---
id: data-designer-engine
version: "0.9.1"
license: Apache-2.0
license_treatment: permissive
maintenance: active
---

# data-designer-engine — Generation engine for DataDesigner synthetic data generation

License: permissive · Maintenance: active · Downloads: 312.2K/mo

## What it is and what it does

data-designer-engine is the execution runtime for NVIDIA's NeMo Data Designer synthetic data generation framework. It orchestrates data transformation, generation, and LLM-based synthesis workflows to create synthetic datasets. The engine depends on data-designer-config for configuration management and integrates with a large ecosystem of data science and HTTP libraries including pandas, numpy, duckdb, and huggingface-hub for model access.

The package is designed for developers and researchers building synthetic data pipelines. It handles the computational heavy lifting of data generation, including native HTTP-based LLM integration via httpx and tiktoken for tokenization. With 31 runtime dependencies covering data processing, networking, cryptography, and schema validation, it represents a complete generation stack rather than a lightweight utility.

Use it for:

- Generate synthetic datasets for machine learning model training when real data is scarce or sensitive
- Create diverse test data for data pipeline validation and quality assurance workflows
- Build data augmentation pipelines using LLM-based generation for NLP and structured data tasks
- Transform and synthesize data across multiple formats using the integrated data processing stack
- Prototype data workflows with configurable generation parameters via data-designer-config

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Execution engine for the NeMo Data Designer synthetic data generation framework, handling data transformation, generation, and LLM integration for creating synthetic datasets.

Yes, if you are building synthetic data generation workflows within the NeMo Data Designer ecosystem. The package is actively maintained (3-day-old release), has low install friction, permissive licensing, and no known vulnerabilities. The 31 dependencies are a commitment; evaluate whether you need the full generation engine or a lighter alternative if you only need configuration management.

## Install

pip install data-designer-engine
uv add data-designer-engine
poetry add data-designer-engine

## Installing data-designer-engine

Before you install: Low friction installation with a pure-Python wheel. Active maintenance with a release 3 days old. The 31 runtime dependencies are substantial but include standard data science and HTTP libraries, suggesting a mature ecosystem integration rather than experimental tooling.

License in practice: Apache-2.0 permissive license allows use in commercial and proprietary projects with minimal restrictions; you must include a copy of the license and notice of modifications if you distribute the package.

Quickstart:

pip install data-designer-engine

from data_designer_engine import <engine_component>
# Engine provides execution capabilities for synthetic data generation workflows

Requires Python 3.10 or later; 31 runtime dependencies including pandas, numpy, duckdb, and LLM integration libraries will be installed.

Verify before relying:

- Specific API entry points and primary classes available in the engine module
- Whether the engine can be used standalone or requires additional NeMo Data Designer components beyond data-designer-config
- Performance characteristics and scalability limits for synthetic data generation tasks

## Package facts

- License: Apache-2.0 (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 312.2K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

synthetic data generation, data synthesis engine, LLM-based data generation, synthetic dataset creation, data transformation pipeline, NeMo data designer, generative data framework, synthetic-data, data-generation, llm-integration

[View on SkillFed](https://skillfed.io/packages/data-designer-engine) · [View on PyPI](https://pypi.org/project/data-designer-engine/)