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# Check if this script is started on an Euler login node, if it is, suggest a custom install location and exit if [[ -z ${HOSTNAME} ]]; then host_name=$(hostname -s) else host_name=${HOSTNAME} fi if [[ -n ${host_name} ]]; then if [[ ${host_name%-*} == 'eu-login' ]]; then echo "It seems you're using this script on the Euler cluster." echo 'Provide a custom location for installation, for example in your Euler home:' echo "${BASH_SOURCE[0]} ${HOME}/conda" exit 1 fi fi |
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`conda` allows to seperate installed software packages from each other by creating so-called ''environments''. Using environments is best practice to generate deterministic and reproducible tools. | `conda` allows to seperate installed software packages from each other by creating so-called ''[[#Environments|environments]]''. Using environments is best practice to generate deterministic and reproducible tools. |
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It is best practice to seperate packages in different environments if they don't need to interact. | It is best practice to seperate packages in different [[#Environments|environments]] if they don't need to interact. |
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conda create --name py37 python=3.7.3 | conda create --name py38 python=3.8.5 |
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conda create --name pytcu10 pytorch torchvision cudatoolkit=10.0 --channel pytorch }}} |
conda create --name pytcu10 pytorch torchvision cudatoolkit=10.1 --channel pytorch }}} * Be sure to read [[Programming/Languages/GPUCPU#Installing_a_specific_toolkit_version_with_conda|Installing a specific toolkit version]] if you intend to use this example for more than just first steps with conda. |
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conda create --name tencu10 tensorflow-gpu cudatoolkit=10.0 }}} |
conda create --name tencu10 tensorflow-gpu cudatoolkit=10.1 }}} * Be sure to read [[Programming/Languages/GPUCPU#Installing_a_specific_toolkit_version_with_conda|Installing a specific toolkit version]] if you intend to use this example for more than just first steps with conda. |
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`conda` automatically installs a default environment called ''base'' with a `python` interpreter, [[https://pypi.org/project/pip/|pip]] and other tools to start coding in python. Whether you want to use and extend this environment or create your own is up to you. At the time of writing this information it is not possible to remove the base environment. | `conda` automatically installs a default environment called ''base'' with a `python` interpreter, [[https://pypi.org/project/pip/|pip]] and other tools to start coding in python. * /!\ It is strongly discouraged to use the ''base'' environment for projects. It's purpose is to provide the tools to maintain other environments, nothing else. * /!\ Set up a new environment for each project. This ensures reproducability and facilitates environment related problem solving. * /!\ Only auto activate an environment in your shell initialisation script if you understand exactly what this entails. * It's good practice to make sure [[#Check_for_conda_initialization_and_active_environment|conda is initialized and the wanted environment is active]] before trying to use it |
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==== Check for conda initialization and active environment ==== To make sure conda is initialized and an environment is active the following script can be started: {{{#!highlight bash numbers=disable #!/bin/bash if [[ -z ${CONDA_EXE} ]]; then echo 'Environment variable CONDA_EXE is not set.' echo 'Please make sure conda is properly initialized.' exit 1 else if [[ ! -x ${CONDA_EXE} ]]; then echo "${CONDA_EXE} is not executable." echo "Please make sure it exists and is executable." exit 2 else if [[ -z ${CONDA_DEFAULT_ENV} ]]; then echo 'Environment variable CONDA_DEFAULT_ENV is not set.' echo 'Please make sure to activate a conda environment.' exit 3 else conda info fi fi fi }}} Save this script as `conda_env_check.sh`, make it executable with {{{ chmod +x ./conda_env_check.sh }}} A use case is to start this script within a [[Services/SLURM#sbatch_-.3E_Submitting_a_job|cluster job]] before using the first command installed in an environment. You can either run the script from your cluster job or place your job commands into the innermost branch after the command `conda info`. |
Contents
-
Setting up a personal python development infrastructure
- Installing conda
- conda storage locations
-
Using conda
- Installation examples
-
Environments
- Create an environment called "my_env" with packages "package1" and "package2" installed
- Activate the environment called "my_env"
- Deactivate the current environment
- List available environments
- Remove the environment called "my_env"
- Create a cloned environment named "cloned_env" from "original_env"
- Export the active environment definition to the file "my_env.yml"
- Recreate a previously exported environment
- Creates the environment "my_env" in the specified location
- Update an active environment
- Packages
- Miscellaneous
- Maintenance
- Backup
Setting up a personal python development infrastructure
This page shows how to set up a personal python development infrastructure, how to use it, how to maintain it and make backups of your project environments.
Some examples for software installation in the field of data sciences are provided.
The infrastructure is driven by the conda packet manager which accesses the Anaconda repositories to install software.
After familiarizing yourself with conda, read this collection of hints and explanations about available platforms on which to use your infrastructure and particularities of the software packages involved.
Installing conda
- Time to install: ~1.5 minutes
- Space required: ~370M
To provide conda, the minimal anaconda distribution miniconda can be installed and configured for the D-ITET infrastructure with the following bash script:
#!/bin/bash
SPACE_MINIMUM_REQUIRED='5'
if [[ -z "${1}" ]]; then
# Default install location
OPTION='netscratch'
else
OPTION="${1}"
fi
line=$(printf '%*s\n' "${COLUMNS:-$(tput cols)}" '' |tr ' ' '-')
# Display underlined title to improve readability of script output
function title()
{
echo
echo "$@"
echo "${line}"
}
case "${OPTION}" in
h|help|'-h'|'--help')
title 'Possible installation options are:'
echo 'Install conda to your local scratch disk:'
echo "${BASH_SOURCE[0]} localscratch"
echo
echo 'Install conda to your directory on net_scratch:'
echo "${BASH_SOURCE[0]}"
echo 'or'
echo "${BASH_SOURCE[0]} netscratch"
echo
echo 'Provide a custom location for installation'
echo "${BASH_SOURCE[0]} /path/to/custom/location"
echo
echo "The recommended minimum space requirement for installation is ${SPACE_MINIMUM_REQUIRED} G."
exit 0
;;
l|local|localscratch|'-l'|'-local'|'-localscratch')
# If local scratch is made available through scratch_net, use its path in
# order to be able to access it on other hosts through scratch_net
if grep -q scratch_net /etc/auto.master; then
CONDA_BASE_DIR="/scratch_net/$(hostname -s)/${USER}"
else
CONDA_BASE_DIR="/scratch/${USER}"
fi
;;
n|net|netscratch|'-n'|'-net'|'-netscratch')
CONDA_BASE_DIR="/itet-stor/${USER}/net_scratch"
;;
*)
CONDA_BASE_DIR="${1}"
;;
esac
# Check if this script is started on an Euler login node, if it is, suggest a custom install location and exit
if [[ -z ${HOSTNAME} ]]; then
host_name=$(hostname -s)
else
host_name=${HOSTNAME}
fi
if [[ -n ${host_name} ]]; then
if [[ ${host_name%-*} == 'eu-login' ]]; then
echo "It seems you're using this script on the Euler cluster."
echo 'Provide a custom location for installation, for example in your Euler home:'
echo "${BASH_SOURCE[0]} ${HOME}/conda"
exit 1
fi
fi
# Create install location if it doesn't exist
if [[ ! -d "${CONDA_BASE_DIR}" ]]; then
mkdir -p "${CONDA_BASE_DIR}"
fi
# Check available space on selected install location
SPACE_AVAILABLE=$(($(stat -f --format="%a*%S" ${CONDA_BASE_DIR})/1024/1024/1024))
if [[ ${SPACE_AVAILABLE} -lt ${SPACE_MINIMUM_REQUIRED} ]]; then
title 'Warning!'
echo "Available space on '${CONDA_BASE_DIR}' is ${SPACE_AVAILABLE} G."
echo "This is less than the minimum recommendation of ${SPACE_MINIMUM_REQUIRED} G."
read -p "Press 'y' if you want to continue installing anwyway: " -n 1 -r
echo
if [[ ! ${REPLY} =~ ^[Yy]$ ]]; then
exit 1
fi
fi
# Locations for conda installation, packet cache and virtual environments
CONDA_INSTALL_DIR="${CONDA_BASE_DIR}/conda"
CONDA_PACKET_CACHE_DIR="${CONDA_BASE_DIR}/conda_pkgs"
CONDA_ENV_DIR="${CONDA_BASE_DIR}/conda_envs"
# Abort if pre-existing installation is found
if [[ -d "${CONDA_INSTALL_DIR}" ]]; then
if [[ -z "$(find "${CONDA_INSTALL_DIR}" -maxdepth 0 -type d -empty 2>/dev/null)" ]]; then
title 'Checking installation path'
echo "The installation path '${CONDA_INSTALL_DIR}' is not empty."
echo 'Aborting installation.'
exit 1
fi
fi
# Installer of choice for conda
CONDA_INSTALLER_URL='https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh'
# Unset pre-existing python paths
if [[ -n ${PYTHONPATH} ]]; then
unset PYTHONPATH
fi
# Downlad latest version of miniconda and install it
title 'Downloading and installing conda'
wget -O miniconda.sh "${CONDA_INSTALLER_URL}" \
&& chmod +x miniconda.sh \
&& ./miniconda.sh -b -p "${CONDA_INSTALL_DIR}" \
&& rm ./miniconda.sh
# Configure conda
title 'Configuring conda'
eval "$(${CONDA_INSTALL_DIR}/bin/conda shell.bash hook)"
conda config --add pkgs_dirs "${CONDA_PACKET_CACHE_DIR}" --system
conda config --add envs_dirs "${CONDA_ENV_DIR}" --system
conda config --set auto_activate_base false
conda deactivate
# Prevent conda from using user site-packages
mkdir -p "${CONDA_INSTALL_DIR}/etc/conda/activate.d"
cat > "${CONDA_INSTALL_DIR}/etc/conda/activate.d/disable-PYTHONUSERBASE.sh" << EOF
#!/bin/bash
export PYTHONUSERBASE=intentionally-disabled
EOF
chmod +x "${CONDA_INSTALL_DIR}/etc/conda/activate.d/disable-PYTHONUSERBASE.sh"
# Update conda and conda base environment
title 'Updating conda and conda base environment'
conda update conda --yes
conda update -n 'base' --update-all --yes
# Clean installation
title 'Removing unused packages and caches'
conda clean --all --yes
# Display information about this conda installation
title 'Information about this conda installation'
conda info
# Show how to initialize conda
title 'Initialize conda immediately'
echo "eval \"\$(${CONDA_INSTALL_DIR}/bin/conda shell.bash hook)\""
title 'Automatically initialize conda for future shell sessions'
echo "echo '[[ -f ${CONDA_INSTALL_DIR}/bin/conda ]] && eval \"\$(${CONDA_INSTALL_DIR}/bin/conda shell.bash hook)\"' >> ${HOME}/.bashrc"
# Show how to remove conda
title 'Completely remove conda'
echo "rm -r ${CONDA_INSTALL_DIR} ${CONDA_INSTALL_DIR}_pkgs ${CONDA_INSTALL_DIR}_envs ${HOME}/.conda"
Save this script as install_conda.sh, make it executable with
chmod +x ./install_conda.sh
and run the script to show options for choosing storage locations by issuing
./install_conda.sh help
Then run the script again with the option of your choosing to start the installation.
When the script ends it prints out information about the installation, commands to initialize conda immediately or every time you log in and a command to completely remove your conda installation.
Choose your preferred method of initializing conda as recommended by the script and note down the deletion command.
conda storage locations
Pre-set install locations
The purpose of the install scripts' options is to store data according to its importance and prevent using up your quota. The difference between the two pre-set installation locations is:
netscratch: fail-safe because it resides on a RAID but slower startup times as it is a network share
localscratch: single point of failure because it is just one disk but faster startup times as it is a local disk
Neither of the pre-set locations has an automatic backup. Use the recommended backup practice instead.
Custom install location
If you intend to use a custom install location, consult the storage overview to choose it adequately and follow these recommendations:
Reproducible, space consuming data like environments and package cache belongs into storage class SCRATCH
Code written by yourself should be backuped regularly. It consumes a small amount of space therefore it's ideal location is in storage class HOME and additionally checked into your git repository.
Data generated over a long time period which would be time consuming to recreate from scratch and is in use regularly should be stored in the storage class PROJECT.
Data generated as a final result which is not needed for ongoing work but needs to be available for later generations should be stored in the storage class ARCHIVE.
conda directories
The installation creates the following two directories in the install location:
conda: Contains the miniconda installation
conda_pkgs: Contains the cache for downloaded and decompressed packages
Creating the first environment creates an additional directory in the install location:
conda_envs: Contains the created environment(s)
Using conda
conda allows to seperate installed software packages from each other by creating so-called environments. Using environments is best practice to generate deterministic and reproducible tools.
conda takes care of dependencies common to the packages it is asked to install. If two packages have a common dependency but define a differing range of version requirements of said dependency, conda chooses the highest common version number. This means the dependency installed in an environment with both packages together might have a lower version number than in environments seperating both packages.
It is best practice to seperate packages in different environments if they don't need to interact.
For a complete guide to conda see the official documentation.
The official cheat sheet contains a compact summary of common commands. An abbreviated list to get you started is shown below.
Installation examples
For conda, python itself is just a software package as any other. After analyzing all packages to be installed it decides which python version works for the whole environment. This means different environments may contain differing versions of python.
Creating an environment with a specific python version
- Time to install: ~1 minute
- Space required: ~140M
conda create --name py38 python=3.8.5
Creating an environment with the GPU version of pytorch and CUDA toolkit 10
- Time to install: ~5 minutes
- Space required: ~2.5G
conda create --name pytcu10 pytorch torchvision cudatoolkit=10.1 --channel pytorch
Be sure to read Installing a specific toolkit version if you intend to use this example for more than just first steps with conda.
Creating an environment with the GPU version of tensorflow and CUDA toolkit 10
- Time to install: ~5 minutes
- Space required: ~2G
conda create --name tencu10 tensorflow-gpu cudatoolkit=10.1
Be sure to read Installing a specific toolkit version if you intend to use this example for more than just first steps with conda.
Environments
conda automatically installs a default environment called base with a python interpreter, pip and other tools to start coding in python.
It is strongly discouraged to use the base environment for projects. It's purpose is to provide the tools to maintain other environments, nothing else.
Set up a new environment for each project. This ensures reproducability and facilitates environment related problem solving.
Only auto activate an environment in your shell initialisation script if you understand exactly what this entails.
It's good practice to make sure conda is initialized and the wanted environment is active before trying to use it
Create an environment called "my_env" with packages "package1" and "package2" installed
conda create --name my_env package1 package2
Activate the environment called "my_env"
conda activate my_env
Deactivate the current environment
conda deactivate
List available environments
conda env list
Remove the environment called "my_env"
conda remove --name my_env --all
Create a cloned environment named "cloned_env" from "original_env"
conda create --name cloned_env --clone original_env
Export the active environment definition to the file "my_env.yml"
This command is also the basis for backing up an environment.
conda env export --json --name my_env > my_env.yml
Recreate a previously exported environment
conda env create --file my_env.yml
Creates the environment "my_env" in the specified location
This example is for creating the environment on local scratch for faster disk access
conda create --prefix /scratch/$USER/conda_envs/my_env
Update an active environment
Make sure to create a backup by exporting the active environment before updating.
conda update --update-all
Packages
Search for a package named "package1"
conda search package1
Search for packages with "pack" in their name
conda search *pack*
Install the package named "package1" in the active environment
conda install package1
List packages installed in the active environment
conda list
Add software channels
The list of available software can be extended by adding channels of selected repositories. The priority of the channels is set in order of configuration. In the following example, Conda-Forge has the highest priority over Bioconda, with the default channel at the lowest priority.
conda config --add channels defaults conda config --add channels bioconda conda config --add channels conda-forge
Show software channels
The following command shows the available channels in order of priority (highest first):
conda config --show channels
Search for public (unofficial) packages
Packages maintained by the public and their respective channels can be searched on Anaconda Cloud.
Miscellaneous
Display information about the current conda installation
conda info
Check for conda initialization and active environment
To make sure conda is initialized and an environment is active the following script can be started:
#!/bin/bash
if [[ -z ${CONDA_EXE} ]]; then
echo 'Environment variable CONDA_EXE is not set.'
echo 'Please make sure conda is properly initialized.'
exit 1
else
if [[ ! -x ${CONDA_EXE} ]]; then
echo "${CONDA_EXE} is not executable."
echo "Please make sure it exists and is executable."
exit 2
else
if [[ -z ${CONDA_DEFAULT_ENV} ]]; then
echo 'Environment variable CONDA_DEFAULT_ENV is not set.'
echo 'Please make sure to activate a conda environment.'
exit 3
else
conda info
fi
fi
fi
Save this script as conda_env_check.sh, make it executable with
chmod +x ./conda_env_check.sh
A use case is to start this script within a cluster job before using the first command installed in an environment. You can either run the script from your cluster job or place your job commands into the innermost branch after the command conda info.
Change TMPDIR
If the message "Not enough space on partition mounted at /tmp." is shown during a package installation, set the TMPDIR variable to a location with enough available space:
export TMPDIR="/scratch/$USER/tmp"
Maintenance
The cache of installed packages will consume a lot of space over time. The default location set for the package cache resides on NetScratch, the terms of use for this storage area require you to clean your cache regularly.
Remove index cache, lock files, unused cache packages, and tarballs
conda clean --all
Update conda without any active environment
conda update conda
Backup
Regular backups are recommended to be able to reproduce an environment used at a certain point in time. Before installing or updating an environment, a backup should always be created in order to be able to revert the changes.
It is not necessary to backup environments themselves, it is sufficient to backup the files of environment exports to recreate them exactly.
For a simple backup of all environments the following script can be used:
#!/bin/bash
BACKUP_DIR="${HOME}/conda_env_backup"
MY_TIME_FORMAT='%Y-%m-%d_%H-%M-%S'
NOW=$(date "+${MY_TIME_FORMAT}")
[[ ! -d "${BACKUP_DIR}" ]] && mkdir "${BACKUP_DIR}"
ENVS=$(conda env list |grep '^\w' |cut -d' ' -f1)
for env in $ENVS; do
echo "Exporting ${env} to ${BACKUP_DIR}/${env}_${NOW}.yml"
conda env export --name "${env}"> "${BACKUP_DIR}/${env}_${NOW}.yml"
done