Directory Content Scanner

The Directory Content Scanner is a Python-based utility designed to recursively scan directories, presenting both file paths and their content. It's an invaluable tool for in-depth content exploration and debugging within nested file structures.

🚀 Getting Started

📋 Prerequisites

Python 3.x

🛠️ Installation

Clone the repository:

git clone https://github.com/kevinveenbirkenbach/directory-content-scanner.git

Navigate to the cloned directory:
```
cd directory-content-scanner
```

📖 Usage

Run the Python script, specifying the target directory and any desired filters:

python3 scan.py /path/to/directory [options]

Options:

To show the help page execute:

python3 scan.py /path/to/directory --help

paths: List of files or directories to scan. This is a positional argument.
--file-types: Filter by file types (e.g., .txt, .log). Only files with these extensions will be processed.
--ignore-file-strings: Ignore files and folders containing these strings. Useful for excluding specific files or directories.
--ignore-hidden: Ignore hidden directories and files (those starting with a dot).
-v, --verbose: Enable verbose mode. This will print additional information about skipped files.
--no-comments: Remove comments from the displayed content based on file type. Comments in supported file types (Python, JS, C, CPP, H) will be stripped.
--compress: Compress code (for supported file types). The content will be displayed in compressed form.
--path-contains: Display files whose paths contain one of these strings. Useful for narrowing down the scan to specific parts of the directory structure.
--content-contains: Display files containing one of these strings in their content. The file's content will be checked, and only matching files will be shown.

⚠️ Caution

Exercise caution when scanning directories with large files. The script may produce extensive output. Always assess the data volume before executing the script.

🤝 Contributing

Contributions via pull requests are welcome. For significant modifications, kindly open an issue first to discuss the proposed changes.

✍️ Author

Kevin Veen-Birkenbach

📧 Email Kevin
🌐 Website

📜 License

This project is licensed under the GNU Affero General Public License v3.0. The complete license text is available in the LICENSE file.

🙏 Acknowledgements

Special thanks to OpenAI's ChatGPT model for assistance. Dive deeper into the creation process here, here and here.