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
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
ID | Status | Action |
---|---|---|
n4watsbidqtpbahs | succeeded | get_practice_count |
hninjwl76civykx3 | succeeded | get_patient_count |
3onleyjujgvxwimd | succeeded | generate_notebook |
b2p6amwsewgkgmpl | failed | get_event_summary |
Pipeline
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
State is inferred from the related Jobs.
Status: Failed
Timings
Timings set to UTC timezone.
- Created:
- Started:
- Finished:
- Runtime: 00:11:17
Config
-
- Backend:
-
GRAPHNET
-
- Workspace:
- sro-measure-cam-test
-
- Branch:
graphnet
-
- Creator:
- chrisyeunggraphnet
-
- Force run dependencies:
- False
-
- Git Commit Hash:
- 049f0cf
-
Requested actions:
get_practice_count
get_patient_count
generate_notebook
get_event_summary