Python bleeds market share as ai coding tools erode its dominance
Python is leaking users faster than a rusty pipe. After four years of unbroken growth, the language that once swallowed the planet has shed more than five percentage points of market share in six months, tumbling from 26.98 % in July 2025 to 21.81 % in March, according to Tiobe’s latest tracker. The slide is the steepest single-period drop Tiobe has recorded for any top-tier language since the index began.
The culprit is not a shiny new competitor; it is the quiet disappearance of hand-written scripts. Code-generating models—GitHub Copilot, Amazon CodeWhisperer, the open-source StarCoder family—now spit out working Python faster than most humans can type. The result: millions of lines that no one actually “programs,” only curates. “Users discover they need a domain-specific finish,” Tiobe CEO Paul Jansen tells TechBloom. “They grab R for stats, Perl for text munging, even Fortran for numerics. Generic simplicity has become Python’s handicap.”
R and perl claw back from the grave
R, long dismissed as a statistical backwater, jumped from 15th to 8th in the rankings, its share doubling to 2.19 %. Perl—yes, the “dead” language—vaulted from 30th to 11th, climbing to 1.67 %. Both offer batteries-included libraries that target narrow, expert domains where prompt-driven IDEs still stumble. “If I need a ranked regression with missing-data imputation, R already has the package,” says Marina Gómez, lead data scientist at Madrid’s Grupo Sese. “Copilot can’t guess which CRAN fork I trust.”
Meanwhile, C and C++ are tightening the noose. C now sits 10.76 percentage points behind Python, the smallest gap since 2018. C++ trails at 8.55 %, buoyed by embedded and high-frequency trading shops that prize deterministic speed over ai convenience. “Latency is a feature, not a bug,” notes Bjarne Stroustrup, C++’s creator, quoting his own maxim: “There are only two kinds of languages: those people complain about and those nobody uses.” Python, suddenly, is hearing the complaints loud and clear.
Two indices, one verdict
Tiobe’s numbers are echoed—though softened—by the rival PYPL index, which measures Google tutorial searches rather than engineer head-counts. There, Python still commands 31.17 %, down just 1.4 points since August. Yet even PYPL shows R surging to 6.88 %, its highest tally ever. The divergence is telling: professionals already made the switch; students are catching up.
The geographic split is stark. In Bangalore and Shenzhen, boot-camps still pump out rookie Pythonistas. In Berlin and Boston, start-ups are ripping Flask APIs apart and replacing them with Rust micro-services. “We rewrote our prediction layer in Rust plus Polars,” says Leo Tang, CTO of fintech PipeFly. “Compile-time safety beats Python’s ‘easy’ any day when you’re moving money.”
Python’s defenders point to its unmatched ecosystem—PyTorch, Django, Pandas—and to the language’s lock on university syllabi. But those advantages are amortized across millions of auto-generated notebooks that no human will ever debug. When the code writes itself, the community that once maintained it drifts away.
Guido van Rossum, Python’s benevolent dictator emeritus, declined to comment on the Tiobe figures. His last public commit to the reference implementation landed in January. Since then, core developer activity has fallen 18 % year-on-year, GitHub telemetry shows. The torch is technically still burning; it just feels colder.
Bottom line: Python isn’t dying—it’s commoditizing. The language that taught the world to code is becoming the wallpaper of ai-generated scripts, invisible and unpaid. Market share is not destiny, but the hemorrhage is real, and the bandages are still in beta.