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Job request: 4751

Organisation:
Bennett Institute
Workspace:
sro-measures-emis
ID:
bkxgctrec635dfo6

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_1:
    run: cohortextractor:latest generate_cohort --study-definition study_definition --index-date-range "2019-01-01 to 2019-12-01 by month" --output-dir=output --output-format=feather
    outputs:
      highly_sensitive:
        cohort: output/input_*.feather
  
  generate_study_population_2:
    run: cohortextractor:latest generate_cohort --study-definition study_definition --index-date-range "2020-01-01 to 2020-12-01 by month" --output-dir=output --output-format=feather
    outputs:
      highly_sensitive:
        cohort: output/input*.feather

  generate_study_population_3:
    run: cohortextractor:latest generate_cohort --study-definition study_definition --index-date-range "2021-01-01 to 2021-06-01 by month" --output-dir=output --output-format=feather
    outputs:
      highly_sensitive:
        cohort: output/inpu*.feather

  get_patient_count:
    run: python:latest python analysis/get_patients_counts.py
    needs: [generate_study_population_1, generate_study_population_2, generate_study_population_3]
    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_1, generate_study_population_2, generate_study_population_3, generate_study_population_ethnicity]
    outputs:
      highly_sensitive:
        cohort: output/inp*.feather

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

  generate_measures_cleaned:
    run: python:latest python analysis/clean_measures.py
    needs: [generate_measures]
    outputs:
        moderately_sensitive:
          measure_csv: output/measure_cleaned_*.csv
          

  generate_measures_demographics:
    run: python:latest python analysis/calculate_measures.py
    needs: [join_ethnicity]
    outputs:
      moderately_sensitive:
        measure: output/combined_measure_*.csv
    
  
  generate_notebook:
    run: jupyter:latest jupyter nbconvert /workspace/analysis/sentinel_measures.ipynb --execute --to html --template basic --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
        subplots: output/sentinel_measures_subplots.png
  

  generate_notebook_demographics:
    run: jupyter:latest jupyter nbconvert /workspace/analysis/sentinel_measures_demographics.ipynb --execute --to html --template basic --output-dir=/workspace/output --ExecutePreprocessor.timeout=86400 --no-input
    needs: [generate_measures, generate_measures_demographics]
    outputs:
      moderately_sensitive:
        notebook: output/sentinel_measures_demographics.html

  get_population_count:
    run: python:latest python analysis/population_counts.py
    needs: [join_ethnicity]
    outputs:
      moderately_sensitive:
        text: output/*_count.csv

  demographic_changes:
    run: python:latest python analysis/demographic_change.py
    needs: [generate_measures_demographics]
    outputs:
      moderately_sensitive:
        csv: output/demographics_differences.csv
        csv_sorted: output/demographics_differences_sorted.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: 00:00:28

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

Job information

Status
Succeeded
Backend
EMIS
Workspace
sro-measures-emis
Requested by
Louis Fisher
Branch
emis
Force run dependencies
No
Git commit hash
52ca7f5
Requested actions
  • generate_measures_cleaned

Code comparison

Compare the code used in this Job Request