Copying Event in Open Event API Server

The Event Copy feature of Open Event API Server provides the ability to create a xerox copy of event copies with just one API call. This feature creates the complete copy of event by copying the related objects as well like tracks, sponsors, micro-locations, etc. This API is based on the simple method where an object is first removed is from current DB session and then applied make_transient. Next step is to remove the unique identifying columns like “id”, “identifier” and generating the new identifier and saving the new record. The process seems simple but becomes a little complex when you have to generate copies of media files associated and copies of related multiple objects ensuring no orders, attendees, access_codes relations are copied.

Initial Step

The first thing to copy the event is first to get the event object and all related objects first

if view_kwargs.get('identifier').isdigit():
   identifier = 'id'

event = safe_query(db, Event, identifier, view_kwargs['identifier'], 'event_'+identifier)

Next thing is to get all related objects to this event.

Creating the new event

After removing the current event object from “db.session”, It is required to remove “id” attribute and regenerate “identifier” of the event.

db.session.expunge(event)  # expunge the object from session
make_transient(event)
delattr(event, 'id')
event.identifier = get_new_event_identifier()
db.session.add(event)
db.session.commit()

Updating related object with new event

The new event created has new “id” and “identifier”. This new “id” is added into foreign keys columns of the related object thus providing a relationship with the new event created.

for ticket in tickets:
   ticket_id = ticket.id
   db.session.expunge(ticket)  # expunge the object from session
   make_transient(ticket)
   ticket.event_id = event.id
   delattr(ticket, 'id')
   db.session.add(ticket)
   db.session.commit()

Finishing up

The last step of Updating related objects is repeated for all related objects to create the copy. Thus a new event is created with all related objects copied with the single endpoint.

References

How to clone a sqlalchemy object
https://stackoverflow.com/questions/28871406/how-to-clone-a-sqlalchemy-db-object-with-new-primary-key

Reset password in Open Event API Server

The addition of reset password API in the Open Event API Server enables the user to send a forgot password request to the server so that user can reset the password. Reset Password API is a two step process. The first endpoint allows you to request a token to reset the password and this token is sent to the user via email. The second process is making a PATCH request with the token and new password to set the new password on user’s account.

Creating a Reset token

This endpoint is not JSON spec based API. A reset token is simply a hash of random bits which is stored in a specific column of user’s table.

hash_ = random.getrandbits(128)
self.reset_password = str(hash_)

Once the user completed the resetting of the password using the specific token, the old token is flushed and the new token is generated. These tokens are all one time use only.

Requesting a Token

A token can be requested on a specific endpoint  POST /v1/auth/reset-password
The token with the direct link will be sent to registered email.

link = make_frontend_url('/reset-password', {'token': user.reset_password})
send_email_with_action(user, PASSWORD_RESET,     
                       app_name=get_settings()['app_name'], link=link)

Flow with frontend

The flow is broken into 2 steps with front end is serving to the backend. The user when click on forget password will be redirected to reset password page in the front end which will call the API endpoint in the backend with an email to send the token. The email received will contain the link for the front end URL which when clicked will redirect the user to the front end page of providing the new password. The new password entered with the token will be sent to API server by the front end and reset password will complete.

Updating Password

Once clicked on the link in the email, the user will be asked to provide the new password. This password will be sent to the endpoint PATCH /v1/auth/reset-password. The body will receive the token and the new password to update. The user will be identified using the token and password is updated for the respective user.

try:
   user = User.query.filter_by(reset_password=token).one()
except NoResultFound:
   return abort(
       make_response(jsonify(error="User not found"), 404)
   )
else:
   user.password = password
   save_to_db(user)

References

  1. Understand Self-service reset password
    https://en.wikipedia.org/wiki/Self-service_password_reset
  2. Python – getrandbits()
    https://docs.python.org/2/library/random.html

Post Payment Charging in Open Event API Server

Order flow in Open Event API Server follows very simple process. On successfully creating a order through API server the user receives the payment-url. API server out of the box provides support for two payment gateways, stripe and paypal.
The process followed is very simple, on creating the order you will receive the payment-url. The frontend will complete the payment through that url and on completion it will hit the specific endpoint which will confirm the payment and update the order status.

Getting the payment-url

Payment Url will be sent on successfully creating the order. There are three type of payment-modes which can be provided to Order API on creating order. The three payment modes are “free”, “stripe” and “paypal”. To get the payment-url just send the payment mode as stripe or paypal.

POST Payment

After payment processing through frontend, the charges endpoint will be called so that payment verification can be done on the server end.

POST /v1/orders/<identifier>/charge

This endpoint receives the stripe token if the payment mode is stripe else no token is required to process payment for paypal.
The response will have the order details on successful verification.

Implementation

The implementation of charging is based on the custom data layer in Orga Server. The custom layer overrides the Base data layer and provide the custom implementation to “create_object” method thus, not using Alchemy layer.

def create_object(self, data, view_kwargs):
   order = Order.query.filter_by(id=view_kwargs['id']).first()
   if order.payment_mode == 'stripe':
       if data.get('stripe') is None:
           raise UnprocessableEntity({'source': ''}, "stripe token is missing")
       success, response = TicketingManager.charge_stripe_order_payment(order, data['stripe'])
       if not success:
           raise UnprocessableEntity({'source': 'stripe_token_id'}, response)

   elif order.payment_mode == 'paypal':
       success, response = TicketingManager.charge_paypal_order_payment(order)
       if not success:
           raise UnprocessableEntity({'source': ''}, response)
   return order

With the resource class as

class ChargeList(ResourceList):
   methods = ['POST', ]
   schema = ChargeSchema

   data_layer = {
       'class': ChargesLayer,
       'session': db.session
   }

Resources

  1. Paypal Payments API
    https://developer.paypal.com/docs/api/payments/
  2. Flask-json-api custom layer docs
    http://flask-rest-jsonapi.readthedocs.io/en/latest/data_layer.html#custom-data-layer
  3. Stripe Payments API
    https://stripe.com/docs/charges

Implementing Users API to Display the Users at Admin Route in Open Event Frontend

This article will illustrate how the users are displayed and updated on the /admin/users route, their roles, user links etc. using the users API in Open Event Frontend. The primary end point of Open Event API with which we are concerned with for fetching the users is

GET /v1/users

First, we need to create a model for the user, which will have the fields corresponding to the API, so we proceed with the ember CLI command:

ember g model user

Next, we need to define the model according to the requirements. The model needs to extend the base model class. As a user can have multiple notifications, orders and  sessions etc. so we have to use ember data relationships “hasMany”. Hence, the model will have the following format.

import ModelBase from 'open-event-frontend/models/base';
import { hasMany } from 'ember-data/relationships';

export default ModelBase.extend({
  email        : attr('string'),
  password     : attr('string'),
  isVerified   : attr('boolean', { readOnly: true }),
  isSuperAdmin : attr('boolean', { readOnly: true }),
  isAdmin      : attr('boolean', { readOnly: true }),
  firstName : attr('string'),
  lastName  : attr('string')
});

The complete code for the model can be seen here

Now, we need to load the data from the API using the above model, so we will send a GET request to the API to fetch the users. This can be easily achieved using this.

return this.get('store').query('user', {'page[size]': 10 });

The above line is querying for the users from the store which is place where cache of all of the records that have been loaded by our application is there. If a route asks for a record, the store can return it immediately if it is there in the cache and we want to display only 10 users in a page so defined how many number of users has to be loaded at a time.

Now we need to filter the users based on whether they are active or they have deleted their accounts. For this purpose, we need to pass filter to the query which will tell what type of users to be loaded at once.

The next thing we need to do is to display the above data fetched from the API into an ember table. Ember table helps in allowing us to render very large data sets by only rendering the rows that are being displayed. For this, we defined a controller class which will help in letting the table know what all columns will be required to display and the attribute values they correspond in the API. We can also define the template for each column. The code for the controller class looks like this.

import Ember from 'ember';

const { Controller } = Ember;
export default Controller.extend({
  columns: [
    {
      propertyName     : 'first-name',
      title            : 'Name',
      disableSorting   : true,
      disableFiltering : true
    },
    {
      propertyName     : 'email',
      title            : 'Email',
      disableSorting   : true,
      disableFiltering : true
     },
     {
      propertyName     : 'last-accessed-at',
      title            : 'Last Accessed',
      template         : 'components/ui-table/cell/admin/users/cell-last-accessed-at',
      disableSorting   : true,
      disableFiltering : true
    }
   ]
});

In the above code, we can see a field called ‘disableSorting’ which is true if we don’t want to sort the table based on that column. Since we want the last-accessed-at column to be customized, so we have separately added a template for the column which will ensure how it will look in the column. The complete code for the other columns which are there in table apart from these can be found here.

Now to display the ember table we will write the following code.

{{events/events-table columns=columns data=model
    useNumericPagination=true
    showGlobalFilter=true
    showPageSize=true
}}

In the above piece of code, we are calling the same ember table as we used in case of events to reduce the code duplication. We are passing the columns and data in the table which remains unique to the table. Next, we are ensuring that our page shows the amount of data we’re fetching at one go, allows the filtering the table based on the columns.

The UI of the users page for the above code snippets look like this.

Fig 1: The UI of the users table under admin/users route

The entire code for implementing the users API can be seen here.

To conclude, this is how we efficiently fetched the users using the Open-Event-Orga users API, ensuring that there is no unnecessary API call to fetch the data and no code duplication using the same ember table again.

Resources:

Configuring Youtube Scraper with Search Endpoint in Loklak Server

Youtube Scraper is one of the interesting web scrapers of Loklak Server with unique implementation of its data scraping and data key creation (using RDF). It couldn’t be accessed as it didn’t have any url endpoint. I configured it to use both as separate endpoint (api/youtubescraper) and search endpoint (/api/search.json).

Usage:

  1. YoutubeScraper Endpoint: /api/youtubescraperExample:http://api.loklak.org/api/youtubescraper?query=https://www.youtube.com/watch?v=xZ-m55K3FhQ&scraper=youtube
  2. SearchServlet Endpoint: /api/search.json

Example: http://api.loklak.org/api/search.json?query=https://www.youtube.com/watch?v=xZ-m55K3FhQ&scraper=youtube

The configurations added in Loklak Server are:-

1) Endpoint

We can access YoutubeScraper using endpoint /api/youtubescraper endpoint. Like other scrapers, I have used BaseScraper class as superclass for this functionality .

2) PrepareSearchUrl

The prepareSearchUrl method creates youtube search url that is used to scrape Youtube webpage. YoutubeScraper takes url as input. But youtube link could also be a shortened link. That is why, the video id is stored as query. This approach optimizes the scraper and adds the capability to add more scrapers to it.

Currently YoutubeScraper scrapes the video webpages of Youtube, but scrapers for search webpage and channel webpages can also be added.

URIBuilder url = null;
String midUrl = "search/";
    try {
       switch(type) {
           case "search":
               midUrl = "search/";
               url = new URIBuilder(this.baseUrl + midUrl);
               url.addParameter("search_query", this.query);
               break;
           case "video":
               midUrl = "watch/";
               url = new URIBuilder(this.baseUrl + midUrl);
               url.addParameter("v", this.query);
               break;
           case "user":
               midUrl = "channel/";
               url = new URIBuilder(this.baseUrl + midUrl + this.query);
               break;
           default:
               url = new URIBuilder("");
               break;
       }
    } catch (URISyntaxException e) {
       DAO.log("Invalid Url: baseUrl = " + this.baseUrl + ", mid-URL = " + midUrl + "query = " + this.query + "type = " + type);
       return "";
    }

 

3) Get-Data-From-Connection

The getDataFromConnection method is used to fetch Bufferedreader object and input it to scrape method. In YoutubeScraper, this method has been overrided to prevent using default method implementation i.e. use type=all

@Override
public Post getDataFromConnection() throws IOException {
    String url = this.prepareSearchUrl(this.type);
    return getDataFromConnection(url, this.type);
}

 

4) Set scraper parameters input as get-parameters

The Map data-structure of get-parameters fetched by scraper fetches type and query. For URL, the video hash-code is separated from url and then used as query.

this.query = this.getExtraValue("query");
this.query = this.query.substring(this.query.length() - 11);

 

5) Scrape Method

Scrape method runs the different scraper methods (in YoutubeScraper, there is only one), iterate it using PostTimeline and wraps in Post object to the output. This simple function can improve flexibility of scraper to scrape different pages concurrently.

Post out = new Post(true);
Timeline2 postList = new Timeline2(this.order);
postList.addPost(this.parseVideo(br, type, url));
out.put("videos", postList.toArray());

 

References

Adding EditText With Google Input Option While Sharing In Phimpme App

In Phimpme Android App an user can share images on multiple platforms. While sharing we have also included caption option to enter description about the image. That caption can be entered by using keyboard as well Google Voice Input method. So in this post, I will be explaining how to add edittext with google voice input option.

Let’s get started

Step-1 Add EditText and Mic Button in layout file

<ImageView
       android:layout_width="20dp"
       android:id="@+id/button_mic"
       android:layout_height="20dp"
       android:background="?android:attr/selectableItemBackground"
       android:background="@drawable/ic_mic_black"
       android:scaleType="fitCenter" />
</RelativeLayout>


Caption Option in Share Activity in Phimpme

In Phimpme we have material design dialog box so right now I am using getTextInputDialogBox(). It will prompt the material design dialog box to enter caption to share image on multiple platform.

Step-2

Now we can get caption from edittext easily using the following code.

if (!captionText.isEmpty()) {
  caption = captionText;
  text_caption.setText(caption);
  captionEditText.setSelection(caption.length());
} else {
  caption = null;
  text_caption.setText(caption);
}


Step – 3 (Now add option Google Voice input option)

To use google input option I have added a global function in Utils class. To use that method just call that method with proper arguments.

public static void promptSpeechInput(Activity activity, int requestCode, View parentView, String promtMsg) {
  Intent intent = new Intent(RecognizerIntent.ACTION_RECOGNIZE_SPEECH);
  intent.putExtra(RecognizerIntent.EXTRA_LANGUAGE_MODEL, RecognizerIntent.LANGUAGE_MODEL_FREE_FORM);
  intent.putExtra(RecognizerIntent.EXTRA_LANGUAGE, Locale.getDefault());
  intent.putExtra(RecognizerIntent.EXTRA_PROMPT, promtMsg);
  try {
      activity.startActivityForResult(intent, requestCode);
  } catch (ActivityNotFoundException a) {
      SnackBarHandler.show(parentView,activity.getString(R.string.speech_not_supported));
  }

}

Just pass the request code to receive the speech text in onActvityResult() method and passs promt message which will be visible to user.

Step – 4 (Set text to caption )

if (requestCode == REQ_CODE_SPEECH_INPUT && data!=null){
       ArrayList<String> result = data.getStringArrayListExtra(RecognizerIntent.EXTRA_RESULTS);
       String voiceInput = result.get(0);
       text_caption.setText(voiceInput);
       caption = voiceInput;
       return;

}

Now we can set the text in caption string right now I am adding text in existing caption i.e If the user enter some text using edittext and after that user clicked on mic button then the extra text will be added after the previous text.

So this is how I have used Google voice input method and made the function globally.

Resources:

Including a Graph Component in the Remote Access Framework for PSLab

The remote-lab software of the pocket science lab enables users to access their devices remotely via the Internet. It includes an API server designed with Python Flask, and a web-app designed with EmberJS that allows users to access the API and carry out various tasks such as writing and executing Python scripts. In a series of blog posts, various aspects of this framework such as  remote execution of function strings, automatic deployment on various domains, creating and submitting python scripts which will be run on the remote server etc have already been explored.  This blog post deals with the inclusion of a graph component in the webapp that will be invoked when the user utilises the `plot` command in their scripts.

The JQPLOT library is being used for this purpose, and has been found to be quite lightweight and has a vast set of example code .

Task list for enabling the plotting feature
  • Add a plot method to the codeEvaluator module in the API server and allow access to it by adding it to the evalGlobals dictionary
  • Create an EmberJS component for handling plots
    • Create a named div in the template
    • Invoke the Jqplot initializer from the JS file and pass necessary arguments and data to the jqplot instance
  • Add a conditional statement to include the jqplot component whenever a plot subsection is present in the JSON object returned by the API server after executing a script
Adding a plot method to the API server

Thus far, in addition to the functions supported by the sciencelab.py instance of PSLab, users had access to print, print_, and button functions. We shall now add a plot function.

def plot(self,x,y,**kwargs):
self.generatedApp.append({"type":"plot","name":kwargs.get('name','myPlot'),"data":[np.array([x,y]).T.tolist()]})

 

The X,Y datasets provided by the user are stacked in pairs because jqplot requires [x,y] pairs . not separate datasets.

We also need to add this to evalGlobals, so we shall modify the __init__ routine slightly:

self.evalGlobals['plot']=self.plot
Building an Ember component for handling plots

First, well need to install jqplot:   bower install –save jqplot

And this must be followed by including the following files using app.import statements in ember-cli-build.js

  • bower_components/jqplot/jquery.jqplot.min.js
  • bower_components/jqplot/plugins/jqplot.cursor.js
  • bower_components/jqplot/plugins/jqplot.highlighter.js
  • bower_components/jqplot/plugins/jqplot.pointLabels.js
  • bower_components/jqplot/jquery.jqplot.min.css

In addition to the jqplot js and css files, we have also included a couple of plugins we shall use later.

Now we need to set up a new component : ember g component jqplot-graph

Our component will accept an object as an input argument. This object will contain the various configuration options for the plot

Add the following line in templates/components/jqplot-graph.hbs:

style="solid gray 1px;" id="{{data.name}}">

The JS file for this template must invoke the jqplot function in order to insert a complete plot into the previously defined <div> after it has been created. Therefore, the initialization routine must override the didInsertElement routine of the component.

components/jqplot-graph.js

import Ember from 'ember';

export default Ember.Component.extend({
  didInsertElement () {
    Ember.$.jqplot(this.data.name,this.data.data,{
        title: this.title,

        axes: {
          xaxis: {
            tickInterval: 1,
            rendererOptions: {
            minorTicks: 4
            }
          },
        },
        highlighter: {
          show: true, 
          showLabel: true, 

          tooltipAxes: 'xy',
          sizeAdjust: 9.5 , tooltipLocation : 'ne'
        },				  
        legend: {
          show: true,
          location: 'e',
          rendererOptions: {
            numberColumns: 1,
          }
        },
        cursor:{ 
          show: true,
          zoom:true, 
          showTooltip:false
          } 

    });
  }
});

Our component is now ready to be used , and we must make the necessary changes to user-home.hbs in order to include the plot component if the output JSON of a script executed on the server contains it.

The following excerpt from the results modal shows how the plot component can be inserted

{{#each codeResults as |element|}}
	{{#if (eq element.type 'text')}}
		{{element.value}}<br>
	{{/if}}
	{{#if (eq element.type 'plot')}}
		{{jqplot-graph data=element}}
	{{/if}}
{{/each}}            

Most of the other components such as buttons and spans have been removed for clarity. Note that the element object is passed to the jqplot-graph component as an argument so that the component may configure itself accordingly.

In conclusion, the following screencast shows what we have created. A simple plot command creates a fancy plot in the output which includes data point highlighting, and can be easily configured to do a lot more. In the next blog post we shall explore how to use this plot to create a persistent application such as an oscilloscope.

Resources:

 

Implementing Sessions API for the event in Open Event Frontend

This article will illustrate how the sessions are displayed and updated on the events/{event_id}/sessions route to display the sessions available for a particular event using the sessions API in Open Event Frontend. The primary end point of Open Event API with which we are concerned with for fetching the sessions is

GET /v1/sessions/{session_id}

First, we need to create a model for the sessions, which will have the fields corresponding to the API, so we proceed with the ember CLI command:

ember g model session

Next, we need to define the model according to the requirements. The model needs to extend the base model class. As a session can have multiple speakers and a session always belongs to an event, so we have to use ember data relationships “hasMany” and “belongsTo”. Hence, the model will have the following format.

import ModelBase from 'open-event-frontend/models/base';
import { belongsTo, hasMany } from 'ember-data/relationships';

export default ModelBase.extend({
  title         : attr('string'),
  subtitle      : attr('string'),

  speakers      : hasMany('speaker'),
  event         : belongsTo('event')
});

Complete code for the model can be seen here

Now, we need to load the data from the API using the above model, so we will send a GET request to the API to fetch the sessions corresponding to a particular event. This can be easily achieved using this.

return this.modelFor('events.view').query('sessions');

The above line is asking for getting the current model that is on the route events.view and query for the sessions property from that model.

Now we need to filter the sessions based on their sessions whether they have been accepted or confirmed or pending or rejected and display them on different pages. For this purpose, we need to pass filter and pages to the query which will tell what type and now of sessions to be loaded at once. Also, we need to display the speakers associated with session and event details. For this case, the above query will be formatted like this.

return this.modelFor('events.view').query('sessions', {
      include      : 'event,speakers',
    filter       : filterOptions,
      'page[size]' : 10
    });  

In the above query, the filterOptions are designed in such a way which check for what type of sessions user is querying for. The code can be found here.

The next thing we need to do is to display the above data fetched from the API into an ember table. For this, we need to have a controller class which will help in letting the table know what all columns will be required to display and the attribute values they correspond in the API. We can also define the template for each column. The code for the controller class looks like this.

export default Controller.extend({
  columns: [
    {
      propertyName   : 'state',
      title          : 'State',
      disableSorting : true,
      template       : 'components/ui-table/cell/events/view/sessions/cell-session-state'
    },
    {
      propertyName : 'title',
      title          : 'Title'
    },
    {
      propertyName    : 'speakers',
      template       : 'components/ui-table/cell/cell-speakers',
      title          : 'Speakers',
      disableSorting  : true
     }]
});

In the above code, we can see a field called ‘disableSorting’ which is true if we don’t want to sort the table based on that column. Since we want the state column to be customized, so we have separately added a template for the column which will ensure how it will look in the column. The complete code for the other columns which are there in table apart from the state, title and speakers can be found here.

Now to display the ember table we will write the following code.

{{events/events-table columns=columns data=model
    useNumericPagination=true
    showGlobalFilter=true
    showPageSize=true
}}
I

In the above piece of code, we are calling the same ember table as we used in case of events to reduce the code duplication. We are passing the columns and data in the table which remains unique to the table. Next, we are ensuring that our page shows the amount of data we’re fetching at one go, allows the filtering the table based on the columns.

The UI of the sessions page for the above code snippets look like this.

Fig 1: The UI of the session table under events/{event_id}/session route

The entire code for implementing the sessions API can be seen here.

To conclude, this is how we efficiently fetched the sessions details using the Open-Event-Orga sessions API, ensuring that there is no unnecessary API call to fetch the data and no code duplication using the same ember table again.

Resources:

Implementing SUSI Linux App as a Finite State Machine

SUSI Linux app provides access to SUSI on Linux distributions on desktop as well as hardware devices like Raspberry Pi. It is a headless client that can be used to interact to SUSI via voice only. As more and more features like multiple hotword detection support and wake button support was added to SUSI Linux, the code became complex to understand and manage. A system was needed to model the app after. Finite State Machine is a perfect approach for such system.

The Wikipedia definition of State Machine is

It is an abstract machine that can be in exactly one of a finite number of states at any given time. The FSM can change from one state to another in response to some external inputs; the change from one state to another is called a transition.”

This means that if you can model your app into a finite number of states, you may consider using the State Machine implementation.

State Machine implementation has following advantages:

  • Better control over the working of the app.
  • Improved Error handling by making an Error State to handle errors.
  • States work independently which helps to modularize code in a better form.

To begin with, we declare an abstract State class. This class declares all the common properties of a state and transition method.

from abc import ABC, abstractclassmethod
import logging

class State(ABC):
   def __init__(self, components):
       self.components = components
       self.allowedStateTransitions = {}

   @abstractclassmethod
   def on_enter(self, payload=None):
       pass

   @abstractclassmethod
   def on_exit(self):
       pass

   def transition(self, state, payload=None):
       if not self.__can_transition(state):
           logging.warning("Invalid transition to State{0}".format(state))
           return

       self.on_exit()
       state.on_enter(payload)

   def __can_transition(self, state):
       return state in self.allowedStateTransitions.values()

We declared the on_enter() and on_exit() abstract method. These methods are executed on the entering and exiting a state respectively. The task designated for the state can be performed in the on_enter() method and it can free up resources or stop listening to callbacks in the on_exit() method. The transition method is to transition between one state to another. In a state machine, a state can transition to one of the allowed states only. Thus, we check if the transition is allowed or not before continuing it. The on_enter() and transition() methods additionally accepts a payload argument. This can be used to transfer some data to the state from the previous state.

We also added the components property to the State. Components store the shared components that can be used across all the State and are needed to be initialized only once. We create a component class declaring all the components that are needed to be used by states.

class Components:

   def __init__(self):
       recognizer = Recognizer()
       recognizer.dynamic_energy_threshold = False
       recognizer.energy_threshold = 1000
       self.recognizer = recognizer
       self.microphone = Microphone()
       self.susi = susi
       self.config = json_config.connect('config.json')

       if self.config['hotword_engine'] == 'Snowboy':
           from main.hotword_engine import SnowboyDetector
           self.hotword_detector = SnowboyDetector()
       else:
           from main.hotword_engine import PocketSphinxDetector
           self.hotword_detector = PocketSphinxDetector()

       if self.config['wake_button'] == 'enabled':
           if self.config['device'] == 'RaspberryPi':
               from ..hardware_components import RaspberryPiWakeButton
               self.wake_button = RaspberryPiWakeButton()
           else:
               self.wake_button = None
       else:
           self.wake_button = None

Now, we list out all the states that we need to implement in our app. This includes:

  • Idle State: App is listening for Hotword or Wake Button.
  • Recognizing State: App actively records audio from Microphone and performs Speech Recognition.
  • Busy State: SUSI API is called for the response of the query and the reply is spoken.
  • Error State: Upon any error in the above state, control transfers to Error State. This state needs to handle the speak the correct error message and then move the machine to Idle State.

Each state can be implemented by inheriting the base State class and implementing the on_enter() and on_exit() methods to implement the correct behavior.

We also declare a SUSI State Machine class to store the information about current state and declare the valid transitions for all the states.

class SusiStateMachine:
   def __init__(self):
       super().__init__()
       components = Components()
       self.__idle_state = IdleState(components)
       self.__recognizing_state = RecognizingState(components)
       self.__busy_state = BusyState(components)
       self.__error_state = ErrorState(components)
       self.current_state = self.__idle_state

       self.__idle_state.allowedStateTransitions = \
           {'recognizing': self.__recognizing_state, 'error': self.__error_state}
       self.__recognizing_state.allowedStateTransitions = \
           {'busy': self.__busy_state, 'error': self.__error_state}
       self.__busy_state.allowedStateTransitions = \
           {'idle': self.__idle_state, 'error': self.__error_state}
       self.__error_state.allowedStateTransitions = \
           {'idle': self.__idle_state}

       self.current_state.on_enter(payload=None)

We also set Idle State as the current State of the System. In this way, State Machine approach is implemented in SUSI Linux.

Resources:

 

Adding Service Workers In Generated Event Websites In Open Event Webapp

var urlsToCache = [
 './css/bootstrap.min.css',
 './offline.html',
 './images/avatar.png'
];
self.addEventListener('install', function(event) {
 event.waitUntil(
   caches.open(CACHE_NAME).then(function(cache) {
     return cache.addAll(urlsToCache);
   })
 );
});

All the other assets are cached lazily. Only when they are requested, we fetch them from the network and store it in the local store. This way, we avoid caching a large number of assets at the install step. Caching of several files in the install step is not recommended since if any of the listed files fails to download and cache, then the service worker won’t be installed!

self.addEventListener('fetch', function(event) {
event.respondWith(caches.match(event.request).then(function(response) {
     // Cache hit - return response
     if (response) { return response; }
     // Fetch resource from internet and put into cache
     var fetchRequest = event.request.clone();
     return fetch(fetchRequest).then(function(response) {
         var responseToCache = response.clone();
         caches.open(CACHE_NAME).then(function(cache) {
           cache.put(event.request, responseToCache);
         });
         return response;
       }).catch(function(err) {
         // Return fallback page when user is offline and resource is not cached
         if (event.request.headers.get('Accept').indexOf('text/html') !== -1) {
           return caches.match('./offline.html');
         }
       });
   })
 );
});

One thing which we need to keep in mind is that the website content should not become stale. Because it might happen that the website is updated but the actual content shown is older since response to every request is being fetched from the outdated cache. We need to delete the old cache and install a new service worker when the content of the site is updated. To deal with this issue, we calculate the hash of event website folder after the site has been generated. This value of the hash is used as the cache name inside which we keep the cached resources. When the content of the event website changes, the value of the hash changes. Due to this, a new service worker (containing the new value of the hash) is installed. After the currently open pages of the website are closed, the old service worker is killed and the activate event of the new service worker is fired. During this activate event, we clear the old cache containing the outdated content!  

// Hash of the event website Folder
var CACHE_NAME = 'Mtj5WiGtMtzesubewqMtdGS9wYI=';
self.addEventListener('activate', function(event) {
 event.waitUntil(caches.keys().then(function(cacheNames) {
   return Promise.all(cacheNames.map(function(cacheName) {
     if (cacheName !== CACHE_NAME) {
       console.log('Deleting cache ' + cacheName);
       return caches.delete(cacheName);
     }
   })
   );
 }));
});

Here are many screenshots showing service workers in action

  • When the site is updated, the outdated cache contents are cleared

29312352-87f9e8da-81d2-11e7-9f05-02a557a820da.png

  • On visiting a page which has not yet been cached, its contents are placed into cache for utilization on future visits

29312487-2155e70e-81d3-11e7-85c1-004c4a475e82.png

  • On visiting the cached page again, the assets will be served from the cache directly.

29312349-87f6c222-81d2-11e7-8fb4-c54feb175ed9.png

  • The page will comfortably load even on offline connections

29312351-87f8eec6-81d2-11e7-985a-7f1ba2dba482.png

  • On requesting for a page which has not yet been cached, we show a custom fallback page which shows a message

29312350-87f821c6-81d2-11e7-90e7-30f6467b2988.pngReferences: