Adding “All” in Skill Categories

The SUSI SKill CMS has various filters to explore the skills of interest.  For example skill category and skill language. The skills are stored in the susi_skill_data Github repo in the following structure:

susi_skill_data/models/<model_name>/<group_name>/<language_name>/<skill_name>.txt

NOTE: group and category are same terms and can be used interchangeably

So when a category filter is applied the skills from the corresponding directory are returned.

susi_skill_data/models/<model_name>/<group_name>/<language_name>/<skill_name>.txt

But there’s no directory called “All”,  so how to get skills of all groups? For this, we need to loop through all the directories present in the model.

Server side implementation

Create a helper function that returns a list of all the folders present in a directory. The function accepts the parent directory name and an empty list. First, fetch all the items (files and folders) present in that directory and store them in an array. Then apply a filter over the array to check if the element is a directory and doesn’t start with a dot(.) i.e., it’s not hidden. Add the filtered array to the list.

private void listFoldersForFolder(final File folder, ArrayList<String> fileList) {
    File[] filesInFolder = folder.listFiles();
    if (filesInFolder != null) {
        Arrays.stream(filesInFolder)
                .filter(fileEntry -> fileEntry.isDirectory() && !fileEntry.getName().startsWith("."))
                .forEach(fileEntry -> fileList.add(fileEntry.getName() + ""));
    }
}

Fetch the group name form the request and add a check if the CMS is asking for all skill. Otherwise, return the skills of a particular group only.

String group_name = call.get("group", "Knowledge");
if (group_name.equals("All")) {
  // Return the list of all skills
} else {
  // Return the list of a skills in a particular group only
}

To fetch the list of all skills, call the listFoldersForFolders() function with the model name and an empty list as arguments. The function adds all the directories, present in that model directory, to folderList.

File allGroup = new File(String.valueOf(model));
ArrayList<String> folderList = new ArrayList<String>();
listFoldersForFolder(allGroup, folderList);

Then loop over all the groups present in the list to get all the skills present in that group. This process is the same as the existing process of getting skills of a particular category. Just keep adding the skill list to a global array.

CMS side implementation

The list of categories is first fetched from the API and then added to the dropdown menu. Since the API doesn’t return “All” in it, so we need to push it to the list manually.

groups.push(<MenuItem
                value="All"
                key="All"
                primaryText="All" />);

References

Continue Reading Adding “All” in Skill Categories

Adding System Image for Event Categories

The Open Event Server is using the JSON 1.0 Specification and build on top of Flask Rest Json API (for building Rest APIs) and Marshmallow (for Schema). In this blog, we will talk about how to add feature of System Image for Event Categories on Open Event Server. The focus is on Model updation, Schema updation and migrating the Database.

Model Updation

For adding System Image, we’ll update our Model EventTopic.

In this feature, we are providing rights to the Admin to add a system image for each Event Category so that if no image is given by a organizer of event on event creation then it will use the system image of that Event Category as event image by default.

Here we are adding a Column named system_image_url which is of type String. This value cannot be nullable and having a default value.

Migrating the Database

For the migrating the Database we will use simple commands.

This command runs migrations. If it cause problems naming Multiple Migration Head, then you need to run

This problem is caused when two developers push a migration file without merging two heads to achieve one head.

The above command will give us ids of two migration heads.

This command is merging two migration heads.

This command is upgrading the migrations.

Finally, we migrate the Database using above command.

Schema Updation

For the system image, we’ll update the Schema EventTopicSchema as follows

In this feature, to provide system image for each Event Category we’ll add a field named system_image_url in the Schema.

Here we are adding a field named system_image_url which is of marshmallow field type URL. This value cannot be none.

Validating the Event Image and using System Image by default

In this step, we’ll check if a event image is provided by organizer. If that is not provided then we’ll use system image of Event Category as Event Image.

Here, we will first take the event topic of event as added by the organizer. Then we will fetch the the database row in Event Topic model which has id == event_topic_id . Then we will return the system image url of that event topic to the event image.

So we saw how we could provide a default image for any event.

Resources

Continue Reading Adding System Image for Event Categories

Adding Event Roles concerning a User on Open Event Server

The Open Event Server enables organizers to manage events from concerts to conferences and meetups. It offers features for events with several tracks and venues. Event managers can create invitation forms for speakers and build schedules in a drag and drop interface. The event information is stored in a database. The system provides API endpoints to fetch the data, and to modify and update it. The Open Event Server is based on JSON 1.0 Specification and hence build on top of Flask Rest Json API (for building Rest APIs) and Marshmallow (for Schema).

In this blog, we will talk about how to add different events role concerning a user on Open Event Server. The focus is on its model and Schema updation.

Model Updation

For the User Table, we’ll update our User Model as follows:

Now, let’s try to understand these hybrid properties.

In this feature, we are providing Admin the rights to see whether a user is acting as a organizer, co-organizer, track_organizer, moderator, attendee and registrar of any of the event or not. Here, _is_role method is used to check whether an user plays a event role like organizer, co-organizer, track_organizer, moderator, attendee and registrar or not. This is done by querying the record from UserEventsRole model. If the record is present then the returned value is True otherwise False.

Schema Updation

For the User Model, we’ll update our Schema as follows

Now, let’s try to understand this Schema.

Since all the properties will return either True or false so these all properties are set to Boolean in Schema. Here dump_only means, we will return this property in the Schema.

So, we saw how User Model and Schema is updated to show events role concerning a user on Open Event Server.

Resources

Continue Reading Adding Event Roles concerning a User on Open Event Server

Adding Statistics of Event-Type on Open Event Server

The Open Event Server enables organizers to manage events from concerts to conferences and meet-ups. It offers features for events with several tracks and venues. In this blog, we will talk about how to add statistics of event-type on Open Event Server. The focus is on to get number of events of a specific event type.

Number of events of a specific event type

Now, let’s try to understand this API. Here, we are using flask Blueprints to add this API to the API index.

  1. First of all, we are using the decorator of event_statistics which will append this API route with that of mentioned in the Blueprint event_statistics.
  2. We will just allow logged in user to access this API using JWT (JSON Web Token)
  3. To return the response having all the event types alongwith number of events of it, requires a lot of queries if tried to fulfilled by SQLALchemy ORM. So instead of using ORM we will query using SQL command so that we query the number of all the events of different event types in just one query, which will eventually reduces the time of server to return the response.
  4. In function event_types_count we are using db.engine.execute to run the SQL command of getting the statistics of events respective to event types.
  5. The response will include id of event_type, name of event_type and count of events of corresponding event_type.
  6. Finally, we jsonify the list having objects of statistics of events respective to event types.

Similarly, event topics statistics can be implemented to return the number of events of all the event topics.

Resources

Continue Reading Adding Statistics of Event-Type on Open Event Server

Open Event Server – Pages API

This article illustrates how the Pages API has been designed and implemented on the server side, i.e., FOSSASIA‘s Open Event Server. Pages endpoint is used to create static pages such as “About Page” or any other page that doesn’t need to be updated frequently and only a specific content is to be shown.

Parameters

  1. name – This stores the name of the page.
      1. Type – String
      2. Required – Yes
  2. title – This stores the title of the page.
      1. Type – String
      2. Required – No
  3. url – This stores the url of the page.
      1. Type – String
      2. Required – Yes
  4. description – This stores the description of the page.
      1. Type – String
      2. Required – Yes
  5. language – This stores the language of the page.
      1. Type – String
      2. Required – No
  6. index – This stores the position of the page.
      1. Type – Integer
      2. Required – No
      3. Default – 0
  7. place – Location where the page will be placed.
      1. Type – String
      2. Required – No
      3. Accepted Values – ‘footer’ and ‘event’

These are the allowed parameters for the endpoint.

Model

Lets see how we model this API. The ORM looks like this :

__tablename__ = 'pages'
id = db.Column(db.Integer, primary_key=True)
name = db.Column(db.String, nullable=False)
title = db.Column(db.String)
url = db.Column(db.String, nullable=False)
description = db.Column(db.String)
place = db.Column(db.String)
language = db.Column(db.String)
index = db.Column(db.Integer, default=0)

As you can see, we created a table called “pages”. This table has 8 columns, 7 of which are the parameters that I have mentioned above. The column “id” is an Integer column and is the primary key column. This will help to differentiate between the various entries in the table.

The visualisation for this table looks as follows :

API

We support the following operations:

  1. GET all the pages in the database
  2. POST create a new page
  3. GET details of a single page as per id
  4. PATCH a single page by id
  5. DELETE a single page by id

To implement this we first add the routes in our python file as follows :

api.route(PageList, 'page_list', '/pages')
api.route(PageDetail, 'page_detail', '/pages/<int:id>')

Then we define these classes to handle the requests. The first route looks as follows:

class PageList(ResourceList):
   """
   List and create page
   """
   decorators = (api.has_permission('is_admin', methods="POST"),)
   schema = PageSchema
   data_layer = {'session': db.session,
                 'model': Page}

As can be seen above, this request requires the user to be an admin. It uses the Page model described above and handles a POST request.

The second route is:

class PageDetail(ResourceDetail):
   """
   Page detail by id
   """
   schema = PageSchema
   decorators = (api.has_permission('is_admin', methods="PATCH,DELETE"),)
   data_layer = {'session': db.session,
                 'model': Page}

This route also requires the user to be an admin. It uses the Page model and handles PATCH, DELETE requests.

To summarise our APIs are:

GET

/v1/pages{?sort,filter}

POST

/v1/pages{?sort,filter}

GET

/v1/pages/{page_id}

PATCH

/v1/pages/{page_id}

DELETE

/v1/pages/{page_id}

References

Continue Reading Open Event Server – Pages API

Adding multiple email support for users on Open Event Server

The Open Event Server enables organizers to manage events from concerts to conferences and meet-ups. It offers features for events with several tracks and venues. Event managers can create invitation forms for speakers and build schedules in a drag and drop interface. The event information is stored in a database. The system provides API endpoints to fetch the data, and to modify and update it.

The Open Event Server is based on JSON 1.0 Specification and hence build on top of Flask Rest Json API (for building Rest APIs) and Marshmallow (for Schema).

In this blog, we will talk about how to add support of multiple emails for a user in Open Event Server. The focus is on model and schema creation for this support.

Model Creation

For the UserEmail, we’ll make our model as follows

from app.models import db

class UserEmail(db.Model):
“””user email model class”””
__tablename__ = ‘user_emails’
id = db.Column(db.Integer, primary_key=True)
email = db.Column(db.String(120), unique=True, nullable=False)
verified = db.Column(db.Boolean, default=False)
user_id = db.Column(db.Integer, db.ForeignKey(‘users.id’, ondelete=’CASCADE’))
user = db.relationship(“User”, backref=”emails”, foreign_keys=[user_id])

def __init__(self, email=None, user_id=None):
self.email = email
self.user_id = user_id

def __str__(self):
return ‘User:’ + unicode(self.user_id).encode(‘utf-8’) + ‘ email: ‘ + unicode(self.email).encode(‘utf-8’)

def __unicode__(self):
return unicode(self.id)

Now, let’s try to understand the attributes of this model.

  1. id is most important Column required in every model to set it as primary key and to uniquely identify an UserEmail object.
  2. email is that attribute which is required hence should be unique and non-nullable.
  3. Verified attribute is used to check whether a email is verified or not (thus should be boolean)
  4. User_id is the attribute which specifies id of the user whose email is contained in the UserEmail object.
  5. Finally, a relationship with the user of id user_id and these emails (associated with the User.id == user_id) will be stored in the attribute emails in User Model.

Schema Creation

For the model UserEmail, we’ll make our schema UserEmailSchema as follows

from marshmallow_jsonapi import fields
from marshmallow_jsonapi.flask import Schema, Relationshipfrom app.api.helpers.utilities import dasherizeclass UserEmailSchema(Schema):
“””   API Schema for user email Model   “””class Meta:
“””  Meta class for user email API schema  “””
type_ = ‘user-emails’
self_view = ‘v1.user_emails_detail’
self_view_kwargs = {‘id’: ‘<id>’}
inflect = dasherize

id = fields.Str(dump_only=True)
email = fields.Email(allow_none=False)
user_id = fields.Integer(allow_none=False)
user = Relationship(attribute=’user’,
self_view=’v1.user_email’,
self_view_kwargs={‘id’: ‘<id>’},
related_view=’v1.user_detail’,
related_view_kwargs={‘user_id’: ‘<id>’},
schema=’UserSchema’,
type_=’user’
)

  • Marshmallow-jsonapi provides a simple way to produce JSON API-compliant data in any Python web framework.

Now, let’s try to understand the schema UserEmailSchema

  1. id : Same as in model id is used as uniquely identify an UserEmail object.
  2. email : Same as in model email is required thus allow_none is set to False.
  3. User_id : user_id is the id of user whose email is contained in a UserEmailSchema object.
  4. User : It tells whole attributes of the user to which this email belongs to.

So, we saw how to add multiple email support for users on Open Event Server. We just required to create a model and its schema to add this feature. Similarly, to add support for any database model in the project, we need to create Model and Schema with all the attributes as specified in the model too. This Schema creation is done with guidelines of JSONAPI 1.0 Specification using Marshmallow.

Resources

Continue Reading Adding multiple email support for users on Open Event Server

Creating A Dockerfile For Yacy Grid MCP

The YaCy Grid is the second-generation implementation of YaCy, a peer-to-peer search engine. A YaCy Grid installation consists of a set of micro-services which communicate with each other using a common infrastructure for data persistence. The task was to deploy the second-generation of YaCy Grid. To do so, we first had created a Dockerfile. This dockerfile should start the micro services such as rabbitmq, Apache ftp and elasticsearch in one docker instance along with MCP. The microservices perform following tasks:

  • Apache ftp server for asset storage.
  • RabbitMQ message queues for the message system.
  • Elasticsearch for database operations.

To launch these microservices using Dockerfile, we referred to following documentations regarding running these services locally: https://github.com/yacy/yacy_grid_mcp/blob/master/README.md

For creating a Dockerfile we proceeded as follows:

FROM ubuntu:latest
MAINTAINER Harshit Prasad# Update
RUN apt-get update
RUN apt-get upgrade -y# add packages
# install jdk package for java
RUN apt-get install -y git openjdk-8-jdk

#install gradle required for build
RUN apt-get update && apt-get install -y software-properties-common
RUN add-apt-repository ppa:cwchien/gradle
RUN apt-get update
RUN apt-get install -y wget
RUN wget https://services.gradle.org/distributions/gradle-3.4.1-bin.zip
RUN mkdir /opt/gradle
RUN apt-get install -y unzip
RUN unzip -d /opt/gradle gradle-3.4.1-bin.zip
RUN PATH=$PATH:/opt/gradle/gradle-3.4.1/bin
ENV GRADLE_HOME=/opt/gradle/gradle-3.4.1
ENV PATH=$PATH:$GRADLE_HOME/bin
RUN gradle -v

# install apache ftp server 1.1.0
RUN wget http://www-eu.apache.org/dist/mina/ftpserver/1.1.0/dist/apache-ftpserver-1.1.0.tar.gz
RUN tar xfz apache-ftpserver-1.1.0.tar.gz

# install RabbitMQ server
RUN wget https://www.rabbitmq.com/releases/rabbitmq-server/v3.6.6/rabbitmq-server-generic-unix-3.6.6.tar.xz
RUN tar xf rabbitmq-server-generic-unix-3.6.6.tar.xz

# install erlang language for RabbitMQ
RUN apt-get install -y erlang

# install elasticsearch
RUN wget https://artifacts.elastic.co/downloads/elasticsearch/elasticsearch-5.5.0.tar.gz
RUN sha1sum elasticsearch-5.5.0.tar.gz
RUN tar -xzf elasticsearch-5.5.0.tar.gz

# clone yacy_grid_mcp repository
RUN git clone https://github.com/nikhilrayaprolu/yacy_grid_mcp.git
WORKDIR /yacy_grid_mcp

RUN cat docker/configftp.properties > ../apacheftpserver1.1.0/res/conf/users.properties

# compile
RUN gradle build
RUN mkdir data/mcp-8100/conf/ -p
RUN cp docker/config-mcp.properties data/mcp-8100/conf/config.properties
RUN chmod +x ./docker/start.sh

# Expose web interface ports
# 2121: ftp, a FTP server to be used for mass data / file storage
# 5672: rabbitmq, a rabbitmq message queue server to be used for global messages, queues and stacks
# 9300: elastic, an elasticsearch server or main cluster address for global database storage
EXPOSE 2121 5672 9300 9200 15672 8100

# Define default command.
ENTRYPOINT [“/bin/bash”, “./docker/start.sh”]

 

We have created a start.sh file to start RabbitMQ and Apache FTP services. At the end, for compilation gradle run will be executed.

adduser –disabled-password –gecos ” r
adduser r sudo
echo ‘%sudo ALL=(ALL) NOPASSWD:ALL’ >> /etc/sudoers
chmod a+rwx /elasticsearch-5.5.0 -R
su -m r -c ‘/elasticsearch-5.5.0/bin/elasticsearch -Ecluster.name=yacygrid &’
cd /apacheftpserver1.1.0
./bin/ftpd.sh res/conf/ftpdtypical.xml &
/rabbitmq_server-3.6.6/sbin/rabbitmq-server -detached
sleep 5s;
/rabbitmq_server-3.6.6/sbin/rabbitmq-plugins enable rabbitmq_management
/rabbitmq_server3.6.6/sbin/rabbitmqctl add_user yacygrid password4account
echo [{rabbit, [{loopback_users, []}]}]. >> /rabbitmq_server-3.6.6/etc/rabbitmq/rabbitmq.config
/rabbitmq_server-3.6.6/sbin/rabbitmqctl set_permissions -p / yacygrid “.*” “.*” “.*”
cd /yacy_grid_mcp
sleep 5s;
gradle run

 

start.sh will first add username and then password. Then it will start RabbitMQ along with Apache FTP.  For username and password, we have created a separate files to configure their properties during Docker run which can be found here:

The logic behind running all the microservices in one docker instance was: creating each container for microservice and then link those containers with the help of docker-compose.yml file.

The Dockerfile which we have created was corresponding to one image. Another image was elasticsearch which was linked to this Dockerfile. The latest version of elasticsearch image was already available on their site: https://www.elastic.co/guide/en/elasticsearch/reference/current/docker.html

We configured the docker-compose.yml file according to the reference link provided above. The docker-compose file can be found here: https://github.com/yacy/yacy_grid_mcp/blob/master/docker/docker-compose.yml

The source code for the implementation of whole structure can be found here: https://github.com/yacy/yacy_grid_mcp/tree/master/docker

Resources

 

Continue Reading Creating A Dockerfile For Yacy Grid MCP

Auto Deployment of SUSI Server using Kubernetes on Google Cloud Platform

Recently, we auto deployed SUSI Server on Google Cloud Platform using Kubernetes and Docker Images after each commit in the GitHub repo with the help of Travis Continuous Integration. So, basically, whenever a new commit is added to the repo, during the Travis build, we build the docker image of the server and then use it to deploy the server on Google Cloud Platform. We use Kubernetes for deployment since it is very easy to scale up the Project when traffic on the server is increased and Docker because using it we can easily build docker images which then can be used to update the deployment. This schematic will make things more clear what exactly is the procedure.

Prerequisites

  1. You must be signed in to your Google Cloud Console and have enabled billing and must have credits left in your account.
  2. You must have a docker account and a repo in it. If you don’t have one, make it now.
  3. You should have enabled Travis on your repo and have a Travis.yml file in your repo.
  4. You must already have a project in Google Cloud Console. Make a new one if you don’t have.

Pre Deployment Steps

You will be needed to do some work on Google Cloud Platform before actually starting the auto deployment process. Those are:

  1. Creating a new Cluster.
  2. Adding and Formatting Persistence Disk
  3. Adding a Persistent Volume CLaim (PVC)
  4. Labeling a node as primary.

Check out this documentation on how to do that. It may help.

Implementation

Img src: https://cloud.google.com/solutions/continuous-delivery-with-travis-ci

1. The first step is simply to add this line in Travis.yml file and create an empty deploy.sh, file mentioned below.

after_success:
- bash kubernetes/travis/deploy.sh

Now we’ll be moving line by line and adding commands in the empty deploy.sh file that we created in the previous step.

2. Next step is to remove obsolete Google Cloud files and install Google Cloud SDK and kubectl command. Use following lines to do that.

echo ">>> Removing obsolete gcoud files"
sudo rm -f /usr/bin/git-credential-gcloud.sh
sudo rm -f /usr/bin/bq
sudo rm -f /usr/bin/gsutil
sudo rm -f /usr/bin/gcloud

echo ">>> Installing new files"
curl https://sdk.cloud.google.com | bash;
source ~/.bashrc
gcloud components install kubectl

3. In this step you will be needed to download a JSON file which contains your Google Cloud Credentials, then copy that file to your repo and encrypt it using Travis encryption keys. Follow https://youtu.be/7U4jjRw_AJk this video to see how to do that.

4. So, now you have added your encrypted credentials.json files in your repo and now you need to use those credentials to login into your google cloud account. So, use below lines to do that.

echo ">>> Decrypting credentials and authenticating gcloud account"
# Decrypt the credentials we added to the repo using the key we added with the Travis command line tool
openssl aes-256-cbc -K $encrypted_YOUR_key -iv $encrypted_YOUR_iv -in ./kubernetes/travis/Credentials.json.enc -out Credentials.json -d
gcloud auth activate-service-account --key-file Credentials.json
export GOOGLE_APPLICATION_CREDENTIALS=$(pwd)/Credentials.json
#add gcoud project id
gcloud config set project YOUR_PROJECT_ID
gcloud container clusters get-credentials YOUR_CONTAINER

The above lines of code first decrypt your credentials, then login into your account and set the project you already created earlier.

5. Now, we have logged into Google Cloud, we need to build docker image from a dockerfile. Follow official docker docs to see how to write a dockerfile. Here is an example of dockerfile. You will need to add “$DOCKER_USERNAME” and “$DOCKER_PASSWORD” as environment variables in Travis settings of your repo.

echo ">>> Building Docker image"
cd kubernetes/images

docker build --no-cache -t YOUR_DOCKER_USERNAME/YOUR_DOCKER_REPO:$TRAVIS_COMMIT .
docker login -u="$DOCKER_USERNAME" -p="$DOCKER_PASSWORD"
docker tag YOUR_DOCKER_USERNAME/YOUR_DOCKER_REPO:$TRAVIS_COMMIT YOUR_DOCKER_USERNAME/YOUR_DOCKER_REPO:latest

6. Now, just push the docker image created in previous step and update the deployment.

echo ">>> Pushing docker image"
docker push YOUR_DOCKER_USERNAME/YOUR_DOCKER_REPO

echo ">>> Updating deployment"
kubectl set image deployment/YOUR_CONTAINER_NAME --namespace=default YOUR_CONTAINER_NAME=YOUR_DOCKER_USERNAME/YOUR_DOCKER_REPO:$TRAVIS_COMMIT

Summary

This blog was about how we have configured travis build and auto deployed SUSI Server on Google Cloud Platform using Kubernetes and Docker. You can do the same with your server too or if you are looking to contribute to SUSI Server, this may help you a little in understanding the code of the repo.

Resources

  1. The documentation for setting up your project on Google CLoud Console before starting auto deployment https://github.com/fossasia/susi_server/blob/afb00cd9c421876f5d640ce87941e502aa52e004/docs/installation/installation_kubernetes_gcloud.md
  2. The documentation for encrypting your google cloud credentials and adding them to your repo https://cloud.google.com/solutions/continuous-delivery-with-travis-ci
  3. Docs for Docker to get you started with Docker https://docs.docker.com/
  4. Travis Documentation on how to secure your credentials https://docs.travis-ci.com/user/encryption-keys/
  5. Travis Documentation on how to add environment variables in your repo settings https://docs.travis-ci.com/user/environment-variables/
Continue Reading Auto Deployment of SUSI Server using Kubernetes on Google Cloud Platform

How to Store and Retrieve User Settings from SUSI Server in SUSI iOS

Any user using the SUSI iOS client can set preferences like enabling or disabling the hot word recognition or enabling input from the microphone. These settings need to be stored, in order to be used across all platforms such as web, Android or iOS. Now, in order to store these settings and maintain a synchronization between all the clients, we make use of the SUSI server. The server provides an endpoint to retrieve these settings when the user logs in.

First, we will focus on storing settings on the server followed by retrieving settings from the server. The endpoint to store settings is as follows:

http://api.susi.ai/aaa/changeUserSettings.json?key=key&value=value&access_token=ACCESS_TOKEN

This takes the key value pair for storing a settings and an access token to identify the user as parameters in the GET request. Let’s start by creating the method that takes input the params, calls the API to store settings and returns a status specifying if the executed successfully or not.

 let url = getApiUrl(UserDefaults.standard.object(forKey: ControllerConstants.UserDefaultsKeys.ipAddress) as! String, Methods.UserSettings)

        _ = makeRequest(url, .get, [:], parameters: params, completion: { (results, message) in
            if let _ = message {
                completion(false, ResponseMessages.ServerError)
            } else if let results = results {
                guard let response = results as? [String : AnyObject] else {
                    completion(false, ResponseMessages.ServerError)
                    return
                }
                if let accepted = response[ControllerConstants.accepted] as? Bool, let message = response[Client.UserKeys.Message] as? String {
                    if accepted {
                        completion(true, message)
                        return
                    }
                    completion(false, message)
                    return
                }
            }
        })

Let’s understand this function line by line. First we generate the URL by supplying the server address and the method. Then, we pass the URL and the params in the `makeRequest` method which has a completion handler returning a results object and an error object. Inside the completion handler, check for any error, if it exists mark the request completed with an error else check for the results object to be a dictionary and a key `accepted`, if this key is `true` our request executed successfully and we mark the request to be executed successfully and finally return the method. After making this method, it needs to be called in the view controller, we do so by the following code.

Client.sharedInstance.changeUserSettings(params) { (_, message) in
  DispatchQueue.global().async {
    self.view.makeToast(message)
  }
}

The code above takes input params containing the user token and key-value pair for the setting that needs to be stored. This request runs on a background thread and displays a toast message with the result of the request.

Now that the settings have been stored on the server, we need to retrieve these settings every time the user logs in the app. Below is the endpoint for the same:

http://api.susi.ai/aaa/listUserSettings.json?access_token=ACCESS_TOKEN

This endpoint accepts the user token which is generated when the user logs in which is used to uniquely identify the user and his/her settings are returned. Let’s create the method that would call this endpoint and parse and save the settings data in the iOS app’s User Defaults.

if let _ = message {
  completion(false, ResponseMessages.ServerError)
} else if let results = results {
  guard let response = results as? [String : AnyObject] else {
    completion(false, ResponseMessages.ServerError)
    return
  }
  guard let settings = 
response[ControllerConstants.Settings.settings.lowercased()] as? [String:String] else {
    completion(false, ResponseMessages.ServerError)
    return
  }
  for (key, value) in settings {
    if value.toBool() != nil {
      UserDefaults.standard.set(value.toBool()!, forKey: key)
    } else {
      UserDefaults.standard.set(value, forKey: key)
    }
  }
  completion(true, response[Client.UserKeys.Message] as? String ?? "error")
}

Here, the creation of the URL is same as we created above the only difference being the method passed. We parse the settings key value into a dictionary followed by a loop which loop’s through all the keys and stores the value in the User Defaults for that key. We simply call this method just after user log in as follows:

Client.sharedInstance.fetchUserSettings(params as [String : AnyObject]) { (success, message) in
  DispatchQueue.global().async {
    print("User settings fetch status: \(success) : \(message)")
  }
}

That’s all for this tutorial where we learned how to store and retrieve settings on the SUSI Server.

References

Continue Reading How to Store and Retrieve User Settings from SUSI Server in SUSI iOS