<div dir="ltr"><div>I'm sorry if this is out-of-topic, but I'm curious on why nobody mentioned Conda yet.</div><div><br></div>Is there any particular reason for not using it?</div><div class="gmail_extra"><br><div class="gmail_quote">On Tue, Oct 27, 2015 at 11:48 AM, James E.H. Turner <span dir="ltr"><<a href="mailto:jehturner@gmail.com" target="_blank">jehturner@gmail.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><span class=""><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">
Apparently it is not well known that if you have a Python project<br>
source tree (e.g., a numpy checkout), then the correct way to install<br>
it is NOT to type<br>
<br>
python setup.py install # bad and broken!<br>
<br>
but rather to type<br>
<br>
pip install .<br>
</blockquote>
<br></span>
Though I haven't studied it exhaustively, it always seems to me that<br>
pip is bad & broken, whereas python setup.py install does what I<br>
expect (even if it's a mess internally). In particular, when<br>
maintaining a distribution of Python packages, you try to have some<br>
well-defined, reproducible build from source tarballs and then you<br>
find that pip is going off and downloading stuff under the radar<br>
without being asked (etc.). Stopping that can be a pain & I always<br>
groan whenever some package insists on using pip. Maybe I don't<br>
understand it well enough but in this role its dependency handling<br>
is an unnecessary complication with no purpose. Just a comment that<br>
not every installation is someone trying to get numpy on their<br>
laptop...<br>
<br>
Cheers,<br>
<br>
James.<div class="HOEnZb"><div class="h5"><br>
<br>
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</div></div></blockquote></div><br></div>