semvec/pypi-packages huggingface dataset:
ganify 1.0.10
An Easy way to use GANs for data augmentation
Requires Python: >=3.6

# GANify
<p align="center">
<img width="200" height="200" src="https://github.com/arnonbruno/ganify/blob/master/logo.png">
</p>

<b> Description: </b> GANify is an algorithm based on Generative Adversarial Learning to generate synthetic non-tensor data. The name GANify is an adaptation of acronym <b>GAN</b> (generative adversarial network) and Ampl<b>IFY</b>, meaning you can amplify the amount of data available with GANs .


<b> Installation: </b>
One can easily install GANify using the PIP:

<i>pip install ganify</i>


<b>How to use:</b>
Once installed, simply import the library and instatiate the model as described below:
<p align="center">
<img width="600" height="500" src="https://github.com/arnonbruno/ganify/blob/master/ganify.gif">
</p>

<b> Other info: </b>
The package also enables the creation of synthetic data using both <b> GANs </b> and <b> WGANs </b>, by simply changing the argument <i>"type"</i> on <i>"fit_data"</i>
Additionally, you can view the model overall loss performance by calling the <i>"plot_performance()"</i> method after fit.
universa 0.2.0
Python package to access Universa API from python.
Keywords: Universa


# Universa

[![Build status](https://travis-ci.org/vkovrigin/universa.svg?master)](https://travis-ci.org/vkovrigin/universa)
[![PyPI Downloads](https://img.shields.io/pypi/dm/universa.svg)](https://pypi.org/project/universa/)
[![Latest PyPI version](https://img.shields.io/pypi/v/universa.svg)](https://pypi.org/project/universa/)
[![License](https://img.shields.io/pypi/l/universa.svg)](https://pypi.org/project/universa/)

This is an under-construction official Python package from
[Universa](https://universablockchain.com)
to facilitate access to the Java library using Universa's UMI protocol.

## Installation

### Installation

```bash
pip install universa
```

## Usage

### Prerequisites

You need to have [UMI](https://kb.universablockchain.com/umi_protocol/98) installed somewhere on your system.
To run, UMI requires JVM v1.8.* (or newer) to be installed, too.

UMI can be used in one of three modes:

* `pipe` – the UMI instance is dynamically executed in a subprocess, and a pipe is used for communication.
* `tcp` – connect to an already running UMI instance via TCP socket.
* `unix` – connect to an already running UMI instance via Unix socket.

 By default it expects an `umi` binary to be installed an reachable via the shell `$PATH`, and will invoke it automatically in `pipe` mode.
 Use `universa.transport.setupUMI` method if you need to switch the connection method to some other.

### Example


```python
#!/usr/bin/env python3
from universa.transport import transport
from universa.types import PrivateKey, Contract, RevokePermission

if __name__ == '__main__':
    # The next line is not necessary if umi is reachable via the $PATH
    # transport.setupUMI('pipe', '/usr/local/bin/umi')

    # To connect to an already running UMI instance you may use one of this modes:
    # transport.setupUMI('tcp', host='127.0.0.1', port=12345)  # IPv6 is also ok
    # transport.setupUMI('unix', path='/path-to-the-socket')

    print(transport.version)

    private_key = PrivateKey(size=2048)
    contract = Contract()
    short_address = private_key.public_key.short_address
    owner_role = contract.set_owner_addresses(short_address)
    revoke_permission = RevokePermission(owner_role)
    contract.add_permission(revoke_permission)
```

## Docs and resources

For more information see:
- [Universa Knowledge Base](https://kb.universablockchain.com/)
- [Universa Java API](https://kb.universablockchain.com/general_java_api/5)
- [Universa UMI server](https://kb.universablockchain.com/umi_protocol/98)

## License

This package is available as open source under the terms of the [MIT License](https://opensource.org/licenses/MIT).