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Job request: 7013

Organisation:
PrescQIPP
Workspace:
the_effects_of_covid-19_on_doac_prescribing
ID:
mqpc7ewfs5jiw4r6

This page shows the technical details of what happened when the 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 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: 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=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 2021-12-01 by month" --output-dir=output --output-format=feather
    outputs:
      highly_sensitive:
        cohort: output/input_*.feather

  generate_dose:
    run: python:latest python analysis/calculate_dose_scaled_back.py
    needs: [generate_study_population_1, generate_study_population_2]
    outputs:
      highly_sensitive:
        cohort: output/inpu*.feather
  
  #generate_study_population_ethnicity:
  #run: cohortextractor:latest generate_cohort --study-definition study_definition_ethnicity --output-dir=output --output-format=csv
  #outputs:
  #highly_sensitive:
  #cohort: output/input_ethnicity.csv

  #join_ethnicity:
  #run: python:latest python analysis/join_ethnicity.py
  #needs: [generate_study_population, generate_study_population_ethnicity]
  #outputs:
  #highly_sensitive:
  #cohort: output/input*.csv

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

  generate_notebook:
    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

  #generate_dose_match:
  #run: python:latest python analysis/dose_match.py
  #needs: [generate_measures]
  #outputs:
  #moderately_sensitive:
  #figure: output/dose_match.png

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime: 00:00:59

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

Job information

Status
Failed
Backend
TPP
Requested by
Rachel Seeley
Branch
main
Force run dependencies
No
Git commit hash
1a7c30b
Requested actions
  • generate_notebook

Code comparison

Compare the code used in this Job Request