get_started.md

Getting started with Launchpad

Implement nodes

The setup in this example is as follows. LaunchPad program launches one consumer and a number of producers to perform some time consuming task. Consumer sends requests to producers and waits for work completion. Afterwards it summarizes the work.

The standard imports and flag setup are as follows. The num_producers flag defined here can be used to control the number of producers.

from absl import app
from absl import flags
from absl import logging
import launchpad as lp

FLAGS = flags.FLAGS
flags.DEFINE_integer('num_producers', 2, 'The number of concurrent producers.')

The interface for the producer has just one method which performs some work (for you to implement) in a given context provided by the caller. Any method of the class can be exposed for other nodes to call by wrapping a node in a CourierNode. In a typical setup, all nodes live in separate processes or on distinct machines, while the communication between the nodes is taken care of transparently by Launchpad. Some care has to be taken though. For example, the work() method may be called from multiple threads within the same process, so if the producer were to have any shared state then access to it must be made thread-safe. In this case, the producer is stateless so it is not a concern.

class Producer:
  def work(self, context):
    return context

The consumer defines an initializer and a run() method. The initializer takes a list of handles to the producers (CourierNodes).

Any Launchpad PyClassNode with a run() method will have that method called automatically upon program entry. Here the run() method simply calls work() on each producer and collects the results. At the end, it calls launchpad.stop() to terminate all nodes running within a program.

class Consumer:
  def __init__(self, producers):
    self._producers = producers

  def run(self):
    results = [producer.work(context)
               for context, producer in enumerate(self._producers)]
    logging.info('Results: %s', results)
    lp.stop()

In the example above, work() methods are called sequentially, so there is no benefit in running this program distributed. Launchpad, however, allows for asynchronous calls as well through the use of futures. In the example below all producers will perform their work in parallel while consumer waits on all of their results when calling future.result(). Note that futures are only supported by the CourierNode.

class Consumer:
  def __init__(self, producers):
    self._producers = producers

  def run(self):
    futures = [producer.futures.work(context)
               for context, producer in enumerate(self._producers)]
    results = [future.result() for future in futures]
    logging.info('Results: %s', results)
    lp.stop()

Define topology

The next step is to instantiate nodes for the consumer and producers and then connect them so that the consumer can call methods on the producers. The connections between nodes define the topology of the distributed program.

Launchpad uses an lp.Program class to hold all the nodes. There are several different types of nodes but here lp.CourierNode is used since it is the simplest type which supports communication between nodes. The parameters to lp.CourierNode are the name of the class and the parameters of its initializer. Connecting the consumer node to the producer nodes is as simple as passing in handles to all producers in the initializer of the consumer. The handles themselves are returned by lp.Program.add_node().

def make_program(num_producers):
  program = lp.Program('consumer_producers')
  with program.group('producer'):
    producers = [
        program.add_node(lp.CourierNode(Producer)) for _ in range(num_producers)
    ]
  node = lp.CourierNode(
      Consumer,
      producers=producers)
  program.add_node(node, label='consumer')
  return program

With the above function defining the topology all that remains is to implement main() for Launchpad:

def main(_):
  program = make_program(num_producers=FLAGS.num_producers)
  lp.launch(program)

if __name__ == '__main__':
  app.run(main)

Launch

To launch the program (assuming it is called launch.py), simply run:

python3 -m launch --lp_launch_type=local_mp

The --lp_launch_type controls how the program is launched. In the above case it is launched locally with each node executed in a separate process. List of supported execution modes can be found here.

Add a test

Here are some points to keep in mind when creating a test for a Launchpad program.

• The easiest way to add a test for your program is to reuse the same topology for an integration test (i.e. call make_program() from above in this example).
• Launch a test by calling lp.launch() just like in main() in the above example, but explicitly specify launch_type='test_mt' (multithreaded tests) or launch_type='test_mp' (multiprocess tests) as a parameter.
• It is possible to disable automatic execution of a node's run() method before launching. Do so by calling disable_run() on the node in question.
• In order to call methods to test on a Courier node you will need to explicitly dereference the handle of the node first. Do so by calling create_handle() followed by dereference() on the node in question.

Below is an incomplete example illustrating the above concepts. A complete example can be found here.

import launchpad as lp
from launchpad.examples.consumer_producers import launch
from absl.testing import absltest

class LaunchTest(absltest.TestCase):
  def test_consumer(self):
    program = launch.make_program(num_producers=2)
    (consumer_node,) = program.groups['consumer']
    consumer_node.disable_run()
    lp.launch(program, launch_type='test_mt')
    consumer = consumer_node.create_handle().dereference()
    # Perform actual test here by calling methods on `consumer` ...