ultragtx / MD2CryptQR

aka 遗言加密器

Home Page:https://ultragtx.github.io/MD2CryptQR/

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MD2CryptQR

Introduction

MD2CryptQR is a powerful tool that transforms your Markdown files into secure, encrypted QR codes, making it simple to share and distribute sensitive text data. The package consists of two main components: a Python-based encryptor and a web-based decryptor for quick and easy viewing.


Table of Contents


Installation

Encryptor Installation

  1. To install the encryptor, first download the source code from GitHub or clone the repository.

  2. Open your terminal, navigate to the encryptor-py directory, and run:

    cd encryptor-py
    pip install -r requirements.txt

Decryptor Installation


Usage

Encryptor Command Line Options

Navigate to the folder containing your Markdown file and execute the following command:

python encryptor/main.py [OPTIONS]

Here are the available options:

  • -i, --input: (Required) Input Markdown file path.
  • -o, --output: Output PDF file path. Default is output.pdf.
  • -e, --error_correction: Level of QR error correction. Options are L, M, Q, H. Default is L.
  • -l, --qr_data_length: The data length for each QR code. Default is 700.
  • -c, --compact_mode: Enable compact mode. In this mode, The encryptor will not split the content into sections based on Markdown title syntax, and will not print titles for each section.

Example:

python encryptor/main.py -i ../README.md -o ../sample-output/output-compact.pdf -e M -l 700 -c

You can find sample PDF outputs generated using standard and compact modes in the repository, created using password "123". Click the links below to view or download them:

Decryptor Usage

  1. Go to the web-based decryptor, either hosted on GitHub or your private HTTPS server.
  2. Input the password used during encryption.
  3. Scan each QR code in the generated document.

Special Acknowledgment A substantial portion of this project was enhanced through interactions with OpenAI's GPT-4 model. The language model aided in generating documentation, code refinement, and idea generation.


Credits

Contributors

Special Thanks

  • OpenAI's GPT-4: For contributing a substantial amount of code and aiding in documentation.

Thank you for using MD2CryptQR. For further assistance, please visit our GitHub repository.

About

aka 遗言加密器

https://ultragtx.github.io/MD2CryptQR/


Languages

Language:Python 51.0%Language:JavaScript 39.4%Language:CSS 6.0%Language:HTML 3.6%