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While not directly applicable within the Databricks environment itself, understanding the concept of virtual environments is still valuable. Virtual environments isolate your project's dependencies from each other and the system's global Python installation. Although Databricks manages environments at the runtime and cluster level, understanding the principles of virtual environments can help you manage your dependencies. If you are developing code locally before deploying it to Databricks, using virtual environments is a good way to manage dependencies. This concept is relevant, especially if you are working on multiple projects with different requirements. This keeps your development environment clean and reproducible. Even when working with **OSCOSC** or projects with **SCSC** constraints, you will develop your code in an isolated environment. This approach prevents conflicts between the requirements of various projects. It also simplifies the management of project-specific libraries and dependencies, making them easier to manage.