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Job request: 20300

Organisation:
PrescQIPP
Workspace:
the_effects_of_covid-19_on_dfms_prescribing
ID:
2mzknoxlo54z4pn6
View repo View project.yaml

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

By cross-referencing the indicated Requested Actions with the Pipeline section below, you can infer what security level various outputs were written to. Outputs marked as highly_sensitive can never be viewed directly by a researcher; 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: 10000

actions:
  generate_study_population_1:
    run: cohortextractor:latest generate_cohort --study-definition study_definition --index-date-range "2018-01-01 to 2019-12-01 by month" --output-dir=output --output-format=csv
    outputs:
      highly_sensitive:
        cohort: output/input*.csv

  generate_study_population_2:
    run: cohortextractor:latest generate_cohort --study-definition study_definition --index-date-range "2020-01-01 to 2021-12-01 by month" --output-dir=output --output-format=csv
    outputs:
      highly_sensitive:
        cohort: output/input_*.csv
  
  generate_study_population_3:
    run: cohortextractor:latest generate_cohort --study-definition study_definition --index-date-range "2022-01-01 to 2023-04-01 by month" --output-dir=output --output-format=csv
    outputs:
      highly_sensitive:
        cohort: output/inp*.csv
 
  generate_indication:
    run: python:latest python analysis/indication_variables.py
    needs: [generate_study_population_1, generate_study_population_2, generate_study_population_3]
    outputs:
      highly_sensitive:
        cohort: output/inpu*.csv
  
  generate_medication:
    run: python:latest python analysis/medication_variables.py
    needs: [generate_indication]
    outputs:
      highly_sensitive:
        cohort: output/in*.csv

  generate_measures:
    run: cohortextractor:latest generate_measures --study-definition study_definition --output-dir=output
    needs: [generate_medication]
    outputs: 
      moderately_sensitive:
        measure_csv: output/measure_*_rate.csv

  generate_report:
    run: jupyter:latest jupyter nbconvert /workspace/analysis/report*.ipynb --execute --to html --template basic --output-dir=/workspace/output --ExecutePreprocessor.timeout=86400 --no-input
    needs: [generate_measures]
    outputs:
      moderately_sensitive:
        notebook: output/report*.html
        plots: output/*.png

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_1 failed on a previous run and must be re-run
Backend
TPP
Workspace
the_effects_of_covid-19_on_dfms_prescribing
Requested by
Rachel Seeley
Branch
main
Force run dependencies
No
Git commit hash
44ad72c
Requested actions
  • generate_indication
  • generate_medication
  • generate_measures

Code comparison

Compare the code used in this Job Request