Metadata-Version: 2.1
Name: synthetig
Version: 0.0.2a1
Summary: Synthetig: An open-source synthetic data generation platform.
Home-page: https://github.com/synthetig/synthetig
Author: Jonathan Hind and Nick Lee-McMaster
Author-email: info@synthetig.ai
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3.7
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
Requires-Dist: torch (==1.6.0)
Requires-Dist: scikit-learn (==0.23.2)
Requires-Dist: numpy (==1.19)
Requires-Dist: pandas (==1.1.3)

<!-- PROJECT LOGO -->
<br />
<p align="center">

  <a href="https://github.com/synthetig/synthetig">
    <img src="logo.png" alt="Logo" width="80" height="80">
  </a>

  <h3 align="center">Synthetig</h3>
  <p align="center">   
        Synthetig is a Python package for creating synthetic data that can be trusted.
    <br />
    <a href="https://github.com/synthetig/synthetig/docs"><strong>Explore the docs »</strong></a>
    <br />
    <br />
    <a href="https://github.com/synthetig/synthetig/issues">Report Bug</a>
    ·
    <a href="https://github.com/synthetig/synthetig/issues">Request Feature</a>
  </p>

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## Table of Contents

[About the Project](#About-the-Project)

[Installing](#Installing)

[Getting Started](#Getting-Started)

[How to Get Involved](#How-to-Get-Involved)

[Contact Us](#Contact-Us)

[Citation](#Citation)


## About the Project

Synthetig is a project to make an open source synthetic data generation platform. 
It is a comprehensive platform that will make the process of generating synthetic data simple, which the user can trust.

## Installing

The easiest way to install Synthetig is by pip install:

```
$ pip install synthetig
```

## Getting Started

Generating your first synthetic data set:

```
$ python
```

```
>>> from synthetig import Model 
>>> from synthetig.example import load_data
>>> ctgan = Model.CTGAN()
>>> real_data = load_data()
>>> ctgam.fit(real_data)
>>> synthetic_data  = ctgan.smaple(number_of_samples=2000)

```
## How to Get Involved  

We would love for you to get involved in anyway you can, at Synthetig we are an open house so anyone is welcome.
We give a brief introduction below on how to give involved.
The [CODE_OF_CONDUCT.md](/CODE_OF_CONDUCT.md) outlines the conduct that we expect from everyone one in the community.


### 1. Say "Hello"
The first thing to do is to say "hello" to the community by joining our [Slack](https://join.slack.com/t/synthetig-community/shared_invite/zt-i61qylly-aCNn19RnTCqy1aDnG6lAJA)
and introduce yourself to the community.

### 2. Read our Contributing Guide 

Have a read of our [contributing guide](/CONTRIBUTING.md). 


### 2. Get Involved 
If you are a bit lost on what to do, have a look at the [list of issues](https://github.com/synthetig/synthetig/issues)
and look for "good first issues". If nothing stands out, just jump on our Slack and send one of the team members a message. 


## Contact Us

[Twitter](https://twitter.com/synthetig)

[Website](https://www.synthetig.ai)

[Slack](https://join.slack.com/t/synthetig-community/shared_invite/zt-i61qylly-aCNn19RnTCqy1aDnG6lAJA)


## Models Used
1. **[CTGAN](https://github.com/sdv-dev/CTGAN/)** (from Data to AI Lab at MIT) released with the paper [Modeling Tabular data using Conditional GAN](https://arxiv.org/abs/1909.11942), by Lei Xu, Maria Skoularidou, Alfredo Cuesta-Infante, Kalyan Veeramachaneni.

## Citation 

Our paper is coming soon, but in the mean time you can cite our Synthetig library:
```bibtex
@misc{hind_lee-mcmaster,
  title={Synthetig-Synthetic data Generation},
  author={Hind, Jonathan and Lee-McMaster, Nick},
  journal={Synthetig},
  url={http://www.synthetig.ai/}
}
```


