was released in November 2018. Currently, it supports the seamless detection of an object, but in the near future, it can do more. To use Luminoth, one must install TensorFlow beforehand.


20– BeautifulSoup

BeautifulSoup is a great python library. It is used for parsing. It can parse different broken HTML and XML documents, as well. It offers an easy way for web scraping by extracting direct data from HTML. Many professionals are really happy with its amazing performance. It can save quite a lot of time on your day.


21- Poetry

Poetry is an easy tool for Python. It allows you to manage python packaging and dependencies. While your project depends on several libraries, Poetry allows you to handle them easily. It is compatible with different python versions. And developers are focused on making it work evenly on Windows, OsX, and Linux as well.


22- Pandas

Pandas is a python software package. It is a must to learn for data-science and dedicatedly written for Python language. It is a fast, demonstrative, and adjustable platform that offers intuitive data-structures. You can easily manipulate any type of data such as – structured or time-series data with this amazing package.



Python Packages play a vital role in day to day developer’s life. Whether it is for data science or machine learning or any other aspects of the programming world, these packages and libraries will definately help in boosting productivity. However, in addition to our combined list of python packages and libraries, there are also many other libraries and packages, as well. You can find a lot of them on PyPI. We hope our article was useful to you. Let others know as well, and share this article with your community.

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