A colleague of mine is trying to update our production environment
with the latest releases of numpy, scipy, mpl and ipython, and is
worried about the lag time when there is a new numpy and old scipy,
etc... as the build progresses. This is the scheme he is considering,
which looks fine to me, but I thought I would bounce it off the list
here in case anyone has confronted or thought about this problem
before.
Alternatively, an install to a tmp dir and then a bulk cp -r should work, no?
JDH
> We're planning to be putting out a bugfix
> matplotlib point release to 0.90.1 -- can you hold off on the mpl
> install for a day or so?
Sure. While I have your attention, do you think this install scheme
would work? It's the body of an email I just sent to c.l.py.
----------------------------------------------------------------------------
At work I need to upgrade numpy, scipy, ipython and matplotlib. They need
to be done all at once. All have distutils setups but the new versions and
the old versions are incompatible with one another as a group because
numpy's apis changed. Ideally, I could just do something like
cd ~/src
cd numpy
python setup.py install
cd ../scipy
python setup.py install
cd ../matplotlib
python setup.py install
cd ../ipython
python setup.py install
however, even if nothing goes awry it leaves me with a fair chunk of time
where the state of the collective system is inconsistent (new numpy, old
everything else). I'm wondering... Can I stage the installs to a different
directory tree like so:
export PYTHONPATH=$HOME/local/lib/python-2.4/site-packages
cd ~/src
cd numpy
python setup.py install --prefix=$PYTHONPATH
cd ../scipy
python setup.py install --prefix=$PYTHONPATH
cd ../matplotlib
python setup.py install --prefix=$PYTHONPATH
cd ../ipython
python setup.py install --prefix=$PYTHONPATH
That would get them all built as a cohesive set. Then I'd repeat the
installs without PYTHONPATH:
unset PYTHONPATH
cd ~/src
cd numpy
python setup.py install
cd ../scipy
python setup.py install
cd ../matplotlib
python setup.py install
cd ../ipython
python setup.py install
Presumably the compilation (the time-consuming part) is all
location-independent, so the second time the build_ext part should be fast.
Can anyone comment on the feasibility of this approach? I guess what I'm
wondering is what dependencies there are on the installation directory.
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