> ## Documentation Index
> Fetch the complete documentation index at: https://codegeninc-jay-docs-fixes-24.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Codegen

export const CODEGEN_SDK_GITHUB_URL = "https://github.com/codegen-sh/codegen-sdk";

export const COMMUNITY_SLACK_URL = "https://community.codegen.com";

[Codegen](https://github.com/codegen-sh/codegen-sdk) is a python library for manipulating codebases.

It provides a scriptable interface to a powerful, multi-lingual language server built on top of [Tree-sitter](https://tree-sitter.github.io/tree-sitter/).

export const metaCode = `from codegen import Codebase

# Codegen builds a complete graph connecting
# functions, classes, imports and their relationships
codebase = Codebase("./")

# Work with code without dealing with syntax trees or parsing
for function in codebase.functions:
    # Comprehensive static analysis for references, dependencies, etc.
    if not function.usages:
        # Auto-handles references and imports to maintain correctness
        function.remove()

# Fast, in-memory code index
codebase.commit()
`;

export const code = `def foo():
  pass

def bar():
  foo()

def baz():
  pass
`;

<iframe
  width="100%"
  height="370px"
  scrolling="no"
  src={`https://codegen.sh/embedded/codemod/?code=${encodeURIComponent(
metaCode
)}&input=${encodeURIComponent(code)}`}
  style={{
backgroundColor: "#15141b",
}}
  className="rounded-xl"
/>

<Note>
  Codegen handles complex refactors while maintaining correctness, enabling a broad set of advanced code manipulation programs.
</Note>

<Tip>Codegen works with both Python and Typescript/JSX codebases. Learn more about language support [here](/building-with-codegen/language-support).</Tip>

## Installation

```bash
# Install CLI
uv tool install codegen

# Install inside existing project
pip install codegen
```

## Get Started

<CardGroup cols={2}>
  <Card title="Get Started" icon="graduation-cap" href="/introduction/getting-started">
    Follow our step-by-step tutorial to start manipulating code with Codegen.
  </Card>

  <Card title="Tutorials" icon="diagram-project" href="/tutorials/at-a-glance">
    Learn how to use Codegen for common code transformation tasks.
  </Card>

  <Card title="View on GitHub" icon="github" href={CODEGEN_SDK_GITHUB_URL}>
    Star us on GitHub and contribute to the project.
  </Card>

  <Card title="Join our Slack" icon="slack" href={COMMUNITY_SLACK_URL}>
    Get help and connect with the Codegen community.
  </Card>
</CardGroup>

## Why Codegen?

Many software engineering tasks - refactors, enforcing patterns, analyzing control flow, etc. - are fundamentally programmatic operations. Yet the tools we use to express these transformations often feel disconnected from how we think about code.

Codegen was engineered backwards from real-world refactors we performed for enterprises at [Codegen, Inc.](/introduction/about). Instead of starting with theoretical abstractions, we built the set of APIs that map directly to how humans and AI think about code changes:

* **Natural Mental Model**: Express transformations through high-level operations that match how you reason about code changes, not low-level text or AST manipulation.
* **Clean Business Logic**: Let the engine handle the complexities of imports, references, and cross-file dependencies.
* **Scale with Confidence**: Make sweeping changes across large codebases consistently across Python, TypeScript, JavaScript, and React.

As AI becomes increasingly sophisticated, we're seeing a fascinating shift: AI agents aren't bottlenecked by their ability to understand code or generate solutions. Instead, they're limited by their ability to efficiently manipulate codebases. The challenge isn't the "brain" - it's the "hands."

We built Codegen with a key insight: future AI agents will need to ["act via code,"](/blog/act-via-code) building their own sophisticated tools for code manipulation. Rather than generating diffs or making direct text changes, these agents will:

1. Express transformations as composable programs
2. Build higher-level tools by combining primitive operations
3. Create and maintain their own abstractions for common patterns

This creates a shared language that both humans and AI can reason about effectively, making code changes more predictable, reviewable, and maintainable. Whether you're a developer writing a complex refactoring script or an AI agent building transformation tools, Codegen provides the foundation for expressing code changes as they should be: through code itself.