What Can I Do With Python? – Real Python (2024)

Web Development

Developing web applications with Python is one of the most in-demand skills, with a lot of opportunities for you out there. In this field, you’ll find several useful Python frameworks, libraries, and tools for developing cool web applications, APIs, and more. Here are some of the most popular Python web frameworks:

To get started with web development, check out:

• Python Web Development Tutorials
• Django Tutorials
• Flask Tutorials
• FastAPI Tutorial

If you want some practical project ideas for applying your web development skills right away, then you can build a portfolio web application with Django. With so many jobs and career opportunities out there, it’s a great idea to have a personal portfolio these days, so go ahead and give it a try. You don’t need to know anything about Django to get started with this step-by-step tutorial. It’s perfect if you’re itching to get your hands dirty with web development in Python.

CLI Development

Another field in which Python shines is command-line interface (CLI) application development. CLI applications are everywhere and allow you to automate repetitive and boring tasks in your day-to-day work by creating small and large tools for your command line.

In Python, you have an impressive set of CLI libraries and frameworks that can make your life more pleasant and help you build command-line tools quickly:

To get started with CLI development, check out:

• How to Build Command Line Interfaces in Python With argparse
• Comparing Python Command-Line Parsing Libraries – Argparse, Docopt, and Click
• Click and Python: Build Extensible and Composable CLI Apps

Additionally, if you want to jump into building a CLI application project, then you can start by creating a directory tree generator tool for your command line. In this step-by-step project, you’ll build a command-line tool for generating ASCII diagrams that display the contents of a directory or folder in your file system. You can also work with ASCII to create a hangman game.

Creating applications with a user-friendly and intuitive command-line interface is a valuable skill for any Python developer.

GUI Development

Creating traditional graphical user interface (GUI) applications for desktop environments is also an attractive option in Python. If you’re interested in building this kind of application, then Python has you covered with a wide range of GUI libraries, frameworks, and toolkits to choose from:

A quick way to start building your GUI applications is to use tkinter. This module comes in the Python standard library. Practice using tkinter and watch your vision materialize on the screen. Once you’ve got your feet wet, you can branch out and start working with other Python GUI toolkits.

To get started with GUI programming, check out:

• Python GUI Programming Tutorials
• Python GUI Programming Learning Path
• GUI Programming With PyQt Learning Path

Building back-end services is an essential part of development. However, you also need a front end. Creating applications that users can effectively interact with is paramount.

If you want to start creating real-world GUI applications, then you can build a calculator using PyQt. Completing this calculator project will help you grasp the fundamentals of this full-featured GUI framework, so you can start building nice things for your desktop immediately.

You can also find some other practical projects to help you out with your GUI programming journey. Take a look at the following resources:

• Build a Bulk File Rename Tool With Python and PyQt
• Build a Contact Book With Python, PyQt, and SQLite

These projects will guide you through the process of building GUI applications with PyQt and Python. They will also help you integrate a wide variety of skills to create fully functional real-world applications.

Game Development

Creating computer games is a great way to learn how to program not only in Python but also in any other language. To develop games, you’ll need to use variables, loops, conditional statements, functions, object-oriented programming, and more. Game development is an excellent option to integrate multiple skills.

Computer games have played an important role in programming. Many people get into programming because they love games and want to re-create their favorite games or build their own. Developing computer games can be a fun and rewarding adventure, in which you can live the great experience of playing the game you just created.

You’ll find several tools, libraries, and frameworks for creating games quickly in the Python ecosystem. Here’s a small sample of them:

To get started with game programming, check out:

• Python Game Development Tutorials
• PyGame: A Primer on Game Programming in Python

You can use Python to create arcade games, adventure games, and puzzle games that you can deploy within a few hours. You can also code classic games, such as hangman, tic-tac-toe, rock paper scissors, and more with your newly acquired programming skills.

If you want to dive into building your first game, then you can start by building an Asteroids game with Python and PyGame. If you want to go a step further and build your first platform game, then check out Build a Platform Game in Python With Arcade.

Machine Learning

Machine learning can be the first step for someone interested in artificial intelligence. Machine learning studies algorithms that learn through experience. These algorithms build models based on samples of training data to make predictions and decisions.

Machine learning can be an intimidating field to get started with because the space is fast and ever-changing. Here’s a summary of some of the most popular tools for doing machine learning with Python:

To get started with machine learning, check out:

• Python Machine Learning Tutorials
• Machine Learning With Python Learning Path

Scientific Computing

Another field in which Python plays a significant role is scientific computing. Scientists use advanced computing capabilities available through supercomputers, clusters of computers, and even desktop and laptop computers to understand and solve complex problems.

Here are some of the libraries and tools you can use for scientific computing in Python these days:

To get started with scientific computing, check out:

• Math for Data Science Learning Path
• NumPy, SciPy, and Pandas: Correlation With Python
• SimPy: Simulating Real-World Processes With Python

The libraries and tools in this section are fundamental pieces in the data science space in Python. Some of them are core components of higher-level libraries for machine learning, data analysis, and more.

Data Analysis and Visualization

Data analysis is a process of collecting, inspecting, cleansing, transforming, and modeling data to discover useful information, make predictions, arrive at conclusions, support decision-making processes, and more. Data analysis is closely related to data visualization, which deals with the graphical representation of data.

In Python, you’ll also find mature and well-established libraries for data analysis and data visualization. Here are some of them:

To get started with data analysis and visualization, check out:

• Data Collection & Storage Learning Path
• Data Visualization With Python Learning Path
• Data Science With Python Core Skills Learning Path
• Pandas for Data Science Learning Path Learning Path
• Develop Data Visualization Interfaces in Python With Dash

If you want to level up your data analysis skills by building a practical project, then you can create a gradebook with Python and pandas. This step-by-step project guides you through the process of creating a Python script that loads the grade data and calculates letter grades for a group of students. The project involves loading the data from a comma-separated values (CSV) file, exploring the data, and calculating and plotting the grades using pandas.

Web Scraping

One of the most significant sources of information for doing data science is the Web. The process of collecting and parsing raw data from the Web with an automated tool (crawler) is known as web scraping.

Python has a great set of tools and libraries for scraping data from the Web. Here are some of them:

To scrape data from the web, check out:

• Python Web Scraping Tutorials
• Python Web Scraping Learning Path

Once you know the basics of web scraping, you can dive into a practical project and build your own web scraper with Python and Beautiful Soup. After finishing this practical project, you’ll be able to apply the same process and tools to any other static websites out there. These skills allow you to extract relevant information and use it in your applications. Go ahead and give it a try!

Note: Before using your Python skills for web scraping, you should check the use policy of your target website to make sure that scraping it with automated tools isn’t a violation of its terms of use.

A second project you can build right away is a Bitcoin price notification service. Since topping out at a price of just over $40,000 in January 2021, the cryptocurrency has been on the minds of millions. Its price continues to fluctuate, but many people out there would consider it a worthwhile investment.

If you’re looking to cash in on the virtual gold rush and just need to know when to make your move, then you’ll need to stay on top of Bitcoin’s prices. The foundation of this project is the creation of IFTTT (If This Then That) applets. You’ll learn how to use requests to send HTTP requests and how to use a webhook to connect your application to external services.

This Bitcoin price notification service is the perfect starter project for a beginner Pythonista with interest in crypto. Then you can extend the service you’ll build in this tutorial to monitor other currencies as well.

Thanks to the Internet—and, increasingly, the Internet of Things—you now have access to hordes of data that weren’t available years ago.

Analytics is a huge part of any field that works with data. What are people talking about? What patterns can you see in their behavior? Twitter is a great place to get answers to some of these questions. If you’re interested in data analysis, then a Twitter sentiment analysis project is a great way to use your Python skills to answer questions about the world around you.

In this project, you’ll learn how to mine Twitter data and analyze user sentiment with a Docker environment. You’ll learn how to register an application with Twitter, which you’ll need to do in order to access their streaming API. You’ll see how to use Tweepy to filter which tweets you want to pull, TextBlob to calculate the sentiment of those tweets, Elasticsearch to analyze their content, and Kibana to visualize the results.

DevOps

DevOps comprises software development and general IT operations. DevOps allows you to handle the entire life cycle of your applications and software products. It includes development, testing, packaging and deployment, and other related operations.

Python is one of the primary technologies people use for DevOps. Its flexibility and accessibility make Python an excellent fit for this job, enabling development teams to improve their workflow and to be more efficient and productive.

In the Python ecosystem, you’ll find that some popular DevOps tools are written in Python. You’ll also find that you can use Python to control most of those tools. Here are a few of them:

To get started with DevOps, check out:

• Python DevOps Tutorials
• DevOps With Python Learning Path

With these resources, you’ll build various skills and learn to use tools and technologies that any DevOps engineer working with Python should know.

Development Environment

Constructing a productive and effective environment for you and your teammates is a fundamental part of software development. To this end, Python has a great set of tools that allows you to isolate your packages, libraries, and Python version in per-project virtual environments.

Here are some of the most popular tools:

To build an effective development environment, check out:

• Python Development Tools Tutorials
• Perfect Your Python Development Setup Learning Path
• An Effective Python Environment: Making Yourself at Home

Learning how to build an effective Python environment for your development adventure will push your productivity to the next level, so it’s important to take the time to polish this skill.

Software Packaging and Deployment

Another critical part of your software development cycle is to package, distribute, and deploy your products to your end users or clients. In Python, a quick and popular way to deploy applications and libraries is to publish them to PyPI.

Here are some of the tools you can use for this purpose:

To get started, check out:

• How to Publish an Open Source Python Package to PyPI
• Using PyInstaller to Easily Distribute Python Applications

With these resources, you can get started with packaging and deploying your Python applications, libraries, and packages to your end users, clients, and colleges. Also, the Python Packaging Authority provides a lot of useful information and tutorials to help you distribute Python packages with modern tools.

Database Systems

Most of the applications you’ll build in your career as a developer will interact with data in some way. This interaction commonly happens through a database management system (DBMS) that allows you to define, create, maintain, and control access to your database or databases.

To connect and manipulate your databases with Python, you have several options that include both standard library packages and third-party packages and libraries. You also have options for SQL and NoSQL databases in Python.

Object-relational mapping tools (ORMs) are another important type of tool you’ll probably use to work with databases in Python. These tools allow you to use object-oriented programming to create and manipulate your databases.

Here are some Python libraries you can use for connecting and operating databases:

To get started with databases, check out:

• Python Database Tutorials
• Data Collection & Storage Learning Path

Creating and working with databases is a powerful way to manage data in your Python applications. Databases add significant functionality and versatility to your programs and allow you to provide exciting features to your users and client. Managing databases is a fundamental skill in your developer education.

Software Testing

When you’re beginning with Python or with programming, you probably start by creating small programs and scripts that you can run and test manually to make sure they work as you expect. However, when your programs grow and get more complex, testing them by hand is near to impossible. This is when automated testing comes into the scene.

Unfortunately, developers make mistakes, and no code is perfect. So, you’ll need a testing process that helps you identify bugs and avoid getting them into production. Testing can also drive your code’s design and help you check non-functional features, such as performance, security, usability, regulatory compliance, and more. Testing, therefore, is an important component of software development.

Python has some of the best tools when it comes to testing. You can use these tools to write consistent tests and to run them automatically. Here’s a small sample of these tools:

To get started with testing, check out:

• Python Testing Tutorials
• Test Your Python Apps Learning Path

As a developer, you need to produce reliable code that works correctly. This means that you need to test your code every time you change it or add new features. Automated tests are the way to go in these situations.