Python is one of the most popular languages and Python developer's demand is increasing in the IT sector, day by day, as it is easy to learn and can be used for various tasks like Data Science, machine learning, web developement etc, so, in this article, I will provide you top python libraries which a python developer must use, with there advantages, before we begin, let's understand what does Python Library or package mean.

A Library or package is a collection of various functions that allow users to perform different activities with writing very less code. There are many python libraries available in the development community which aims to reduce code writing, and a library is a collection of various modules.

Python has a huge collection of libraries. So here is the list of best and popular python libraries, which we can use:


Tensorflow is an open-source python library. Most of the developers use the library to build and deploy machine learning models into production. And this library is designed for dataflow, machine learning, and neural network projects.

  • Tensorflow provides a very intuitive high-level API for building and training models.
  • You can deploy models on Cloud, in a browser, or on a device.
  • Tensorflow’s simple architecture makes it a good tool for researchers, as it allows them to move from idea to code to publication quickly.
  • Tensorflow has it’s very large community support, which is a great positive side for Tensorflow.
  • Tensorflow is flexible to operate and easily compatible on the train on CPU. And it is highly useful to visualize each part of the graph easily.



Flask is another very popular Python framework. This is a lightweight framework and designed to deploy complex applications easily and quickly. Since it is a microframework, it does not require any particular tool. And we can add many functionalities in many ways.

  • It is widely used for developing a strong backend system because it is a very famous web framework. And we can make complex web applications too.
  • Flask is easy to learn for beginners because boilerplate code is included by default in it.



Scrapy is an open-source framework that is designed for crawling web sites and extracting their data. Scrapy can also be used for data mining and in many other ways. And scrappy is also a high-level web crawling and web scraping framework.

  • Scrapy can be used in several ways from data mining to monitoring and automated testing.
  • Scrappy can also be used to data using API’s or as a general web crawler. This library avails some tools for the efficient extraction of data from websites, processes them, and stores them in a structured format.
  • Scrapy comes under a BSD license.
  • Scrapy can extract data into different formats such as JSON, CSV, and XML. And it has inbuilt support for selecting and extracting data from resources like XPath. The Scrapy is also a cross-platform application framework. The only con is that it requires different installation as per operating systems



Numpy is also one of the most popular python library, Tensorflow and some other libraries use NumPy internally.

NumPy is one of the fundamental packages for Python providing support for large multidimensional arrays and matrices along with a collection of high-level mathematical functions to execute.

It is also used to analyze andformat data in a structured way, and this library isalso used widely among the developers, so its development community is also large. Numpy got a large number of new updates forbug fixing and some improvements.

  • With NumPy, you can define arbitrary data types and easily integrate with most databases.
  • The key features of NumPy include powerful N-dimensional array object, broadcasting functions, and out-of-box tools to integrate C/C++ and Fortran code.


Matplotlib is one of the most popular python library used for data visualization. It is used to make 2D plots from data in a given array. Matplotlib is a multi-platform data visualization library that is built on NumPy arrays. And it was introduced in 2002, after gaining so much popularity, many versions were released.

  • Matplotlib consists of several plots like line, bar, scatter, histogram, boxplot, etc. Plots help to understand the data in easy and in an interactive way, which makes easy to analyze the data
  • Matplotlib and its other packages are available in the form of wheel packages and can be installed on Windows, Using pip manager this can be installed in Linux and macOS as well.
  • Matplotlib requires a large number of dependencies like NumPy, etc. So make sure that you install all the required dependencies.


Pandas is a free open source python library for data analysis and data handling and for data manipulation too. It was initially released in 2008, after getting popularity, several versions have been released till the date.

  • Pandas provide high performing data structures that make working with data easy and fast. This library mainly consists of two data structure which is Series & Data Frame.
  • Pandas have several uses, it can be used in different fields in finance, statistics, social science, and engineering.
  • Pandas is used in conjunction with many libraries such as NumPy, Matplotlib, etc.
  • Pandas have several amazing features like overcoming missing data, deleting and inserting data in different data frames, easily can be convertible different data into different data structures.



Scipy is a also popular open-source library of Python, this library was designed with the aim of performing scientific calculations.

  • Scipy is also developed using NumPy.
  • The SciPy library offers modules for linear algebra, image optimization, integration interpolation, special functions, Fast Fourier transform, signal and image processing, Ordinary Differential Equation (ODE) solving, and other computational tasks in science and analytics.
  • Scipy regularly updated its version bringing more stability and making it cross-platform.



Keras is also famous deep learning library, allow developers to build neural network projects, and it can run fluently on CPU’s and GPU’s, and this library is also beginner-friendly.

It avails some tools for compiling models, data-sets processing, etc.



Seaborn is also a data visualization library, but it’s API is ahigher level that is based on Matplotlib.

A developer can easily create complicated plots using Seaborn. The latest update of seaborn was all about bug-fixing.



PyTorch library is open-source and is based on the Torch library.

Pytorch is a machine learning as well as a deep learning library. It can also run fluently on CPU’s & GPU’s as well and it’s easy for developers for converting researched prototype into production deployment.

That's it, these were most used and popular python packages, basically all libraries/packages are meant for or designed to give some extra functionalities to code and decrease the code length, to give better results by writing few lines of code.