awesome-swift vs awesome-v

Swift and V ecosystem directories compared

awesome-swift and awesome-v are community-curated directories for discovering projects and learning resources in their respective language ecosystems. awesome-swift emphasizes Swift libraries and development resources, while awesome-v organizes V applications, libraries, tools, and community materials.

awesome-swiftawesome-v
LanguageRuby—
LicenseCC0-1.0CC0-1.0
Stars26.3k2.1k
Forks3.1k144
Last analyzedOct 10, 2026Oct 22, 2026

Key differences

  • awesome-swift covers Apple-platform development, server-side Swift, and resources marked as Linux-ready; awesome-v covers V projects across areas such as web development, graphics, databases, and scientific computing.
  • awesome-swift groups resources into categories including networking, testing, and concurrency; awesome-v organizes entries around applications, libraries, and other resources.
  • awesome-swift lists official documentation, style guides, and newsletters; awesome-v includes editor support, online playgrounds, and community links.
  • The repository language is listed as Ruby for awesome-swift; awesome-v's repository language field is empty.
  • Both directories use the CC0-1.0 license, and both are marked as not archived.
  • The provided figures list 26.3k stars and 3.1k forks for awesome-swift, compared with 2.1k stars and 142 forks for awesome-v.

Choose awesome-swift if you…

  • need a directory focused on Swift libraries, developer tools, and learning resources.
  • want to explore Swift resources across Apple platforms, server-side development, or Linux-ready entries.
  • are looking for Swift categories such as networking, testing, or concurrency.
Read the awesome-swift analysis →

Choose awesome-v if you…

  • need a directory of V applications, libraries, frameworks, and bindings.
  • want V learning resources such as books, tutorials, editor support, or playgrounds.
  • are exploring V projects in areas such as web development, graphics, databases, or scientific computing.
Read the awesome-v analysis →

Compare the numbers side by side, or add more projects

This comparison is generated with AI from the OSRepos analyses of both projects. Always check each project's repository and documentation before choosing.