Python Popularity Reasons

You misunderstand the ecosystem. Many folk program in Python because it’s largely forced upon them. It’s often the easiest language to work with for data science, ML Eng, or data engineering, despite many frameworks actually running in the JVM. It’s simply more accessible. The appeal of Python has not been its provenance or design for over 15 years, but rather the ecosystem.

Anecdotally, it seems to me that it's increasingly common to see Python as the language of choice in greenfield projects. I've seen this in organizations -- scientific, academic, industrial -- that aren't primarily software-oriented. This involves both internal applications/utilities and general use for statistical analysis, machine learning, and data processing.It may be that choosing Python for a customer-facing web service would only be done now because of inertia or ri

I’m not the parent poster, but I’ve seen two major spurts of Python’s popularity: (1) the mid-2000s when Python became a popular scripting language, displacing Perl, and (2) beginning in the first half of the 2010s when an entire ecosystem of Python APIs backed by code written in C, C++, and even Fortran made up the infrastructure for machine learning code (e.g., NumPy, SciPy, scikit-learn, Pandas, etc.). If Python didn’t have a good way of interfacing with code written in languages like C, the

Python seems adecuate, big ecosystem in many domains, language gets out the way for quickly writing stuff.Note: not a fan of python as a language.

Python optimized for C-interop (NumPy) just as data science exploded. While Perl won text processing, Python became the universal interface for C libraries. That ecosystem lock-in—not syntax—is why it won. It was the right glue at the right time.

I wouldn't call it sudden at all. Python is great for the reason Java is great: diverse robust ecosystem for a ton of different fields. It's about ubiquity.It's installed on virtually everything already. It's one of the easiest languages to learn (the basics), and is used as a teaching language. Even outside of CS everyone knows it.Used in web programming (Django, Flask, etc.), numerical computing (Jupyter, numpy, scipy, pandas), AI/ML (TensorFlow, scikit-learn), b

I don't know really, but I was under the same impression, python taking over. That wouldn't be surprising since it's a more general, more expressive, more known language that has been embedded in many other softwares (blender comes to mind)

Seem to me that Python has won. What I mean by that is that it is used almost everywhere and there is almost no compelling reason to use anything else. You want web? Django, plus a million other frameworks, all well tested and documented. Machine learning? Tensorflow, Keras or PyTorch. Scientific computing? Numpy.For the last two decades people have complained about (C)Python not being multi-threaded, not jitted, not having tco, being to simplistic and so on. In practice it seem to have matte

I use Python by choice and the more there is growing need for Natural Language Processing, Machine Learning, Data Mining, the more I can not leave Python.I try Rust, Ruby and others on the side. But Python is just so heavily fortified now that I constantly suggest startups who are going to build non-trivial tech to select Python. Also the whole Linux, deployment, etc. space is filled with Python.Biology, Physics, Math folks also use more Python than any other language.

Python is not technically superior to other languages enough that you can rhetorically ask that question. It’s main advantage is the ecosystem and network effects. If a bunch of people, especially the people who work on numpy, scipy, etc., decide to work on developing libraries for other languages like R and Julia, the data science ecosystem would switch over in a few years. Similarly for other fields people might switch to languages like Elixir, Haskell, OCaml, Go, Swift, Scala, Ruby, Kotlin, e