Installation¶

We put significant effort into making the installation process for ipyrad as easy as possible, whether you are working on your own desktop computer, or remotely on a large computing cluster. Simply copy and paste a few lines of code below and you will be ready to go.

Conda install¶

The easiest way to install ipyrad and all of its dependencies is with conda, a command line program for installing Python packages. If you already have conda installed skip to the ipyrad install section below. Otherwise, follow these instructions to first install conda for Python 2.7 on your system.

Conda comes in two flavors, anaconda and miniconda. The only difference between the two is that anaconda installs a large suite of commonly used Python packages along with the base installer, whereas miniconda installs only a bare bones version that includes just the framework for installing new packages. I recommend miniconda, and that’s what we’ll use here.

The code below includes a line that will download the conda installer. Make sure you follow either the Linux or Mac instructions, whichever is appropriate for your system. If you are working on an HPC cluster it is almost certainly Linux.

While conda is installing it will ask you to answer yes to a few questions. This includes whether it can append the newly created miniconda/ (or anaconda/) directory to your $PATH, say yes. What this does is add a line to your ~/.bashrc (or ~/.bash_profile on Mac) file so that the software in your conda directory can be automatically found by the systems whenever you login. Mac install instructions for conda¶ ## The curl command is used to download the installer from the web. ## Take note that the -O flag is a capital o not a zero. curl -O https://repo.continuum.io/miniconda/Miniconda2-latest-MacOSX-x86_64.sh ## Install miniconda. By default it will propose installing to your ## home directory, which should be fine, e.g., /home/user/miniconda2 ## When asked yes/no to append the miniconda directory to$PATH, say yes.
bash Miniconda2-latest-MacOSX-x86_64.sh

## Now run the following command to reload your ~/.bash_profile so that
## miniconda will be in your path. This is necessary so that the conda
## program can be found from the terminal by simply typing conda. If a
## ~/.bash_profile does not exist it might alternatively be named ~/.bashrc.
source ~/.bash_profile

## test that conda is installed. This will print info about your conda install.
conda info


Linux install instructions for conda¶

## The curl command is used to download the installer from the web. Take note
## that the -O flag is a capital o not a zero.
wget https://repo.continuum.io/miniconda/Miniconda2-latest-Linux-x86_64.sh

## Install miniconda. Follow the directions, by default it will propose installing
## to your home directory, which should be fine, e.g., /home/user/miniconda2
## When asked yes/no whether to append the miniconda directory to \$PATH, say yes.
bash Miniconda2-latest-Linux-x86_64.sh

## You could now quit and reopen the terminal, or just run the following command
## This is necessary so that the conda program can be found from the terminal by
## simply typing conda.
source ~/.bashrc

## test that conda is installed. This will print info about your conda install.
conda info


Once conda is installed, ipyrad can be installed by typing the following command into a terminal. This sometimes takes a few minutes to check all of the dependencies before the installation finishes, so be patient. Make sure you do not forget the -c ipyrad flag. This tells conda that the ipyrad package is located in a channel called ipyrad.

conda update conda                 ## updates conda


If you wish to install a specific version of ipyrad, or to upgrade from an older version to the most recent release, you can use one of the following commands:

conda install -c ipyrad ipyrad=0.5.1     ## install specific version


How does this work on a HPC cluster?¶

If you’re working on an HPC cluster you should still follow the exact same instructions above to install conda into your local home directory (e.g., /home/user). This does not require administrative privileges. In fact, the whole point is to create a local repository for software that you control yourself, separate from the system-wide software.

This is useful because it then allows you to install and access ipyrad and all its dependencies (other Python modules and executables), and to update them yourself. Lot’s of useful software is available on conda, which you can find and install by googling conda and the software name.

How do I ignore or remove conda?¶

Conda is super easy to ignore or remove if you ever find that it is not working for you. Conda itself, as well as all of the software that it installs is located in the miniconda/ directory, and so you can remove all of it by removing that directory. I would advise, however, that a much simpler way to switch on/off conda software would be to simply comment out the line in your ~/.bashrc file that appends miniconda/ to your PATH. Then run source ~/.bashrc and your system will completely ignore the conda software. Likewise, you can uncomment the line, re-source the file, and your conda software will be back. Conda is hugely popular, but it is also quite new, and actively under development, which has caused some issues with compatibility when major updates have arisen over the last 1-2 years. If you have a quite old conda distribution (pre v.4) that is giving you troubles when you try to update software I would recommend removing it and reinstalling. You can then reinstall all of your conda software quite easily.

The conda installation will install the following required dependencies:

Python Packages:

• Numpy – Scientific processing
• Scipy – Scientific processing
• Pandas – Used for manipulating data frames
• Sphinx – Used for building documentation
• ipyparallel – Parallel, threading, MPI support
• jupyter – Creating reproducible notebooks (IPython)
• Cython – C bindings for Python
• H5py – Database and HDF5 headers
• Toyplot – Plotting

Executables:

• vsearch – used for de novo clustering
• muscle – used for sequence alignment
• bwa_ – used for reference mapping
• smalt – alternatively can used for reference mapping
• samtools – used for reference mapping
• bedtools – used for reference mapping
• hdf5 – used for large array storage/access
• mpich – used for parallelization (mpirun, mpiexec)

Installation Troubleshooting note¶

If after installing ipyrad via conda you are getting errors like this:

ValueError(numpy.dtype has the wrong size, try recompiling)


You may be having conflicts between your system or local python packages and those installed by conda. In order to work around the problem you can do the following from your shell:

export PYTHONNOUSERSITE=True


And then running ipyrad. This will disable python from looking for libraries in it’s usual places, and use only packages installed via conda.