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Investigating interoperability of the LSST Data Management software stack with Astropy

Jenness, Tim and Bosch, James and Owen, Russell and Parejko, John and Sick, Jonathan and Swinbank, John and de Val-Borro, Miguel and Dubois-Felsmann, Gregory and Lim, K. T. and Lupton, Robert H. and Schellart, Pim and Krughoff, K. Simon and Tollerud, Erik J. (2016) Investigating interoperability of the LSST Data Management software stack with Astropy. In: Software and Cyberinfrastructure for Astronomy IV. Proceedings of SPIE. No.9913. Society of Photo-Optical Instrumentation Engineers (SPIE) , Bellingham, WA, Art. No. 99130G. ISBN 978-1-5106-0205-2.

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The Large Synoptic Survey Telescope (LSST) will be an 8.4m optical survey telescope sited in Chile and capable of imaging the entire sky twice a week. The data rate of approximately 15TB per night and the requirements to both issue alerts on transient sources within 60 seconds of observing and create annual data releases means that automated data management systems and data processing pipelines are a key deliverable of the LSST construction project. The LSST data management software has been in development since 2004 and is based on a C++ core with a Python control layer. The software consists of nearly a quarter of a million lines of code covering the system from fundamental WCS and table libraries to pipeline environments and distributed process execution. The Astropy project began in 2011 as an attempt to bring together disparate open source Python projects and build a core standard infrastructure that can be used and built upon by the astronomy community. This project has been phenomenally successful in the years since it has begun and has grown to be the de facto standard for Python software in astronomy. Astropy brings with it considerable expectations from the community on how astronomy Python software should be developed and it is clear that by the time LSST is fully operational in the 2020s many of the prospective users of the LSST software stack will expect it to be fully interoperable with Astropy. In this paper we describe the overlap between the LSST science pipeline software and Astropy software and investigate areas where the LSST software provides new functionality. We also discuss the possibilities of re-engineering the LSST science pipeline software to build upon Astropy, including the option of contributing affliated packages.

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Additional Information:© 2016 Society of Photo-Optical Instrumentation Engineers (SPIE). We thank those who attended the LSST/Astropy Summit at the University of Washington in March 2016 that forms the basis for the approaches outlined in this paper. We thank Chris Walter, Ben Emmons, Adam Ginsburg and Brigitta Sipocz for comments on the draft manuscript. This material is based upon work supported in part by the National Science Foundation through Cooperative Support Agreement (CSA) Award No. AST-1227061 under Governing Cooperative Agreement 1258333 managed by the Association of Universities for Research in Astronomy (AURA), and the Department of Energy under Contract No. DE-AC02-76SF00515 with the SLAC National Accelerator Laboratory. Additional LSST funding comes from private donations, grants to universities, and in-kind support from LSSTC Institutional Members.
Funding AgencyGrant Number
Association of Universities for Research in Astronomy (AURA)1258333
Department of Energy (DOE)DE-AC02-76SF00515
Subject Keywords:LSST, Astropy, Astronomy Software, Python, Code Reuse
Series Name:Proceedings of SPIE
Issue or Number:9913
Record Number:CaltechAUTHORS:20170110-112626018
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Official Citation:Tim Jenness ; James Bosch ; Russell Owen ; John Parejko ; Jonathan Sick ; John Swinbank ; Miguel de Val-Borro ; Gregory Dubois-Felsmann ; K.-T. Lim ; Robert H. Lupton ; Pim Schellart ; K. S. Krughoff ; Erik J. Tollerud; Investigating interoperability of the LSST data management software stack with Astropy. Proc. SPIE 9913, Software and Cyberinfrastructure for Astronomy IV, 99130G (July 26, 2016); doi:10.1117/12.2231313.
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:73373
Deposited By: Ruth Sustaita
Deposited On:10 Jan 2017 20:15
Last Modified:03 Oct 2019 16:27

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