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Job request: 12133

Organisation:
Bennett Institute
Workspace:
sro-measures
ID:
m2xp6lqcgfbktlpb
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_population:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_population --index-date-range "2019-01-01 to 2022-05-01 by month" --output-dir=output --output-format=feather
    outputs:
      highly_sensitive:
        cohort: output/input_population*.feather
        
  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 2022-05-01 by month" --output-dir=output --output-format=feather
    outputs:
      highly_sensitive:
        cohort: output/i*.feather


  get_patient_count:
    run: python:latest python analysis/get_patients_counts.py
    needs: [generate_study_population_4, generate_study_population_5, join_ethnicity]
    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, generate_study_population_4, generate_study_population_5]
    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, generate_study_population_4, generate_study_population_5]
    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

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime: 05:55:19

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

Job information

Status
Succeeded
Backend
TPP
Workspace
sro-measures
Requested by
Louis Fisher
Branch
master
Force run dependencies
No
Git commit hash
f5d1f08
Requested actions
  • generate_study_population_population

Code comparison

Compare the code used in this Job Request