XBee Wi-Fi Cloud Kit

The XBee Wi-Fi Cloud Kit helps users quickly connect XBee Wi-Fi enabled devices to the Internet of Things. This is the source code for the web application for the XBee Wi-Fi Cloud Kit. This source has been contributed by Digi International.

The web application allows the user to quickly create a dashboard of widgets to communicate with and control their XBee Wi-Fi Cloud Kit.
With this source code, you can run your own instance of the application in Heroku, and customize it to your needs, including creating new types of widgets and extending the application's functionality.

Requirements

This application should run in Windows, Linux and Mac OS X, provided the necessary programs are installed. These are:

Installing node.js will also install NPM, node.js's package manager. Using NPM, install Grunt and Bower:

$ npm install -g grunt-cli
$ npm install -g bower

Install pip, the Python package manager, to handle the installation of the application's Python dependencies.

Installation ------------s

Once you have checked out the source code from Git, navigate to the root directory of the code and run

$ npm install
$ bower install
$ grunt heroku:production

to install all Node modules required for developing the front-end application. This installation process will also use Bower to download the necessary front-end dependencies, and use Grunt to build the code.

For Windows machines only:

Follow the directions for full setup of Python on Windows including setup of your PATH environment variable, ez_setup.py and get-pip.py:

http://docs.python-guide.org/en/latest/starting/install/win/

Download and install gevent-0.13.8 for Python 2.7. Use gevent-0.13.8.win32-py2.7.msi from gevent.

Download and install psycopg2 for Python 2.7. Use psycopg2-2.5.1.win32-py2.7-pg9.2.4-release.exe from win-psycopg.

You must have a C compiler installed so that pip can build some of the required packages, typically this means you need Microsoft Visual Studio Express for C/C++ from the Microsoft Downloads site. Python 2.7 was built with Microsoft Visual Studio 2008, so if you do not have it, use 2010 and run:

C:\set VS90COMNTOOLS=%VS100COMNTOOLS%

Finally, run

C:\pip install -r requirements.WINDOWS.txt

to install the Python module dependencies needed for the application. Note this is the step that requires the C compiler. If you see the error "Unable to find vcvarsall.bat", then setup.py cannot locate your C compiler environment.

For Linux and Mac:

Run C:\ pip install -r requirements.txt

to install the Python module dependencies needed for the application.

App setup for Heroku

Heroku setup

Deploying a version of this application for your own use requires a Heroku account and the Heroku command line toolbelt.

Create a new Heroku app
```
 $ heroku create *appname*
```

Configure the new app to use multi-buildpacks (NodeJS & python in our case)

 $ heroku config:add BUILDPACK_URL=https://github.com/ddollar/heroku-buildpack-multi.git

Deploy the application code to Heroku
```
 $ git push heroku master
```
Provision the database for the app
```
 $ heroku run python manage.py syncdb
```

Setup to run app locally:

Run the grunt build
```
 $ grunt build
```
Provision the database
```
 $ python manage.py syncdb
```
Start the back-end server
```
 $ foreman start
```

foreman should be included with the Heroku Toolbelt heroku_dev: http://toolbelt.herokuapp.com/

XBee Wi-Fi Cloud Kit (Front-end)

To enable more rapid development, the front-end application can be easily hosted on a local computer. This front-end shell will communicate with the back-end server which has been previously deployed to Heroku.

Getting started

If you followed the steps in 'Installation' above, you should be ready to develop and build the front-end source code. Running npm install should have automatically run bower install, which will download the dependencies of the application (Bootstrap, jQuery, etc). Check that bower install was run by examining the contents of the vendor/ directory; if it does not contain such subdirectories as bootstrap, raphael, and angular, you will need to run the bower install command again.

Run grunt build to gather all the necessary files into the build/ directory and run unit tests. Run grunt build-notest to gather the files without running unit tests.

Finally, start the mock back-end server with

$ node server.js build <heroku_app_name>

and open your browser to http://localhost:3000. This server allows the front-end application to run on your local machine without running into cross-site scripting errors. The server simply pipes requests and responses to and from the RESTful API of the your Heroku instance. The command

$ PORT=9000 node server.js build <heroku_app_name>

will run the local server at a different port, if this is necessary or desired.

Note: You may choose to run the Django back-end server locally, rather than use the mock Node server to forward requests to a Heroku instance. See "Setup to run app locally" above for more information on how to do so.

Application structure

The application front-end is built off of Josh David Miller's ng-boilerplate project template.

Widgets

Widgets in the /src/app/widgets are considered "built-in" widgets. Additional widgets should be placed in /src/common/widgets. In general, widgets have a template, a controller, and a set of unit tests. Most widgets with a heavy UI component have their UI abstracted into a directive in the /src/common/directives folder. Generally, a widget's controller should be responsible for handling data updates, while the directive should be responsible for how the UI responds to those updates. The widget's template usually just has a single HTML element that instantiates the proper directive.

Services

Services in the /src/app/services/ directory are accessible by all parts of the application, and are useful for calculations and data that need to be accessible in multiple places. Creating a new widget generally won't involve creating a new service.

Controllers

Most controllers in the application are paired with their respective templates. Again, controllers are used to handle what application logic should occur when data is received either from the device or from user input.

Directives

Directives should control how the application UI reacts to user input or new data from the device. Directives for widget UI elements exist in /src/common/directives. Directives for different pages of the application (such as widget_settings) exist with the other code in their respective page's directory.

Unit Tests

Jasmine unit tests are differentiated by ending in .spec.js. The build system is able to differentiate unit tests from application files in this manner, which allows unit tests to exist right next to the tested code. Theoretically, all application code should have a unit test.

Widgets

Dashboard widgets are loaded from the back-end server via the /api/dashboards API. This is an example of a simple dashboard widget model:

{
    device: "00000000-00000000-00409DFF-FF111111",
    id: "widget_1234567",
    type: "switch",
    label: "Switch #1",
    sets: "DIO/3"
}

This widget model is used by the Cloud Kit application to generate a switch widget, labeled "Switch #1", which can be used to set the state of DIO3 on the device 00000000-00000000-00409DFF-FF111111.

The precise fields required on a widget model will vary depending on the type specified, but every widget must specify the following four fields:

id: string used to uniquely identify the widget
device: ID of the device this widget is associated with (specifically, this device ID is used in conjunction with any stream/pin settings to map input and output to/from the correct device)
type: widget type key, specifying what type of widget to render
label: string label to display at the top of the widget

See Widget Settings API for more details on widget settings.

Built-In Widget Types

The XBee Wi-Fi Cloud Kit application is designed to be extensible, and to make it very easy for the user to create their own custom widget types. We have, however, provided a small set of built-in, generic widgets, to provide insight into widget design and as a starting point for your dashboard.

The following widget types are provided with the Cloud Kit application:

Gauge Widget (gauge): draws a circular, speedometer-like gauge, to render the value of a datastream between a low and high value. See JustGage
- "Units" (units): String label for gauge to display the units of the values
- "Input Transform" (transform): See data transforms
- "Low value" (low): Number value, the low end of the gauge
- "High value" (high): Number value, the high end of the gauge. Must be greater than the low value
Line Graph Widget (line-graph): draws data in a chronological line graph. See FlotCharts
- "Input Transform" (transform): See data transforms
- "Color" (color): the color used for the dots and lines in the chart. Must be a valid CSS color (hex, RGB, or name)
- "Timespan" (timespan): the range of time, in seconds, to display in the graph
- "X-axis tick size" (ticksize): the spacing, in seconds, between ticks/lines drawn along the X-axis of the chart
Progress Bar Widgets (progress/progress-vertical): represents data values in a progress-bar view. Widget settings allow you to set the low and high values for the bar. Vertical and horizontal versions of the widget exist.
- "Input Transform" (transform): see data transforms
- "Low value" (low): low-end value for the progress bar
- "High value" (high): high-end value for the progress bar
Serial Data Widget (serial): presents an view for interacting with the serial port (UART) of the Cloud Kit board. Text sent to the board appears in blue and data received from the board appears in red
- This widget has no custom options
Slider Widget (slider): allows the user to drag a slider to choose a value to set down to the device. See jQuery UI docs
- "PWM Output" (pwm): dropdown menu to select the PWM output to write to
- "Low value" (low): low-end value for the slider
- "High value" (high): high-end value for the slider
- "Step Size" (step): slider step size (spacing between 'snaps') - default 1
Switch Widget (switch): presents a flip-switch widget to toggle values on/off
- "Invert Values" (invert): checkbox - if checked, the switch moving to "On" sends a 0 to the device, and "Off" sends a 1
- "Read-Only Switch" (read_only): checkbox - if checked, the switch will only represent the data stream value last received from the server, i.e. it will not be interactive
Tilt Widget (tilt): Creates a two-dimensional display which represents the output of the acellerometer in the kit, similar to a two-dimensional bubble level.
- "X-Axis Stream" (stream_x): dropdown menu to select the data stream represented on the X axis of the widget
- "Y-Axis Stream" (stream_y): dropdown menu to select the data stream represented on the Y axis of the widget
Timeout Slider Widget (timeout): Allows the timeout to be changed for components of the kit which require one, such as the buzzer.
- "Setting" (setting): dropdown menu to select the XBee module timeout setting that this widget will write to
- "Low value" (low): the low-end value of the slider (see Slider Widget)
- "High value" (high): the high-end value of the slider (see Slider Widget)
- "Step Size" (step): slider step size (see Slider Widget)

Creating Your Own Widgets

The XBee Wi-Fi Cloud Kit allows you to create your own widget types from scratch. To start, open a command line and run grunt widget.

<u>Running "widget" task</u>
Widget type (e.g. led): *led*
Type description (e.g. LED Widget): *LED Widget*
Created new widget definition in /home/mike/xbeewifi/src/common/widgets/ledCustomWidget
The widget type key is: led-custom
The description of the widget is: LED Widget

After running this command and inputting the necessary information, Grunt will generate the files for the new widget in /src/common/widgets (the exact path can be found in Grunt's output). You can edit the widget template and directive files there, re-build the application, and you will see the new widget type appear in the widget type dropdown menu on the Add Widget page.

## Widget Settings API

User-configurable settings for widgets are defined within each widget type's "registry specification" (the object passed into the call to widgetRegistry.put at the bottom of the widget's associated run block). These settings are built on the Revalidator API.

The following is an example of a basic widget setting definition:

{
  key: "example",
  label: "My Example Setting",
  type: "string",
  required: false,
  "default": "Hello"
}

key: a unique name/key for this setting; used to identify this setting in a widget's JSON representation, and for creating the widget settings form
label: a string used to label the form input associated with this setting on the widget settings form
type: used by Revalidator to check the data type of the setting
required: used by Revalidator to specify if this setting must be specified in the widget's JSON representation
default: used by the Cloud Kit to auto-populate this setting if required is false and no value is specified

(Note: the word 'default' MUST be placed in quotes. If not, older versions of IE will raise an error because 'default' is a reserved keyword.)

Widget Settings Formats

By default, widget settings will be rendered (displayed) on the widget settings page as basic text input fields. The type of input field is determined by the type attribute set in the settings object:

string: a basic text input, suitable for names and titles.
integer or number: an HTML <input type="number">, which will display a number-picker on Chrome and other browsers supporting this feature. (Other browsers will just display a text input).
boolean: a checkbox

In addition to these types of form elements, setting the form attribute in the widget setting object will alter how the input is displayed. These formats allow for more semantic form elements and more useful validation. The available options are:

color: a text input field, with a small box next to it. Input in the field must be a valid hex or rgb color specification, or match a name provided by jQuery Color. Valid colors will be displayed in the square; invalid colors will replace the square with a red crossed-out circle.
stream: a dropdown menu, presenting all possible data streams served up by the XBee Wi-Fi device
pin: a dropdown menu, presenting all possible streams/settings which can be written out to
pwm: a dropdown menu, presenting all PWM outputs available
timeout: a dropdown menu, presenting all XBee module settings corresponding to timeouts for pins

As an example, the following widget settings object

{
    key: "max",
    label: "Max Value",
    type: "integer",
    required: "false",
    "default": 30,
}

would create a form element similar to the one below:

Max Value:

Data Transforms

As noted in the Built-in Widget Types section, multiple widgets have a transform setting. This setting allows incoming data to be processed with an expression for display. The transform field is implemented using Angular.js's $eval function. This function will only evaluate basic Angular expressions without side affects, so one doesn't have to worry about users inserting malicious code into the application.

For instance, imagine a temperature sensor that reported a number between 0 (corresponding to -40 degrees Fahrenheit) and 1023 (corresponding to 140 degrees Fahrenheit). If a user wished to display this on a gauge widget as a meaningful value in Fahrenheit as opposed to the less useful binary representation, they could insert:

    x * (180/1024) - 40

in the Transform widget settings page. x in this expression is the value of the incoming data. To round this to the nearest whole number, the expression can be put through an Angular filter:

    x * (180/1024) - 40 | number:0

Here number:0 means "show as a number with 0 decimal places." Note that because this field doesn't evaluate real JavaScript,

    Math.round((x*180/1024)-40)

will not work correctly.

XBee Wi-Fi Cloud Kit (Back-end)

The application backend is written in Python, using the Django web framework. Most users looking to extend the dashboard with new widgets should have no need to modify this code. However, advanced users may wish to extend the API with new functionality or do local debugging alongside frontend changes.

The backend was designed to be relatively light-weight, largly wrapping existing Device Cloud Web Services for use by the frontend. Users looking to extend or modify the API should first familizarize themselves with the Device Cloud features and API (documentation available here. Between these APIs and the frontend, the backend layer adds some simple persistence for dashboards, user authentication and session handling, and a channel for new data from Device Cloud to travel through down to the frontend client over a WebSocket connection.

Getting started on Heroku

As part of the application setup, a number of configuration related environment variables are checked (see settings.py).

The following are required to run the application:

DATABASE_URL: Should be set automatically by heroku during initial deployment, as part of the postgres addon. If not, once the Heroku Postgres (or other db layer) addon is attached, this variable can by set by running
```
  heroku pg:promote <FULL_DB_URL>
```

See Heroku Documentation for more details

The following should be used to set once before deployment

Secret, unique security keys and credentials for your app:

DJANGO_SECRET_KEY: Random 50 character string. Randomly generated if not found.
AES_CRYPTO_KEY_HEX: Random 16 Bytes, represented as string of 32 hex characters. Used for extra encrypting of various things. Randomly generated if not found.

The following are used to customize the basic authentication crdentials used by Device Cloud when pushing monitor events to the server:

DEVICE_CLOUD_MONITOR_AUTH_USER: Username. Defaults to "change" if not found.
DEVICE_CLOUD_MONITOR_AUTH_PASS: Password. Defaults to "me" if not found.

The following are useful for debugging and local development, and may be changed at any time:

DJANGO_DEBUG: Used to run Django in debug mode (see documentation)
DJANGO_LOCAL_DEV: will make Django to use a local sqlite3 file instead of trying to connect to DATABASE_URL

Exploring the API

The Backend incorporates an interactive API explorer which can be used to browse the API resources and try out the calls made by the frontend. To get started, navigate to /api from the root of the site (ex https://xbeewifi.herokuapp.com/api)

Much of the API is locked down to only authenticated users. If you are not already logged in via the main site, you may login/logout via a link in the upper-right corner of the page, using your Device Cloud credentials and selecting the corresponding cloud server. Attempts to access most resources while not authenticated will return a 403-Forbidden error.

One logged in, navigate around via the url's in each response. Each view contains a description and other documentation related to that resource.

Application structure

The application backend code is structured as a Django project containing a number of django apps and plugins

Essential 3rd party packages

A full list of dependencies can be found in requirements.txt. To install (assuming python and pip are installed), simply run (VirtualEnv recommended)

    pip install -r requirements.txt

Django

The main web framework

Django Rest Framework

The app makes heavy use of the Django Rest Framework to define and implement the API, handle authentication, and provide the browsable interface

Gevent-socketio

Python implmentation of Socket.IO to provide real-time communication between browser and server

dj-static

Used to serve static files when running on the Heroku platform

Device Cloud Layer

Django extensions to support Device Cloud user models, authentication, and wrappers around web services can be found under xbeewifiapp\libs\digi

Views

Url routing to views is done in xbeewifiapp\urls.py. Most view code is located in xbeewifiapp\apps\dashboard\views.py. Note that most views will use the default REST framework settings for permissions and authentication unless annotated otherwise.

Data Flow

Information is retrieved from Device Cloud through a combination of querying and recieving push events. Most of the views defined in the API will perform an equivalent query against Device Cloud web services.

However, to facilitate real-time updates of sensor information, the application creates two Device Cloud Monitors - one for device data (DataStreams), the other for device connectivity status (DeviceCore). These monitors will be atuomatically created as needed once under the account of each logged in user, and re-used on subsequent logins. NOTE: monitors are created pointing to the address that users see when interacting with your site. If the application is accessable via multiple routes or urls, it may lead to duplicate monitors created under the same user. Note too that monitors won't be created for urls such as localhost.

Running locally

Local development is relatively simple to get started with. Users have a few options, see the file Procfile for some possibilities, users may wish to emulate the Heroku environment by running with Foreman

  foreman run

Or in the simplest case, With dependencies installed via pip, simply run Django directly, setting the debug variables DJANGO_DEBUG=True and DJANGO_LOCAL_DEV=True

  python manage.py runserver_socketio "0.0.0.0:$PORT"

Note: users running the app for the first time will still need to provision the local database (defined in settings.py or via DATABASE_URL environment variable)

  python manage.py syncdb

Running on Heroku

Addons

When the addon is deployed on the Heroku platform, there are a number of addons users may find useful for monitoring and debug purposes. These may be attached to your app via the Heroku Addons Page, and have free tiers suitable for development use:

Heroku Scheduler: If your application will be supporting many users, it may be necessary to clean up old sessions periodically. A Django command to do this can be scheduled daily by adding the task python manage.py clearsessions
New Relic: Useful for monitoring performance characteristics and availablility of the application. NOTE: when running with New Relic agent, a different command is used in the Procfile
Papertrail: Log management, archive, and search

License

This Source Code Form is subject to the terms of the Mozilla Public License, v. 2.0. If a copy of the MPL was not distributed with this file, You can obtain one at http://mozilla.org/MPL/2.0/.

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