DataDreamer is an open-source Python library designed to facilitate the implementation of large language model (LLM) workflows, addressing challenges such as scale, closed-source nature, and lack of standardized tooling. The library simplifies the process of synthetic data generation, fine-tuning, instruction-tuning, and alignment, making it easier for researchers to adhere to best practices for open science and reproducibility. DataDreamer provides a standardized interface for LLMs, supports caching and resumability, and integrates with various LLM libraries and commercial APIs. It also includes features for sharing open datasets and models, generating synthetic data cards and model cards, and optimizing workflows for efficiency. The library aims to make LLM workflows more accessible and reproducible, contributing to the advancement of research in natural language processing (NLP).DataDreamer is an open-source Python library designed to facilitate the implementation of large language model (LLM) workflows, addressing challenges such as scale, closed-source nature, and lack of standardized tooling. The library simplifies the process of synthetic data generation, fine-tuning, instruction-tuning, and alignment, making it easier for researchers to adhere to best practices for open science and reproducibility. DataDreamer provides a standardized interface for LLMs, supports caching and resumability, and integrates with various LLM libraries and commercial APIs. It also includes features for sharing open datasets and models, generating synthetic data cards and model cards, and optimizing workflows for efficiency. The library aims to make LLM workflows more accessible and reproducible, contributing to the advancement of research in natural language processing (NLP).