By ByteBot
Python just had its biggest adoption jump in over a decade. The 2025 Stack Overflow Developer Survey shows Python usage surged by 7 percentage points year-over-year, reaching 57.9% adoption among developers. That’s the largest single-year increase in Python’s modern history, and it’s not a coincidence. The survey explicitly connects this growth to the AI boom, noting that “programming languages growing in popularity are also known to be AI-compatible.”
The AI Connection Isn’t Speculation—It’s Data
Stack Overflow doesn’t bury the lede here. In fact, the survey directly attributes Python’s explosive growth to AI development, and the numbers back it up. With 84% of developers now using or planning to use AI tools—up from 76% in 2024—and 41% of Python developers specifically working on machine learning, the correlation is undeniable.
Moreover, Python didn’t just grow in surveys. It overtook JavaScript as the most-used language on GitHub in 2025, with a 22.5% year-over-year increase in contributions. It now holds the #1 position on the TIOBE Index at 22.85%, crushing C (10.64%) and Java (9.6%). This isn’t gradual adoption—it’s an acceleration driven by one force: the AI revolution.
When ChatGPT launched and LLM development exploded, Python was the obvious choice. Consequently, the ecosystem—NumPy, pandas, PyTorch, TensorFlow—has been battle-tested for years, making it the foundation for AI development. AI agent frameworks like LangChain and LangGraph? Python. Model training and fine-tuning? Python. Data pipelines feeding AI systems? Also Python. The survey proves what practitioners already knew: if you’re building anything AI-adjacent in 2025, you’re probably writing Python.
FastAPI’s Rise Is the Real Story
While everyone focuses on Python’s overall growth, FastAPI’s +5 point increase is quietly rewriting the web framework landscape. Stack Overflow calls it “one of the most significant shifts in the web framework space,” and they’re not exaggerating. FastAPI adoption jumped from 29% in 2023 to 38% in 2025, while Flask declined 5% and Django grew a modest 10%.
The performance gap explains the shift. FastAPI delivers 2,847 requests per second compared to Flask’s 892 and Django’s 743. That’s 3.2x faster than Flask and 3.8x faster than Django—not through clever hacks, but through modern Python: async/await, type hints, and automatic API documentation. In other words, FastAPI represents what Python looks like when it evolves instead of stagnating.
Market share tells the story: Django still holds 45%, Flask 30%, but FastAPI is already at 20% with +120% growth. The framework isn’t just popular—it’s changing how developers build with Python. Type hints aren’t optional anymore. Async patterns are expected. Automatic docs are table stakes. FastAPI proved Python could be fast, modern, and still feel like Python.
Python Adoption Drives 356K Jobs, $128K Salaries
Python’s growth translates directly into opportunity. The job market projects 356,700 annual openings through 2033, with over 1.19 million current LinkedIn listings requiring Python skills. Average salary sits at $127,976, with senior machine learning engineers clearing $212,928+. That’s a 10.1% year-over-year salary increase, driven by Python’s dominance in high-growth sectors like AI, machine learning, and cloud computing.
For developers considering career paths, this data is actionable. Learning Python isn’t just about staying relevant—it’s about positioning yourself in the highest-demand, highest-paying segment of the market. Furthermore, enterprise adoption will increase 25% by the end of 2025, meaning demand isn’t slowing down.
Rust-Powered Tools Are Solving Python’s Weaknesses
Rust is systematically dismantling Python’s historical knock—”it’s slow.” Tools like uv (package manager), Ruff (linter), and Pydantic v2 (validation library) rewrite Python tooling in Rust, delivering 10-100x speed improvements without sacrificing Python’s developer experience.
uv replaces pip, poetry, and conda with Rust-powered package management that’s 10-100x faster. Ruff replaces Flake8 and Black with linting that’s orders of magnitude quicker. Additionally, Pydantic v2, which powers FastAPI’s validation, rebuilt its core in Rust for performance. The pattern is clear: Python keeps its readability and ergonomics while Rust handles the performance-critical paths. Best of both worlds.
What This Means for Developers
Python’s AI moat is deepening, not shrinking. On the other hand, Rust and Go each gained 2 percentage points in the survey, competing in infrastructure and cloud-native development. However, Python’s ecosystem advantage in AI/ML is massive. Replacing NumPy, pandas, and PyTorch would require an entire ecosystem migration—not happening anytime soon.
The takeaways are clear:
- Learn Python for AI roles – It’s the entry point. 41% of Python developers work in ML, and that percentage is growing.
- Explore FastAPI for modern web development – It’s not just faster; it’s setting the standard for what Python frameworks should be.
- Embrace type hints and async patterns – Modern Python isn’t optional Python. Tools expect type annotations, and async is the performance unlock.
- Watch the Rust-Python integration trend – Python’s future performance gains come from Rust-powered tooling, not Python itself.
Everyone knew Python was popular. What’s news is that growth accelerated in 2025. The AI boom explains everything—without ChatGPT and LLMs, Python’s adoption would be incremental, not explosive. The 2025 Stack Overflow survey doesn’t just confirm Python’s dominance. It proves the AI revolution is reshaping the entire developer landscape, and Python is at the center.
