Five-minute quickstart

In this quickstart, you will:

  • Add a simple workflow to the central database via the command line
  • Run that workflow
  • Monitor your job status with the FireWorks database
  • Get a flavor of the Python API

This tutorial will emphasize “hands-on” usage of FireWorks via the command line and not explain things in detail.

Start FireWorks

  1. If not already running, start MongoDB:

    mongod --logpath <FILENAME_TO_LOG_TO> --fork
    

Note

If MongoDB is outputting a lot of text, you might want to start it in a dedicated Terminal window or use the --quiet option. In addition, if you are running it on a shared machine, make sure that the --dbpath variable is set to a directory that you can access. You may also wish to set up your Mongo config in a file and use the –config option.

  1. Reset/Initialize the FireWorks database (the LaunchPad):

    lpad reset

Note

If your FireWorks database is located on a different computer from your FireWorks installation, navigate to the computer containing FireWorks and type lpad init. This will set up a file that points to your remote database. You can now run lpad commands from within this directory. Alternatively, use the lpad -l option to point to this file or set up this file as your default db location using the FW config.

Note

All FireWorks commands come with built-in help. For example, type lpad -h or lpad reset -h. There often exist many different options for each command.

Add a Workflow

  1. There are many ways to add Workflows to the database. You can do it directly from the command line as:

    lpad add_scripts 'echo "hello"' 'echo "goodbye"' -n hello goodbye -w test_workflow

    Output:

    2013-10-03 13:51:19,991 INFO Added a workflow. id_map: {0: 1, 1: 2}

    This added a two-job linear workflow. The first jobs prints hello to the command line, and the second job prints goodbye. We gave names (optional) to each step as “hello” and “goodbye”. We named the workflow overall (optional) as “test_workflow”.

  2. Let’s look at our test workflow:

    lpad get_wfs -n test_workflow -d more

    Output:

    {
        "created_on": "2013-10-03T20:54:28.296672",
        "states": {
            "hello--1": "READY",
            "goodbye--2": "WAITING"
        },
        "state": "READY",
        "launch_dirs": {
            "hello--1": [],
            "goodbye--2": []
        },
        "name--id": "test_workflow--1",
        "updated_on": "2013-10-03T20:54:28.296676"
    }
    

    We get back basic information on our workflows. The second step “goodbye” is waiting for the first one to complete; it is not ready to run because it depends on the first job.

Run all Workflows

  1. You can run jobs one at a time (“singleshot”) or all at once (“rapidfire”). Let’s run all jobs:

    rlaunch --silencer rapidfire

    Output:

    hello
    goodbye
    

    Clearly, both steps of our workflow ran in the correct order.

  2. Let’s again look at our workflows:

    lpad get_wfs -n test_workflow -d more

    Output:

    {
        "created_on": "2013-10-03T20:57:24.978665",
        "states": {
            "hello--1": "COMPLETED",
            "goodbye--2": "COMPLETED"
        },
        "state": "COMPLETED",
        "launch_dirs": {
            "hello--1": [
                "/some/path/launcher_2013-10-03-20-56-29-345603"
            ],
            "goodbye--2": [
                "/some/path/launcher_2013-10-03-20-56-29-861385"
            ]
        },
        "name--id": "test_workflow--1",
        "updated_on": "2013-10-03T20:57:24.978670"
    }
    

    FireWorks automatically created launcher_ directories for each step in the Workflow and ran them. We see that both steps are complete. Note that there exist options to choose where to run jobs, as well as to tear down empty directories after running jobs.

Launch the web GUI

  1. If you have a web browser and installed Django (pip install django), you can launch the web browser to see your results:

    lpad webgui

Python code

The following Python code achieves the same behavior:

from fireworks.core.firework import FireWork, Workflow
from fireworks.core.launchpad import LaunchPad
from fireworks.core.rocket_launcher import rapidfire
from fireworks.user_objects.firetasks.script_task import ScriptTask

# set up the LaunchPad and reset it
launchpad = LaunchPad()
launchpad.reset('', require_password=False)

# create the individual FireWorks and Workflow
fw1 = FireWork(ScriptTask.from_str('echo "hello"'), name="hello", fw_id=1)
fw2 = FireWork(ScriptTask.from_str('echo "goodbye"'), name="goodbye", fw_id=2)
wf = Workflow([fw1, fw2], {1:2}, name="test workflow")

# store workflow and launch it locally
launchpad.add_wf(wf)
rapidfire(launchpad)

Note

The {1:2} argument is adding a dependency of fw2 to fw1. Meaning, fw2 will only run after fw1 completes.

Next steps

Now that you’ve successfully gotten things running, we encourage you to learn about all the different options FireWorks provides for designing, managing, running, and monitoring workflows. A good next step is the Introductory tutorial, which takes things more slowly than this quickstart.

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