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Cloud Skills Challenge

FOSSASIA Summit 2022 Cloud Skills Challenge

The FOSSASIA Summit 2022 Cloud Skills Challenge offers participants a free E-Learning opportunity to build up cloud skills, opening the doors to a professional IT journey. Join the Cloud Skills Challenge today to build up your cloud skills, get your certificate and stand a chance to win exciting prizes. 
Until March 31, you can sign-up for a series of Free E-Learning Modules on: 
  • Introduction to Cloud Computing 
  • Introduction to Machine Learning
  • Best AI service for your needs 
  • Objects Detection with the Custom Vision service
  • Database and Data storage services 
  • Concept of Data Analysis 
  • IoT service for your applications 
  • And many more 

Learning Rewards 

  • Complete at least 5 modules to get a digital certificate 
  • Complete 10 modules to receive a digital swag
  • Complete all 51 modules to stand a chance to win top prizes: 
    • 1st Prize: Surface Go 2 
    • 2nd Prize: Surface Headphone 2
    • 3rd Prize: JBL Charge 4 


  • Winners will be announced during the FOSSASIA Summit 2022, April 7-9 by jury members.

Sign Up Now at   

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Using S3 for Cloud storage

In this post, I will talk about how we can use the Amazon S3 (Simple Storage Service) for cloud storage. As you may know, S3 is a no-fuss, super easy cloud storage service based on the IaaS model. There is no limit on the size of file or the amount of files you can keep on S3, you are only charged for the amount of bandwidth you use. This makes S3 very popular among enterprises of all sizes and individuals.

Now let’s see how to use S3 in Python. Luckily we have a very nice library called Boto for it. Boto is a library developed by the AWS team to provide a Python SDK for the amazon web services. Using it is very simple and straight-forward. Here is a basic example of uploading a file on S3 using Boto –

import boto
from boto.s3.key import Key
# connect to the bucket
conn = boto.connect_s3(AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY)
bucket = conn.get_bucket(BUCKET_NAME)
# set the key
key = 'key/for/file'
file = '/full/path/to/file'
# create a key to keep track of our file in the storage
k = Key(bucket)
k.key = key

The above example uploads a file to s3 bucket BUCKET_NAME.

Buckets are containers which store data. The key here is the unique key for an item in the bucket. Every item in the bucket is identified by a unique key assigned to it. The file can be downloaded from the{key}. It is therefore essential to choose the key name smartly so that you don’t end up overwriting an existing item on the server.

In the Open Event project, I thought of a scheme that will allows us to avoid conflicts. It relies on using IDs of items for distinguishing them and goes as follows –

  • When uploading user avatar, key should be ‘users/{userId}/avatar’
  • When uploading event logo, key should be ‘events/{eventId}/logo’
  • When uploading audio of session, key should be ‘events/{eventId}/sessions/{sessionId}/audio’

Note that to store user ‘avatar’, I am setting the key as /avatar and not /avatar.extension. This is because if user uploads pictures in different formats, we will end up storing different copies of avatars for the same user. This is nice but it’s limitation is that downloading file from the url will give the file without an extension. So to solve this issue, we can use the Content-Disposition header.

		'Content-Disposition': 'attachment; filename=filename.extension'

So now when someone tries to download the file from that link, they will get the file with an extension instead of a no-extension “Choose what you want to do” file.

This covers up the basics of using S3 for your Python project. You may explore Boto’s S3 documentation to find other interesting functions like deleting a folder, copy one folder to another and so.

Also don’t forget to have a look at the awesome documentation we wrote for the Open Event project. It provides a more pictorial and detailed guide on how to setup S3 for your project.


{{ Repost from my personal blog }}

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