Job request: 19010
- Organisation:
- PrescQIPP
- Workspace:
- the_effects_of_covid-19_on_doac_prescribing
- ID:
- vh4fnzb7v3zj43ro
This page shows the technical details of what happened when the 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 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
-
- Job identifier:
-
h4tvussaihitxjpw
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 2022-06-01 by month" --output-dir=output --output-format=feather
outputs:
highly_sensitive:
cohort: output/input_*.feather
generate_study_population_3:
run: cohortextractor:latest generate_cohort --study-definition study_definition --index-date-range "2022-07-01 to 2023-06-01 by month" --output-dir=output --output-format=feather
outputs:
highly_sensitive:
cohort: output/inp*.feather
generate_dose:
run: python:latest python analysis/calculate_dose_scaled_back.py
needs: [generate_study_population_1, generate_study_population_2, generate_study_population_3]
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_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
Timeline
-
Created:
-
Started:
-
Finished:
-
Runtime: 00:01:58
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
- 05995e5
- Requested actions
-
-
generate_notebook
-
Code comparison
Compare the code used in this Job Request