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Scheduler Documentation (Core Algorithm and Surrounding Modules)
This documentation explains the end‑to‑end flow for the scheduler and its supporting modules, and provides detailed per‑directory guides that document individual files. Start with the high‑level flowchart, then dive into the directory guides.
- High‑level flowchart: see
docs/scheduler_flowchart.md - Directory guides (each includes per‑file details):
docs/core.md— core scheduler domain and algorithmdocs/simulation.md— discrete‑event simulation and policiesdocs/control.md— manual overrides and explainability surfacesdocs/dashboard.md— Streamlit dashboard and pagesdocs/data.md— data loaders, defaults and configurationdocs/metrics.md— basic metrics utilitiesdocs/monitoring.md— ripeness monitoring (not yet integrated)docs/utils.md— utilities (calendar)
Related (outside current scope but referenced):
- Outputs (cause lists, reports) live under
scheduler/output/andoutputs/.
Quick Start Reading Order
scheduler_flowchart.md(overview)core.md(domain + algorithm)simulation.md(how scenarios are evaluated at scale)control.md(how human inputs override the algorithm)dashboard.md(how the UI wires it together)
Definitions at a Glance
- Case ripeness: classification indicating whether a case is ready to be scheduled and with what priority. Implemented in
scheduler/core/ripeness.py. - Scheduling algorithm: orchestrates filtering, prioritization, overrides, and courtroom allocation. Implemented in
scheduler/core/algorithm.py. - Simulation: forward model to evaluate policy performance over time. Implemented in
scheduler/simulation/engine.pyand related modules.