Python library is a collection of a huge number of functions, methods, and modules that allows you to perform many actions without writing your code in everyday programming such as File I/O, Image processing, numerical operations, extract data, web crawling, data monitoring, or game development.

Python Libraries

Let’s see some examples.

a) You might take 1 hour to finish writing a script for a certain data transformation and the script takes O(n^3) time to run. Then, Python libraries like Numpy, Scipy, or Pandas have a function that runs in O(n).
b) Python imaging library (PIL) is one of the core libraries for image manipulation.
c) Open-CV Python (also binds to C++, C#, etc.) aimed at real-time computer vision and image processing.

Python Applications

Python programming is an easy, open-source, high level, object-oriented, interpreted, and multi-paradigm language used in many applications as shown in the below picture. Python offers extensive libraries that make these applications up and running effortlessly.

Python Applications

Python Libraries That You Cannot Live Without

I have listed them here for a quick review. This article will help you choose the best libraries depending on your needs. You can learn and apply their functionality in detail on-the-job or during the project.


requests tool

Requests is a Python HTTP library that makes HTTP requests simpler and more human-friendly. It is released under the Apache2 License with current version being 2.22.0.

2) Scrapy

scrapy tool

Scrapy is a free and open-source web-crawling framework written in Python that is designed for web scraping, to extract data using APIs or as a general-purpose web crawler. It is licensed under BSD and is maintained by Scrapinghub Ltd.

Scrapy project architecture is built around “spiders”, which are self-contained crawlers that are given a set of instructions, a web-crawling shell used by developers to test their assumptions on a site’s behavior and reusable code.

3) wxPython

wxPython Phenix

Phoenix is the improved next-generation wxPython, “better, stronger, faster than he was before. It is focused on improving speed, maintainability and extensibility.” – Github

It is a wrapper for the cross-platform “GUI API/toolkit wxWidgets” in Python programming. It provides access to the user interface portions of the wxAPI, enabling Python applications to have a graphical user interface on Windows, Mac or Unix systems with a native look and feel and requiring very little, if any, platform-specific code. It is one of the alternatives to Tkinter and is free software.

Few applications developed with wxPython are BitTorrent, Chandler, Editra, Google Drive, GRASS GIS, Métamorphose, and Patch.

You can use other libraries like pyQT and pyGtk for GUI development.

4) Beautiful Soup


Beautiful Soup is a Python package that creates a parse tree for parsed pages that can be used to extract data from HTML and XML documents. It is useful for web scraping.

5) Numpy

numpy tool

NumPy is a library that provides math functions to operate on large, multi-dimensional arrays and matrices. NumPy is an open-source software.

6) Twisted

python twisted tool

Twisted is an event-driven network programming framework used for networking application development where users write short callbacks which are called by the framework. It is written in Python and licensed under the MIT License. It supports HTTP, FTP, TCP, UDP, SSL/TLS, SSH, IP multicast, Unix domain sockets, and much more.

7) SciPy

scipy tool

SciPy is a free and open-source Python library used for scientific computing and technical computing comprising algorithm and mathematical tools for optimization, linear algebra, integration, interpolation, special functions, FFT, signal and image processing, ODE solvers and other tasks common in science and engineering.

SciPy is part of the NumPy stack which includes scientific computing libraries like Matplotlib, pandas and SymPy. The SciPy library is licensed under BSD and is also supported by NumFOCUS.

8) Pyglet

pyglet tool

Pyglet is a cross-platform windowing and multimedia library for Python, that provides an object-oriented application programming interface intended for developing games and other visually rich applications. Pyglet works on Microsoft Windows, Mac OS X, Linux and supports windowing, user interface event handling, Joysticks, OpenGL graphics, loading images, and videos, and playing sounds and music.

9) Matplotlib


Matplotlib is a numerical plotting library for Python, SciPy and its numerical mathematics extension NumPy. It provides an object-oriented API for embedding plots into applications using general-purpose GUI toolkits like Tkinter, wxPython, Qt, or GTK+.

You can refer to Pydot – used to visualize data, though for much more complex graph structures such as in neural networks.

10) SQLAlchemy

SQLAlchemy is the Python SQL toolkit and Object Relational Mapper that facilitates the communication between Python programs and databases. This library translates Python classes to tables on relational databases and automatically converts function calls to SQL statements.


sympy tool

SymPy is a Python library for algebraic evaluation, complex numbers, differentiation, and symbolic computation. It is simple to install, extensible, and provides computer algebra capabilities(ranging from basic symbolic arithmetic to calculus, algebra, discrete mathematics and quantum physics) either as a standalone application, as a library to other applications, or live on the web as SymPy Live or SymPy Gamma.

12) Nose

It is a testing framework for Python where the purpose is to extend unittest to make testing nicer and easier to understand.



The pytest framework is better than Nose and makes it easy to write small tests, yet scales to support complex functional testing for applications and libraries. Few of its features are – can run unittest, suitable on Python 3.5+ and PyPy 3, can manage small or parametrized long-lived test resources, auto-discovery of test modules and functions, and rich plugin architecture with over 315+ external plugins and thriving community.

14) TensorFlow

TensorFlow tool

TensorFlow is an end-to-end free and open-source software library for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries, and community resources and developers can easily build and deploy neural networks, dataflow, ML-powered applications, and differentiable programming. TensorFlow was developed by the Google Brain team for internal Google use.

You can refer to PyBrain – contains algorithms for neural networks that can be used by entry-level students yet can be used for state-of-the-art research.

15) Theano

theano tool

It is a numerical computation library for Python and best for implementing neural network models. You can define, optimize, and evaluate mathematical expressions, especially matrix-valued ones. It is an open-source project primarily developed by a Montreal Institute for Learning Algorithms (MILA) at the Université de Montréal.

16) Keras

keras tool

Keras is an open-source neural network library written in Python and can run on top of TensorFlow or Theano. It is designed to enable fast experimentation with deep neural networks. It is user-friendly, modular, and extensible.

17) Pygame

pygame tool

Pygame is a cross-platform library that uses Python language, SDL multimedia library, computer graphics and sound libraries for writing video games.

18) PyTorch

pytorch tool

It is an open-source python package based on the Torch library for machine learning. It is used for applications Tensor computation (like NumPy) with strong GPU acceleration, Deep neural networks built on a tape-based autograd system, computer vision, and natural language processing. It was primarily developed by Facebook’s artificial intelligence research group. It is free and open-source software licensed under BSD.

19) Seaborn


Seaborn is a Python data visualization library based on matplotlib that provides a high-level interface for drawing attractive and informative statistical graphics.

20) Natural Language Toolkit(NLTK)

Natural Language Toolkit

The Natural Language Toolkit, or more commonly NLTK, is a suite of open source Python libraries, programs data sets, and tutorials, supporting research and development in Natural Language Processing. It includes graphical demonstrations & sample data and supports classification, tokenization, stemming, tagging, parsing, and semantic reasoning functionalities. It is used in applications like empirical linguistics, cognitive science, artificial intelligence, information retrieval, and machine learning.

21) IPython (Interactive Python)

ipython tool

It is a command shell for productive interactive computing in Python programming. It offers features like Interactive shells (terminal and Qt-based), a browser-based notebook interface, embeddable interpreters, GUI toolkits, tools for parallel computing and interactive data visualization.

22) Pandas

Python Pandas

Pandas – the name is derived from the term “panel data”, an econometrics term for data sets. It is a Python package providing fast, flexible, and expressive data structures for data manipulation and analysis. It offers operations for manipulating numerical tables and time series. It is free software released under the three-clause BSD license and has a broader goal of becoming the most powerful and flexible open-source data analysis/manipulation tool available in any language.

23) spaCy


It is an open-source software library for advanced natural language processing, written in Python and Cython.  It is published under the MIT license and offers pretrained statistical neural network models, word vectors, and tokenization for 50+ languages.

Unlike NLTK, which is widely used for teaching and research, spaCy focuses on providing software for production usage and deep learning. It provides neural network models for tagging, parsing and named entity recognition and easy deep learning integration.

You can also refer to Gensim, an open-source library for unsupervised topic modeling and natural language processing

24) Plotly Python

python plotly

Plotly’s Python graphing library makes interactive, publication-quality graphs such as line plots, scatter plots, area charts, bar charts, error bars, box plots, histograms, heatmaps, subplots, multiple-axes, polar charts, and bubble charts.

25) Bokeh 

bokeh python tool

Bokeh is a data visualization library in Python that provides elegant, concise construction of versatile graphics, high-performance interactive charts and plots for modern web browsers. It is possible to embed bokeh plots in Django and flask apps and it can help developers quickly and easily make interactive plots, dashboards, and data applications.

26) Scikit-learn

scikit learn tool

Scikit-learn is a Python module for machine learning. It is distributed under the 3-Clause BSD license. It features various classification, regression and clustering algorithms including support vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy.

You can implement machine learning algorithms under the Gradient Boosting framework using LightGBM or XGBoost.

27) Statsmodels

statsmodels tool

Statsmodels is a Python package that provides a complement to Scipy for statistical computations including descriptive statistics and estimation. It adds statistical tools/algorithms like regression models, time series analysis, autoregression in the form of classes and functions to the python world.

28) Flask

python flask

Flask is a lightweight micro web framework written in Python which does not require particular tools or libraries, has no database abstraction layer, form validation, or any other components where pre-existing third-party libraries provide common functions.

Eve is a free Python-based REST API framework, powered by Flask and Cerberus.

You can also refer to Falcon is a lightweight, SWGI-compliant web framework, designed for building RESTful APIs.

29) Django

Django is a Python-based free and open-source web framework, which follows the model-template-view architectural pattern and encourages rapid development and clean, pragmatic design.

Ending Here with a Note

The above libraries top the list of python libraries used in web/full-stack development, data science (data visualization, machine learning, artificial intelligence, deep learning), automation testing and game development.

If you are an absolute beginner, have a little exposure to Python programming or a programmer worked on other programming languages, it’s worth gaining in-depth knowledge of these libraries.

We can help you! Enroll with us to obtain world-class theoretical and hands-on experience in Advanced Python Programming.

There are many other frameworks and libraries that deserve attention for particular tasks. So, if you have any library in mind other than the ones mentioned above, you can let me know in the comments section.

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