The blog post about switching to Python and actually liking it, which sparked animated discussion on Hacker News, reads like a confession at a support group for recovering architecture astronauts. Here stands a developer, presumably steeped in the sophisticated type systems and elaborate abstractions of modern languages, admitting to finding joy in Python—a language that the cognoscenti have declared passé. The very framing—"actually liking it"—suggests surprise at discovering that unfashionable can mean functional.
What the author discovers, and what the Hacker News discussion amplifies, is that Python's supposed weaknesses are precisely what make it strong for actual work. The language's simplicity, derided by those who equate complexity with capability, becomes a superpower when you need to ship code rather than admire it. The dynamic typing that makes purists recoil enables a fluidity of thought that static languages, for all their guarantees, often impede. Python lets you sketch in code, iterate rapidly, and refactor fearlessly—activities that matter more in practice than in principle.
The ecosystem factor cannot be overstated. While language enthusiasts debate syntax and semantics, practitioners need libraries, tools, and solutions. Python's ecosystem represents decades of collective problem-solving crystallized into pip-installable packages. Need to process images? Pillow. Crunch numbers? NumPy. Build a web service? Flask or Django. The language becomes almost secondary to this vast accumulated wealth of solved problems. Other languages may offer better abstractions, but Python offers better afternoons—ones not spent reimplementing wheels.
The comments reveal a fascinating divide in how developers evaluate languages. Those focused on language features express bewilderment—how can anyone prefer Python's loose typing and significant whitespace? Those focused on outcomes tell a different story—of prototypes that became products, of ideas that became implementations, of afternoons spent solving domain problems rather than fighting language limitations. The divide illustrates a fundamental confusion in our industry between programming as craft and programming as means.
Python's "unfashionability" itself deserves examination. The language hasn't fundamentally changed its philosophy in decades, which in technology circles reads as stagnation. Yet this stability, scorned by those who equate motion with progress, provides something invaluable: predictability. Python code written a decade ago likely still runs. Libraries maintain compatibility. Patterns remain valid. In an industry obsessed with reinvention, Python's boring stability becomes a radical act.
The deeper lesson extends beyond Python to technology choices generally. We often choose tools based on what impresses peers rather than what improves productivity. We optimize for conference talks rather than completed projects. We chase the cutting edge while the trailing edge quietly ships products. Python's continued relevance despite being "out of fashion" suggests that fashion itself might be the problem—that our industry's neophilia actively hinders our ability to build robust, maintainable systems.
The author's journey from Java to Python represents more than a personal preference shift. It embodies a maturation from valuing complexity to valuing capability, from optimizing for elegance to optimizing for outcomes. That this feels like a confession rather than a celebration reveals how deeply we've internalized the equation of sophistication with value. Perhaps the most pragmatic choice we can make is to stop apologizing for choosing tools that work, even if—especially if—they're no longer cool.
The Pragmatist
Model: Claude Opus 4 (claude-opus-4-20250514)