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--- echo_stock_price [2017/05/30 16:39] – created tbrodeur
+++ echo_stock_price [2017/05/30 17:13] (current) – tbrodeur
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 <fs large>Overview</fs>
+Create an Alexa Skill that returns stock data for 10 listed companies.
@@ Line 32: / Line 34: @@
 . <fs large>Add the code</fs>
+<fc #4682b4>
+******The code below is commented out in order to provide you with a better understanding. If you have any further questions, please feel free to contact me at the email listed above.******</fc>
 <code python index.py>
@@ Line 46: / Line 50: @@
 	if (event['session']['application']['applicationId'] !=
 		#Change to application id listed under your alexa skill in the developer portal
-		"amzn1.ask.skill.f976aad9-6567-4a27-8bce-7a0cfe9861e7"):
+		"amzn1.ask.skill.XXXXXXXX-XXXX-XXXX-XXXX-XXXXXXXXXXXX"):
 		raise ValueError("Invalid Application ID")
@@ Line 291: / Line 295: @@
 <fc #4682b4>
 ******Make sure to change the application id listed in lambda_handler() to your own id once you create the Alexa Skill with Alexa Skills Kit******</fc>
-<color #22b14c>-----------------------------------------------------------------------------------------------------------------------------
-</color>
-The handler function takes two parameters:
-  * event: will contain an object with information about the request.
-  * context: will represent the state of the Lambda function (for
-  * example, how much time is left before the function times out). The
-  * context parameter is also used for sending a response back to the
-  * caller.
-In this tutorial, we’ll run the web service on AWS Lambda, a service
-that executes code in response to events, thus saving the developer
-the trouble of maintaining a server. Lambda also links seamlessly to
-the Alexa Skills Kit, which makes it an excellent tool for running the
-code for Alexa Skills.
-We will implement the server functionality as a python module, so to
-complete the tutorial, you’ll need a basic understanding of python2.7.
-Every request from the Alexa Skills Kit has a type, passed in event.request.type.
-In all, there are three request types, all of which the service needs to
-respond to separately:
-  * Launch request: Sent when the user launches the Skill. The
-  * example code calls the helper function onLaunch to initialize the
-  * help function.
-  * SessionEndedRequest: Sent when the user stops using the skill
-  * by saying “exit”, by not responding for a while, or if an error occurs.
-  * The example code calls the helper function onSessionEnded,
-  * which is currently just a placeholder and doesn’t do anything.
-  * IntentRequest: Sent when the user speaks a command that
-  * maps to an intent. The example code calls the helper function
-  * onIntent.
-Amazon’s documentation explains that:
-“[A]n intent represents a high-level action that fulfills a user’s
-spoken request. Intents can optionally have arguments called
-slots that collect additional information needed to fulfill the
-user’s request.”
-When a user speaks a command, Alexa converts it to text and
-compares it to a list of phrases the application understands. Each
-phrase is mapped to an intent definition so that your code doesn’t
-have to worry about parsing the free-form input from the user but can
-rely on the intents to organize its communication with the user.
-<color #22b14c>-----------------------------------------------------------------------------------------------------------------------------
-</color>
-You’ll soon see how to specify the intents for your skill, but first, let’s
-take a look at the onIntent function to see how Alexa handles
-the intents.
-<code python>
-def on_intent(intent_request, session):
-	intent = intent_request["intent"]
-	intent_name = intent_request["intent"]["name"]
-	if intent_name == "Hello":
-		return say_hello()
-	elif intent_name == "AMAZON.HelpIntent":
-		return get_welcome_response()
-	elif intent_name == "AMAZON.CancelIntent" or intent_name == "AMAZON.StopIntent":
-		return handle_session_end_request()
-	else:
-		raise ValueError("Invalid intent")
-</code>
-As you can see, most of the function is an if..else structure that
-compares the intent name from the request to a set of intents the
-skill accepts. Depending on the intent name, it then calls a matching function.
-For example, when Alexa receives a request with the intent name
-Hello, it calls the corresponding say_hello() function.
-<color #22b14c>-----------------------------------------------------------------------------------------------------------------------------
-</color>
-Looking at the say_hello function,
-<code python>
-def say_hello():
-	session_attributes = {}
-	card_title = "Hello World"
-	speech_output = "Hello World"
-	reprompt_text = ""
-	should_end_session = True
-	return build_response(session_attributes, build_speechlet_response(
-        card_title, speech_output, reprompt_text, should_end_session))
-</code>
-we can see that the function returns a build_response function that will pass arguments defined in the say_hello function.
--card_title: name of the card that will display on the Alexa app on your smartphone
--speech_output: what the Echo or Echo Dot will ouput once the function build_response function is called
--should_end_session: tells Alexa whether to end the skill session after a response has been outputed. This should be set to True in this case. If a reprompt text is defined, usually should_end_session would be set to false, however all we are doing with this function is asking for a simple output.
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