11 Python Libraries and Modules Every Developer Should Know

Libraries and Modules make the life of a programmer smooth.

When you are working with projects, you may encounter scenarios where you won’t be able to solve with the standard coding of a programming language. We need some libraries and modules to overcome those problems.

Luckily Python supports a plethora of modules and libraries. Python has built-in modules as well as third-party libraries and modules for the development. We will see both integrated and third-party modules, which are very beneficial for Python projects. Let’s explore the built-in modules first.

# Built-in Modules

comes with plenty of built-in modules for different use cases. We will study the modules one by one according to the usage.

Collections – Container datatypes

Python has different types of collections to store the collection of data. For example, tuple, list, dict, etc.., are some of the built-in collections of Python. The collections module provides additional features to the built-in collections.

If you take deque data collection from the collections module, it more like a Python list. But, we can push and pop the elements from both sides. It’s faster than the list. You can use the deque based on your needs. Let’s see some real coding with collections.deque data collection.

import collectionsnums = [1, 2, 3]# creating deque collection from the listdeque = collections.deque(nums)print(deque)# adding an element at the enddeque.append(4)print(deque)# adding element at the startingdeque.appendleft(0)print(deque)# removing the element at the enddeque.pop()print(deque)# removing element at the startingdeque.popleft()print(deque)

Run the above code; see the results. We have other data collections as well in the collections module.

Some of them are:

Counter Returns a dict which contains the frequency of elements from the list.

It’s a subclass of the dict class.

UserList Used for a quick subclass of the list.
UserDict Used for a quick subclass of the dict.
UserString Used for a quick subclass of the str.

Go to the documentation of themodule to explore all the data collections and methods.

Quick Note:- Use the dir(object) built-in method of Python to see all the methods of an object.

CSV – file Handling

We can use the CSV (comma-separated values) files to store the tabular data. The most commonly used format for importing and exporting the data from spreadsheets and databases. Python comes with a module called CSV to handle the CSV files.

Let’s see one example of reading the data from a CSV file.

Create a file with the name sample.csv in your laptop and paste the following data.

Name,Age,Graduation YearHafeez,21,2021Aslan,23,2019Rambabu,21,2021

We have methods to read and write in the CSV module. We will see how to read the data from the CSV files using the CSV module.

import csvwith open('sample.csv') as file: # creating the reader reader = csv.reader(file) # reading line by line using loop for row in reader: # row is a list containing elements from the CSV file # joingin the list using join(list) method print(','.join(row))

Run the above code to see the results.

We will also have an object called csv.writer() to write the data into the CSV file. Play with the other methods on your own using the dir() and help()built-in methods. We have another module called JSON, which is used for handling the JSON files. It’s also a built-in module.

Random – generation

Python has a module called random that allows generating the data randomly. We can produce anything randomly using different ways of the random module. You can use this module in applications like tic-tac-toe, a dice game, etc..,

Let’s see a simple program to generate random integers from a given range.

import random# generating a random number from the range 1-100print(random.randint(1, 100)) 

You check the other methods of the random module using dir()and help() methods. Let’s write a small and simple game using the random module. We can call it a Number Guessing Game.

What is the Number Guessing Game?

The program will generate a random number in the range of 1 – 100. The user will guess the number until it matches the random number generated by the program. Every time you will print whether the user number is less than the random number or higher than the random number. Then, the source code will display the number of guesses.

See the below code for the above program.

# importing random moduleimport random# generating random numberrandom_number = random.randint(1, 100)# initializing no. of guess to 0guess_count = 0# running loop until user guess the random numberwhile True: # getting user input user_guessed_number = int(input('Enter a number in the range of 1-100:- ')) # checking for the equality if user_guessed_number == random_number: print(f'You have guessed the number in {guess_count} guesses') # breaking the loop break elif user_guessed_number < random_number: print('Your number is low') elif user_guessed_number > random_number: print('Your number is high') # incrementing the guess count guess_count += 1

Tkinter – GUI applications

Tkinter is a built-in module for the development of GUI (Graphical User Interface) applications. It is convenient for beginners. We can develop GUI applications like calculator, login system, text editor, etc.., There are many resources out there to learn the GUI development with Tkinter.

The best support is to follow the official. To get started with the Tkinter, go to the docs and start creating beautiful GUI applications.

# Third-party Modules

Requests – HTTP requests

Requests module is used to send all kinds of HTTP requests to the server. It allows HTTP/1.1 requests to send. We can also add headers, data, and other things using Python dictionaries. As it is a third-party module, we have to install it. Run the following command in the terminal or command-line to install the requests module.

pip install requests

It’s straightforward to work with the requests module. We can start working with the requests without any prior knowledge. Let’s see how to send a get request and what it returns.

import requests# sening a get requestrequest = requests.get('')# print(request.status_code)print(request.url)print(request.request)

The above code will print the status_code, URL, and request method (GET, POST). You will get the source of the URL as well. You can access it with the request.content bytes. Go to theof the requests module and explore more.

BeautifulSoup4 – web scraping

BeautifulSoup library is used for the web scraping. It’s a handy module to work with. Even beginners can start working with it using the. See the sample code to scrap the customer reports details.

You can install BeautifulSoup by typing the following command in the terminal/command-line.

pip install beautifulsoup4

And, a simple program for your first scraping.

## Scrping the ConsumerReport products list using BeautifulSoup## importing bs4, requests modulesimport bs4import requests## initializing urlurl = ''## getting the reponse from the page using get method of requests modulepage = requests.get(url)## storing the content of the page in a variablehtml = page.content## creating BeautifulSoup objectsoup = bs4.BeautifulSoup(html, 'lxml')## see the class or id of the tag which contains names ans linksdiv_class = 'crux-body-copy'## getting all the divs using find_all methoddiv_tags = soup.find_all('div', class_=div_class) ## finding divs whichs has mentioned class## we will see all the tags with a tags which has name and link inside the divfor tag in div_tags: print(tag)

Run the above code to see the magic of web scraping. There are moreout there for you to try.

# Data Science and Machine Learning

There are some libraries out there specially created for data science and machine learning. All these are developed in C. They are lightning-fast.


is used for scientific computation.

It allows us to work multidimensional arrays. Arrays implementation is not there in Python. Mainly the developers use numpy in their machine learning projects. It’s easy to learn and open-source library. Almost every machine learning engineer or data scientist uses this module for complex mathematical computations.

Run the following command to install the numpy module.

pip install numpy


is a data analysis module. We can filter the data most effectively using the pandas library. It offers different types of data structures that are handy to work. It also provides file handling with different file formats.

Install the module using the following command.

pip install pandas


is a 2D graph plotting library. You can visualize the data using Matplotlib.

We can generate images of the figures in different formats. We plot different types of diagrams like bar charts, error charts, histograms, scatterplots, etc.., You can install the matplotlib using the following command.

pip install matplotlib

Quick Note:- You can installto get all the libraries and modules required for Data Science.

If you are serious about learning Python for data science and ML then check out this brilliant.

# Web Frameworks

We can find many web frameworks in Python. We will discuss two frameworks that are widely used by the developers. The two frameworks are Django and Flask.


is an open-source web framework developed in Python. It is convenient to create websites with Django. We can generate any kinds of sites using this framework. Some of the most popular sites built with Django are Instagram, bitbucket, Disqus, Mozilla Firefox, etc..,

  • We can build complex websites quickly with the features of Django.
  • The Django already does a lot of the tasks required for web development.
  • It also provides security for the attacks SQL Injection, cross-site scripting, cross-site request forgery, and clickjacking.
  • We can build any website from the content management system to social sites.

The documentation of Django is unambiguous. You have to familiar with the Python for Django. But don’t worry if you’re not.is easy.


Flask is a micro web framework developed in Python.

It is more pythonic than Django. It has excellent documentation. It uses the Jinja template engine. It is very complex to create big websites Flask. Most of the features like URL routing, Request dispatching, Secure cookies, Sessions, etc.., are present in both Django and Flask.

Choose the framework based on the complexity of your website. Django is gaining popularity among developers. It’s the most used framework for web development in Python.


I hope you got to know about different modules, libraries, and frameworks for Python.

Everyone once a beginner.

Whatever you want to start, first go the documentation and start learning it. If you can’t understand the docs, then find crash courses on the.