Reviewing verification JSON outputs on the command line with inspect_job.py

inspect_job.py is a command-line tool that lets you quickly see what information is stored in the *verify.json files generated whenever you run code that integrates with LSST’s verification framework (lsst.verify). It’s particularly useful when you want to see measurement values and don’t need a full report comparing measurements to metric specifications.

See also

See inspect_job.py for a complete reference of that script’s command-line interface.

Running inspect_job.py

inspect_job.py takes one or more verification framework JSON files as command-line arguments. Since JSON files output by the verification framework generally have names that end with verify.json, you can quickly inspect all available outputs by using a *verify.json wildcard:

inspect_job.py *.verify.json

Interpreting the results

inspect_job.py prints a report for each file passed to it. An example report looks like this:

Common metadata:
                                    ccdnum = 42
                                     visit = 411657
                                    object = Blind15A_26
                                      date = 2015-02-19
                                instrument = DECAM
                                    filter = g

Measurements:
                   ip_diffim.numSciSources =  1326.0 ct
      ip_diffim.fracDiaSourcesToSciSources =     0.0385
ap_association.totalUnassociatedDiaObjects =   540.0 ct
                        ap_pipe.ApPipeTime =  63.1475 s ({'estimator': 'pipe.base.timeMethod'})
                 pipe_tasks.ProcessCcdTime =  24.3298 s ({'estimator': 'pipe.base.timeMethod'})
                            ip_isr.IsrTime =   0.9623 s ({'estimator': 'pipe.base.timeMethod'})
          pipe_tasks.CharacterizeImageTime =   7.5473 s ({'estimator': 'pipe.base.timeMethod'})
                  pipe_tasks.CalibrateTime =  11.0519 s ({'estimator': 'pipe.base.timeMethod'})
            pipe_tasks.ImageDifferenceTime =  37.5217 s ({'estimator': 'pipe.base.timeMethod'})
       meas_algorithms.SourceDetectionTime =   1.0205 s ({'estimator': 'pipe.base.timeMethod'})
                   ip_diffim.DipoleFitTime =   1.9112 s ({'estimator': 'pipe.base.timeMethod'})
            ap_association.AssociationTime =   0.6594 s ({'estimator': 'pipe.base.timeMethod'})
           ap_association.numNewDiaObjects =    51.0 ct
      ap_association.fracUpdatedDiaObjects =        0.0
  ap_association.numUnassociatedDiaObjects =     0.0 ct

Each report starts with the job-level metadata in the file, formatted as one key-value pair per line.

Next, the report lists each measurement in the JSON file, including:

• The metric’s fully-qualified name.
• The measurement, including units if applicable.
• Any additional metadata associated specifically with that measurement.

Going further

inspect_job.py provides easy access to measurements and metadata in the verification framework’s JSON output files. If you’re developing tasks that generic metric measurements, inspect_job.py is often enough.

However, if you need to generate a report that compares measurements against specifications, you can directly use the Job and Report Python APIs. The SQR-019 technical note includes a demo of this method.