Python is Becoming the New PHP

Ma Xiaobian^{HundredMillionFans CertifiedAccount}

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Last Tuesday at 2 AM, staring at a performance analysis report, my stomach was in knots. Our Flask API waschoked by 500 concurrent— not 50,000, butfive hundred. The problem was not in the business code.The blame lies with Python.

No one at the conference was willing to admit it, and no one wrote in their blogs, “Maybe we took a wrong turn.” But if you’ve been around long enough, you can feel it:the cracks are widening.

The Foundation is Crumbling: The Foundation is Losing Money

Let’s get to the facts.The Python Software Foundation— the group responsible for keeping Python alive —lost $1.46 million in 2025 and was forced to suspend its funding programs. This is not a startup running out of funding; this is themoat of the “most popular” language in the world.

Now they are basically relying onprayers + corporate donations to survive.

Think about it: if the JavaScript Foundation reported such losses, X (Twitter) would have exploded. **Python? Silence.

Rust is Eating Python’s Lunch

Even more surreal:At the 2025 Python Language Summit, a bombshell was dropped —one-third of the new native modules in PyPI are written in Rust.

Read that again.To make Python run decently, Python developers learned another language and then rewrote the core logicin Rust.

Pandas? is being overshadowed by Polars (underlying Rust).
Pydantic? Corerewritten in Rust because Python couldn’t handle it.

The Blind Spot of “Growth”: Many Users, but Shallow

Yes,Python grew by 7% last year. Sounds cool, right? But on the other hand,half of Python users have been in the field for less than two years.Half.

This is not prosperity; this is arevolving door.

Moreover, only 15% of developers are using 3.13 (the latest stable version). This is not “conservative”; this isunwillingness to progress.

JS developers complain aboutframeworks not updating for 6 months; Python developers are still using code from 2018. It’s called “robust engineering,” but in essence, it’sstagnation.

The AI Myth We All Believed

“Python is carrying AI!” Of course, just like my steering wheel “drives” the car.

TensorFlow? is built on C++/CUDA.
PyTorch? also relies on C++/CUDA.
NumPy? has ancestral roots in Fortran.

Python is not the engine; it isthe pretty steering wheel outside the engine. As AI moves to mobile, embedded, and edge computing— everywhereperformance is critical— Python will be left behind.

You can’t just stuff a 200MB Python runtime into a mobile device and call it a day. The real players have already turned tocompiled languages,Python is too slow to keep up.

The Trap of “Ease”

Python is popular because it issimple. The selling point is: “No need to understand the underlying computer! pip install and take off!“

The marketing was successful, butthe aftereffects are terrible.

Now we have a large number of developers:

who thinkmemory management is someone else’s concern;
who rely on increasing AWS budgets to solve performance issues;
who treat restarting services as debugging.

Meanwhile, Rust developers write code that isfast and safe becausethe compiler forces them to learn the fundamentals. It’s not that they are smarter; it’s just thatthey can’t skip class.

The Big Companies Have Already Left

Go to any big company and seewhat real production systems are written in. It’s not Python.

Python is used for:

scripts, data analysis,glue layers. Boring but useful.

When it comes to building atruly resilient system that can handle millions of users? They are using:

**Java / Go / C#**.

Because in scalable scenarios,“writing fast” = “burning money fast”. No engineering director wants to explain on Black Friday:“Python GC is acting up today.”

Toolchain: No One Can Fix It

After writing code for 10 years, I’ve seen many languages.Python’s dependency management is the most chaotic.

pip ignores poetry,conda has its own faction;
virtualenv sometimes works, sometimes fails.
Every Python project starts from the same hell:half an hour of environment firefighting, like defusing a bomb.

Rust?<span>cargo new</span>,done.Go?<span>go build</span>,that’s it.Python? Please reserve yourmorning.

The community’s standard answer is:“Use Docker.” That’s not a solution; that’sraising the white flag— putting the problemin a container and pretending it doesn’t exist.

How Languages Become “Zombies”

Python will not disappear overnight. It will be like:

Perl, PHP, COBOL — still alive but no longer growing.

The signs are already clear:

Foundation losses;
Core libraries switching to other languages;
Version stagnation;
Big companies have already changed lanes;
Growth comes from newcomers, who run away when they hit performance walls.

The language’s curtain calldoes not come with thunder, but rather everyonepretending nothing is wrong and slowly fading away.

The Sentence You Least Want to Hear

Every hour you spend improving your Python skills today is an hournot spent learning the languages that will truly be in demand in the next five years.

I’m not telling you to delete your repositories. But if you’re just starting out or considering where to invest your learning,putting all your chips on Python is like buying a house in a small town that just announced layoffs.

The writing on the wall is already there, but most people are unwilling to read it.

What Comes Next

Python will still exist:

in university courses, legacy systems, and “beginner articles” from 2019.

Butthe cutting edge? has already moved on.

The future does not reward “ease”. It rewards:speed, stability, and maintainability.

Python has had its glory days, and for many, it wasa beautiful time. Buttime moves on.

The question is no longer “Is Python dying?” But rather —Do you want to sink with it, or learn to sail a new ship?.

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