Implementing Leak Canary in PSLab Android App

This post discusses the issue of memory leaks and how to handle them efficiently and what are the tools available which help developers in managing the memory leaks. After working on PR #824 opened under PSLab – Android repository I have got a greater idea about how to manage the memory efficiently and what are the tools that should be used to ease the work.

What are memory leaks and how it affects the quality of app?

In simple words, memory leaks happen when you hold on to an item for long after its purpose have been served. It is as simple as that. But let us dive in further to understand more about this topic. Programming languages like C and C++ need memory management done by user whereas in higher level languages like Java, Python, etc. low-level memory management and garbage collection is done automatically by the system. But it is due to programming faults that memory leaks happen and so care needs to be taken with higher level languages too in handling memory efficiently.

In Android or say in any OS (operating system), every item has to be destroyed or say deleted or freed from the memory after its purpose is served. But if the reference of this object is passed on to any other object which has a greater time of importance than this, then it will try to hold this object for long and so the garbage collector won’t be able to collect it and so there will be memory leaks in the code. This is how memory leaks occurs inside an app.

Now, the issue of memory leaks is utmost important among developers as due to it, the app becomes slow, laggy, eats up a lot of memory and the app crashes after some time of use which creates a very bad user experience. As the user keeps on using the app, the heap memory also keeps on increasing and due to memory leaks, this heap can’t be freed by the garbage collector. Thus, all these issues contribute to making the threads or processes running inside the app slower and it can result in a lag of time from microseconds to milliseconds too!!

How can you detect these memory leaks?

This blog is mostly for Android developers and so I will use the environment of Android Studio for reference. For controlling memory leaks, Android Studio has a very powerful tool named Monitors. There are individual monitors not only for memory usage but for CPU, GPU, and network usage as well. An example of it is shown in figure 1 below.

Figure 1. Monitor in Android Studio

Now how to observe the graphs that are produced by Monitors to see if there are any memory leaks? The first alarming case is when the memory usage graph constantly increases and doesn’t come down as time passes and even not decreases when you put the app in the background. The tools which are used to undo memory leaks as soon as they are found are:

  1. Allocation Tracker: The allocation tracker comes with an indicator to show the percentage of memory allocated to different types of objects in your app. The developer can have a clear idea about which object is taking what amount of memory and which objects are exceeding the memory limit. But it is itself not enough as the developer needs other tools to dump the extra memory.
  2. Leak Canary Library: It is the most used library by developers to check for memory leaks in an app. This library runs along with app and dumps memory when needed, looks for potential memory leaks  and gives a notification for a memory leak with a clean trace to find the root of the leak with sub-roots attached to it as shown in figure 2 :

Figure 2. Screenshot from Leaks application made by Leak Canary for PSLab app

It is clearly visible from the image that the applications show the root of the memory leak with an indication of how much memory is leaked in the toolbar.

Explanation of leak shown in figure 2 :

In the PSLab app, there is a navigation drawer consisting of all main functionalities in it. It is as shown in figure 3 :

Figure 3. Navigation drawer in PSLab

The memory leak as shown in figure 2 originated in the following steps :

  • It started with ArrayList which is here the list of items as shown in figure 3.
  • After it comes to the ScrollContainer which helps in scrolling this list on small screens.
  • Then comes the Drawer Layout which is the actual layout seen in figure 3 that slides over the main layout which is here the Instruments layout.
  • At last, comes the InputMethodManager which is introduced by Leak Canary library which watches the activity that is being opened.
  • Here, InputMethodManager kept watching on Drawer Layout but after closing the layout too it referenced it which is due to the source code of LeakCanary Library and so memory Leak occurred.

How to stop this leak from occurring ?

A simple way is to add a transparent activity as soon as the layout is closed for a very small time i.e. 500 ms so that the reference watcher gets shifted from the actual layout. This solution is based on the article published on Medium [5].

How to implement Leak Canary in your app?

Below is the step-by-step guide on implementing Leak Canary library in your app to implement a watcher for memory leaks :

    • Add dependencies (App Level) in your project to implement Leak Canary
debugImplementation 'com.squareup.leakcanary:leakcanary-android:1.5.4'
releaseImplementation 'com.squareup.leakcanary:leakcanary-android-no-op:1.5.4'
testImplementation 'com.squareup.leakcanary:leakcanary-android-no-op:1.5.4'
      1. debugImplementation – For debug flavor of app
      2. releaseImplementation – For release flavor of app
      3. testImplementation – For testing the current flavor of the app

Add dependencies according to the need for the application.

Add Realm dependencies (Project Level) in your app to create a database which can be used by Leak Canary to maintain and provide crash reports as shown in the figure above.

NOTE: Any database can be used here according to the need of the app

buildscript {
            repositories {
            dependencies {
                classpath "io.realm:realm-gradle-plugin:0.88.2"
 apply plugin: 'realm-android'

App-level dependency :

compile 'io.realm:android-adapters:2.0.0'
  • Add an activity class in your application to construct the Leak Canary for your entire application. In PSLab Android application, it was made as under :
package org.fossasia.pslab;


import com.squareup.leakcanary.LeakCanary;
import com.squareup.leakcanary.RefWatcher;

import io.realm.Realm;

public class PSLabApplication extends Application {

	public RefWatcher refWatcher;

	public void onCreate() {


	private void initializeLeakCanary() {
    	if (LeakCanary.isInAnalyzerProcess(this)) {
    	refWatcher = LeakCanary.install(this);

Explanation of the above-implemented code :

  1. First import all the necessary libraries
  2. Realm.init(this) is used to initiate the database as soon as the layout of the Leak Canary is ready to work so that before any crashes, the database is ready to accept the entry
  3. initializeLeakCanary() method first checks if the analyzer is in the process i.e. if the Leak Canary is already initiated so that there’s no need to again initiate it else a reference watcher is initiated with variable refWatcher which looks out for any potential memory leaks

After this, you can provide a watcher with an object to watch by writing :;

Now your app is ready to handle any case of memory leaks and thus the developer can find the root of the issue if any and can solve it with ease. The app will now work 94% more efficiently than what it used to be with memory leaks. Thus, a greater user experience can be provided now but in the backend!!


  1. How to use Leak Canary – Article on Stack Overflow
  2. Everything you need to know about memory leaks – Article on
  3. Leak Canary: Detect all memory leaks -Another great article on
  4. – Actual GitHub repo of Leak Canary library
  5. – Medium article on how to solve InputMethodManager related leaks


Ember Data Integration In Badgeyay Frontend

Badgeyay is an open source utility to develop badges for events and tech conferences. Badgeyay project is divided into two components. Frontend part is designed with ember and backend part is designed with Flask and database as PostgreSQL and Firebase as PaaS.

After refactoring the backend API for generation of badges, now it is time to consume the API in frontend by ember, and the way to consume the api in ember front–end is with the use of in built ember-data library. Ember data behaves in a way similar to server side ORM’s (Object Relational Mappers). It is a very versatile library and can be equipped with variety of backend services. It can be used with REST as well as sockets and other transfer protocols for communication.

For better understanding the working of ember data, let’s see how to use the same to consume the File Upload endpoint in the backend.


  1. Enabling CORS on server, to allow cross-domain requests to the API.
from flask_cors import CORS
CORS(app, resources={r"*": {"origins": "*"}})
  1. Creating Adapter for the model in frontend. In our case it is csv-file. In the adapter we need to specify the host and the path, because our backend api is not running on the same port.
import DS from 'ember-data';

const { RESTAdapter } = DS;

export default RESTAdapter.extend({
host : 'http://localhost:5000',
pathForType : () => {
return 'api/upload/file';
  1. After creating the adapter we need to create the record in the controller of the respective component. The record is like an object of a class, which when pushed to store will make a network request to backend (POST) and fetch the response from the backend. Backend response will provide the id to save in store
import Controller from '@ember/controller';
import { inject as service } from '@ember/service';

export default Controller.extend({
routing : service('-routing'),
actions : {
mutateCSV(csvData) {
let csv_ = this.get('store').createRecord('csv-file', {
csvFile : csvData,
extension : 'csv'

mutateText(txtData) {

Model for the csv-file

import DS from 'ember-data';

const { Model, attr } = DS;

export default Model.extend({
csvFile : attr('string'),
extension : attr('string')
  1. Next is to create serializers for the model. Serializers gets triggered at two moments, first when the data is sent to the server and second when data is received from the server. Each time an independent function gets executed. As the naming conventions of the functions pretty much explains their role, but for the sake of clarification serialize function gets executed when we send request to the server and normalizeResponse gets executed when we are getting response from the server.
import DS from 'ember-data';

const { JSONAPISerializer } = DS;

export default JSONAPISerializer.extend({

serialize(snapshot, options) {
let json = this._super(...arguments);
json.csvFile = {
'csvFile' :['csv-file'],
'extension' :

return json;

normalizeResponse(store, primaryModelClass, payload, id, requestType) {
return payload;
  1. After receiving the response a promise is returned by the push method to save the record in the store and we can see the id is saved in the ember-data object.

Pull Request for the same is at this Link

Topics Involved

Working on the issue involve following topics:

  • Enabling CORS to accept cross-domain requests at server
  • Creating models in ember data
  • Passing action from controller to component
  • Modifying the Params and Response on the network sent by ember-data via serializers



  • Ember data repository – Link
  • Documentation for creating record in ember data – Link
  • API Doc for JSONAPIAdapter – Link
  • API Doc for JSONAPISerializer – Link
  • Property methods for serializer – serialize, normalizeResponse

Implementing Sign up Feature through Email in Badgeyay

Badgeyay project is divided into two parts i.e front-end of Ember JS and back-end with REST-API programmed in Python.

We already have logging In features implemented with the help of Firebase Authentication. A User can login in the Badgeyay with the help of Google, Facebook and Twitter credentials through a single click. Now, the challenging part is to implement the sign up with Email feature in Frontend and Backend to enable the user to signup and Login with the help of Email and Password

In this blog, I will be discussing how I set up Sign up feature in Badgeyay frontend to send the data in backend besides having Oauth logging features in Badgeyay integrated with Firebase in my Pull Request.

The sign up form is already implemented and I have already mentioned in my previous blog. So we need to send the form data to backend to register user so that user can login using the registered credentials. We need an Adapter, Signup action, controller , Signup Data model  and a serializer for doing this task.

Let’s get started and understand the terminologies before implementing the feature.

What is Ember Data ?

It is a data management library for Ember Framework which help to deal with persistent application data.
We will generate Ember data model using Ember CLI in which we will define the data structure we will be requiring to provide to our application for User Signup.

Step 1 : Generate ember data model for signup.

$ ember g model user-signup


Step 2: Define the user-signup data model.

import DS from 'ember-data';

const { Model, attr } = DS;

export default Model.extend({
  username : attr('string'),
  email    : attr('string'),
  password : attr('string')


What are Actions ?

We already have the signup form implemented in frontend. Now we need to provide a action to the form when the user enters the data in form.

If we add the {{action}} helper to any HTML DOM element, when a user clicks the element, the named event will be sent to the template’s corresponding component or controller.

<button class="ui orange submit button" {{ action 'signUp' }}>Sign Up</button>


We need to add signUp action in sign-up component and controller.

// Signup Controller 
import Controller from '@ember/controller';

import { inject as service } from '@ember/service';

export default Controller.extend({
  routing : service('-routing'),
  actions : {
    signUp(email, username, password) {
      const _this = this;
      let user_ = this.get('store').createRecord('user-signup', {
        .then(record => {
        .catch(err => {

// Sign up Component
import Component from '@ember/component';

export default Component.extend({
  init() {

  email     : '',
  password  : '',
  isLoading : false,

  actions: {
    signUp(event) {
      let email = '';
      let password = '';
      let username = '';
      email = this.get('email');
      password = this.get('password');
      username = this.get('username');
      this.get('signUp')(email, username, password);


What is an Adapter ?

An adapter determines how the data is persisted to a backend data store. We can configure the backend host, URL format and headers for REST API.

Now as we have specific Data Model for User Signup that we will be using for communicating with its backend so we have to create User-Signup Adapter with the help of Ember-CLI.

Step 1: Generate User Signup Adapter by following together.

$ ember generate adapter user-signup


Step 2: Extend the Adapter according to User-Signup Model.

import DS from 'ember-data';
import ENV from '../config/environment';

const { APP } = ENV;
const { JSONAPIAdapter } = DS;

export default JSONAPIAdapter.extend({
  host        : APP.backLink,
  pathForType : () => {
    return 'user/register';


What are Serializers ?

Serializers format the Data sent to and received from the backend store. By default, Ember Data serializes data using the JSON API format.

Now as we have specific Data Model for User Signup that we will be using for communicating with its backend so we have to create User-Signup Serializer with the help Ember-CLI.

Step 1: Generate the User Signup Adapter by following command:

$ ember generate serializer user-signup


Step 2: Extend the serializer according to User-Signup Model.

import DS from 'ember-data';

const { JSONAPISerializer } = DS;

export default JSONAPISerializer.extend({

  serialize(snapshot, options) {
    let json = this._super(...arguments);
    return json;

  normalizeResponse(store, primaryModelClass, payload, id, requestType) {
    return payload;


We have successfully set up the User Signup in the frontend and data is communicated to backend in JSON API v1 specification with the help of serializers and Adapters.

This is how I set up Sign up feature in Badgeyay frontend to send the data in backend besides having Oauth logging features in Badgeyay integrated with Firebase in my Pull Request.


  1. Ember Docs – Link
  2. Firebase Docs – Link
  3. Badgeyay Repository – Link

Database Listener for User Centric Events

Badgeyay is an open-source utility developed by FOSSASIA to generate badges for conferences and events. The project is separated into two components to ease maintainability. First is the frontend part which is in ember and second part is backend which is in Flask. The choice of database to support backend is PostgreSQL.

Now comes the problem, whenever a user is registered in the database, he should receive  a verification mail, that he is successfully registered on the platform. For this case we have to listen to the database events on User model. This issue has greater extendibility than only sending greeting or verification mail to the user. We can extend this to trigger services that are dependent on user registration, like subscribing the user to some set of services based on the plan he opted while registration and many more.

These type of issues cannot be handled by normal relationship with tables and other entities, there has to be logic in place to support such functionalities. So the challenges for tackling the problem are as follows:

  • Listen to the insert_action in User model
  • Extracting the details necessary for the logic
  • Execute particular logic


  1. Attaching insert_action listener to the User model. This function will get triggered whenever an entity is saved in the User model.

<!– HTML generated using –>

@db.event.listens_for(User, "after_insert")
def logic(mapper, connection, target): {
  1. When the function gets triggered, extract the details of the saved user that is necessary for the logic. As currently we are sending greeting mail to the user,we only need the email of the user. Target is the actual saved user passed as argument to the listening function from the library.

<!– HTML generated using –>

msg = {}
msg['subject'] = "Welcome to Badgeyay"
msg['receipent'] =
msg['body'] = "It's good to have you onboard with Badgeyay. Welcome to " \
"FOSSASIA Family."
  1. Now the details are passed to sendMail() function for sending mail which uses flask-mail library to send mail to the recipient.
    def sendMail(message):
    if message and message.receipent:
    msg = Message(
    sender=app.config['MAIL_USERNAME'], Response(200).generateMessage(
    except Exception as e:
    return jsonify(
    'Unable to send the mail'))
    return jsonify(
    'Mail Sent'))
    return jsonify(
    'No data received')) 'No data received'))
  2. This will send mail to the user who has been registered to the application.

Similarly we can use separate logics according to the need of the application.


The Pull Request for the above functionality is at this Link

Topics Involved

Working on the issue involve following topics:

  • Configuring mail service to allow insecure apps access.
  • Sending mail from the flask-mail to end user
  • Attaching listener to listen for database change
  • Extraction of data from saved object in database sqlalchemy.


  • Sending Mails Programmatically –  Link
  • Flask Mail Documentation – Link
  • Listening to database events – Link
  • Enabling access to GMAIL to send mails to recipient – Link

Badgeyay: Integrating EmberJS Frontend with Flask Backend

Badgeyay is a simple badge generator with a simple web UI that generates a printable badge in PDFs. The project had gone through different cycles starting from a Flask server to a CLI application then a python library and now API Interface for generation of badges.

According to latest changes in the project structure, now the frontend and backend are independent components developed in Ember JS and Flask respectively. Now there is a need to connect the frontend to the backend, which means the user should see the response on the same page without refresh, if the badge generated successfully. AJAX would fit right into the spot. Asynchronous Javascript and XML also known as AJAX, will enable us to perform asynchronous operation on the page without refreshing the page.

We can make an API call to the Server running in backend or deployed on heroku, but the server is not suitable for doing CORS(Cross-Origin Resource Sharing), ability to share the resources on server with the client having different domain names, but as the server and the frontend are not hosted on the same host  so there is a need to enable the server to accept CORS request calls.

Now the challenges were:

  • Enabling Flask Server to accept CORS requests.
  • AJAX query for sending request to the Flask server.


  1. Giving the form an id and creating an AJAX request to the Flask server (may be localhost or deployed on heroku).
<form id=”form1″ action=”” method=”post” enctype=”multipart/form-data” onsubmit=”return validate()”>


When the generate button is clicked, an AJAX request is made to the server to generate badges and at the same time prevent the page from refreshing. In the AJAX request we set the CORS header to allow the domain.


<script type=”text/javascript”>
$(document).ready(function () {
$(‘#form1’).submit(function (event) {
headers: {“Access-Control-Allow-Origin”: “*”}
url: “”,
data: $(this).serialize(),
type: ‘POST’,
success: function (data) {…},
error: function (error) {…}


  1. Import the library and enable the API endpoint to accept CORS requests.
from flask_cors import CORS
cors = CORS(app, resources={r”/api/*”: {“origins”: “*”}})


  1. Add Logic for appending the download link by extracting the download link from the response and replacing the static text in the template with the download link, also changing the download variable to the filename, by stripping the base url from the download link.
if (data[“response”][0][“type”] === “success”) {
$(‘#success’).css(‘visibility’, ‘visible’);
let link = data[“response”][0][“download_link”];
link = link.replace(“backend/app/”, “”);
$(‘#badge-link’).attr(“href”, link);
link = link.replace(“static/badges/”, “”);
$(‘#badge-link’).attr(“download”, link);


  1. Output the success on the page.
<div id=”success” style=”visibility: hidden;”>
<div class=”flash-success”>Your badges have been created successfully.</div>
<div class=”text-center”>
<a id=”badge-link” href=”{{msg}}-badges.pdf”
class=”btn btn-success”
download=”{{msg}}-badges.pdf”>Download as


  1. Frontend and Backend now are connected to each other.The Server now accepts CORS requests and response is generated after the user requests from Frontend.


The Pull Request with the above changes is on this Link

Topics Involved

Working on this issue (Link)  involves following topics :

  • Enabling Flask Server for CORS
  • Request Headers
  • AJAX request for CORS.


Badgeyay: Custom Fonts in generation of badges

Badgeyay is an open source project of FOSSASIA. The main idea for this project is to provide an open-source alternative for badge generation process for any event. It can generate badges according to a predefined config or we can also submit our own custom config for the generation of the badges. We can use custom background, text and other things. One thing that is not present is the choice for choosing a custom font for the badge. I have made a contribution for adding this functionality with selection of some common fonts in the code.


  1. Add a Button in index.html for the choice of the font and also preview them at the same time. 
    <label>Choose your font</label>
    <ul style=“list-style-type:none”>
        <input type=“radio” name=“fontsource” id=“custfont”> Use Custom font
                        <section id=“custom-font” style=“display: none;”>
        <label for=“inputFile”>Select from following fonts</label>
        <div class=“btn-group”>
           <button type=“button” class=“btn btn-default dropdown-toggle” data-toggle=“dropdown” aria-haspopup=“true” aria-expanded=“false”>
              <span class=“placeholder2”>Select a font</span>
              <span class=“glyphicon glyphicon-chevron-down”></span>
           <ul class=“dropdown-menu”>
              {% for i in custom_fonts %}
              <li class=“font-options” style=“font-family:'{{i}}'” data-item=“{{i}}”>{{i}}</li>
              {% endfor %}
     <input type=“hidden” name=“custfont” value=“”>



  2. Add javascript for the toggle in the check button and CSS for the Font option button.
.$(“.font-options”).click(function () {
  var i = $(this).data(“item”);


.font-options {
border-bottom: 1px solid darkgray;
padding: 9px;


  1. Font list is passed in the index page.
CUSTOM_FONTS = [‘monospace’, ‘sans-serif’, ‘sans’, ‘Courier 10 Pitch’, ‘Source Code Pro’]


render_template(‘index.html’, default_background=default_background, custom_fonts=CUSTOM_FONTS)


  1. Config file for font has been created, so that it can be used by different files.
custom_font = request.form[‘custfont’]
# Custom font is selected for the text
if custom_font != :
  json_str = json.dumps({
      ‘font’: custom_font
  f = open(os.path.join(app.config[‘UPLOAD_FOLDER’], ‘fonts.json’), “w+”)


  1. Font preference is taken from the file at the time of generation of the badge (once only for all the badges in a single run).
font_choice = None
if os.path.isfile(os.path.join(UPLOAD_FOLDER, ‘fonts.json’)):
  DATA = json.load(open(os.path.join(UPLOAD_FOLDER, “fonts.json”)))
  font_choice = DATA[‘font’]


  1. Changes in the SVG are made according to the preference for the PDF generation. If the user wants a custom font then it updates the svg using the config else not.
content = CONTENT
if font_choice:
  content = content.replace(“font-family:sans-serif”,
                            “font-family:” + font_choice)
  content = content.replace(“inkscape-font-specification:sans-serif”,
                            “inkscape-font-specification:” + font_choice)
  content = content.replace(“font-family:ubuntu”,
                            “font-family:” + font_choice)
  content = content.replace(“inkscape-font-specification:ubuntu”,
                            “inkscape-font-specification:” + font_choice)


  1. Finally the Updated SVG is used for Badge Generation with custom fonts embedded.


Resources utilised for adding this functionality

  • Fonts in SVG – Link
  • Embed fonts in Inkscape SVG – Link
  • Embed fonts in PDF and SVG – Link


Make Flask Fast and Reliable – Simple Steps

Flask is a microframework for Python, which is mostly used in web-backend development.There are projects in FOSSASIA that are using flask for development purposes such as Open Event Server, Query Server, Badgeyay. Optimization is indeed one of the most important steps for a successful software product. So, in this post some few off- the-hook tricks will be shown which will make your flask-app more fast and reliable.


  1. Flask-Compress is a python package which basically provides de-facto lossless compression  to your Flask application.
  2. Enough with the theory, now let’s understand the coding part:
    1. First install the module

2. Then for a basic setup

3.That’s it! All it takes is just few lines of code to make your flask app optimized .To know more about the module check out flask-compress module.

Requirements Directory

  1. A common practice amongst different FOSSASIA  projects which involves dividing requirements.txt files for development,testing as well as production.
  2. Basically when projects either use TRAVIS CI for testing or are deployed to Cloud Services like Heroku, there are some modules which are not really required at some places.  For example: gunicorn is only required for deployment purposes and not for development.
  3. So how about we have a separate directory wherein different .txt files are created for different purposes.
  4. Below is the image of file directory structure followed for requirements in badgeyay project.

  1. As you can see different .txt files are created for different purposes
    1. dev.txt – for development
    2. prod.txt – for production(i.e. deployment)
    3. test.txt – for testing.


Building the Meilix Generator with Flask

Meilix Generator is a webapp which is used to trigger the Travis build of Meilix and mail the user the link of the iso. Meilix Generator webapp is based on Flask. This blog shows that how easy is to build a webapp and take the HTML files to render it into the webapp as well as to call and pass various function. Here I used Flask, the Python framework to render the HTML templates and send requests for various purposes (mentioned later in the article) without coding everything from scratch because of import facility of the Flask.

What is Flask?

Flask is a Python micro web framework based on Werkzeug, Jinja 2 template engine. It is used as the backbone of the webapp. It features us with a whole set of Python from which we can easily generate webapp. It is micro as it has no tools and no library itself. It come up with minimum requirements and one who needs can import different library and use it. And I used several import function for Meilix Generator like render_template, send_from_directory, etc.

Implementation (The use case in Meilix Generator)

First of all, the installation process: We will do the installation in a virtual environment. We prefer virtual environment to differentiate the Python working environment since few programs are there which require different Python versions to work.
Install virtual environment 

sudo pip install virtualenv

Now go to the folder (project) and activate it using

. venv/bin/activate

Now install Flask

pip install flask
Creating your project

Now it’s time to create a simple project in the directory.
Let’s use HTML as the frontend. In the folder create styles.css for styling and index.html template for the frontend of the page.We will make one file which would look similar to this: 

from flask import Flask, render_template
app = Flask(__name__)
def index():
	"""Index page"""
	return render_template("index.html")
if __name__ == '__main__':

Flask looks for the / (root) path and here the root return the main template (index.html) which is the main function.

Compiling it to view the page:

export FLASK_DEBUG=1
flask run

You will find your page at

More options (how more it can help you)

  • Add more HTML template options and refer it in
  • Easily use Github API  from a different .py file (this file should get import to to fetch data like: : It will fetch user name, repos, followers and many more important information.

How I used this idea for FOSSASIA (Meilix Generator)

I used Flask for the backbone of project Meilix Generator. First, I used from function to import various library needed for the project and then made several functions for the same. Let’s understand the concept using few example:

from flask import Flask, render_template
def about():
		#About page
		return render_template("about.html")


from flask import Flask, send_from_directory
def uploaded_file(filename):
		return send_from_directory(app.config['UPLOAD_FOLDER'],filename)

For more details file can be found here of the Meilix Generator repository where we used the above idea.

Important Links and Repositories:

Ticket Ordering or Positioning (back-end)

One of the many feature requests that we got for our open event organizer server or the eventyay website is ticket ordering. The event organizers wanted to show the tickets in a particular order in the website and wanted to control the ordering of the ticket. This was a common request by many and also an important enhancement. There were two main things to deal with when ticket ordering was concerned. Firstly, how do we store the position of the ticket in the set of tickets. Secondly, we needed to give an UI in the event creation/edit wizard to control the order or position of a ticket. In this blog, I will talk about how we store the position of the tickets in the backend and use it to show in our public page of the event.

Continue reading Ticket Ordering or Positioning (back-end)

Multiple Tickets: Back-end

In my previous post I talked about approach for Multiple Ticket feature’s user-interface [Link]. In this post I’ll discuss about Flask back-end used for saving multiple tickets.

HTML Fields Naming

Since the number of Tickets a user creates is unknown to the server, details of tickets were needed to be sent as an array of values. So the server would accept the list of values and iterate over them. To send data as an array the naming had to include brackets. Below are some input fields used in tickets:

        <input type="hidden" name="tickets[type]">
        <input type="text" name="tickets[name]" class="form-control" placeholder="Ticket Name" required="required" data-uniqueticket="true">
        <div class="help-block with-errors"></div>
        <input type="number" min="0" name="tickets[price]" class="form-control"  placeholder="$" value="">
        <input type="number" min="0" name="tickets[quantity]" class="form-control" placeholder="100" value="{{ quantity }}">
    <!-- Other fields -->

At the server

When the POST request reaches the server, any of the above fields (say tickets[name]) would be available as a list. The Flask Request object includes a form dictionary that contains all the POST parameters sent with the request. This dictionary is an ImmutableMultiDict object, which has a getlist method to get array of elements.

For instance in our case, we can get tickets[name] using:

@expose('/create', methods=('POST', 'GET'))
def create_view(self):
    if request.method == 'POST':
        ticket_names = request.form.getlist('tickets[name]')

    # other stuff

The ticket_names variable would contain the list of all the Ticket names sent with the request. So for example if the user created three tickets at the client-side, the form would possibly look like:

<form method="post">
  <!-- Ticket One -->
  <input type="text" name="tickets[name]" class="form-control" value="Ticket Name One">
  <!-- Ticket Two -->
  <input type="text" name="tickets[name]" class="form-control" value="Ticket Name Two">
  <!-- Ticket Three -->
  <input type="text" name="tickets[name]" class="form-control" value="Ticket Name Three">


After a successful POST request to the server, ticket_names should contain ['Ticket Name One', 'Ticket Name Two', 'Ticket Name Three'].

Other fields, like tickets[type], tickets[price], etc. can all be extracted from the Request object.

Checkbox Fields

A problem arose when a checkbox field was needed for every ticket. In my case, a “Hide Ticket” option was needed to let the user decide if he wants the ticket to be shown at the public Events page.

Screenshot from 2016-08-13 12:39:29

The problem with checkboxes is that, for a checkbox of a particular name attribute, if it is not selected, POST parameters of the request made by the client will not contain the checkbox input field parameter. So if I define an input field as a checkbox with the following naming convention, and make a POST request to the server, the server will receive blah[] parameter only if the input element had been checked.

<input type="checkbox" name="blah[]" >

This creates a problem for “Hide ticket” checkboxes. For instance, at the client-side the user creates three tickets with the first and last tickets having their checkboxes selected, the server would get an array of two.

  <!-- Ticket One -->
  <input type="checkbox" name="tickets[hide]" checked>
  <!-- Ticket Two -->
  <input type="checkbox" name="tickets[hide]">
  <!-- Ticket Three -->
  <input type="checkbox" name="tickets[hide]" checked>

ticket_hide_opts = request.form.getlist('tickets[hide]')

ticket_hide_opts would be an array of length two. And there is no way to tell what ticket had its “Hide ticket” option checked. So for the hide checkbox field I had to define input elements with unique names to extract them at the server.

There is also a hack to overcome the unchecked-checkbox problem. It is by using a hidden field with the same name as the checkbox. You can read about it here: