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Comment by simonw | Hacker News Reader

If I'm fluent with virtualenv and already use it for all of my Mac OS X Python development, is there a reason I should still consider trying Anaconda?

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It ships with intel MKL optimizations for e.g numpy/sciy. That’s a lot of hassle to get working in a virtualenv, not to mention maintaining several!

MKL is also multicore parallelized out of the box.

Isn't that working on the Mac ootb as well? If I install numpy it links it against https://developer.apple.com/documentation/accelerate which is very close to MKL/OpenBLAS performance.

There are also tons of other libs that apple don’t have equivalents for. E.g GDAL, libgfortran, and lots of others.

Not sure if Accelerate is multicore ootb?

Yeah, it allows working with multiple Python versions fine, like not just 2 vs 3 like on modern Linuxes, but also having one virtualnenv use 2.4, another 2.7, another 3.6 etc.

Couple this with good support for Windows too, and it's basically the only usable cross platform Python version manager... kind of sad all this functionality is not baked into core CPython's package, it would make language adoption 10x easier since "multiple python madness" is what trips newbies, especially if they use Windows or a Linux they don't administer themselves...

Also nicely optimized precompiled stuff, again, for the benefit of new Windows users, for which anything that needs compiling anything has a 50% change of breaking.

If you use data science libraries like numpy, pandas etc then these rely on OS level packages like libgfortran and liblapack. Anaconda is a way to guarantee you are running a known stack from dev machine through to production. This is the key benefit IMO (as well as getting improving deploy times)

All these packages provide wheels on OS X, there is no need to install gfortran these days.

A good point about a known stack.

Many people who do data science on OS X have to deploy or scale their things on Linux servers. Or serve Python scripts to collaborators on Windows.

Even if you are a working on an island and you fully control your own dev and production environments, there are myriad subtle divergences between the build toolchain on Linux and BSD/Darwin that can trip you up.

I don't know if you use some of Enthought's tools like MayaVi and such, but those used to be a pain to install under MacOs. I haven't tried lately though without Anaconda (it's just incredibly convenient).

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