Documenting Open Event API Using API-Blueprint

FOSSASIA‘s Open Event Server API documentation is done using an api-blueprint. The API Blueprint language is a format used to describe API in an API blueprint file, where a blueprint file (or a set of files) is such that describes an API using the API Blueprint language. To follow up with the blueprint, an apiary editor is used. This editor is responsible for rendering the API blueprint and printing the result in user readable API documented format. We create the API blueprint manually.

Using API Blueprint:-
We create the API blueprint by first adding the name and metadata for the API we aim to design. This step looks like this :-


# Open Event API Server

The Open Event API Server

# Group Authentication

The API uses JWT Authentication to authenticate users to the server. For authentication, you need to be a registered user. Once you have registered yourself as an user, you can send a request to get the access_token.This access_token you need to then use in Authorization header while sending a request in the following manner: `Authorization: JWT <access_token>`

API blueprint starts with the metadata, here FORMAT and HOST are defined metadata. FORMAT keyword specifies the version of API Blueprint . HOST defines the host for the API.

The heading starts with # and the first heading is regarded as the name of the API.

NOTE – Also all the heading starts with one or more # symbol. Each symbol indicates the level of the heading. One # symbol followed by heading serves as the top level i.e. one # = Top Level. Similarly for  ## = second level and so on. This is in compliance with normal markdown format.
        Following the heading section comes the description of the API. Further, headings are used to break up the description section.

Resource Groups:
    By using group keyword at the starting of a heading , we create a group of related resources. Just like in below screenshot we have created a Group Users.

# Group Users

For using the API you need(mostly) to register as an user. Registering gives you access to all non admin API endpoints. After registration, you need to create your JWT access token to send requests to the API endpoints.

| Parameter | Description | Type | Required |
| `name`  | Name of the user | string | - |
| `password` | Password of the user | string | **yes** |
| `email` | Email of the user | string | **yes** |


    In the Group Users we have created a resource Users Collection. The heading specifies the URI used to access the resource inside of the square brackets after the heading. We have used here parameters for the resource URI which takes us into how to add parameters to the URI. Below code shows us how to add parameters to the resource URI.

## Users Collection [/v1/users{?page%5bsize%5d,page%5bnumber%5d,sort,filter}]
+ Parameters
    + page%5bsize%5d (optional, integer, `10`) - Maximum number of resources in a single paginated response.
    + page%5bnumber%5d (optional, integer, `2`) - Page number to fetchedfor the paginated response.
    + sort (optional, string, `email`) - Sort the resources according to the given attribute in ascending order. Append '-' to sort in descending order.
    + filter(optional, string, ``) - Filter according to the flask-rest-jsonapi filtering system. Please refer: for more.


    An action is specified with a sub-heading inside of  a resource as the name of Action, followed by HTTP method inside the square brackets.
    Before we get on further, let us discuss what a payload is. A payload is an HTTP transaction message including its discussion and any additional assets such as entity-body validation schema.

There are two payloads inside an Action:

  1. Request: It is a payload containing one specific HTTP Request, with Headers and an optional body.
  2. Response: It is a payload containing one HTTP Response.

A payload may have an identifier-a string for a request payload or an HTTP status code for a response payload.

+ Request

    + Headers

            Accept: application/vnd.api+json

            Authorization: JWT <Auth Key>

+ Response 200 (application/vnd.api+json)

Types of HTTP methods for Actions:

  • GET – In this action, we simply send the header data like Accept and Authorization and no body. Along with it we can send some GET parameters like page[size]. There are two cases for GET: List and Detail. For example, if we consider users, a GET for List helps us retrieve information about all users in the response, while Details, helps us retrieve information about a particular user.

The API Blueprint examples implementation of both GET list and detail request and response are as follows.

### List All Users [GET]
Get a list of Users.

+ Request

    + Headers

            Accept: application/vnd.api+json

            Authorization: JWT <Auth Key>

+ Response 200 (application/vnd.api+json)

            "meta": {
                "count": 2
            "data": [
                    "attributes": {
                        "is-admin": true,
                        "last-name": null,
                        "instagram-url": null,


### Get Details [GET]
Get a single user.

+ Request

    + Headers

            Accept: application/vnd.api+json

            Authorization: JWT <Auth Key>

+ Response 200 (application/vnd.api+json)

            "data": {
                "attributes": {
                    "is-admin": false,
                    "last-name": "Doe",
                    "instagram-url": "",


  • POST – In this action, apart from the header information, we also need to send a data. The data must be correct with jsonapi specifications. A POST body data for an users API would look something like this:
### Create User [POST]
Create a new user using an email, password and an optional name.

+ Request (application/vnd.api+json)

    + Headers

            Authorization: JWT <Auth Key>

    + Body

                  "email": "[email protected]",
                  "password": "password",

A POST request with this data, would create a new entry in the table and then return in jsonapi format the particular entry that was made into the table along with the id assigned to this new entry.

  • PATCH – In this action, we change or update an already existing entry in the database. So It has a header data like all other requests and a body data which is almost similar to POST except that it also needs to mention the id of the entry that we are trying to modify.
### Update User [PATCH]
+ `id` (integer) - ID of the record to update **(required)**

Update a single user by setting the email, email and/or name.

Authorized user should be same as user in request body or must be admin.

+ Request (application/vnd.api+json)

    + Headers

            Authorization: JWT <Auth Key>

    + Body

              "data": {
                "attributes": {
                  "password": "password1",
                  "avatar_url": "",
                  "first-name": "Jane",
                  "last-name": "Dough",
                  "details": "example1",
                  "contact": "example1",
                  "facebook-url": "",
                  "twitter-url": "",
                  "instagram-url": "",
                  "google-plus-url": "",
                  "thumbnail-image-url": "",
                  "small-image-url": "",
                  "icon-image-url": ""
                "type": "user",
                "id": "2"

Just like in POST, after we have updated our entry, we get back as response the new updated entry in the database.

  • DELETE – In this action, we delete an entry from the database. The entry in our case is soft deleted by default. Which means that instead of deleting it from the database, we set the deleted_at column with the time of deletion. For deleting we just need to send header data and send a DELETE request to the proper endpoint. If deleted successfully, we get a response as “Object successfully deleted”.
### Delete User [DELETE]
Delete a single user.

+ Request

    + Headers

            Accept: application/vnd.api+json

            Authorization: JWT <Auth Key>

+ Response 200 (application/vnd.api+json)

          "meta": {
            "message": "Object successfully deleted"
          "jsonapi": {
            "version": "1.0"

How to check after manually entering all these? We can use the
apiary website to render it, or simply use different renderer to do it. How? Checkout for my next blog on apiary and aglio.

Learn more about api blueprint here:

Open Event Server: No (no-wrap) Ellipsis using jquery!

Yes, the title says it all i.e., Enabling multiple line ellipsis. This was used to solve an issue to keep Session abstract view within 200 characters (#3059) on FOSSASIA‘s Open Event Server project.

There is this one way to ellipsis a paragraph in html-css and that is by using the text-overflow property:

white-space: nowrap;
overflow: hidden;
text-overflow: ellipsis;

But the downside of this is the one line ellipis. Eg: My name is Medozonuo. I am…..

And here you might pretty much want to ellipsis after a few characters in multiple lines, given that your div space is small and you do want to wrap your paragraph. Or maybe not.

So jquery to the rescue.

There are two ways you can easily do this multiple line ellipsis:

1) Height-Ellipsis (Using the do-while loop):

if ($('.div_class').height() > 100) {
    var words = $('.div_class').html().split(/\s+/);

    do {
        words.splice(-2, 1);
        $('.div_class').html( words.join(' ') );
    } while($('.div_class').height() > 100);

Here, you check for the div content’s height and split the paragraph after that certain height and add a “…”, do- while making sure that the paragraphs are in multiple lines and not in one single line. But checkout for that infinite loop.

2) Length-Ellipsis (Using substring function):  

$.each($('.div_class'), function() {
        if ($(this).html().length > 100) {
               var cropped_words = $(this).html();
               cropped_words = cropped_words.substring(0, 200) + "...";

Here, you check for the length/characters rather than the height, take in the substring of the content starting from 0-th character to the 200-th character and then add in extra “…”.

This is exactly how I used it in the code.

$.each($('.short_abstract',function() {
   if ($(this).html().length > 200) {
       var  words = $(this).html();
       words = words.substring(0,200 + "...";

So ellipsing paragraphs over heights and lengths can be done using jQuery likewise.

DetachedInstanceError: Dealing with Celery, Flask’s app context and SQLAlchemy in the Open Event Server

In the open event server project, we had chosen to go with celery for async background tasks. From the official website,

What is celery?

Celery is an asynchronous task queue/job queue based on distributed message passing.

What are tasks?

The execution units, called tasks, are executed concurrently on a single or more worker servers using multiprocessing.

After the tasks had been set up, an error constantly came up whenever a task was called

The error was:

DetachedInstanceError: Instance <User at 0x7f358a4e9550> is not bound to a Session; attribute refresh operation cannot proceed

The above error usually occurs when you try to access the session object after it has been closed. It may have been closed by an explicit session.close() call or after committing the session with session.commit().

The celery tasks in question were performing some database operations. So the first thought was that maybe these operations might be causing the error. To test this theory, the celery task was changed to :

def lorem_ipsum():

But sadly, the error still remained. This proves that the celery task was just fine and the session was being closed whenever the celery task was called. The method in which the celery task was being called was of the following form:

def restore_session(session_id):
    session = DataGetter.get_session(session_id)
    session.deleted_at = None
    save_to_db(session, "Session restored from Trash")
    update_version(session.event_id, False, 'sessions_ver')

In our app, the app_context was not being passed whenever a celery task was initiated. Thus, the celery task, whenever called, closed the previous app_context eventually closing the session along with it. The solution to this error would be to follow the pattern as suggested on

def make_celery(app):
    celery = Celery(app.import_name, broker=app.config['CELERY_BROKER_URL'])
    task_base = celery.Task

    class ContextTask(task_base):
        abstract = True

        def __call__(self, *args, **kwargs):
            if current_app.config['TESTING']:
                with app.test_request_context():
                    return task_base.__call__(self, *args, **kwargs)
            with app.app_context():
                return task_base.__call__(self, *args, **kwargs)

    celery.Task = ContextTask
    return celery

celery = make_celery(current_app)

The __call__ method ensures that celery task is provided with proper app context to work with.


Event-driven programming in Flask with Blinker signals

Setting up blinker:

The Open Event Project offers event managers a platform to organize all kinds of events including concerts, conferences, summits and regular meetups. In the server part of the project, the issue at hand was to perform multiple tasks in background (we use celery for this) whenever some changes occurred within the event, or the speakers/sessions associated with the event.

The usual approach to this would be applying a function call after any relevant changes are made. But the statements making these changes were distributed all over the project at multiple places. It would be cumbersome to add 3-4 function calls (which are irrelevant to the function they are being executed) in so may places. Moreover, the code would get unstructured with this and it would be really hard to maintain this code over time.

That’s when signals came to our rescue. From Flask 0.6, there is integrated support for signalling in Flask, refer . The Blinker library is used here to implement signals. If you’re coming from some other language, signals are analogous to events.

Given below is the code to create named signals in a custom namespace:

from blinker import Namespace

event_signals = Namespace()
speakers_modified = event_signals.signal('event_json_modified')

If you want to emit a signal, you can do so by calling the send() method:


From the user guide itself:

“ Try to always pick a good sender. If you have a class that is emitting a signal, pass self as sender. If you are emitting a signal from a random function, you can pass current_app._get_current_object() as sender. “

To subscribe to a signal, blinker provides neat decorator based signal subscriptions.

def name_of_signal_handler(app, **kwargs):


Some Design Decisions:

When sending the signal, the signal may be sending lots of information, which your signal may or may not want. e.g when you have multiple subscribers listening to the same signal. Some of the information sent by the signal may not be of use to your specific function. Thus we decided to enforce the pattern below to ensure flexibility throughout the project.

def new_handler(app, **kwargs):
# do whatever you want to do with kwargs['event_id']

In this case, the function new_handler needs to perform some task solely based on the event_id. If the function was of the form def new_handler(app, event_id), an error would be raised by the app. A big plus of this approach, if you want to send some more info with the signal, for the sake of example, if you also want to send speaker_name along with the signal, this pattern ensures that no error is raised by any of the subscribers defined before this change was made.

When to use signals and when not ?

The call to send a signal will of course be lying in another function itself. The signal and the function should be independent of each other. If the task done by any of the signal subscribers, even remotely affects your current function, a signal shouldn’t be used, use a function call instead.

How to turn off signals while testing?

When in testing mode, signals may slow down your testing as unnecessary signals subscribers which are completely independent from the function being tested will be executed numerous times. To turn off executing the signal subscribers, you have to make a small change in the send function of the blinker library.

Below is what we have done. The approach to turn it off may differ from project to project as the method of testing differs. Refer for the original function.

def new_send(self, *sender, **kwargs):
    if len(sender) == 0:
        sender = None
    elif len(sender) > 1:
        raise TypeError('send() accepts only one positional argument, '
                        '%s given' % len(sender))
        sender = sender[0]
    # only this line was changed
    if not self.receivers or app.config['TESTING']:
        return []
        return [(receiver, receiver(sender, **kwargs))
                for receiver in self.receivers_for(sender)]
Signal.send = new_send

event_signals = Namespace
# and so on ....

That’s all for now. Have some fun signaling 😉 .


Set proper content type when uploading files on s3 with python-magic

In the open-event-orga-server project, we had been using Amazon s3 storage for a long time now. After some time we encountered an issue that no matter what the file type was, the Content-Type when retrieving this files from the storage solution was application/octet-stream.

An example response when retrieving an image from s3 was as follows:

Accept-Ranges →bytes
Content-Disposition →attachment; filename=HansBakker_111.jpg
Content-Length →56060
Content-Type →application/octet-stream
Date →Fri, 09 Sep 2016 10:51:06 GMT
ETag →"964b1d839a9261fb0b159e960ceb4cf9"
Last-Modified →Tue, 06 Sep 2016 05:06:23 GMT
Server →AmazonS3
x-amz-id-2 →1GnO0Ta1e+qUE96Qgjm5ZyfyuhMetjc7vfX8UWEsE4fkZRBAuGx9gQwozidTroDVO/SU3BusCZs=
x-amz-request-id →ACF274542E950116


As seen above instead of providing image/jpeg as the Content-Type, it provides the Content-Type as application/octet-stream.While uploading the files, we were not providing the content type explicitly, which seemed to be the root of the problem.

It was decided that we would be providing the content type explicitly, so it was time to choose an efficient library to determine the file type based on the content of the file and not the file extension. After researching through the available libraries python-magic seemed to be the obvious choice. python-magic is a python interface to the libmagic file type identification library. libmagic identifies file types by checking their headers according to a predefined list of file types.

Here is an example straight from python-magic‘s readme on its usage:

>>> import magic
>>> magic.from_file("testdata/test.pdf")
'PDF document, version 1.2'
>>> magic.from_buffer(open("testdata/test.pdf").read(1024))
'PDF document, version 1.2'
>>> magic.from_file("testdata/test.pdf", mime=True)


Given below is a code snippet for the s3 upload function in the project:

file_data =
    file_mime = magic.from_buffer(file_data, mime=True)
    size = len(file_data)
    # k is defined as  k = Key(bucket) in previous code
    sent = k.set_contents_from_string(
            'Content-Disposition': 'attachment; filename=%s' % filename,
            'Content-Type': '%s' % file_mime


One thing to note that as python-magic uses libmagic-dev as a dependency and many of the distros do not come with libmagic-dev pre-installed, make sure you install libmagic-dev explicitly. (Installation instructions may vary per distro)

sudo apt-get install libmagic-dev

Voila !! Now when retrieving each and every file you’ll get the proper content type.


Generating xCal calendar in python

{ Repost from my personal blog @ }

“xCal”, is an XML format for iCalendar data.

The iCalendar data format (RFC5545) is a widely deployed interchange format for calendaring and scheduling data.

A Sample xCal document

<?xml version="1.0" encoding="utf-8"?>  
<iCalendar xmlns:xCal="urn:ietf:params:xml:ns:xcal">  
        <prodid>-//Pentabarf//Schedule 1.0//EN</prodid>
        <x-wr-caldesc>FOSDEM 2016</x-wr-caldesc>
        <x-wr-calname>Schedule for events at FOSDEM 2016</x-wr-calname>
            <summary>Introduction to the SDR Track- Speakers, Topics, Algorithm</summary>
            <description>&lt;p&gt;The opening talk for the SDR devroom at FOSDEM 2016.&lt;/p&gt;</description>
            <categories>Software Defined Radio</categories>
            <attendee>Martin Braun</attendee>

Each event/session will be in a seperate vevent block. Each speaker/attendee of an event/session will be in an attendee block inside a vevent block.

Some important elements are:

  1. version – Has the version of the iCalendar data
  2. prodid – Contains the name of the application/generator that generated this document
  3. x-wr-caldesc – A descriptive name for this calendar
  4. x-wr-calname – A description of the calendar

The structure and keywords used in xCal are the same as those used in the iCal format. To generate the XML document, we’ll be using python’s ElementTreeXML API that is part of the Python standard library.

We’ll be using two main classes of the ElementTree API:

  1. Element – used to create a standard node. (Used for the root node)
  2. SubElement – used to create a sub element and attache the new node to a parent

Let’s start with the root iCalendar node and set the required attributes.

from xml.etree.ElementTree import Element, SubElement, tostring

i_calendar_node = Element('iCalendar')  
i_calendar_node.set('xmlns:xCal', 'urn:ietf:params:xml:ns:xcal')

Now, to add the vcalendar node to the iCalendar node.

v_calendar_node = SubElement(i_calendar_node, 'vcalendar')

Let’s add the other aspects of the calendar to the vcalendar node as separate sub nodes.

version_node = SubElement(v_calendar_node, 'version')  
version_node.text = '2.0'

prod_id_node = SubElement(v_calendar_node, 'prodid')  
prod_id_node.text = '-//fossasia//open-event//EN'

cal_desc_node = SubElement(v_calendar_node, 'x-wr-caldesc')  
cal_desc_node.text = "Calendar"

cal_name_node = SubElement(v_calendar_node, 'x-wr-calname')  
cal_name_node.text = "Schedule for sessions"

Now, we have added information about our calendar. Now to add the actual events to the calendar. Each event would be a vevent node, a child of vcalendar node. We can loop through all our available event/sessions and add them to the calendar.

for session in sessions:  
    v_event_node = SubElement(v_calendar_node, 'vevent')

    uid_node = SubElement(v_event_node, 'uid')
    uid_node.text = str(

    dtstart_node = SubElement(v_event_node, 'dtstart')
    dtstart_node.text = session.start_time.isoformat()

    dtend_node = SubElement(v_event_node, 'dtend')
    dtend_node.text = tz.localize(session.end_time).isoformat()

    duration_node = SubElement(v_event_node, 'duration')
    duration_node.text =  "00:30"

    summary_node = SubElement(v_event_node, 'summary')
    summary_node.text = session.title

    description_node = SubElement(v_event_node, 'description')
    description_node.text = session.short_abstract

    class_node = SubElement(v_event_node, 'class')
    class_node.text = 'PUBLIC'

    status_node = SubElement(v_event_node, 'status')
    status_node.text = 'CONFIRMED'

    categories_node = SubElement(v_event_node, 'categories')
    categories_node.text =

    url_node = SubElement(v_event_node, 'url')
    url_node.text = "https://some.conf/event/" + str(

    location_node = SubElement(v_event_node, 'location')
    location_node.text =

    for speaker in session.speakers:
        attendee_node = SubElement(v_event_node, 'attendee')
        attendee_node.text =

Please note that all the timings in the XML Document must comply with ISO 8601 and must have the date+time+timezone. Example: 2007-04-05T12:30-02:00.

We’re still not done yet. We now have the XML document as an Element object. But we’ll be needing it as a string to either store it somewhere or display it.

The document can be converted to a string by using the ElementTree API’s tostring helper method and passing the root node.

xml_as_string = tostring(i_calendar_node)

And that’s it. You now have a proper XML document representing your events.

KISS Datatable

Recenlty I’ve faced a problem with sorting columns in Datatable.

What is Datatable?

Datatable is a plug-in for Jquery library. It provides a lot of features like pagination, quick search or multi-column ordering. Besides, you can develop easily Bootstrap or Foundation ui css styles. There are also more other option but It doesn’t make sense to list it here, because you can visit their site and you can read clearly documentation. On Datatable website you can see a lot of examples. First of them shows how to improve your ordinary table to awesome and rich of features table. One function changes everything, It’s fantastic!  


Returning to my problem which I’ve faced, as I told it was problem related to sorting column in table.

I know sorting is a trivial thing. I hope that everyone knows it 🙂 Sorting by a date is also implemented in a datatable library. So everything is clear when we don’t change date format to human readable format. I mean something like this ‘3 hours ago’, ‘1 year ago’.

When Open Event team tested how datatable manages ordering columns in that format it didn’t work. It’s quite hard to sort by that format, So I’ve invented an idea. Surely you are wondering what i’ve invented. I’ve postponed my minds about sort by this values. It can direct to overwork. When I thought about it, weird ideas came to my mind, a lots of conditions, If statements… Therefore I’ve resigned from this. I’ve used KISS principle. KISS means ‘keep it simple stupid’. I like it!

Therefore that sorting is implemented on frontend side. I’ve decided not to display human readable date format at the beginning. I find  all dates which have format “YYYY-MM-DD HH:mm” then I replace that format to human readable format. So it’s very quick and comfortable, and doesn’t require a lot conditions to write. Of course I’ve tried to implement it in Datatable library. I suppose that it would  require more effort than it’s now.

Below You can see great function which changes a date in frontend side but does not change data in a datatable. So sorting process takes place in a datatable using format  “YYYY-MM-DD HH:mm” but user see human readable format. Isn’t it awesome?!

function change_column_time_to_humanize_format(datatable_name, column_id) {
  $(datatable_name).each(function( key, value ) {
    $(value).children().each(function( key1, value2 ) {
       if(key1 === column_id ){
          var current_value = $(value2).text().slice(0, 16);
          var changed_value = moment(current_value, "YYYY-MM-DD hh:mm").fromNow()
          var isValid = moment(current_value, "YYYY-MM-DD HH:mm", true).isValid()
          if (changed_value !== current_value && isValid === true){


Building the Scheduler UI

{ Repost from my personal blog @ }

If you hadn’t already noticed, Open Event has got a shiny new feature. A graphical and an Interactive scheduler to organize sessions into their respective rooms and timings.

As you can see in the above screenshot, we have a timeline on the left. And a lot of session boxes to it’s right. All the boxes are re-sizable and drag-drop-able. The columns represent the different rooms (a.k.a micro-locations). The sessions can be dropped into their respective rooms. Above the timeline, is a toolbar that controls the date. The timeline can be changed for each date by clicking on the respective date button.

The Clear overlaps button would automatically check the timeline and remove any sessions that are overlapping each other. The Removed sessions will be moved to the unscheduled sessions pane at the left.

The Add new micro-location button can be used to instantly add a new room. A modal dialog would open and the micro-location will be instantly added to the timeline once saved.

The Export as iCal allows the organizer to export all the sessions of that event in the popular iCalendar format which can then be imported into various calendar applications.

The Export as PNG saves the entire timeline as a PNG image file. Which can then be printed by the organizers or circulated via other means if necessary.

Core Dependencies

The scheduler makes use of some javascript libraries for the implementation of most of the core functionality

  • Interact.js – For drag-and-drop and resizing
  • Lodash – For array/object manipulations and object cloning
  • jQuery – For DOM Manipulation
  • Moment.js – For date time parsing and calculation
  • Swagger JS – For communicating with our API that is documented according to the swagger specs.
Retrieving data via the API

The swagger js client is used to obtain the sessions data using the API. The client is asynchronously initialized on page load. The client can be accessed from anywhere using the javascript function initializeSwaggerClient.

The swagger initialization function accepts a callback which is called if the client is initialized. If the client is not initialized, the callback is called after that.

var swaggerConfigUrl = window.location.protocol + "//" + + "/api/v2/swagger.json";  
window.swagger_loaded = false;  
function initializeSwaggerClient(callback) {  
    if (!window.swagger_loaded) {
        window.api = new SwaggerClient({
            url: swaggerConfigUrl,
            success: function () {
                window.swagger_loaded = true;
                if (callback) {

    } else {
        if (callback) {

For getting all the sessions of an event, we can do,

initializeSwaggerClient(function () {  
    api.sessions.get_session_list({event_id: eventId}, function (sessionData) {
        var sessions = sessionData.obj;  // Here we have an array of session objects

In a similar fashion, all the micro-locations of an event can also be loaded.

Processing the sessions and micro-locations

Each session object is looped through, it’s start time and end time are parsed into moment objects, duration is calculated, and it’s distance from the top in the timeline is calculated in pixels. The new object with additional information, is stored in an in-memory data store, with the date of the event as key, for use in the timeline.

The time configuration is specified in a separate time object.

var time = {  
    start: {
        hours: 0,
        minutes: 0
    end: {
        hours: 23,
        minutes: 59
    unit: {
        minutes: 15,
        pixels: 48,
        count: 0
    format: "YYYY-MM-DD HH:mm:ss"

The smallest unit of measurement is 15 minutes and 48px === 15 minutes in the timeline.

Each day of the event is stored in a separate array in the form of Do MMMM YYYY(eg. 2nd May 2013).

The array of micro-location objects is sorted alphabetically by the room name.

Displaying sessions and micro-locations on the timeline

According to the day selected, the sessions for that day are displayed on the timeline. Based on their time, the distance of the session div from the top of the timeline is calculated in pixels and the session box is positioned absolutely. The height of the session in pixels is calculated from it’s duration and set.

For pixels-minutes conversion, the following are used.

 * Convert minutes to pixels based on the time unit configuration
 * @param {number} minutes The minutes that need to be converted to pixels
 * @returns {number} The pixels
function minutesToPixels(minutes) {  
    minutes = Math.abs(minutes);
    return (minutes / time.unit.minutes) * time.unit.pixels;

 * Convert pixels to minutes based on the time unit configuration
 * @param {number} pixels The pixels that need to be converted to minutes
 * @returns {number} The minutes
function pixelsToMinutes(pixels) {  
    pixels = Math.abs(pixels);
    return (pixels / time.unit.pixels) * time.unit.minutes;
Adding interactivity to the session elements

Interact.js is used to provide interactive capabilities such as drag-drop and resizing.

To know how to use Interact.js, you can checkout some previous blog posts on the same, Interact.js + drag-drop and Interact.js + resizing.

Updating the session information in database on every change

We have to update the session information in database whenever it is moved or resized. Every time a session is moved or resized, a jQuery event is triggered on $(document) along with the session object as the payload.

We listen to this event, and make an API request with the new session object to update the session information in the database.

The scheduler UI is more complex than said in this blog post. To know more about it, you can checkout the scheduler’s javascript code atapp/static/js/admin/event/scheduler.js.

Python code examples

I’ve met many weird examples of  behaviour in python language while working on Open Event project. Today I’d like to share some examples with you. I think this knowledge is necessary, if you’d like to increase a  bit your knowledge in python area.

Simple adding one element to python list:

def foo(value, x=[]):
  return x

>>> print(foo(1))
>>> print(foo(2))
>>> print(foo(3, []))
>>> print(foo(4))


[1, 2] 
[1, 2, 4]

First output is obvious, but second not exactly. Let me explain it, It happens because x(empty list) argument is only evaluated once, So on every call foo(), we modify that list, appending a value to it. Finally we have [1,2, 4] output. I recommend to avoid mutable params as default.

Another example:

Do you know which type it is?

>>> print(type([ el for el in range(10)]))
>>> print(type({ el for el in range(10)}))
>>> print(type(( el for el in range(10))))

Again first and second type are obvious <class ‘list’>, <class ‘set’>. You may  think that last one should return type tuple but it returns a generator <class ‘generator’>.


Do you think that below code returns an exception?

list= [1,2,3,4,5]
>>> print(list [8:])

If you think that above expression returns index error you’re wrong. It returns empty list [].

Example funny boolean operators

>>> 'c' == ('c' or 'b')
>>> 'd' == ('a' or 'd')
>>> 'c' == ('c' and 'b')
>>> 'd' == ('a' and 'd')

You can think that that OR and AND operators are broken.

You have to know how python interpreter behaves while looking for OR and AND operators.

So OR Expression takes the first statement and checks if it is true. If the first statement is true, then Python returns object’s value without checking second value. If first statement is false interpreter checks second value and returns that value.

AND operator checks if first statement is false, the whole statement has to be false. So it returns first value, but if first statement is true it checks second statement and returns second value.

Below i will show you how it works

>>> 'c' == ('c' or 'b')
>>> 'c' == 'c'
>>> 'd' == ('a' or 'd')
>>> 'd' == 'a'
>>> 'c' == ('c' and 'b')
>>> 'c' == 'b'
>>> 'd' == ('a' and 'd')
>>> 'd' == 'd'

I hope that i have explained you how the python interpreter checks OR and AND operators. So know above examples should be more understandable.

Accepting Stripe payments on behalf of a third-party

{ Repost from my personal blog @ }

In Open Event, we allow the organizer of each event to link their Stripe account, so that all ticket payments go directly into their account. To make it simpler for the organizer to setup the link, we have a Connect with stripe button on the event creation form.

Clicking on the button, the organizer is greeted with a signup flow similar to Login with Facebook or any other social login. Through this process, we’re able to securely and easily obtain the credentials required to accept payments on behalf of the organizer.

For this very purpose, stripe provides us with an OAuth interface called as Stripe Connect. Stripe Connect allows us to connect and interact with other stripe accounts through an API.

We’ll be using Python’s requests library for making all the HTTP Requests to the API.
You will be needing a stripe account for this.

Registering your platform
The OAuth Flow

The OAuth flow is similar to most platforms.

  • The user is redirected to an authorization page where they login to their stripe account and authorize your app to access their account
  • The user is then redirected back to a callback URL with an Authorization code
  • The server makes a request to the Token API with the Authorization code to retrieve the access_token, refresh_token and other credentials.

Implementing the flow

Redirect the user to the Authorization URL.  

The authorization url accepts the following parameters.

  1. client_id – The client ID acquired when registering your platform.required.
  2. response_type – Response type. The value is always code. required.
  3. redirect_uri – The URL to redirect the customer to after authorization.
  4. scope – Can be read_write or read_only. The default is read_only. For analytics purposes, read_only is appropriate; To perform charges on behalf of the connected user, We will need to request read_write scope instead.

The user will be taken to stripe authorization page, where the user can login to an existing account or create a new account without breaking the flow. Once the user has authorized the application, he/she is taken back to the Callback URL with the result.

Requesting the access token with the authorization code

The user is redirected back to the callback URL.

If the authorization failed, the callback URL has a query string parameter error with the error name and a parameter error_description with the description of the error.

If the authorization was a success, the callback URL has the authorization code in the code query string parameter.

import requests

data = {  
    'client_secret': 'CLIENT_SECRET',
    'grant_type': 'authorization_code'

response ='', data=data)

The client_secret is also obtained when registering your platform. The codeparameter is the authorization code.

On making this request, a json response will be returned.

If the request was a success, the following response will be obtained.

  "token_type": "bearer",
  "stripe_publishable_key": PUBLISHABLE_KEY,
  "scope": "read_write",
  "livemode": false,
  "stripe_user_id": USER_ID,
  "refresh_token": REFRESH_TOKEN,
  "access_token": ACCESS_TOKEN

If the request failed for some reason, an error will be returned.

  "error": "invalid_grant",
  "error_description": "Authorization code does not exist: AUTHORIZATION_CODE"

The access_token token obtained can be used as the secret key to accept payments like discussed in Integrating Stripe in the Flask web framework.