Job request: 12949
- Organisation:
- Bennett Institute
- Workspace:
- appointments-short-data-report
- ID:
- porhjznnkfcln7oy
This page shows the technical details of what happened when the authorised researcher Iain Dillingham 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.
Pipeline
Show project.yaml
version: "3.0"
expectations:
population_size: 1000
actions:
query_distinct_values:
run: >
sqlrunner:latest
--output output/distinct_values/rows.csv
analysis/distinct_values/query.sql
outputs:
highly_sensitive:
rows: output/distinct_values/rows.csv
wrangle_distinct_values:
needs: [query_distinct_values]
run: >
python:latest python -m analysis.distinct_values.wrangle
outputs:
moderately_sensitive:
results: output/distinct_values/results.csv
query_date_range:
run: >
sqlrunner:latest
--output output/date_range/rows.csv
analysis/date_range/query.sql
outputs:
highly_sensitive:
rows: output/date_range/rows.csv
wrangle_date_range:
needs: [query_date_range]
run: >
python:latest python -m analysis.date_range.wrangle
outputs:
moderately_sensitive:
results: output/date_range/results.csv
query_num_rows_by_month:
run: >
sqlrunner:latest
--output output/num_rows_by_month/rows.csv
analysis/num_rows_by_month/query.sql
outputs:
highly_sensitive:
rows: output/num_rows_by_month/rows.csv
wrangle_num_rows_by_month:
needs: [query_num_rows_by_month]
run: >
python:latest python -m analysis.num_rows_by_month.wrangle
outputs:
moderately_sensitive:
results: output/num_rows_by_month/results.csv
query_lead_time:
run: >
sqlrunner:latest
--output output/lead_time/rows.csv
analysis/lead_time/query.sql
outputs:
highly_sensitive:
rows: output/lead_time/rows.csv
wrangle_lead_time:
needs: [query_lead_time]
run: >
python:latest python -m analysis.lead_time.wrangle
outputs:
moderately_sensitive:
results: output/lead_time/results.csv
make_html_reports:
# --execute
# execute notebooks before converting them to HTML reports
# --no-input
# exclude input cells and output prompts from HTML reports
# --to=html
# convert notebooks to HTML reports (not e.g. to PDF reports)
# --template basic
# use the basic (unstyled) template for HTML reports
# --output-dir=output/reports
# write HTML reports to the `output/reports` directory
run: >
python:latest jupyter nbconvert
--execute
--no-input
--to=html
--template basic
--output-dir=output/reports
analysis/reports/*.ipynb
needs:
- wrangle_distinct_values
- wrangle_date_range
- wrangle_num_rows_by_month
outputs:
moderately_sensitive:
reports: output/reports/*.html
Timeline
-
Created:
-
Started:
-
Finished:
-
Runtime:
These timestamps are generated and stored using the UTC timezone on the TPP backend.
Job information
- Status
-
Failed
JobRequestError: make_html_reports failed on a previous run and must be re-run
- Backend
- TPP
- Workspace
- appointments-short-data-report
- Requested by
- Iain Dillingham
- Branch
- main
- Force run dependencies
- No
- Git commit hash
- 2c4761a
- Requested actions
-
-
query_date_range
-
wrangle_date_range
-
run_all
-
Code comparison
Compare the code used in this Job Request