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Job request: 11380

Organisation:
Bennett Institute
Workspace:
dmd_codelist_investigation
ID:
qtk3mnpywyrltv6t
View repo View project.yaml

This page shows the technical details of what happened when the authorised researcher Jon Massey requested one or more actions to be run against real patient data within a secure environment.

By cross-referencing the list of jobs with the pipeline section below, you can infer what security level the outputs were written to.

The output security levels are:

  • highly_sensitive
    • Researchers can never directly view these outputs
    • Researchers can only request code is run against them
  • moderately_sensitive
    • Can be viewed by an approved researcher by logging into a highly secure environment
    • These are the only outputs that can be requested for public release via a controlled output review service.

Jobs

Pipeline

Show project.yaml 
version: '3.0'

expectations:
  population_size: 1000

actions:

  generate_study_population_2019:
    run: cohortextractor:latest generate_cohort --study-definition study_definition --index-date-range "2019-01-01" --output-format=csv.gz
    outputs:
      highly_sensitive:
        cohort: output/input_2019-01-01.csv.gz

  generate_study_population_2020:
    run: cohortextractor:latest generate_cohort --study-definition study_definition --index-date-range "2020-01-01" --output-format=csv.gz
    outputs:
      highly_sensitive:
        cohort: output/input_2020-01-01.csv.gz

  generate_study_population_2021:
    run: cohortextractor:latest generate_cohort --study-definition study_definition --index-date-range "2021-01-01" --output-format=csv.gz
    outputs:
      highly_sensitive:
        cohort: output/input_2021-01-01.csv.gz

  generate_study_population_2022:
    run: cohortextractor:latest generate_cohort --study-definition study_definition --index-date-range "2022-01-01" --output-format=csv.gz
    outputs:
      highly_sensitive:
        cohort: output/input_2022-01-01.csv.gz

  run_counts:
    run: python:latest python analysis/counts.py
    needs: [generate_study_population_2019, generate_study_population_2020, generate_study_population_2021, generate_study_population_2022]
    outputs:
      moderately_sensitive:
        counts_2019:
          output/counts_2019.csv
        counts_2020:
          output/counts_2020.csv
        counts_2021:
          output/counts_2021.csv
        counts_2022:
          output/counts_2022.csv

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime: 81:35:57

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

Job request

Status
Succeeded
Backend
TPP
Workspace
dmd_codelist_investigation
Requested by
Jon Massey
Branch
main
Force run dependencies
No
Git commit hash
7063354
Requested actions
  • run_counts

Code comparison

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