Join CHAOSS & GrimoireLab GSoC 2020!

CHAOSS and GrimoireLab is part of Google Summer of Code 2020! Students interested will get the opportunity to be working in a real cutting edge company with international spirit and a strong commitment with Open Source. Are you a student willing to improve your Python, Open Source and Data Science skills? Keep reading!

Why considering CHAOSS and Grimoirelab for GSoC?

Since the software development industry has declared Open Source as key for their success, more developers and companies engage in Open Source every year because it is cost efficient, it enables rapid innovation, and it promotes open standards.

CHAOSS community creates software and metrics to better understand community health within Open Source environments. One of their main components is the GrimoireLab project, a reference in Software Development analytics. GrimoireLab is widely used by organizations such as The Linux Foundation, Adobe, Wikimedia, GitLab or Uber Open Source among others.

Which kind of technologies can I find?

Participants gain valuable experience working and contributing directly with different Open Source technologies such as:

  • ElasticSearch and Kibana: ElasticSearch is a tool largely used in industry which daily help users and companies to store and analyze data. GrimoireLab uses ElasticSearch as its Non-SQL database. On the other hand, Kibana, part of the ElasticSearch ecosystem, allows users to visualize the data
  • Python and Django: GrimoireLab is written in Python3, which is one of the top three programming languages used nowadays, highly demanded by companies related with Big Data, Machine Learning or Deep Learning, plus Data engineering and Data Science jobs. In certain proposals, you will be also using Django framework for web development

How can I participate?

You can join GrimoireLab for GSoC by applying for these proposed Ideas:

1. Creating Quality Models

The GrimoireLab module Prosoul is a web application that empowers decision makers with the means to create and manage their own quality models, which are useful means to evaluate and compare software projects. This project idea is about supporting the definition of Quality Models using GrimoireLab data and Prosoul. You will work with Python, Django and ElasticSearch.

elk-stack
djangourls

2. Boosting data processing

A common execution of GrimoireLab consists in collecting data from a given repository, processing and enriching the data obtained and finally visualizing it on dynamic Web dashboards. At the core of this process there is a component called ELK, which is in charge of integrating the data finally shown on the dashboards. This project idea is about refactoring and redesigning the core of ELK using popular libraries for data management and processing such as ElasticSearch-py and Pandas.

python-pandas-install-cover
elk-stack

3. API development: Implement Social Currency Metrics system

The SCMS shows why trends occur and identifies missed pitfalls in conclusions taken from quantitative data. With an SCMS platform built natively for the CHAOSS GrimoireLab tool, open source communities can use it to facilitate members’ input in decisions essential to community health. The purpose of this project is to: Build the SCMS in GrimoireLab

4. Improve management of visualizations with Open Distro for ElasticSearch

In the current stage, GrimoireLab doesn’t provide an approach to share custom dashboards, thus limiting the end-user capabilities. This project idea is about implementing such an approach leveraging on Python, the Kibana API, ElasticSearch and OpenDistro for ElasticSearch (ODFE).

Next steps

Applications open March 16, 2020 (Central European Standard Time). You can learn more about CHAOSS and Grimoirelab and read our guidance for submitting a proposal here

Our mentors Alberto, David ,Quan , Miguel Angel, Santiago, and Valerio will help the selected candidates during the whole program.

Remember to send your proposal before deadline ends! If you have any questions, please feel free to contact us.

Good luck developers!

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