codebatcher 0.1.1

Codebase Batcher (cbatch) - CLI tool to output codebase to structured file for AI context.

Codebatcher (cbatch)

A CLI tool that formats your codebase into a structured markdown file, making it easier to provide context to AI tools like ChatGPT or Claude.

Features

• 📝 Converts your entire codebase into a single, well-structured markdown file
• 🎯 Intelligent file filtering with .cbatchignore support
• ⚙️ Configurable project metadata through cbatch.ini
• 📊 Token estimation for AI context windows
• 🚀 Simple and intuitive CLI interface

Installation

Install codebatcher using pip:

pip install codebatcher

Quick Start

1. Navigate to your project directory:

cd your-project

2. Initialize cbatch configuration:

cbatch init

3. Generate the structured codebase file:

cbatch update

Commands

• cbatch init - Initialize configuration and create default ignore patterns
• cbatch update [path] [output-file] - Update/create the structured codebase file
• cbatch tokens - Display estimated token count for the generated file

Configuration

cbatch.ini

During initialization (cbatch init), you can configure:

• Codebase Type (e.g., FastAPI backend, React frontend)
• Deployment Location
• General Description
• Execution Command

Example cbatch.ini:

[General]
codebase_type = FastAPI backend
deployment_location = AWS
general_description = REST API for user management
execution_command = uvicorn main:app --reload

[Summary]
input_token_estimate = 12345

.cbatchignore

Similar to .gitignore, specify patterns for files and directories to exclude. Default patterns include:

• Common version control files (.git/, .gitignore)
• Build artifacts (*.pyc, build/, dist/)
• Environment files (.env, venv/)
• Dependencies (node_modules/)
• System files (.DS_Store)
• Temporary files (*.swp, temp/, tmp/)
• Log files (*.log)

Add custom patterns by editing .cbatchignore:

# Custom ignore patterns
secrets/
*.config.js
private/*

Output Format

The generated markdown file (codebatch.md by default) includes:

1. Instructions section
2. General project information
3. Structured listing of all codebase files with their contents

Example structure:

# Instructions #

This file represents the entire codebase...

## General Info ##

**Codebase Type**: FastAPI backend
**Deployment Location**: AWS
...

## Files ##

### `src/main.py` ###
```python
# File contents here

## Use Cases

- Providing context to AI tools about your entire codebase
- Generating documentation overviews
- Sharing code context with team members
- Creating structured backups of your source code

## Token Estimation

The tool provides a simple word-count based token estimation to help you stay within AI context windows. Check the current estimate using:

```bash
cbatch tokens

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

MIT License

Author

Zach ([e-mail])