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Job request: 7256

Organisation:
PrescQIPP
Workspace:
the_effects_of_covid-19_on_doac_prescribing
ID:
n6mfanee3atxeuo3

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.

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
  
  filter_population:
    run: python:latest python analysis/filter_population.py
    needs: [generate_dose]
    outputs:
      highly_sensitive:
        cohort: output/filtered/input*.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/filtered
    needs: [filter_population]
    outputs: 
      moderately_sensitive:
        measure_csv: output/filtered/measure_*_rate.csv

  generate_notebook:
    run: jupyter:latest jupyter nbconvert /workspace/analysis/report.ipynb --execute --to html --template basic --output-dir=/workspace/output/filtered --ExecutePreprocessor.timeout=86400 --no-input
    needs: [generate_measures]
    outputs:
      moderately_sensitive:
        notebook: output/filtered/report.html
        plots: output/filtered/*.png
        tables: output/filtered/*.csv
        
  #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: 00:30:52

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

Job information

Status
Succeeded
Backend
TPP
Requested by
Rachel Seeley
Branch
main
Force run dependencies
No
Git commit hash
4f6d031
Requested actions
  • generate_measures
  • generate_notebook

Code comparison

Compare the code used in this Job Request