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Job request: 2226

Organisation:
Bennett Institute
Workspace:
sro-measures-demographics
ID:
n2gfvxdancq5a2i2
View repo View project.yaml

This page shows the technical details of what happened when the 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 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 2021-04-01 by month" --output-dir=output --output-format=feather
    outputs:
      highly_sensitive:
        cohort: output/input_*.feather
        
  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_study_population_ethnicity:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_ethnicity --output-dir=output --output-format=feather
    outputs:
      highly_sensitive:
        cohort: output/input_ethnicity.feather

  join_ethnicity:
    run: python:latest python analysis/join_ethnicity.py
    needs: [generate_study_population, generate_study_population_ethnicity]
    outputs:
      highly_sensitive:
        cohort: output/input*.feather

  generate_study_population_practice_count:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_practice_count --output-dir=output --output-format=feather
    outputs:
      highly_sensitive:
        cohort: output/input_practice_count.feather
    
  generate_measures:
    run: python:latest python analysis/calculate_measures.py
    needs: [join_ethnicity]
    outputs:
      moderately_sensitive:
        measure: output/combined_measure_*.csv
    
#   generate_measures:
#       run: cohortextractor:latest generate_measures --study-definition study_definition --output-dir=output
#       needs: [join_ethnicity]
#       outputs:
#         moderately_sensitive:
#           measure_csv: output/measure_*.csv

#   generate_measure_ethnicity:
#     run: python:latest python analysis/generate_measure_ethnicity.py
#     needs: [join_ethnicity]
#     outputs:
#       moderately_sensitive:
#         measure: output/measure_*_ethnicity.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
  
  
  
#   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_demographics:
    run: jupyter:latest jupyter nbconvert /workspace/notebooks/sentinel_measures_demographics.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_demographics.html
        figures: output/test_*.png
     
  # 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: [join_ethnicity]
#     outputs:
#       moderately_sensitive:
#         text: output/*_event_summary.csv

#   run_tests:
#     run: python:latest python -m pytest --junit-xml=output/pytest.xml --verbose
#     outputs:
#       moderately_sensitive:
#         log: output/pytest.xml

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime: 00:00:23

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

Job information

Status
Succeeded
Backend
TPP
Workspace
sro-measures-demographics
Requested by
Louis Fisher
Branch
demographics-notebook
Force run dependencies
No
Git commit hash
61ca223
Requested actions
  • generate_notebook_demographics

Code comparison

Compare the code used in this Job Request