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Title: easyaccess: Enhanced SQL command line interpreter for astronomical surveys

Journal Article · · Journal of Open Source Software
DOI:https://doi.org/10.21105/joss.01022· OSTI ID:1488601
ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [1]; ORCiD logo [1]
  1. Univ. of Illinois at Urbana-Champaign, IL (United States)
  2. Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States)
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easyaccess is an enhanced command line interpreter and Python package created to facilitate access to astronomical catalogs stored in SQL Databases. It provides a custom interface with custom commands and was specifically designed to access data from the Dark Energy Survey Oracle database, including autocompletion of tables, columns, users and commands, simple ways to upload and download tables using csv, fits and HDF5 formats, iterators, search and description of tables among others. It can easily be extended to another surveys or SQL databases. The package was completely written in Python and support customized addition of commands and functionalities. Visit https://github.com/mgckind/easyaccess to view installation instructions, tutorials, and the Python source code for easyaccess.

Research Organization:
Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States)
Sponsoring Organization:
USDOE Office of Science (SC), High Energy Physics (HEP); National Science Foundation (NSF)
Grant/Contract Number:
AC02-07CH11359; NSF AST 07-15036; NSF AST 08-13543
OSTI ID:
1488601
Report Number(s):
arXiv:1810.02721; FERMILAB-PUB-18-520-AE; oai:inspirehep.net:1699160
Journal Information:
Journal of Open Source Software, Vol. 4, Issue 33; ISSN 2475-9066
Publisher:
Open Source Initiative - NumFOCUSCopyright Statement
Country of Publication:
United States
Language:
English

References (5)

The Dark Energy Survey: more than dark energy – an overview journal March 2016
The Dark Energy Survey: Data Release 1 journal November 2018
Data Structures for Statistical Computing in Python conference January 2010
The Dark Energy Survey: Data Release 1 text January 2018
The Dark Energy Survey: more than dark energy - an overview text January 2016

Cited By (3)

H0LiCOW – X. Spectroscopic/imaging survey and galaxy-group identification around the strong gravitational lens system WFI 2033−4723 journal September 2019
Identification of RR Lyrae Stars in Multiband, Sparsely Sampled Data from the Dark Energy Survey Using Template Fitting and Random Forest Classification journal June 2019
Identification of RR Lyrae stars in multiband, sparsely-sampled data from the Dark Energy Survey using template fitting and Random Forest classification text January 2019

Figures / Tables (5)

Figure 1(p. 2)figure Figure 1
Figure 1(p. 2)figure Figure 1
Figure 2(p. 3)figure Figure 2
Figure 2(p. 3)figure Figure 2
Figure 3(p. 4)figure Figure 3

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Related Subjects

79 ASTRONOMY AND ASTROPHYSICS
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY