The Astropy Project supports and fosters the development of open-source and openly developed Python packages that provide commonly needed functionality to the astronomical community. A key element of the Astropy Project is the core package astropy, which serves as the foundation for more specialized projects and packages. In this article, we provide an overview of the organization of the Astropy project and summarize key features in the core package, as of the recent major release, version 2.0. We then describe the project infrastructure designed to facilitate and support development for a broader ecosystem of interoperable packages. We conclude with a future outlook of planned new features and directions for the broader Astropy Project.

The Astropy Project supports and fosters the development of open-source and openly developed Python packages that provide commonly needed functionality to the astronomical community. A key element of the Astropy Project is the core package astropy, which serves as the foundation for more specialized projects and packages. In this article, we summarize key features in the core package as of the recent major release, version 5.0, and provide major updates on the Project. We then discuss supporting a broader ecosystem of interoperable packages, including connections with several astronomical observatories and missions. We also revisit the future outlook of the Astropy Project and the current status of Learn Astropy. We conclude by raising and discussing the current and future challenges facing the Project.

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Light field rendering is a widely used technique to generate novel views of a scene from novel viewpoints. Interpolative methods for light field rendering require a dense description of the scene in the form of closely spaced images. In this work, we present a simple method for dense view interpolation over general static scenes, using commonly available mobile devices. We capture an approximate focal stack of the scene from adjacent camera locations and interpolate intermediate images by shifting each focal region according to appropriate disparities. We do not rely on focus distance control to capture focal stacks and describe an automatic method of estimating the focal textures and the blur and disparity parameters required for view interpolation.