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Python module with a base class to support an Alexa skill set, and scripts to build an AWS python distibution

Project description

PyPI Package to search for is: pyalexa-skill

PyAlexa-Skill is an Open Source licensed Python package with a base class that support the necessary methods for an Alexa Skill set and two scripts to help with the creation of the main entry point and the packaging of the AWS Lambda Function for the Alexa Skill Set.

AlexaBaseHandler class

The AlexaBaseHandler class is an abstract class that provides the necessary framework to build the response hooks for an Alexa application.

It has a single abstract method, and it will dynamically call methods based on the Alexa intent or request.

Alexa Requests

For Alexa requests, this class will look for methods of the form:

def on_<request name>

For example, the LaunchRequest will look for a method of the name:

def on_launchrequest(self, launch_request, session):

Alexa/Amazon Intents

For Alexa intents, this class will look for methods of the form:

def on_<intentname>_intent

For example,


will look for a method of the name:

def on_yes_intent(intent_request, session)


will look fr a method of the name:

def on_help_intent(intent_request, session)

Application Defined Intents

And intents that are application defined will follow the form:

def on_<application intent name>_intent(intent_request, session)

abstract method

The only abstract method that has to be implemented is the following:

def on_processing_error(self, event, context, exc):


This method will take the 2 parameters that are sent to the lambda function and determine which of the Alexa handlers to invoke.

For the Amazon Built-in requests such as AMAZON.YesIntent, process request will call a method of the form: on_<intentname>_intent, e.g. on_yes_intent(). It is expected that the concrete implementation will have a the necessary methods to support the built-in intents.

For custom intents, such as, MyCustomIntent, process request will call a method of the form: on_<intentname>_intent, e.g. on_mycustomintent_intent(). In this case, no assumption is made about the custom intent name, so the entire name is lower cased, then used in the creation of the dynamic method call.

For Amazon Built-in requests such as AudioPlayer.PlaybackStarted, process request will call a method of the form: on_<major name>_<minor name>, e.g. on_audioplayer_playbackstarted().

If any of the dynamically called methods is not found, a NotImplementedError exception is raised.


This method ( from the Alexa color example ) will put together the speechlet portion into a properly formatted json message. This is typically called by the concrete implementations of the AlexaBaseHandler.


This method (from the Alexa color example ) will construct a properly formatted response message so the Amazon Echo knows what to respond with.

AlexaDeploymentHandler class

This class is a reference implementation that does nothing useful. All Alexa handlers are handled the same way.

To create the concrete implementation use the following:

from pyalexaskill import AlexaBaseHandler
class MyConcreteAlexaHandler(AlexaBaseHandler.AlexaBaseHandler):
    # implement the abstract methods

This file contains the main entry point of the lambda function that is called for the Alexa skill.

lambda_handler(event, context)

This method ( which can be called anything, you just need to configure it in the lambda handler ), is the method that is called with the 2 parameters.

This method will typically instantiate an concrete implementation of the AlexaBaseHandler and delegate to the process_request method.


This file is the standard Python requirements file. This file is used by the script to install the necessary 3rd party libraries that your Alexa skill might need. Any library specified in the requirements.txt file will be installed into your deployment directory.

Create a zip file of all code necessary for AWS Lambda

This script creates a zip file per the Amazon lambda specification, such that it is suitable to upload as your lambda function implementation.

activate your virtualenv and execute like: -r <rootdir> -i "list,of,all,python,files,to,include"

This script creates a template main entry point

All deployments are stored in the deployments subdirectory and follow the naming convention of ‘deployment_n’ and ‘’, where ‘n’ is automatically calculated to the next largest ‘n’ in the directory. Right now it does this based on the name of the subdirectories of deployments - NOT - the names of the zip files.

The deployment script will create a deployment directory and zip file for everything in the requirements.txt file AND the files in the deployment_files variable in the file.

When this script is done running, there should be a ‘’ file in the deployments directory. It is that file that needs to be upload to the Amazon Lambda console.

activate your virutal env and execute like:

This script creates a template concrete handler class.

This template can be used as the starting point to create the necessary implementation details for the handler.

activate your virtualenv and execute like:

This script creates a template utterance and intent schema.

This template can be used as the starting point to create the necessary implementation details for an actual utterance and intent schema.

activate your virtualenv and execute like:

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pyalexa-skill-0.2.8.tar.gz (19.4 kB) Copy SHA256 hash SHA256 Source None Dec 1, 2017

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