DSC Installation Guide

Follow these steps to get started using DSC.

If you encounter a problem during the installation procedure, please see the “Troubleshooting installation” section in the FAQ for a possible solution.

Note: If you have Docker, you can follow the Docker instructions instead of installing DSC from source. Once you have completed the Docker instructions, jump directly to Installation Step 5 below.

Note to developers: Please refer to the installation instructions in the README of the dsc repository.

Overview of DSC components

DSC consists of several components that interact with each other. Before beginning the installation, it is helpful to know: (1) what is being installed, (2) where DSC is installed, and (3) what software is needed to run DSC successfully.

To install DSC, you will need to have the following software on your computer:

  1. Python (version 3.6 or greater).

  2. Several Python modules, including NumPy and Pandas.

  3. Optionally, R. Although not required, to get the full benefit of DSC we recommend installing R.

The DSC software consists of the following three components:

  1. A Python module called dsc. It is installed in the same location as other Python modules (unless you choose to override the standard choice).

  2. Two Python executables, dsc and dsc-query, that can be run from the command-line shell. These executables are also installed and managed by the pip program. It is installed in the same location as other Python executables (unless you choose to override the standard choice).

  3. An R package called dscrutils that provides an interface for querying DSC results in R, as well as tools to run R code inside a DSC program. It is installed in the same location as other R packages.

A complete installation of DSC not only involves installing these components, but also setting up your computing environment to ensure that these components can communicate with each other. We will explain how to do this in the steps below.

1. Install python >= 3.6

To use DSC, you must have Python version 3.6 or greater. There are several ways you can install Python >= 3.6.

Our recommendation: Install Python via a conda-based package manager such as Miniconda or Anaconda. If you are starting from scratch, we recommend Miniconda. See here for additional advice on installing and configuring Miniconda.

** Other options:** DSC will also work with standalone distributions of Python (e.g., downloaded from Python.org), and the instructions below should work regardless of how Python is installed on your computer. However, we recommend conda because it will provide easy access to various Python packages DSC depends on, thus making it a lot easier to install DSC.

2. Check your Python installation

DSC is distributed via pypi. The simplest way to install a Python module from pypi is with pip. All recent Python versions are by default bundled with pip. Before running pip, check that you are running the version bundled with Python >= 3.6:

python --version
pip --version


python3 --version
pip3 --version

If the reported Python version is or greater than 3.6.0 and pip is reported to come from that version (eg. pip 9.0.1 from /path/to/python (python 3.6)), then you are ready for the next step.

Important: In the instructions below, we assume your Python 3.6+ executable is python, and your pip (python 3.6+) executable is pip. However, you might need to replace python with python3 and pip with pip3.

If you already have an old version of Miniconda or Anaconda installed, but you do not have Python >= 3.6, see here for advice on how to proceed.

3. Install (or upgrade) DSC

We provide two sets of installation instructions: Python installed with conda (i.e., Anaconda or Miniconda), and Python not installed with conda.

3a. If Python is installed with conda (Anaconda or Miniconda)

Using conda, install DSC from the conda-forge channel:

conda install -c conda-forge dsc

3b. If Python is not installed with conda

Run this command to install or upgrade DSC (and any Python dependencies that remain uninstalled):

pip install -U --upgrade-strategy only-if-needed dsc

However, we caution that:

  • You must have both C and Fortran compilers (and accompanying libraries).

  • The pip command may take a long time to run because several packages will need to be built from source.

  • Installation of some packages may fail. If so, try running the same command again; sometimes running the same pip command a second time works!

If you are having difficulty installing DSC and its dependnencies directly from source, we recommend switching to using conda. Since conda installs binary packages that have already been compiled, this saves you from having to configure the correct compiler settings on your local machine.

4. Install modules for network visualization of benchmarks (optional)

If you’d like to be able to create a network visualization of your benchmarks, you’ll need to install some additional Python modules. This is an entirely optional feature which will not affect the running of your DSC benchmarks.

3a. If Python is installed with conda (Anaconda or Miniconda)

Run the following:

conda install -c conda-forge python-graphviz imageio pillow

3b. If Python is not installed with conda

Run the following:

pip install -U --upgrade-strategy only-if-needed graphviz imageio pillow

5. Verify installation of Python module

Check that the Python module is installed and recognized in your current shell environment by running this command:

pip show dsc

After running this command, you should see something like this:

Name: dsc
Summary: Implementation of Dynamic Statistical Comparisons
Home-page: https://github.com/stephenslab/dsc
Author: Gao Wang
Author-email: gaow@uchicago.edu
License: MIT
Location: /home/jsmith/anaconda3/lib/python3.6/site-packages
Requires: numpy, pandas, sympy, numexpr, sos, sos-pbs, h5py, pyarrow, sqlalchemy, msgpack-python

6. Test installation of Python executables

Run the following commands to verify that the Python executables are accessible in your current shell environment:

dsc --version
dsc-query --version

For both commands, you should see the software version number printed to the screen.

If you get an error, and you have verified that the Python module has been successfully installed, the most likely explanation is that the Python executables are stored in a location that is not in your command search path. In particular, this location needs to be included in the PATH environment variable.

NOTE: I think it would be better to move this to the FAQ Troubleshooting section, with title, “What do I do when it says that commands dsc or dsc-query cannot be found”?

The most reliable is to way to find the location of the executables is to run these two commands:

pip show dsc
pip show dsc --files | grep dsc-query

The first command gives the install location of the Python module, and the second command gives the install location of the executables which may be relative to the Python module. Based on this, you can run the following command in the bash shell to add the appropriate location to your command search path:

export PATH=<python-exec-path>:$PATH

where <python-exec-path> was identified from running the commands above. For example, in Anaconda the first and second install locations may look something like /home/jsmith/anaconda3/lib/python3.6/site-packages and ../../../bin/dsc-query, in which case running

export PATH=/home/jsmith/anaconda3/lib:$PATH

should make the dsc and dsc-query commands accessible.

7. Install R (optional)

R is optional, but highly recommended—it is useful for querying DSC results. It is also required for running any DSC benchmarks that run R code. Follow the instructions on the CRAN website to install R on your computer. DSC also works with RStudio, although an additional setup step may be required for RStudio.

8. Install dscrutils R package (optional)

The simplest way to install the dscrutils package is to start up R or RStudio and run the following code:

install_github("stephenslab/dsc",subdir = "dscrutils",force = TRUE)

This will also install the devtools package.

9. Ensure dsc-query is recognized in R (optional)

In a previous step, you verified that dsc-query can be run from the command-line shell. In order to query DSC results, we also need to make sure that it can be run inside your preferred R environment.

Start up R or RStudio, and run

system("dsc-query --version")

If this outputs a version number, then you are ready to use the dscrutils package. If this command reports an error, then most likely you will need to fix the command search path inside R or RStudio; see the Troubleshooting section of the FAQ page for instructions on how to do this.

10. Start your first DSC project

If you have reached this point, you have everything you need to start working with DSC.

Start from here for a first course on DSC. See here for more introductory tutorials.