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Job request: 19761

Organisation:
Bennett Institute
Workspace:
sro-measures-dashboard-updating
ID:
hyyhgqj5fcnijvra
View repo View project.yaml

This page shows the technical details of what happened when the authorised researcher Rose Higgins 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.

Pipeline

Show project.yaml 
version: "3.0"

expectations:
  population_size: 1000

actions:
  
  generate_study_population_population:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_population --index-date-range "2019-01-01 to 2023-08-01 by month" --output-dir=output --output-format=feather
    outputs:
      highly_sensitive:
        cohort: output/input_population*.feather

  join_ethnicity_population:
    run: >
      cohort-joiner:v0.0.46
        --lhs output/input_population_20*.feather
        --rhs output/input_ethnicity.feather
        --output-dir output/joined
    needs: [generate_study_population_population, generate_study_population_ethnicity]
    outputs:
      highly_sensitive:
        cohort: output/joined/input_population_20*.feather

  get_moved_count:
    run: python:latest python analysis/population_count.py
    needs: [join_ethnicity_population]
    outputs:
      moderately_sensitive:
        text: output/move*.json


  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

  generate_study_population_4:
    run: cohortextractor:latest generate_cohort --study-definition study_definition --index-date-range "2021-07-01 to 2021-12-01 by month" --output-dir=output --output-format=feather
    outputs:
      highly_sensitive:
        cohort: output/in*.feather

  generate_study_population_5:
    run: cohortextractor:latest generate_cohort --study-definition study_definition --index-date-range "2022-01-01 to 2023-08-01 by month" --output-dir=output --output-format=feather
    outputs:
      highly_sensitive:
        cohort: output/i*.feather


  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_4,
        generate_study_population_5,
        generate_study_population_ethnicity,
      ]
    outputs:
      highly_sensitive:
        cohort: output/inp*.feather

  get_patient_count:
    run: python:latest python analysis/get_patients_counts.py
    needs: [join_ethnicity]
    outputs:
      moderately_sensitive:
        text: output/patient_count.json
      
  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_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,
        generate_measures_cleaned,
        get_practice_count,
        get_patient_count,
      ]
    outputs:
      moderately_sensitive:
        notebook: output/sentinel_measures.html
        subplots: output/sentinel_measures_subplots.png
        code_tables: output/code_table_*.csv
        events_count: output/event_count.json

  generate_notebook_updating:
      run: jupyter:latest jupyter nbconvert /workspace/analysis/sentinel_measures_updating.ipynb --execute --to html --template basic --output-dir=/workspace/output --ExecutePreprocessor.timeout=86400 --no-input
      needs:
        [
          generate_measures,
          generate_measures_cleaned,
          get_practice_count,
          get_patient_count,
        ]
      outputs:
        moderately_sensitive:
          notebook: output/sentinel_measures_updating.html
          code_tables: output/code_table*.csv
          practices: output/num_practices_included*.csv

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

  measures_ehrql:
    run: ehrql:v0 generate-measures analysis/dataset_definition.py --output output/measures.csv
    outputs:
      moderately_sensitive:
        measure_csv: output/measures.csv

  generate_notebook_updating_ehrql:
    run: jupyter:latest jupyter nbconvert /workspace/analysis/sentinel_measures_updating_ehrql.ipynb --execute --to html --template basic --output-dir=/workspace/output --ExecutePreprocessor.timeout=86400 --no-input
    needs:
      [measures_ehrql]
    outputs:
      moderately_sensitive:
        notebook: output/sentinel_measures_updating_ehrql.html

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime:

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

Job information

Status
Failed 
JobRequestError: generate_study_population_5 failed on a previous run and must be re-run
Backend
TPP
Workspace
sro-measures-dashboard-updating
Requested by
Rose Higgins
Branch
main
Force run dependencies
No
Git commit hash
279ec78
Requested actions
  • run_all

Code comparison

Compare the code used in this Job Request