> On Jan 25, 2016, at 5:21 PM, G Young <gfyoun...@gmail.com> wrote:
>
> With regards to testing numpy, both Conda and Pip + Virtualenv work quite
> well. I have used both to install master and run unit tests, and both pass
> with flying colors. This chart here illustrates my point nicely as well.
>
> However, I can't seem to find / access Conda installations for slightly older
> versions of Python (e.g. Python 3.4). Perhaps this is not much of an issue
> now with the next release (1.12) being written only for Python 2.7 and Python
> 3.4 - 5. However, if we were to wind the clock slightly back to when we were
> testing 2.6 - 7, 3.2 - 5, I feel Conda falls short in being able to test on a
> variety of Python distributions given the nature of Conda releases. Maybe
> that situation is no longer the case now, but in the long term, it could
> easily happen again.
Why do you need the installers? The whole point of conda is to be able to
create environments with whatever configuration you need. Just pick the newest
installer and use "conda create" from there:
bryan@0199-bryanv (git:streaming) ~/work/bokeh/bokeh $ conda create -n py26
python=2.6
Fetching package metadata: ..............
Solving package specifications: ..........
Package plan for installation in environment /Users/bryan/anaconda/envs/py26:
The following packages will be downloaded:
package | build
---------------------------|-----------------
setuptools-18.0.1 | py26_0 343 KB
pip-7.1.0 | py26_0 1.4 MB
------------------------------------------------------------
Total: 1.7 MB
The following NEW packages will be INSTALLED:
openssl: 1.0.1k-1
pip: 7.1.0-py26_0
python: 2.6.9-1
readline: 6.2-2
setuptools: 18.0.1-py26_0
sqlite: 3.9.2-0
tk: 8.5.18-0
zlib: 1.2.8-0
Proceed ([y]/n)?
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