Magic Wormhole: Securely Transfer Files and Text Between Computers
This repository profile is provided by osrepos.com, an open source repository discovery platform.

Summary
Magic Wormhole is an open-source tool that enables secure and easy transfer of files, directories, or text snippets between computers. It uses unique, human-pronounceable "wormhole codes" to identify endpoints, ensuring safe, one-time use transfers without complex setup. This Python-based utility simplifies cross-device data sharing with strong cryptographic guarantees.
Repository Information
Topics
Click on any tag to explore related repositories
Use at your own risk
OSRepos shares public repositories for knowledge and discovery only. Any installation, execution, configuration, or use of code from these repositories is the user's own responsibility. Always review the repository, source code, dependencies, licenses, and security implications before running or installing anything. OSRepos is not responsible for issues, damages, or losses resulting from third-party repositories.
Introduction
Magic Wormhole is an innovative open-source tool designed to facilitate the secure and straightforward transfer of files, directories, and short pieces of text between computers. Developed by the magic-wormhole organization, this Python-based utility simplifies the often-complex process of moving data across different machines. It achieves this by using unique, human-pronounceable "wormhole codes" that act as a shared secret between the sending and receiving endpoints, ensuring that only the intended parties can access the data. Each wormhole code is single-use, enhancing security and privacy.
Installation
Magic Wormhole is widely available and can be installed through various operating system package managers. For detailed instructions or to install it without an OS package, refer to the official documentation. The project is compatible with Python 3.10 and higher.
# Example for pip installation (refer to docs for recommended method)
pip install magic-wormhole
For comprehensive installation guides, please visit the Installation documentation.
Examples
Using Magic Wormhole is intuitive. The sending machine generates a wormhole code, which is then typed into the receiving machine. For instance, to send a file:
On the sending machine:
wormhole send my_document.pdf
This command will output a wormhole code, such as "4-purple-dragon".
On the receiving machine:
wormhole receive 4-purple-dragon
Upon entering the correct code, the file transfer will commence securely. You can also send text or entire directories with similar commands.
Why Use It
Magic Wormhole stands out for its emphasis on security and user-friendliness. The human-pronounceable, single-use codes eliminate the need for complex key exchanges or server configurations, making secure transfers accessible to everyone. Its cryptographic design ensures that data is transferred safely, protecting it from eavesdropping. Whether you need to quickly share a document with a colleague or move files between your own devices, Magic Wormhole provides a robust, efficient, and secure solution.
Links
- GitHub Repository: https://github.com/magic-wormhole/magic-wormhole
- Official Documentation: https://magic-wormhole.readthedocs.io
- PyPI Package: https://pypi.python.org/pypi/magic-wormhole
- PyCon 2016 Presentation Video: https://youtu.be/oFrTqQw0_3c
Related repositories
Similar repositories that may be relevant next.

TensorRT-LLM: Optimizing Large Language Model Inference on NVIDIA GPUs
July 3, 2026
TensorRT-LLM is an open-source library by NVIDIA designed to optimize inference for Large Language Models (LLMs) and Visual Generation models. It offers a user-friendly Python API, state-of-the-art optimizations, and specialized kernels to ensure efficient performance on NVIDIA GPUs. This powerful tool enables developers to deploy LLMs with high throughput and low latency, from single-GPU setups to multi-node deployments.

DataDreamer: Streamlining Synthetic Data Generation and LLM Workflows
July 3, 2026
DataDreamer is an open-source Python library designed for efficient prompting, synthetic data generation, and model training workflows. It simplifies the process of creating complex LLM workflows, generating high-quality synthetic datasets, and aligning or fine-tuning models. Built to be simple, efficient, and research-grade, DataDreamer empowers users to build reproducible and shareable AI solutions.
EasyInstruct: An Easy-to-Use Instruction Processing Framework for LLMs
July 2, 2026
EasyInstruct is an open-source Python framework designed to simplify instruction processing for Large Language Models (LLMs). Accepted at ACL 2024, it offers modularized components for instruction generation, selection, and prompting, supporting various LLMs like GPT-4 and LLaMA. This framework is ideal for researchers and developers working on LLM-based experiments and applications.

LazyLLM: Low-Code Development for Multi-Agent LLM Applications
July 2, 2026
LazyLLM offers a low-code development tool designed for building multi-agent LLM applications with ease. It simplifies the creation of complex AI applications, providing a streamlined workflow for rapid prototyping, data feedback, and iterative optimization. Developers can leverage its extensive features for deployment, cross-platform compatibility, and efficient model fine-tuning.
Source repository
Open the original repository on GitHub.
14 counted GitHub visits