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Job request: 14823

Organisation:
Bennett Institute
Workspace:
winter-pressures
ID:
r5uwxvg7wxwerygp

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.

Jobs

Pipeline

Show project.yaml
version: "3.0"

expectations:
  population_size: 5000

actions:
  # Other data
  # ----------
  # Add actions for other data to this section. Prefix them with a suitable name; place
  # scripts in a similarly named sub-directory of the analysis directory; write outputs
  # to a similarly named sub-directory of the output directory.
  #
  # For example, let's call our other data "metrics". We would prefix our actions
  # "metrics_"; we would place our scripts in analysis/metrics; we would write outputs
  # to output/metrics.

  # Appointments data
  # -----------------
  appointments_generate_dataset_sql:
    run: >
      sqlrunner:latest
        analysis/appointments/dataset_query.sql
        --output output/appointments/dataset_long.csv
        --dummy-data-file analysis/appointments/dummy_dataset_long.csv
    outputs:
      highly_sensitive:
        dataset: output/appointments/dataset_long.csv

  # appointments_generate_dataset:
  #   run: >
  #     databuilder:v0
  #       generate-dataset
  #       analysis/appointments/dataset_definition.py
  #       --output output/appointments/dataset_wide.arrow
  #   outputs:
  #     highly_sensitive:
  #       dataset: output/appointments/dataset_wide.arrow

  # appointments_get_freq_na_values:
  #   run: >
  #     python:latest
  #       python
  #       -m analysis.appointments.get_freq_na_values
  #   needs: [appointments_generate_dataset]
  #   outputs:
  #     moderately_sensitive:
  #       dataset: output/appointments/freq_na_values.csv

  # appointments_reshape_dataset:
  #   run: >
  #     python:latest
  #       python
  #       -m analysis.appointments.reshape_dataset
  #   needs: [appointments_generate_dataset]
  #   outputs:
  #     highly_sensitive:
  #       dataset: output/appointments/dataset_long.arrow

  # appointments_generate_measure:
  #   run: >
  #     python:latest
  #       python
  #       -m analysis.appointments.generate_measure
  #   needs: [appointments_reshape_dataset]
  #   outputs:
  #     moderately_sensitive:
  #       measure: output/appointments/measure_median_lead_time_in_days_by_nunique_patient_id.csv

  # appointments_generate_deciles_charts:
  #   run: >
  #     deciles-charts:v0.0.33
  #       --input-files output/appointments/measure_*.csv
  #       --output-dir output/appointments
  #   config:
  #     show_outer_percentiles: true
  #   needs: [appointments_generate_measure]
  #   outputs:
  #     moderately_sensitive:
  #       deciles_charts: output/appointments/deciles_chart_*.png
  #       deciles_tables: output/appointments/deciles_table_*.csv

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime: 01:53:52

These timestamps are generated and stored using the UTC timezone on the TPP backend.

Job information

Status
Succeeded
Backend
TPP
Workspace
winter-pressures
Requested by
Iain Dillingham
Branch
main
Force run dependencies
Yes
Git commit hash
88f76f8
Requested actions
  • run_all

Code comparison

Compare the code used in this Job Request