Skip to main content
Pre-release

This release is a pre-release and may not be stable for production use.

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 3.10, 3.11, 3.12 or 3.13 already installed on a Windows, Linux, or MacOS machine (note that MacOS requires Python 3.11 or later).

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
Babel >=2.2.1
cleanco >=2.2
faker >=18.0.0
insight >=0.8, <0.9
matplotlib >=3.4, <3.10
numpy >=1.19.2, <3.0
pandas >=2.1.1, <3.0
prompt-toolkit >=3.0
psutil >=5.0
PyYAML >=5.2
rsa >=4.7
rstr >=2.2
scikit_learn >=0.23, <1.10
scipy >=1.7, <1.19
seaborn >=0.11, <0.14
tensorflow >=2.18, <2.22
tf-keras >=2.18, <2.22
typo >=0.1.7
yamale >=4.0.4

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

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-2.31rc0-cp313-cp313-win_amd64.whl (6.7 MB view details)

Uploaded CPython 3.13Windows x86-64

synthesized-2.31rc0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl (50.8 MB view details)

Uploaded CPython 3.13manylinux: glibc 2.17+ x86-64manylinux: glibc 2.28+ x86-64

synthesized-2.31rc0-cp313-cp313-macosx_11_0_arm64.whl (8.1 MB view details)

Uploaded CPython 3.13macOS 11.0+ ARM64

synthesized-2.31rc0-cp312-cp312-win_amd64.whl (6.9 MB view details)

Uploaded CPython 3.12Windows x86-64

synthesized-2.31rc0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl (51.7 MB view details)

Uploaded CPython 3.12manylinux: glibc 2.17+ x86-64manylinux: glibc 2.28+ x86-64

synthesized-2.31rc0-cp312-cp312-macosx_11_0_arm64.whl (8.2 MB view details)

Uploaded CPython 3.12macOS 11.0+ ARM64

synthesized-2.31rc0-cp311-cp311-win_amd64.whl (7.0 MB view details)

Uploaded CPython 3.11Windows x86-64

synthesized-2.31rc0-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl (50.8 MB view details)

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

synthesized-2.31rc0-cp311-cp311-macosx_11_0_arm64.whl (8.2 MB view details)

Uploaded CPython 3.11macOS 11.0+ ARM64

synthesized-2.31rc0-cp310-cp310-win_amd64.whl (7.0 MB view details)

Uploaded CPython 3.10Windows x86-64

synthesized-2.31rc0-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl (45.9 MB view details)

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

File details

Details for the file synthesized-2.31rc0-cp313-cp313-win_amd64.whl.

File metadata

File hashes

Hashes for synthesized-2.31rc0-cp313-cp313-win_amd64.whl
Algorithm Hash digest
SHA256 08adfb65d6d6dfc86b28884021ad4b0819e9e3632ff9571c1d6adb6ba1fe7611
MD5 2b7aa50140dbc4438d989f898277247c
BLAKE2b-256 66243657fdbe5446256c729b4249ae8846a3931fe2dfe24d78b25d732c7703d5

See more details on using hashes here.

File details

Details for the file synthesized-2.31rc0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for synthesized-2.31rc0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 4aa8cd2466b1a0c025e0c6209e13b1f842c4ed6d7fe41a551e4643e52df20336
MD5 c5d89b061b976639b8d106b4b57c62dd
BLAKE2b-256 60b75059eba08baa674a8619ff6a04804937b966df4433af8e1a821a71562404

See more details on using hashes here.

File details

Details for the file synthesized-2.31rc0-cp313-cp313-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for synthesized-2.31rc0-cp313-cp313-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 0a58bc19fad71871e3c7efc90b2802f81a3ba09c68a2812ead594a3af1c8d3c4
MD5 e8a5486be97bd919c64e5ea180a05f4d
BLAKE2b-256 c95f19c2b0dbb8949dae861f12f36f952c80ad2044797683d6aa00c8f83e1026

See more details on using hashes here.

File details

Details for the file synthesized-2.31rc0-cp312-cp312-win_amd64.whl.

File metadata

File hashes

Hashes for synthesized-2.31rc0-cp312-cp312-win_amd64.whl
Algorithm Hash digest
SHA256 1fedcbd0f71fc746d1cb3cfbb499b2fd49c4e1508b61ebc47dda5f02445b3e5a
MD5 66b06e3c434882e42204ecb24aff2e4b
BLAKE2b-256 a3f1009fd71b2f3611f2c544f355f760bf15c81143d3b6ea9e0f7a478898b913

See more details on using hashes here.

File details

Details for the file synthesized-2.31rc0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for synthesized-2.31rc0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 212b83261ecafe563d1a5eeb49aa0d9632b6297964e21f87e57ffa895c19f137
MD5 db80f85ca34bf3f933435c3ce88c6e97
BLAKE2b-256 daae90c4e97c4a5c020137476bbe6ee4b20ae33e4d0fc41c2cc0be2899de144b

See more details on using hashes here.

File details

Details for the file synthesized-2.31rc0-cp312-cp312-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for synthesized-2.31rc0-cp312-cp312-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 a317aa84e40e323935aab3b7113dff03ba28aa69cc20dd3ea76b8f8f98867724
MD5 e295a44b5913135132470d343563c8a5
BLAKE2b-256 e4c53151796e1cfad09b9ee5a02d7af30a0f024803479035b75175d99186999b

See more details on using hashes here.

File details

Details for the file synthesized-2.31rc0-cp311-cp311-win_amd64.whl.

File metadata

File hashes

Hashes for synthesized-2.31rc0-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 1f12b6b08ee13f58af14834411f7bf20b821003de21370d4e26c56e97c8db54f
MD5 6e8cb53ebba15923bff846006542bb1b
BLAKE2b-256 ed921d793d0661f63338fd5753ba13162f2b9ae9cbf16d08730df5df87ab5120

See more details on using hashes here.

File details

Details for the file synthesized-2.31rc0-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for synthesized-2.31rc0-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 ce8833084828a75156c79ad14360ec79aad612b10022b467472de3190b1be0fe
MD5 892fd5447386b558afe741da5402a2f8
BLAKE2b-256 9e5fe282657bd719b386f631984d1e9cc4eeaf5da5839a4ca82883a0128fd1a2

See more details on using hashes here.

File details

Details for the file synthesized-2.31rc0-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for synthesized-2.31rc0-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 b08517acd99f2af13e34a52fd926084eca2f310668cfb12f9be59c5239886784
MD5 8b2de5f4769f379771d15fc25b7964b7
BLAKE2b-256 50f488d18001106596a623d365f1af6e2ec1b9ce8213de055e43c3c4a453a902

See more details on using hashes here.

File details

Details for the file synthesized-2.31rc0-cp310-cp310-win_amd64.whl.

File metadata

File hashes

Hashes for synthesized-2.31rc0-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 2247bbfecbfda52a6481700e39760169efe5329b12787da70a53a7837b1aa8d3
MD5 3b566bda0e5d0268c6fea819665e2005
BLAKE2b-256 b3c7a6106b4904bd8dfe7f6b6d1d561310ce89bf7a6794e9874ae48a6a9b3330

See more details on using hashes here.

File details

Details for the file synthesized-2.31rc0-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for synthesized-2.31rc0-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 54359e4c3a3fd681433cad787bbacc5dd2cbcff309e283d5246444e913ef991d
MD5 ab148c6c9c2f024aca363ebc2b60f9ed
BLAKE2b-256 0eff81a1cdcdb19959fe084e27766be03442c4f4d255c1386466130d96c27b5f

See more details on using hashes here.

Release history Release notifications | RSS feed

2.31

11 files

This release

2.31rc0 This release

11 files

2.30

8 files

2.29

8 files

2.28

5 files

2.27

7 files

2.26

7 files

2.25

9 files

2.24

9 files

2.23

16 files

2.22

16 files

2.21

16 files

2.20

16 files

2.19

16 files

2.18

19 files

2.17

19 files

2.16

19 files

2.15

19 files

2.14

19 files

2.13

19 files

2.12

16 files

2.11

19 files

2.10

19 files

2.9

19 files

2.8

19 files

2.7

12 files

2.6

12 files

2.5

15 files

2.4

15 files

2.3

15 files

2.2

9 files

2.1

9 files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page