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Interesting list. I love Anaconda! A few years ago I tried to set up a Mac with a scientific computing stack and it took me days to hack my way through all the various dependencies and incompatible versions. Anaconda now lets me do that in a minutes.
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Me too...I taught a python class by making everyone download Anaconda's distribution of 3.x...and everyone could do the assignments no matter what kind of computer they used. Anaconda does a little too much for me to have it be my own default install but it does quite well in on boarding beginners. I use pyenv to install maintain Anaconda on my own machine when I need to replicate student work
What does it do that ends up being a little too much for your use?
I don't know if that's the case (curl being part of the package) now, with Anaconda 3 2.4.0+? It certainly isn't so when installed via pyenv, so I'm happy with that. But there were other issues in the past build...BeautifulSoup was inexplicably broken. I mean that it simply did not correctly parse non-trivial HTML pages and yet threw no errors. The results could be replicated for all of my students but I never could isolate the issue... I installed Python 3 and the same version of BS4 from scratch and had no problems, but I can't imagine where the Anaconda build would have gotten wrong. It ended up being OK since I just switched to lxml which I now happily use over BS4 on any day, but it was frustrating to not be able to diagnose the problem (I didn't get a response in the support forums either). I'm assuming this problem has gone away in subsequent versions of Anaconda though I haven't tried since lxml is perfectly fine to me.
And finally...well, I have to admit it, but I use Python like a goddamned moron in that I still don't know how to use virutalenv/venv to do proper dev isolation. And from the brief research I did, I see that Anaconda has its own conventions, or work flow...something with the conda utility. Again, I can see why it's necessary for Anaconda's use case (people who want to do data science and not hand-tweak their environment every time they upgrade a package over pip), but it added too many layers for me at the time.
[1] https://groups.google.com/a/continuum.io/forum/#!topic/anaco...
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Could you name it?
This is probably what he meant: $ py Python 2.7.8 |Anaconda 2.1.0 (64-bit) ... on win32 >>> import bsddb >>> print bsddb.__doc__ Support for Berkeley DB 4.3 through 5.3 with a simple interface. For the full featured object oriented interface use the bsddb.db module instead. It mirrors the Oracle Berkeley DB C API.
The Python module I learned to love this year is Click. Gets me better command line interfaces fast. URL is http://click.pocoo.org . It does progress bars too...
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Could you name it?
This is probably what he meant: $ py Python 2.7.8 |Anaconda 2.1.0 (64-bit) ... on win32 >>> import bsddb >>> print bsddb.__doc__ Support for Berkeley DB 4.3 through 5.3 with a simple interface. For the full featured object oriented interface use the bsddb.db module instead. It mirrors the Oracle Berkeley DB C API.