Skip to content

Job request: 275

Organisation:
The London School of Hygiene & Tropical Medicine
Workspace:
households
ID:
tobtpcdypjti3qgr
View repo View project.yaml

This page shows the technical details of what happened when the authorised researcher Kevin Wing 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: 100000


actions:
  generate_cohort:
    run: cohortextractor:latest generate_cohort
    outputs:
      highly_sensitive:
        cohort: output/input.csv

  prepare_data:
    run: stata-mp:latest analysis/01_hh_cr_analysis_dataset.do
    needs: [generate_cohort]
    outputs:
      highly_sensitive:
        allvars: hh_analysis_dataset.dta

  descriptive_notebook:
    run: jupyter:latest jupyter nbconvert /workspace/analysis/opensafely_eda_test_notebook.ipynb --execute --to html --output-dir=/workspace --ExecutePreprocessor.timeout=86400
    needs: [prepare_data]
    outputs:
      moderately_sensitive:
        notebook: opensafely_eda_test_notebook.html
        ages: analysis/ages.png
        hhsize: analysis/hh_sizes.png
        cases: analysis/hh_cases_*.png

  vo_test:
    run: python:latest python analysis/fit_vo.py 20
    needs: []
    outputs:
      moderately_sensitive:
        vo: vo.txt

  generate_model_data:
    run: python:latest python analysis/generate_model_data.py
    needs: [prepare_data]
    outputs:
      moderately_sensitive:
        log: generate_model_data.log
        timeseries: output/case_series.pickle
        agecats: output/age_categories_series.pickle

  run_model_with_ridge:
    run: python:latest python analysis/opensafely_age_hh.py increase_nll
    needs: [generate_model_data]
    outputs:
      moderately_sensitive:
        log: opensafely_age_hh_with_ridge.log

  run_model_no_ridge:
    run: python:latest python analysis/opensafely_age_hh_th.py
    needs: [generate_model_data]
    outputs:
      moderately_sensitive:
        log: opensafely_age_hh_without_ridge.log

Timeline

  • Created:

  • Started:

  • Runtime:

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

Job information

Status
Succeeded
Backend
TPP
Workspace
households
Requested by
Kevin Wing
Branch
master
Force run dependencies
No
Git commit hash
aadd456
Requested actions
  • generate_model_data

Code comparison

Compare the code used in this Job Request