Generating synthetic data practically relies on software tools and libraries. Manually creating large or complex datasets is often inefficient. This chapter introduces the software ecosystem surrounding basic synthetic data generation.

You will learn about the function of software in automating data creation. We will look at how fundamental Python libraries such as NumPy and Pandas can be used for generating and manipulating data structures. We will also cover libraries specifically designed for generating realistic placeholder data, like Faker. Additionally, you'll get an overview of libraries used for simple image generation and manipulation tasks. Finally, we'll provide brief guidance on identifying appropriate tools for different synthetic data requirements.