Codesearch FAQs

Question 1

How does Codesearch handle indexing and updates for large codebases?

Accepted Answer

Codesearch features fast incremental indexing. It efficiently detects and re-indexes only modified files based on mtime, size, and content hashing, avoiding costly full re-embeddings. It also integrates with Git to allow searching in recently changed files with revision history.

Question 2

Does Codesearch offer advanced filtering or query capabilities?

Accepted Answer

Yes, Codesearch provides a robust query syntax. You can precisely target your searches using filters like `function:name`, `class:name`, `path:prefix`, `-path:exclude`, and `scope:function`. It also includes synonym expansion for common programming terms.

Question 3

How does Codesearch improve search accuracy and relevance?

Accepted Answer

It leverages AST-aware chunking via Tree-sitter to understand code structure, providing contextual search. Its hybrid approach combines semantic vector embeddings with sparse TF-IDF keyword matching, fused by Reciprocal Rank Fusion (RRF), for highly accurate and relevant results.

Question 4

What programming languages does Codesearch support?

Accepted Answer

Codesearch offers full AST-aware chunking for 18 major languages like Python, JavaScript, Go, Rust, Java, C/C++, and C#. Additionally, it supports line-based fallback chunking for over 140 other file types, ensuring comprehensive coverage.

Question 5

What is Codesearch?

Accepted Answer

Codesearch is a powerful developer tool for semantic code search across over 160 programming languages. It intelligently finds relevant code snippets, functions, and classes using advanced AST-aware chunking, hybrid dense and sparse search, and a rich query syntax.

Codesearch

Codesearch

Características Principales

Casos de Uso

Características Principales

Casos de Uso