Testing your skill

Once you have developed your skill, you should test it. You can launch the pytlas repl and test it manually or (the prefered approach) use some code to trigger agent state and make assertions about how your skill has answered.

In order to help you do the later approach, there’s some utilities in the pytlas package itself.

Let’s consider this tiny skill:

from pytlas import training, intent

def en_data(): return """
  turn the @[room]'s lights on would you
  turn lights on in the @[room]
  lights on in @[room] please
  turn on the lights in @[room]
  turn the lights on in @[room]
  enlight me in @[room]


  living room

def on_lights_on(r):
  rooms = req.intent.slot('room')

  if not rooms:
    return req.agent.ask('room', 'For which rooms?')

  req.agent.answer('Turning lights on in %s' % ', '.join(room.value for room in rooms))

  return req.agent.done()

Writing tests

In order to make assertions, pytlas use the excellent sure library so let’s use them here too.

Now, let’s create a file test_lights.py next to your skill python file.


Since create_skill_agent uses the SnipsInterpreter, you must have snips-nlu installed and language resources too. See snips for more informations.

from sure import expect
from pytlas.testing import create_skill_agent
import os

# Let's instantiate an agent specifically designed to make assertions easier.
# It will fit the data with the SnipsInterpreter so you have pretty much what
# will be used in a real case scenario.
agent = create_skill_agent(os.path.dirname(__file__))

class TestLights:

  def setup(self):
    # Between each tests, resets the model mock so calls are dismissed and we
    # start on a fresh state.

  def test_it_should_answer_directly_when_room_is_given(self):
    agent.parse('Turn the lights on in the kitchen please')

    # Retrieve the last call on on_answer (you can also give an integer if you have multiple calls in your skill).
    # Here `agent.model.on_answer` is a `pytlas.testing.ModelMock` with some utilities to make assertions.
    on_answer = agent.model.on_answer.get_call()

    # And make assertions on argument names
    expect(on_answer.text).to.equal('Turning lights on in kitchen')

  def test_it_should_ask_for_room_when_no_one_is_given(self):
    agent.parse('Turn the lights on')

    on_ask = agent.model.on_ask.get_call()

    expect(on_ask.text).to.equal('For which rooms?')

    agent.parse('In the bedroom')

    on_answer = agent.model.on_answer.get_call()

    expect(on_answer.text).to.equal('Turning lights on in bedroom')

    # Since it inherits from `MagicMock`, you can use all methods to make assertions

Launching tests

In order to launch tests, pytlas uses nose, so you may use it to test your skill too.

In your skill directory, just launch the following command:

$ python -m nose
Ran 2 tests in 0.016s