Hacktoberfest 2018 T-Shirt and goodies

Hacktoberfest 2018

Hacktoberfest is an initiative by DigitalOcean and Github that is held every year in October to promote Open Source software development. To win a T-Shirt and some goodies, one had to submit five pull requests for any project on Github and get it merged. I contributed by adding 3 of my projects to this challenge as I wanted to help the people who were new to the open source world. These were:

  1. yoda: Personal assistant, based on the command line, implemented in Python.

    • I had many ideas that I wanted to be implemented in this project, and many enhancements were suggested from the community as well.
    • There were many contributions to yoda this year as well, and I was able to release v0.4.0 for this project.
    • The next goal of this project would be the first stable release of yoda.
  2. stlmp: Implementation of data structures and algorithms in C++, like the Standard Template Library (STL).

    • I added this because I hoped the beginners who did not have any knowledge of how professional software projects work and were only familiar with implementing Algorithms and data structures.
    • I also encouraged the contributors to write tests for the algorithms they write, so that they would gain some familiarity with software testing.
  3. IdeaTrackerPlus: Android app - Idea tracking for the creative ones.

    • This project also attracted some contributors this year, but not as much as last year.

It was a great experience, interacting with so many developers from all around the world, discussing ideas, reading their code, etc. I am looking forward to the next year, where I am hoping to host more projects than this year and contributing to some exciting projects as well.

This was my second time as a participant and a maintainer during Hacktoberfest, and I intend to continue contributing to open-source software for the next many more years too.

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Man Parvesh Singh Randhawa
Software Enthusiast | Life-long learner

I am a Software Engineer interested in efficient large-scale distributed software systems.

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