codebase-to-text 1.2

A Python package to convert codebase to text

Codebase to Text Converter

A powerful Python tool that converts codebases (folder structures with files) into a single text file or Microsoft Word document (.docx), while preserving folder structure and file contents. Perfect for AI/LLM processing, documentation generation, and code analysis.

✨ Features

• Multi-source input: Local directories and GitHub repositories
• Flexible output: Text files (.txt) and Microsoft Word documents (.docx)
• Smart exclusions: Advanced pattern matching for files and directories
• Performance optimized: Efficient traversal of large codebases
• Comprehensive logging: Detailed verbose mode for transparency
• Encoding support: Handles various file encodings gracefully

🚀 Installation

pip install codebase-to-text

📖 Usage

Command Line Interface (CLI)

Basic Usage

codebase-to-text --input "path_or_github_url" --output "output_path" --output_type "txt"

Advanced Usage with Exclusions

# Exclude specific patterns
codebase-to-text --input "./my_project" --output "output.txt" --output_type "txt" --exclude "*.log,temp/,**/__pycache__/**"

# Multiple exclude arguments
codebase-to-text --input "./my_project" --output "output.txt" --output_type "txt" --exclude "*.pyc" --exclude "build/" --exclude "venv/"

# Exclude hidden files
codebase-to-text --input "./my_project" --output "output.txt" --output_type "txt" --exclude_hidden

# Verbose mode for detailed logging
codebase-to-text --input "./my_project" --output "output.txt" --output_type "txt" --verbose

Python API

from codebase_to_text import CodebaseToText

# Basic usage
converter = CodebaseToText(
    input_path="path_or_github_url",
    output_path="output_path",
    output_type="txt"
)
converter.get_file()

# Advanced usage with exclusions
converter = CodebaseToText(
    input_path="./my_project",
    output_path="./output.txt",
    output_type="txt",
    exclude=["*.log", "temp/", "**/__pycache__/**"],
    exclude_hidden=True,
    verbose=True
)
converter.get_file()

# Get text content without saving to file
text_content = converter.get_text()
print(text_content)

🎯 Exclusion Patterns

The tool supports powerful exclusion patterns to filter out unwanted files and directories:

Pattern Types

1. Exact filename: README.md, config.yaml
2. Wildcard patterns: *.log, *.tmp, test_*
3. Directory patterns: __pycache__/, .git/, node_modules/
4. Recursive patterns: **/__pycache__/**, **/node_modules/**
5. Path-based patterns: src/temp/, docs/build/

Exclusion Sources

1. CLI Arguments: Use --exclude flag (can be used multiple times)
2. .exclude file: Place in your project root (see example below)
3. Default patterns: Common files/folders are excluded automatically

Default Exclusions

The tool automatically excludes common development files:

• .git/, __pycache__/, *.pyc, *.pyo
• node_modules/, .venv/, venv/, env/
• *.log, *.tmp, .DS_Store
• .pytest_cache/, build/, dist/

📝 .exclude File Example

Create a .exclude file in your project root:

# .exclude file - Patterns for files/folders to exclude

# Version control
.git/
.gitignore

# Python
__pycache__/
*.pyc
venv/
.pytest_cache/

# Node.js
node_modules/
*.log

# IDE files
.vscode/
.idea/

# Project specific
config/secrets.yaml
data/large_files/

🔧 CLI Parameters

Parameter	Description	Example
--input	Input path (local folder or GitHub URL)	./my_project or https://github.com/user/repo
--output	Output file path	./output.txt
--output_type	Output format (txt or docx)	txt
--exclude	Exclusion patterns (repeatable)	--exclude "*.log" --exclude "temp/"
--exclude_hidden	Exclude hidden files/folders	Flag (no value)
--verbose	Enable detailed logging	Flag (no value)

💡 Examples

Convert Local Project

# Basic conversion
codebase-to-text --input "~/projects/my_app" --output "my_app_code.txt" --output_type "txt"

# With custom exclusions
codebase-to-text --input "~/projects/my_app" --output "my_app_code.txt" --output_type "txt" --exclude "*.log,build/,dist/" --verbose

Convert GitHub Repository

# Public repository
codebase-to-text --input "https://github.com/username/repo" --output "repo_analysis.docx" --output_type "docx"

# With exclusions for cleaner output
codebase-to-text --input "https://github.com/username/repo" --output "repo_clean.txt" --output_type "txt" --exclude "*.md,docs/,examples/"

Python Integration

# Analyze a codebase programmatically
from codebase_to_text import CodebaseToText

def analyze_codebase(project_path):
    converter = CodebaseToText(
        input_path=project_path,
        output_path="analysis.txt",
        output_type="txt",
        exclude=["*.log", "test/", "**/__pycache__/**"],
        verbose=True
    )
    
    # Get the content
    content = converter.get_text()
    
    # Process with your preferred LLM/AI tool
    # analysis_result = your_ai_tool.analyze(content)
    
    return content

# Usage
code_content = analyze_codebase("./my_project")

🎯 Use Cases

• AI/LLM Training: Prepare codebases for language model training
• Code Review: Generate comprehensive code overviews for review
• Documentation: Create single-file documentation from projects
• Analysis: Feed entire codebases to AI tools for analysis
• Migration: Document legacy codebases before migration
• Learning: Study open-source projects more effectively

🔄 Output Format

The generated output includes:

1. Folder Structure: Tree-like representation of the directory structure
2. File Contents: Full content of each file with metadata
3. Clear Separators: Distinct sections for easy navigation

✒️ License

License This project is licensed under the MIT License - see the LICENSE file for details.