One Click Deployment Button for loklak Using Heroku with Gradle Build

The one click deploy button makes it easy for the users of loklak to get their own cloud instance created and deployed in their heroku account and can be used according to their flexibility. Heroku uses an app.json manifest in the code repo to figure out what add-ons, config and other deployment steps are required to make the code run. This is used to configure and deploy the app.

Once you have provide the app name and then click on deploy button, Heroku will start deploying the loklak server to a new app on your account:

When setup is complete, you can open the deployed app in your browser or inspect it in Dashboard.

All these steps and requirements can now be encoded in an app.json file and placed in a repo alongside a button that kicks off the setup with a single click.

App.json is a manifest format for describing apps and specifying what their config requirements are. Heroku uses this file to figure out how code in a particular repo should be deployed on the platform. Here is the loklak’s app.json file which used gradle build pack:

{
	"name": "Loklak Server",
	"description": "Distributed Tweet Search Server",
	"logo": "https://raw.githubusercontent.com/loklak/loklak_server/master/html/images/loklak_anonymous.png",
	"website": "http://api.loklak.org",
	"repository": "https://github.com/loklak/loklak_server.git",
	"image": "loklak/loklak_server:latest-master",
	"env": {
		"BUILDPACK_URL": "https://github.com/heroku/heroku-buildpack-gradle.git"
	}
}

 

If you are interested you can try deploying the peer from here itself. Checkout how simple it can be to deploy.

Deploy button:

Deploy

Resources:

Know the Usage of all Emoji’s on Twitter with loklak Emoji Heatmap

Loklak apps page now has a new app in its store, Emoji Heatmap. This app can be used to see the usage of all the emoji’s in the tweets all over the world in the form of heatmap. So, the major difference between the emoji heatmap and emoji heatmapper apps are heatmapper shows the tweets related to specific search query whereas this heatmapper app, it displays all the tweets which contains emojis.

How do the App fetches and stores the locations

The emoji heatmap uses the loklak search API . The search API needs a query in order to search and output the JSON data. But this app takes no input from the user end to search any query. To make the search dynamic, we are using an existing JSON file from emojiHeatmapper app and loklak-fetcher-client javascript file. From the emoji.json file, we collect the each query item and search it using loklak-fetcher-client. The output json file which we get from loklak-fetcher-client is retrieved into the emojiHeatmap and we extract the location parameter. The location parameter is then stored into the “feature” option of open layers 3 maps.

So, here in the emoji Heatmap app, we iterate over the emoji.json, get different search query each time when we search for it using loklak search API.

Code which adds the location retrieved into feature

  $.getJSON("../emojiHeatmapper/emoji.json", function(json) {
    for (var i = 0; i < json.data.length; i++){
      var query = json.data[i][1];
      // Fetch loklak API data, and fill the vector
      loklakFetcher.getTweets(query, function(tweets) {
        for(var i = 0; i < tweets.statuses.length; i++) {
          if(tweets.statuses[i].location_point !== undefined){
          // Creation of the point with the tweet's coordinates
          //  Coords system swap is required: OpenLayers uses by default
          //  EPSG:3857, while loklak's output is EPSG:4326
            var point = new ol.geom.Point(ol.proj.transform(tweets.statuses[i].location_point, 'EPSG:4326', 'EPSG:3857'));
            vector.addFeature(new ol.Feature({  // Add the point to the data vector
              geometry: point,
              weight: 20
            }));
          }
        }
      });
    }
  });

 

The above function gets has two variables query and point. The query variable stores the data that is being retrieved from the emoji.json file each time it iterates and that query is being sent into the loklak-fetcher-client. Then the point variable is in which the location tracked using the loklak search API is converted into the co-ordinates system followed by the Open Layers 3. Then the point is added as a feature to the map vector. The map vector is the place where all the features are stored and then appended onto the map as a heatmap.

Resources