MOSTLY AI - SDK 🚀¶
Package Documentation | Platform Documentation | Usage Examples
The official Python SDK for MOSTLY AI, the #1 platform for high-fidelity privacy-safe Synthetic Data.
This toolkit allows you to programmatically create, browse and manage the 3 key resources of the MOSTLY AI platform:
- Generators - Train a synthetic data generator on your existing tabular or language data assets
- Synthetic Datasets - Use a generator to create any number of synthetic samples to your needs
- Connectors - Connect to any data source within your organization, for reading and writing data
Intent | Primitive | Documentation |
---|---|---|
Train a Generator on tabular or language data | g = mostly.train(config) |
see mostly.train |
Generate any number of synthetic data records | sd = mostly.generate(g, config) |
see mostly.generate |
Live probe the generator on demand | df = mostly.probe(g, config) |
see mostly.probe |
Connect to any data source within your org | c = mostly.connect(config) |
see mostly.connect |
Installation¶
The latest release of mostlyai
can be installed via pip:
Quick Start¶
Please obtain your personal API key from your account settings page, and adjust the following code snippet, before running it.
import pandas as pd
from mostlyai import MostlyAI
# initialize client
mostly = MostlyAI(
api_key='INSERT_YOUR_API_KEY', # or set env var `MOSTLYAI_API_KEY`
base_url='https://app.mostly.ai' # or set env var `MOSTLYAI_BASE_URL`
)
# train a generator on original data
df_original = pd.read_csv('https://github.com/mostly-ai/public-demo-data/raw/dev/census/census.csv.gz')
g = mostly.train(name='census', data=df_original) # shorthand syntax for 1-table config
# live probe the generator for synthetic samples
df_samples = mostly.probe(g, size=10)
# generate a synthetic dataset
sd = mostly.generate(g, size=10_000)
# download the synthetic dataset
df_synthetic = sd.data()
Further Resources¶
- MOSTLY AI Website
- MOSTLY AI Blog
- Platform Documentation
- OpenAPI Documentation
- MOSTLY AI @ GitHub
- Synthetic Data - Quality Assurance
mostlyai-qa
Citation¶
Please consider citing our project if you find it useful: