#Code Analysis

Swift-code-metrics analyzes project architecture by evaluating key metrics such as LOC, NOC, and framework dependencies, offering detailed insights into multiple-module Swift applications. This Python-dependent tool generates comprehensive reports and visual graphs, ideal for medium to large codebases. Installation is via pip, with optional arguments to customize output. Note that spm libraries and specific comment types may not be supported, and optimal function requires an appropriate file hierarchy.

SwiftLint offers a robust toolset for enforcing Swift coding conventions, enhancing code quality and consistency across various projects. By utilizing Clang and SourceKit for precise linting through AST analysis, SwiftLint supports flexible installation via Swift Package Manager, CocoaPods, and other methods, catering to diverse development needs. It can be seamlessly integrated into CI pipelines, employed as a command-line utility, or even used within a Docker container. SwiftLint is engineered for straightforward integration and configuration, reinforcing adherence to widely-recognized Swift style guides without unnecessary complexity.