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This page shows the technical details of what happened when authorised researcher Chris Yeung requested one or more actions to be run against real patient data in the Graphnet-OpenSAFELY-Test 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
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.
Show Hide project.yaml
version: '3.0' expectations: population_size: 1000 actions: generate_study_population: run: cohortextractor:latest generate_cohort --study-definition study_definition --index-date-range "2019-01-01 to 2021-02-01 by month" --output-dir=output outputs: highly_sensitive: cohort: output/input_*.csv generate_study_population_practice_count: run: cohortextractor:latest generate_cohort --study-definition study_definition_practice_count --output-dir=output outputs: highly_sensitive: cohort: output/input_practice_count.csv generate_measures: run: cohortextractor:latest generate_measures --study-definition study_definition --output-dir=output needs: [generate_study_population] outputs: moderately_sensitive: measure_csv: output/measure_*.csv get_practice_count: run: python:latest python analysis/get_practice_count.py needs: [generate_study_population_practice_count] outputs: moderately_sensitive: text: output/practice_count.json get_patient_count: run: python:latest python analysis/get_patients_counts.py needs: [generate_study_population] outputs: moderately_sensitive: text: output/patient_count.json generate_notebook: run: jupyter:latest jupyter nbconvert /workspace/notebooks/sentinel_measures.ipynb --execute --to html --output-dir=/workspace/output --ExecutePreprocessor.timeout=86400 --no-input needs: [generate_measures, get_practice_count, get_patient_count] outputs: moderately_sensitive: notebook: output/sentinel_measures.html # generate_notebook_practice: # run: jupyter:latest jupyter nbconvert /workspace/notebooks/sentinel_measures_by_practice.ipynb --execute --to html --output-dir=/workspace/output --ExecutePreprocessor.timeout=86400 --no-input # needs: [generate_measures, get_practice_count, get_patient_count] # outputs: # moderately_sensitive: # notebook: output/sentinel_measures_by_practice.html # csvs: output/*_check.csv get_event_summary: run: python:latest python analysis/get_event_summary.py needs: [generate_study_population] outputs: moderately_sensitive: text: output/*_event_summary.csv
State is inferred from the related Jobs.
Timings set to UTC timezone.
- Runtime: 00:11:36