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https://github.com/bsc-dom/dataclay

Python distributed data store that enables remotely access and method execution.
https://github.com/bsc-dom/dataclay

active-storage distributed-computing distributed-database distributed-storage parallel-computing python

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Python distributed data store that enables remotely access and method execution.

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![dataClay](https://github.com/bsc-dom/dataclay/blob/main/docs/_static/dataclay-full.png)


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dataClay is a distributed data store that enables applications to store and access objects in the same format they have in memory, and executes object methods within the data store. These two main features accelerate both the development of applications and their execution.

## Installation

To install dataClay, you can use [pip](https://pip.pypa.io):

```bash
pip install dataclay
```

Alternatively, you can obtain the latest source code from [GitHub](https://github.com/bsc-dom/dataclay):

```bash
git clone https://github.com/bsc-dom/dataclay.git
cd dataclay
pip install .
```

## Documentation

dataClay has usage and reference documentation at [dataclay.readthedocs.io](https://dataclay.readthedocs.io/en/latest/)

## Contributing

We welcome contributions to dataClay. Please see the [Contributing](https://dataclay.readthedocs.io/en/latest/contributing.html) for more details.

## Maintainers

- [@alexbarcelo](https://github.com/alexbarcelo) (Alex Barcelo)
- [@aqueralt](https://github.com/aqueralt) (Anna Queralt)
- [@marcmonfort](https://github.com/marcmonfort) (Marc Monfort)
- [@Canicula98](https://github.com/Canicula98) (David Cano)

## Other resources

[BSC official website](https://www.bsc.es/dataclay)

## Acknolwedgments

See the [full list of acknowledgments](ACKNOWLEDGMENTS.md)