This page shows the technical details of what happened when authorised researcher Helen Curtis 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
various outputs were written to. Outputs marked as
can never be viewed directly by a researcher; they can only
request that code runs against them. Outputs marked as
can be viewed by an approved researcher by logging into a highly
secure environment. Only outputs marked as
can be requested for release to the public, via a controlled
output review service.
- Status: Succeeded
- Job identifier:
version: '3.0' expectations: population_size: 10000 actions: generate_study_population: run: cohortextractor:latest generate_cohort --study-definition study_definition --index-date-range "2021-10-01 to 2021-10-08 by week" --output-dir=output --output-format=feather outputs: highly_sensitive: cohort: output/input_*.feather generate_report: run: cohort-report:v3.0.0 output/input_2021-10-01.feather needs: [generate_study_population] config: output_path: output/cohort_reports_outputs outputs: moderately_sensitive: reports: output/cohort_reports_outputs/descriptives_input_2021-10-01.html generate_measures: run: cohortextractor:latest generate_measures --study-definition study_definition --output-dir=output needs: [generate_study_population] outputs: moderately_sensitive: measure_csv_1: output/measure_*_rate.csv measure_csv_2: output/measure_*_rate_by_region.csv measure_csv_3: output/measure_*_rate_by_comparator.csv measure_csv_4: output/measure_*_rate_by_value.csv # note the weekly files are not stored, only the compiled file calculate_rates: run: python:latest python analysis/rate_calculations.py needs: [generate_measures] outputs: moderately_sensitive: tables: output/*_per_test.csv # generate_notebook: # run: jupyter:latest jupyter nbconvert /workspace/analysis/SRO_Notebook.ipynb --execute --to html --output-dir=/workspace/output --ExecutePreprocessor.timeout=86400 --no-input # needs: [create_notebook, calculate_rates, generate_study_population_practice_count] # outputs: # moderately_sensitive: # notebook: output/SRO_Notebook.html # run_tests: # run: python:latest python -m pytest --junit-xml=output/pytest.xml --verbose # outputs: # moderately_sensitive: # log: output/pytest.xml
These timestamps are generated and stored using the UTC timezone on the backend.