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Google Summer of Code 2025 — OSGeo GRASS

What Is Google Summer of Code (GSoC)?

Nishant Bansal · 2025-06-02 15:27 · 2 claps · 4.0 min read
#osgeo #grass #gsoc
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Wiki topics: 🔒 · Cybersecurity

Google Summer of Code 2025 — OSGeo GRASS

What Is Google Summer of Code (GSoC)?

Google Summer of Code (GSoC) is a global program that brings together beginner open source developers and open-source organisations. Each summer, selected students work full-time on a specific open-source project, mentored by experienced community members. Since its inception in 2005, GSoC has helped hundreds of students gain real-world software development experience, build confidence, and contribute lasting code to major open-source ecosystems. Being accepted into GSoC is not only a validation of one’s coding skills, but also an opportunity to collaborate with seasoned mentors, learn best practices, and give back to communities that power so much of today’s technology.

Introduction

Hello everyone! I’m Nishant Bansal, a Mechanical Engineering graduate turned open-source enthusiast. Over the past year, I had the privilege of being an LFX mentee under CNCF’s KCL project, where I worked on implementing checksum verification for third-party dependencies. This experience deepened my understanding of software security and fueled my passion for contributing to open-source communities. Today, I’m thrilled to share some exciting news: I have been selected for Google Summer of Code 2025 under the OSGeo GRASS project — and I was the only candidate chosen for this organisation!

My Selection Under OSGeo GRASS

I am delighted to announce that I was selected as a GSoC participant under the OSGeo GRASS organisation for Summer 2025. Geographic Resources Analysis Support System (GRASS) is a comprehensive software suite for geographic information system (GIS) applications, focusing on geospatial data management and analysis, image processing, and the creation of graphics and maps. It facilitates spatial and temporal modeling and visualization, accommodating various spatial data types, including raster, vector, and imagery. GRASS GIS is structured to allow specific GIS computations to be performed through modules. Although its main interface operates within a Unix shell tailored for these modules, many can also be accessed via a graphical user interface.

Out of all the applicants, I was honoured to be the only student chosen for this organisation— an achievement that makes this opportunity even more special for me.

Fun fact: I submitted only one proposal to GSoC and was fortunate enough to have it selected.

Below is a direct link to my accepted GSoC project page:

Project Details

Title:

Add JSON output to different tools in C for GRASS GIS

Technologies:

C, Python, CMake, Markdown, Makefile

Abstract:

Currently, most GRASS tools produce data in plain text by default. This means that users who want to process the output in Python need to create custom parsing code. To make this easier, several modules could be improved by offering JSON as an alternative output format. Recently, the Parson library was added to the GRASS codebase to support JSON output in addition to plain text. Building on the advancements made during the last GSoC, my project aims to expand JSON output capabilities to more tools using the Parson library.

Project Goals

  1. Working with mentors to finalize the structure of the JSON output.
  2. Adding an option to choose the output format (plain text or JSON) for each updated tool.
  3. Developing Python test cases to ensure that the JSON output works correctly and to avoid future issues.
  4. Providing basic documentation and example JSON outputs for each modified tool.
  5. Develop simple examples demonstrating how to use JSON output in a data science workflow, such as reading JSON data into pandas or python.

Wiki and Ongoing Updates

I have created a dedicated Wiki page to document every aspect of this project. The wiki will include:

  • Weekly Progress Reports: Every Sunday, I will post a summary of completed tasks, encountered challenges, and plans for the next week.
  • Pull Request (PR) Links: As I submit code for review, I will link each PR on the wiki so that mentors and community members can easily track changes.

Feel free to bookmark and follow the wiki here:

Acknowledgements

I would like to express my heartfelt gratitude to my mentors Anna Petrasova, Corey White, and Vaclav Petras. They have been incredibly supportive and motivating during the application phase. Whenever I needed help, they guided me toward solutions. Our discussions throughout the contribution period were fascinating and pushed me to expand my learning.

A big thank you also goes out to the GRASS community for their unwavering support.

Finally, I’m grateful to Google for organising Google Summer of Code, which has made a tremendous positive impact on both the open-source community and me.

Conclusion

Participating in GSoC under OSGeo GRASS has been a dream come true. From my early days as an LFX mentee working on checksum verification under CNCF KCL to now leading a full-scale integration project in GRASS, this journey has been both challenging and rewarding. Over the next three months, I look forward to learning from my mentors, collaborating with fellow GRASS contributors, and delivering a robust JSON output solution that benefits the entire GIS community. I encourage anyone interested in open source to dive in — take that first step by contributing a small patch or updating documentation. You never know where it might lead!

Fun Fact: I had the opportunity to attend the GRASS Developer Summit in Raleigh, North Carolina, in May 2025, fully sponsored. Unfortunately, I was unable to go due to visa constraints — just bad luck!

Thank you for reading, and stay tuned for weekly updates on my wiki. Feel free to leave your comments or reach out if you have questions.

— Nishant Bansal


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