Google Code-In 2018 with CloudCV
Introduction
I am Sayam Kanwar, a high school student in New Delhi, India. I was very keen to participate in Google Code-In this year. Google Code-In is a contest to introduce pre-university students (ages 13–17) to open source software development. Even before the contest started, I was searching for the organizations to which I want to contribute and I was fascinated by the projects of CloudCV. It is a young open source cloud platform started in 2013 by students and faculty from Machine Learning and Perception Lab at Virginia Tech (now at Georgia Tech) with the aim to make AI research more reproducible. The reason I liked contributing to CloudCV is that they make sure to keep their task description illustrative so that it is easy for the new contributors to understand and implement it.
Initial Phase
As soon as GCI started, I took a glance at all the tasks that were listed. At first sight, I thought I couldn’t complete any of the tasks as it required the knowledge of ReactJS/AngularJS and Django and I was a novice in these frameworks. I started learning ReactJS and Django and picked some easy tasks for understanding the codebase better. Once I became familiar with frontend code, I started ramping up on the backend part as well to get the complete grasp of the project. It took me 2 days to get the basic understanding of the whole workflow and I was really happy that I could understand the design of the project and the working of frontend and backend part. I gradually started moving my level up, progressing onto medium level tasks and then finally the hard tasks. On every medium and hard task, I had to do immense research before I could write the code or figure out the logic behind each problem, but all I needed was perseverance and I started solving more and more tasks. One such example was to add the functionality of setting the Authorization token through EvalAI’s CLI tool. CLI is written using Click package and that was my starting point for this task. I studied Click’s documentation and was able to write the code to set the authorization token through CLI, I was really elated when my first hard task got approved and it boosted my confidence to work on similar tasks.
What did I learn?
It was very interesting to research on the tasks even though it was a cumbersome process but I got to learn a lot. I have learned to manage my time properly as every task I did had some timeline associated with it during which it has to be completed. Patience is also one of the qualities that were cultivated during GCI since both mentor and I was in different time zone and it was challenging to collaborate remotely. Through GCI, I have also explored new libraries and frameworks which have expanded my skills. All this would not have been possible without my mentors’ help.
Community
The community is very active in responding to the new contributors and also helped me throughout by providing useful feedback to improve upon my work. When I joined this organization’s Gitter channel, people were posting their doubts and mentors and even other students were helping them out. I aspired to be one of those students who would help others but initially, I could barely understand things. In the last 2 months, I had learned a lot of things and now I am able to answer some of the students’ queries on the channel.
Conclusion
To sum up everything, Google Code-In has been more of a learning experience for me rather than a contest. I’ve learned a multitude of things through CloudCV’s projects and was the second highest contributor on their projects along with winning the Grand-Prize trip to Google headquarters in San Fransisco and I am aiming to become a mentor next year to help other students. CloudCV has helped me grow a lot in a short span of time, and I would recommend these projects to anyone who aims to expand their repertoire in Web Development and be a part of an extensive, collaborative community.
