Often you will get the opportunity to run your code on a cluster, or even simply a guest computer, where you don't have root access (sudo does not work). The great thing about Python is that Python and any modules can be completely installed in user space (in your account) without disturbing any one else. In the computer I am accessing (Partners' HPC setup) they are hip and have all versions of Python. In case your setup doesn't you first want to do:
cd /tmp #(We have write access here) curl -O http://www.python.org/ftp/python/2.7.5/Python-2.7.5.tar.bz2 #Or whatever the version you want tar -xzf Python-2.7.5.tar.bz2 cd Python-2.7.5 ./configure --prefix=$HOME/local/Python #Or where ever you want it make make installMake sure this directory is in your path such that you can call python.
#Add this path to .bash_profile PATH=$HOME/local/Python/bin:$PATHPython has a very neat, principled, way of storing its infrastructure (modules) that is detailed here. A quick way to figure out where this is is to do
python -m site --user-siteWe need to add this to our path too. In my case is was ~/.local/bin
#Add this path to .bash_profile PATH=$PATH:$HOME/.local/binNext you will want pip, which is a more modern package manager than easy_install, but first you'll want setup tools:
wget https://bitbucket.org/pypa/setuptools/raw/bootstrap/ez_setup.py -O - | python
cd /tmp #(We have write access here) curl -O https://pypi.python.org/packages/source/p/pip/pip-1.3.tar.gz tar -xzf pip-1.3.tar.gz cd pip-1.3/ python setup.py install --userPython informs us pip is now installed under
~/.local/bin/. The magic from now on is to simply add --user to our pip install commands to install packages in our userspace. Let's try this out:
pip install matplotlib --user pip install ipython --user pip install --upgrade nose --user #(The server had an older version of nose)And we have our environment. The HPC cluster I went into already had numpy and scipy, but you may need to install those as well.