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The Python ecosystem is far too diversified to get knocked down by one language. Python has a wealth of production-quality libraries across a ton of domains (Web, scientific computing, data science, NLP, parsing, scripting/automating, etc). Go is a non-entity in most of these domains and isn't even a top-20 programming language on Github (source: http://sogrady-media.redmonk.com/sogrady/files/2013/07/progr...)

Python went everywhere Perl did and then expanded the map for "scripting languages". This didn't happen by accident: Python is, by design, very easy comprehend and learn. The Python community also one of the most newbie-friendly around, with mountains of freely available resources for beginners.

A programming language cannot be sustained by uber hackers, PLT nerds, and hipsters alone. You gotta make it reach the world (Like JavaScript, Java) or it'll never be"Tier 1" programming language. I have yet to see the Go's developer or community put forth a strategy to make this happen -- which is completely understandable given how new the language is.



The scientific Python community will never leave 2.5 -> 2.7, though...


The science community will get there. The problem is that for a long time, NumPy/SciPy/etc. didn't support 3.x. And when you're more interested in end results, why would you rewrite your code (or spend days/weeks/months relearning) when you could use a still perfectly acceptable and supported version?

There's also a lot of reuse and expansion on existing code bases, which would involve a lot of work to migrate to 3.x. There's also the matter that on top of moving to 3.x, you also have the task of making sure there's no hidden bugs that may alter your results in ways you may not notice. A lot of scientific code has been repeatedly vetted to make sure that there's no bias or glitches that may skew your results.

Hell, I know astronomers who are still using Fortran code that was written in the 80's. It still works (though now it requires a long build process, as it is no longer compatible with the latest Fortran compilers), so no reason to try to rewrite it just because the language is dated.


> The science community will get there. The problem is that for a long time, NumPy/SciPy/etc. didn't support 3.x.

They were some of the earliest ported widely-used packages. Numpy was ported in 2010, scipy very early in 2011 (except for weave iirc)


Half the core scientific packages are already P3-compatible. Numpy has supported P3 since 2010[0] and scipy since early 2011[0][1]

[0] http://sourceforge.net/projects/numpy/files//NumPy/1.5.0/NOT... https://pypi.python.org/pypi/numpy/1.5.0

[1] http://docs.scipy.org/doc/scipy-0.9.0/reference/release.0.9....


Im just going by the (very limited sample) people ive talked to.


Yeah that's true. Getting everyone to 3 is going to be quite a slog. I have a feeling once Python 3 becomes the default Python installation for OSX and Linux systems you'll see a big uptick in adoption (and probably some abandonment as well).


NLP will definitely be on Python3 sooner rather than later. unicode strings is a really killer feature for us.


I'm hearing more rumblings about using 3.x now. Certainly people in this community aren't racing to switch, but I wouldn't say it will never happen.




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