Why Use Python for Web Development? Pros, Cons, and Business Benefits (2024)

Python has been around since the ‘90s. That’s almost 30 years of constant improvement led—until recently—by Python’s original creator Guido van Rossum.

Mature, stable technologies might be boring for some developers, but they work. An experienced Python programmer knows exactly what the strong and weak parts of the language are. There’s no need to reinvent the wheel or get creative, developers can easily find solutions to common issues.

This comes in handy especially when you need your web application to be as secure as possible. Python is often used in fintech because it’s great for dealing with large amounts of data, and it’s relatively easy (for a senior developer) to make an airtight app with military-grade security.

Do you need beautiful plots on your website? Developers can employ Matplotlib to take care of generating them.

Maybe you need machine learning capabilities in your web app? There’s TensorFlow, the world’s most popular ML library.

Or, something more specific, do you need the power of SQL but with Python code? There’s SQLAlchemy, with only 25,000,000 downloads per month, no biggie. It’s a library that gives you the power of tried-and-tested enterprise development patterns for quick and simple database access using Python.

The Python Package Index has over 300,000 projects. They range from tiny libraries to large, complex tools. There’s a library for everything, including many niche web development use cases.

We need a separate point for one of these tools, Python’s secret weapon for web development: Django.

Django is the main web development framework for Python. It’s a very useful collection of libraries that come together to form a very flexible, powerful, comprehensive platform for building any type of web application. Oh, and it’s used by Instagram among many other major internet companies.

It does exactly what a great framework should do: it takes away the pain of building and gluing together all the parts necessary to form a web server. Developers can focus on creatively demanding tasks rather than low-impact, basic issues.

Plus, if somebody really doesn’t like Django but wants a Python web dev framework, there’s still Flask, which is kind of a polar opposite of Django. It’s a microframework, so it comes with much fewer ready-made parts than Django, but it’s more flexible.

From a business point of view, the main difference between Django and Flask is risk management—Django can cover more use cases out of the box, so it saves you time, whereas it will take more time to adapt Flask to changing requirements.

It’s the second most popular general-purpose programming language, less popular than JavaScript and two other fundamental web technologies—HTML/CSS and SQL—as shown in the 2020 Stack Overflow survey.

Source: 2020 Stack Overflow Developer Survey

However, this doesn’t mean that all developers who picked Python in the survey are senior developers whose main tool of choice is Python. Building a web backend with Python is a very common use case, but a lot of developers use Python in their everyday work in other ways, for things like:

• automating processes like web scraping or data segmentation,
• gluing together different APIs and components built with various technologies,
• visualizing data.

And then there’s AI and machine learning. Python truly reigns supreme in this area. It’s currently the main language used for AI and ML, while experts say it will continue to dominate.

Given that AI/ML is currently one of the hottest, if not the single hottest thing to do in computer science, it’s a big contributor to Python’s popularity.

This popularity results in a large number of Python developers with professional experience. For you, this means that it should be much easier to hire Python developers for your team than, for example, C++ developers.

As it usually happens, some developers will tell you that Python is great for performance, others will give you 10 reasons why it isn’t. Our Solutions Architect, Piotr Podgórski, is here to tell you not to worry too much about performance:

“Selecting tech for speed of execution, rather than speed of development, is a rookie mistake. Python is a very good language to build and iterate quickly. Performance is important, but responding to changing needs even more so. Plus, with good architecture, you can always find and optimize bottlenecks.”

—Piotr Podgórski, Solutions Architect

That’s not all. The opinion that Python makes it hard to achieve fast performance is simply not true.

The myth comes from CPython, the default implementation of Python. By itself, CPython is indeed slow and eats up resources like every day is cheat day—but this is a solvable problem! We can optimize it, employ a special architecture, or use tools like asyncio, PyPy, and Cython to improve performance.

What’s more, after a failed attempt to retire, Guido van Rossum (Python’s original creator) is working on Python again—this time at Microsoft. His main goal is to turbocharge CPython to make it faster than ever, so the performance will only keep getting better.

Junior Python programmers can do web development with great results. You don’t have to be worried about junior Pythonistas building your next web app, even if there’s money on the line—there are projects in our portfolio that are proof of this.

Which is great, because finding junior Python developers is relatively easy compared to most programming languages. As a matter of fact, Python seniors are a little easier to find, too—although remember that, in this industry, “a little easier” doesn’t mean it’s simple. There’s just a wider talent pool available than with less popular languages.

If you need to build a team quickly, start development as fast as possible, and make sure you reach the MVP stage quickly—Python is a great choice.

Fintech and medtech come to mind as the most prominent examples of industries that are perfect for Python.

Large amounts of data, visualizations, analyses, the need to predict things, the need for AI because the problems are too complex for humans to do efficiently, the often devastating consequences of bad decisions—finance and healthcare have it all.

Of course, they’re not the only industries with huge amounts of data and a lot of risks. If you’re wondering whether Python is right for your project, consider the data at the core of your business model.

If it’s as complex as in finance or healthcare, then Python might be a great choice either as the main technology or in a supportive role.