This page shows the technical details of what happened when authorised researcher Milan Wiedemann 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
-
- Job identifier:
-
u2r6oailev5u6oni
-
- Job identifier:
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ovfultmdu7m7kms7
Pipeline
Show project.yaml
version: '3.0'
expectations:
population_size: 10000
actions:
generate_study_population:
run: cohortextractor:latest generate_cohort --study-definition study_definition --index-date-range "2019-09-01 to 2022-03-31 by month" --output-dir=output
outputs:
highly_sensitive:
cohort: output/input_*.csv
generate_study_population_ethnicity:
run: cohortextractor:latest generate_cohort --study-definition study_definition_ethnicity --output-dir=output
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_study_population_practice_count:
run: cohortextractor:latest generate_cohort --study-definition study_definition_practice_count --index-date-range "2019-09-01 to 2022-03-31 by month" --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: [join_ethnicity]
outputs:
moderately_sensitive:
measure_csv: output/measure_*_rate.csv
calculate_rates:
run: python:latest python analysis/rate_calculations.py
needs: [generate_measures]
outputs:
moderately_sensitive:
tables: output/rate_table_*.csv
child_code_table: output/child_code_table.csv
plots: output/plot_*.png
decile_chart: output/decile_chart.png
generate_notebook:
run: jupyter:latest jupyter nbconvert /workspace/analysis/qof_notebook.ipynb --execute --to html --output-dir=/workspace/output --ExecutePreprocessor.timeout=86400 --no-input
needs: [calculate_rates, generate_study_population_practice_count]
outputs:
moderately_sensitive:
notebook: output/qof_notebook.html
run_tests:
run: python:latest python -m pytest --junit-xml=output/pytest.xml --verbose
outputs:
moderately_sensitive:
log: output/pytest.xml
Timeline
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Created:
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Started:
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Finished:
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Runtime:
These timestamps are generated and stored using the UTC timezone on the backend.
Job information
- Status
-
Succeeded
- Backend
- TPP
- Workspace
- blood-pressure-qof
- Requested by
- Milan Wiedemann
- Branch
- master
- Force run dependencies
- No
- Git commit hash
- ae436b8
- Requested actions
-
-
calculate_rates
-
generate_notebook
-