epam/OSCI

Open Source Contributor Index

Owned by EPAM Systems

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epam/OSCI has 150+ stars and 100+ forks on GitHub, is written in Python, and was last pushed on Mar 6, 2025. Data as of . Signed-in members get hourly updates — create a free account.

Summary Information

Updated 41 minutes ago
Added to GitGenius on October 12th, 2026
Created on September 10th, 2019
Open Issues & Pull Requests: 37 (+0)
GitHub issues: Enabled
Number of forks: 112
Total Stargazers: 191 (+0)
Total Subscribers: 11 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 16.7 hours
Mean response time: 14.7 hours
90th percentile: 27.2 hours
Tracked items: 3

Charts & Analytics

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Issue Activity (beta)

Open issues: 4
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 633 days
Stale 30+ days: 4
Stale 90+ days: 3

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

Top labels

  • help wanted (1)
  • question (1)

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Detailed Description

OSCI is an analytics platform that tracks and measures open source activity on GitHub by commercial organizations.

The project addresses the need to understand contribution trends across the commercial open source ecosystem. It processes GitHub push event data from GH Archive to identify and rank organizations by their open source engagement. The system links commit authors to commercial organizations using email domain matching, then calculates two key metrics: active contributors (those with ten or more commits in a period) and total community (anyone making at least one commit). This approach provides organizations, communities, and analysts with visibility into how commercial entities participate in open source development.

Organizations considering adoption should understand that OSCI focuses exclusively on commercial entities and explicitly excludes universities, research institutions, non-profits, and individual entrepreneurs from its rankings. The tool suits companies wanting to benchmark their open source contributions against competitors or track their own engagement over time. Any organization can submit its email domains for inclusion in the ranking through a pull request to the company domain match list, selecting from predefined industry categories. The system processes data with a one-month lag, so newly added organizations appear in rankings at the start of the following month.

The project maintains active development with regular updates to its data processing pipeline and ranking system. The codebase uses Python and PySpark for data processing, with Azure Functions for cloud infrastructure. The team actively reviews and merges community contributions for adding new organizations to the index. Documentation includes clear contribution guidelines and a structured process for company submissions, indicating ongoing engagement with both technical contributors and the organizations being tracked.