synthesized 2.1

Synthesized SDK

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Synthesized's Scientific Data Kit (SDK)

The SDK generates high quality, privacy-preserving datasets for machine learning and data science use cases. It's available on PyPi for a free 30-day trial.

Usage

A licence key is required to use the full version of the package. If you don't have one, a free 30-day trial licence key will be provided during the installation. See the comparison table in the documentation for details about the features included in the trial.

Please contact us for more information about obtaining a full licence key.

Installation

It is assumed that you have Python 3.7+ already installed on a Windows, Linux, or MacOS machine.

Before starting, ensure that pip and wheel are installed and up to date.

pip install -U pip wheel

Synthesized can then be installed directly with pip.

pip install synthesized

Setting the licence key

Once you have installed the package, you'll need a licence key to run the software. The quickest way to check if the SDK is working is by running the command:

synth-validate

The first time this is run you will be asked if you have a licence key. If you do not have one simply select "no" and the prompts will guide you in acquiring one by entering your email address.

Once you have set your licence key, the SDK will briefly verify the installation was successful.

With the SDK installed you are now able to get synthesizing! Check out our quick start or user guides for ways that the SDK can be put to use.

Dependencies

Below are the minimum dependencies required to run the SDK.

Package	Version
faker	>=8.0
matplotlib	>=3.4
numpy	>=1.19.2
pandas	>=1.2
prompt-toolkit	>=3.0
PyYAML	>=5.2
rsa	>=4.7
rstr	>=2.2
scikit_learn	>=0.23
scipy	>=1.5
seaborn	>=0.11
synthesized_insight	>=0.5
tensorflow_privacy	<0.8, >=0.6
tensorflow_probability	>=0.14.0
tensorflow	>=2.6

Additional Technical Details

There is no explicit limit for the size of a dataset, this is limited by the size of the RAM on the machine running the processing. More information can be found in the [Benchmarks(https://docs.synthesized.io/sdk/latest/user_guide/benchmark) section.

The library can use a GPU but it is not required.