Introducing Priority Kaizen Harvester for loklak server

In the previous blog post, I discussed the changes made in loklak’s Kaizen harvester so it could be extended and other harvesting strategies could be introduced. Those changes made it possible to introduce a new harvesting strategy as PriorityKaizen harvester which uses a priority queue to store the queries that are to be processed. In this blog post, I will be discussing the process through which this new harvesting strategy was introduced in loklak.

Background, motivation and approach

Before jumping into the changes, we first need to understand that why do we need this new harvesting strategy. Let us start by discussing the issue with the Kaizen harvester.

The produce consumer imbalance in Kaizen harvester

Kaizen uses a simple hash queue to store queries. When the queue is full, new queries are dropped. But numbers of queries produced after searching for one query is much higher than the consumption rate, i.e. the queries are bound to overflow and new queries that arrive would get dropped. (See loklak/loklak_server#1156)

Learnings from attempt to add blocking queue for queries

As a solution to this problem, I first tried to use a blocking queue to store the queries. In this implementation, the producers would get blocked before putting the queries in the queue if it is full and would wait until there is space for more. This way, we would have a good balance between consumers and producers as the consumers would be waiting until producers can free up space for them –

public class BlockingKaizenHarvester extends KaizenHarvester {
   public BlockingKaizenHarvester() {
       super(new KaizenQueries() {
           private BlockingQueue<String> queries = new ArrayBlockingQueue<>(maxSize);

           public boolean addQuery(String query) {
               if (this.queries.contains(query)) {
                   return false;
               try {
                   this.queries.offer(query, this.blockingTimeout, TimeUnit.SECONDS);
                   return true;
               } catch (InterruptedException e) {
                   DAO.severe("BlockingKaizen Couldn't add query: " + query, e);
                   return false;
           public String getQuery() {
               try {
                   return this.queries.take();
               } catch (InterruptedException e) {
                   DAO.severe("BlockingKaizen Couldn't get any query", e);
                   return null;

[SOURCE, loklak/loklak_server#1210]

But there is an issue here. The consumers themselves are producers of even higher rate. When a search is performed, queries are requested to be appended to the KaizenQueries instance for the object (which here, would implement a blocking queue). Now let us consider the case where queue is full and a thread requests a query from the queue and scrapes data. Now when the scraping is finished, many new queries are requested to be inserted to most of them get blocked (because the queue would be full again after one query getting inserted).

Therefore, using a blocking queue in KaizenQueries is not a good thing to do.

Other considerations

After the failure of introducing the Blocking Kaizen harvester, we looked for other alternatives for storing queries. We came across multilevel queues, persistent disk queues and priority queues.

Multilevel queues sounded like a good idea at first where we would have multiple queues for storing queries. But eventually, this would just boil down to how much queue size are we allowing and the queries would eventually get dropped.

Persistent disk queues would allow us to store greater number of queries but the major disadvantage was lookup time. It would terribly slow to check if a query already exists in the disk queue when the queue is large. Also, since the queries would always increase practically, the disk queue would also go out of hand at some point in time.

So by now, we were clear that not dropping queries is not an alternative. So what we had to use the limited size queue smartly so that we do not drop queries that are important.

Solution: Priority Queue

So a good solution to our problem was a priority queue. We could assign a higher score to queries that come from more popular Tweets and they would go higher in the queue and do not drop off until we have even higher priority queried in the queue.

Assigning score to a Tweet

Score for a tweet was decided using the following formula –

α= 5* (retweet count)+(favourite count)


This equation generates a score between zero and one from the retweet and favourite count of a Tweet. This normalisation of score would ensure we do not assign an insanely large score to Tweets with a high retweet and favourite count. You can see the behaviour for the second mentioned equation here.


Changes required in existing Kaizen harvester

To take a score into account, it became necessary to add an interface to also provide a score as a parameter to the addQuery() method in KaizenQueries. Also, not all queries can have a score associated with it, for example, if we add a query that would search for Tweets older than the oldest in the current timeline, giving it a score wouldn’t be possible as it would not be associated with a single Tweet. To tackle this, a default score of 0.5 was given to these queries –

public abstract class KaizenQueries {

   public boolean addQuery(String query) {
       return this.addQuery(query, 0.5);

   public abstract boolean addQuery(String query, double score);


Defining appropriate KaizenQueries object

The KaizenQueries object for a priority queue had to define a wrapper class that would hold the query and its score together so that they could be inserted in a queue as a single object.

ScoreWrapper and comparator

The ScoreWrapper is a simple class that stores score and query object together –

private class ScoreWrapper {

   private double score;
   private String query;

   ScoreWrapper(String m, double score) {
       this.query = m;
       this.score = score;



In order to define a way to sort the ScoreWrapper objects in the priority queue, we need to define a Comparator for it –

private Comparator<ScoreWrapper> scoreComparator = (scoreWrapper, t1) -> (int) (scoreWrapper.score - t1.score);


Putting things together

Now that we have all the ingredients to declare our priority queue, we can also declare the strategy to getQuery and putQuery in the corresponding KaizenQueries object –

public class PriorityKaizenHarvester extends KaizenHarvester {

   private static class PriorityKaizenQueries extends KaizenQueries {
       private Queue<ScoreWrapper> queue;
       private int maxSize;

       public PriorityKaizenQueries(int size) {
           this.maxSize = size;
           queue = new PriorityQueue<>(size, scoreComparator);

       public boolean addQuery(String query, double score) {
           ScoreWrapper sw = new ScoreWrapper(query, score);
           if (this.queue.contains(sw)) {
               return false;
           try {
               return true;
           } catch (IllegalStateException e) {
               return false;

       public String getQuery() {
           return this.queue.poll().query;



In this blog post, I discussed the process in which PriorityKaizen harvester was introduced to loklak. This strategy is a flavour of Kaizen harvester which uses a priority queue to store queries that are to be processed. These changes were possible because of a previous patch which allowed extending of Kaizen harvester.

The changes were introduced in pull request loklak/loklak#1240 by @singhpratyush (me).


Continue Reading Introducing Priority Kaizen Harvester for loklak server

Fetching URL for Embedded Twitter Videos in loklak server

The primary web service that loklak scrapes is Twitter. Being a news and social networking service, Twitter allows its users to post videos directly to Twitter and they convey more thoughts than what text can. But for an automated scraper, getting the links is not a simple task.

Let us see that what were the problems we faced with videos and how we solved them in the loklak server project.

Previous setup and embedded videos

In the previous version of loklak server, the TwitterScraper searched for videos in 2 ways –

  1. Youtube links
  2. HTML5 video links

To fetch the video URL from HTML5 video, following snippet was used –

if ((p = input.indexOf("<source video-src")) >= 0 && input.indexOf("type=\"video/") > p) {
   String video_url = new prop(input, p, "video-src").value;

Here, input is the current line from raw HTML that is being processed and prop is a class defined in loklak that is useful in parsing HTML attributes. So in this way, the HTML5 videos were extracted.

The Problem – Embedded videos

Though the previous setup had no issues, it was useless as Twitter embeds the videos in an iFrame and therefore, can’t be fetched using simple HTML5 tag extraction.

If we take the following Tweet for example,

the requested HTML from the search page contains video in following format –

<src="" allowfullscreen="" id="player_tweet_881946694413422593" style="width: 100%; height: 100%; position: absolute; top: 0; left: 0;">

So we needed to come up with a better technique to get those videos.

Parsing video URL from iFrame

The <div> which contains video is marked with AdaptiveMedia-videoContainer class. So if a Tweet has an iFrame containing video, it will also have the mentioned class.

Also, the source of iFrame is of the form{Tweet-ID}. So now we can programmatically go to any Tweet’s video and parse it to get results.

Extracting video URL from iFrame source

Now that we have the source of iFrame, we can easily get the video source using the following flow –

public final static Pattern videoURL = Pattern.compile("video_url\\\":\\\"(.*?)\\\"");

private static String[] fetchTwitterIframeVideos(String iframeURL) {
   // Read fron iframeURL line by line into BufferReader br
   while ((line = br.readLine()) != null ) {
       int index;
       if ((index = line.indexOf("data-config=")) >= 0) {
           String jsonEscHTML = (new prop(line, index, "data-config")).value;
           String jsonUnescHTML = HtmlEscape.unescapeHtml(jsonEscHTML);
           Matcher m = videoURL.matcher(jsonUnescHTML);
           if (!m.find()) {
               return new String[]{};
           String url =;
           url = url.replace("\\/", "/");  // Clean URL
            * Play with url and return results

MP4 and M3U8 URLs

If we encounter mp4 URLs, we’re fine as it is the direct link to video. But if we encounter m3u8 URL, we need to process it further before we can actually get to the videos.

For Twitter, the hosted m3u8 videos contain link to further m3u8 videos which are of different resolution. These m3u8 videos again contain link to various .ts files that contain actual video in parts of 3 seconds length each to support better streaming experience on the web.

To resolve videos in such a setup, we need to recursively parse m3u8 files and collect all the .ts videos.

private static String[] extractM3u8(String url) {
   return extractM3u8(url, "");

private static String[] extractM3u8(String url, String baseURL) {
   // Read from baseURL + url line by line
   while ((line = br.readLine()) != null) {
       if (line.startsWith("#")) {  // Skip comments in m3u8
       String currentURL = (new URL(new URL(baseURL), line)).toString();
       if (currentURL.endsWith(".m3u8")) {
           String[] more = extractM3u8(currentURL, baseURL);  // Recursively add all
           Collections.addAll(links, more);
       } else {
   return links.toArray(new String[links.size()]);

And then in fetchTwitterIframeVideos, we can return the all .ts URLs for the video –

if (url.endsWith(".mp4")) {
   return new String[]{url};
} else if (url.endsWith(".m3u8")) {
   return extractM3u8(url);

Putting things together

Finally, the TwitterScraper can discover the video links by tweaking a little –

if (input.indexOf("AdaptiveMedia-videoContainer") > 0) {
   // Fetch Tweet ID
   String tweetURL = props.get("tweetstatusurl").value;
   int slashIndex = tweetURL.lastIndexOf('/');
   if (slashIndex < 0) {
   String tweetID = tweetURL.substring(slashIndex + 1);
   String iframeURL = "" + tweetID;
   String[] videoURLs = fetchTwitterIframeVideos(iframeURL);
   Collections.addAll(videos, videoURLs);


This blog post explained the process of extracting video URL from Twitter and the problem faced. The discussed change enabled loklak to extract and serve URLs to video for tweets. It was introduced in PR loklak/loklak_server#1193 by me (@singhpratyush).

The service was further enhanced to collect single mp4 link for videos (see PR loklak/loklak_server#1206), which is discussed in another blog post.


Continue Reading Fetching URL for Embedded Twitter Videos in loklak server

Documenting APIs with Yaydoc

API Documentation is a quick and concise way to tell a user about how to use a library or work with a program. It details classes, functions, parameters, return types and more. Courtesy of Sphinx, Yaydoc had build in support for Documenting APIs for Python based projects right from it’s inception. Sphinx has a built in tool autodoc which provides certain directives such as autoclass, automodule, etc which can be used to automatically extract docstrings from all specified Python packages and modules and use it to generate API documentation. As a user of Yaydoc you could add ReST sources files with appropriate directives provided by autodoc and we would handle the rest. As part of enhancing this feature we wanted to do three things.

  • Enhance support for Python
  • Extend API documentation to other languages apart from Python
  • Automate the process of generating ReST source files

For Enhancing support for python projects, we implemented a few things.

Since autodoc imports the modules it needs to document, There could be import errors if a dependency was not met. To fix this issue, Now a user can specify certain modules to be mocked. This would really come in handy with projects depending on packages with third party C extensions such as numpy, scipy, etc.

{% if mock_modules %}
mock_modules = [name.strip() for name in '{{ mock_modules }}'.split(',')]
sys.modules.update((mod_name, mock.Mock()) for mod_name in mock_modules)
{% endif %}

Apart from this, if we detect a in the repository or a requirements.txt, we automatically try to install from it to meet dependencies.

# autodoc imports the module while building source files. To avoid
# ImportError, install any packages in requirements.txt of the project
# if available
if [ -f $ROOT_DIR/ ]; then
  pip install $ROOT_DIR/
elif [ -f $ROOT_DIR/requirements.txt ]; then
  pip install -q -r $ROOT_DIR/requirements.txt

We also crawl the repository to detect any packages and add them to sys.path. With these changes, a user can expected generated API docs without having to extend

{% if autoapi_python == 'true' %}
for (dirpath, dirnames, filenames) in os.walk('{{ root_dir }}'):
    # Directory contains It should be a python package
    if '' in filenames:
        # appending instead of inserting at front so that user
        # cannot overwrite some of our own modules.
{% endif %}

The second goal is a no brainer. We would like to support as many languages as we can. With this week’s update, Java has been added to the officially supported list of languages for which Yaydoc can generate full API documentation without any manual intervention. To extract API documentation for java source files, we used a sphinx extension named javasphinx. From the official javasphinx docs,

javasphinx is a Sphinx extension that provides a Sphinx domain for documenting Java projects and a javasphinx-apidoc command line tool for automatically generating API documentation from existing Java source code and Javadoc documentation.

javasphinx-apidoc -o source/ $ROOT_DIR/$AUTOAPI_JAVA_PATH/
sphinx-apidoc -o source/ $ROOT_DIR/$AUTOAPI_PYTHON_PATH/

For the third goal, we use the tools sphinx-apidoc and javasphinx-apidoc to generate source files.


Continue Reading Documenting APIs with Yaydoc

JSON Deserialization Using Jackson in Open Event Android App

The Open Event project uses JSON format for transferring event information like tracks, sessions, microlocations and other. The event exported in the zip format from the Open Event server also contains the data in JSON format. The Open Event Android application uses this JSON data. Before we use this data in the app, we have to parse the data to get Java objects that can be used for populating views. Deserialization is the process of converting JSON data to Java objects. In this post I explain how to deserialize JSON data using Jackson.

1. Add dependency

In order to use Jackson in your app add following dependencies in your app module’s build.gradle file.

dependencies {
	compile 'com.fasterxml.jackson.core:jackson-core:2.8.9'
	compile 'com.fasterxml.jackson.core:jackson-annotations:2.8.9'
	compile 'com.fasterxml.jackson.core:jackson-databind:2.8.9'

2.  Define entity model of data

In the Open Event Android we have so many models like event, session, track, microlocation, speaker etc. Here i am only defining track model because of it’s simplicity and less complexity.

public class Track {

	private int id;
	private String name;
	private String description;
	private String color;
	private String fontColor;
	//getters and setters

Here if the property name is same as json attribute key then no need to add JsonProperty annotation like we have done for id, name color property. But if property name is different from json attribute key then it is necessary to add JsonProperty annotation.

3.  Create sample JSON data

Let’s create sample JSON format data we want to deserialize.

        "id": 273,
        "name": "Android",
        "description": "Sample track",
        "color": "#94868c",
        "font-color": "#000000"

4.  Deserialize using ObjectMapper

ObjectMapper is Jackson serializer/deserializer. ObjectMapper’s readValue() method is used for simple deserialization. It takes two parameters one is JSON data we want to deserialize and second is Model entity class. Create an ObjectMapper object and initialize it.

ObjectMapper objectMapper = new ObjectMapper();

Now create a Model entity object and initialize it with deserialized data from ObjectMapper’s readValue() method.

Track track = objectMapper.readValue(json, Track.class);

So we have converted JSON data into the Java object.

Jackson is very powerful library for JSON serialization and deserialization. To learn more about Jackson features follow the links given below.

Continue Reading JSON Deserialization Using Jackson in Open Event Android App

Cache Thumbnails and Images Using Picasso in Open Event Android

In the event based Android projects like Open Event Android, we have speakers and sponsors. And these projects needs to display image of the speakers and sponsors because it affects project a lot. So instead of every time fetching image from the server it is good to store small images(thumbnails) in the cache and load images even if device is offline. It also reduces data usage.

Picasso is mostly used image loading library for Android. It automatically handles ImageView recycling and download cancellation in an adapter, complex image transformations with minimal memory use, memory and disk caching.

But one problem is Picasso caches images for only one session by default. I mean if you close the app then all by default cached image will be removed.  If you are offline then Picasso will not load cached images because of it. It will make network calls every time you open the app.

In this post I explain how to manually cache images using Picasso so that images load even if the device is offline. It will make a network call only once for a particular image and will cache image in memory.

We will use okhttp3 library for OkHttpClient.

1. Add dependency

In order to use Picasso in your app add following dependencies in your app module’s build.gradle file.

dependencies {
        compile 'com.squareup.okhttp3:okhttp:3.8.1'
        compile 'com.squareup.picasso:picasso:2.5.2'

2. Make static Picasso object

Make static Picasso object in the Application class so that we can use it directly from the other activity.

public static Picasso picassoWithCache;

3. Initialize cache

Create a File object with path as app specific cache and use this object to create a Cache object.

File httpCacheDirectory = new File(getCacheDir(), "picasso-cache");
Cache cache = new Cache(httpCacheDirectory, 15 * 1024 * 1024);

Here it will create a Cache object with 15MB. getCacheDir() method returns the absolute path to the application specific cache directory on the filesystem.

OkHttpClient.Builder okHttpClientBuilder = new OkHttpClient.Builder().cache(cache);

4. Initialize Picasso with cache

Now initialize picassoWithCache object using Picass.Builder(). Set downloader for picasso by adding  new OkHttp3Downloader object.

picassoWithCache = new Picasso.Builder(this).downloader(new OkHttp3Downloader(;

5. Use picassoWithCache object

As it is a static object you can directly use it from any activity. All the images loaded using this picassoWithCache instance will be cached in memory.

Application.picassoWithCache().load(thumbnail/image url);


To know more how i solved this issue in Open Event Project visit this link. To learn more about Picasso features follow the links given below.

Continue Reading Cache Thumbnails and Images Using Picasso in Open Event Android

Implementing Loklak APIs in Java using Reflections

Loklak server provides a large API to play with the data scraped by it. Methods in java can be implemented to use these API endpoints. A common approach of implementing the methods for using API endpoints is to create the request URL by taking the values passed to the method, and then send GET/POST request. Creating the request URL in every method can be tiresome and in the long run maintaining the library if implemented this way will require a lot of effort. For example, assume a method is to be implemented for suggest API endpoint, which has many parameters, for creating request URL a lot of conditionals needs to be written – whether a parameter is provided or not.

Well, the methods to call API endpoints can be implemented with lesser and easy to maintain code using Reflection in Java. The post ahead elaborates the problem, the approach to solve the problem and finally solution which is implemented in loklak_jlib_api.

Let’s say, the status API endpoint needs to be implemented, a simple approach can be:

public class LoklakAPI {
    public static String status(String baseUrl) {
        String requestUrl = baseUrl   "/api/status.json";
        // GET request using requestUrl 

    public static void main(String[] argv) {
        JSONObject result = status("");

This one is easy, isn’t it, as status API endpoint requires no parameters. But just imagine if a method implements an API endpoint that has a lot of parameters, and most of them are optional parameters. As a developer, you would like to provide methods that cover all the parameters of the API endpoint. For example, how a method would look like if it implements suggest API endpoint, the old SuggestClient implementation in loklak_jlib_api does that:

public static ResultList<QueryEntry> suggest(
           final String hostServerUrl,
           final String query,
           final String source,
           final int count,
           final String order,
           final String orderBy,
           final int timezoneOffset,
           final String since,
           final String until,
           final String selectBy,
           final int random) throws JSONException, IOException {
       ResultList<QueryEntry>  resultList = new ResultList<>();
       String suggestApiUrl = hostServerUrl
               + SUGGEST_API
               + URLEncoder.encode(query.replace(' ', '+'), ENCODING)
               + PARAM_TIMEZONE_OFFSET + timezoneOffset
               + PARAM_COUNT + count
               + PARAM_SOURCE + (source == null ? PARAM_SOURCE_VALUE : source)
               + (order == null ? "" : (PARAM_ORDER + order))
               + (orderBy == null ? "" : (PARAM_ORDER_BY + orderBy))
               + (since == null ? "" : (PARAM_SINCE + since))
               + (until == null ? "" : (PARAM_UNTIL + until))
               + (selectBy == null ? "" : (PARAM_SELECT_BY + selectBy))
               + (random < 0 ? "" : (PARAM_RANDOM + random))
                // GET request using suggestApiUrl

A lot of conditionals!!! The targeted users may also get irritated if they need to provide all the parameters every time even if they don’t need them. The obvious solution to that is overloading the methods. But,  then again for each overloaded method, the same repetitive conditionals need to be written, a form of code duplication!! And what if you have to implement some 30 API endpoints and in future maintaining them, a single thought of it is scary and a nightmare for the developers.

Approach to the problem

To reduce the code size, one obvious thought that comes is to implement static methods that send GET/POST requests provided request URL and the required data. These methods are implemented in loklak_jlib_api by JsonIO and NetworkIO.

You might have noticed the method name i.e. status, suggest is also the part of the request URL. So, the common pattern that we get is:

base_url + "/api/" + methodName + ".json" + "?" + firstParameterName + "=" + firstParameterValue + "&" + secondParameterName + "=" + secondParameterValue ...

Reflection API to rescue

Using Reflection API inspection of classes, interfaces, methods, and variables can be done, yes you guessed it right if we can inspect we can get the method and parameter names. It is also possible to implement interfaces and create objects at runtime.

So, an interface is created and API endpoint methods are defined in it. Using reflection API the interface is implemented lazily at runtime. LoklakAPI interface defines all the API endpoint methods. Some of the defined methods are:

public interface LoklakAPI {
    @interface GET {}
    @interface POST {}
    JSONObject search(String q);
    JSONObject search(String q, int count);
    JSONObject search(String q, int timezoneOffset, String since, String until);
    JSONObject search(String q, int timezoneOffset, String since, String until, int count);
    JSONObject peers();
    JSONObject hello();
    JSONObject status();
    JSONObject push(JSONObject data);

Here GET and POST annotations are used to mark the methods which use GET and POST request respectively, so that appropriate method for GET and POST static method can be used JsonIOloadJson for GET request and pushJson for POST request.

A private static inner class ApiInvocationHandler is created in APIGenerator, which implements InvocationHandler – used for implementing interfaces at runtime.

private static class ApiInvocationHandler implements InvocationHandler {
   private String mBaseUrl;
   public ApiInvocationHandler(String baseUrl) {
       this.mBaseUrl = baseUrl;
   public Object invoke(Object o, Method method, Object[] values) throws Throwable {
       Parameter[] params = method.getParameters();
       Object[] paramValues = values;
       format of annotation name:
       Example: @org.loklak.client.LoklakAPI$GET()
       Annotation annotation = method.getAnnotations()[0];
       String annotationName = annotation.toString().toLowerCase();
       String apiUrl = createGetRequestUrl(mBaseUrl, method.getName(),
               params, paramValues);
       if (annotationName.contains("get")) { // GET REQUEST
           return loadJson(apiUrl);
       } else { // POST REQUEST
           JSONObject jsonObjectToPush = (JSONObject) paramValues[0];
           String postRequestUrl = createPostRequestUrl(mBaseUrl, method.getName());
           return pushJson(postRequestUrl, params[0].getName(), jsonObjectToPush);

The base URL is provided while creating the object, in the constructor. The invoke method is called whenever a defined method in the interface is called in actual code. This way an interface is implemented at runtime. The parameters of invoke method:

  • Object o – the object on which to call the method.
  • Method method – method which is called, parameters and annotations of the method are obtained using getParameters and getAnnotations methods respectively which are required to create our request url.
  • Object[] values – an array of parameter values which are passed to the method when calling it.

createGetRequestUrl is used to create the request URL for sending GET requests.

private static String createGetRequestUrl(
       String baseUrl, String methodName, Parameter[] params, Object[] paramValues) {
   String apiEndpointUrl = baseUrl.replaceAll("/+$", "") + "/api/" + methodName + ".json";
   StringBuilder url = new StringBuilder(apiEndpointUrl);
   if (params.length > 0) {
       String queryParamAndVal = "?" + params[0].getName() + "=" + paramValues[0];
       for (int i = 1; i < params.length; i++) {
           String paramAndVal = "&" + params[i].getName()
                   + "=" + String.valueOf(paramValues[i]);
   return url.toString();

Similarly, createPostRequestUrl is used to create request URL for sending POST requests.

private static String createPostRequestUrl(String baseUrl, String methodName) {
   baseUrl = baseUrl.replaceAll("/+$", "");
   return baseUrl + "/api/" + methodName + ".json";

Finally, Proxy.newProxyInstance is used to implement the interface at runtime. An instance of ApiInvocationHandler class is passed to the newProxyInstance method. This is all done by static method createApiMethods.

public static <T> T createApiMethods(Class<T> service, final String baseUrl) {
   ApiInvocationHandler apiInvocationHandler = new ApiInvocationHandler(baseUrl);
   return (T) Proxy.newProxyInstance(
           service.getClassLoader(), new Class<?>[]{service}, apiInvocationHandler);


  • Class<T> service – is the interface where API endpoint methods are defined, here LoklakAPI.class.
  • String baseUrl – web address of the server where Loklak server is hosted.

NOTE: For all this to work the library must be build using “-parameters” flag, else parameter names can’t be obtained. Since loklak_jlib_api uses maven, “-parameters” is provided in pom.xml file.

A small example:

String baseUrl = "";
LoklakAPI loklakAPI = APIGenerator.createApiMethods(LoklakAPI.class, baseUrl);
JSONObject searchResult ="FOSSAsia");
Continue Reading Implementing Loklak APIs in Java using Reflections

Using FastAdapter in Open Event Organizer Android Project

RecyclerView is an important graphical UI component in any android application. Android provides RecyclerView.Adapter class which manages all the functionality of RecyclerView. I don’t know why but android people have kept this class in a very abstract form with only basic functionalities implemented by default. On the plus side it opens many doors for custom adapters with new functionalities for example, sticky headers, scroll indicator, drag and drop actions on items, multiview types items etc. A developer should be able to make an adapter of his need by extending RecyclerView.Adapter. There are many custom adapters developers have shared which comes with built in functionalities. FastAdapter is one of them which comes with all the good functionalities built in and also it is very easy to use. I just got to use this in the Open Event Organizer Android App of which the core feature is Attendees Check In. We have used FastAdapter library to show attendees list which needs many features which are absent in plane RecyclerView.Adapter. FastAdapter is built in such way that there are many different ways of using it on developer’s need. I have found a simplest way which I will be sharing here. The first part is extending the item model to inherit AbstractItem.

public class Attendee extends AbstractItem<Attendee, AttendeeViewHolder> {
  private long id;

  public long getIdentifier() {
      return id;

  public int getType() {
      return 0;

  public int getLayoutRes() {
      return R.layout.attendee_layout;

  public AttendeeViewHolder getViewHolder(View view) {
      return new AttendeeViewHolder(DataBindingUtil.bind(view));

  public void bindView(AttendeeViewHolder holder, List<Object> list) {
      super.bindView(holder, list);

  public void unbindView(AttendeeViewHolder holder) {

The methods are pretty obvious by name. Implement these methods accordingly. You may notice that we have used Databinding here to bind data to views but it is not necessary. Also you will have to create your ViewHolder for adapter. You can either use RecyclerView.ViewHolder or you can just create a custom one by inheriting it as per your need. Once this part is over you are half done as most of the things are been taken care in model itself. Now we will be writing code for adapter and setting it to your RecyclerView.

FastItemAdapter<Attendee> fastItemAdapter = new FastItemAdapter<>();
// functionalities related code

Initialize FastItemAdapter which will be our main adapter handling all the direct functions related to the RecyclerView. Set up some boolean constants according to the project need. In our project we have Attendee model which has id as a primary field. FastItemAdapter can take advantage of distinct field of the model called as identifier . Hence it is set true as Attendee model has id field. But you should be careful about setting it to True as then you must have implemented getIdentifier in the model to return correct field which will be used as an identifier by our adapter. And the adapter is good to set to the RecyclerView.

Now we got to decide which functionalities we will be implementing to our RecyclerView. In our case we needed: 1. Search filter for attendees, 2. Sticky header for attendees groups arranged alphabetically and 3. On click listener for attendee item.

FastItemAdapter has ItemFilter adapter wrapped inside which manages all the filtering stuff. Filtering logic can be set using it.


Where shallFilter is method which takes attendee object and returns boolean whether to filter the item or not. And after this you can use FastItemAdapter’s filter method to filter the items. For sticky headers you need to implement StickyRecyclerHeadersAdapter extending AbstractAdapter. In this class you will have to implement your filter logic in getHeaderId method. This must return an unique id for items of the same group.

public long getHeaderId(int position) {
   IItem item = getItem(position);
   if(item instanceof Attendee && ((Attendee)item).getFirstName() != null)
       return ((Attendee) item).getFirstName().toUpperCase().charAt(0);
   return -1;

Like in this case we have grouped attendees alphabetically hence just returning initial character’s ASCII value will do good. You can modify this method according to your need. For other unimplemented methods just keep their default return values. With this you will also have to implement onCreateHeaderViewHolder and onBindHeaderViewHolder methods to bind view and data to the header layout. Once this is done you are ready to set sticky headers to your RecyclerView with following code:

stickyHeaderAdapter = new StickyHeaderAdapter();
final HeaderAdapter headerAdapter = new HeaderAdapter();

final StickyRecyclerHeadersDecoration decoration = new StickyRecyclerHeadersDecoration(stickyHeaderAdapter);
adapterDataObserver = new RecyclerView.AdapterDataObserver() {
   public void onChanged() {

For click listener, the code is similar to the RecyclerView.Adapter’s one.

fastItemAdapter.withOnClickListener(new FastAdapter.OnClickListener<Item>() {
  public boolean onClick(View v, IAdapter<Item> adapter, Item item, int position) {
     // your on click logic
   return true;

With this now you have successfully implemented FastItemAdapter to your RecyclerView. Although there are some important points to be taken care of. If you are using filter in your application then you will have to modify your updateItem logic. As when filter is applied to the adapter its items list is filtered. And if you are updating the item using its position from original list it then it will result in exception or updating the wrong item. So you will have to change the position to the one in filtered list. For example the updateAttendee method from Organizer App code looks like this:

public void updateAttendee(int position, Attendee attendee) {
   position = fastItemAdapter.getAdapterPosition(attendee);
   fastItemAdapter.getItemFilter().set(position, attendee);
Continue Reading Using FastAdapter in Open Event Organizer Android Project

Lambda expressions in Android

What are Lambda expressions

Lambda Expressions are one of the most important features added to Java 8. Prior to Lambda Expressions, implementing functional interfaces i.e interfaces with only one abstract method has been done using syntax that has a lot of boilerplate code in it.
In cases like this, what we are trying to do is pass a functionality as an argument to a method, such as what happens when a button is clicked.

Lambda expressions enables you to do just that, in a way that is much more compact and clear.

Syntax of Lambda Expressions

A lambda expression consist of the following:

  • A comma separated list of formal parameters enclosed in parentheses. The data types of the parameters in a lambda expression can be omitted. Also the parenthesis can be omitted if there is only one parameter. For example:
TextView tView = (TextView) findViewById(;
tView.setOnLongClickListener(v -> System.out.println("Testing Long Click"));
  • The arrow token ->
  • A body which contains a single expression or a statement block. If a single expression is specified, the java runtime evaluates the expression and then return its value. To specify a statement block, enclose statements in curly braces "{}"

Lambda Expressions in Android

To use Lambda Expressions and other Java 8 features in Android, you need to use the Jack tool-chain. Open your module level build.gradle file and add the following:

android {
  defaultConfig {
    jackOptions {
      enabled true
  compileOptions {
    sourceCompatibility JavaVersion.VERSION_1_8
    targetCompatibility JavaVersion.VERSION_1_8

Sync your build.gradle file and if you are having any issue with build tools, you may need to update buildToolsVersion in your build.gradle file to "24rc4" or just download the latest Android SDK Build-tools from the SDK Manager, under the Tools (Preview channel).


Adding a click listener to a button

without lambda expression

Button button = (Button)findViewById(;
button.setOnClickListener(button.setOnClickListener(new View.OnClickListener() {
    public void onClick(View v) {
        Toast.makeText(this, "Button clicked", Toast.LENGTH_LONG).show();

with lambda expressions It is as simple as:

Button button = (Button)findViewById(;
button.setOnClickListener(v -> Toast.makeText(this, "Button clicked", Toast.LENGTH_LONG).show(););

As we can see above, using lambda expressions makes implementing a functional interface clearer and compact. Standard functional interfaces can be found in the java.util.function package [included in Java 8]. These interfaces can be used as target types for lambda expressions and method references.

Credits :

Another way to have Java 8 features in your Android app is using the RetroLambda plugin.

Continue Reading Lambda expressions in Android