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  • 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

    Python 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 form 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 collections
    nums = [1, 2, 3]
    # creating deque collection from the list
    deque = collections.deque(nums)
    # adding an element at the end
    # adding element at the starting
    # removing the element at the end
    # removing element at the starting

    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 the collections module 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 Year

    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 csv
    with 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

    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 1-100
    print(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 module
    import random
    # generating random number
    random_number = random.randint(1, 100)
    # initializing no. of guess to 0
    guess_count = 0
    # running loop until user guess the random number
    while 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
        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 docs. 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 request
    request = requests.get("https://www.google.com/")

    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 the docs of 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 docs. 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 modules
    import bs4
    import requests
    ## initializing url
    url = "https://www.consumerreports.org/cro/a-to-z-index/products/index.htm"
    ## getting the reponse from the page using get method of requests module
    page = requests.get(url)
    ## storing the content of the page in a variable
    html = page.content
    ## creating BeautifulSoup object
    soup = bs4.BeautifulSoup(html, "lxml")
    ## see the class or id of the tag which contains names ans links
    div_class = "crux-body-copy"
    ## getting all the divs using find_all method
    div_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 div
    for tag in div_tags:

    Run the above code to see the magic of web scraping. There are more web scraping frameworks out 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.


    Numpy 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


    Pandas 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


    Matplotlib 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 install Anaconda to 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 Udemy course.

    # 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.


    Django 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. Learning Django is easy.


    Flask is a micro web framework developed in Python.

    It is more pythonic than Django. It has excellent documentation here. 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 educational websites.