Is Python Heading for Obsolescence? Rust’s Rise and the Cracks in the Ecosystem

Foundation Loss and Financial Strain

The Python Software Foundation, which keeps the language alive, reported a loss of $1.46 million in 2025 and had to suspend its sponsorship program. This loss reflects a reliance on donations and corporate funding rather than a robust financial model.

Rust’s Encroachment on Python Core

At the 2025 Python Language Summit, it was announced that one‑third of new native PyPI modules are written in Rust. Projects such as Pandas are being overtaken by Rust‑based alternatives like Polars, and Pydantic is being rewritten in Rust because pure Python cannot meet performance demands.

Growth Numbers Mask Underlying Issues

Python’s user base grew 7 % last year, but half of those users have less than two years of experience. Only 15 % of developers use the latest stable release (3.13), indicating a reluctance to adopt newer versions. Many still rely on outdated code from 2018, leading to stagnation.

The AI Myth and Its Reality

While Python is often touted as the engine behind AI, many core AI libraries (TensorFlow, PyTorch) are implemented in C++/CUDA, and NumPy’s performance core is Fortran. Python serves mainly as a high‑level wrapper, and when AI workloads move to mobile, embedded, or edge devices, Python’s performance becomes a bottleneck.

“Easy” Appeal as a Double‑Edged Sword

The simplicity of installing packages with pip install has driven massive adoption, but it also creates a false sense of security. Developers often ignore memory management, rely on increasing AWS budgets to mask performance problems, and resort to frequent service restarts for debugging.

Toolchain Chaos and Dependency Hell

Python’s dependency management is fragmented: pip, poetry, and conda each have their own ecosystems, while virtualenv is unreliable. Setting up a Python project frequently turns into a half‑hour “environment rescue” operation.

Language Becoming a “Zombie”

Python is not disappearing overnight; it remains alive like Perl, PHP, or COBOL, but it no longer grows. The foundation’s losses, core libraries migrating to other languages, version stagnation, and large companies moving away from Python all point to a gradual decline.

Future Outlook

Python will persist in university curricula, legacy systems, and older tutorials, but cutting‑edge development is shifting to compiled languages that offer speed, stability, and maintainability. The ecosystem rewards fast, reliable, and maintainable code rather than ease of use.

Conclusion

The real question is not whether Python will die, but whether developers will continue to rely on it or start building new “ships” with languages better suited for high‑performance, large‑scale systems.