# plex
**A Python package for running scientific workflows on a decentralized infrastructure**
Plex is a Python package that allows scientists to run their workflows on a decentralized infrastructure. It is a client that can be used to run containers on a public network, and it supports distributed compute and storage. This means that scientists can use plex to run their workflows on any machine that is connected to the internet, and they can also use GPUs if they need them.
Plex is strictly composable, which means that every tool in plex has declared inputs and outputs. This makes it easy to plug together tools by different authors, and it also makes it easier to share results with other scientists.
In addition, every file processed by plex has a deterministic address based on its content. This means that you can always track your files and share the right results with other scientists.
The plex pip package provides a simple and easy way to install and use plex. It also includes documentation and examples to help you get started.
**Features**
- Distributed compute and storage
- Strictly composable tools
- Content-addressed files
- Easy to share results
**Benefits**
- Run your workflows on any machine that is connected to the internet
- Use GPUs if you need them
- Easy to plug together tools by different authors
- Always track your files and share the right results with other scientists
**Installation**
To install the plex pip package, you can use the following command:
```
pip install PlexLabExchange
```
**Documentation**
The plex documentation can be found at https://docs.labdao.xyz.
**Contributing**
If you would like to contribute to plex, you can do so by submitting a pull request on the GitHub [repository](https://github.com/labdao/plex).
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"description": "# plex\n\n**A Python package for running scientific workflows on a decentralized infrastructure**\n\nPlex is a Python package that allows scientists to run their workflows on a decentralized infrastructure. It is a client that can be used to run containers on a public network, and it supports distributed compute and storage. This means that scientists can use plex to run their workflows on any machine that is connected to the internet, and they can also use GPUs if they need them.\n\nPlex is strictly composable, which means that every tool in plex has declared inputs and outputs. This makes it easy to plug together tools by different authors, and it also makes it easier to share results with other scientists.\n\nIn addition, every file processed by plex has a deterministic address based on its content. This means that you can always track your files and share the right results with other scientists.\n\nThe plex pip package provides a simple and easy way to install and use plex. It also includes documentation and examples to help you get started.\n\n**Features**\n- Distributed compute and storage\n- Strictly composable tools\n- Content-addressed files\n- Easy to share results\n\n**Benefits**\n- Run your workflows on any machine that is connected to the internet\n- Use GPUs if you need them\n- Easy to plug together tools by different authors\n- Always track your files and share the right results with other scientists\n\n**Installation**\n\nTo install the plex pip package, you can use the following command:\n\n```\npip install PlexLabExchange\n```\n\n**Documentation**\n\nThe plex documentation can be found at https://docs.labdao.xyz.\n\n**Contributing**\n\nIf you would like to contribute to plex, you can do so by submitting a pull request on the GitHub [repository](https://github.com/labdao/plex).\n",
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