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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. Furthermore you might want to use a different version of 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. |
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The recommended way to install additional python modules is through {{{pip}}}. Unfortunately, {{{pip}}} does not allow users to install modules in the user context. That means that you will first have to install your own version of python in your home. From that moment on, you can install modules through {{{pip}}}. | 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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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 [[Programming/Languages/Conda|Conda documentation]]. |
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{{{Pyenv}}} is a collection of tools that allow users to manage different versions of python. In the simplest case you will need it to simply get an installation of python in your user space. Using that custom python installation, you will then be able to install additional modules in a very comfortable way, since you can install them in the "system path" (which is then somewhere within your home). | `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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Here is a small howto for installing python 2.7.9 in your home: | 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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* Install pyenv: {{{ curl -L https://raw.githubusercontent.com/yyuu/pyenv-installer/master/bin/pyenv-installer | bash}}} |
Here is a small howto for installing python 3.9.1 in your home: |
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* Add the following three lines to your ~/.bashrc: {{{ export PATH="$HOME/.pyenv/bin:$PATH" eval "$(pyenv init -)" eval "$(pyenv virtualenv-init -)"}}} |
* 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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* Restart your shell so the path changes take effect: {{{ exec $SHELL}}} |
* 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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* Install some python version, e.g. for python 2.7.9: {{{ pyenv install 2.7.9 |
* 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 |
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Note, that settting of `PYTHON_CONFIGURE_OPTS="--enable-shared"` is needed if you need to link against the libpython shared library. | |
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* Make sure that this new python version will be used when you run python. You only need to run this command once: {{{ pyenv global 2.7.9}}} |
* 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}}} |
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* In order to update {{{pyenv}}} run: {{{ |
* In order to update `pyenv` run: {{{#!highlight bash numbers=disable |
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|| Website of pyenv || https://github.com/yyuu/pyenv/ || || Website of pyenv installer || https://github.com/yyuu/pyenv-installer || |
|| Website of pyenv || https://github.com/pyenv/pyenv || || Website of pyenv installer || https://github.com/pyenv/pyenv-installer || |
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== 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>> |
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== Installation of additional or newer modules with pip == | 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 $HOME as not to impact your quota. |
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Once you installed your custom python with the explanations given above, you are ready to install additional or newer modules the easy way. The usage of {{{pip}}} is very easy. The following command installs the module {{{numpy}}} {{{ pip install numpy}}} while the next command would upgrade an existing installation of {{{numpy}}} {{{ pip install --upgrade numpy}}} |
{{{#!highlight bash numbers=disable export PYTHONUSERBASE=/scratch/$USER/local mkdir -p $PYTHONUSERBASE/bin export PIP_USER=true export PATH=$PYTHONUSERBASE/bin:$PATH wget https://bootstrap.pypa.io/get-pip.py -O ~/.local/bin/get-pip.py python3 ~/.local/bin/get-pip.py -vvv --user }}} Set default installations to the user's environment permanently (stored in `~/.config/pip/pip.conf`): {{{#!highlight bash numbers=disable pip config set install.user true }}} |
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For advanced usage of {{{pip}}}, please consult the manuals: http://pip.readthedocs.org/en/latest/ | The exported environment variables will be lost after closing the shell. To enable local pip on demand, add the following function to your `.bashrc`: {{{#!highlight bash numbers=disable function localpip { PYTHONUSERBASE=/scratch/$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. |
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=== pip cache === `pip` uses a cache which is by default stored under `~/.cache/pip` or `$XDG_CACHE_HOME/pip` if it is set to a non-default location. This cache tends to fill up quickly and should occasionally be cleared with {{{#!highlight bash numbers=disable pip cache purge }}} It is advisable to set the cache's location to the local scratch disk to avoid using up quota: |
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== Installation of Python modules that are not available in the archives of pip == | 1. Create a directory for the cache: {{{#!highlight bash numbers=disable mkdir -p /scratch/$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 }}} |
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Here we provide some shell script snippets for installing frequently asked modules 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 module work correctly with the version of python you are using (e.g. if you run your custom python provided through {{{pyenv}}}). | === 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`). |
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{{{#!highlight bash | {{{#!highlight bash numbers=disable |
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