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#rev 2020-09-10 bonaccos <<TableOfContents()>> |
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We provide as many modules as possible that come with the current Debian GNU/Linux stable release. Nevertheless, that might not be enough for your needs since you may want to use the newest version of some module or one that is not part of Debian. | We provide some packages that come with the current Debian GNU/Linux stable release, but usually this is because they are dependencies of an installed software. For python we strongly recommend to build own python environments with the desired python versions and packages. |
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Since Python 2.6 there is an easy way to install missing or outdated modules in your home through `easy_install`. | Our recommended way to install such environments is trough `conda`, especially if you want to build a tool or toolchain where the setup will possibly be published in a paper. Alternatively, building an environment via `pyenv` is possible. |
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== How to use easy_install == | For just quickly trying out some python tool a local installation of `pip` is recommended. |
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|| Command line help: || `easy_install --help` || || Online documentation: || http://packages.python.org/distribute/easy_install.html || || Install a new module: || `easy_install --user MODULENAME` || || Update an existing module: || `easy_install --user -U MODULENAME` || |
== Installing your own python environment with Conda == |
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Modules will be installed in your home within `~/.local/`. You do not need to adapt the `PYTHONPATH` environment variable since python will look for modules in this directory automatically. | For a detailed overview of `conda` please follow the [[Programming/Languages/Conda|Conda documentation]]. |
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== Installing other versions of Python == | == Installing your own python versions with pyenv == |
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You can of course install other versions of Python in your home. A very comfortable way of doing that is by using [[https://github.com/utahta/pythonbrew|pythonbrew]]. You will find a howto on that website with detailled instructions how to use it. | `pyenv` is a collection of tools that allow users to manage different versions of python. The simplest case is to install python in your user space. Using this custom python installation, you will be able to install additional packages in a comfortable way, since you can install them in the "system path" (which is then somewhere within your home). |
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== Installation of custom (non easy_install-able) Python modules in the home directory of a user == | The documentation on `pyenv` can be found on its Github page at [[https://github.com/pyenv/pyenv|github.com/pyenv/pyenv]]. |
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We are sometimes asked for newer version of Python modules. We do no longer build Python modules in SEPP as the requests for modules and their versions is too widespread to keep these modules maintainable. | Here is a small howto for installing python 3.9.1 in your home: |
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On this page we will list some bash-snippets that install some often requested modules in a users home. | * Install pyenv: {{{#!highlight bash numbers=disable curl https://raw.githubusercontent.com/pyenv/pyenv-installer/master/bin/pyenv-installer -o pyenv-installer }}} Check what the script is doing and then execute it: {{{#!highlight bash numbers=disable bash ./pyenv-installer }}} You can remove the installer file afterwards. * Add the following lines to your `~/.profile` before sourcing `~/.bashrc`: {{{#!highlight bash numbers=disable export PYENV_ROOT="$HOME/.pyenv" export PATH="$PYENV_ROOT/bin:$PATH" eval "$(pyenv init --path)" }}} * In the `~/.bashrc`: {{{#!highlight bash numbers=disable eval "$(pyenv init -)" }}} * If you want to pyenv-virtualenv automatically (in the `~/.bashrc`): {{{#!highlight bash numbers=disable eval "$(pyenv virtualenv-init -)" }}} |
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== numpy == | * You need a new login shell for all settings to take effect (when logged in on a Desktop environment logoff and login again) |
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{{{#!highlight bash | * Install some python version, e.g. for python 3.9.1: {{{#!highlight bash numbers=disable env PYTHON_CONFIGURE_OPTS="--enable-shared" pyenv install 3.9.1 pyenv rehash}}} Note, that settting of `PYTHON_CONFIGURE_OPTS="--enable-shared"` is needed if you need to link against the libpython shared library. * Make sure that this new python version will be used when you run python. You only need to run this command once: {{{#!highlight bash numbers=disable pyenv global 3.9.1}}} * In order to update `pyenv` run: {{{#!highlight bash numbers=disable pyenv update}}} === Documentation of pyenv === || Website of pyenv || https://github.com/pyenv/pyenv || || Website of pyenv installer || https://github.com/pyenv/pyenv-installer || == Installation of a local pip == `pip` can be installed in a user's environment and work with the `python` version installed on the system. Every package will be installed for the user only in one location, there is no separation with virtual environments.<<BR>> The following commands set up a local `pip` in a location of your choice. As example `/scratch/$USER/local` is used. You may use a location of your choice, preferrably outside your $HOME as not to impact your quota. {{{#!highlight bash numbers=disable export PYTHONUSERBASE=/scratch/$USER/local mkdir -p $PYTHONUSERBASE/bin export PIP_USER=true export PATH=$PYTHONUSERBASE/bin:$PATH wget https://bootstrap.pypa.io/get-pip.py -O ~/.local/bin/get-pip.py python3 ~/.local/bin/get-pip.py -vvv --user }}} Set default installations to the user's environment permanently (stored in `~/.config/pip/pip.conf`): {{{#!highlight bash numbers=disable pip config set install.user true }}} The exported environment variables will be lost after closing the shell. To enable local pip on demand, add the following function to your `.bashrc`: {{{#!highlight bash numbers=disable function localpip { PYTHONUSERBASE=/scratch/$USER/local PATH=$PYTHONUSERBASE/bin:$PATH export PYTHONUSERBASE PATH } }}} When you open a new shell, entering the command `localpip` will call the function and initialize your local pip installation. === pip cache === `pip` uses a cache which is by default stored under `~/.cache/pip` or `$XDG_CACHE_HOME/pip` if it is set to a non-default location. This cache tends to fill up quickly and should occasionally be cleared with {{{#!highlight bash numbers=disable pip cache purge }}} It is advisable to set the cache's location to the local scratch disk to avoid using up quota: 1. Create a directory for the cache: {{{#!highlight bash numbers=disable mkdir -p /scratch/$USER/pip_cache }}} 1. Temporarily set the environment variable to tell `pip` to use a different cache location: {{{#!highlight bash numbers=disable export PIP_CACHE_DIR=/scratch/$USER/pip_cache/ }}} or store the location permanently (in `~/.config/pip/pip.conf`): {{{#!highlight bash numbers=disable pip config set global.cache-dir /scratch/$USER/pip_cache }}} 1. Check if the cache location is correct: {{{#!highlight bash numbers=disable pip cache info }}} === Installation of additional or newer packages with pip === Once you installed your custom python with the explanations given above, you are ready to install additional or newer packages the easy way. The usage of `pip` is very easy. The following command installs the package `numpy`. {{{#!highlight bash numbers=disable pip install numpy }}} while the next command would upgrade an existing installation of `numpy` {{{#!highlight bash numbers=disable pip install --upgrade numpy }}} === pip package management === Show installed packages: {{{#!highlight bash numbers=disable pip list --user }}} Show installed packages with their dependencies: {{{#!highlight bash numbers=disable pip freeze user | cut -d '=' -f 1 | xargs -r pip show | grep -E '^(Name|Required-by):' }}} Show outdated packages {{{#!highlight bash numbers=disable pip list --user --outdated }}} Update all outdated packages: {{{#!highlight bash numbers=disable pip list --user --outdated | awk '{if ($2 ~ /[0-9\.]+/) print $1}' | xargs -r pip install --user --upgrade }}} For advanced usage of `pip`, please consult the [[https://pip.pypa.io/en/stable/user_guide/|official user guide]]. == Installation of Python packages that are not available in the archives of pip == Here we provide some shell script snippets for installing frequently asked packages which cannot be installed through `pip`. These scripts just provide an example installation. You might have to adapt some paths in order to make the package work correctly with the version of python you are using (e.g. if you run your custom python provided through `pyenv`). === nlopt === {{{#!highlight bash numbers=disable |
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VERSION_NUMPY=1.6.0 installdir="${HOME}/opt" builddir="/scratch/${USER}/build/numpy" |
# Installation script for nlopt library |
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export PYTHONPATH=${installdir}/lib/python | VERSION=2.3 INSTALLDIR=$HOME/.local BUILDDIR=/scratch/$USER/nlopt |
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mkdir -p ${builddir} | mkdir -p $BUILDDIR cd $BUILDDIR |
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cd ${builddir} wget --output-document=numpy-${VERSION_NUMPY}.tar.gz \ http://sourceforge.net/projects/numpy/files/NumPy/${VERSION_NUMPY}/numpy-${VERSION_NUMPY}.tar.gz/download tar -xvvzkf numpy-${VERSION_NUMPY}.tar.gz cd numpy-${VERSION_NUMPY} python setup.py build --fcompiler=gnu95 python setup.py install --home=${installdir} }}} |
wget "http://ab-initio.mit.edu/nlopt/nlopt-${VERSION}.tar.gz" tar -xvvzkf nlopt-${VERSION}.tar.gz cd nlopt-${VERSION} |
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== scipy == | ./configure \ --enable-shared \ --prefix=$INSTALLDIR \ OCT_INSTALL_DIR=$INSTALLDIR/octave/oct \ M_INSTALL_DIR=$INSTALLDIR/octave/m/ \ MEX_INSTALL_DIR=$INSTALLDIR/mex \ GUILE_INSTALL_DIR=$INSTALLDIR/guile |
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* First you need to install scipy as shown above and make sure PYTHONPATH points to the new numpy installation. {{{ #!/bin/bash VERSION_SCIPY=1.6.0 installdir="${HOME}/opt" builddir="/scratch/${USER}/build/scipy" export PYTHONPATH=${installdir}/lib/python mkdir -p ${builddir} cd ${builddir} wget --output-document=scipy-${VERSION_SCIPY}.tar.gz \ http://sourceforge.net/projects/scipy/files/scipy/${VERSION_SCIPY}/scipy-${VERSION_SCIPY}.tar.gz/download tar -xvvzkf scipy-${VERSION_SCIPY}.tar.gz cd scipy-${VERSION_SCIPY} python setup.py build python setup.py install --home=${installdir} }}} == matplotlib == * First you need to install scipy as shown above and make sure PYTHONPATH points to the new numpy installation. {{{ #!/bin/bash VERSION_MATPLOTLIB=1.0.1 installdir="${HOME}/opt" builddir="/scratch/${USER}/build/matplotlib" export PYTHONPATH=${installdir}/lib/python mkdir -p ${builddir} cd ${builddir} wget --output-document=matplotlib-${VERSION_MATPLOTLIB}.tar.gz \ http://sourceforge.net/projects/matplotlib/files/matplotlib/matplotlib-${VERSION_MATPLOTLIB}/matplotlib-${VERSION_MATPLOTLIB}.tar.gz/download tar -xvvzkf matplotlib-${VERSION_MATPLOTLIB}.tar.gz cd matplotlib-${VERSION_MATPLOTLIB} python setup.py build python setup.py install --home=${installdir} }}} == nose == * This module is required to run e.g. the numpy and scipy test suites. {{{ #!/bin/bash VERSION_NOSE=1.0.0 installdir="${HOME}/opt" builddir="/scratch/${USER}/build/nose" export PYTHONPATH=${installdir}/lib/python mkdir -p ${builddir} cd ${builddir} wget http://somethingaboutorange.com/mrl/projects/nose/nose-${VERSION_NOSE}.tar.gz tar -xvvzkf nose-${VERSION_NOSE}.tar.gz cd nose-${VERSION_NOSE} python setup.py build python setup.py install --home=${installdir} |
make make install |
Contents
Python
We provide some packages that come with the current Debian GNU/Linux stable release, but usually this is because they are dependencies of an installed software. For python we strongly recommend to build own python environments with the desired python versions and packages.
Our recommended way to install such environments is trough conda, especially if you want to build a tool or toolchain where the setup will possibly be published in a paper. Alternatively, building an environment via pyenv is possible.
For just quickly trying out some python tool a local installation of pip is recommended.
Installing your own python environment with Conda
For a detailed overview of conda please follow the Conda documentation.
Installing your own python versions with pyenv
pyenv is a collection of tools that allow users to manage different versions of python. The simplest case is to install python in your user space. Using this custom python installation, you will be able to install additional packages in a comfortable way, since you can install them in the "system path" (which is then somewhere within your home).
The documentation on pyenv can be found on its Github page at github.com/pyenv/pyenv.
Here is a small howto for installing python 3.9.1 in your home:
Install pyenv:
curl https://raw.githubusercontent.com/pyenv/pyenv-installer/master/bin/pyenv-installer -o pyenv-installer
Check what the script is doing and then execute it:
You can remove the installer file afterwards.bash ./pyenv-installer
Add the following lines to your ~/.profile before sourcing ~/.bashrc:
export PYENV_ROOT="$HOME/.pyenv" export PATH="$PYENV_ROOT/bin:$PATH" eval "$(pyenv init --path)"
In the ~/.bashrc:
eval "$(pyenv init -)"
If you want to pyenv-virtualenv automatically (in the ~/.bashrc):
eval "$(pyenv virtualenv-init -)"
- You need a new login shell for all settings to take effect (when logged in on a Desktop environment logoff and login again)
Install some python version, e.g. for python 3.9.1:
env PYTHON_CONFIGURE_OPTS="--enable-shared" pyenv install 3.9.1 pyenv rehash
Note, that settting of PYTHON_CONFIGURE_OPTS="--enable-shared" is needed if you need to link against the libpython shared library.
Make sure that this new python version will be used when you run python. You only need to run this command once:
pyenv global 3.9.1
In order to update pyenv run:
pyenv update
Documentation of pyenv
Website of pyenv
Website of pyenv installer
Installation of a local pip
pip can be installed in a user's environment and work with the python version installed on the system. Every package will be installed for the user only in one location, there is no separation with virtual environments.
The following commands set up a local pip in a location of your choice. As example /scratch/$USER/local is used. You may use a location of your choice, preferrably outside your $HOME as not to impact your quota.
export PYTHONUSERBASE=/scratch/$USER/local
mkdir -p $PYTHONUSERBASE/bin
export PIP_USER=true
export PATH=$PYTHONUSERBASE/bin:$PATH
wget https://bootstrap.pypa.io/get-pip.py -O ~/.local/bin/get-pip.py
python3 ~/.local/bin/get-pip.py -vvv --user
Set default installations to the user's environment permanently (stored in ~/.config/pip/pip.conf):
pip config set install.user true
The exported environment variables will be lost after closing the shell. To enable local pip on demand, add the following function to your .bashrc:
function localpip {
PYTHONUSERBASE=/scratch/$USER/local
PATH=$PYTHONUSERBASE/bin:$PATH
export PYTHONUSERBASE PATH
}
When you open a new shell, entering the command localpip will call the function and initialize your local pip installation.
pip cache
pip uses a cache which is by default stored under ~/.cache/pip or $XDG_CACHE_HOME/pip if it is set to a non-default location. This cache tends to fill up quickly and should occasionally be cleared with
pip cache purge
It is advisable to set the cache's location to the local scratch disk to avoid using up quota:
Create a directory for the cache:
mkdir -p /scratch/$USER/pip_cache
Temporarily set the environment variable to tell pip to use a different cache location:
export PIP_CACHE_DIR=/scratch/$USER/pip_cache/
or store the location permanently (in ~/.config/pip/pip.conf):
pip config set global.cache-dir /scratch/$USER/pip_cache
Check if the cache location is correct:
pip cache info
Installation of additional or newer packages with pip
Once you installed your custom python with the explanations given above, you are ready to install additional or newer packages the easy way. The usage of pip is very easy. The following command installs the package numpy.
pip install numpy
while the next command would upgrade an existing installation of numpy
pip install --upgrade numpy
pip package management
Show installed packages:
pip list --user
Show installed packages with their dependencies:
pip freeze user | cut -d '=' -f 1 | xargs -r pip show | grep -E '^(Name|Required-by):'
Show outdated packages
pip list --user --outdated
Update all outdated packages:
pip list --user --outdated |
awk '{if ($2 ~ /[0-9\.]+/) print $1}' |
xargs -r pip install --user --upgrade
For advanced usage of pip, please consult the official user guide.
Installation of Python packages that are not available in the archives of pip
Here we provide some shell script snippets for installing frequently asked packages which cannot be installed through pip. These scripts just provide an example installation. You might have to adapt some paths in order to make the package work correctly with the version of python you are using (e.g. if you run your custom python provided through pyenv).
nlopt
#!/bin/bash
# Installation script for nlopt library
VERSION=2.3
INSTALLDIR=$HOME/.local
BUILDDIR=/scratch/$USER/nlopt
mkdir -p $BUILDDIR
cd $BUILDDIR
wget "http://ab-initio.mit.edu/nlopt/nlopt-${VERSION}.tar.gz"
tar -xvvzkf nlopt-${VERSION}.tar.gz
cd nlopt-${VERSION}
./configure \
--enable-shared \
--prefix=$INSTALLDIR \
OCT_INSTALL_DIR=$INSTALLDIR/octave/oct \
M_INSTALL_DIR=$INSTALLDIR/octave/m/ \
MEX_INSTALL_DIR=$INSTALLDIR/mex \
GUILE_INSTALL_DIR=$INSTALLDIR/guile
make
make install