This page shows the technical details of what happened when authorised researcher Louis Fisher 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:
-
owwe2nlhuf6m765z
Pipeline
Show project.yaml
version: "3.0"
expectations:
population_size: 1000
actions:
generate_study_population_1:
run: cohortextractor:latest generate_cohort --study-definition study_definition --index-date-range "2019-01-01 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 2020-12-01 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 "2021-01-01 to 2021-06-01 by month" --output-dir=output --output-format=feather
outputs:
highly_sensitive:
cohort: output/inpu*.feather
generate_study_population_4:
run: cohortextractor:latest generate_cohort --study-definition study_definition --index-date-range "2021-07-01 to 2021-12-01 by month" --output-dir=output --output-format=feather
outputs:
highly_sensitive:
cohort: output/in*.feather
generate_study_population_5:
run: cohortextractor:latest generate_cohort --study-definition study_definition --index-date-range "2022-01-01 to 2022-05-01 by month" --output-dir=output --output-format=feather
outputs:
highly_sensitive:
cohort: output/i*.feather
get_patient_count:
run: python:latest python analysis/get_patients_counts.py
needs: [generate_study_population_4, generate_study_population_5, join_ethnicity]
outputs:
moderately_sensitive:
text: output/patient_count.json
generate_study_population_ethnicity:
run: cohortextractor:latest generate_cohort --study-definition study_definition_ethnicity --output-dir=output --output-format=feather
outputs:
highly_sensitive:
cohort: output/input_ethnicity.feather
join_ethnicity:
run: python:latest python analysis/join_ethnicity.py
needs:
[
generate_study_population_1,
generate_study_population_2,
generate_study_population_3,
generate_study_population_ethnicity,
]
outputs:
highly_sensitive:
cohort: output/inp*.feather
get_practice_count:
run: python:latest python analysis/get_practice_count.py
needs: [join_ethnicity, generate_study_population_4, generate_study_population_5]
outputs:
moderately_sensitive:
text: output/practice_count.json
generate_measures:
run: cohortextractor:latest generate_measures --study-definition study_definition --output-dir=output
needs: [join_ethnicity, generate_study_population_4, generate_study_population_5]
outputs:
moderately_sensitive:
measure_csv: output/measure_*_rate.csv
generate_measures_cleaned:
run: python:latest python analysis/clean_measures.py
needs: [generate_measures]
outputs:
moderately_sensitive:
measure_csv: output/measure_cleaned_*.csv
generate_notebook:
run: jupyter:latest jupyter nbconvert /workspace/analysis/sentinel_measures.ipynb --execute --to html --template basic --output-dir=/workspace/output --ExecutePreprocessor.timeout=86400 --no-input
needs:
[
generate_measures,
generate_measures_cleaned,
get_practice_count,
get_patient_count,
]
outputs:
moderately_sensitive:
notebook: output/sentinel_measures.html
subplots: output/sentinel_measures_subplots.png
code_tables: output/code_table_*.csv
events_count: output/event_count.json
generate_notebook_updating:
run: jupyter:latest jupyter nbconvert /workspace/analysis/sentinel_measures_updating.ipynb --execute --to html --template basic --output-dir=/workspace/output --ExecutePreprocessor.timeout=86400 --no-input
needs:
[
generate_measures,
generate_measures_cleaned,
get_practice_count,
get_patient_count,
]
outputs:
moderately_sensitive:
notebook: output/sentinel_measures_updating.html
code_tables: output/code_table*.csv
practices: output/num_practices_included*.csv
# run_tests:
# run: python:latest python -m pytest --junit-xml=output/pytest.xml --verbose
# outputs:
# moderately_sensitive:
# log: output/pytest.xml
Timeline
-
Created:
-
Started:
-
Finished:
-
Runtime: 00:01:36
These timestamps are generated and stored using the UTC timezone on the backend.
Job information
- Status
-
Succeeded
- Backend
- TPP
- Workspace
- sro-measures
- Requested by
- Louis Fisher
- Branch
- master
- Force run dependencies
- No
- Git commit hash
- 49ff190
- Requested actions
-
-
generate_notebook_updating
-