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Job request: 1532

Organisation:
Bennett Institute
Workspace:
sro-measures
ID:
w7p4lf5kbihhnl6s
View repo View project.yaml

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

By cross-referencing the indicated Requested Actions with the Pipeline section below, you can infer what security level various outputs were written to. Outputs marked as highly_sensitive can never be viewed directly by a researcher; 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

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime: 01:45:58

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

Job information

Status
Failed
Backend
TPP
Workspace
sro-measures
Requested by
Louis Fisher
Branch
master
Force run dependencies
No
Git commit hash
0764022
Requested actions
  • generate_notebook_practice

Code comparison

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