Skip to main content

Synthesized SDK

Project description

Synthesized

Documentation PyPI codecov Quality Gate Status Technical Debt Supported Python Versions Supported OS


synthesize

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 3.9+ 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.

asciicast

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 >=18.0.0
matplotlib >=3.4, <3.10
numpy >=1.19.2, <2.0
pandas >=1.3, <2.0
prompt-toolkit >=3.0
PyYAML >=5.2
rsa >=4.7
rstr >=2.2
scikit_learn >=0.23, <1.4
scipy >=1.5, <1.12
seaborn >=0.11, <0.14
synthesized_insight >=0.5, <0.8
tensorflow >=2.18, <2.22
yamale >=4.0.4

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

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

synthesized-2.27-cp311-cp311-win_amd64.whl (7.0 MB view details)

Uploaded CPython 3.11Windows x86-64

synthesized-2.27-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl (50.7 MB view details)

Uploaded CPython 3.11manylinux: glibc 2.17+ x86-64manylinux: glibc 2.28+ x86-64

synthesized-2.27-cp311-cp311-macosx_11_0_arm64.whl (8.2 MB view details)

Uploaded CPython 3.11macOS 11.0+ ARM64

synthesized-2.27-cp310-cp310-win_amd64.whl (7.0 MB view details)

Uploaded CPython 3.10Windows x86-64

synthesized-2.27-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl (45.8 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.17+ x86-64manylinux: glibc 2.28+ x86-64

synthesized-2.27-cp39-cp39-win_amd64.whl (7.0 MB view details)

Uploaded CPython 3.9Windows x86-64

synthesized-2.27-cp39-cp39-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl (45.8 MB view details)

Uploaded CPython 3.9manylinux: glibc 2.17+ x86-64manylinux: glibc 2.28+ x86-64

File details

Details for the file synthesized-2.27-cp311-cp311-win_amd64.whl.

File metadata

  • Download URL: synthesized-2.27-cp311-cp311-win_amd64.whl
  • Upload date:
  • Size: 7.0 MB
  • Tags: CPython 3.11, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.13

File hashes

Hashes for synthesized-2.27-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 78e8e7ec756c0e22a108f94bfa2ea67b8dd90b16d5f025070d6a69bc1cc3c334
MD5 13e9126aba5f8e2e18a7b3c043225f9d
BLAKE2b-256 01b8bbf21c359896c827239b166fc43640951ca619ed41902d54c951dc6a976f

See more details on using hashes here.

File details

Details for the file synthesized-2.27-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for synthesized-2.27-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 d115d187bb93cbf5057dc9cba51fef87211f0588115c163639a9c1f596f02149
MD5 44c297de5901a80c99d7e6b2ecb6296b
BLAKE2b-256 9ddd75080674500ba54afc2da5884de400fabf37b449741d3018a08ecc5fad39

See more details on using hashes here.

File details

Details for the file synthesized-2.27-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for synthesized-2.27-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 9fdc99519dc4356d63fe5d8bf24e55ef7df0529fe70f162971f113cf0ef9f13f
MD5 fb2222f694acbc2deb625736d06cb607
BLAKE2b-256 c88e7d17a3d4250ec9d3a35d74fa75cbb53ed966a8536935123a2bbaae5bc1e2

See more details on using hashes here.

File details

Details for the file synthesized-2.27-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: synthesized-2.27-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 7.0 MB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.13

File hashes

Hashes for synthesized-2.27-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 f9ead1c4653656a981ac69b457ac85e0c76b2f2a86a054ce35a4517dc578266a
MD5 10573bd8996968ecf36db327ea5e5997
BLAKE2b-256 95c115e8ad11736900c91fbbcab908f603254acd595e79f4095d0357c65c88c3

See more details on using hashes here.

File details

Details for the file synthesized-2.27-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for synthesized-2.27-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 f9e7708274b7efdb18373b7f46554088c320a6c6d85e85123bf6fe68f3343fa4
MD5 8d27856a5bca1edf488b0fe2e9c7509e
BLAKE2b-256 d766eb03e3859458feb4222dda2b72383f762f4d1043da2e9fa0a37a0924989f

See more details on using hashes here.

File details

Details for the file synthesized-2.27-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: synthesized-2.27-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 7.0 MB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.13

File hashes

Hashes for synthesized-2.27-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 01d626624851a66c928a57a4d6b2116343db18122eaa6edd30274accc23203b4
MD5 2099099da8aea03a82cbd82da6d71cf0
BLAKE2b-256 bab30fba2fe9943c228027bbff0576b01795ea71da26ceca3eb7b5f7f0dabcda

See more details on using hashes here.

File details

Details for the file synthesized-2.27-cp39-cp39-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for synthesized-2.27-cp39-cp39-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 33a4d6c8b32c8b638b7fff64ec4ecfbad1beb3bbe5bc4aaf5cefc02e659cabca
MD5 7a85c933ab17cdc63b7a129af8e06704
BLAKE2b-256 7722baf95b36d71c5ad4aa3c07a31520facaac9def49e368bb009c2f3d83f502

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page