zwitschi
4b3a15ed15
- Introduced multiple architecture documentation files covering building block view, runtime view, deployment view, concepts, architecture decisions, quality requirements, technical risks, glossary, UI and styling, testing, CI, and development setup. - Migrated existing content from `architecture_overview.md` and `implementation_plan.md` into structured documentation. - Created scripts for checking broken links in documentation and formatting Markdown files for consistency. - Updated quickstart guide to provide clearer setup instructions and usage overview. - Removed outdated MVP features and testing strategy documents to streamline documentation.
45 lines
2.9 KiB
Markdown
45 lines
2.9 KiB
Markdown
# 01 — Introduction and Goals
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Status: skeleton
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Describe the system purpose, stakeholders, and high-level goals. Fill this file with project introduction and business/technical goals.
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## Overview
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CalMiner is a FastAPI application that collects mining project inputs, persists scenario-specific records, and surfaces aggregated insights. The platform targets Monte Carlo driven planning, with deterministic CRUD features in place and simulation logic staged for future work.
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Frontend components are server-rendered Jinja2 templates, with Chart.js powering the dashboard visualization. The backend leverages SQLAlchemy for ORM mapping to a PostgreSQL database.
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### Runtime Flow
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1. Users navigate to form templates or API clients to manage scenarios, parameters, and operational data.
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2. FastAPI routers validate payloads with Pydantic models, then delegate to SQLAlchemy sessions for persistence.
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3. Simulation runs (placeholder `services/simulation.py`) will consume stored parameters to emit iteration results via `/api/simulations/run`.
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4. Reporting requests POST simulation outputs to `/api/reporting/summary`; the reporting service calculates aggregates (count, min/max, mean, median, percentiles, standard deviation, variance, and tail-risk metrics at the 95% confidence level).
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5. `templates/Dashboard.html` fetches summaries, renders metric cards, and plots distribution charts with Chart.js for stakeholder review.
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### Current implementation status (summary)
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- Currency normalization, simulation scaffold, and reporting service exist; see `docs/quickstart.md` for full status and migration instructions.
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## MVP Features (migrated)
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The following MVP features and priorities were migrated from `docs/mvp.md`.
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### Prioritized Features
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1. **Scenario Creation and Management** (High Priority): Allow users to create, edit, and delete scenarios. Rationale: Core functionality for what-if analysis.
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1. **Parameter Input and Validation** (High Priority): Input process parameters with validation. Rationale: Ensures data integrity for simulations.
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1. **Monte Carlo Simulation Run** (High Priority): Execute simulations and store results. Rationale: Key differentiator for risk analysis.
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1. **Basic Reporting** (Medium Priority): Display NPV, IRR, EBITDA from simulation results. Rationale: Essential for decision-making.
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1. **Cost Tracking Dashboard** (Medium Priority): Visualize CAPEX and OPEX. Rationale: Helps monitor expenses.
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1. **Consumption Monitoring** (Low Priority): Track resource consumption. Rationale: Useful for optimization.
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1. **User Authentication** (Medium Priority): Basic login/logout. Rationale: Security for multi-user access.
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1. **Export Results** (Low Priority): Export simulation data to CSV/PDF. Rationale: For external analysis.
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### Rationale for Prioritization
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- High: Core simulation and scenario features first.
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- Medium: Reporting and auth for usability.
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- Low: Nice-to-haves after basics.
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