Automating data transfer to the ATLAS ITk Production Database

The high collision rates of the High-Luminosity Large Hadron Collider (HL-LHC) will require an upgrade for its experiments to perform adequately. The ATLAS experiment's current detector will be replaced with a new Inner Tracker (ITk), with installation starting in 2026. Components that will come together to become the ITk are currently being built around the world and their location and status are tracked on the ITk Production Database. The University of Toronto and its partner Celestica use a Google Spreadsheet to document their progress and their tests relating to the ITk components they are producing. A channel is necessary to efficiently transcribe the relevant data from that spreadsheet to the ITk Production Database. Along with my collaborator Ruchi Soni, I have developed six Python scripts that upload necessary information to the Database. Three of these scripts are for relaying information about the assembly status of components, while the other three are for uploading different test results. The programs written are successful and promise to be useful. The biggest strength of the programs is that, while they perform one upload at a time for each component, they will not crash when encountering a problem with an upload and continue to perform subsequent uploads, all while tracking successful transmissions. A major weakness of all the scripts is their heavy reliance on the structure and contents of Celestica's spreadsheet—changes or errors in the spreadsheet can impede their performance. This report focuses more on the test upload scripts (hybrid glue weight test, module glue weight test, and hybrid wire bonding test) while Ruchi Soni's report focuses on assembly scripts.