Adding additional information to store listing page of Loklak apps site

Loklak apps site has now got a completely functional store listing page where users can find all relevant information about the app which they want to view. The page has a left side bar which shows various categories to switch between, a right sidebar for suggesting similar kind of apps to users and a middle section to provide users with various important informations about the app like getting started, use of app, promo images, preview images, test link and various other details. In this blog I will be describing how the bottom section of the middle column has been created (related issue: #209).

The bottom section

The bottom section provides various informations like updated, version, app source, developer information, contributors, technology stack, license. All these informations has to be dynamically loaded for each selected app. As I had previously mentioned here, no HTML content can be hard coded in the store listing page. So how do we show the above mentioned informations for the different apps? Well, for this we will once again use the app.json of the corresponding app like we had done for the middle section here.

At first, for a given app we need to define some extra fields in the app.json file as shown below.

"appSource": "https://github.com/fossasia/apps.loklak.org/tree/master/MultiLinePlotter",
  "contributors": [{"name": "djmgit", "url": "http://djmgit.github.io/"}],
  "techStack": ["HTML", "CSS", "AngularJs", "Morris.js", "Bootstrap", "Loklak API"],
  "license": {"name": "LGPL 2.1", "url": "https://www.gnu.org/licenses/old-licenses/lgpl-2.1"},
  "version": "1.0",
  "updated": "June 10,2017",

The above code snippet shows the new fields included in app.json. The fields are as described below.

  • appSource: Stores link to the source code of the app.
  • Contributors: Stores a list containing objects. Each object stores name of the contributor and an url corresponding to that contributor.
  • techStack: A list containing names of the technologies used.
  • License: Name and link of the license.
  • Version: The current version of the app.
  • Updated: Date on which the app was last updated.

These fields provide the source for the informations present in the bottom section of the app.

Now we need to render these information on the store listing page. Let us take an example. Let us see how version is rendered.

<div ng-if="appData.version !== undefined && appData.version !== ''" class="col-md-4 add-info">
                  <div class="info-type">
                    <h5 class="info-header">
                      <strong>Version</strong>
                    </h5>
                  </div>
                  <div class="info-body">
                    {{appData.version}}
                  </div>
                </div>

We first check if version field is defined and version is not empty. Then we print a header (Version in this case) and then we print the value. This is how updated, appSource and license are also displayed. What about technology stack and contributors? Technology stack is basically an list and it may contain quite a number of strings(technology names). If we display all the values at once the bottom section will get crowded and it may degrade the UI of the page.To avoid this a popup dialog has been used. When user clicks on the technology stack label, a popup dialogue appears which shows the various technologies used in the app.

<div class="info-body">
                    <div class="dropdown">
                      <div class="dropdown-toggle" type="button" data-toggle="dropdown">
                        View technology stack
                      </div>
                      <ul class="dropdown-menu">
                        <li ng-repeat="item in appData.techStack" class="tech-item">
                           {{item}}
                        </li>
                      </ul>
                    </div>
                  </div>

After displaying a header, we iterate over the techStack list and populate our popup dialogue. This popup dialogue is attached to the label ‘View technology stack‘. Whenever a user clicks on this label, the popup is shown. The same technique technique is also applied for rendering contributors. A popup dialogue is used to display all the contributors. Thus technology stack and contributors list is shown only on demand.

For developer information, name of the developer is shown which is linked to his/her website and there is an option to send email or copy email id if present.

<div class="info-body">
                    <span ng-if="appData.author.url !== undefined && appData.author.url !== ''">
                      <a href="{{appData.author.url}}"> {{appData.author.name}} </a>
                    </span>
                    <a ng-if="appData.author.email !== undefined && appData.author.email !== ''" class="mail"
                      href="mailto:{{appData.author.email}}">
                      <span class="glyphicon glyphicon-envelope"></span>
                    </a>
                  </div>



For email id, bootstrap’s email glyphicon is used along with a mailto link pointing to the developer’s email id. What does mailto do? It simply opens your default mail client. For example if you are on linux, it might open Thunderbird. If you do not have a mail client installed, but your default browser is google chrome, it will open gmail mail composer. If you are viewing the site on android device, it will open gmail app directly.

The bottom section can be viewed here.

Important resources

 

Continue ReadingAdding additional information to store listing page of Loklak apps site

Improving Loklak apps site

In this blog I will be describing some of the recent improvements made to the Loklak apps site. A new utility script has been added to automatically update the loklak app wall after a new app has been made. Invalid app query in app details page has been handled gracefully.

A proper message is shown when a user enters an invalid app name in the url of the details page. Tests has been added for details page.

Developing updatewall script

This is a small utility script to update Loklak wall in order to expose a newly created app or update an existing app. Before moving into the working of this script let us discuss how Loklak apps site tracks all the apps and their details. In the root of the project there is a file names apps.json. This file contains an aggregation of all the app.json files present in the individual apps. Now when the site is loaded, index.html loads the Javascript code present in app_list.js. This app_list.js file makes an ajax call to root apps.json files, loads all the app details in a list and attaches this list to the AngularJS scope variable. After this the app wall consisting of various app details is rendered using html. So whenever a new app is created, in order to expose the app on the wall, the developer needs to copy the contents of the application’s app.json and paste it in the root apps.json file. This is quite tedious on the part of the developer as for making a new app he will first have to know how the site works which is not all directly related to his development work. Next, whenever he updates the app.json of his app, he needs to again update apps.json file with the new data.

This newly added script (updatewall) automates this entire process. After creating a new app all that the developer needs to do is run this script from within his app directory and the app wall will be updated automatically.

Now, let us move into the working of this script. The basic workflow of the updatewall script can be described as follows. The script loads the json data present in the app.json file of the app under consideration. Next it loads the json data present in the root apps.json file.

if __name__ == '__main__':

    #open file containg json object
    json_list_file = open(PATH_TO_ROOT_JSON, 'r')

    #load json object
    json_list = json.load(json_list_file,  object_pairs_hook=OrderedDict)
    json_list_file.close()

    app_json_file = open(PATH_TO_APP_JSON, 'r')
    app_json = json.load(app_json_file,  object_pairs_hook=OrderedDict)
    app_json_file.close()

    #method to update Loklak app wall
    expose_app(json_list, app_json)

When we are loading the json data we are using object_pairs_hook in order to load the data into an OrderedDict rather than a normal python dictionary. We are doing this so that the order of the dictionary items are maintained. Once the data is loaded we invoke the expose method.

def expose_app(json_list, app_json):
    #if app is already present in list then fetch that app
    app = getAppIfPesent(json_list, app_json)

    #if app is not present then add a new entry
    if app == None:
        json_list['apps'].append(app_json)
        update_list_file(json_list)
        print colors.BOLD + colors.OKGREEN + 'App exposed on app wall' + colors.ENDC

    #else update the existing app entry
    else:
        for key in app_json:
            app[key] = app_json[key]
        update_list_file(json_list)
        print colors.BOLD + colors.OKGREEN + 'App updated on app wall' + colors.ENDC

The apps.json file contain a key called apps. This value of this key is a list of json objects, each object being the json data of an individual app’s app.json file. In the above function we iterate over all the json objects present in the list. If we are unable to find a json object whose name value is same as that of the newly created app then we simply append the new app’s app.json object to that list. However if we find an object containing the same name value as that of the newly created app, then we simply update its properties. In short, if the app is a new one, its data gets added to apps.json otherwise the corresponding app data is updated.

Handling invalid app names in the URL of details page

The url of the app details page takes the app name as parameter. If any user wants to see the store listing of an app then he has to use the following url.

https://apps.loklak.org/details.html?q=<app_name>

Here app name is a url parameter used to load the store listing information. Now if anyone enters an invalid app name, that is an app which does not exists, then a proper error message has to be shown to the user. This can be done by checking whether the given app name is present in the root apps.json file or not. If not present if simply set a flag so that the error message can be conditionally rendered.

$scope.getSelectedApp = function() {
        for (var i = 0; i < $scope.apps.length; i++) {
            if ($scope.apps[i].name === $scope.appName) {
                $scope.selectedApp = $scope.apps[i];
                $scope.found = true;
                $("nav").show();
                break;
            }
        }
        if ($scope.found == false) {
            $scope.notFound = true;
        }
    }

In the above snippet if the app is not found then we set notFound to true. This causes the error message to appear on the page.

<div ng-if="notFound" class="not-found">
        <span class="brand-and-image">
          <img src="images/loklak_icon.png">
          <span class="loklak-brand"> <span class="loklak-header">
            loklak </span> <span>apps</span>
          </span>
        </span>
        <span class="error-404">
          Error: Requested app not found
        </span>
        <span class="go-back">
          <a href="/"> Go Back to Home Page >> </a>
        </span>
      </div>

The code renders the error message if notFound is set to true.

Writing tests for store listing page

Almost the entire content of the store listing is loaded dynamically by Javascript logic. So it is very important to write tests for store listing page. Protractor framework has been used to write automated browser test. The tests make sure that for a given app, the content of the middle section is loaded correctly.

it("should have basic information", function() {
    expect(element(by.css(".app-name")).getText()).toEqual("MultiLinePlotter");
    expect(element(by.css(".app-headline")).getText()).toEqual("App to plot tweet aggregations and statistics");
    expect(element(by.css(".author")).getText()).toEqual("by Deepjyoti Mondal");
    expect(element(by.css(".short-desc")).getText()).toEqual("An applicaton to visually compare tweet statistics");
  });

The above tests make sure that the top section is loaded properly. Next we check that getting started section and app use section are not empty.

it("main content should not be empty", function() {
    expect(element(by.css(".get-started-md")).getText()).not.toBe("");
    expect(element(by.css(".app-use-md")).getText()).not.toBe("");
  });

Apart from these, two more tests are performed to check the behaviour of the side bar menu items on click event and the functionality of the Try now button.

Future roadmap

There is still a lot of scope for the site’s improvement and enhancement. Some of the features which can be implemented next are given below.

  • Add more tests to make the site stable and add tests to travis build.
  • Make the apps independent. Work on this has already been started and can be viewed here – issue, PR
  • Optimise the site for mobile using services workers and caching (making a progressive web app).
  • Add a splash screen and home screen icon for mobile.

Important resources

Continue ReadingImproving Loklak apps site

Using Protractor for UI Tests in Angular JS for Loklak Apps Site

Loklak apps site’s home page and app details page have sections where data is dynamically loaded from external javascript and json files. Data is fetched from json files using angular js, processed and then rendered to the corresponding views by controllers. Any erroneous modification to the controller functions might cause discrepancies in the frontend. Since Loklak apps is a frontend project, any bug in the home page or details page will lead to poor UI/UX. How do we deal with this? One way is to write unit tests for the various controller functions and check their behaviours. Now how do we test the behaviours of the site. Most of the controller functions render something on the view. One thing we can do is simulate the various browser actions and test site against known, accepted behaviours with Protractor.

What is Protractor

Protractor is end to end test framework for Angular and AngularJS apps. It runs tests against our app running in browser as if a real user is interacting with our browser. It uses browser specific drivers to interact with our web application as any user would.

Using Protractor to write tests for Loklak apps site

First we need to install Protractor and its dependencies. Let us begin by creating an empty json file in the project directory using the following command.

echo {} > package.json

Next we will have to install Protractor.

The above command installs protractor and webdriver-manager. After this we need to get the necessary binaries to set up our selenium server. This can be done using the following.

./node_modules/protractor/bin/webdriver-manager update
./node_modules/protractor/bin/webdriver-manager start

Let us tidy up things a bit. We will include these commands in package.json file under scripts section so that we can shorten our commands.

Given below is the current state of package.json

{
    "scripts": {
        "start": "./node_modules/http-server/bin/http-server",
        "update-driver": "./node_modules/protractor/bin/webdriver-manager update",
        "start-driver": "./node_modules/protractor/bin/webdriver-manager start",
        "test": "./node_modules/protractor/bin/protractor conf.js"
    },
    "dependencies": {
        "http-server": "^0.10.0",
        "protractor": "^5.1.2"
    }
}

The package.json file currently holds our dependencies and scripts. It contains command for starting development server, updating webdriver and starting webdriver (mentioned just before this) and command to run test.

Next we need to include a configuration file for protractor. The configuration file should contain the test framework to be used, the address at which selenium is running and path to specs file.

// conf.js
exports.config = {
    framework: "jasmine",
    seleniumAddress: "http://localhost:4444/wd/hub",
    specs: ["tests/home-spec.js"]
};

We have set the framework as jasmine and selenium address as http://localhost:4444/wd/hub. Next we need to define our actual file. But before writing tests we need to find out what are the things that we need to test. We will mostly be testing dynamic content loaded by Javascript files. Let us define a spec. A spec is a collection of tests. We will start by testing the category name. Initially when the page loads it should be equal to All apps. Next we test the top right hand side menu which is loaded by javascript using topmenu.json file.

it("should have a category name", function() {
    expect(element(by.id("categoryName")).getText()).toEqual("All apps");
  });

  it("should have top menu", function() {
    let list = element.all(by.css(".topmenu li a"));
    expect(list.count()).toBe(5);
  });

As mentioned earlier, we are using jasmine framework for writing our specs. In the above code snippet ‘it’ describes a particular test. It takes a test description and a callback function thereby providing a very efficient way to document our tests white write the test code itself. In the first test we use expect function to check whether the category name is equal to All apps or not. Here we select the div containing the category name by its id.

Next we write a test for top menu. There should be five menu options in total for the top menu. We select all the list items that are supposed to contain the top menu items and check whether the number of such items are five or not using expect function. As it can be seen from the snippet, the process of selecting a node is almost similar to that of Jquery library.

Next we test the left hand side category list. This list is loaded by AngularJS controller from apps,json file. We should make sure the list is loaded properly and all the options are present.

it("should have a category list", function() {
    let categoryIds = ["All", "Scraper", "Search", "Visualizer", "LoklakLibraries", "InternetOfThings", "Misc"];
    let categoryNames = ["All", "Scraper", "Search", "Visualizer", "Loklak Libraries", "Internet Of Things", "Misc"];

    expect(element(by.css("#catTitle")).getText()).toBe("Categories");

    let categoryList = element.all(by.css(".category-main"));
    expect(categoryList.count()).toBe(7);

    categoryIds.forEach(function(id, index) {
      element(by.css("#" + id)).isPresent().then(function(present) {
        expect(present).toBe(true);
      });

      element(by.css("#" + id)).getText().then(function(text) {
        expect(text).toBe(categoryNames[index]);
      });
    });
  });

At first we maintain two lists of category id and category names. We begin by confirming that Category title is equal to Categories. Next we get the list of categories and iterate over them, For each category we check whether the corresponding id is present in the DOM or not. After confirming this, we match the names of the categories with the expected names. Elements.all function allows us to get a list of selected nodes.

Finally we check the click functionality of the left side menu. Expected behaviour is, on clicking a menu item, the category name should get replaced with the selected category name. For this we need to simulate the click event. Protractor allows us to do it very easily using click function.

it("category list should respond to click", function() {
    let categoryIds = ["All", "Scraper", "Search", "Visualizer", "LoklakLibraries", "InternetOfThings", "Misc"];
    let categoryNames = ["All apps", "Scraper", "Search", "Visualizer", "Loklak Libraries", "Internet Of Things", "Misc"];

    categoryIds.forEach(function(id, index) {
      element(by.id(categoryIds[index])).click().then(function() {
        browser.getCurrentUrl().then(function(url) {
          expect(url).toBe("http://127.0.0.1:8080/#/" + categoryIds[index]);
        });
        element(by.id("categoryName")).getText().then(function(text) {
          expect(text).toBe(categoryNames[index]);
        });
      });
    });
  });



Once again we maintain two lists, category id and category names. We obtain the present list of categories and iterate over them. For each category link we simulate a click event. For each click event we check two values. We check the new browser URL which should now contain the category id. Next we check the value of category name. It should be equal to the category selected.
FInally after all the tests are over we get the final report on our terminal.
In order to run the tests, use the following command.

npm test

This will start executing the tests.

Important resources

Continue ReadingUsing Protractor for UI Tests in Angular JS for Loklak Apps Site

Adding download feature to LoklakWordCloud app on Loklak apps site

One of the most important and useful feature that has recently been added to LoklakWordCloud app is enabling the user to download the generated word cloud as a png/jpeg image. This feature will allow the user to actually use this app as a tool to generate a word cloud using twitter data and save it on their disks for future use.

All that the user needs to do is generate the word cloud, choose an image type (png or jpeg) and click on export as image, a preview of the image to be downloaded will be displayed. Just hit enter and the word cloud will be saved on your disk. Thus users will not have to use any alternative process like taking a screenshot of the word cloud generated, etc.

Presently the complete app is hosted on Loklak apps site.

How does it work?

What we are doing is, we are exporting a part of the page (a div) as image and saving it. Apparently it might seem that we are taking a screenshot of a particular portion of a page and generating a download link. But actually it is not like that. The word cloud that is being generated by this app via Jqcloud is actually a collection of HTML nodes. Each node contains a word (part of the cloud) as a text content with some CSS styles to specify the size and color of that word. As user clicks on export to image option, the app traverses the div containing the cloud. It collects information about all the HTML nodes present under that div and creates a canvas representation of the entire div. So rather than taking a screenshot of the div, the app recreates the entire div and presents it to us. This entire process is accomplished by a lightweight JS library called html2canvas.

Let us have a look into the code that implements the download feature. At first we need to create the UI for the export and download option. User should be able to choose between png and jpeg before exporting to image. For this we have provided a dropdown containing the two options.

<div class="dropdown type" ng-if="download">
                <div class="dropdown-toggle select-type" data-toggle="dropdown">
                  {{imageType}}
                <span class="caret"></span></div>
                <ul class="dropdown-menu">
                  <li ng-click="changeType('png', 'png')"><a href="">png</a></li>
                  <li ng-click="changeType('jpeg', 'jpg')"><a href="">jpeg</a></li>
                </ul>
              </div>
              <a class="export" ng-click="export()" ng-if="download">Export as image</a>

In the above code snippet, firstly we create a dropdown menu with two list items, png and jpeg. With each each list item we attach a ng-click event which calls changeType function and passes two parameters, image type and extension.

The changeType function simply updates the current image type and extension with the selected ones.

$scope.changeType = function(type, ext) {
        $scope.imageType = type;
        $scope.imageExt = ext;
    }

The ‘export as image’ on clicking calls the export function. The export function uses html2canvas library’s interface to generate the canvas representation of the word cloud and also generates the download link and attaches it to the modal’s save button (described below). After everything is done it finally opens a modal with preview image and save option.

$scope.export = function() {
        html2canvas($(".wordcloud"), {
          onrendered: function(canvas) {
            var imgageData = canvas.toDataURL("image/" + $scope.imageType);
            var regex = /^data:image\/jpeg/;
            if ($scope.imageType === "png") {
                regex = /^data:image\/png/;
            }
            var newData = imgageData.replace(regex, "data:application/octet-stream");
            canvas.style.width = "80%";
            $(".wordcloud-canvas").html(canvas);
            $(".save-btn").attr("download", "Wordcloud." + $scope.imageExt).attr("href", newData);
            $("#preview").modal('show');
          },
          background: "#ffffff"
        });
    }

At the very beginning of this function, a call is made to html2canvas module and the div containing the word cloud is passed as a parameter. An object is also passed which contains a callback function defined for onrendered key. Inside the callback function we check the current image type and generate the corresponding url from the canvas. We display this canvas in the modal and set this download url as the href value of the modal’s save button.

Finally we display the modal.

The modal simply contains the preview image and a button to save the image on disk.

A sample image produced by the app is shown below.

Important resources

  • Know more about html2canvas here.
  • Know more about Jqcloud here.
  • View the app source here.
  • View loklak apps site source here.
  • View Loklak API documentation here
  • Learn more about AngularJS here.
Continue ReadingAdding download feature to LoklakWordCloud app on Loklak apps site

Developing LoklakWordCloud app for Loklak apps site

LoklakWordCloud app is an app to visualise data returned by loklak in form of a word cloud.

The app is presently hosted on Loklak apps site.

Word clouds provide a very simple, easy, yet interesting and effective way to analyse and visualise data. This app will allow users to create word cloud out of twitter data via Loklak API.

Presently the app is at its very early stage of development and more work is left to be done. The app consists of a input field where user can enter a query word and on pressing search button a word cloud will be generated using the words related to the query word entered.

Loklak API is used to fetch all the tweets which contain the query word entered by the user.

These tweets are processed to generate the word cloud.

Related issue: https://github.com/fossasia/apps.loklak.org/pull/279

Live app: http://apps.loklak.org/LoklakWordCloud/

Developing the app

The main challenge in developing this app is implementing its prime feature, that is, generating the word cloud. How do we get a dynamic word cloud which can be easily generated by the user based on the word he has entered? Well, here comes in Jqcloud. An awesome lightweight Jquery plugin for generating word clouds. All we need to do is provide list of words along with their weights.

Let us see step by step how this app (first version) works. First we require all the tweets which contain the entered word. For this we use Loklak search service. Once we get all the tweets, then we can parse the tweet body to create a list of words along with their frequency.

var url = "http://35.184.151.104/api/search.json?callback=JSON_CALLBACK&count=100&q=" + query;
        $http.jsonp(url)
            .then(function (response) {
                $scope.createWordCloudData(response.data.statuses);
                $scope.tweet = null;
            });

Once we have all the tweets, we need to extract the tweet texts and create a list of valid words. What are valid words? Well words like ‘the’, ‘is’, ‘a’, ‘for’, ‘of’, ‘then’, does not provide us with any important information and will not help us in doing any kind of analysis. So there is no use of including them in our word cloud. Such words are called stop words and we need to get rid of them. For this we are using a list of commonly used stop words. Such lists can be very easily found over the internet. Here is the list which we are using. Once we are able to extract the text from the tweets, we need to filter stop words and insert the valid words into a list.

 tweet = data[i];
            tweetWords = tweet.text.replace(", ", " ").split(" ");

            for (var j = 0; j < tweetWords.length; j++) {
                word = tweetWords[j];
                word = word.trim();
                if (word.startsWith("'") || word.startsWith('"') || word.startsWith("(") || word.startsWith("[")) {
                    word = word.substring(1);
                }
                if (word.endsWith("'") || word.endsWith('"') || word.endsWith(")") || word.endsWith("]") ||
                    word.endsWith("?") || word.endsWith(".")) {
                    word = word.substring(0, word.length - 1);
                }
                if (stopwords.indexOf(word.toLowerCase()) !== -1) {
                    continue;
                }
                if (word.startsWith("#") || word.startsWith("@")) {
                    continue;
                }
                if (word.startsWith("http") || word.startsWith("https")) {
                    continue;
                }
                $scope.filteredWords.push(word);
            }

What are we actually doing in the above snippet? We are simply iterating over each of the statuses returned by Loklak API. For each tweet, first we are splitting the text into words and then we are iterating over those words. For a given word we do a number of checks. First we check if the word begins or ends with a special character, for example quotation marks or brackets. If so we remove those character as it will cause trouble in calculating frequencies. Next we also check if the word is beginning with ‘#’ or ‘@’. If it is true, then we discard such words as we are handling hashtags and mentions separately. Finally we check whether the word is a stop word or not. If it is a stop word then we discard it. If a word passes all the checks, we add it to our list of valid words.

Once we are done with the tweet bodies, next we need to handle hashtags and mentions.

tweet.hashtags.forEach(function (hashtag) {
                $scope.filteredWords.push("#" + hashtag);
            });

            tweet.mentions.forEach(function (mention) {
                $scope.filteredWords.push("@" + mention);
            });

The above code simply iterates over the hashtags and mentions and inserts them into the filteredWords list. We have handled hashtags and mentions separately so that we can apply filters in future.

Once we are done with generating list of valid words, we need to calculate weight for each of the word. Here weight is nothing but the number of times a particular word is present in the list. We calculate this using JavaScript object. We iterate over the list of valid words. If word is not present in the object (or dictionary as you wish to call it), we create a new key by the name of that word and set its value to one. If a word is already present as a key, then we simply increment its value by one.

for (var word in $scope.wordFreq) {
            $scope.wordCloudData.push({
                text: word,
                weight: $scope.wordFreq[word]
            });
        }

The above code snippet calculates the frequency of each word by the process mentioned above.

Now we are all set to generate our word cloud. We simply use Jqcloud’s interface to configure it with the words and their respective frequencies, provide a list of color codes for a color gradient, and set autoResize to true so that our word cloud resizes itself when the screen size changes.

$scope.generateWordCloud = function() {
        if ($scope.wordCloud === null) {
            $scope.wordCloud = $('.wordcloud').jQCloud($scope.wordCloudData, {
                colors: ["#D50000", "#FF5722", "#FF9800", "#4CAF50", "#8BC34A", "#4DB6AC", "#7986CB", "#5C6BC0", "#64B5F6"],
                fontSize: {
                    from: 0.06,
                    to: 0.01
                },
                autoResize: true
            });
        } else {
            $scope.wordCloud = $(".wordcloud").jQCloud('update', $scope.wordCloudData);
        }
    }

Whenever the user searches for a new word, we simply update the existing word cloud with the cloud of the new word.

Future roadmap

  • Make the words in the cloud clickable. On clicking a word, the cloud should get replaced by the selected word’s cloud.
  • Add filters for hashtags, mentions, date.
  • Add option for exporting the cloud to an image, so that user’s can also use this app as a tool to generate word clouds as images and save them.
  • Add a loader and error notification for invalid or empty input.

Important resources

  • View the app source code here.
  • Learn more about Loklak API here.
  • Learn more about Jqcloud here.
  • Learn more about AngularJS here.
Continue ReadingDeveloping LoklakWordCloud app for Loklak apps site

Visualising Tweet Statistics in MultiLinePlotter App for Loklak Apps

MultiLinePlotter app is now a part of Loklak apps site. This app can be used to compare aggregations of tweets containing a particular query word and visualise the data for better comparison. Recently there has been a new addition to the app. A feature for showing tweet statistics like the maximum number of tweets (along with date) containing the given query word and the average number of tweets over a period of time. Such statistics is visualised for all the query words for better comparison.

Related issue: https://github.com/fossasia/apps.loklak.org/issues/236

Obtaining Maximum number of tweets and average number of tweets

Before visualising the statistics we need to obtain them. For this we simply need to process the aggregations returned by the Loklak API. Let us start with maximum number of tweets containing the given keyword. What we actually require is what is the maximum number of tweets that were posted and contained the user given keyword and on which date the number was maximum. For this we can use a function which will iterate over all the aggregations and return the largest along with date.

$scope.getMaxTweetNumAndDate = function(aggregations) {
        var maxTweetDate = null;
        var maxTweetNum = -1;

        for (date in aggregations) {
            if (aggregations[date] > maxTweetNum) {
                maxTweetNum = aggregations[date];
                maxTweetDate = date;
            }
        }

        return {date: maxTweetDate, count: maxTweetNum};
    }

The above function maintains two variables, one for maximum number of tweets and another for date. We iterate over all the aggregations and for each aggregation we compare the number of tweets with the value stored in the maxTweetNum variable. If the current value is more than the value stored in that variable then we simply update it and keep track of the date. Finally we return an object containing both maximum number of tweets and the corresponding date.Next we need to obtain average number of tweets. We can do this by summing up all the tweet frequencies and dividing it by number of aggregations.

$scope.getAverageTweetNum = function(aggregations) {
        var avg = 0;
        var sum = 0;

        for (date in aggregations) {
            sum += aggregations[date];
        }

        return parseInt(sum / Object.keys(aggregations).length);
    }

The above function calculates average number of tweets in the way mentioned before the snippet.

Next for every tweet we need to store these values in a format which can easily be understood by morris.js. For this we use a list and store the statistics values for individual query words as objects and later pass it as a parameter to morris.

var maxStat = $scope.getMaxTweetNumAndDate(aggregations);
        var avg = $scope.getAverageTweetNum(aggregations);

        $scope.tweetStat.push({
            tweet: $scope.tweet,
            maxTweetCount: maxStat.count,
            maxTweetOn: maxStat.date,
            averageTweetsPerDay: avg,
            aggregationsLength: Object.keys(aggregations).length
        });

We maintain a list called tweetStat and the list contains objects which stores the query word and the corresponding values.

Apart from plotting these statistics, the app also displays the statistics when user clicks on an individual treat present in the search record section. For this we filter tweetStat list mentioned above and get the required object corresponding to the query word the user selected bind it to angular scope. Next we display it using HTML.

<div class="tweet-stat max-tweet">
                  <div class="stat-label"> <h4>Maximum number of tweets containing '{{modalHeading}}' :</h4></div>
                  <div class="stat-value"> <strong>{{selectedTweetStat.maxTweetCount}}</strong> tweets on
                    <strong>{{selectedTweetStat.maxTweetOn}}</strong>
                  </div>
                </div>

Finally we need to plot the statistics. For this we use a function called plotStatGraph dedicated only for plotting statistics graph. We pass the tweetStat list as a parameter to morris and configure all the other parameters.

$scope.plotStatGraph = function() {
        $scope.plotStat = new Morris.Bar({
            element: 'graph',
            data: $scope.tweetStat,
            xkey: 'tweet',
            ykeys: ['maxTweetCount', 'averageTweetsPerDay'],
            labels: ['Maximum no. of tweets : ', 'Average no. of tweets/day'],
            parseTime: false,
            hideHover: 'auto',
            resize: true,
            stacked: true,
            barSizeRatio: 0.40
        });
        $scope.graphLoading = false;
    }

But now we have two graphs. One for showing variations in aggregation and the other for showing statistics. How do we manage them? Somehow we need to show them in the same page as this is a single page app. Also we need to avoid vertical scrolling as it would degrade both UI and UX. So we need to implement a switching mechanism. The user should be able to switch between the two graph views as per their wish. How to achieve that? Well, for this we maintain a global variable which will keep track of the current plot type. If the current graph type is aggregations then we call the function to plot aggregations otherwise we call the above mentioned function to plot statistics.

$scope.plotData = function() {
        $(".plot-data").html("");
        if ($scope.currentGraphType === "aggregations") {
            $scope.plotAggregationGraph();
        } else {
            $scope.plotStatGraph();
        }
    }

Lastly we integrate this state variable (currentGraphType) with the UI so that users can easily toggle between graph views with just a click.

<div class="switch" ng-click="toggle()">
                <span ng-if="queryRecords.length !== 0" class="glyphicon glyphicon-stats"></span>
              </div>

Important resources

Continue ReadingVisualising Tweet Statistics in MultiLinePlotter App for Loklak Apps

Developing MultiLinePlotter App for Loklak

MultiLinePlotter is a web application which uses Loklak API under the hood to plot multiple tweet aggregations related to different user provided query words in the same graph. The user can give several query words and multiple lines for different queries will be plotted in the same graph. In this way, users will be able to compare tweet distribution for various keywords and visualise the comparison. All the searched queries are shown under the search record section. Clicking on a record causes a dialogue box to pop up where the individual tweets related to the query word is displayed. Users can also remove a series from the plot dynamically by just pressing the Remove button beside the query word in record section. The app is presently hosted on Loklak apps site.

Related issue – https://github.com/fossasia/apps.loklak.org/issues/225

Getting started with the app

Let us delve into the working of the app. The app uses Loklak aggregation API to get the data.

A call to the API looks something like this:

http://api.loklak.org/api/search.json?q=fossasia&source=cache&count=0&fields=created_at

A small snippet of the aggregation returned by the above API request is shown below.

"aggregations": {"created_at": {
    "2017-07-03": 3,
    "2017-07-04": 9,
    "2017-07-05": 12,
    "2017-07-06": 8,
}}

The API provides a nice date v/s number of tweets aggregation. Now we need to plot this. For plotting Morris.js has been used. It is a lightweight javascript library for visualising data.

One of the main features of this app is addition and removal of multiple series from the graph dynamically. How do we achieve that? Well, this can be achieved by manipulating the morris.js data list whenever a new query is made. Let us understand this in steps.

At first, the data is fetched using angular HTTP service.

$http.jsonp('http://api.loklak.org/api/search.json?callback=JSON_CALLBACK',
            {params: {q: $scope.tweet, source: 'cache', count: '0', fields: 'created_at'}})
                .then(function (response) {
                    $scope.getData(response.data.aggregations.created_at);
                    $scope.plotData();
                    $scope.queryRecords.push($scope.tweet);
                });

Once we get the data, getData function is called and the aggregation data is passed to it. The query word is also stored in queryRecords list for future use.

In order to plot a line graph morris.js requires a data object which will contain the required values for a series. Given below is an example of such a data object.

data: [
    { x: '2006', a: 100, b: 90 },
    { x: '2007', a: 75,  b: 65 },
    { x: '2008', a: 50,  b: 40 },
    { x: '2009', a: 75,  b: 65 },
],

For every ‘x’, ‘a’ and ‘b’ will be plotted. Thus two lines will be drawn. Our app will also maintain a data list like the one shown above, however, in our case, the data objects will have a variable number of keys. One key will determine the ‘x’ value and other keys will determine the ordinates (number of tweets).

All the data objects present in the data list needs to be updated whenever a new search is done.

The getData function does this for us.

var value = $scope.tweet;
        for (date in aggregations) {
            var present = false;
            for (var i = 0; i < $scope.data.length; i++) {
                var item = $scope.data[i];
                if (item['day'] === date) {
                    item[[value]] = aggregations[date];
                    $scope.data[i] = item
                    present = true;
                    break;
                }
            }
            if (!present) {
                $scope.data.push({day: date, [value]: aggregations[date]});
            }
        }


The for loop in the above code snippet updates the global data list used by morris.js. It simply iterates over the dates in the aggregation, extracts the object corresponding to a particular date, adds the new query word as a key and, the number of tweets on that date as the value.If a date is not already present in the list, then it inserts a new object corresponding to the date and query word. Once our data list is updated, we are ready to redraw the graph with the updated data. This is done using plotData function. The plotData function simply checks the user selected graph type. If the selected type is aggregations then it calls plotAggregationGraph() to redraw the aggregations plot.

$scope.remove = function(record) {
        $scope.queryRecords = $scope.queryRecords.filter(function(e) {
            return e !== record });

        $scope.data.forEach(function(item) {
            delete item[record];
        });

        $scope.data = $scope.data.filter(function(item) {
            return Object.keys(item).length !== 1;
        });

        $scope.ykeys = $scope.ykeys.filter(function(item) {
            return item !== record;
        });

        $scope.labels = $scope.labels.filter(function(item) {
            return item !== record;
        });

        $scope.plotData();
}

The above function simply scans the data list, filters the objects which contains selected record as a key and removes them using filter method of javascript arrays. It also removes the corresponding labels and entries from labels and ykeys arrays. Finally, it once again calls plotData function to redraw the plot.

Given below is a sample plot generated by this app with the query words – google, android, microsoft, samsung.

 

Conclusion

This blog post explained how multiple series are plotted dynamically in the MultiLinePlotter app. Apart from aggregations plot it also plots tweet statistics like maximum tweets and average tweets containing a query word and visualises them using stacked bar chart. I will be discussing about them in my subsequent blogs.

Important resources

Continue ReadingDeveloping MultiLinePlotter App for Loklak