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Comment by sandGorgon | Hacker News Reader

the biggest concern I have heard from friends who work in stats and mathematics academia is that it is much, MUCH easier to publish a package in CRAN than to PyPi.

I think most users of Python are that... "users". But R is used by creators of algorithms who find it very easy to create and distribute code.

In fact a lot of them talk about how difficult it is to install packages in python, while any R script has "install.packages" right in it.

I'm willing to bet if Pandas/Numpy/Jupyter built a CRAN-PY and made the packaging system similar to R, the adoption would be much different.

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I do agree that stats people love R. This is one of the reasons I wrote this article. So that I can leverage all the good work they've gone. It is way better to write a wrapper than to reimplement everything from scratch. I'm coming from academia where I have a lot of systems work. So, I tend to be Python first user. But, I do want to utilise all the packages that are exclusively available in R.

Packaging is improving in Python afaik. People like Anaconda!

its not packaging per se - conda and gem are brilliant, but its intended for software creators and not math acads. install.package may not be a brilliant piece of software, but its perfect for people who develop stats algorithms and just publish to cran.

This is the package submission page to CRAN - https://cran.r-project.org/submit.html

This is the equivalent for Pypi - https://pypi.python.org/pypi?%3Aaction=submit_form

Submitting a package is the least important part of distributing it. For CRAN you can use the submit form you link to, for Python it's `python setup.py sdist upload` and you're done. CRAN in fact has much stricter standards for packages than Python -- you need a vignette, you need tests etc. -- which is why new R packages are usually on GitHub long before they make it to CRAN, whereas PyPI is happy to accept alpha and beta releases without documentation and without tests.

thats actually interesting to know - it would be illuminating to find out what really is the mental roadblock there, because this is something I have heard from multiple acads.

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