Generates call graphs for Python, JavaScript, Ruby, and PHP to visualize code structure and dependencies.
Code2flow is a static analysis tool that generates call graphs for dynamic programming languages like Python, JavaScript, Ruby, and PHP. It helps developers visualize the flow of function calls in their codebase to understand dependencies, untangle complex logic, and identify unused functions. The tool uses AST parsing and heuristics to approximate call relationships where exact determination is impossible due to dynamic language features.
Developers working with dynamic language codebases who need to understand, refactor, or document complex projects, especially those dealing with legacy or spaghetti code. It's also useful for technical leads onboarding new team members.
Code2flow offers a practical, multi-language solution for call graph generation where perfect accuracy is unattainable. Its straightforward CLI and library interface, combined with the ability to filter subgraphs, make it a lightweight yet powerful tool for code exploration without heavy IDE dependencies.
Pretty good call graphs for dynamic languages
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Generates call graphs for Python, JavaScript, Ruby, and PHP from a single tool, as highlighted in the README's features and installation sections.
Allows focusing on specific functions with configurable upstream and downstream depth limits, useful for isolating code areas, demonstrated in CLI examples.
Automatically trims unused functions in the graph output, helping identify dead code, mentioned in the key features.
Can be used via command-line for quick graphs or imported as a Python library for programmatic use, offering multiple integration options.
The README admits static analysis cannot perfectly handle dynamic language features like duck typing, leading to skipped or mislinked function calls.
Lambda expressions and generated functions are excluded from analysis, which omits significant parts of modern, functional codebases.
Requires Graphviz for output and additional parsers for some languages (e.g., Acorn for JS), adding complexity beyond a simple pip install.