What Is Python? The Python Programming Language Explained: Uses, Pros and Careers

The Python programming language is a general-purpose tool: people use it to build websites and APIs, analyse data, train neural networks, automate routine work and write small utilities. It is loved for its readable syntax. Python code looks like carefully written English, which is why many people pick it as their first language. Below we explain how it works, where it is used, its strengths and weaknesses, and what a Python developer does all day.

What Python is in plain English

A programming language is a way to tell a computer what to do using text that people can read. Python is one such language, and it needs very few symbols: code blocks are marked by indentation instead of curly braces, and variables do not have to be declared with a type in advance.

Here is a complete program that adds up expenses by category:

expenses = [("Food", 450), ("Transport", 120), ("Food", 300)]

totals = {}
for category, amount in expenses:
    totals[category] = totals.get(category, 0) + amount

for category, total in totals.items():
    print(f"{category}: {total}")

Food: 750
Transport: 120

Even without experience, it is fairly easy to see what is going on. That is the main idea behind the language: code is read far more often than it is written, so it has to be easy to read.

How to pronounce Python and where the name comes from

The name is pronounced "PIE-thon". The language is named after the British comedy show "Monty Python's Flying Circus", not after the snake. The snake appeared later, in the logo and in book covers.

How the Python language works

High-level and interpreted

Python is a high-level language: you work with lists, dictionaries, strings and files, not with memory addresses. Memory is managed by a garbage collector.

Python programs are usually not compiled into a separate executable file. The interpreter (the standard implementation is called CPython) reads the .py source file, translates it into bytecode and runs it straight away. That is why the "write, run, see the result" cycle is very short:

$ python3 hello.py
hello

Dynamic but strict typing

A variable's type is determined by its value at run time: the same variable can hold a number first and a string later. Python does not mix types silently, though. You cannot add a string and a number:

>>> "5" + 3
Traceback (most recent call last):
  File "<python-input-0>", line 1, in <module>
    "5" + 3
    ~~~~^~~
TypeError: can only concatenate str (not "int") to str

For large projects there are type annotations (def total(items: list[int]) -> int) and checking tools such as mypy. The interpreter does not enforce annotations, but editors and checks point out errors before the program runs.

Multi-paradigm

In Python you can write simple top-to-bottom scripts, functions, object-oriented classes or functional code with generators and comprehensions. The language does not force you to pick one approach. Usually they are mixed depending on the task.

"Batteries included"

Python ships with a large standard library: working with files and paths, JSON and CSV, dates, HTTP, regular expressions, SQLite databases, testing and asynchronous code. Everything else comes from the hundreds of thousands of packages in the PyPI catalogue, which you install with one command using pip or the uv manager.

What Python is used for: where it applies

Python is a general-purpose language, so the question "what is Python used for" really asks where it is especially strong.

Python is also embedded in other programs as a scripting language, for example in Blender, QGIS and many data tools. It also sits under the hood of many utilities on Linux and macOS.

Where Python is rarely used

Python is not a language for everything. Browser interfaces are written in JavaScript or TypeScript, mobile apps in Kotlin and Swift, games on large engines in C++ and C#, and drivers and firmware in C, C++ and Rust. Python does appear there, but in a supporting role: build scripts, tests and tooling.

Pros and cons of Python

Pros

• Readability. Short, clear code that is easy to maintain and to review.
• Quick start. You can write your first useful program on the first day, without any build setup.
• Ecosystem. There is a ready library for almost any task, and for data and AI Python is the de facto standard.
• Cross-platform. The same code runs on Windows, macOS and Linux.
• Free and open. The language is developed by a community and the non-profit Python Software Foundation, and changes go through open PEP proposals.
• Demand. Python skills are useful not only to programmers but also to analysts, testers, engineers and scientists.

Cons

• Execution speed. Pure Python is slower than compiled languages in heavy computational loops. In practice, heavy computation is done by libraries written in C (NumPy, PyTorch), and bottlenecks are found with a profiler.
• Type errors show up at run time. Without annotations and tests, some errors appear only while the program is running.
• Start-up time and memory. Importing large libraries noticeably slows down short scripts, and Python objects take more memory than similar structures in C.
• Distribution. Handing a user a single ready-made executable is harder than in Go or Rust.
• Not for the browser or mobile. Python is almost never used in these areas.

The language is gradually closing some of these gaps. For example, Python 3.15 added lazy import (PEP 810): a module is loaded on first use rather than at start-up. The course shows a measurement: a script that imports pandas and prints one word started in 280 ms, and with the lazy import it started in 14 ms.

# Python 3.15
lazy import pandas as pd
print("hello")                 # pandas is not loaded yet
df = pd.read_csv("trips.csv")  # loading happens here

Python history and its creator

Python was created by the Dutch programmer Guido van Rossum. He started work on the language in the late 1980s, and the first public version came out in 1991. For many years Guido was the language's chief architect; today decisions are made by an elected Steering Council.

• Python 2 — the branch on which a huge part of the ecosystem grew. Its support ended on 1 January 2020.
• Python 3 — released in 2008 and deliberately broke compatibility for the sake of a cleaner language: for example, print became a function and strings became Unicode by default.
• Modern rhythm — a new Python 3 version comes out every October. Python 3.15 was released on 9 October 2026, and Python 3.10 stops receiving even security fixes in October 2026.

If you come across a tutorial with print "hello" without parentheses, it is written for Python 2, and that code will not run on a modern version.

What is new in Python 3.15

A short overview of the notable changes in the latest release:

• PEP 810 — lazy imports with lazy import;
• PEP 814 — the immutable dictionary frozendict;
• PEP 798 — unpacking in comprehensions: [*g for g in [[1, 2], [3]]] gives [1, 2, 3];
• PEP 799 — the Tachyon sampling profiler: python -m profiling.sampling run app.py;
• PEP 686 — UTF-8 as the default when working with files;
• "Did you mean" hints in error messages.

The Python logo

The Python logo shows two stylised snakes, one blue and one yellow, intertwined into a shape that looks like a plus sign. It is used on python.org, in the documentation and as the icon for .py files. The logo is a trademark of the Python Software Foundation: you may use it for the community, educational materials and talks, but for commercial products check the PSF rules on python.org.

Who a Python developer is

A Python developer is a programmer who writes and maintains programs in Python. "Python developer" is more of a foundation than a specific job title: in practice the work depends heavily on the field.

What a Python developer does in a working day

A typical day: understand the task, write code and tests, send changes for review through Git, fix comments from colleagues, and track down a bug from a traceback in the logs. A large share of the time goes not to writing new code but to reading existing code, and this is where Python's readability pays off again.

Core skills

• syntax and data types, conditions, loops, functions;
• collections: lists, dictionaries, sets, comprehensions;
• exceptions and reading a traceback;
• modules, packages, virtual environments and dependencies (pip or uv);
• working with files, JSON and CSV;
• classes and OOP, the basics of asynchronous code;
• Git, the terminal, tests.

Is Python a good first language?

Yes, for most people it is one of the best choices. The minimum of syntactic noise lets you focus on programming itself: variables, conditions, loops and functions. At the same time, the language is not a toy: the same knowledge applies directly at work.

To start, you only need a computer with Windows, macOS or Linux and the ability to open a terminal. You can check whether Python is installed and which version it is with one command:

$ python3 --version
Python 3.12.3

If the version is older than 3.15, or the command is not found, install a recent Python. It is better to learn on a current version from the start, so you do not have to relearn things later.

Summary

Python is a versatile, readable and free programming language that is equally at home in web back ends, data, AI and automation. Its weak points, the speed of pure code and late detection of type errors, are in practice covered by libraries, annotations and profiling. The overview of the language and the learning path from the first command to the profiler are covered in the introductory lecture of the course "Python 3.15: from beginner to pro".