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https://github.com/openmined/pysyft

Perform data science on data that remains in someone else's server
https://github.com/openmined/pysyft

cryptography deep-learning federated-learning hacktoberfest privacy python pytorch secure-computation syft

Last synced: 5 days ago
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Perform data science on data that remains in someone else's server

Host: GitHub
URL: https://github.com/openmined/pysyft
Owner: OpenMined
License: apache-2.0
Created: 2017-07-18T20:41:16.000Z (over 7 years ago)
Default Branch: dev
Last Pushed: 2024-10-15T14:39:13.000Z (4 months ago)
Last Synced: 2024-10-29T09:17:06.882Z (3 months ago)
Topics: cryptography, deep-learning, federated-learning, hacktoberfest, privacy, python, pytorch, secure-computation, syft
Language: Python
Homepage: https://www.openmined.org/
Size: 667 MB
Stars: 9,482
Watchers: 199
Forks: 1,995
Open Issues: 40
Metadata Files:
- Readme: README.md
- License: LICENSE

Awesome Lists containing this project

README

Data Science on data you are not allowed to see

PySyft enables a new way to do data science, where you can use non-public information, without seeing nor obtaining a copy of the data itself. All you need is to connect to a Datasite!

Datasites are like websites, but for data. Designed with the principles of structured transparency, they enable data owners to control how their data is protected and data scientists to use data without obtaining a copy.

PySyft supports any statistical analysis or machine learning, offering support for directly running Python code - even using third-party Python libraries.

Supported on:

✅ Linux
✅ macOS
✅ Windows
✅ Docker
✅ Kubernetes

# Quickstart

Try out your first query against a live demo Datasite!

## Install Client

```bash
pip install -U "syft[data_science]"
```

More instructions are available here.

## Launch Server

Launch a development server directly in your Jupyter Notebook:

```python
import syft as sy

sy.requires(">=0.9.2,<0.9.3")

server = sy.orchestra.launch(
name="my-datasite",
port=8080,
create_producer=True,
n_consumers=1,
dev_mode=False,
reset=True, # resets database
)
```

or from the command line:

```bash
$ syft launch --name=my-datasite --port=8080 --reset=True

Starting syft-datasite server on 0.0.0.0:8080
```

Datasite servers can be deployed as a single container using Docker or directly in Kubernetes. Check out our deployment guide.

## Launch Client

Main way to use a Datasite is via our Syft client, in a Jupyter Notebook. Check out our PySyft client guide:

```python
import syft as sy

sy.requires(">=0.9.2,<0.9.3")

datasite_client = sy.login(
port=8080,
email="[email protected]",
password="changethis"
)
```

## PySyft - Getting started 📝

Learn about PySyft via our getting started guide:

- PySyft from the ground up
- Part 1: Datasets & Assets
- Part 2: Client and Datasite Access
- Part 3: Propose the research study
- Part 4: Review Code Requests
- Part 5: Retrieving Results

# PySyft In-depth

📚 Check out our docs website.

Quick PySyft components links:

- DataSite Server

- Syft Client

- Datasets API (`.datasets`)

- Users API (`.users`)

- Request API (`.requests`)

- Code API (`.code`)

- Syft Policies API (`.policy`)

- Settings API (`.settings`)

- Notifications API (`.notifications`)

- Sync API (`.sync`)

## Why use PySyft?

In a variety of domains across society, data owners have **valid concerns about the risks associated with sharing their data**, such as legal risks, privacy invasion (_misuing the data_), or intellectual property (_copying and redistributing it_).

Datasites enable data scientists to **answer questions** without even seeing or acquiring a copy of the data, **within the data owners's definition of acceptable use**. We call this process Remote Data Science.

This means that the **current risks** of sharing information with someone will **no longer prevent** the vast benefits such as innovation, insights and scientific discovery. With each Datasite, data owners are able to enable `1000x more accesible data` in each scientific field and lead, together with data scientists, breakthrough innovation.

Learn more about our work on our website.

## Support

For questions about PySyft, reach out via `#support` on Slack.

## Syft Versions

:exclamation: PySyft and Syft Server must use the same `version`.

**Latest Stable**

- `0.9.2` (Stable) - Docs
- Install PySyft (Stable): `pip install -U syft`

**Latest Beta**

- `0.9.3` (Beta) - `dev` branch 👈🏽
- Install PySyft (Beta): `pip install -U syft --pre`

Find more about previous releases here.

# Community

Supported by the OpenMined Foundation, the OpenMined Community is an online network of over 17,000 technologists, researchers, and industry professionals keen to _unlock 1000x more data in every scientific field and industry_.

# Courses

# Contributors

OpenMined and Syft appreciates all contributors, if you would like to fix a bug or suggest a new feature, please reach out via Github or Slack!

Contributors

# About OpenMined

OpenMined is a non-profit foundation creating technology infrastructure that helps researchers get answers from data without needing a copy or direct access. Our community of technologists is building Syft.

# Supporters

# License

[Apache License 2.0](LICENSE)

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