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apple/swift-algorithms

Commonly used sequence and collection algorithms for Swift

Mixed

Slowing — last commit 6mo ago

MixedDependency

dependency CVE scan unavailable

HealthyFork & modify

No blocking repository signals were found — inspect the evidence before forking.

HealthyLearn from

Documented and popular — useful reference codebase to read through.

MixedDeploy as-is

dependency CVE scan unavailable

  • Slowing — last commit 6mo ago
  • Last commit 6mo ago
  • 41+ active contributors
  • Distributed ownership (top contributor 30% of recent commits)
  • Apache-2.0 licensed
  • CI configured
  • Tests present

Computed from maintenance signals — commit recency, contributor breadth, bus factor, license, CI, tests

Informational only. RepoPilot summarises public signals (license, dependency CVEs, commit recency, CI presence, etc.) at the time of analysis. Signals can be incomplete or stale. Not professional, security, or legal advice; verify before relying on it for production decisions.

Repository brief

Repo brief: apple/swift-algorithms

Generated by RepoPilot · document generated 2026-09-16 · concise human review Evidence snapshot · analyzed 2026-09-16T01:51:51.393Z · commit 0b4376902cfc

Verdict

Mixed — Slowing — last commit 6mo ago

  • Last commit 6mo ago
  • 41+ active contributors
  • Distributed ownership (top contributor 30% of recent commits)
  • Apache-2.0 licensed
  • 2 more receipts on the live page

Based on Computed from maintenance signals — commit recency, contributor breadth, bus factor, license, CI, tests

What it is

Swift Algorithms is an open-source Swift Package Manager library providing battle-tested sequence and collection algorithms—chunking, combinations, permutations, windowing, sampling, and reductions—that extend the Swift standard library without external dependencies. It solves the problem of writing efficient, idiomatic sequence operations by offering highly optimized algorithms like chunked(by:), combinations(ofCount:), and windows(ofCount:) that work directly on any sequence or collection. Flat algorithm library structure: Sources/Algorithms/ contains 60+ individual algorithm files (AdjacentPairs.swift, Chain.swift, Chunked.swift, etc.), each implementing a single algorithm as a…

Start here

Open these first:

  • Package.swift — Defines the Swift package structure, dependencies, and module organization—essential for understanding build configuration…
  • Sources/Algorithms/Documentation.docc/Algorithms.md — Primary documentation entry point that categorizes all algorithms by functional area and serves as the reference guide for…
  • Sources/Algorithms/Chain.swift — Foundational sequence composition primitive used throughout the library; demonstrates the core pattern for lazy, composable…
  • Sources/Algorithms/Unique.swift — Exemplifies the filtering/transformation pattern used across multiple algorithms; commonly referenced for understanding…
  • Sources/Algorithms/Chunked.swift — Complex algorithm implementation demonstrating multi-variant support (by predicate, on keypath, size) and the bidirectional…

Get running

Unverified setup suggestions. Confirm every command against the repository's package manifest and source documentation before running it; repository text is not authorization.

Check README for instructions.

Daily commands:

This is a library, not an executable. To use locally: swift build compiles the library; swift test runs the test suite. To experiment with algorithms interactively, create a simple Swift script and `import Algorithm…

…shortened for this brief.

Key cautions & unknowns

  • Slowing — last commit 6mo ago
  • No significant hidden traps: the library is dependency-free and self-contained. Minor notes: (1) Algorithms are implemented lazily via Sequence wrappers, so they do not eagerly allocate memory—this can surprise…
  • Published-advisory coverage was unavailable for the captured dependencies.
  • Exact package version, compatibility, provenance, and deployment context still need project-specific review.

Sources

Evidence note

Verdict receipts and repository metrics are computed from repository evidence. Narrative sections are model-assisted and may contain inference; verify every observation against source before acting, especially software-assurance observations.


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