What is Python?

Python is a programming language used for everything from website development to data analysis and machine learning. It’s a high-level language, which means it’s closer to how people understand language compared to more low-level languages like Assembly.

Every year, StackOverflow does a developer survey to “explore the tools and technologies developers are currently using and the ones they want to use”. In its 2025 survey of just over 30,000 people, 57.9% of all respondents said they had used Python in the past year — a 7-point increase compared to 2024. It put Python in 4th place behind JavaScript (68.8%), HTML/CSS (63%), and SQL (61.3%).

Data suggests that rise is only expected to increase, given that among those learning to code, 71.8% of respondents said they had used Python in the last year. That makes Python one of the most popular programming languages in the world right now, especially with the AI wave — 57.7% of respondents who worked with AI had used Python in the last year.

The TIOBE Index has consistently listed Python as the most popular programming language, too. Python has been listed in TIOBE’s Programming Language Hall of Fame six times over the past 21 years, the most entries of any language.

Let’s explore what Python is, its history, why it’s so popular, the advantages it offers, and the frameworks that it works well with. We’ll also take a look at popular use cases and what makes Python such a natural choice for those applications.

Brief History and Origin of Python

The history of Python is an interesting one. It started as a side project for its creator, Guido van Rossum. First released in February of 1991, Guido reportedly named the language after sketch comedy show Monty Python’s Flying Circus.

Over the course of the 90s, van Rossum set out four clear goals for Python:

• To be an an easy and intuitive language as powerful as other major languages
• To be open source, so anyone can contribute to its development
• To have its code be as understandable as plain English
• To be suitable for everyday tasks, allowing for short development times

It’s safe to say that he achieved those goals successfully. Today, Python is used in projects of every possible variety, from data analysis and AI development to web scraping and web automation — even video games like Eve Online, which had more than 100,000 players logging on every day.

Python Pros and Cons

Python is considered one of the fastest growing languages in the world. Today, it’s mainly used for building automation and — with today’s AI hype — Python is helping lay the foundation on which AI is being built.

The fact Python’s easy to use is a big reason why developers and newcomers are choosing to learn it, but it’s only one of several reasons:

Advantages of Python

• Open source: Python can be downloaded and used for free, which means the barrier to entry is almost zero. The transparency that Python’s open-source nature provides means builders can trust it. It also then itself attracts those who believe in open-source projects and software, growing a likeminded community.
• Active community: Having an active community is a blessing. Python’s community is very active, which means there’s endless tutorials to learn from, forums to ask questions and share ideas, and existing projects of all sizes to borrow inspiration from.
• Easy to use and learn: Python’s a high-level language and van Rossum intentionally set about creating a language that is easy to understand. The result is a language that’s easy to learn both for people completely new to coding and for builders who want to branch out into a new language.
• High efficiency: Python offers flexible process control, which gives developers control over which processes should run at which time, including whether they run at the same time or not. It also offers a massive ecosystem of libraries that work well on their own but can also communicate with each other. That makes managing large-scale projects much easier, because otherwise complex tasks become much easier to coordinate, especially among larger teams. This means that the investment of time and resources to quickly developing projects — from single-purpose programs, to web automation, to getting AI models to be trained, deployed, and maintained — is much lower.

Disadvantages of Python

As is often the case, some of Python’s greatest advantages are also the source of some of its disadvantages. Let’s dive into some of the trade-offs that come with using Python.

• Performance: Python is an interpreted (rather than compiled) language, which means the code is executed line by line (rather than translated ahead of time and executed all at once). To grossly simplify it, the high-level Python code has to be translated into something your computer understands before those instructions can be carried out. Python performs slower than Java or C, which are compiled languages.
• Not strict enough: Since Python does not have any restrictions on values, i.e. it doesn’t have fixed types. This can cause issues for larger teams, where several people might be working on the same code at different times. Without fixed types it can be difficult to see at first glance what a function expects and returns. Bugs are also harder to catch ahead of time.
• Learning curve: Python is easy to learn, but it can quickly become overwhelming to know how to proceed once you’ve gotten started. There are hundreds of thousands of packages and libraries (due to its open-source nature). There can be hundreds of resources to help you complete the same task and navigating through all these options can be difficult for newcomers.
• Not native to mobile: Python is mainly used for server-side programming, so client-side activities like web and mobile development aren’t directly supported by Python itself. With that said, there are a couple of libraries that you can use to create a web UI, which is mostly used for prototyping.

Like any programming language, there are pros and cons to Python. It’s up to each developer to choose a language, whether that choice is based on preference, the project and its scale, personal skillsets, community support, or any combination of these factors.

What Is Python Used For?

As we discussed, Python is a very easy language to start learning, regardless of your initial level of knowledge. As a result, people have used it to do all sorts of things in the last 20 years — there are hundreds of thousands of Python frameworks. It’s so accessible that both technical and non-technical people can and have used it to do everything from web automation to managing artificial intelligence — some have even used it to make a basketball hoop catch a ball no matter how bad your aim is. Let’s explore Python’s wide variety of use cases.

Python for AI

With the current wave of interest and investment into LLMs, Python has emerged as the main language for interacting with AI (most companies I have worked with have used Python for AI). It’s easy to use and learn, and the number of AI-related frameworks keeps growing.

Let’s use just one example: Python is the language of choice for anything related to computer vision, the field of computer science dedicated to teaching AI to interpret and understand images and videos. On top of that, Python is the primary language to build and train GenAI chatbots (GPT, LLama, Claude, Gemini, Deepseek, and more).

Python for Data Analysis

Data analysis has been around for a long time, but never has the need for data been greater for so many people with such a wide range of technical knowledge. Everyone from dedicated data analysis experts at a multibillion-dollar multinational to the teenager doing dropshipping on the weekends — and everyone in between — has data that they want to analyze.

Everyone uses Python for data analysis for a few straightforward reasons, but we’ll break down just one: Python has mature, dedicated libraries to handle every aspect of the data analysis process, from pandas and NumPy for aggregating and cleaning data at the start of the process and something like PyTorch doing predictive analysis at the end of the process.

Python for Development

Server-side development is Python’s bread and butter. Frameworks like Django or Flask are great at handling logic; dealing with databases; and managing content, security and URL routing.

The community is a strong reason Python’s so popular for server-side development. There are lots of resources available, lots of people who have tackled similar problems, and lots of ways to learn how to tackle problems you may encounter.

It’s so versatile that Python for development has the added bonus of being able to tackle such a wide variety of problems without needing to switch to a different programming language. In the event you do need to switch languages, Python works well with others, too.

Python for Automation

Python is such a great tool for automating repetitive tasks. By repetitive task I mean something you do every day with the same steps every time. Python excels at automation, as long as the steps are clear and achievable — especially now with AI tools.

AI tools like activepieces and zapier can help you automate things even if you’re not technical at all, which is great for marketers and salespeople. It’s easily readable at a glance, and there are lots of libraries available.

Python for Internet of Things

Python plays a major role in a whole range of internet of things (IoT) technologies. Once again, it’s because Python’s easy to use, easy to read, and because it has a long list of libraries that support IoT applications.

There are lightweight versions of Python, like MicroPython and CircuitPython, which are designed to run on really small devices (both physically and devices with very limited resources). Additionally, Python has libraries for interfacing with hardware. Concretely, this means that Python is being used in everything from self-driving cars and traffic lights to smart homes.

Conclusion

Python is one of the most popular programming languages in the world and it has been for a while. It continues to be a rising start with more developers adopting it. Its growth shows no signs of slowing, given its popularity among new learners and its strong presence in innovative spaces like AI.

Its easy-to-understand nature makes it easy to learn and it doesn’t sacrifice any complexity to achieve that — if anything, its popularity sometimes means there are too many libraries and frameworks to choose from, which can be overwhelming. That being said, Python’s active community means there are countless tutorials, courses, videos, and teaching material to satisfy every type of learner.

Key takeaways:

• Python is easy to learn.
• Python has a very active community around it.
• There are hundreds of thousands of libraries and frameworks to support every possible topic of development.
• Python can be used to do everything from data analysis and web automation to making video games and programming self-driving cars.
• Python is at the forefront of AI development.

Python’s versatility seems to be limitless; if you can think of something to do, you can use Python to do it. Whether it’s someone with a hyperspecific pet project or a multibillion-dollar company finding new ways to proxy traffic over HTTP/3, Python and the community that has supported it for the past two decades seem to be eager to make it possible.

With the AI hype reaching unprecedented levels, Python adoption seems to be in for another spike. In another 10 years, who knows what other fields of computer science it will find itself in the foundations of?

Frequently Asked Questions