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Sarah Gibson - Sharing Reproducible Python Environments with Binder
Learn how to share reproducible Python environments with Binder, a tool that uses Docker to create containers with software dependencies, suitable for researchers, students, and institutions worldwide.
- Reproducible research is important for efficiency and success
- Binder is a tool that makes it easy to share reproducible computational environments
- It uses Docker to create containers with software dependencies
- Binder is not a tool for analysis, but for sharing results
- It supports multiple programming languages, including Python
- The project has grown to hosting over 140,000 user sessions per week
- The main use case for Binder is sharing reproducible computational environments
- The service can be used by anyone, including researchers, students, and institutions
- It is hosted on multiple clusters around the world, including Google Cloud, Azure, and OVH
- The project is open source and built modularly using other open source tools
- It provides a repeatable analysis by capturing the software dependencies and high-level architecture
- The service can be used to run Jupyter notebooks and provide interactive computing environments
- It does not support GPU services, but can be configured to only allow sharing between specific teams
- The project has been awarded a Moore Foundation grant to run its operations
- The funding streams come from institutions and cloud providers