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To index a multi-language codebase for functions and call graphs, you can build a local SQLite database by loading the tree-sitter-db environment and invoking tsdb on your target repository. This extracts code structure into searchable SQL tables.

Yes, you can analyze Python, C, and C++ codebases together by indexing them into a single local SQLite database. The tool uses tree-sitter to parse multiple languages, allowing cross-language architecture navigation and dependency analysis.

The best way to navigate code architecture and understand change impact is by querying an indexed SQLite database of your codebase. It stores functions, classes, imports, and call graphs, enabling SQL-based exploration of dependencies across modules.

Tree-sitter code indexing works by parsing source code into syntax trees and extracting functions, classes, imports, and variables into a local SQLite database. You then use SQL queries to find callers and callees by traversing the stored call graphs.

Yes, you need to source the tree-sitter-db environment before running tsdb on your repository. Sourcing the environment ensures the required parsing tools are available to build the SQLite index of functions, classes, and call graphs.

A limitation of using SQLite for code navigation is that it requires building a local database index first, meaning it reflects the codebase state at index time rather than real-time. It currently supports Python, C, and C++ codebases.