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Popularity Metrics Explained ​

This page explains the key popularity metrics tracked by LFX Insights. These indicators help you understand how widely adopted and talked-about an open source project is across the web and developer ecosystem.

Stars ​

What it is: The number of stars a project has received on GitHub.

Why it matters: Stars are a quick way for users to express interest. A high star count suggests broad awareness and community appreciation.

Forks ​

What it is: The number of times a project has been forked on GitHub.

Why it matters: Forks often indicate developer interest in modifying, contributing to, or building on top of a project.

Social Mentions ​

Coming soon.

What it is: Mentions of the project across platforms like Twitter/X, Reddit, Hacker News, and other social media.

Why it matters: Social mentions show real-time buzz and community conversations, signaling current relevance and visibility.

GitHub Mentions ​

Coming soon.

What it is: References to the project repository in issues, pull requests, and READMEs on GitHub.

Why it matters: Frequent GitHub mentions show that developers are integrating or referencing the project in their workflows and codebases.

Press Mentions ​

Coming soon.

What it is: The number of times the project is mentioned in online news outlets, blogs, and tech media.

Why it matters: Press mentions reflect broader industry attention and can drive credibility and adoption beyond the developer community.

Search Queries Volume ​

What it is: The volume of search engine queries for the project.

Why it matters: Search trends indicate public interest and awareness. A rising number of queries often correlates with growing adoption.

How the Data Is Collected ​

To estimate search volume, we use Keywords Everywhere, a third-party API that provides monthly search trends based on aggregated data from platforms like Google Trends and Keyword Planner.

For each project:

  • The project's slug (e.g., linux, datahub) is used as the query term. This assumes the slug most accurately reflects the name users would search for.
  • Query the Keywords Everywhere /v1/get_keyword_data endpoint to return the monthly search volume estimates for the last 12 months.
  • The historical aggregation is designed to be run monthly. Each run captures a rolling 12-month window.

Note: Historical data before June 2024 is unavailable, as we initiated data collection in June 2025.

Package Downloads ​

What it is: The total number of downloads for a project’s packages across supported package registries (e.g., PyPI, npm, Maven, Conda, Docker Hub).

Why it matters: High download counts are a strong signal of adoption and usage. They indicate how widely the project is being installed, integrated, and potentially relied upon by users and systems in the ecosystem.

How the Data Is Collected ​

Package download data is retrieved using the ecosyste.ms API.

For each project repository:

  • Query the ecosyste.ms /packages/lookup endpoint to retrieve all packages linked to that repository.
  • For each package, it pulls the downloads_count (downloads from the primary registry) and docker_downloads_count (if applicable).
  • The historical aggregation is designed to be run daily. Each run captures a rolling 24-hours window.

These values are aggregated and stored, grouped by registry and package name.

Note: Historical data prior to June 1, 2025 is unavailable, as data collection began on that date.

Package Dependency ​

What it is: A set of metrics reflecting how many other repositories, packages, or Docker images depend on the project’s packages.

Why it matters: Dependency data is a proxy for influence and integration within the software ecosystem. If many other projects or containers depend on a package, it suggests trust, stability, and criticality.

How the Data Is Collected ​

Package download data is retrieved using the ecosyste.ms API.

For each project repository:

  • Query the ecosyste.ms API to retrieve associated packages across various registries.
  • For each package, it collects:
    • dependent_repos_count: Number of repositories that depend on the package.
    • dependent_packages_count: Number of packages that list this package as a dependency.
    • docker_dependents_count: Number of Docker images that rely on the package.
  • The historical aggregation is designed to be run daily. Each run captures a rolling 24-hours window.

These values are aggregated and stored, grouped by registry and package name.

Historical data prior to June 1, 2025 is unavailable, as data collection began on that date.

Mailing List Messages ​

This metric is only available for selected projects of the Linux Foundation.

What it is: The number of messages exchanged on the project’s public mailing lists.

Why it matters: Mailing list activity reflects the depth and frequency of technical discussions, support requests, and community coordination.