More than 30,000 Python developers from around the world answered questions for the Python Software Foundation's [1]annual survey — and PSF Fellow Michael Kennedy [2]tells the Python community what they've learned in a new blog post . Some highlights:

> Most still use older Python versions despite benefits of newer releases ... Many of us (15%) are running on the very latest released version of Python, but more likely than not, we're using a version a year old or older (83%). [Although less than 1% are using "Python 3.5 or lower".] The survey also indicates that many of us are using Docker and containers to execute our code, which makes this 83% or higher number even more surprising... You simply choose a newer runtime, and your code runs faster. CPython has been extremely good at backward compatibility. There's rarely significant effort involved in upgrading... [He calculates some cloud users are paying up to $420,000 and $5.6M more in compute costs.] If your company realizes you are burning an extra $0.4M-$5M a year because you haven't gotten around to spending the day it takes to upgrade, that'll be a tough conversation...

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> Rust is how we speed up Python now ... The Python Language Summit of 2025 [3]revealed that "Somewhere between one-quarter and one-third of all native code being uploaded to PyPI for new projects uses Rust", indicating that "people are choosing to start new projects using Rust". Looking into the survey results, we see that Rust usage grew from 27% to 33% for binary extensions to Python packages... [The blog post later advises Python developers to learn to read basic Rust, "not to replace Python, but to complement it," since Rust "is becoming increasingly important in the most significant portions of the Python ecosystem."]

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> PostgreSQL is the king of Python databases , and only it's growing, going from 43% to 49%. That's +14% year over year, which is remarkable for a 28-year-old open-source project... [E]very single database in the top six grew in usage year over year. This is likely another indicator that web development itself is growing again, as discussed above...

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> [N]early half of the respondents (49%) plan to try AI coding agents in the coming year. Program managers at major tech companies have stated that they almost cannot hire developers who don't embrace agentic AI. The productive delta between those using it and those who avoid it is simply too great (estimated at about 30% greater productivity with AI).

It's their eighth annual survey (conducted in collaboration with JetBrains last October and November). But even though Python is 34 years old, it's still evolving. "In just the past few months, we have seen two new high-performance typing tools released," notes the blog post. (The ty and Pyrefly typecheckers — both written in Rust.) And Python 3.14 will be the first version of Python to completely support free-threaded Python...

> Just last week, the steering council and core developers officially accepted this as a permanent part of the language and runtime... Developers and data scientists will have to think more carefully about threaded code with locks, race conditions, and the performance benefits that come with it. Package maintainers, especially those with native code extensions, may have to rewrite some of their code to support free-threaded Python so they themselves do not enter race conditions and deadlocks.

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> There is a massive upside to this as well. I'm currently writing this on the cheapest Apple Mac Mini M4. This computer comes with 10 CPU cores. That means until this change manifests in Python, the maximum performance I can get out of a single Python process is 10% of what my machine is actually capable of. Once free-threaded Python is fully part of the ecosystem, I should get much closer to maximum capacity with a standard Python program using threading and the async and await keywords.

Some other notable findings from the survey:

Data science is now over half of all Python. This year, 51% of all surveyed Python developers are involved in data exploration and processing, with pandas and NumPy being the tools most commonly used for this.

Exactly 50% of respondents have less than two years of professional coding experience! And 39% have less than two years of experience with Python (even in hobbyist or educational settings)...

"The survey tells us that one-third of devs contributed to open source. This manifests primarily as code and documentation/tutorial additions."



[1] https://lp.jetbrains.com/python-developers-survey-2024/

[2] https://blog.jetbrains.com/pycharm/2025/08/the-state-of-python-2025/

[3] https://pyfound.blogspot.com/2025/06/python-language-summit-2025-what-do-core-developers-want-from-rust.html