The following sections contain quick instructions for getting started on specific machines.
The fastest way to get Balsam on Theta is to load the module.
$ module load balsam $ which balsam /soft/datascience/Balsam/0.3.5.1/env/bin/balsam $ which python /soft/datascience/Balsam/0.3.5.1/env/bin/python
As you can see, the module loads a Python 3.6 environment with pre-configured Balsam installation. Don't worry if your applications rely on different environments or Python installations. You can simply use the Balsam Python environment to set up and manage your workflows, while a different version of Python runs in the backend.
$ source /soft/datascience/balsam/setup.sh $ which balsam /soft/datascience/balsam/env/bin/balsam
Balsam requires Python 3.6 or later. Preferably, set up an isolated virtualenv or conda environment for Balsam. It's no problem if some applications in your workflow run in different Python environments. You will need setuptools 39.2 or newer:
$ pip install --upgrade pip setuptools
Some Balsam components require
mpi4py, so it is best to install
Balsam in an environment with mpi4py already in place.
At the minimum, a working MPI
mpicc compiler wrapper should be in the
search path, in which case
pip install balsam-flow will automatically build
Finally, Balsam requires PostgreSQL version 9.6.4 or newer to be
installed. You can verify that PostgreSQL is in the search
PATH and the version is up-to-date with:
$ pg_ctl --version
It's very easy to get the PostgreSQL
you don't already have them. Simply adding the PostgreSQL
bin/ to your search
PATH should be enough to use Balsam
without having to bother a system administrator.
Installation from PyPI
$ pip install balsam-flow
Create a Balsam DB to start working
You can use the command line to start working with Balsam.
init is used to create a new database at the specified
source balsmactivate takes a database path (or
unique substring) and starts up the database.
$ balsam init ~/myWorkflow $ source balsamactivate myWorkflow $ balsam app --name SayHello --executable "echo hello," $ balsam job --name hi --workflow test --application SayHello --args "World!" $ balsam submit-launch -A MyProject -q DebugQueue -t 5 -n 1 --job-mode=mpi $ watch balsam ls # follow status in realtime from command-line
For production workflows, be sure to create a database on the appropriate filesystem for your platform. Typically, your home directory is not the right place for production I/O!