On O2, we encourage cluster users to install the packages and software they need. One method to install packages and manage environments is to use conda, which is available through the
conda2/4.2.13 module. Conda manages dependencies by default when you install packages, which can make it easier to install software. Packages that can be installed with conda include Python modules, libraries, or executable programs. Conda includes its own version of Python (2.7.12), though you can explicitly request to use Python 3 if you would prefer.
Commonly used commands, examples
|module spider conda||shows the versions of conda installed on O2|
|module load conda2/version|
loads an individual conda module
(replace version with an actual version)
|conda info --envs||see available conda environments|
|conda create -n test_env|
create conda environment named test_env
(name the environment whatever you'd like)
|conda create -n aligners_env bwa bowtie star||create conda environment, and install some packages (bwa, bowtie, and star) on the fly|
|source activate test_env|
"activate" a conda environment named test_env
|source deactivate||exit current conda environment|
|conda-env remove -n test_env||delete a conda environment named test_env|
|conda search numpy|
search for a package
(replace numpy with the package of your choice)
|conda install numpy|
install a package, and must be within a conda environment or this command will fail.
(replace numpy with the package of your choice)
To install packages on O2 using conda, you must first create a conda environment. Environments are simply directories in
~/.conda/envs/ that contain packages you installed. You "source" an environment to use those packages, and can "deactivate" to exit the environment. You can have multiple environments, and can switch between them.
First let's get into an interactive session, as installing conda packages is resource intensive and should not be done on the login nodes.
Next, load the conda module:
conda command will be available:
conda info will return information about the current conda installation:
You can see available conda environments with
conda info --envs. If you have not created any conda environments yet, the only listing you will see is the root environment in
/n/app/conda2. Cluster users do not have access to alter this.
You can create your own environment to install packages to. You can change the environment name (specified after
If you no longer want an environment, use
conda-env remove to delete the environment and any packages installed to it:
To use the conda environment, it must be activated. Note that your prompt will change:
To exit an environment you run
source deactivate, and your prompt will return to normal:
As you just exited the environment, any packages installed to that environment will not be able to be used now.
You can create as many conda environments as you need. Environments are independent (changing one environment won't affect another). They can be used for different analyses, or perhaps if you need more than one version of the same tool. You can run
conda info --envs to list all of your conda environments.
To search for available versions of a package that can be installed, use
With your conda environment activate, you can install a package with
conda install. Conda will handle dependencies by default. Make sure that you do not install conda packages when on a login node. Only install packages when you have requested dedicated resources beforehand (i.e. you are on a compute node and in a interactive job).
Conda and Python versions
Note that conda includes its own version of Python:
The default version of Python that's available through the conda module is Python 2.7.12:
If you want to use conda and Python 3, you can create a conda environment and install Python 3 to it. For example to create an environment using Python 3.6.5:
A full example
The centralized conda installation, available through the
conda2/4.2.13 module, includes several channels that we support. Channels are repositories where conda looks for packages. This is done with a centralized .condarc file that contains:
The order here matters, as conda will pull packages from channels based upon the channel "priority". For example, the channel listed first in .condarc has the highest priority, and the channel listed last has the lowest priority. This means that if the package you want to install is found in multiple channels in your .condarc, conda will default to installing the version found in the highest priority channel. See here in the conda documentation for more information on channel management.
Conda-forge is a repository of recipes, which are used to build conda packages. The defaults channel is necessary for several dependencies, including conda and conda-build. The r channel contains common R packages, some of which are dependencies for bioconda packages. Bioconda is a channel geared for bioinformatics packages.
If you wish, you can still maintain your own
~/.condarc file, but we may be unable to assist when using unsupported channels.