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Job request: 3022

Organisation:
Workspace:
sro-measure-cam-test
ID:
mioivu5hdewswwg2
View repo View project.yaml

This page shows the technical details of what happened when the authorised researcher Chris Yeung requested one or more actions to be run against real patient data in the project, within a secure environment.

By cross-referencing the list of jobs with the pipeline section below, you can infer what security level various outputs were written to. Researchers can never directly view outputs marked as highly_sensitive ; they can only request that code runs against them. Outputs marked as moderately_sensitive can be viewed by an approved researcher by logging into a highly secure environment. Only outputs marked as moderately_sensitive can be requested for release to the public, via a controlled output review service.

Jobs

Pipeline

Show project.yaml 
version: '3.0'

expectations:
  population_size: 1000
   
    
actions:

  generate_study_population:
    run: cohortextractor:latest generate_cohort --study-definition study_definition --index-date-range "2019-01-01 to 2021-02-01 by month" --output-dir=output
    outputs:
      highly_sensitive:
        cohort: output/input_*.csv

  generate_study_population_practice_count:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_practice_count --output-dir=output
    outputs:
      highly_sensitive:
        cohort: output/input_practice_count.csv

  generate_measures:
      run: cohortextractor:latest generate_measures --study-definition study_definition --output-dir=output
      needs: [generate_study_population]
      outputs:
        moderately_sensitive:
          measure_csv: output/measure_*.csv
  
  get_practice_count:
    run: python:latest python analysis/get_practice_count.py
    needs: [generate_study_population_practice_count]
    outputs:
      moderately_sensitive:
        text: output/practice_count.json
  
  get_patient_count:
    run: python:latest python analysis/get_patients_counts.py
    needs: [generate_study_population]
    outputs:
      moderately_sensitive:
        text: output/patient_count.json
        


        
  
  generate_notebook:
    run: jupyter:latest jupyter nbconvert /workspace/notebooks/sentinel_measures.ipynb --execute --to html --output-dir=/workspace/output --ExecutePreprocessor.timeout=86400 --no-input
    needs: [generate_measures, get_practice_count, get_patient_count]
    outputs:
      moderately_sensitive:
        notebook: output/sentinel_measures.html
     
  
  # generate_notebook_practice:
  #   run: jupyter:latest jupyter nbconvert /workspace/notebooks/sentinel_measures_by_practice.ipynb --execute --to html --output-dir=/workspace/output --ExecutePreprocessor.timeout=86400 --no-input
  #   needs: [generate_measures, get_practice_count, get_patient_count]
  #   outputs:
  #     moderately_sensitive:
  #       notebook: output/sentinel_measures_by_practice.html
  #       csvs: output/*_check.csv

  get_event_summary:
    run: python:latest python analysis/get_event_summary.py
    needs: [generate_study_population]
    outputs:
      moderately_sensitive:
        text: output/*_event_summary.csv

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime: 00:00:51

These timestamps are generated and stored using the UTC timezone on the GRAPHNET backend.

Job information

Status
Failed
Backend
GRAPHNET
Workspace
sro-measure-cam-test
Requested by
Chris Yeung
Branch
graphnet
Force run dependencies
No
Git commit hash
049f0cf
Requested actions
  • generate_study_population

Code comparison

Compare the code used in this Job Request