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Job request: 17788

Organisation:
Bennett Institute
Workspace:
opensafely-internal-interactive
ID:
akpo4pp5w7wbkazy
View repo View project.yaml

This page shows the technical details of what happened when the authorised researcher Catherine Stables 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_ethnicity_01H1BTGHGKYTT9B729STV09QG3:
    run: cohortextractor:latest generate_cohort
      --study-definition study_definition_ethnicity
      --output-dir output/01H1BTGHGKYTT9B729STV09QG3 --output-format=feather
    outputs:
      highly_sensitive:
        cohort: output/01H1BTGHGKYTT9B729STV09QG3/input_ethnicity.feather

  generate_study_population_weekly_01H1BTGHGKYTT9B729STV09QG3:
    run: cohortextractor:latest generate_cohort
      --study-definition study_definition
      --param codelist_1_frequency="weekly"
      --param breakdowns=""
      --index-date_range="2023-05-08 to 2023-05-08 by week"
      --output-dir=output/01H1BTGHGKYTT9B729STV09QG3
      --output-format=feather
      --output-file=output/01H1BTGHGKYTT9B729STV09QG3/input_weekly_2023-05-08.feather
    outputs:
      highly_sensitive:
        cohort: output/01H1BTGHGKYTT9B729STV09QG3/input_weekly_2023-05-08.feather

  generate_study_population_01H1BTGHGKYTT9B729STV09QG3:
    run: cohortextractor:latest generate_cohort
      --study-definition study_definition
      --index-date-range="2019-09-01 to 2023-04-30 by month"
      --output-dir=output/01H1BTGHGKYTT9B729STV09QG3
      --output-format=feather
    outputs:
      highly_sensitive:
        cohort: output/01H1BTGHGKYTT9B729STV09QG3/input_*.feather

  join_cohorts_01H1BTGHGKYTT9B729STV09QG3:
    run: >
      cohort-joiner:v0.0.38
        --lhs output/01H1BTGHGKYTT9B729STV09QG3/input_20*.feather
        --rhs output/01H1BTGHGKYTT9B729STV09QG3/input_ethnicity.feather
        --output-dir output/01H1BTGHGKYTT9B729STV09QG3/joined
    needs: [generate_study_population_01H1BTGHGKYTT9B729STV09QG3, generate_study_population_ethnicity_01H1BTGHGKYTT9B729STV09QG3]
    outputs:
      highly_sensitive:
        cohort: output/01H1BTGHGKYTT9B729STV09QG3/joined/input_20*.feather

  generate_measures_01H1BTGHGKYTT9B729STV09QG3:
    run: >
      python:latest -m analysis.measures
        --breakdowns=sex
        --breakdowns=age
        --breakdowns=ethnicity
        --breakdowns=imd
        --breakdowns=region
        --input-dir="output/01H1BTGHGKYTT9B729STV09QG3/joined"
        --output-dir="output/01H1BTGHGKYTT9B729STV09QG3"

    needs: [join_cohorts_01H1BTGHGKYTT9B729STV09QG3]
    outputs:
      moderately_sensitive:
        measure: output/01H1BTGHGKYTT9B729STV09QG3/measure_all.csv
        decile_measure: output/01H1BTGHGKYTT9B729STV09QG3/measure_practice_rate_deciles.csv

  top_5_table_01H1BTGHGKYTT9B729STV09QG3:
    run: >
      python:latest python analysis/top_5.py
      --codelist-1-path="interactive_codelists/codelist_1.csv"
      --codelist-2-path="interactive_codelists/codelist_2.csv"
      --output-dir="output/01H1BTGHGKYTT9B729STV09QG3"
    needs: [generate_measures_01H1BTGHGKYTT9B729STV09QG3]
    outputs:
      moderately_sensitive:
        table_1: output/01H1BTGHGKYTT9B729STV09QG3/top_5_code_table_1.csv
        table_2: output/01H1BTGHGKYTT9B729STV09QG3/top_5_code_table_2.csv
        tables_for_checking: output/01H1BTGHGKYTT9B729STV09QG3/for_checking/top_5*.csv

  plot_measure_01H1BTGHGKYTT9B729STV09QG3:
    run: >
      python:latest python analysis/plot_measures.py
        --breakdowns=sex
        --breakdowns=age
        --breakdowns=ethnicity
        --breakdowns=imd
        --breakdowns=region
        --input-dir output/01H1BTGHGKYTT9B729STV09QG3
        --output-dir output/01H1BTGHGKYTT9B729STV09QG3
    needs: [generate_measures_01H1BTGHGKYTT9B729STV09QG3]
    outputs:
      moderately_sensitive:
        measure: output/01H1BTGHGKYTT9B729STV09QG3/plot_measure*.png
        data: output/01H1BTGHGKYTT9B729STV09QG3/for_checking/plot_measure_for_checking.csv
        deciles: output/01H1BTGHGKYTT9B729STV09QG3/deciles_chart.png

  event_counts_01H1BTGHGKYTT9B729STV09QG3:
    run: >
      python:latest -m analysis.event_counts --input-dir="output/01H1BTGHGKYTT9B729STV09QG3" --output-dir="output/01H1BTGHGKYTT9B729STV09QG3"
    needs: [join_cohorts_01H1BTGHGKYTT9B729STV09QG3, generate_study_population_weekly_01H1BTGHGKYTT9B729STV09QG3]
    outputs:
      moderately_sensitive:
        measure: output/01H1BTGHGKYTT9B729STV09QG3/event_counts.json

  generate_report_01H1BTGHGKYTT9B729STV09QG3:
    run: >
      python:latest python analysis/render_report.py
      --output-dir="output/01H1BTGHGKYTT9B729STV09QG3"
    needs: [event_counts_01H1BTGHGKYTT9B729STV09QG3, top_5_table_01H1BTGHGKYTT9B729STV09QG3, plot_measure_01H1BTGHGKYTT9B729STV09QG3]
    outputs:
      moderately_sensitive:
        notebook: output/01H1BTGHGKYTT9B729STV09QG3/report.html

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime: 08:19:29

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

Job information

Status
Succeeded
Backend
TPP
Workspace
opensafely-internal-interactive
Requested by
Catherine Stables
Branch
main
Force run dependencies
Yes
Git commit hash
29ffb18
Requested actions
  • run_all

Code comparison

Compare the code used in this Job Request