Amazon SageMaker Studio notebooks provide a full-featured integrated development environment (IDE) for flexible machine learning (ML) experimentation and development. Security measures secure and support a versatile and collaborative environment. In some cases, such as to protect sensitive data or meet regulatory requirements, security protocols require that public internet access be disabled in the development environment.
Typically, developers have access to the public internet and can install any new libraries you want to import. You can install Python packages from the public Python Package Index (PyPI), a Python software repository, using standard tools such as pip. You can find hundreds of thousands of packages, including common packages such as NumPy, Pandas, Matplotlib, Pytest, Requests, Django, and BeautifulSoup.
In a development environment with internet access disabled, you can instead mirror packages and host your own PyPI server hosted in your own Amazon Virtual Private Cloud (Amazon VPC). A VPC is a logically

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