Python: How the Slowest Programming Language Became the King of Neural Networks

Python, created by Guido van Rossum back in February 1991, had established itself by 2026 as the main language of machine learning and data science, despite its reputation as one of the slowest languages. An analysis on Habr explains that the reason is not the speed of the language itself but its architecture and ecosystem.

Why Python is considered slow

Python runs slower than compiled languages because it is interpreted, uses dynamic typing, and has a global interpreter lock (GIL), which prevents threads from executing bytecode in parallel. The interpreter parses each line at runtime rather than in advance, which is where the speed penalty comes from.

Yet the language is far from young. The first version of Python came out in 1991 and was named after the British comedy show "Monty Python's Flying Circus". Python 2.0 appeared in 2000, and the incompatible Python 3.0 in 2008, years before the current AI boom and most modern web and ML frameworks.

How Python took over machine learning

Python became the standard in data science thanks to an ecosystem of libraries that move heavy computation into fast C/C++ code and onto GPUs. The developer writes a simple, readable script, and under the hood the matrix operations are computed not by the interpreter but by optimized backends.

Key milestones of this ecosystem:

• 1991 — Guido van Rossum releases the first version of Python
• 2006 — NumPy appears, a library for fast array computations in C
• 2008 — pandas is released for working with tabular data
• 2015 — Google open-sources the TensorFlow framework
• 2016 — Facebook (now Meta*) releases PyTorch, which became the standard in research

This combination of a convenient syntax on top and fast C and CUDA underneath removed the main objection to Python: users do not have to sacrifice speed for simplicity, because the performance-critical parts are already written in low-level languages.

What Python offers developers

Python's main advantage is its low barrier to entry and readable code, which is why both beginners and researchers choose it, since for them testing a hypothesis quickly matters more than squeezing the maximum out of the hardware. By the philosophy of the language, simple and clear code is valued above clever and "fast" code.

"Simple is better than complex.

Readability counts." — Tim Peters, "The Zen of Python" (PEP 20)

Rankings confirm its popularity: in the TIOBE index, which tracks the demand for programming languages, Python has held first place for several years now, overtaking traditional leaders such as C and Java.

What this means

Python's story shows that dominance of a language in AI is decided not by raw speed but by ecosystem and convenience: heavy math can be delegated to C and the GPU, leaving people with simple syntax. That is why a language from 1991, rather than faster newcomers, became the face of the current wave of neural networks.

Frequently asked questions

Who created Python and in what year?

Python was created by the Dutch programmer Guido van Rossum, and the first version came out in February 1991. The name of the language refers not to the snake but to the comedy show "Monty Python's Flying Circus".

Why is Python slow yet used in machine learning?

The Python interpreter itself is slow because of dynamic typing and the GIL, but in ML the heavy computation is done by the NumPy, TensorFlow, and PyTorch libraries, which are written in fast C/C++ and run on the GPU. The developer writes simple code, while a low-level backend provides the speed.

Is Python the most popular programming language?

According to the TIOBE index, Python has ranked first among programming languages for several years now, largely thanks to the boom in data science and machine learning.

*Meta is designated an extremist organization and banned in Russia.