MOSTLY AI Python client

Use the MOSTLY AI Python client to train generators, generate synthetic data, connect to data sources, share data with your team, and much more.

Intent	Primitive
Train a Generative AI on tabular data	`g = mostly.train(data)`
Empower your team with safe synthetic data	`mostly.share(g, email)`
Generate unlimited synthetic data on demand	`mostly.generate(g, size)`
Prompt the generator for the data that you need	`mostly.generate(g, seed)`
Connect to any data source within your org	`mostly.connect(config)`
List the available models	`mostly.models(model_type)`
List the available computes	`mostly.computes`
Usage information	`mostly.usage_reports()`
Info about the current user	`mostly.me()`
Info about the platform	`mostly.about()`

💡

For a complete API reference, see the Python Client API reference (opens in a new tab).

Installation

bash

pip install mostlyai

Get an API key

To use the Python client, you need an API key. Get your API key for the REST API or Python client from your user profile menu.

Steps

Hover over the profile menu in the upper right and select API key.
Click Generate API Key.

What's next

Your key is immediately copied to your clipboard. You can now use it for the REST API or to instantiate your Python client.

python

from mostlyai import MostlyAI
mostly = MostlyAI(api_key="mostly-**********")

Examples

As you explore the Generators, Synthetic datasets, and Connectors pages, you will find code snippets that show how to accomplish a task with the Python client. Use the Python and UI tabs to switch between the code snippets and the UI steps.

Basic Usage

python

from mostlyai import MostlyAI
mostly = MostlyAI(api_key='your_api_key')
g = mostly.train(data)      # train a generator on your data (Pandas DataFrame, URL to CSV, or a connector location)
sd = mostly.generate(g)     # generate a synthetic dataset
syn = sd.data()             # consume synthetic as pd.DataFrame

Supported Methods

Connectors

python

c = mostly.connect(config)
 
c = mostly.connectors.create(config)
c = mostly.connectors.get(id)
it = mostly.connectors.list()
c = c.update(config)
ls = c.locations(prefix)
config = c.config()
c.delete()

Generators

python

g = mostly.train(data, config, name, start=True, wait=True)
 
g = mostly.generators.create(config)
g = mostly.generators.get(id)
it = mostly.generators.list()
g = g.update(config)
config = g.config()
g.delete()
 
g.training.start()
g.training.progress()
g.training.cancel()
g.training.wait()

Synthetic Datasets

python

sd = mostly.generate(g, seed=seed)
sd = mostly.generate(g, size=size)
sd = mostly.generate(g, config=config)
 
sd = mostly.synthetic_datasets.create(g, config)
sd = mostly.synthetic_datasets.get(id)
it = mostly.synthetic_datasets.list()
config = sd.config()
sd.delete()
 
sd.generation.start()
sd.generation.progress()
sd.generation.cancel()
sd.generation.wait()
 
sd.data()
sd.download(file, format)

Synthetic probes

python

sp = mostly.probe(g, seed=seed)
sp = mostly.probe(g, size=size)
sp = mostly.probe(g, config=config)

Sharing

python

mostly.share(g | sd | c, email)
mostly.unshare(g | sd | c, email)
 
g.shares()
sd.shares()
c.shares()

Usage

python

mostly.me()
mostly.usage_reports()
mostly.usage_reports(by_periods=True)