How does GritQL handle code that matches but shouldn't be changed?

You use powerful 'where' clauses to add conditions. For example, you can exclude matches inside test functions or only apply transformations in specific file paths.

Which languages are fully supported?

Officially supported: JavaScript, TypeScript, Python, JSON, Java, Terraform, Solidity, CSS, Markdown, YAML, Rust, Go, and SQL. Support varies by language maturity.

Can I share custom patterns with my team?

Yes. Grit has a built-in module system for importing and sharing patterns, which can be hosted or shared via a pattern library.

How does the auto-fix feature work?

The '=>' operator in GritQL defines a rewrite rule. When 'grit apply' finds a match, it replaces the matched code with the rewritten pattern directly in the source files.

What is the performance architecture behind the 10M+ line claim?

GritQL is implemented in Rust, using tree-sitter for fast, incremental parsing. It employs query optimization techniques to minimize full-AST traversals and leverage parallelism where possible.

How does the 'bubble' and scoping mechanism function?

It controls pattern matching context. By default, a pattern only matches its direct scope. 'Bubble' lets a pattern match nested sub-trees, which is essential for complex, hierarchical transformations.

Directory/Coding/Development/GritQL

GritQL

GritQL is a declarative query language for searching and modifying source code, allowing developers to perform large-scale code migrations and refactoring. It uses a simple, pattern-based syntax where any code snippet is a valid query, leveraging Rust and query optimization to handle repositories with over 10 million lines of code. The tool includes a built-in module system with over 200 standard patterns and supports auto-fix rules for faster remediation. Targeted at software engineers, tech leads, and developers, GritQL excels at automating tasks like API migrations, custom linting, code quality improvements, and dependency upgrades across multiple programming languages including JavaScript, Python, Java, and Go. It provides a CLI, VS Code extension, and playground for interactive use.

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Sep 22, 2026

Declarative Query LanguageCode ModificationMulti-LanguageCustom LintingRust Engine

Product information

Everything worth knowing about GritQL

The complete picture — from everyday features to the technical detail builders and IT folks dig for.

Core features

What it actually does

Declarative Code Search & Modify

Use a simple query language to search and transform source code with patterns and metavariables.

Auto-Fix Rules

Define patterns with auto-fix rules for automated code remediation and faster migrations.

Custom Linting

Save patterns to enforce as custom lints with powerful `where` clauses for team-specific standards.

Multi-Language Support

Works on a wide range of languages including JavaScript, TypeScript, Python, Java, Go, Rust, and more.

Pattern Library & Module System

Reuse patterns from a library of 200+ standard patterns or share your own via a built-in module system.

Technical capabilities

Rust-Powered Performance

Written in Rust with query optimization, enabling scale to repositories with millions of lines of code.

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Who uses it

Real use cases, no hype

Large-Scale Code Migrations

Systematically migrate APIs, frameworks, or syntax across entire codebases with millions of lines.

Custom Linting & Code Standards

Enforce team-specific style guides and best practices beyond standard linters.

Automated Dependency Upgrades

Automatically refactor code to handle breaking changes when upgrading libraries.

Code Quality & Consistency

Apply consistent refactoring patterns to improve overall codebase health.

Repository-wide Search

Find complex patterns, anti-patterns, or potential bugs that simple text search misses.

Framework/Platform Adoption

Convert code to a new framework (e.g., migrate to a new React version) in bulk.

Cross-Language Consistency

Enforce similar patterns or naming conventions across different language services.

What's great

Start with simple code snippets, no AST expertise needed.
Scales to massive codebases (10M+ lines) via Rust optimization.
Works across 12+ major languages from a single query language.
Built-in module system with 200+ ready-to-use patterns.
Includes auto-fix rules for direct code remediation.

Technical strengths

Written in Rust for high performance and memory safety.
Uses a tree-sitter based parser for accurate multi-language AST handling.

Where it falls short

Steep learning curve for complex pattern authoring.
Primarily CLI-focused; VS Code integration exists but is an add-on.
Community and ecosystem are still growing compared to older tools.
Learning a new query language (GritQL) is an upfront investment.

Technical limitations

Complex transformations can become verbose and harder to debug.
Debugging failed matches requires understanding the AST 'bubble' concept.

For technical folks

The deep-dive specs

FAQ

Includes technical Q&A

No, that's the core design. Any valid code snippet in your target language is a valid starting point for a GritQL query. You work with code patterns, not raw AST nodes.