How to Build Your First Amazon Alexa Skill, Pt. 2: Skill Interface

Welcome back, Alexa geeks! In the last article, we laid the groundwork for making our first Amazon Alexa skill. We covered the concepts and frameworks in Alexa skill development. We also did some work in AWS Lambda to prepare for voice requests  being made to our service.

 

Quick Recap on The Alexa Skill Service / AWS

We’ve slept a few times since covering the concepts and AWS framework, so let’s quickly recap.

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Whenever we use an Alexa skill , our voice data is processed through the hardware device, through the skill interface (what we’re looking at today) for language processing, then converted into text for a program to execute against, and back again. Simple enough, right?

In the last article, we looked at the “last” leg of this process, the skill service and AWS Lambda. Now, we’ll be working with that and the skill interface portion.

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Setting Up the Basic Skill Information

Alright, log into the Amazon Developer Portal and Select the Alexa menu option. Once there, you should have a choice between the Alexa Skills Kit or the Alexa Voice Service. Click on the Alexa Skills Kit link to continue. You’ll want to click, “Add a New Skill”. Because I’ve already developed a skill, Silly Marketing Strategies is already there. However,  most of y’all will probably not have anything else on screen.

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To start, you’ll want to select Custom Interaction Model, leave the default language to US (unless you’re developing in Espanol?). Type out the name and invocation name for your skill. The name isn’t necessarily important this moment. However, the invocation name will be extremely important!! This will be how users will call your Skill into service.

Note: the astute will notice I’ve deviated from the Space Geek example of the last article. More on that later. 🙂

When you’re ready, click next to proceed, and we’ll tackle the interaction model.

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Setting up the Skill’s Interaction Model

Alright, time for some important things here. For the purposes of the factoid-based game, we’ll only be looking at the Intent Schema and Sample Utterances fields.

First, we need to look at the Intent Schema. Remember the files you downloaded in the first article? You’ll need to go into the SpaceGeek folder, Speech Assets sub folder and open the IntentSchema.json file. I’ve opened it up in Sublime Text 2 briefly, so we can take a quick look at the file. So this is JSON, with intent pairs. Below, we’ve got a pretty simple set, intents for retrieving a fact from the skill, getting help, stopping and cancelling a function. It’s easy right? Ha.

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Quick note: because these intents are proceeded by Amazon – it means they’re built in for Amazon. Enough babbling, copy and paste the contents of this file into the Intent Schema section of Amazon Developer Console.

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Above, we’ve pasted in the Intent Schema. Next, we need to provide some sample utterances. Sample utterances are what you think users might say to engage your Alexa Skill. Below, we’ve provided such examples as, “Tell me a Weimaraner fact”.

Next, we need to hook up the Alexa Skill interface we’ve put together with some computing power. Specifically, we need to hook it up to AWS Lambda! (Remember the first article where we did a bunch of Lambda setup?)

If you recall, there was an Amazon Resource Name (ARN) string that we copied and saved to a text file. Retrieve it now and paste into the “Configuration” screen of the Skill interface setup.

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Providing the ARN you’ve provided is valid, you should be able to proceed to the next step. Note: we are ignoring the account linking functionality for now. This functionality allows you, for example, to integrate Twitter sharing functionality into your skill by sharing a Tweet.

Next, we’ll move on to the Test tab. Three things (below) to take note of:

  1. Ensure you’ve completed the Interaction Model tab, so you can complete the testing in this tab.
  2. Try / type out key phrases in your skill to hear how they’ll be pronounced, via the Voice Simulator.
  3. Enter some utterances into the Service Simulator to A) make sure your skill is functioning as intended and B) Get a feel for how the end user experience will happen

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Once you’ve tested your Skill, proceed to Publishing Information. Here, you’ll need to include the following:

  • Category of your Alexa SKill
  • The relevant Sub Category
  • Optional: testing instructions if your skill requires credentials or other unusual needs. You probably don’t need to include anything for this example
  • Country & Region targeting
  • Short Skill Description
  • Full Skill Description
  • Example Phrases, drawn from your sample utterances, and preceded by the Alexa wake word and skill invocation name
  • Optional: keywords that will help Alexa users find your skill in search
  • Images in 108 and 512 pixel squared dimensions

Below are a couple of screenshots for how I’ve filled out these fields.

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Alright, we’re so close! The last field is Privacy & Compliance. For this example, you should be checking “No” to all the radio buttons:

  • No, skill doesn’t allow users to make purchases or spend real money
  • No, skill does not collect personal information from users
  • No, skill does not target children under the age of 13

However, do note that some of these things (except for child targeting) may change as we progress in our Alexa Skill development capabilities.

If desired (or later required by more advanced capabilities) you may specify privacy policy and terms of use URLs.

If you’ve completed the above, you should be good to Save & Submit for Certification!

 

Wrap Up

This is a deceivingly involved process. You will note that neither in the previous article, nor this article, have we changed the original source code for the SpaceGeek / Weimaraner Facts Skill. We’ll cover this in more detail in the next article. Until next time, check out my journey in learning NoSQL and keep an eye out for more content soon!

 

The IN Statement: SQL Fundamentals

Howdy, budding SQL masters! It’s been a minute since the last SQL post! I’ve taken some time to devote to Alexa Skills, some other personal housekeeping, and adopting a dog with my wife!!

Last time we talked SQL, we learned the BETWEEN statement to hone in on the exact values we wanted for a SQL query. Prior to that, we looked at the LIMIT statement to get a small return data sample and also working with ORDER BY to take sorting and filtering into our own hands.

Today we’ll be working with the IN statement.

About the IN Statement

The IN SQL operator is a companion to the WHERE clause to see if a value matches any value in a list of values. Sounds something kind of like VLOOKUP’s, yeah? The syntax of an IN statement might look like:

value IN (value1, value2)

The expression in your SQL query will return true if the value(s) you’ve specified in the query match any value in the list you’re referencing.

Sub-queries: Using the IN Statement with SELECT

The list of values is not limited to a static number or list of strings. That is, you can be a bit more dynamic and free-flowing with your query by getting the value via a SELECT statement.

This is also known as a sub-query. To illustrate, the syntax might look like:

value IN (SELECT value FROM table)

NOT IN: Not Making Fetch Happen

The IN statement has a similar corollary as the BETWEEN statement- a NOT modifier. So, we can take the inverse of a statement. (Drawing on some experience in data analysis, this can just as, if not more useful than the original statement!)

value NOT IN (SELECT value FROM table)

 

Sample SQL Queries for the NOT IN Statement

Alright, let’s run some sample queries using the IN statement! Here’s our first go, working again with the ever-present dvdrental sample database. Below, we are selecting rental information for customers matching only a certain ID cohort (think perhaps loyalty group?), with a few columns and sorting by descending order for the return date:

SELECT customer_id,rental_id,return_date

FROM rental

WHERE customer_id IN (1,2)

ORDER BY return_date DESC;

Below, we see our results returned as intended!

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How about our corollary? If we want to add the NOT IN modifier, it’s as straightforward as you would imagine.

FROM rental

WHERE customer_id NOT IN (1,2)

ORDER BY return_date DESC;

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Above, we again receive the desired result. I believe we also get a lesson in the importance of clean data here, as blank values are presented first. Let’s try one more sample query, just for kicks. We’ll switch it up ever so slightly, now working with the payment table.

SELECT city_id,city,last_update

FROM city

WHERE country_id IN (44,82,60)

ORDER BY city ASC;

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Above, we’ve demonstrated that we don’t necessarily need to display a column we use in the query (country_id) and have sorted by city name in ascending order.

 

Wrap Up

So why the IN statement? At face value, it seems rather simplistic among SQL clauses we’ve explored thus far. Let’s consider the following.

The IN statement allows us to avoid a messy swath of values courtesy of BETWEEN (if we’re working with a proper large data set), or daisy chain list of a bunch of equals OR statements. Here’s another plus, it’s thought by some that pgAdmin / PostgreSQL will execute the IN query faster than the list of OR statements.

Alright, that’s it for today’s article. If you’re like me and need a quick refresh, revisit our page on Learning SQL that contains all the topics we’ve covered so far.

 

How to Build Your First Amazon Alexa Skill, Part 1 – The Skill Service

Introductory Disclaimer: AWS is changing, and changing fast! Between developing my first skill in mid-January 2017 and now going back to learn more / teach, quite a lot has changed in the AWS developer areas. All that to say is that I’ve already had to cobble screen shots together to make this article work, and the details could quickly become outdated. I don’t really intend to update this frequently, once I’ve completed my learnings. Apologies!

Welcome back, Amazon Alexa geeks! First, thanks for both your patience and kind feedback on the process of building your own Alexa and testing your DIY Alexa. Honestly, that was one of the hardest challenges I’ve had since first learning HTML / CSS coding back in college. (Thanks Raspian / Linux command line…)

Today, we’re getting back into actual Alexa skill development. We’ll be building your first (my second) Amazon Alexa skill for use on Echo and other devices.

Side note: I have previously developed an unremarkable skill, Silly Marketing Strategies, but I want to start fresh to:

  1. A) do it better, and,
  2. B) take a first stab at incorporating analytics capabilities into Alexa skills.

Without further ado, let’s get started with a conceptual overview to how Alexa skills work, and where developers (us!) play.

Quick Concept Introduction

First, let’s look at a simplified process of you using an Alexa skill:

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  • You’ll say something like, “Alexa, play Road Trip Country Playlist on Spotify”
  • The Echo, Fire TV, Raspberry Pi or other hardware takes in the audio and routes it into software/programs
  • The Alexa Skills Kit Interface employs speech recognition and natural language processing/understanding to convert your speech into text strings, then to code
  • The Skill service, facilitated by AWS Lambda processes the text strings against it’s suite of skills and programs, and outputs code,
  • Which is fed back through the programs to hardware and to a lovely voice response, something like, “Resuming your queue…”

That’s the front end experience. As a developer, we’ll hone in toward the “last” two parts of user experience. In that frame of reference, we start at the logic of our program, working “backwards” to handling user input, and the desired result.

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Setting up AWS Lambda

Are we there yet? Okay, for real this time, let’s hop into code…by pulling up 2 URLs and logging in:

  1. https://aws.amazon.com
  2. https://developer.amazon.com/public/solutions/alexa

In the AWS console, you should see a screen like the below. First, update your region (top right) to US East, N. Virgnia. Why, you might ask? It’s the only region (currently, Mar. 2017) that supports Alexa.

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Next you need to select Lambda from the list of AWS services. It should be readily available on your screen. Mine will likely look a bit different from having used it already. 🙂

If you’re a first-time Lambda user, you’ll likely see a welcome/splash screen that resembles the following:

You’ll have the option to select a blueprint (optional). You should be able to click next, or, there should be an Alexa skills kit SDK fact skill option you can select.

Moving along, when you launch Lambda for the first time, you’ll need to configure triggers. Below, you’ll want to select the Amazon Skills kit, and click, “Next”. Why are we configuring triggers for functions? Because our Alexa Skill is event-based, and only triggers when an event pertaining to it occurs.

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You should now land on a Configure Function screen. These are the baby steps to making a skill! Give the skill a name and description. We’ve used SpaceGeek as values below, since we’ll be using the SpaceGeek template at first. Also, always select Node.js 4.3 for Alexa Skill Development.

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Beneath the basic naming and settings is a Lambda function code section. Choose the “Upload a .ZIP file” option. Remember all the files we downloaded in our first article? You’ll need to go the SpaceGeek folder, src subfolder and zip the contents (shown below) and upload accordingly.

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(You can download the sample files again if needed from here.

Note: It’s March 2017, I started in Jan. 2017 and the original tree /Github URL has already been deprecated. Zoinks, it’s moving fast!)

After you’ve uploaded the file, you need to create a new role from templates (beneath the file upload you just completed.) Feel free to name the role whatever you like, but the important detail here is that you select the S3 object read-only permission option under the policy templates dropdown selection.

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Finally! You should be able to click, “Next” and clear this screen. You should see a review screen confirming the selections you’ve made. Click, “Create Function” and proceed! You should land within the Function itself. Since my new experience was already spent, here’s what the equivalent screen looks like, for Silly Marketing Strategies.

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Last thing you’ll want to do is copy the ARN into a text file, word document, etc. for safekeeping down the line. You’ll need it soon.

Wrap Up

Alright, we made a ton of progress in today’s article! I was hoping to make more progress, but the process of organizing, documenting, processing and writing is quite time consuming. It’s now 1 a.m. local time for me, and I need sleep for a long day at work tomorrow! We’ll be back very soon on how to work on the Skills Interface (utterances, logic, etc.) in more detail to publish your first skill! If you’re new or need a refresh, here’s our running list of articles on how to learn Amazon Alexa Skill development.

Update: Testing Your DIY Amazon Alexa / Echo Device (Raspberry Pi)

Hey there folks, happy weekend! Hope this post finds you well. This is a follow up to my previous post on how to make your own Amazon Alexa / Echo device from a Raspberry Pi.

First, an Apology for the Cliff Hanger

I left you hanging at the end of that post, and I’m very sorry about that. It was a Friday morning at almost 4 a.m., and I was ready for bed. So, here we are on the weekend! I’ve now had the chance to do some further validation and documentation in testing our DIY Amazon Alexa / Echo from a Raspberry Pi.

The samples I’ve provided aren’t super in depth, but serve as proof of concept.

Recap: Where We Left Off

Here’s where we were at the end of the last article:

The first terminal will set Alexa up to be listening on port 3000 (remember the local host URLs from earlier?) The second window deals with setting up a Java client and logging into Amazon with the Security profile we set up. Logging in and confirming will enable you to initiate the connection to Alexa, paving the way for the third terminal, which enables the wake word detection and actual running of the Alexa service. Woohoo! I’ll update with examples later.

I’ve booted up our trusty Raspberry Pi back up, and opened 3 command line terminals.

Preparing for Test

1. Companion Service

First item of business, is to run the companion service, first command line terminal. Type the below:

cd Desktop/alexa-avs-sample-app/samples/companion service && npm start

After returning the above line of code, successful output should end with, “Listening on Port 3000” and “Successfully retrieved registration code for xxxxxxx / xxxxxxx ”

Below, steps 1 & 2 combined since I was a bit slow on thinking to photograph in the moment. 🙂

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2. Java Client / Authorizing Device

The second piece for testing here is the Java client and authorizing the device with Amazon. (Remember the security profile setup from the previous How to Build Article?) In the second command line terminal, type the following:

cd Desktop/alexa-avs-sample-app/samples/javaclient && mvn exec:exec

A few things should happen here, outside of Matrix-like code waterfalls. First, a window prompting you to login to Amazon to enable the security profile for your device should appear. Second, after you click through to the browser (or paste URL into browser), you should see a log-in screen like the below. Enter your credentials, approve access, and close the window after you see a screen that displays the message, “device tokens ready”

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After you’ve completed the above steps, you should have a window (slightly hidden in the center, photo above) with a bearer token and a button to listen. At this point, I just ran a simple test saying, “hello” and Alexa said, “hello” back. We’re almost there!

3. Wake Word Detection / Connecting to AVS Client

The final piece is connecting to the AVS client and enabling wake word detection, which means we don’t have to press the “Listen” button every time we want to do something. Last piece of command line!

cd Desktop/alexa-avs-sample-app/samples/wakeWordAgent/src && ./wakeWordAgent -e kitt_ai

After the script runs, the last line of code output should read, “Connected to AVS Client”. You’re now ready to use Alexa.

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Testing!

Below is one of the quick tests I ran on Pi Alexa. Si

mple time check and request for a joke. Now we’re cooking with gas!

 

Wrap Up

Building an Alexa has been a very instructive process. I don’t know about you, but I’m ready for actual skill development now. Stay tuned as I recap the changes through my first Alexa skill, a remix of the Space Geek sample, and begin working through more advanced skills and concepts such as analytics integration. Cheers!

DSC_0005 Cover Photo by Zach Doty for Build Your Own Amazon Alexa x Echo from Raspberry Pi

How to Build Your Own Amazon Alexa with a Raspberry Pi

Howdy, it’s been a minute since my last post on Alexa Skill Development. I left us hanging, as I mentioned in one of my previous SQL posts, work craziness, sickness, and general life stuff happening imposed a brief, involuntary hiatus on writing.

Enough self talk to make future self feel better. Let’s build our own Amazon Alexa with a Raspberry Pi! What a step up from our previous articles. 🙂

But first! A couple of notes: This is NOT necessary for you to do in learning Alexa Skill Development. You can use a regular Echo instead of this expedition into Computer Homebrew 102. Also, I developed my first Alexa skill without an Echo or comparable device at all. One more thing, this is a long post that is both deep and wide ranging. Don’t say I didn’t warn you.

1. The Materials List

To get started, you’ll need a few things:

  1. Raspberry Pi, version 2 or later
  2. Power source
  3. Micro SD card (Recommended at least 8 gb in storage size)
  4. Speaker with a line-in 3.5mm cable (or headphones of similar line-in spec)
  5. USB microphone
  6. Keyboard and Mouse
  7. HDMI cable to connect to a monitor or TV
    1. Obviously, you need a monitor or TV. 🙂

 

A few notes on the Raspberry Pi: I recommend you get a pre-assembled kit, for time and convenience, if nothing else. I previously purchased from CanaKit on Amazon, and have been pleased with it. If, for some reason, you are building your own or need to reformat, the two articles below from RaspberryPi.org are simple, fast instructions to get you up to speed.

 

Formatting a MicroSD card 32 GB or less:

https://www.raspberrypi.org/documentation/installation/noobs.md

Downloading New Out of Box Software (NOOBS) for Raspberry Pi, in preparation of your first boot.

https://www.raspberrypi.org/downloads/noobs/

 

Okay, we’re going to proceed assuming that you’ve taken care of the above, and have successfully booted your Pi, connected all requisite hardware, connected to the internet, and so on. Below is where I’m at.

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2. Installing Other Utilities

Another note here, it is possible to SSH (read: a bit like Microsoft’s RDP remote desktop application, but command line style) your way into the Raspberry Pi. I will not be doing that. This may sound a bit silly, but I don’t have a multi-screen dock for my laptop (capped at 2), and I’m happy for the Pi and other monitor to be a standalone computer. (Perks of a wide desk.) Also, the Wi-Fi USB card I’m using is very slow at the moment. Also, an edit after I’ve written this post offline: Linux-esque command line work is a royal pain in the you-know-what. Remarkable computing has advanced to where it is today. More on Raspberry Pi intricacies later.

Enough of my discourse, let’s continue setting up our Raspberry Pi / DIY Alexa to-be. Task time.

Navigate to your Pi’s command line module.

  1. We’re going to update the GET. Type:
    1. sudo apt-get update (Pro tip: don’t misspell sudo as I’ve laughingly done on the first try.)
    2. In the new line created by default, type: clear and hit enter. This will clear your command line.

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3. Registering Your Raspberry Pi as an Alexa Voice Service Device Type

Alright, head to the Amazon Developer Portal and log in with your credentials.. (If you’ve followed along with previous posts, you have a login! If not, see this article on setting up an AWS account.)

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Once you’ve logged in, click on the Alexa navigation item, then click “Get Started”. You should land on a page that has a “Register Product Type” drop-down. Select Device and continue.

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You’ll be taken to a new screen / process to create a new device type. Choose and type your  device type ID and display name. For ease of process here, I’ve used the same value for device type ID and display name.

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Once you’ve selected your ID and name of choice, click next. Now we need to create a new security profile. Click the dropdown menu that reads, “Select Security Profile” and click, “Create New Profile”. If you’ve filled out all the fields properly, you should have the option to submit this device / product. Hooray! Below is what I see after I submit the new device.

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Create a Security Profile Name and Description of your choosing and click “Next”.

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You’ll now see a new screen with your created security profile. Below, you should see some tabs such as, “General”, “Web Settings”, “Android/Kindle Settings”, and so forth. Click on “Web Settings” and then click “Edit”.

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You should now be able to edit the “Allowed Origins” and “Allowed Return URLs” fields. Enter the following values into each of the fields, respectively:

1) https://localhost:3000

2) https://localhost:3000authresponse

Once you’ve entered the above values, click “Next”.

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Now we need to add some additional detail about our device type.

  • Upload an image (I used this one, they’re picky about sizing)
  • Choose a category (I selected “Other”)
  • Provide a short description to your pleasing
  • Select “No” for plans on making product available to general public
  • Select “No” for product directed to children

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Click “Next” to proceed. The next screen asks about applying for access to Amazon Music. I’m selecting “No” for the purposes of this exercise.

4. Enable Login With Amazon for your new Device / Product

Sweet! After you click, “Submit”, you should see the below. Now head over to the “Apps & Services” section, and select the “Login with Amazon” item, once the Apps & Services screen has loaded.

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From the drop-down menu of existing security profiles, select the profile we just created. You’ll need to enter a consent privacy notice URL and a consent logo image. Because we’re doing anything public facing, you can enter any URL you’d like here. For the image, I used the same image from the device creation process. Click “Save” and let’s keep moving.

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Upon a successful save, you should see a table with a column labeled “Oauth2 Credentials”. Click, “Show Client ID and Client Secret”, copy and save the information somewhere safe. Next stop, Raspberry Pi.

5. Install the Application on Your Raspberry Pi

Flip back over to your Raspberry Pi and type the following two bullet point texts as unique lines into command line.

  • cd Desktop
  • git clone https://github.com/alexa/alexa-avs-sample-app.git

It should take a minute or two to process, and you should see the below.

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Next, type the below point texts as unique lines into command line:

  • cd alexa-avs-sample-app/
  • nano automated_install.sh

After returning the two above lines, you should see something like the below. Remember what we entered in the Developer Console a few steps ago? You’ll need this information here. (Highlighted boxes.) Update from 2/25/2017: I actually had quite a bit of trouble with this step. Linux command line / text emulator is not my friend yet. The trouble I had here was making and saving my changes to the below. However, the program is surprisingly helpful! It will prompt you to verify credentials before install proceeds.

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After you’ve made the appropriate changes, command line language of CTRL + X should help you save the changes. Close out the command line window and re-open. Type the following bullet texts:

  • cd Desktop
  • cd alexa-avs-sample-app
  • . automated_install.sh

When prompted for the AVS + Raspberry Pi License and Agreement, obviously answer and/or “y” to proceed, and answer yes and appropriate and desired throughout the setup process. E.g., you’ll be asked about language preference, audio input settings, enabling wake word detection, and so forth. (It takes anywhere from 30 min to 1 hour.)

Once the install runs, it’s time to start the Alexa service!

6. Running the Alexa Service / Finishing Touches

To test and run the Alexa service, we need 3 command line terminals open. The command paths for these are at the end of the install. (As I type this, the latest install on my Pi is approaching 45 minutes, so I’ll have to give you the bare bones for now based on past tests and some generous documentation.

The first terminal will set Alexa up to be listening on port 3000 (remember the local host URLs from earlier?) The second window deals with setting up a Java client and logging into Amazon with the Security profile we set up. Logging in and confirming will enable you to initiate the connection to Alexa, paving the way for the third terminal, which enables the wake word detection and actual running of the Alexa service. Woohoo! I’ll update with examples later.

Update — 2/25/2017:

So, the whole process took a looooong time. At about 3 am of the night I wrote / finished this post, the Pi finally finished unpacking and installing everything. Below is our success confirmation! I’ll be testing this evening…

Wrap-Up

Goodness, what a ride, if you stuck it through the whole article. You could do this, or just get a darn Echo. After all this, I recommend you buy an Echo. 🙂

Other miscellaneous updates from 2/25/2107: By the time I got to the wrap up, it was 3:30 in the morning, yikes! I wasn’t feeling very descriptive, nor was I yesterday either. This was an incredibly long process that took several days from start to finish. Was it worth it? Yes. I’m still going to test the capabilities tonight and hopefully have some follow up’s in the coming days. Will I be primarily using an Echo moving forward? Yes.

The BETWEEN Statement: SQL Statement Fundamentals

Hey there, folks! Welcome back to our journey in learning SQL. Our last few of posts covered the ORDER BY clause, LIMIT statement and the COUNT function. (See full list of SQL tutorials here.)

Today, we’re going to cover the BETWEEN statement. This is the start of some deeper material. In addition to the BETWEEN statement, we’ll also soon be covering IN and LIKE statements.

 

About the BETWEEN Statement

The BETWEEN statement (rather, operator) is used to match a value against a specified range of values. Maybe we want to get transactions between a certain dollar amount.

For example, value BETWEEN low AND high;

More about the BETWEEN statement. If the value is greater than or equal to the low value and  less than or equal to the high value, the expression returns true, or vice versa. Also, the BETWEEN operator can be rewritten by using the greater than or equal to ( >=) or less than or equal to ( <=) operators as the following statement.

value >= low and value <= high;

One other way to think about the BETWEEN statement is that takes two WHERE statements and lumps them into one. Think back to the WHERE statement, as we would say first:

SELECT column1 FROM table WHERE column1 >= 2 AND column1 <= 7;

 

To BETWEEN or NOT BETWEEN

Conversely, you can extend the usage of the original BETWEEN operator to NOT BETWEEN. This is similar in concept, except working toward exclusion, instead of inclusion. So, if we want to check if a given value is outside of a range, we can use the NOT BETWEEN operator as below.

value NOT BETWEEN low AND high;

Again, similarly to the double WHERE statements, NOT BETWEEN simplifies the burden into a single statement. For sanity, we’ll skip the SELECT WHERE example.

 

Using BETWEEN in pgAdmin / PostgreSQL

Below, we’ve taken the BETWEEN statement for a road test on our address table.

SELECT address_id,address FROM address

WHERE address_id BETWEEN 10 AND 20;

2017-02-18-001-BETWEEN-SQL-Statement-Example

How sweet was that? Syonara, comparison operators. Conversely, if we convert the above query into a NOT BETWEEN operator, we should see the below statement return the following results.

SELECT address_id,address FROM address

WHERE address_id NOT BETWEEN 10 AND 20;

2017-02-18-002-NOT-BETWEEN-SQL-Statement-Example

Okay, that was cool. Let’s hold up for a quick second. What about non-integer columns, such as data? Caveat: there’s a lot more to data types than our humble example below. For the purposes of this article, we can take a YYYY-MM-DD date and place the values into strings.

SELECT rental_id,rental_date,inventory_id FROM rental

WHERE rental_date BETWEEN ‘2005-05-24’ AND ‘2005-05-27’;

2017-02-18-003-BETWEEN-Non-Integer-SQL-Statement-Example

Voila!

Wrap-Up

Alright, for those of you reading this later, it’s 2 a.m. on a Friday night / Saturday morning, and I’m about ready to call it a night. Sorry I’m not providing a better conclusion for you today. I’m excited to delve further into more complex SQL queries. Keep track of my shared journey of a beginner learning SQL. Cheers!

 

 

DSC_0163 Zach Doty Cover Photo for ORDER BY SQL Clause

ORDER BY Clause: SQL Statement Fundamentals

Welcome back to our SQL learning journey! It’s been a week and a half since my last post on using LIMIT. Work got crazy and I got the flu! 🙁 But we’re back in action. Today, we’ll delving deeper into SQL statements in PostgreSQL: ORDER BY.

Let’s jump in. Why would you need a statement that orders data? Whenever you query data from a table, PostgreSQL will by default return the rows in the order they were inserted into the table. (Read: not the order you want.)

To sort the result set from your SQL query, you can use the ORDER BY clause in the SELECT statement and specify a certain ascending or descending order.

Sample ORDER BY Clause Syntax

Here’s an example of the ORDER BY clause would look like within a SELECT statement.

SELECT column_1, column_2

FROM table_name

ORDER BY column_1 ASC / DESC;

Some important notes for the ORDER BY clause:

  • Specify the column you want to sort by with the ORDER BY clause
    • If you sort the results by multiple columns, use a comma to separate between the two columns
  • Use ASC to sort the results in ascending order
  • Use DESC to sort the results in descending order
  • Should you leave the ORDER BY clause blank, it will use ASC (ascending) by default

ORDER BY Clause Examples in SQL Statements

Alright, first up. We’ll do a basic SELECT statement, adding both ORDER BY and LIMIT clauses. Code and screen shot below. The query should select the first and last name columns from the customer table, ordered by last name ascending (A > Z), returning only the first 10 rows.

SELECT first_name,last_name  FROM customer

ORDER BY last_name ASC

LIMIT 10;

2017-02-16-001-ORDER-BY-SQL-Statement-Example

 

Let’s try another example. What if we want to do an advanced / multiple sort? Let’s try it out, and change it up ever so slightly from the first sample query.

SELECT first_name,last_name

FROM customer

ORDER BY first_name ASC,

last_name DESC;

2017-02-16-002-ORDER-BY-SQL-Statement-Example-Multiple

If we scroll down to the first set of duplicate first names, we’ll see the last name has been presented in descending order (Z > A).

More Details About the ORDER BY Clause

Did you know? In PostgreSQL, you can ORDER BY columns that aren’t explicitly selected within the SELECT statement? E.g. We could only select first and last name, but order by their address_id value. Interesting, yes? Important caveat, other SQL programs, such as MySQL, may not let you do this.

Below:

SELECT first_name FROM customer

ORDER BY last_name ASC;

2017-02-16-003-ORDER-BY-SQL-Statement-Example-Other-Sort

Wrap-Up

Thanks for joining me and hopefully you’ve learned the essentials for the ORDER BY clause. Feel free to check out the entire journey on how to learn SQL, thanks!

Getting Started with Alexa Development 02: Signing Up to Alexa Development Portal

Welcome back to our journey in learning how to program Amazon Alexa Skills via Echo voice search. In the previous article, we walked through the process of setting up an Amazon Web Services (AWS) account. Today, we’ll set up an account at the Alexa Development portal, a distinct entity from the AWS portal.

 

Without further ado, let’s jump in. Go to https://developer.amazon.com/public/solutions/alexa.

2017-02-03-001-Alexa-Developer-Home-Screen

You should land on something like the above screen. Click on the “Sign In” button, you can create a new account from this screen if you need.

Important Note: If you already have an Amazon.com account (regular old Amazon shopping account), use those credentials to log in.

Obviously, if you’re a returning Alexa Development Portal user, you can skip the account creation process shown below. If you’re creating a new account, you’ll need to fill out a screen that will likely resemble the below, and click “Save and Continue” when you’ve finished.

2017-02-03-002-Alexa-Developer-Account-Creation

Next, you should be presented with an App Distribution and Services Agreement screen. Be sure to give it a quick read. If you want to use the services, then you’ll need to agree by clicking save and continue. 🙂

The final registration step addresses payments and whether you plan to monetize the apps you develop. For the purposes of my usage, and this learning, I checked “No” to both options before proceeding.

2017-02-03-003-Alexa-Developer-Account-Creation-Monetization

Once you finish that step, you should find yourself in the Amazon Developer Console! Good thing we got the hard material out of the way first, huh?

This should wrap up a pretty quick introductory section for setups. Feel free to visit my previous article on getting set up with AWS, or go to my learning home page on how to start developing Alexa Skills. Thanks and see you at the next article!

bluebonnets Zach Doty cover photo for SQL COUNT Function

SQL Statement Fundamentals: The COUNT Function

 

Hello, hello, hello SQL fans! (Or gracious friends and family perusing the site. 🙂 ) The journey into learning SQL continues, and today we’ll cover the COUNT function. Jumping right into it, here’s our working definition of the SQL COUNT function:

The COUNT function should return the number of input rows that match a specific condition of a query.

Rather, this would appear to work similarly in concept to the COUNTIF(s) formula(s) in Excel.

COUNT Statement Syntax Examples

Here’s what a simple COUNT SQL statement might look like:

1. Basic COUNT (*) FROM SQL Statement

SELECT COUNT (*) FROM table;

Breaking it down a bit, the COUNT () function returns the number of rows returned by a SELECT clause. When you apply the COUNT () statement to the entire table, pgAdmin/PostgreSQL will scan the entire table in a sequential manner.

Additionally, you can specify a certain column count in your COUNT statement for better readability:

2. COUNT (column) FROM SQL Statement

SELECT COUNT(column) FROM table;

Similar to the COUNT(*) function, the COUNT(column) function returns the number of rows returned by a SELECT clause. However, if you have empty or NULL values, the COUNT function will not take those into account.

3. COUNT (DISTINCT column) FROM SQL Statement

If we do a bit of application from our past learnings, we can make a COUNT with DISTINCT SQL statement:

SELECT COUNT(DISTINCT column) FROM table;

Applying the COUNT SQL Function

Alright, so let’s work our way toward applying what we’ve learned. To start, let’s do the traditional probe of the table before diving in, to familiarize ourselves. Below, we’ve done a basic,

SELECT * FROM address;

2017-02-01-001-SELECT-ALL-Starting-SELECT-COUNT

As we get familiar with the table, we can scroll down and see this particular table has 605 rows in it. This will be a reference point as we continue.

Moving forward, we’ll execute a basic SELECT COUNT (*) FROM address; SQL query. Below, you’ll see a slightly different result was returned. Inst3ead of 605 rows, 603 was returned. At this point, kindly reference our note about empty / NULL  values being excluded from the COUNT function.

2017-02-01-002-SELECT-ALL-COUNT-1

We’ve established a general proof of concept for the SELECT COUNT statement, considering the reduced load on the server and yourself, for a quick count. Let’s now try calling specific columns. In our first exploration of the address table, we saw a number of columns, including the district. Let’s say we want to get a count for how many districts/states our customer base covers.

2017-02-01-003-SELECT-COUNT-DISTINCT-1

Above, a count of 378 distinct district values has been returned. Wow, what coverage!

A quick aside for future usage, you can also nest the column reference in its own set of parentheses, as shown and returned below.

2017-02-01-004-SELECT-COUNT-DISTINCT-Nested

Wrap-Up

There you have it! We’ve learned a bit about the COUNT function, what it does and how to use it. It will likely come in handy for future articles, particularly when we delve into group-by excercises. If you missed it, here’s the previous article on learning how to use SELECT WHERE and another recent article on learning how to use SELECT DISTINCT. Also, to start from the beginning, here’s my running list of articles on how to learn SQL. Cheers!