Python App Development: When to Use it + 7 Best Frameworks for 2023

Python is a very popular programming language. That doesn’t mean it’s the right one to use in your development process. Find out when to do Python app development and the best frameworks to use depending on your goals.

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by Matias Emiliano Alvarez Duran


Python wasn’t named after the snake* but this programming language is similar to a serpent thanks to its flexibility.(And you can actually use it to code Snake, that classic 90s Nokia game.)

If you’ve been trawling the internet to find out more about Python programming, you’ve probably read that it’s open-source. This means that Python is free to use and edit by users. And, it’s community-based, so you get the support of hundreds of developers in forums.

From progressive web apps to machine learning algorithms, we’ve successfully coded plenty of platforms using different frameworks and Python libraries. That’s why we’ve compiled this comprehensive guide to Python app development, including when to use it and when to choose an alternative. 

*Seriously, it was actually named after the famous comedy sketch group, Monty Python.

Here’s what we’ll cover!

Ready to build your own custom software with a team that cares about you and your processes? We’re not code monkeys, we care about you

When should you use Python?

Python is a popular programming language because it emulates written English to code commands. Source:

Python’s internal engine is highly developed and qualified to come up with machine learning algorithms. That's why Python is an excellent choice for scraping and data-intensive projects. You’ll benefit the most from using Python in these cases: 

Web app development

Python is suitable for web app development because it’s open-source, free, and relatively easy to use. Plus, you can use Python to code both for object-oriented programming (OOP) and functional programming (FP), so it’s quite versatile.

There are also many frameworks for Python that support web development, like Django, Flask, and Pyramid. These come with Python libraries filled with out-of-the-box, ready-to-use code functionality (more on frameworks later!).

Game development

Developers choose Python to code games because it’s easy to use and highly powerful. Many large gaming companies create prototypes using Python because it’s fast to write and allows them to test their ideas quickly. Then, they switch to a different language. 

Programmers who are new to game development are likely to choose Python because

  • It's easy to read and write. Python emulates natural English syntax, so you can learn how to use it even if you’ve never written code before.

  • You can use out-of-the-box code from libraries. Since Python is open-source, it has a large active community that keeps frameworks up to date with ready-to-use, reusable code. 

  • You spend less time debugging. As Python is an interpreted language, the code isn’t compiled before running, it is directly executed. Also, Python has a wide variety of debugging tools that can speed up the process. So, it’s less likely to encounter bugs after the code is live. 

BattleField 2 is a well-known video game that uses Python programming language for all internal add-ons. Source: r/Battlefield2 on

Scientific or numeric software

Python is particularly well suited for solving computational problems requiring complex or specialized algorithms. However, using Python alone isn’t always enough to tackle mathematics problems—or at least not in the same way it’d work with C or C++. 

To make Python up for the challenge, you need to combine it with multiple code libraries to implement numeric algorithms and data structures. 

Artificial intelligence (AI) and machine learning (ML)

Python is pretty much like that friend who can find someone’s Instagram account in minutes. It can scrape data, read it, and produce answers in seconds, which makes it ideal for creating AI or ML algorithms. 

But that’s not the only reason why developers choose Python for AI and ML. It’s also because:

  • You get access to standard libraries with pre-built code to reuse (e.g. PyBrain, Pandas, Keras).

  • You can use OOP or scripting to code algorithms.  

  • You can code parts in other languages and achieve more powerful results. 

  • You’re able to run ML on any platform no matter the operating system (it works with Microsoft, macOS, Linux, and over twenty others).

An example of an AI Python application is ChatGPT. This OpenAI product uses machine learning algorithms to understand and generate text-form answers to your questions—and other requests too! (We highly recommend you ask this bot to write you a song or a comedy sketch featuring your favorite colleagues…)

Users are asking ChatGPT to write jokes or apology letters. Here’s what it told us about its configuration. Source: ChatGPT

Web crawlers

Also known as spider bots, web crawlers are autonomous programs that “crawl” the Internet looking for data. The most famous web crawler is probably the Googlebot, which examines web pages and rates them against an index to see which ones are more relevant to specific search queries. That’s how Google gives you such helpful search results.

With Python, you can create web crawlers and scrapers that do more than just find data. This language facilitates data extraction, analysis, introduction, and visualization.

When should you avoid using Python?

Python works for almost every use case. However, it’s probably not your best option for these types of projects:

  • Real-time computing systems. These applications mix hardware and software requirements to reach an expected performance, like apps for managing air traffic control devices. Since Python is desktop-based, it’s not best suited to this use-case (desktop operating systems enforce a lower bound on the maximum fluctuation).

  • Embedded systems. These systems have a clear input and output, like fire alarms. Python can often take up CPU memory usage and its runtime overhead may be too much for small, resource-constrained devices. C or C++ are more suited languages for this type of system.

  • Mobile apps. You can use Python to develop apps that look and feel like mobile-native applications, but Android and iOS can’t process interpreted languages. That means you need a workaround to do this using frameworks that convert the code for operating system readability like Kivy or BeeWare.

7 Useful frameworks for Python app development

Every programming language has a set of open-source frameworks. These are community-based and help developers come up with faster answers to their code requirements. Check out the 7 frameworks that we recommend and use when coding in Python: 

1. BeeWare

BeeWare contains different libraries for developing native mobile and desktop applications. It’s a powerful tool as it converts the code into a compatible format for your target platform. So, you can use it with Python for iOS, Windows, Linux, or Android app development.

2. Kivy 

Kivy comes with a big library for developing multi-touch and mobile applications. It helps developers code software with a natural user interface for smartphones, tablets, and desktop computers. Kivy uses a modern graphics engine for creating visually rich and highly interactive software like games or interactive apps. 

3. Django 

Django is mostly used for building web apps. It comes with plenty of built-in features and tools for common web development tasks. These include:

  • Handling requests and responses

  • Interacting with databases

  • Creating forms

Django is known for its scalability, security, and ease of use. We used it with Python and React.js to help build a custom progressive web application (PWA) for real estate brokers and buyers. The framework helped us deliver an intuitive user interface and a robust, bug-free backend—all in three months! 

4. Pyramid 

Pyramid is also used for building web applications with Python. Developers like it because it’s lightweight and flexible. You can use it for apps of any size, from small business to enterprise-level applications. Pyramid mainly uses the Model-View-Controller (MVC) structure, but it also allows for Model-View-View-Model (MVVM) and the Model-View-Presenter (MVP).

5. Falcon 

Falcon is a Python framework for building web applications. It’s commonly used for building APIs and enterprise microservices fast and efficiently. This light-weighted framework also provides a simple routing system and query and response objects. That makes it simple to use for building web services that are both fast and scalable.

6. Flask 

You can use this framework to build web applications with Python. It’s minimalistic and easy to use. Flask allows developers to use the libraries and tools of their choosing. Flask is mostly used for developing small to medium-sized web apps and APIs. You can also code prototypes and practice web development. 

7. Fast API

Fast API is meant for building API connections using Python as it simplifies coding. This framework implements the standards for asynchronous programming. This tool is easy to use due to its highly intuitive routing system. Plus, it helps determine the endpoint of the API along with the endpoint path and methods. It supports OpenAPI and JSON Schema. 

Pro tip: If you use GitHub, check out our NaNLABS code repository. It’s filled with tools and apps we use for internal and client-facing projects. It comes with a large set of Fast API examples.

5 Examples of Python apps worth knowing about

Python is everything, everywhere, all at once. Most of the apps we use on a daily basis have some parts of their code written in Python. These are five examples: 

  • Reddit. This social media platform analyzes large amounts of daily data. Python is one of the best languages to scrap, analyze, and come up with answers. Reddit’s backend was coded with Python, using Pyramid as a framework.

  • Uber. This transportation company uses various languages, but Python is one of the main ones. Uber uses Python for retrieving, analyzing, and visualizing data, creating a logging function, and routing.  

  • Spotify. This music streaming service uses Python for data analysis, prototyping, integrating with other platforms, and machine learning to identify user-specific algorithms. 

  • Amalgam. This financial platform allows individuals to automate complex processes. We used Python to scale the architecture and simplify the debugging process for them. Read the Amalgam case study.  

  • Internet of things (IoT) cyber-security application. This client needed to scale their platform and fix bugs. We used Python for the backend to get rid of legacy code and deliver an application fast. Read the case study.

Should you hire a Python-savvy development agency?

If you’re working on a data extensive software project or want to make your software more scalable, you should consider Python.  And if you don’t have the expertise or the time to handle the development in-house, augment your team with a software development agency like NaNLABS. 

Not only are we experts using Python frameworks, but we can also:

  • Merge with your development team to work toward the same goal

  • Implement Agile software development practices and organize work in sprints, stories, or increments 

  • Act as consultants and advise you on which technologies to use and which is the best way to achieve a goal

  • Work on your MVP development and make it funding-round-ready

Ready to build your own custom software with a team that cares about you and your processes? We’re not code monkeys, we care about you

Frequently asked questions about Python app development

  • Can Python be used for app development?

    Python can be used for app development. In fact, many of the apps we use today have their backend written in Python. This language is great for web app development, but it’s a bit tricky to use for mobile app coding as you need additional tools to “translate” the code into something mobile operating systems can read. 

  • What’s the difference between Python and Java?

    The difference between Python and Java is that Python is easier to learn, but Java is faster in terms of debugging. Java is also statistically compiled, while Python is dynamically compiled. Other differences include:

    • Syntax: Python is easier to write and read.

    • Object-oriented programming: While both are OOP, Python is more flexible in these terms, whereas Java uses a more traditional class-based approach.}

    • Speed: Java is considered faster than Python. 

    These are both backend programming languages. Whereas Javascript, HTML, or CSS are front-end languages. 

  • Can Python replace Java?

    Python isn’t a direct replacement for Java. While these two languages focus on the backend, they’re used for different purposes. Python is mostly used for machine learning and scientific computing. Almost every type of data-heavy application. Java, on the other hand, is mostly used for large and enterprise-level applications, Android application development, and big data. 

  • What’s the best integrated development environment (IDE) for Python app development?

    The best IDE for Python app development depends on your specific needs and preferences. But, the most popular and widely used is PyCharm. PyCharm was developed by JetBrains. With it, you have access to a free community or paid professional access. It has a wide range of features including code completion, debugging, and integration with version control systems.

  • Can Python be used for enterprise application development?

    Python can be used for enterprise application development as it simplifies the debugging process and allows for extensive data processing. However, since it’s open source and doesn’t have professional documentation, many enterprises rather use Java instead. 

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