Produce a run list from the Temporary RCT (Google spreadsheets)

• The configuration file
  • sheet_name: the name of the google spreadsheets, e.g., QC_summary_data_2023_pbpb for 2023 Pb-Pb.
  • tab_name: the name of the tab that you want to take.
  • periods: add which period(s) you want to include in the runlist; if empty, takes all periods in the tab.
  • runlists name: the dumped file name. detectors: add the requested detectors and the flags.
  • pass_shift: select which apass to be checked. For example, "1" refers to the first apass for a detector.
  • pass_name: set the apass name which will be in the dumped file.
  • runlists -> name: indicating which run list it is, e.g., CBT, CBT_hadronPID
  • separate_22o_test: set whether to separate LHC22o_test. Default is "False"
• Make sure you have the certificate runlist-5dfcf12a816d.json under the same folder where you run the script. Contact Jian Liu (jian.liu@cern.ch) for the certificate.
• python3 runlist.py config_pp.json
• Take config_pp_2022.json as the reference configuration file for 2022 periods, config_pp.json or config_pbpb.json for 2023 periods

Export runs from RCT (in Bookkeeping)

• The configuration file:
  • "token": add your token to access Bookkeeping
  • "dataPassNames": asynchronous pass name(s). Example:

    "dataPassNames": {
        "LHC23zzo_apass3": {},
        "LHC24al_cpass0": {
            "run_range": [554413,554538]
        }
    },

The range of runs can be set in this configration file by the "run_range" for each period. No filtering on the runs if the "run_range" is null.

• Example file: config_rct.json.
• python3 rct.py config_rct.json. Add --convert-time if you want to save the timestamps in human-readable format.
• Separate .csv files are saved for each period if you have more than one period in the configuration file

Produce run lists from RCT

• Produce the .csv files mentioned in Export runs from RCT (in Bookkeeping)
• Example configuration file: rct_runlist.json. Modify it according to your needs
• python3 rct_runlist.py rct_runlist.json -d csv_file_path. The -d can be omitted if the .csv files are already in the current directory.

Calculate and upload mu/INEL rate to RCT

The scritps needed and the example configuration files can be found under INEL_Mu.

• python3 inel_mu_calculation.py mu_inel.json
• python3 uploading.py upload.json

Flagging multi-runs in RCT

Currently, only run-based (covering the whole run duration) flags can be added with this script. Put your Bookkeeping token to the json configuration file. The flagTypeId can be found at QC flag types in Bookkeeping. --max_run, --min_run, --excluded_runs and --comment are optional. If omitted, all runs from the pass will be flagged. Add your BK token to the configuration json file.

• Example command for unique flag type and comment:

python3 rct_post_flag.py rct_post_flag.json --data_pass "LHC24a_cpass0" --detector "ITS" --flagTypeId 11 --max_run 106 --min_run 53 --excluded_runs 54

• Example command for multiple flags and comments in a .csv file. The structure of the .csv file needs to be as the one in test.csv, meaning that you need a column called 'post' that indicates the runs that you want to post, a column called run_number that contains the list of the runs, and several column with the name of a certain pass (e.g. LHC24an_apass1_skimmed) that contains the run quality for that pass, and a colum called comment that contains the comment to the run. The quality posted on the RCT correspond to the quality of the run in the pass provided in input using --data_pass. Note that you need a .csv file for each period, but per peiod you can have the quality of the different passes. To include a certain run in the run posted write ok under the column post in the .csv file.

python3 rct_post_flag.py rct_post_flag.json --data_pass "LHC24al_cpass0" --detector "ITS" -b test.csv

• It is possible to have in output a file that contains the minutes for the aQC meeting, based on the posted runs. To produce it use the argument --minutes <name_of_the_file.txt>, if the file is not present it will be generated and filled, otherwise the new info will be added to that file. The flags considered for the minutes at the moment are: Good, Limited Acceptance (MC Reproducible), Limited Acceptance (MC Not Reproducible), Bad Tracking, Bad PID, Unknown, and No Detector Data. An example of the minutes that can produced with the script is reported in ex-minutes.txt. If you are checking runs in a pass that is not cpass0 you may want to say explicitly that the quality of the run in the new pass is the same as in the previous pass, you can add this info to the minutes by adding the arguent --no_diff. At the moment these features are available only when using the script in batch mode. An example of the command to post the flags and obtain the minutes is:

python3 rct_post_flag.py rct_post_flag.json --data_pass "LHC24al_cpass0" --detector "ITS" -b test.csv --minutes minutes.txt --no_diff

Verifying multi-runs in RCT

Both the latest run-based and time-dependent flags for each run can be verified with this script. Put your Bookkeeping token to the json configuration file. The --comment, --max_run, --min_run and --excluded_runs are optional. If --max_run and --min_run are omitted, all runs from the pass will be verified. Add your BK token to the configuration json file. This script is not well tested. Suggest verifying the time-dependent flags by hand.

• Example command:

python3 rct_verify_flag.py rct_verify_flag.json --data_pass "LHC22a_apass1" --detector "FT0"  --max_run 106 --min_run 53 --excluded_runs 54 --comment "test"

How to generate a token in BK/RCT

• Login to the BK
• In your browser (below an example in Chrome),

navigate to the settings (3-dot icon on the left) -> open the `Developer Tools`,

type `sessionService.session.token`, and press Enter to produce the token.

The token expires in 1 week! One needs to reproduce it regularly.