GaussDal: An open source database management system for quantum chemical computations

Abstract An open source software system called GaussDal for management of results from quantum chemical computations is presented. Chemical data contained in output files from different quantum chemical programs are automatically extracted and incorporated into a relational database (PostgreSQL). The Structural Query Language (SQL) is used to extract combinations of chemical properties (e.g., molecules, orbitals, thermo-chemical properties, basis sets etc.) into data tables for further data analysis, processing and visualization. This type of data management is particularly suited for projects involving a large number of molecules. In the current version of GaussDal, parsers for Gaussian and Dalton output files are supported, however future versions may also include parsers for other quantum chemical programs. For visualization and analysis of generated data tables from GaussDal we have used the locally developed open source software SciCraft. Program summary Title of program: GaussDal Catalogue identifier: ADVT Program summary URL: http://cpc.cs.qub.ac.uk/summaries/ADVT Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Computers: Any Operating system under which the system has been tested: Linux Programming language used: Python Memory required to execute with typical data: 256 MB No. of bits in word: 32 or 64 No. of processors used: 1 Has the code been vectorized or parallelized?: No No. of lines in distributed program, including test data, etc: 543 531 No. of bytes in distribution program, including test data, etc: 7 718 121 Distribution format: tar.gzip file Nature of physical problem: Handling of large amounts of data from quantum chemistry computations. Method of solution: Use of SQL based database and quantum chemistry software specific parsers. Restriction on the complexity of the problem: Program is currently limited to Gaussian and Dalton output, but expandable to other formats. Generates subsets of multiple data tables from output files.

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