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zwitschi
c6a0eb2588 v2 init 2025-11-09 16:49:46 +01:00
zwitschi
d807a50f77 v2 init 2025-11-09 16:49:27 +01:00
zwitschi
22ddfb671d update README
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2025-11-09 13:28:24 +01:00
zwitschi
971b4a19ea moved docs to own repo
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zwitschi
5b1278cbea fix: add echo statement to log pip cache directory in CI workflow 2025-11-06 12:08:26 +01:00
zwitschi
b6511e5273 feat: add build job to CI workflow for Docker image creation and pushing
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zwitschi
bcb15bd0e4 chore: remove obsolete CI workflow configuration 2025-11-06 11:59:48 +01:00
zwitschi
42f8714d71 feat: add CI workflow configuration for testing and building
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zwitschi
1881ebe24f fix: correct syntax for environment variable references in CI workflow
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d90aae3d0a style: update CSS variables and styles for improved theming and consistency
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zwitschi
9934d1483d Merge pull request 'feat/ci-overhaul-20251029' (#11) from feat/ci-overhaul-20251029 into main
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Reviewed-on: #11
 2025-11-02 18:13:14 +01:00
153 changed files with 227 additions and 15049 deletions
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74
.gitea/workflows/ci.yml
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@@ -1,74 +0,0 @@
name: CI
on:
push:
branches: [main, develop]
pull_request:
branches: [main, develop]
jobs:
test:
env:
APT_CACHER_NG: http://192.168.88.14:3142
DB_DRIVER: postgresql+psycopg2
DB_HOST: 192.168.88.35
DB_NAME: calminer_test
DB_USER: calminer
DB_PASSWORD: calminer_password
runs-on: ubuntu-latest
services:
postgres:
image: postgres:17
env:
POSTGRES_USER: ${ { env.DB_USER } }
POSTGRES_PASSWORD: ${ { env.DB_PASSWORD } }
POSTGRES_DB: ${ { env.DB_NAME } }
options: >-
--health-cmd pg_isready
--health-interval 10s
--health-timeout 5s
--health-retries 5
steps:
- uses: actions/checkout@v4
- name: Set up Python
uses: actions/setup-python@v4
with:
python-version: '3.11'
- name: Update apt-cacher-ng config
run: |-
echo 'Acquire::http::Proxy "{{ env.APT_CACHER_NG }}";' | tee /etc/apt/apt.conf.d/01apt-cacher-ng
apt-get update
- name: Update system packages
run: apt-get upgrade -y
- name: Install dependencies
run: |
python -m pip install --upgrade pip
pip install -r requirements.txt
pip install -r requirements-test.txt
- name: Install Playwright system dependencies
run: playwright install-deps
- name: Install Playwright browsers
run: playwright install
- name: Run tests
env:
DATABASE_DRIVER: ${ { env.DB_DRIVER } }
DATABASE_HOST: ${ { env.DB_HOST } }
DATABASE_PORT: 5432
DATABASE_USER: ${ { env.DB_USER } }
DATABASE_PASSWORD: ${ { env.DB_PASSWORD } }
DATABASE_NAME: ${ { env.DB_NAME } }
run: |
pytest tests/ --cov=.
- name: Build Docker image
run: |
docker build -t calminer .

141
.gitea/workflows/cicache.yml Normal file
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@@ -0,0 +1,141 @@
name: CI
on:
push:
branches: [main, develop]
pull_request:
branches: [main, develop]
jobs:
test:
env:
APT_CACHER_NG: http://192.168.88.14:3142
DB_DRIVER: postgresql+psycopg2
DB_HOST: 192.168.88.35
DB_NAME: calminer_test
DB_USER: calminer
DB_PASSWORD: calminer_password
runs-on: ubuntu-latest
services:
postgres:
image: postgres:17
env:
POSTGRES_USER: ${{ env.DB_USER }}
POSTGRES_PASSWORD: ${{ env.DB_PASSWORD }}
POSTGRES_DB: ${{ env.DB_NAME }}
options: >-
--health-cmd pg_isready
--health-interval 10s
--health-timeout 5s
--health-retries 5
steps:
- uses: actions/checkout@v4
- name: Set up Python
uses: actions/setup-python@v4
with:
python-version: '3.11'
- name: Get pip cache dir
id: pip-cache
run: |
echo "path=$(pip cache dir)" >> $GITEA_OUTPUT
echo "Pip cache dir: $(pip cache dir)"
- name: Cache pip dependencies
uses: actions/cache@v4
with:
path: ${{ steps.pip-cache.outputs.path }}
key: ${{ runner.os }}-pip-${{ hashFiles('requirements.txt', 'requirements-test.txt') }}
restore-keys: |
${{ runner.os }}-pip-
- name: Update apt-cacher-ng config
run: |-
echo 'Acquire::http::Proxy "{{ env.APT_CACHER_NG }}";' | tee /etc/apt/apt.conf.d/01apt-cacher-ng
apt-get update
- name: Update system packages
run: apt-get upgrade -y
- name: Install dependencies
run: |
python -m pip install --upgrade pip
pip install -r requirements.txt
pip install -r requirements-test.txt
- name: Install Playwright system dependencies
run: playwright install-deps
- name: Install Playwright browsers
run: playwright install
- name: Run tests
env:
DATABASE_DRIVER: ${{ env.DB_DRIVER }}
DATABASE_HOST: postgres
DATABASE_PORT: 5432
DATABASE_USER: ${{ env.DB_USER }}
DATABASE_PASSWORD: ${{ env.DB_PASSWORD }}
DATABASE_NAME: ${{ env.DB_NAME }}
run: |
pytest tests/ --cov=.
- name: Build Docker image
run: |
docker build -t calminer .
build:
runs-on: ubuntu-latest
needs: test
env:
DEFAULT_BRANCH: main
REGISTRY_URL: ${{ secrets.REGISTRY_URL }}
REGISTRY_USERNAME: ${{ secrets.REGISTRY_USERNAME }}
REGISTRY_PASSWORD: ${{ secrets.REGISTRY_PASSWORD }}
REGISTRY_CONTAINER_NAME: calminer
steps:
- name: Checkout
uses: actions/checkout@v4
- name: Collect workflow metadata
id: meta
shell: bash
run: |
ref_name="${GITHUB_REF_NAME:-${GITHUB_REF##*/}}"
event_name="${GITHUB_EVENT_NAME:-}"
sha="${GITHUB_SHA:-}"
if [ "$ref_name" = "${DEFAULT_BRANCH:-main}" ]; then
echo "on_default=true" >> "$GITHUB_OUTPUT"
else
echo "on_default=false" >> "$GITHUB_OUTPUT"
fi
echo "ref_name=$ref_name" >> "$GITHUB_OUTPUT"
echo "event_name=$event_name" >> "$GITHUB_OUTPUT"
echo "sha=$sha" >> "$GITHUB_OUTPUT"
- name: Set up QEMU and Buildx
uses: docker/setup-buildx-action@v3
- name: Log in to gitea registry
if: ${{ steps.meta.outputs.on_default == 'true' }}
uses: docker/login-action@v3
continue-on-error: true
with:
registry: ${{ env.REGISTRY_URL }}
username: ${{ env.REGISTRY_USERNAME }}
password: ${{ env.REGISTRY_PASSWORD }}
- name: Build and push image
uses: docker/build-push-action@v5
with:
context: .
file: Dockerfile
push: ${{ steps.meta.outputs.on_default == 'true' && steps.meta.outputs.event_name != 'pull_request' && (env.REGISTRY_URL != '' && env.REGISTRY_USERNAME != '' && env.REGISTRY_PASSWORD != '') }}
tags: |
${{ env.REGISTRY_URL }}/allucanget/${{ env.REGISTRY_CONTAINER_NAME }}:latest
${{ env.REGISTRY_URL }}/allucanget/${{ env.REGISTRY_CONTAINER_NAME }}:${{ steps.meta.outputs.sha }}

8
.prettierrc
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@@ -1,8 +0,0 @@
{
"semi": true,
"singleQuote": true,
"trailingComma": "es5",
"printWidth": 80,
"tabWidth": 2,
"useTabs": false
}

95
README.md
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@@ -6,99 +6,6 @@ Focuses on ore mining operations and covering parameters such as capital and ope
The system is designed to help mining companies make informed decisions by simulating various scenarios and analyzing potential outcomes based on stochastic variables.
## Current Features
> [!TIP]
> TODO: Update this section to reflect the current feature set.
| Feature | Category | Description | Status |
| ---------------------- | ----------- | ------------------------------------------------------------------------------------ | ----------- |
| Scenario Management | Core | Manage multiple mining scenarios with independent parameter sets and outputs. | Done |
| Parameter Definition | Core | Define and manage various parameters for each scenario. | Done |
| Cost Tracking | Financial | Capture and analyze capital and operational expenditures. | Done |
| Consumption Tracking | Operational | Record resource consumption tied to scenarios. | Done |
| Production Output | Operational | Store and analyze production metrics such as tonnage, recovery, and revenue drivers. | Done |
| Equipment Management | Operational | Manage equipment inventories and specifications for each scenario. | Done |
| Maintenance Logging | Operational | Log maintenance events and costs associated with equipment. | Started |
| Reporting Dashboard | Analytics | View aggregated statistics and visualizations for scenario outputs. | In Progress |
| Monte Carlo Simulation | Analytics | Run stochastic simulations to assess risk and variability in outcomes. | Started |
| Application Settings | Core | Manage global application settings such as themes and currency options. | Done |
## Key UI/UX Features
- **Unified UI Shell**: Server-rendered templates extend a shared base layout with a persistent left sidebar linking scenarios, parameters, costs, consumption, production, equipment, maintenance, simulations, and reporting views.
- **Modular Frontend Scripts**: Page-specific interactions in `static/js/` modules, keeping templates lean while enabling browser caching and reuse.
## Planned Features
See [Roadmap](docs/roadmap.md) for details on planned features and enhancements.
## Documentation & quickstart
This repository contains detailed developer and architecture documentation in the `docs/` folder.
### Settings overview
The Settings page (`/ui/settings`) lets administrators adjust global theme colors stored in the `application_setting` table. Changes are instantly applied across the UI. Environment variables prefixed with `CALMINER_THEME_` (for example, `CALMINER_THEME_COLOR_PRIMARY`) automatically override individual CSS variables and render as read-only in the form, ensuring deployment-time overrides take precedence while remaining visible to operators.
[Quickstart](docs/quickstart.md) contains developer quickstart, migrations, testing and current status.
Key architecture documents: see [architecture](docs/architecture/README.md) for the arc42-based architecture documentation.
For contributors: the `routes/`, `models/` and `services/` folders contain the primary application code. Tests and E2E specs are in `tests/`.
## Run with Docker
The repository ships with a multi-stage `Dockerfile` that produces a slim runtime image.
### Build container
```bash
docker build -t calminer .
```
### Push to registry
To push the image to a registry, tag it appropriately and push:
```bash
docker tag calminer your-registry/calminer:latest
docker push your-registry/calminer:latest
```
### Run container
To run the container, ensure PostgreSQL is available and set environment variables:
```bash
docker run -p 8000:8000 \
-e DATABASE_HOST=your-postgres-host \
-e DATABASE_PORT=5432 \
-e DATABASE_USER=calminer \
-e DATABASE_PASSWORD=your-password \
-e DATABASE_NAME=calminer_db \
calminer
```
## Development with Docker Compose
For local development, use `docker-compose.yml` which includes the app and PostgreSQL services.
```bash
# Start services
docker-compose up
# Or run in background
docker-compose up -d
# Stop services
docker-compose down
```
The app will be available at `http://localhost:8000`, PostgreSQL at `localhost:5432`.
## CI/CD
CalMiner uses Gitea Actions workflows stored in `.gitea/workflows/`:
- `ci.yml`: Runs on push and PR to main/develop branches. Sets up Python, installs dependencies, runs tests with coverage, and builds the Docker image.
This repository contains only code. See detailed developer and architecture documentation in the [Docs](https://git.allucanget.biz/allucanget/calminer-docs) repository.

35
config/setup_production.env.example
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@@ -1,35 +0,0 @@
# Copy this file to config/setup_production.env and replace values with production secrets
# Container image and runtime configuration
CALMINER_IMAGE=registry.example.com/calminer/api:latest
CALMINER_DOMAIN=calminer.example.com
TRAEFIK_ACME_EMAIL=ops@example.com
CALMINER_API_PORT=8000
UVICORN_WORKERS=4
UVICORN_LOG_LEVEL=info
CALMINER_NETWORK=calminer_backend
API_LIMIT_CPUS=1.0
API_LIMIT_MEMORY=1g
API_RESERVATION_MEMORY=512m
TRAEFIK_LIMIT_CPUS=0.5
TRAEFIK_LIMIT_MEMORY=512m
POSTGRES_LIMIT_CPUS=1.0
POSTGRES_LIMIT_MEMORY=2g
POSTGRES_RESERVATION_MEMORY=1g
# Application database connection
DATABASE_DRIVER=postgresql+psycopg2
DATABASE_HOST=production-db.internal
DATABASE_PORT=5432
DATABASE_NAME=calminer
DATABASE_USER=calminer_app
DATABASE_PASSWORD=ChangeMe123!
DATABASE_SCHEMA=public
# Optional consolidated SQLAlchemy URL (overrides granular settings when set)
# DATABASE_URL=postgresql+psycopg2://calminer_app:ChangeMe123!@production-db.internal:5432/calminer
# Superuser credentials used by scripts/setup_database.py for migrations/seed data
DATABASE_SUPERUSER=postgres
DATABASE_SUPERUSER_PASSWORD=ChangeMeSuper123!
DATABASE_SUPERUSER_DB=postgres

11
config/setup_staging.env.example
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@@ -1,11 +0,0 @@
# Sample environment configuration for staging deployment
DATABASE_HOST=staging-db.internal
DATABASE_PORT=5432
DATABASE_NAME=calminer_staging
DATABASE_USER=calminer_app
DATABASE_PASSWORD=<app-password>
# Admin connection used for provisioning database and roles
DATABASE_SUPERUSER=postgres
DATABASE_SUPERUSER_PASSWORD=<admin-password>
DATABASE_SUPERUSER_DB=postgres

14
config/setup_test.env.example
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@@ -1,14 +0,0 @@
# Sample environment configuration for running scripts/setup_database.py against a test instance
DATABASE_DRIVER=postgresql
DATABASE_HOST=postgres
DATABASE_PORT=5432
DATABASE_NAME=calminer_test
DATABASE_USER=calminer_test
DATABASE_PASSWORD=<test-password>
# optional: specify schema if different from 'public'
#DATABASE_SCHEMA=public
# Admin connection used for provisioning database and roles
DATABASE_SUPERUSER=postgres
DATABASE_SUPERUSER_PASSWORD=<superuser-password>
DATABASE_SUPERUSER_DB=postgres

62
docs/architecture/01_introduction_and_goals.md
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@@ -1,62 +0,0 @@
---
title: "01 — Introduction and Goals"
description: "System purpose, stakeholders, and high-level goals; project introduction and business/technical goals."
status: draft
---
# 01 — Introduction and Goals
## Purpose
CalMiner aims to provide a comprehensive platform for mining project scenario analysis, enabling stakeholders to make informed decisions based on data-driven insights.
## Stakeholders
- **Project Managers**: Require tools for scenario planning and risk assessment.
- **Data Analysts**: Need access to historical data and simulation results for analysis.
- **Executives**: Seek high-level insights and reporting for strategic decision-making.
## High-Level Goals
1. **Comprehensive Scenario Analysis**: Enable users to create and analyze multiple project scenarios to assess risks and opportunities.
2. **Data-Driven Decision Making**: Provide stakeholders with the insights needed to make informed decisions based on simulation results.
3. **User-Friendly Interface**: Ensure the platform is accessible and easy to use for all stakeholders, regardless of technical expertise.
## System Overview
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.
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.
### Runtime Flow
1. Users navigate to form templates or API clients to manage scenarios, parameters, and operational data.
2. FastAPI routers validate payloads with Pydantic models, then delegate to SQLAlchemy sessions for persistence.
3. Simulation runs (placeholder `services/simulation.py`) will consume stored parameters to emit iteration results via `/api/simulations/run`.
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).
5. `templates/Dashboard.html` fetches summaries, renders metric cards, and plots distribution charts with Chart.js for stakeholder review.
### Current implementation status (summary)
- Currency normalization, simulation scaffold, and reporting service exist; see [quickstart](../quickstart.md) for full status and migration instructions.
## MVP Features (migrated)
The following MVP features and priorities were defined during initial planning.
### Prioritized Features
1. **Scenario Creation and Management** (High Priority): Allow users to create, edit, and delete scenarios. Rationale: Core functionality for what-if analysis.
1. **Parameter Input and Validation** (High Priority): Input process parameters with validation. Rationale: Ensures data integrity for simulations.
1. **Monte Carlo Simulation Run** (High Priority): Execute simulations and store results. Rationale: Key differentiator for risk analysis.
1. **Basic Reporting** (Medium Priority): Display NPV, IRR, EBITDA from simulation results. Rationale: Essential for decision-making.
1. **Cost Tracking Dashboard** (Medium Priority): Visualize CAPEX and OPEX. Rationale: Helps monitor expenses.
1. **Consumption Monitoring** (Low Priority): Track resource consumption. Rationale: Useful for optimization.
1. **User Authentication** (Medium Priority): Basic login/logout. Rationale: Security for multi-user access.
1. **Export Results** (Low Priority): Export simulation data to CSV/PDF. Rationale: For external analysis.
### Rationale for Prioritization
- High: Core simulation and scenario features first.
- Medium: Reporting and auth for usability.
- Low: Nice-to-haves after basics.

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docs/architecture/02_architecture_constraints.md
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---
title: '02 — Architecture Constraints'
description: 'Document imposed constraints: technical, organizational, regulatory, and environmental constraints that affect architecture decisions.'
status: draft
---
# 02 — Architecture Constraints
## Constraints Overview
- [Technical Constraints](02_constraints/02_01_technical_constraints.md)
- [Organizational Constraints](02_constraints/02_02_organizational_constraints.md)
- [Regulatory Constraints](02_constraints/02_03_regulatory_constraints.md)
- [Environmental Constraints](02_constraints/02_04_environmental_constraints.md)
- [Performance Constraints](02_constraints/02_05_performance_constraints.md)
## Security Constraints
> e.g., authentication mechanisms, data encryption standards.
## Budgetary Constraints
> e.g., licensing costs, infrastructure budgets.
## Time Constraints
> e.g., project deadlines, release schedules.
## Interoperability Constraints
> e.g., integration with existing systems, third-party services.
## Maintainability Constraints
> e.g., code modularity, documentation standards.
## Usability Constraints
> e.g., user interface design principles, accessibility requirements.
## Data Constraints
> e.g., data storage formats, data retention policies.
## Deployment Constraints
> e.g., deployment environments, cloud provider limitations.
## Testing Constraints
> e.g., testing frameworks, test coverage requirements.
## Localization Constraints
> e.g., multi-language support, regional settings.
## Versioning Constraints
> e.g., API versioning strategies, backward compatibility.
## Monitoring Constraints
> e.g., logging standards, performance monitoring tools.
## Backup and Recovery Constraints
> e.g., data backup frequency, disaster recovery plans.
## Development Constraints
> e.g., coding languages, frameworks, libraries to be used or avoided.
## Collaboration Constraints
> e.g., communication tools, collaboration platforms.
## Documentation Constraints
> e.g., documentation tools, style guides.
## Training Constraints
> e.g., training programs, skill development initiatives.
## Support Constraints
> e.g., support channels, response time expectations.
## Legal Constraints
> e.g., compliance requirements, intellectual property considerations.
## Ethical Constraints
> e.g., ethical considerations in data usage, user privacy.
## Environmental Impact Constraints
> e.g., energy consumption considerations, sustainability goals.
## Innovation Constraints
> e.g., limitations on adopting new technologies, risk tolerance for experimentation.
## Cultural Constraints
> e.g., organizational culture, team dynamics affecting development practices.
## Stakeholder Constraints
> e.g., stakeholder expectations, communication preferences.
## Change Management Constraints
> e.g., processes for handling changes, version control practices.
## Resource Constraints
> e.g., availability of hardware, software, and human resources.
## Process Constraints
> e.g., development methodologies (Agile, Scrum), project management tools.
## Quality Constraints
> e.g., code quality standards, testing requirements.

16
docs/architecture/02_constraints/02_01_technical_constraints.md
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@@ -1,16 +0,0 @@
---
title: '02 — Technical Constraints'
description: 'Technical constraints that affect architecture decisions.'
status: draft
---
# Technical Constraints
> e.g., choice of FastAPI, PostgreSQL, SQLAlchemy, Chart.js, Jinja2 templates.
The architecture of CalMiner is influenced by several technical constraints that shape its design and implementation:
1. **Framework Selection**: The choice of FastAPI as the web framework imposes constraints on how the application handles requests, routing, and middleware. FastAPI's asynchronous capabilities must be leveraged appropriately to ensure optimal performance.
2. **Database Technology**: The use of PostgreSQL as the primary database system dictates the data modeling, querying capabilities, and transaction management strategies. SQLAlchemy ORM is used for database interactions, which requires adherence to its conventions and limitations.
3. **Frontend Technologies**: The decision to use Jinja2 for server-side templating and Chart.js for data visualization influences the structure of the frontend code and the way dynamic content is rendered.
4. **Simulation Logic**: The Monte Carlo simulation logic must be designed to efficiently handle large datasets and perform computations within the constraints of the chosen programming language (Python) and its libraries.

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docs/architecture/02_constraints/02_02_organizational_constraints.md
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@@ -1,18 +0,0 @@
---
title: '02 — Organizational Constraints'
description: 'Organizational constraints that affect architecture decisions.'
status: draft
---
# Organizational Constraints
> e.g., team skillsets, development workflows, CI/CD pipelines.
Restrictions arising from organizational factors include:
1. **Team Expertise**: The development team’s familiarity with FastAPI, SQLAlchemy, and frontend technologies like Jinja2 and Chart.js influences the architecture choices to ensure maintainability and ease of development.
2. **Development Processes**: The adoption of Agile methodologies and CI/CD pipelines (using Gitea Actions) shapes the architecture to support continuous integration, automated testing, and deployment practices.
3. **Collaboration Tools**: The use of specific collaboration and version control tools (e.g., Gitea) affects how code is managed, reviewed, and integrated, impacting the overall architecture and development workflow.
4. **Documentation Standards**: The requirement for comprehensive documentation (as seen in the `docs/` folder) necessitates an architecture that is well-structured and easy to understand for both current and future team members.
5. **Knowledge Sharing**: The need for effective knowledge sharing and onboarding processes influences the architecture to ensure that it is accessible and understandable for new team members.
6. **Resource Availability**: The availability of hardware, software, and human resources within the organization can impose constraints on the architecture, affecting decisions related to scalability, performance, and feature implementation.

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docs/architecture/02_constraints/02_03_regulatory_constraints.md
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@@ -1,17 +0,0 @@
---
title: '02 — Regulatory Constraints'
description: 'Regulatory constraints that affect architecture decisions.'
status: draft
---
# Regulatory Constraints
> e.g., data privacy laws, industry standards.
Regulatory constraints that impact the architecture of CalMiner include:
1. **Data Privacy Compliance**: The architecture must ensure compliance with data privacy regulations such as GDPR or CCPA, which may dictate how user data is collected, stored, and processed.
2. **Industry Standards**: Adherence to industry-specific standards and best practices may influence the design of data models, security measures, and reporting functionalities.
3. **Auditability**: The system may need to incorporate logging and auditing features to meet regulatory requirements, affecting the architecture of data storage and access controls.
4. **Data Retention Policies**: Regulatory requirements regarding data retention and deletion may impose constraints on how long certain types of data can be stored, influencing database design and data lifecycle management.
5. **Security Standards**: Compliance with security standards (e.g., ISO/IEC 27001) may necessitate the implementation of specific security measures, such as encryption, access controls, and vulnerability management, which impact the overall architecture.

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docs/architecture/02_constraints/02_04_environmental_constraints.md
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@@ -1,16 +0,0 @@
---
title: '02 — Environmental Constraints'
description: 'Environmental constraints that affect architecture decisions.'
status: draft
---
# Environmental Constraints
> e.g., deployment environments, cloud provider limitations.
Environmental constraints affecting the architecture include:
1. **Deployment Environments**: The architecture must accommodate various deployment environments (development, testing, production) with differing configurations and resource allocations.
2. **Cloud Provider Limitations**: If deployed on a specific cloud provider, the architecture may need to align with the provider's services, limitations, and best practices, such as using managed databases or specific container orchestration tools.
3. **Containerization**: The use of Docker for containerization imposes constraints on how the application is packaged, deployed, and scaled, influencing the architecture to ensure compatibility with container orchestration platforms.
4. **Scalability Requirements**: The architecture must be designed to scale efficiently based on anticipated load and usage patterns, considering the limitations of the chosen infrastructure.

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docs/architecture/02_constraints/02_05_performance_constraints.md
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@@ -1,14 +0,0 @@
---
title: '02 — Performance Constraints'
description: 'Performance constraints that affect architecture decisions.'
status: draft
---
# Performance Constraints
> e.g., response time requirements, scalability needs.
Current performance constraints include:
1. **Response Time Requirements**: The architecture must ensure that the system can respond to user requests within a specified time frame, which may impact design decisions related to caching, database queries, and API performance.
2. **Scalability Needs**: The system should be able to handle increased load and user traffic without significant degradation in performance, necessitating a scalable architecture that can grow with demand.

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---
title: "03 — Context and Scope"
description: "Describe system context, external actors, and the scope of the architecture."
status: draft
---
# 03 — Context and Scope
## System Context
The CalMiner system operates within the context of mining project management, providing tools for scenario analysis and decision support. It interacts with various data sources, including historical project data and real-time operational metrics.
## External Actors
- **Project Managers**: Utilize the platform for scenario planning and risk assessment.
- **Data Analysts**: Analyze simulation results and derive insights.
- **Executives**: Review high-level reports and dashboards for strategic decision-making.
## Scope of the Architecture
See [Architecture Scope](03_scope/03_01_architecture_scope.md) for details.
## Diagram
```mermaid
sequenceDiagram
participant PM as Project Manager
participant DA as Data Analyst
participant EX as Executive
participant CM as CalMiner System
PM->>CM: Create and manage scenarios
DA->>CM: Analyze simulation results
EX->>CM: Review reports and dashboards
CM->>PM: Provide scenario planning tools
CM->>DA: Deliver analysis insights
CM->>EX: Generate high-level reports
```
This diagram illustrates the key components of the CalMiner system and their interactions with external actors.

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---
title: '03 — Architecture Scope'
description: 'Key areas encompassed by the architecture.'
status: draft
---
# Architecture Scope
The architecture encompasses the following key areas:
1. **Data Ingestion**: Mechanisms for collecting and processing data from various sources.
2. **Data Storage**: Solutions for storing and managing historical and real-time data.
3. **Simulation Engine**: Core algorithms and models for scenario analysis.
3.1. **Modeling Framework**: Tools for defining and managing simulation models.
3.2. **Parameter Management**: Systems for handling input parameters and configurations.
3.3. **Execution Engine**: Infrastructure for running simulations and processing results.
3.4. **Result Storage**: Systems for storing simulation outputs for analysis and reporting.
4. **Financial Reporting**: Tools for generating reports and visualizations based on simulation outcomes.
5. **Risk Assessment**: Frameworks for identifying and evaluating potential project risks.
6. **Profitability Analysis**: Modules for calculating and analyzing project profitability metrics.
7. **User Interface**: Design and implementation of the user-facing components of the system.
8. **Security and Compliance**: Measures to ensure data security and regulatory compliance.
9. **Scalability and Performance**: Strategies for ensuring the system can handle increasing data volumes and user loads.
10. **Integration Points**: Interfaces for integrating with external systems and services.
11. **Monitoring and Logging**: Systems for tracking system performance and user activity.
12. **Maintenance and Support**: Processes for ongoing system maintenance and user support.

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---
title: "04 — Solution Strategy"
description: "High-level solution strategy describing major approaches, technology choices, and trade-offs."
status: draft
---
# 04 — Solution Strategy
This section outlines the high-level solution strategy for implementing the CalMiner system, focusing on major approaches, technology choices, and trade-offs.
## Solution Strategy Overview
- [Client-Server Architecture](04_strategy/04_01_client_server_architecture.md)
- [Technology Choices](04_strategy/04_02_technology_choices.md)
- [Trade-offs](04_strategy/04_03_trade_offs.md)
- [Future Considerations](04_strategy/04_04_future_considerations.md)

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---
title: '04.01 — Client-Server Architecture'
description: 'Details on the client-server architecture of CalMiner.'
---
# 04.01 — Client-Server Architecture
- **Backend**: FastAPI serves as the backend framework, providing RESTful APIs for data management, simulation execution, and reporting. It leverages SQLAlchemy for ORM-based database interactions with PostgreSQL.
- **Frontend**: Server-rendered Jinja2 templates deliver dynamic HTML views, enhanced with Chart.js for interactive data visualizations. This approach balances performance and simplicity, avoiding the complexity of a full SPA.
- **Middleware**: Custom middleware handles JSON validation to ensure data integrity before processing requests.

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---
title: '04.02 — Technology Choices'
description: 'Detailed explanation of technology choices in CalMiner.'
---
# 04.02 — Technology Choices
- **FastAPI**: Chosen for its high performance, ease of use, and modern features like async support and automatic OpenAPI documentation.
- **PostgreSQL**: Selected for its robustness, scalability, and support for complex queries, making it suitable for handling the diverse data needs of mining project management.
- **SQLAlchemy**: Provides a flexible and powerful ORM layer, facilitating database interactions while maintaining code readability and maintainability.
- **Chart.js**: Utilized for its simplicity and effectiveness in rendering interactive charts, enhancing the user experience on the dashboard.
- **Jinja2**: Enables server-side rendering of HTML templates, allowing for dynamic content generation while keeping the frontend lightweight.
- **Pydantic**: Used for data validation and serialization, ensuring that incoming request payloads conform to expected schemas.
- **Docker**: Employed for containerization, ensuring consistent deployment across different environments and simplifying dependency management.
- **Redis**: Used as an in-memory data store to cache frequently accessed data, improving application performance and reducing database load.

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---
title: '04.03 — Trade-offs'
description: 'Discussion of trade-offs made in the CalMiner architecture.'
---
# 04.03 — Trade-offs
- **Server-Rendered vs. SPA**: Opted for server-rendered templates over a single-page application (SPA) to reduce complexity and improve initial load times, at the cost of some interactivity.
- **Synchronous vs. Asynchronous**: While FastAPI supports async operations, the initial implementation focuses on synchronous request handling for simplicity, with plans to introduce async features as needed.
- **Monolithic vs. Microservices**: The initial architecture follows a monolithic approach for ease of development and deployment, with the possibility of refactoring into microservices as the system scales.
- **In-Memory Caching**: Implementing Redis for caching introduces additional infrastructure complexity but significantly enhances performance for read-heavy operations.
- **Database Choice**: PostgreSQL was chosen over NoSQL alternatives due to the structured nature of the data and the need for complex querying capabilities, despite potential scalability challenges.
- **Technology Familiarity**: Selected technologies align with the team's existing skill set to minimize the learning curve and accelerate development, even if some alternatives may offer marginally better performance or features.
- **Extensibility vs. Simplicity**: The architecture is designed to be extensible for future features (e.g., Monte Carlo simulation engine) while maintaining simplicity in the initial implementation to ensure timely delivery of core functionalities.

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---
title: '04.04 — Future Considerations'
description: 'Future considerations for the CalMiner architecture.'
---
# 04.04 — Future Considerations
- **Scalability**: As the user base grows, consider transitioning to a microservices architecture and implementing load balancing strategies.
- **Asynchronous Processing**: Introduce asynchronous task queues (e.g., Celery) for long-running simulations to improve responsiveness.
- **Enhanced Frontend**: Explore the possibility of integrating a frontend framework (e.g., React or Vue.js) for more dynamic user interactions in future iterations.
- **Advanced Analytics**: Plan for integrating advanced analytics and machine learning capabilities to enhance simulation accuracy and reporting insights.
- **Security Enhancements**: Implement robust authentication and authorization mechanisms to protect sensitive data and ensure compliance with industry standards.
- **Continuous Integration/Continuous Deployment (CI/CD)**: Establish CI/CD pipelines to automate testing, building, and deployment processes for faster and more reliable releases.
- **Monitoring and Logging**: Integrate monitoring tools (e.g., Prometheus, Grafana) and centralized logging solutions (e.g., ELK stack) to track application performance and troubleshoot issues effectively.
- **User Feedback Loop**: Implement mechanisms for collecting user feedback to inform future development priorities and improve user experience.
- **Documentation**: Maintain comprehensive documentation for both developers and end-users to facilitate onboarding and effective use of the system.
- **Testing Strategy**: Develop a robust testing strategy, including unit, integration, and end-to-end tests, to ensure code quality and reliability as the system evolves.

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---
title: '05 — Architecture Overview'
description: "This overview complements architecture with a high-level map of CalMiner's module layout and request flow."
status: draft
---
This overview complements [architecture](README.md) with a high-level map of CalMiner's module layout and request flow.
Refer to the detailed architecture chapters in `docs/architecture/`:
- Module map & components: [Building Block View](../05_building_block_view.md)
- Request flow & runtime interactions: [Runtime View](../06_runtime_view.md)
- Simulation roadmap & strategy: [Solution Strategy](../04_solution_strategy.md)

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---
title: '05 — Backend Components'
description: 'Description of the backend components of the CalMiner application.'
status: draft
---
- **FastAPI application** (`main.py`): entry point that configures routers, middleware, and startup/shutdown events.
- **Routers** (`routes/`): modular route handlers for scenarios, parameters, costs, consumption, production, equipment, maintenance, simulations, and reporting. Each router defines RESTful endpoints, request/response schemas, and orchestrates service calls.
- leveraging a shared dependency module (`routes/dependencies.get_db`) for SQLAlchemy session management.
- **Models** (`models/`): SQLAlchemy ORM models representing database tables and relationships, encapsulating domain entities like Scenario, CapEx, OpEx, Consumption, ProductionOutput, Equipment, Maintenance, and SimulationResult.
- **Services** (`services/`): business logic layer that processes data, performs calculations, and interacts with models. Key services include reporting calculations and Monte Carlo simulation scaffolding.
- `services/settings.py`: manages application settings backed by the `application_setting` table, including CSS variable defaults, persistence, and environment-driven overrides that surface in both the API and UI.
- **Database** (`config/database.py`): sets up the SQLAlchemy engine and session management for PostgreSQL interactions.

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---
title: '05 — Frontend Components'
description: 'Description of the frontend components of the CalMiner application.'
status: draft
---
- **Templates** (`templates/`): Jinja2 templates for server-rendered HTML views, extending a shared base layout with a persistent sidebar for navigation.
- **Static Assets** (`static/`): CSS and JavaScript files for styling and interactivity. Shared CSS variables in `static/css/main.css` define the color palette, while page-specific JS modules in `static/js/` handle dynamic behaviors.
- **Reusable partials** (`templates/partials/components.html`): macro library that standardises select inputs, feedback/empty states, and table wrappers so pages remain consistent while keeping DOM hooks stable for existing JavaScript modules.
- `templates/settings.html`: Settings hub that renders theme controls and environment override tables using metadata provided by `routes/ui.py`.
- `static/js/settings.js`: applies client-side validation, form submission, and live CSS updates for theme changes, respecting environment-managed variables returned by the API.

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# Theming
## Overview
CalMiner uses a centralized theming system based on CSS custom properties (variables) to ensure consistent styling across the application. The theme is stored in the database and can be customized through environment variables or the UI settings page.
## Default Theme Settings
The default theme provides a light, professional color palette suitable for business applications. The colors are defined as CSS custom properties and stored in the `application_setting` table with category "theme".
### Color Palette
| CSS Variable | Default Value | Description |
| --------------------------- | ------------------------ | ------------------------ |
| `--color-background` | `#f4f5f7` | Main background color |
| `--color-surface` | `#ffffff` | Surface/card background |
| `--color-text-primary` | `#2a1f33` | Primary text color |
| `--color-text-secondary` | `#624769` | Secondary text color |
| `--color-text-muted` | `#64748b` | Muted text color |
| `--color-text-subtle` | `#94a3b8` | Subtle text color |
| `--color-text-invert` | `#ffffff` | Text on dark backgrounds |
| `--color-text-dark` | `#0f172a` | Dark text for contrast |
| `--color-text-strong` | `#111827` | Strong/bold text |
| `--color-primary` | `#5f320d` | Primary brand color |
| `--color-primary-strong` | `#7e4c13` | Stronger primary |
| `--color-primary-stronger` | `#837c15` | Strongest primary |
| `--color-accent` | `#bff838` | Accent/highlight color |
| `--color-border` | `#e2e8f0` | Default border color |
| `--color-border-strong` | `#cbd5e1` | Strong border color |
| `--color-highlight` | `#eef2ff` | Highlight background |
| `--color-panel-shadow` | `rgba(15, 23, 42, 0.08)` | Subtle shadow |
| `--color-panel-shadow-deep` | `rgba(15, 23, 42, 0.12)` | Deeper shadow |
| `--color-surface-alt` | `#f8fafc` | Alternative surface |
| `--color-success` | `#047857` | Success state color |
| `--color-error` | `#b91c1c` | Error state color |
## Customization
### Environment Variables
Theme colors can be overridden using environment variables with the prefix `CALMINER_THEME_`. For example:
```bash
export CALMINER_THEME_COLOR_BACKGROUND="#000000"
export CALMINER_THEME_COLOR_ACCENT="#ff0000"
```
The variable names are derived by:
1. Removing the `--` prefix
2. Converting to uppercase
3. Replacing `-` with `_`
4. Adding `CALMINER_THEME_` prefix
### Database Storage
Settings are stored in the `application_setting` table with:
- `category`: "theme"
- `value_type`: "color"
- `is_editable`: true
### UI Settings
Users can modify theme colors through the settings page at `/ui/settings`.
## Implementation
The theming system is implemented in:
- `services/settings.py`: Color management and defaults
- `routes/settings.py`: API endpoints for theme settings
- `static/css/main.css`: CSS variable definitions
- `templates/settings.html`: UI for theme customization
## Seeding
Default theme settings are seeded during database setup using the seed script:
```bash
python scripts/seed_data.py --theme
```
Or as part of defaults:
```bash
python scripts/seed_data.py --defaults
```

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---
title: '05 — Middleware & Utilities'
description: 'Description of the middleware and utility components of the CalMiner application.'
status: draft
---
- **Middleware** (`middleware/validation.py`): applies JSON validation before requests reach routers.
- **Testing** (`tests/unit/`): pytest suite covering route and service behavior, including UI rendering checks and negative-path router validation tests to ensure consistent HTTP error semantics. Playwright end-to-end coverage is planned for core smoke flows (dashboard load, scenario inputs, reporting) and will attach in CI once scaffolding is completed.

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---
title: "05 — Building Block View"
description: "Explain the static structure: modules, components, services and their relationships."
status: draft
---
<!-- markdownlint-disable-next-line MD025 -->
# 05 — Building Block View
## Building Block Overview
- [Architecture Overview](05_blocks/05_01_architecture_overview.md)
- [Backend Components](05_blocks/05_02_backend_components.md)
- [Frontend Components](05_blocks/05_03_frontend_components.md)
- [Middleware & Utilities](05_blocks/05_04_middleware_utilities.md)

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---
title: "06 — Runtime View"
description: "Describe runtime aspects: request flows, lifecycle of key interactions, and runtime components."
status: draft
---
# 06 — Runtime View
## Overview
The runtime view focuses on the dynamic behavior of the CalMiner application during execution. It illustrates how various components interact to fulfill user requests, process data, and generate outputs. Key runtime scenarios include scenario management, parameter input handling, cost tracking, consumption tracking, production output recording, equipment management, maintenance logging, Monte Carlo simulations, and reporting.
## Request Flow
1. **User Interaction**: A user interacts with the web application through the UI, triggering actions such as creating a scenario, inputting parameters, or generating reports.
2. **API Request**: The frontend sends HTTP requests (GET, POST, PUT, DELETE) to the appropriate API endpoints defined in the `routes/` directory.
3. **Routing**: The FastAPI framework routes the incoming requests to the corresponding route handlers.
4. **Service Layer**: Route handlers invoke services from the `services/` directory to process the business logic.
5. **Database Interaction**: Services interact with the database via ORM models defined in the `models/` directory to perform CRUD operations.
6. **Response Generation**: After processing, services return data to the route handlers, which format the response (JSON or HTML) and send it back to the frontend.
7. **UI Update**: The frontend updates the UI based on the response, rendering new data or updating existing views.
8. **Reporting Pipeline**: For reporting, data is aggregated from various sources, processed to generate statistics, and presented in the dashboard using Chart.js.
9. **Monte Carlo Simulations**: Stochastic simulations are executed in the backend, generating probabilistic outcomes that are stored temporarily and used for risk analysis in reports.
10. **Error Handling**: Throughout the process, error handling mechanisms ensure that exceptions are caught and appropriate responses are sent back to the user.
Request flow diagram:
```mermaid
sequenceDiagram
participant User
participant Frontend
participant API
participant Service
participant Database
User->>Frontend: Interact with UI
Frontend->>API: Send HTTP Request
API->>Service: Route to Handler
Service->>Database: Perform CRUD Operation
Database-->>Service: Return Data
Service-->>API: Return Processed Data
API-->>Frontend: Send Response
Frontend-->>User: Update UI
participant Reporting
Service->>Reporting: Aggregate Data
Reporting-->>Service: Return Report Data
Service-->>API: Return Report Response
API-->>Frontend: Send Report Data
Frontend-->>User: Render Report
participant Simulation
Service->>Simulation: Execute Monte Carlo Simulation
Simulation-->>Service: Return Simulation Results
Service-->>API: Return Simulation Data
API-->>Frontend: Send Simulation Data
Frontend-->>User: Display Simulation Results
```
## Key Runtime Scenarios
### Scenario Management
1. User accesses the scenario list via the UI.
2. The frontend sends a GET request to `/api/scenarios`.
3. The `ScenarioService` retrieves scenarios from the database.
4. The response is rendered in the UI.
5. For scenario creation, the user submits a form, triggering a POST request to `/api/scenarios`, which the `ScenarioService` processes to create a new scenario in the database.
6. The UI updates to reflect the new scenario.
Scenario management diagram:
```mermaid
sequenceDiagram
participant User
participant Frontend
participant API
participant ScenarioService
participant Database
User->>Frontend: Access Scenario List
Frontend->>API: GET /api/scenarios
API->>ScenarioService: Route to Handler
ScenarioService->>Database: Retrieve Scenarios
Database-->>ScenarioService: Return Scenarios
ScenarioService-->>API: Return Scenario Data
API-->>Frontend: Send Response
Frontend-->>User: Render Scenario List
User->>Frontend: Submit New Scenario Form
Frontend->>API: POST /api/scenarios
API->>ScenarioService: Route to Handler
ScenarioService->>Database: Create New Scenario
Database-->>ScenarioService: Confirm Creation
ScenarioService-->>API: Return New Scenario Data
API-->>Frontend: Send Response
Frontend-->>User: Update UI with New Scenario
```
### Process Parameter Input
1. User navigates to the parameter input form.
2. The frontend fetches existing parameters via a GET request to `/api/parameters`.
3. The `ParameterService` retrieves parameters from the database.
4. The response is rendered in the UI.
5. For parameter updates, the user submits a form, triggering a PUT request to `/api/parameters/:id`, which the `ParameterService` processes to update the parameter in the database.
6. The UI updates to reflect the changes.
Parameter input diagram:
```mermaid
sequenceDiagram
participant User
participant Frontend
participant API
participant ParameterService
participant Database
User->>Frontend: Navigate to Parameter Input Form
Frontend->>API: GET /api/parameters
API->>ParameterService: Route to Handler
ParameterService->>Database: Retrieve Parameters
Database-->>ParameterService: Return Parameters
ParameterService-->>API: Return Parameter Data
API-->>Frontend: Send Response
Frontend-->>User: Render Parameter Form
User->>Frontend: Submit Parameter Update Form
Frontend->>API: PUT /api/parameters/:id
API->>ParameterService: Route to Handler
ParameterService->>Database: Update Parameter
Database-->>ParameterService: Confirm Update
ParameterService-->>API: Return Updated Parameter Data
API-->>Frontend: Send Response
Frontend-->>User: Update UI with Updated Parameter
```
### Cost Tracking
1. User accesses the cost tracking view.
2. The frontend sends a GET request to `/api/costs` to fetch existing cost records.
3. The `CostService` retrieves cost data from the database.
4. The response is rendered in the UI.
5. For cost updates, the user submits a form, triggering a PUT request to `/api/costs/:id`, which the `CostService` processes to update the cost record in the database.
6. The UI updates to reflect the changes.
Cost tracking diagram:
```mermaid
sequenceDiagram
participant User
participant Frontend
participant API
participant CostService
participant Database
User->>Frontend: Access Cost Tracking View
Frontend->>API: GET /api/costs
API->>CostService: Route to Handler
CostService->>Database: Retrieve Cost Records
Database-->>CostService: Return Cost Data
CostService-->>API: Return Cost Data
API-->>Frontend: Send Response
Frontend-->>User: Render Cost Tracking View
User->>Frontend: Submit Cost Update Form
Frontend->>API: PUT /api/costs/:id
API->>CostService: Route to Handler
CostService->>Database: Update Cost Record
Database-->>CostService: Confirm Update
CostService-->>API: Return Updated Cost Data
API-->>Frontend: Send Response
Frontend-->>User: Update UI with Updated Cost Data
```
## Reporting Pipeline and UI Integration
1. **Data Sources**
- Scenario-linked calculations (costs, consumption, production) produce raw figures stored in dedicated tables (`capex`, `opex`, `consumption`, `production_output`).
- Monte Carlo simulations (currently transient) generate arrays of `{ "result": float }` tuples that the dashboard or downstream tooling passes directly to reporting endpoints.
2. **API Contract**
- `POST /api/reporting/summary` accepts a JSON array of result objects and validates shape through `_validate_payload` in `routes/reporting.py`.
- On success it returns a structured payload (`ReportSummary`) containing count, mean, median, min/max, standard deviation, and percentile values, all as floats.
3. **Service Layer**
- `services/reporting.generate_report` converts the sanitized payload into descriptive statistics using Python’s standard library (`statistics` module) to avoid external dependencies.
- The service remains stateless; no database read/write occurs, which keeps summary calculations deterministic and idempotent.
- Extended KPIs (surfaced in the API and dashboard):
- `variance`: population variance computed as the square of the population standard deviation.
- `percentile_5` and `percentile_95`: lower and upper tail interpolated percentiles for sensitivity bounds.
- `value_at_risk_95`: 5th percentile threshold representing the minimum outcome within a 95% confidence band.
- `expected_shortfall_95`: mean of all outcomes at or below the `value_at_risk_95`, highlighting tail exposure.
4. **UI Consumption**
- `templates/Dashboard.html` posts the user-provided dataset to the summary endpoint, renders metric cards for each field, and charts the distribution using Chart.js.
- `SUMMARY_FIELDS` now includes variance, 5th/10th/90th/95th percentiles, and tail-risk metrics (VaR/Expected Shortfall at 95%); tooltip annotations surface the tail metrics alongside the percentile line chart.
- Error handling surfaces HTTP failures inline so users can address malformed JSON or backend availability issues without leaving the page.
Reporting pipeline diagram:
```mermaid
sequenceDiagram
participant User
participant Frontend
participant API
participant ReportingService
User->>Frontend: Input Data for Reporting
Frontend->>API: POST /api/reporting/summary
API->>ReportingService: Route to Handler
ReportingService->>ReportingService: Validate Payload
ReportingService->>ReportingService: Compute Statistics
ReportingService-->>API: Return Report Summary
API-->>Frontend: Send Report Summary
Frontend-->>User: Render Report Metrics and Charts
```
## Monte Carlo Simulation Execution
1. User initiates a Monte Carlo simulation via the UI.
2. The frontend sends a POST request to `/api/simulations/run` with simulation parameters.
3. The `SimulationService` executes the Monte Carlo logic, generating stochastic results.
4. The results are temporarily stored and returned to the frontend.
5. The UI displays the simulation results and allows users to trigger reporting based on these outcomes.
6. The reporting pipeline processes the simulation results as described above.
7. Error handling ensures that any issues during simulation execution are communicated back to the user.
8. Monte Carlo simulation diagram:
```mermaid
sequenceDiagram
participant User
participant Frontend
participant API
participant SimulationService
User->>Frontend: Input Simulation Parameters
Frontend->>API: POST /api/simulations/run
API->>SimulationService: Route to Handler
SimulationService->>SimulationService: Execute Monte Carlo Logic
SimulationService-->>API: Return Simulation Results
API-->>Frontend: Send Simulation Results
Frontend-->>User: Render Simulation Results
```
## Error Handling
Throughout the runtime processes, error handling mechanisms are implemented to catch exceptions and provide meaningful feedback to users. Common error scenarios include:
- Invalid input data
- Database connection issues
- Simulation execution errors
- Reporting calculation failures
- API endpoint unavailability
- Timeouts during long-running operations
- Unauthorized access attempts
- Data validation failures
- Resource not found errors
Error handling diagram:
```mermaid
sequenceDiagram
participant User
participant Frontend
participant API
participant Service
User->>Frontend: Perform Action
Frontend->>API: Send Request
API->>Service: Route to Handler
Service->>Service: Process Request
alt Success
Service-->>API: Return Data
API-->>Frontend: Send Response
Frontend-->>User: Update UI
else Error
Service-->>API: Return Error
API-->>Frontend: Send Error Response
Frontend-->>User: Display Error Message
end
```

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# Testing, CI and Quality Assurance
This chapter centralizes the project's testing strategy, CI configuration, and quality targets.
## Overview
CalMiner uses a combination of unit, integration, and end-to-end tests to ensure quality.
### Frameworks
- Backend: pytest for unit and integration tests.
- Frontend: pytest with Playwright for E2E tests.
- Database: pytest fixtures with psycopg2 for DB tests.
### Test Types
- Unit Tests: Test individual functions/modules.
- Integration Tests: Test API endpoints and DB interactions.
- E2E Tests: Playwright for full user flows.
### CI/CD
- Use Gitea Actions for CI/CD; workflows live under `.gitea/workflows/`.
- `ci.yml` runs on push and pull requests to `main` and `develop` branches. It provisions a temporary PostgreSQL 15 service, sets up Python 3.11, installs dependencies from `requirements.txt` and `requirements-test.txt`, runs pytest with coverage on all tests, and builds the Docker image.
- Run tests on pull requests to shared branches; enforce coverage target ≥80% (pytest-cov).
### Running Tests
- Unit: `pytest tests/unit/`
- E2E: `pytest tests/e2e/`
- All: `pytest`
### Test Directory Structure
Organize tests under the `tests/` directory mirroring the application structure:
```text
tests/
unit/
test_<module>.py
e2e/
test_<flow>.py
fixtures/
conftest.py
```
### Fixtures and Test Data
- Define reusable fixtures in `tests/fixtures/conftest.py`.
- Use temporary in-memory databases or isolated schemas for DB tests.
- Load sample data via fixtures for consistent test environments.
- Leverage the `seeded_ui_data` fixture in `tests/unit/conftest.py` to populate scenarios with related cost, maintenance, and simulation records for deterministic UI route checks.
### E2E (Playwright) Tests
The E2E test suite, located in `tests/e2e/`, uses Playwright to simulate user interactions in a live browser environment. These tests are designed to catch issues in the UI, frontend-backend integration, and overall application flow.
#### Fixtures
- `live_server`: A session-scoped fixture that launches the FastAPI application in a separate process, making it accessible to the browser.
- `playwright_instance`, `browser`, `page`: Standard `pytest-playwright` fixtures for managing the Playwright instance, browser, and individual pages.
#### Smoke Tests
- UI Page Loading: `test_smoke.py` contains a parameterized test that systematically navigates to all UI routes to ensure they load without errors, have the correct title, and display a primary heading.
- Form Submissions: Each major form in the application has a corresponding test file (e.g., `test_scenarios.py`, `test_costs.py`) that verifies: page loads, create item by filling the form, success message, and UI updates.
### Running E2E Tests
To run the Playwright tests:
```bash
pytest tests/e2e/
```
To run headed mode:
```bash
pytest tests/e2e/ --headed
```
### Mocking and Dependency Injection
- Use `unittest.mock` to mock external dependencies.
- Inject dependencies via function parameters or FastAPI's dependency overrides in tests.
### Code Coverage
- Install `pytest-cov` to generate coverage reports.
- Run with coverage: `pytest --cov --cov-report=term` (use `--cov-report=html` when visualizing hotspots).
- Target 95%+ overall coverage. Focus on historically low modules: `services/simulation.py`, `services/reporting.py`, `middleware/validation.py`, and `routes/ui.py`.
- Latest snapshot (2025-10-21): `pytest --cov=. --cov-report=term-missing` returns **91%** overall coverage.
### CI Integration
`test.yml` encapsulates the steps below:
- Check out the repository and set up Python 3.10.
- Configure the runner's apt proxy (if available), install project dependencies (requirements + test extras), and download Playwright browsers.
- Run `pytest` (extend with `--cov` flags when enforcing coverage).
> The pip cache step is temporarily disabled in `test.yml` until the self-hosted cache service is exposed (see `docs/ci-cache-troubleshooting.md`).
`build-and-push.yml` adds:
- Registry login using repository secrets.
- Docker image build/push with GHA cache storage (`cache-from/cache-to` set to `type=gha`).
`deploy.yml` handles:
- SSH into the deployment host.
- Pull the tagged image from the registry.
- Stop, remove, and relaunch the `calminer` container exposing port 8000.
When adding new workflows, mirror this structure to ensure secrets, caching, and deployment steps remain aligned with the production environment.
## Workflow Optimization Opportunities
### `test.yml`
- Run the apt-proxy setup once via a composite action or preconfigured runner image if additional matrix jobs are added.
- Collapse dependency installation into a single `pip install -r requirements-test.txt` call (includes base requirements) once caching is restored.
- Investigate caching or pre-baking Playwright browser binaries to eliminate >650 MB cold downloads per run.
### `build-and-push.yml`
- Skip QEMU setup or explicitly constrain Buildx to linux/amd64 to reduce startup time.
- Enable `cache-from` / `cache-to` settings (registry or `type=gha`) to reuse Docker build layers between runs.
### `deploy.yml`
- Extract deployment script into a reusable shell script or compose file to minimize inline secrets and ease multi-environment scaling.
- Add a post-deploy health check (e.g., `curl` readiness probe) before declaring success.
### Priority Overview
1. Restore shared caching for Python wheels and Playwright browsers once infrastructure exposes the cache service (highest impact on runtime and bandwidth; requires coordination with CI owners).
2. Enable Docker layer caching in `build-and-push.yml` to shorten build cycles (medium effort, immediate benefit to release workflows).
3. Add post-deploy health verification to `deploy.yml` (low effort, improves confidence in automation).
4. Streamline redundant setup steps in `test.yml` (medium effort once cache strategy is in place; consider composite actions or base image updates).
### Setup Consolidation Opportunities
- `Run Tests` matrix jobs each execute the apt proxy configuration, pip installs, database wait, and setup scripts. A composite action or shell script wrapper could centralize these routines and parameterize target-specific behavior (unit vs e2e) to avoid copy/paste maintenance as additional jobs (lint, type check) are introduced.
- Both the test and build workflows perform a `checkout` step; while unavoidable per workflow, shared git submodules or sparse checkout rules could be encapsulated in a composite action to keep options consistent.
- The database setup script currently runs twice (dry-run and live) for every matrix leg. Evaluate whether the dry-run remains necessary once migrations stabilize; if retained, consider adding an environment variable toggle to skip redundant seed operations for read-only suites (e.g., lint).
### Proposed Shared Setup Action
- Location: `.gitea/actions/setup-python-env/action.yml` (composite action).
- Inputs:
- `python-version` (default `3.10`): forwarded to `actions/setup-python`.
- `install-playwright` (default `false`): when `true`, run `python -m playwright install --with-deps`.
- `install-requirements` (default `requirements.txt requirements-test.txt`): space-delimited list pip installs iterate over.
- `run-db-setup` (default `true`): toggles database wait + setup scripts.
- `db-dry-run` (default `true`): controls whether the dry-run invocation executes.
- Steps encapsulated:
1. Set up Python via `actions/setup-python@v5` using provided version.
2. Configure apt proxy via shared shell snippet (with graceful fallback when proxy offline).
3. Iterate over requirement files and execute `pip install -r <file>`.
4. If `install-playwright == true`, install browsers.
5. If `run-db-setup == true`, run the wait-for-Postgres python snippet and call `scripts/setup_database.py`, honoring `db-dry-run` toggle.
- Usage sketch (in `test.yml`):
```yaml
- name: Prepare Python environment
uses: ./.gitea/actions/setup-python-env
with:
install-playwright: ${{ matrix.target == 'e2e' }}
db-dry-run: true
```
- Benefits: centralizes proxy logic and dependency installs, reduces duplication across matrix jobs, and keeps future lint/type-check jobs lightweight by disabling database setup.
- Implementation status: action available at `.gitea/actions/setup-python-env` and consumed by `test.yml`; extend to additional workflows as they adopt the shared routine.
- Obsolete steps removed: individual apt proxy, dependency install, Playwright, and database setup commands pruned from `test.yml` once the composite action was integrated.
## CI Owner Coordination Notes
### Key Findings
- Self-hosted runner: ASUS System Product Name chassis with AMD Ryzen 7 7700X (8 physical cores / 16 threads) and 63.2 GB usable RAM; `act_runner` configuration not overridden, so only one workflow job runs concurrently today.
- Unit test matrix job: completes 117 pytest cases in roughly 4.1 seconds after Postgres spins up; Docker services consume ~150 MB for `postgres:16-alpine`, with minimal sustained CPU load once tests begin.
- End-to-end matrix job: `pytest tests/e2e` averages 21‑22 seconds of execution, but a cold run downloads ~179 MB of apt packages plus ~470 MB of Playwright browser bundles (Chromium, Firefox, WebKit, FFmpeg), exceeding 650 MB network transfer and adding several gigabytes of disk writes if caches are absent.
- Both jobs reuse existing Python package caches when available; absent a shared cache service, repeated Playwright installs remain the dominant cost driver for cold executions.
### Open Questions
- Can we raise the runner concurrency above the default single job, or provision an additional runner, so the test matrix can execute without serializing queued workflows?
- Is there a central cache or artifact service available for Python wheels and Playwright browser bundles to avoid ~650 MB downloads on cold starts?
- Are we permitted to bake Playwright browsers into the base runner image, or should we pursue a shared cache/proxy solution instead?
### Outreach Draft
```text
Subject: CalMiner CI parallelization support
Hi <CI Owner>,
We recently updated the CalMiner test workflow to fan out unit and Playwright E2E suites in parallel. While validating the change, we gathered the following:
- Runner host: ASUS System Product Name with AMD Ryzen 7 7700X (8 cores / 16 threads), ~63 GB RAM, default `act_runner` concurrency (1 job at a time).
- Unit job finishes in ~4.1 s once Postgres is ready; light CPU and network usage.
- E2E job finishes in ~22 s, but a cold run pulls ~179 MB of apt packages plus ~470 MB of Playwright browser payloads (>650 MB download, several GB disk writes) because we do not have a shared cache yet.
To move forward, could you help with the following?
1. Confirm whether we can raise the runner concurrency limit or provision an additional runner so parallel jobs do not queue behind one another.
2. Let us know if a central cache (Artifactory, Nexus, etc.) is available for Python wheels and Playwright browser bundles, or if we should consider baking the browsers into the runner image instead.
3. Share any guidance on preferred caching or proxy solutions for large binary installs on self-hosted runners.
Once we have clarity, we can finalize the parallel rollout and update the documentation accordingly.
Thanks,
<Your Name>
```

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# Database Deployment
## Migrations & Baseline
A consolidated baseline migration (`scripts/migrations/000_base.sql`) captures all schema changes required for a fresh installation. The script is idempotent: it creates the `currency` and `measurement_unit` reference tables, provisions the `application_setting` store for configurable UI/system options, ensures consumption and production records expose unit metadata, and enforces the foreign keys used by CAPEX and OPEX.
Configure granular database settings in your PowerShell session before running migrations:
```powershell
$env:DATABASE_DRIVER = 'postgresql'
$env:DATABASE_HOST = 'localhost'
$env:DATABASE_PORT = '5432'
$env:DATABASE_USER = 'calminer'
$env:DATABASE_PASSWORD = 's3cret'
$env:DATABASE_NAME = 'calminer'
$env:DATABASE_SCHEMA = 'public'
python scripts/setup_database.py --run-migrations --seed-data --dry-run
python scripts/setup_database.py --run-migrations --seed-data
```
The dry-run invocation reports which steps would execute without making changes. The live run applies the baseline (if not already recorded in `schema_migrations`) and seeds the reference data relied upon by the UI and API.
> ℹ️ When `--seed-data` is supplied without `--run-migrations`, the bootstrap script automatically applies any pending SQL migrations first so the `application_setting` table (and future settings-backed features) are present before seeding.
>
> ℹ️ The application still accepts `DATABASE_URL` as a fallback if the granular variables are not set.
## Database bootstrap workflow
Provision or refresh a database instance with `scripts/setup_database.py`. Populate the required environment variables (an example lives at `config/setup_test.env.example`) and run:
```powershell
# Load test credentials (PowerShell)
Get-Content .\config\setup_test.env.example |
ForEach-Object {
if ($_ -and -not $_.StartsWith('#')) {
$name, $value = $_ -split '=', 2
Set-Item -Path Env:$name -Value $value
}
}
# Dry-run to inspect the planned actions
python scripts/setup_database.py --ensure-database --ensure-role --ensure-schema --initialize-schema --run-migrations --seed-data --dry-run -v
# Execute the full workflow
python scripts/setup_database.py --ensure-database --ensure-role --ensure-schema --initialize-schema --run-migrations --seed-data -v
```
Typical log output confirms:
- Admin and application connections succeed for the supplied credentials.
- Database and role creation are idempotent (`already present` when rerun).
- SQLAlchemy metadata either reports missing tables or `All tables already exist`.
- Migrations list pending files and finish with `Applied N migrations` (a new database reports `Applied 1 migrations` for `000_base.sql`).
After a successful run the target database contains all application tables plus `schema_migrations`, and that table records each applied migration file. New installations only record `000_base.sql`; upgraded environments retain historical entries alongside the baseline.
### Seeding reference data
`scripts/seed_data.py` provides targeted control over the baseline datasets when the full setup script is not required:
```powershell
python scripts/seed_data.py --currencies --units --dry-run
python scripts/seed_data.py --currencies --units
```
The seeder upserts the canonical currency catalog (`USD`, `EUR`, `CLP`, `RMB`, `GBP`, `CAD`, `AUD`) using ASCII-safe symbols (`USD$`, `EUR`, etc.) and the measurement units referenced by the UI (`tonnes`, `kilograms`, `pounds`, `liters`, `cubic_meters`, `kilowatt_hours`). The setup script invokes the same seeder when `--seed-data` is provided and verifies the expected rows afterward, warning if any are missing or inactive.
### Rollback guidance
`scripts/setup_database.py` now tracks compensating actions when it creates the database or application role. If a later step fails, the script replays those rollback actions (dropping the newly created database or role and revoking grants) before exiting. Dry runs never register rollback steps and remain read-only.
If the script reports that some rollback steps could not complete—for example because a connection cannot be established—rerun the script with `--dry-run` to confirm the desired end state and then apply the outstanding cleanup manually:
```powershell
python scripts/setup_database.py --ensure-database --ensure-role --dry-run -v
# Manual cleanup examples when automation cannot connect
psql -d postgres -c "DROP DATABASE IF EXISTS calminer"
psql -d postgres -c "DROP ROLE IF EXISTS calminer"
```
After a failure and rollback, rerun the full setup once the environment issues are resolved.

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@@ -1,152 +0,0 @@
# Gitea Action Runner Setup
This guide describes how to provision, configure, and maintain self-hosted runners for CalMiner's Gitea-based CI/CD pipelines.
## 1. Purpose and Scope
- Explain the role runners play in executing GitHub Actions–compatible workflows inside our private Gitea instance.
- Define supported environments (Windows hosts running Docker for Linux containers today, Alpine or other Linux variants as future additions).
- Provide repeatable steps so additional runners can be brought online quickly and consistently.
## 2. Prerequisites
- **Hardware**: Minimum 8 vCPU, 16 GB RAM, and 50 GB free disk. For Playwright-heavy suites, plan for ≥60 GB free to absorb browser caches.
- **Operating system**: Current runner uses Windows 11 Pro (10.0.26100, 64-bit). Linux instructions mirror the same flow; see section 7 for Alpine specifics.
- **Container engine**: Docker Desktop (Windows) or Docker Engine (Linux) with pull access to `docker.gitea.com/runner-images` and `postgres:16-alpine`.
- **Dependencies**: `curl`, `tar`, PowerShell 7+ (Windows), or standard GNU utilities (Linux) to unpack releases.
- **Gitea access**: Repository admin or site admin token with permission to register self-hosted runners (`Settings → Runners → New Runner`).
### Current Runner Inventory (October 2025)
- Hostname `DESKTOP-GLB3A15`; ASUS System Product Name chassis with AMD Ryzen 7 7700X (8C/16T) and ~63 GB usable RAM.
- Windows 11 Pro 10.0.26100 (64-bit) hosting Docker containers for Ubuntu-based job images.
- `act_runner` version `v0.2.13`; no `act_runner.yaml` present, so defaults apply (single concurrency, no custom labels beyond registration).
- Registered against `http://192.168.88.30:3000` with labels:
- `ubuntu-latest:docker://docker.gitea.com/runner-images:ubuntu-latest`
- `ubuntu-24.04:docker://docker.gitea.com/runner-images:ubuntu-24.04`
- `ubuntu-22.04:docker://docker.gitea.com/runner-images:ubuntu-22.04`
- Runner metadata stored in `.runner`; removing this file forces re-registration and should only be done intentionally.
## 3. Runner Installation
### 3.1 Download and Extract
```powershell
$runnerVersion = "v0.2.13"
$downloadUrl = "https://gitea.com/gitea/act_runner/releases/download/$runnerVersion/act_runner_${runnerVersion}_windows_amd64.zip"
Invoke-WebRequest -Uri $downloadUrl -OutFile act_runner.zip
Expand-Archive act_runner.zip -DestinationPath C:\Tools\act-runner -Force
```
For Linux, download the `linux_amd64.tar.gz` artifact and extract with `tar -xzf` into `/opt/act-runner`.
### 3.2 Configure Working Directory
```powershell
Set-Location C:\Tools\act-runner
New-Item -ItemType Directory -Path logs -Force | Out-Null
```
Ensure the directory is writable by the service account that will execute the runner.
### 3.3 Register With Gitea
1. In Gitea, navigate to the repository or organization **Settings → Runners → New Runner**.
2. Copy the registration token and instance URL.
3. Execute the registration wizard:
```powershell
.\act_runner.exe register --instance http://192.168.88.30:3000 --token <TOKEN> --labels "ubuntu-latest:docker://docker.gitea.com/runner-images:ubuntu-latest" "ubuntu-24.04:docker://docker.gitea.com/runner-images:ubuntu-24.04" "ubuntu-22.04:docker://docker.gitea.com/runner-images:ubuntu-22.04"
```
Linux syntax is identical using `./act_runner register`.
This command populates `.runner` with the runner ID, UUID, and labels.
## 4. Service Configuration
### 4.1 Windows Service
Act Runner provides a built-in service helper:
```powershell
.\act_runner.exe install
.\act_runner.exe start
```
The service runs under `LocalSystem` by default. Use `.\act_runner.exe install --user <DOMAIN\User> --password <Secret>` if isolation is required.
### 4.2 Linux systemd Unit
Create `/etc/systemd/system/act-runner.service`:
```ini
[Unit]
Description=Gitea Act Runner
After=docker.service
Requires=docker.service
[Service]
WorkingDirectory=/opt/act-runner
ExecStart=/opt/act-runner/act_runner daemon
Restart=always
RestartSec=10
Environment="HTTP_PROXY=http://apt-cacher:3142" "HTTPS_PROXY=http://apt-cacher:3142"
[Install]
WantedBy=multi-user.target
```
Enable and start:
```bash
sudo systemctl daemon-reload
sudo systemctl enable --now act-runner.service
```
### 4.3 Environment Variables and Proxy Settings
- Configure `HTTP_PROXY`, `HTTPS_PROXY`, and their lowercase variants to leverage the shared apt cache (`http://apt-cacher:3142`).
- Persist Docker registry credentials (for `docker.gitea.com`) in the service user profile using `docker login`; workflows rely on cached authentication for builds.
- To expose pip caching once infrastructure is available, set `PIP_INDEX_URL` and `PIP_EXTRA_INDEX_URL` at the service level.
### 4.4 Logging
- Windows services write to `%ProgramData%\act-runner\logs`. Redirect or forward to centralized logging if required.
- Linux installations can leverage `journalctl -u act-runner` and logrotate rules for `/opt/act-runner/logs`.
## 5. Network and Security
- **Outbound**: Allow HTTPS traffic to the Gitea instance, Docker Hub, docker.gitea.com, npm (for Playwright), PyPI, and the apt cache proxy.
- **Inbound**: No inbound ports are required; block unsolicited traffic on internet-facing hosts.
- **Credentials**: Store deployment SSH keys and registry credentials in Gitea secrets, not on the runner host.
- **Least privilege**: Run the service under a dedicated account with access only to Docker and required directories.
## 6. Maintenance and Upgrades
- **Version checks**: Monitor `https://gitea.com/gitea/act_runner/releases` and schedule upgrades quarterly or when security fixes drop.
- **Upgrade procedure**: Stop the service, replace `act_runner` binary, restart. Re-registration is not required as long as `.runner` remains intact.
- **Health checks**: Periodically validate connectivity with `act_runner exec --detect-event -W .gitea/workflows/test.yml` and inspect workflow durations to catch regressions.
- **Cleanup**: Purge Docker images and volumes monthly (`docker system prune -af`) to reclaim disk space.
- **Troubleshooting**: Use `act_runner diagnose` (if available in newer versions) or review logs for repeated failures; reset by stopping the service, deleting stale job containers (`docker ps -a`), and restarting.
## 7. Alpine-based Runner Notes
- Install baseline packages: `apk add docker bash curl coreutils nodejs npm python3 py3-pip libstdc++`.
- Playwright requirements: add `apk add chromium nss freetype harfbuzz ca-certificates mesa-gl` or install Playwright browsers via `npx playwright install --with-deps` using the Alpine bundle.
- Musl vs glibc: When workflows require glibc (e.g., certain Python wheels), include `apk add gcompat` or base images on `frolvlad/alpine-glibc`.
- Systemd alternative: Use `rc-service` or `supervisord` to manage `act_runner daemon` on Alpine since systemd is absent.
- Storage: Mount `/var/lib/docker` to persistent storage if running inside a VM, ensuring browser downloads and layer caches survive restarts.
## 8. Appendix
- **Troubleshooting checklist**:
- Verify Docker daemon is healthy (`docker info`).
- Confirm `.runner` file exists and lists expected labels.
- Re-run `act_runner register` if the runner no longer appears in Gitea.
- Check proxy endpoints are reachable before jobs start downloading dependencies.
- **Related documentation**:
- `docs/architecture/07_deployment/07_01_testing_ci.md` (workflow architecture and CI owner coordination).
- `docs/ci-cache-troubleshooting.md` (pip caching status and known issues).
- `.gitea/actions/setup-python-env/action.yml` (shared job preparation logic referenced in workflows).

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@@ -1,165 +0,0 @@
---
title: '07 — Deployment View'
description: 'Describe deployment topology, infrastructure components, and environments (dev/stage/prod).'
status: draft
---
<!-- markdownlint-disable-next-line MD025 -->
# 07 — Deployment View
## Deployment Topology
The CalMiner application is deployed using a multi-tier architecture consisting of the following layers:
1. **Client Layer**: This layer consists of web browsers that interact with the application through a user interface rendered by Jinja2 templates and enhanced with JavaScript (Chart.js for dashboards).
2. **Web Application Layer**: This layer hosts the FastAPI application, which handles API requests, business logic, and serves HTML templates. It communicates with the database layer for data persistence.
3. **Database Layer**: This layer consists of a PostgreSQL database that stores all application data, including scenarios, parameters, costs, consumption, production outputs, equipment, maintenance logs, and simulation results.
```mermaid
graph TD
A[Client Layer] --> B[Web Application Layer]
B --> C[Database Layer]
```
## Infrastructure Components
The infrastructure components for the application include:
- **Reverse Proxy (optional)**: An Nginx or Apache server can be used as a reverse proxy.
- **Containerization**: Docker images are generated via the repository `Dockerfile`, using a multi-stage build to keep the final runtime minimal.
- **CI/CD Pipeline**: Automated pipelines (Gitea Actions) run tests, build/push Docker images, and trigger deployments.
- **Gitea Actions Workflows**: Located under `.gitea/workflows/`, these workflows handle testing, building, pushing, and deploying the application.
- **Gitea Action Runners**: Self-hosted runners execute the CI/CD workflows.
- **Testing and Continuous Integration**: Automated tests ensure code quality before deployment, also documented in [Testing & CI](07_deployment/07_01_testing_ci.md.md).
- **Docker Infrastructure**: Docker is used to containerize the application for consistent deployment across environments.
- **Portainer**: Production deployment environment for managing Docker containers.
- **Web Server**: Hosts the FastAPI application and serves API endpoints.
- **Database Server**: PostgreSQL database for persisting application data.
- **Static File Server**: Serves static assets such as CSS, JavaScript, and image files.
- **Cloud Infrastructure (optional)**: The application can be deployed on cloud platforms.
```mermaid
graph TD
G[Git Repository] --> C[CI/CD Pipeline]
C --> GAW[Gitea Action Workflows]
GAW --> GAR[Gitea Action Runners]
GAR --> T[Testing]
GAR --> CI[Continuous Integration]
T --> G
CI --> G
W[Web Server] --> DB[Database Server]
RP[Reverse Proxy] --> W
I((Internet)) <--> RP
PO[Containerization] --> W
C[CI/CD Pipeline] --> PO
W --> S[Static File Server]
S --> RP
PO --> DB
PO --> S
```
## Environments
The application can be deployed in multiple environments to support development, testing, and production.
```mermaid
graph TD
R[Repository] --> DEV[Development Environment]
R[Repository] --> TEST[Testing Environment]
R[Repository] --> PROD[Production Environment]
DEV --> W_DEV[Web Server - Dev]
DEV --> DB_DEV[Database Server - Dev]
TEST --> W_TEST[Web Server - Test]
TEST --> DB_TEST[Database Server - Test]
PROD --> W_PROD[Web Server - Prod]
PROD --> DB_PROD[Database Server - Prod]
```
### Development Environment
The development environment is set up for local development and testing. It includes:
- Local PostgreSQL instance (docker compose recommended, script available at `docker-compose.postgres.yml`)
- FastAPI server running in debug mode
`docker-compose.dev.yml` encapsulates this topology:
- `api` service mounts the repository for live reloads (`uvicorn --reload`) and depends on the database health check.
- `db` service uses the Debian-based `postgres:16` image with UTF-8 locale configuration and persists data in `pg_data_dev`.
- A shared `calminer_backend` bridge network keeps traffic contained; ports 8000/5432 are published for local tooling.
See [docs/quickstart.md](../quickstart.md#compose-driven-development-stack) for command examples and volume maintenance tips.
### Testing Environment
The testing environment is set up for automated testing and quality assurance. It includes:
- Staging PostgreSQL instance
- FastAPI server running in testing mode
- Automated test suite (e.g., pytest) for running unit and integration tests
`docker-compose.test.yml` provisions an ephemeral CI-like stack:
- `tests` service builds the application image, installs `requirements-test.txt`, runs the database setup script (dry-run + apply), then executes pytest.
- `api` service is available on port 8001 for manual verification against the test database.
- `postgres` service seeds a disposable Postgres 16 instance with health checks and named volumes (`pg_data_test`, `pip_cache_test`).
Typical commands mirror the CI workflow (`docker compose -f docker-compose.test.yml run --rm tests`); the [quickstart](../quickstart.md#compose-driven-test-stack) lists variations and teardown steps.
### Production Environment
The production environment is set up for serving live traffic and includes:
- Production PostgreSQL instance
- FastAPI server running in production mode
- Load balancer (Traefik) for distributing incoming requests
- Monitoring and logging tools for tracking application performance
#### Production docker compose topology
- `docker-compose.prod.yml` defines the runtime topology for operator-managed deployments.
- `api` service runs the FastAPI image with resource limits (`API_LIMIT_CPUS`, `API_LIMIT_MEMORY`) and a `/health` probe consumed by Traefik and the Compose health check.
- `traefik` service (enabled via the `reverse-proxy` profile) terminates TLS using the ACME resolver configured by `TRAEFIK_ACME_EMAIL` and routes `CALMINER_DOMAIN` traffic to the API.
- `postgres` service (enabled via the `local-db` profile) exists for edge deployments without managed PostgreSQL and persists data in the `pg_data_prod` volume while mounting `./backups` for operator snapshots.
- All services join the configurable `CALMINER_NETWORK` (defaults to `calminer_backend`) to keep traffic isolated from host networks.
Deployment workflow:
1. Copy `config/setup_production.env.example` to `config/setup_production.env` and populate domain, registry image tag, database credentials, and resource budgets.
2. Launch the stack with `docker compose --env-file config/setup_production.env -f docker-compose.prod.yml --profile reverse-proxy up -d` (append `--profile local-db` when hosting Postgres locally).
3. Run database migrations and seeding using `docker compose --env-file config/setup_production.env -f docker-compose.prod.yml run --rm api python scripts/setup_database.py --run-migrations --seed-data`.
4. Monitor container health via `docker compose -f docker-compose.prod.yml ps` or Traefik dashboards; the API health endpoint returns `{ "status": "ok" }` when ready.
5. Shut down with `docker compose -f docker-compose.prod.yml down` (volumes persist unless `-v` is supplied).
## Containerized Deployment Flow
The Docker-based deployment path aligns with the solution strategy documented in [Solution Strategy](04_solution_strategy.md) and the CI practices captured in [Testing & CI](07_deployment/07_01_testing_ci.md.md).
### Image Build
- The multi-stage `Dockerfile` installs dependencies in a builder layer (including system compilers and Python packages) and copies only the required runtime artifacts to the final image.
- Build arguments are minimal; database configuration is supplied at runtime via granular variables (`DATABASE_DRIVER`, `DATABASE_HOST`, `DATABASE_PORT`, `DATABASE_USER`, `DATABASE_PASSWORD`, `DATABASE_NAME`, optional `DATABASE_SCHEMA`). Secrets and configuration should be passed via environment variables or an orchestrator.
- The resulting image exposes port `8000` and starts `uvicorn main:app` (see main [README.md](../../README.md)).
### Runtime Environment
- For single-node deployments, run the container alongside PostgreSQL/Redis using Docker Compose or an equivalent orchestrator.
- A reverse proxy (Traefik) terminates TLS and forwards traffic to the container on port `8000`.
- Migrations must be applied prior to rolling out a new image; automation can hook into the deploy step to run `scripts/run_migrations.py`.
### CI/CD Integration
- Gitea Actions workflows reside under `.gitea/workflows/`.
- `test.yml` executes the pytest suite using cached pip dependencies.
- `build-and-push.yml` logs into the container registry, rebuilds the Docker image using GitHub Actions cache-backed layers, and pushes `latest` (and additional tags as required).
- `deploy.yml` connects to the target host via SSH, pulls the pushed tag, stops any existing container, and launches the new version.
- Required secrets: `REGISTRY_URL`, `REGISTRY_USERNAME`, `REGISTRY_PASSWORD`, `SSH_HOST`, `SSH_USERNAME`, `SSH_PRIVATE_KEY`.
- Extend these workflows when introducing staging/blue-green deployments; keep cross-links with [Testing & CI](07_deployment/07_01_testing_ci.md.md) up to date.
## Integrations and Future Work (deployment-related)
- **Persistence of results**: `/api/simulations/run` currently returns in-memory results; next iteration should persist to `simulation_result` and reference scenarios.
- **Deployment**: implement infrastructure-as-code (e.g., Terraform/Ansible) to provision the hosting environment and maintain parity across dev/stage/prod.

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---
title: "08 — Concepts"
description: "Document key concepts, domain models, and terminology used throughout the architecture documentation."
status: draft
---
# 08 — Concepts
## Key Concepts
### Scenario
A `scenario` represents a distinct mining project configuration, encapsulating all relevant parameters, costs, consumption, production outputs, equipment, maintenance logs, and simulation results. Each scenario is independent, allowing users to model and analyze different mining strategies.
### Parameterization
Parameters are defined for each scenario to capture inputs such as resource consumption rates, production targets, cost factors, and equipment specifications. Parameters can have fixed values or be linked to probability distributions for stochastic simulations.
### Monte Carlo Simulation
The Monte Carlo simulation engine allows users to perform risk analysis by running multiple iterations of a scenario with varying input parameters based on defined probability distributions. This helps in understanding the range of possible outcomes and their associated probabilities.
## Domain Model
The domain model consists of the following key entities:
- `Scenario`: Represents a mining project configuration.
- `Parameter`: Input values for scenarios, which can be fixed or probabilistic.
- `Cost`: Tracks capital and operational expenditures.
- `Consumption`: Records resource usage.
- `ProductionOutput`: Captures production metrics.
- `Equipment`: Represents mining equipment associated with a scenario.
- `Maintenance`: Logs maintenance events for equipment.
- `SimulationResult`: Stores results from Monte Carlo simulations.
- `Distribution`: Defines probability distributions for stochastic parameters.
- `User`: Represents application users and their roles.
- `Report`: Generated reports summarizing scenario analyses.
- `Dashboard`: Visual representation of key performance indicators and metrics.
- `AuditLog`: Tracks changes and actions performed within the application.
- `Notification`: Alerts and messages related to scenario events and updates.
- `Tag`: Labels for categorizing scenarios and other entities.
- `Attachment`: Files associated with scenarios, such as documents or images.
- `Version`: Tracks different versions of scenarios and their configurations.
### Detailed Domain Models
See [Domain Models](08_concepts/08_01_domain_models.md) document for detailed class diagrams and entity relationships.
## Data Model Highlights
- `scenario`: central entity describing a mining scenario; owns relationships to cost, consumption, production, equipment, and maintenance tables.
- `capex`, `opex`: monetary tracking linked to scenarios.
- `consumption`: resource usage entries parameterized by scenario and description.
- `parameter`: scenario inputs with base `value` and optional distribution linkage via `distribution_id`, `distribution_type`, and JSON `distribution_parameters` to support simulation sampling.
- `production_output`: production metrics per scenario.
- `equipment` and `maintenance`: equipment inventory and maintenance events with dates/costs.
- `simulation_result`: staging table for future Monte Carlo outputs (not yet populated by `run_simulation`).
- `application_setting`: centralized key/value store for UI and system configuration, supporting typed values, categories, and editability flags so administrators can manage theme variables and future global options without code changes.
Foreign keys secure referential integrity between domain tables and their scenarios, enabling per-scenario analytics.
### Detailed Data Models
See [Data Models](08_concepts/08_02_data_models.md) document for detailed ER diagrams and table descriptions.

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# User Roles and Permissions Model
This document outlines the proposed user roles and permissions model for the CalMiner application.
## User Roles
- **Admin:** Full access to all features, including user management, application settings, and all data.
- **Analyst:** Can create, view, edit, and delete scenarios, run simulations, and view reports. Cannot modify application settings or manage users.
- **Viewer:** Can view scenarios, simulations, and reports. Cannot create, edit, or delete anything.
## Permissions (examples)
- `users:manage`: Admin only.
- `settings:manage`: Admin only.
- `scenarios:create`: Admin, Analyst.
- `scenarios:view`: Admin, Analyst, Viewer.
- `scenarios:edit`: Admin, Analyst.
- `scenarios:delete`: Admin, Analyst.
- `simulations:run`: Admin, Analyst.
- `simulations:view`: Admin, Analyst, Viewer.
- `reports:view`: Admin, Analyst, Viewer.
## Authentication System
The authentication system uses JWT (JSON Web Tokens) for securing API endpoints. Users can register with a username, email, and password. Passwords are hashed using a `passlib` CryptContext for secure, configurable hashing. Upon successful login, an access token is issued, which must be included in subsequent requests for protected resources.
## Key Components
- **Password Hashing:** `passlib.context.CryptContext` with `bcrypt` scheme.
- **Token Creation & Verification:** `jose.jwt` for encoding and decoding JWTs.
- **Authentication Flow:**
1. User registers via `/users/register`.
2. User logs in via `/users/login` to obtain an access token.
3. The access token is sent in the `Authorization` header (Bearer token) for protected routes.
4. The `get_current_user` dependency verifies the token and retrieves the authenticated user.
- **Password Reset:** A placeholder `forgot_password` endpoint is available, and a `reset_password` endpoint allows users to set a new password with a valid token (token generation and email sending are not yet implemented).

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# Data Models
## Data Model Highlights
- `scenario`: central entity describing a mining scenario; owns relationships to cost, consumption, production, equipment, and maintenance tables.
- `capex`, `opex`: monetary tracking linked to scenarios.
- `consumption`: resource usage entries parameterized by scenario and description.
- `parameter`: scenario inputs with base `value` and optional distribution linkage via `distribution_id`, `distribution_type`, and JSON `distribution_parameters` to support simulation sampling.
- `production_output`: production metrics per scenario.
- `equipment` and `maintenance`: equipment inventory and maintenance events with dates/costs.
- `simulation_result`: staging table for future Monte Carlo outputs (not yet populated by `run_simulation`).
Foreign keys secure referential integrity between domain tables and their scenarios, enabling per-scenario analytics.
## Schema Diagrams
```mermaid
erDiagram
SCENARIO ||--o{ CAPEX : has
SCENARIO ||--o{ OPEX : has
SCENARIO ||--o{ CONSUMPTION : has
SCENARIO ||--o{ PARAMETER : has
SCENARIO ||--o{ PRODUCTION_OUTPUT : has
SCENARIO ||--o{ EQUIPMENT : has
EQUIPMENT ||--o{ MAINTENANCE : has
SCENARIO ||--o{ SIMULATION_RESULT : has
SCENARIO {
int id PK
string name
string description
datetime created_at
datetime updated_at
}
CAPEX {
int id PK
int scenario_id FK
float amount
string description
datetime created_at
datetime updated_at
}
OPEX {
int id PK
int scenario_id FK
float amount
string description
datetime created_at
datetime updated_at
}
CONSUMPTION {
int id PK
int scenario_id FK
string resource_type
float quantity
string description
datetime created_at
datetime updated_at
}
PRODUCTION_OUTPUT {
int id PK
int scenario_id FK
float tonnage
float recovery_rate
float revenue
datetime created_at
datetime updated_at
}
EQUIPMENT {
int id PK
int scenario_id FK
string name
string type
datetime created_at
datetime updated_at
}
MAINTENANCE {
int id PK
int equipment_id FK
date maintenance_date
float cost
string description
datetime created_at
datetime updated_at
}
SIMULATION_RESULT {
int id PK
int scenario_id FK
json result_data
datetime created_at
datetime updated_at
}
PARAMETER {
int id PK
int scenario_id FK
string name
float value
int distribution_id FK
string distribution_type
json distribution_parameters
datetime created_at
datetime updated_at
}
```

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# 09 — Architecture Decisions
Status: skeleton
Record important architectural decisions, their rationale, and alternatives considered.

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# 10 — Quality Requirements
Status: skeleton
List non-functional requirements (performance, scalability, reliability, security) and measurable acceptance criteria.

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# 11 — Technical Risks
Status: skeleton
Document potential technical risks, mitigation strategies, and monitoring suggestions.

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# 12 — Glossary
Status: skeleton
Project glossary and definitions for domain-specific terms.

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---
title: 'CalMiner Architecture Documentation'
description: 'arc42-based architecture documentation for the CalMiner project'
---
# Architecture documentation (arc42 mapping)
This folder mirrors the arc42 chapter structure (adapted to Markdown).
## Files
- [01 Introduction and Goals](01_introduction_and_goals.md)
- [02 Architecture Constraints](02_architecture_constraints.md)
- [02_01 Technical Constraints](02_constraints/02_01_technical_constraints.md)
- [02_02 Organizational Constraints](02_constraints/02_02_organizational_constraints.md)
- [02_03 Regulatory Constraints](02_constraints/02_03_regulatory_constraints.md)
- [02_04 Environmental Constraints](02_constraints/02_04_environmental_constraints.md)
- [02_05 Performance Constraints](02_constraints/02_05_performance_constraints.md)
- [03 Context and Scope](03_context_and_scope.md)
- [03_01 Architecture Scope](03_scope/03_01_architecture_scope.md)
- [04 Solution Strategy](04_solution_strategy.md)
- [04_01 Client-Server Architecture](04_strategy/04_01_client_server_architecture.md)
- [04_02 Technology Choices](04_strategy/04_02_technology_choices.md)
- [04_03 Trade-offs](04_strategy/04_03_trade_offs.md)
- [04_04 Future Considerations](04_strategy/04_04_future_considerations.md)
- [05 Building Block View](05_building_block_view.md)
- [05_01 Architecture Overview](05_blocks/05_01_architecture_overview.md)
- [05_02 Backend Components](05_blocks/05_02_backend_components.md)
- [05_03 Frontend Components](05_blocks/05_03_frontend_components.md)
- [05_03 Theming](05_blocks/05_03_theming.md)
- [05_04 Middleware & Utilities](05_blocks/05_04_middleware_utilities.md)
- [06 Runtime View](06_runtime_view.md)
- [07 Deployment View](07_deployment_view.md)
- [07_01 Testing & CI](07_deployment/07_01_testing_ci.md.md)
- [07_02 Database](07_deployment/07_02_database.md)
- [08 Concepts](08_concepts.md)
- [08_01 Security](08_concepts/08_01_security.md)
- [08_02 Data Models](08_concepts/08_02_data_models.md)
- [09 Architecture Decisions](09_architecture_decisions.md)
- [10 Quality Requirements](10_quality_requirements.md)
- [11 Technical Risks](11_technical_risks.md)
- [12 Glossary](12_glossary.md)

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# CI Cache Troubleshooting
## Background
The test workflow (`.gitea/workflows/test.yml`) uses the `actions/cache` action to reuse the pip download cache located at `~/.cache/pip`. The cache key now hashes both `requirements.txt` and `requirements-test.txt` so the cache stays aligned with dependency changes.
## Current Observation
Recent CI runs report the following warning when the cache step executes:
```text
::warning::Failed to restore: getCacheEntry failed: connect ETIMEDOUT 172.17.0.5:40181
Cache not found for input keys: Linux-pip-<hash>, Linux-pip-
```
The timeout indicates the runner cannot reach the cache backend rather than a normal cache miss.
## Recommended Follow-Up
- Confirm that the Actions cache service is enabled for the CI environment (Gitea runners require the cache server URL to be provided via `ACTIONS_CACHE_URL` and `ACTIONS_RUNTIME_URL`).
- Verify network connectivity from the runner to the cache service endpoint and ensure required ports are open.
- After connectivity is restored, rerun the workflow to allow the cache to be populated and confirm subsequent runs restore the cache without warnings.
## Interim Guidance
- The workflow will proceed without cached dependencies, but package installs may take longer.
- Keep the cache step in place so it begins working automatically once the infrastructure is configured.

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# Development Environment Setup
This document outlines the local development environment and steps to get the project running.
## Prerequisites
- Python (version 3.11+)
- PostgreSQL (version 13+)
- Git
- Docker and Docker Compose (optional, for containerized development)
## Clone and Project Setup
```powershell
# Clone the repository
git clone https://git.allucanget.biz/allucanget/calminer.git
cd calminer
```
## Development with Docker Compose (Recommended)
For a quick setup without installing PostgreSQL locally, use Docker Compose:
```powershell
# Start services
docker-compose up
# The app will be available at http://localhost:8000
# Database is automatically set up
```
To run in background:
```powershell
docker-compose up -d
```
To stop:
```powershell
docker-compose down
```
## Manual Development Setup
### Virtual Environment
```powershell
# Create and activate a virtual environment
python -m venv .venv
.\.venv\Scripts\Activate.ps1
```
### Install Dependencies
```powershell
pip install -r requirements.txt
```
### Database Setup
1. Create database user:
```sql
CREATE USER calminer_user WITH PASSWORD 'your_password';
```
1. Create database:
```sql
CREATE DATABASE calminer;
```
### Environment Variables
1. Copy `.env.example` to `.env` at project root.
1. Edit `.env` to set database connection details:
```dotenv
DATABASE_DRIVER=postgresql
DATABASE_HOST=localhost
DATABASE_PORT=5432
DATABASE_USER=calminer_user
DATABASE_PASSWORD=your_password
DATABASE_NAME=calminer
DATABASE_SCHEMA=public
```
1. The application uses `python-dotenv` to load these variables. A legacy `DATABASE_URL` value is still accepted if the granular keys are omitted.
### Running the Application
```powershell
# Start the FastAPI server
uvicorn main:app --reload
```
## Testing
```powershell
pytest
```
E2E tests use Playwright and a session-scoped `live_server` fixture that starts the app at `http://localhost:8001` for browser-driven tests.

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# Staging Environment Setup
This guide outlines how to provision and validate the CalMiner staging database using `scripts/setup_database.py`. It complements the local and CI-focused instructions in `docs/quickstart.md`.
## Prerequisites
- Network access to the staging infrastructure (VPN or bastion, as required by ops).
- Provisioned PostgreSQL instance with superuser or delegated admin credentials for maintenance.
- Application credentials (role + password) dedicated to CalMiner staging.
- The application repository checked out with Python dependencies installed (`pip install -r requirements.txt`).
- Optional but recommended: a writable directory (for example `reports/`) to capture setup logs.
> Replace the placeholder values in the examples below with the actual host, port, and credential details supplied by ops.
## Environment Configuration
Populate the following environment variables before invoking the setup script. Store them in a secure location such as `config/setup_staging.env` (excluded from source control) and load them with `dotenv` or your shell profile.
| Variable | Description |
| ----------------------------- | ----------------------------------------------------------------------------------------- |
| `DATABASE_HOST` | Staging PostgreSQL hostname or IP (for example `staging-db.internal`). |
| `DATABASE_PORT` | Port exposed by the staging PostgreSQL service (default `5432`). |
| `DATABASE_NAME` | CalMiner staging database name (for example `calminer_staging`). |
| `DATABASE_USER` | Application role used by the FastAPI app (for example `calminer_app`). |
| `DATABASE_PASSWORD` | Password for the application role. |
| `DATABASE_SCHEMA` | Optional non-public schema; omit or set to `public` otherwise. |
| `DATABASE_SUPERUSER` | Administrative role with rights to create roles/databases (for example `calminer_admin`). |
| `DATABASE_SUPERUSER_PASSWORD` | Password for the administrative role. |
| `DATABASE_SUPERUSER_DB` | Database to connect to for admin tasks (default `postgres`). |
| `DATABASE_ADMIN_URL` | Optional DSN that overrides the granular admin settings above. |
You may also set `DATABASE_URL` for application runtime convenience, but the setup script only requires the values listed in the table.
### Loading Variables (PowerShell example)
```powershell
$env:DATABASE_HOST = "staging-db.internal"
$env:DATABASE_PORT = "5432"
$env:DATABASE_NAME = "calminer_staging"
$env:DATABASE_USER = "calminer_app"
$env:DATABASE_PASSWORD = "<app-password>"
$env:DATABASE_SUPERUSER = "calminer_admin"
$env:DATABASE_SUPERUSER_PASSWORD = "<admin-password>"
$env:DATABASE_SUPERUSER_DB = "postgres"
```
For bash shells, export the same variables using `export VARIABLE=value` or load them through `dotenv`.
## Setup Workflow
Run the setup script in three phases to validate idempotency and capture diagnostics:
1. **Dry run (diagnostic):**
```powershell
python scripts/setup_database.py --ensure-database --ensure-role --ensure-schema --initialize-schema --run-migrations --seed-data --dry-run -v `
2>&1 | Tee-Object -FilePath reports/setup_staging_dry_run.log
```
Confirm that the script reports planned actions without failures. If the application role is missing, a dry run will log skip messages until a live run creates the role.
2. **Apply changes:**
```powershell
python scripts/setup_database.py --ensure-database --ensure-role --ensure-schema --initialize-schema --run-migrations --seed-data -v `
2>&1 | Tee-Object -FilePath reports/setup_staging_apply.log
```
Verify the log for successful database creation, role grants, migration execution, and seed verification.
3. **Post-apply dry run:**
```powershell
python scripts/setup_database.py --ensure-database --ensure-role --ensure-schema --initialize-schema --run-migrations --seed-data --dry-run -v `
2>&1 | Tee-Object -FilePath reports/setup_staging_post_apply.log
```
This run should confirm that all schema objects, migrations, and seed data are already in place.
## Validation Checklist
- [ ] Confirm the staging application can connect using the application DSN (for example, run `pytest tests/e2e/test_smoke.py` against staging or trigger a smoke test workflow).
- [ ] Inspect `schema_migrations` to ensure the baseline migration (`000_base.sql`) is recorded.
- [ ] Spot-check seeded reference data (`currency`, `measurement_unit`) for correctness.
- [ ] Capture and archive the three setup logs in a shared location for audit purposes.
## Troubleshooting
- If the dry run reports skipped actions because the application role does not exist, proceed with the live run; subsequent dry runs will validate as expected.
- Connection errors usually stem from network restrictions or incorrect credentials. Validate reachability with `psql` or `pg_isready` using the same host/port and credentials.
- For permission issues during migrations or seeding, confirm the admin role has rights on the target database and that the application role inherits the expected privileges.
## Rollback Guidance
- Database creation and role grants register rollback actions when not running in dry-run mode. If a later step fails, rerun the script without `--dry-run`; it will automatically revoke grants or drop newly created resources as part of the rollback routine.
- For staged environments where manual intervention is required, coordinate with ops before dropping databases or roles.
## Next Steps
- Keep this document updated as staging infrastructure evolves (for example, when migrating to managed services or rotating credentials).

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# UI, templates and styling
This document outlines the UI structure, template components, CSS variable conventions, and per-page data/actions for the CalMiner application.
## Reusable Template Components
To reduce duplication across form-centric pages, shared Jinja macros live in `templates/partials/components.html`.
- `select_field(...)`: renders labeled `<select>` controls with consistent placeholder handling and optional preselection. Existing JavaScript modules continue to target the generated IDs, so template calls must pass the same identifiers (`consumption-form-scenario`, etc.).
- `feedback(...)` and `empty_state(...)`: wrap status messages in standard classes (`feedback`, `empty-state`) with optional `hidden` toggles so scripts can control visibility without reimplementing markup.
- `table_container(...)`: provides a semantic wrapper and optional heading around tabular content; the `{% call %}` body supplies the `<thead>`, `<tbody>`, and `<tfoot>` elements while the macro applies the `table-container` class and manages hidden state.
Pages like `templates/consumption.html` and `templates/costs.html` already consume these helpers to keep markup aligned while preserving existing JavaScript selectors.
Import macros via:
```jinja
{% from "partials/components.html" import select_field, feedback, table_container with context %}
```
## Styling Audit Notes (2025-10-21)
- **Spacing**: Panels (`section.panel`) sometimes lack consistent vertical rhythm between headings, form grids, and tables. Extra top/bottom margin utilities would help align content.
- **Typography**: Headings rely on browser defaults; font-size scale is uneven between `<h2>` and `<h3>`. Define explicit scale tokens (e.g., `--font-size-lg`) for predictable sizing.
- **Forms**: `.form-grid` uses fixed column gaps that collapse on small screens; introduce responsive grid rules to stack gracefully below ~768px.
- **Tables**: `.table-container` wrappers need overflow handling for narrow viewports; consider `overflow-x: auto` with padding adjustments.
- **Feedback/Empty states**: Messages use default font weight and spacing; a utility class for margin/padding would ensure consistent separation from forms or tables.
## CSS Variable Naming Conventions
The project adheres to a clear and descriptive naming convention for CSS variables, primarily defined in `static/css/main.css`.
## Naming Structure
Variables are prefixed based on their category:
- `--color-`: For all color-related variables (e.g., `--color-primary`, `--color-background`, `--color-text-primary`).
- `--space-`: For spacing and layout-related variables (e.g., `--space-sm`, `--space-md`, `--space-lg`).
- `--font-size-`: For font size variables (e.g., `--font-size-base`, `--font-size-lg`).
- Other specific prefixes for components or properties (e.g., `--panel-radius`, `--table-radius`).
## Descriptive Names
Color names are chosen to be semantically meaningful rather than literal color values, allowing for easier theme changes. For example:
- `--color-primary`: Represents the main brand color.
- `--color-accent`: Represents an accent color used for highlights.
- `--color-text-primary`: The main text color.
- `--color-text-muted`: A lighter text color for less emphasis.
- `--color-surface`: The background color for UI elements like cards or panels.
- `--color-background`: The overall page background color.
This approach ensures that the CSS variables are intuitive, maintainable, and easily adaptable for future theme customizations.
## Per-page data & actions
Short reference of per-page APIs and primary actions used by templates and scripts.
- Scenarios (`templates/ScenarioForm.html`):
- Data: `GET /api/scenarios/`
- Actions: `POST /api/scenarios/`
- Parameters (`templates/ParameterInput.html`):
- Data: `GET /api/scenarios/`, `GET /api/parameters/`
- Actions: `POST /api/parameters/`
- Costs (`templates/costs.html`):
- Data: `GET /api/costs/capex`, `GET /api/costs/opex`
- Actions: `POST /api/costs/capex`, `POST /api/costs/opex`
- Consumption (`templates/consumption.html`):
- Data: `GET /api/consumption/`
- Actions: `POST /api/consumption/`
- Production (`templates/production.html`):
- Data: `GET /api/production/`
- Actions: `POST /api/production/`
- Equipment (`templates/equipment.html`):
- Data: `GET /api/equipment/`
- Actions: `POST /api/equipment/`
- Maintenance (`templates/maintenance.html`):
- Data: `GET /api/maintenance/` (pagination support)
- Actions: `POST /api/maintenance/`, `PUT /api/maintenance/{id}`, `DELETE /api/maintenance/{id}`
- Simulations (`templates/simulations.html`):
- Data: `GET /api/scenarios/`, `GET /api/parameters/`
- Actions: `POST /api/simulations/run`
- Reporting (`templates/reporting.html` and `templates/Dashboard.html`):
- Data: `POST /api/reporting/summary` (accepts arrays of `{ "result": float }` objects)
- Actions: Trigger summary refreshes and export/download actions.
## Navigation Structure
The application uses a sidebar navigation menu organized into the following top-level categories:
- **Dashboard**: Main overview page.
- **Overview**: Sub-menu for core scenario inputs.
- Parameters: Process parameters configuration.
- Costs: Capital and operating costs.
- Consumption: Resource consumption tracking.
- Production: Production output settings.
- Equipment: Equipment inventory (with Maintenance sub-item).
- **Simulations**: Monte Carlo simulation runs.
- **Analytics**: Reporting and analytics.
- **Settings**: Administrative settings (with Themes and Currency Management sub-items).
## UI Template Audit (2025-10-20)
- Existing HTML templates: `ScenarioForm.html`, `ParameterInput.html`, and `Dashboard.html` (reporting summary view).
- Coverage gaps remain for costs, consumption, production, equipment, maintenance, and simulation workflows—no dedicated templates yet.
- Shared layout primitives (navigation/header/footer) are absent; current pages duplicate boilerplate markup.
- Dashboard currently covers reporting metrics but should be wired to a central `/` route once the shared layout lands.
- Next steps: introduce a `base.html`, refactor existing templates to extend it, and scaffold placeholder pages for the remaining features.

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# Consolidated Migration Baseline Plan
This note outlines the content and structure of the planned baseline migration (`scripts/migrations/000_base.sql`). The objective is to capture the currently required schema changes in a single idempotent script so that fresh environments only need to apply one SQL file before proceeding with incremental migrations.
## Guiding Principles
1. **Idempotent DDL**: Every `CREATE` or `ALTER` statement must tolerate repeated execution. Use `IF NOT EXISTS` guards or existence checks (`information_schema`) where necessary.
2. **Order of Operations**: Create reference tables first, then update dependent tables, finally enforce foreign keys and constraints.
3. **Data Safety**: Default data seeded by migrations should be minimal and in ASCII-only form to avoid encoding issues in various shells and CI logs.
4. **Compatibility**: The baseline must reflect the schema shape expected by the current SQLAlchemy models, API routes, and seeding scripts.
## Schema Elements to Include
### 1. `currency` Table
- Columns: `id SERIAL PRIMARY KEY`, `code VARCHAR(3) UNIQUE NOT NULL`, `name VARCHAR(128) NOT NULL`, `symbol VARCHAR(8)`, `is_active BOOLEAN NOT NULL DEFAULT TRUE`.
- Index: implicit via unique constraint on `code`.
- Seed rows matching `scripts.seed_data.CURRENCY_SEEDS` (ASCII-only symbols such as `USD$`, `CAD$`).
- Upsert logic using `ON CONFLICT (code) DO UPDATE` to keep names/symbols in sync when rerun.
### 2. Currency Integration for CAPEX/OPEX
- Add `currency_id INTEGER` columns with `IF NOT EXISTS` guards.
- Populate `currency_id` from legacy `currency_code` if the column exists.
- Default null `currency_id` values to the USD row, then `ALTER` to `SET NOT NULL`.
- Create `fk_capex_currency` and `fk_opex_currency` constraints with `ON DELETE RESTRICT` semantics.
- Drop legacy `currency_code` column if it exists (safe because new column holds data).
### 3. Measurement Metadata on Consumption/Production
- Ensure `consumption` and `production_output` tables have `unit_name VARCHAR(64)` and `unit_symbol VARCHAR(16)` columns with `IF NOT EXISTS` guards.
### 4. `measurement_unit` Reference Table
- Columns: `id SERIAL PRIMARY KEY`, `code VARCHAR(64) UNIQUE NOT NULL`, `name VARCHAR(128) NOT NULL`, `symbol VARCHAR(16)`, `unit_type VARCHAR(32) NOT NULL`, `is_active BOOLEAN NOT NULL DEFAULT TRUE`, `created_at TIMESTAMP WITH TIME ZONE DEFAULT NOW()`, `updated_at TIMESTAMP WITH TIME ZONE DEFAULT NOW()`.
- Assume a simple trigger to maintain `updated_at` is deferred: automate via application layer later; for now, omit trigger.
- Seed rows matching `MEASUREMENT_UNIT_SEEDS` (ASCII names/symbols). Use `ON CONFLICT (code) DO UPDATE` to keep descriptive fields aligned.
### 5. Transaction Handling
- Wrap the main operations in a single `BEGIN; ... COMMIT;` block.
- Use subtransactions (`DO $$ ... $$;`) only where conditional logic is required (e.g., checking column existence before backfill).
## Migration Tracking Alignment
- Baseline file will be named `000_base.sql`. After execution, insert a row into `schema_migrations` with filename `000_base.sql` to keep the tracking table aligned.
- Existing migrations (`20251021_add_currency_and_unit_fields.sql`, `20251022_create_currency_table_and_fks.sql`) remain for historical reference but will no longer be applied to new environments once the baseline is present.
## Next Steps
1. Draft `000_base.sql` reflecting the steps above.
2. Update `run_migrations` to recognise the baseline file and mark older migrations as applied when the baseline exists.
3. Provide documentation in `docs/quickstart.md` explaining how to reset an environment using the baseline plus seeds.

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docs/quickstart.md
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# Developer Quickstart
- [Developer Quickstart](#developer-quickstart)
- [Development](#development)
- [User Interface](#user-interface)
- [Testing](#testing)
- [Staging](#staging)
- [Deployment](#deployment)
- [Using Docker Compose](#using-docker-compose)
- [Manual Docker Deployment](#manual-docker-deployment)
- [Database Deployment \& Migrations](#database-deployment--migrations)
- [Usage Overview](#usage-overview)
- [Theme configuration](#theme-configuration)
- [Where to look next](#where-to-look-next)
This document provides a quickstart guide for developers to set up and run the CalMiner application locally.
## Development
See [Development Setup](docs/developer/development_setup.md).
### User Interface
There is a dedicated [UI and Style](docs/developer/ui_and_style.md) guide for frontend contributors.
### Testing
Testing is described in the [Testing CI](docs/architecture/07_deployment/07_01_testing_ci.md) document.
## Staging
Staging environment setup is covered in [Staging Environment Setup](docs/developer/staging_environment_setup.md).
## Deployment
The application can be deployed using Docker containers.
### Using Docker Compose
For production deployment, use the provided `docker-compose.yml`:
```bash
docker-compose up -d
```
This starts the FastAPI app and PostgreSQL database.
### Manual Docker Deployment
Build and run the container manually:
```bash
docker build -t calminer .
docker run -d -p 8000:8000 \
-e DATABASE_HOST=your-postgres-host \
-e DATABASE_USER=calminer \
-e DATABASE_PASSWORD=your-password \
-e DATABASE_NAME=calminer_db \
calminer
```
Ensure the database is set up and migrated before running.
### Database Deployment & Migrations
See the [Database Deployment & Migrations](docs/architecture/07_deployment/07_02_database_deployment_migrations.md) document for details on database deployment and migration strategies.
## Usage Overview
- **Run the application**: Follow the [Development Setup](docs/developer/development_setup.md) to get the application running locally.
- **Access the UI**: Open your web browser and navigate to `http://localhost:8000/ui` to access the user interface.
- **API base URL**: `http://localhost:8000/api`
- Key routes include creating scenarios, parameters, costs, consumption, production, equipment, maintenance, and reporting summaries. See the `routes/` directory for full details.
- **UI base URL**: `http://localhost:8000/ui`
### Theme configuration
Theming is laid out in [Theming](docs/architecture/05_03_theming.md).
## Where to look next
- Architecture overview & chapters: [architecture](architecture/README.md) (per-chapter files under `docs/architecture/`)
- [Testing & CI](architecture/07_deployment/07_01_testing_ci.md.md)
- [Development setup](developer/development_setup.md)
- Implementation plan & roadmap: [Solution strategy](architecture/04_solution_strategy.md)
- Routes: [routes](../routes/)
- Services: [services](../services/)
- Scripts: [scripts](../scripts/) (migrations and backfills)

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docs/roadmap.md
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# Roadmap
## Overview
## Scenario Enhancements
For each scenario, the goal is to evaluate financial viability, operational efficiency, and risk factors associated with the mining project. This data is used to perform calculations, generate reports, and visualize results through charts and dashboards, enabling users to make informed decisions based on comprehensive analysis.
### Scenario & Data Management
Scenarios are the core organizational unit within CalMiner, allowing users to create, manage, and analyze different mining project configurations. Each scenario encapsulates a unique set of parameters and data inputs that define the mining operation being modeled.
#### Scenario Creation
Users can create new scenarios by providing a unique name and description. The system will generate a new scenario with default parameters, which can be customized later.
#### Scenario Management
Users can manage existing scenarios by modifying their parameters, adding new data inputs, or deleting them as needed.
#### Data Inputs
Users can define and manage various data inputs for each scenario, including:
- **Geological Data**: Input data related to the geological characteristics of the mining site.
- **Operational Parameters**: Define parameters such as mining methods, equipment specifications, and workforce details.
- **Financial Data**: Input cost structures, revenue models, and financial assumptions.
- **Environmental Data**: Include data related to environmental impact, regulations, and sustainability practices.
- **Technical Data**: Specify technical parameters such as ore grades, recovery rates, and processing methods.
- **Social Data**: Incorporate social impact assessments, community engagement plans, and stakeholder analysis.
- **Regulatory Data**: Include data related to legal and regulatory requirements, permits, and compliance measures.
- **Market Data**: Input market conditions, commodity prices, and economic indicators that may affect the mining operation.
- **Risk Data**: Define risk factors, probabilities, and mitigation strategies for the mining project.
- **Logistical Data**: Include data related to transportation, supply chain management, and infrastructure requirements.
- **Maintenance Data**: Input maintenance schedules, costs, and equipment reliability metrics.
- **Human Resources Data**: Define workforce requirements, training programs, and labor costs.
- **Health and Safety Data**: Include data related to workplace safety protocols, incident rates, and health programs.

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models/__init__.py
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"""
models package initializer. Import key models so they're registered
with the shared Base.metadata when the package is imported by tests.
"""
from . import application_setting # noqa: F401
from . import currency # noqa: F401
from . import role # noqa: F401
from . import user # noqa: F401
from . import theme_setting # noqa: F401

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models/application_setting.py
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from datetime import datetime
from typing import Optional
from sqlalchemy import Boolean, DateTime, String, Text
from sqlalchemy.orm import Mapped, mapped_column
from sqlalchemy.sql import func
from config.database import Base
class ApplicationSetting(Base):
__tablename__ = "application_setting"
id: Mapped[int] = mapped_column(primary_key=True, index=True)
key: Mapped[str] = mapped_column(String(128), unique=True, nullable=False)
value: Mapped[str] = mapped_column(Text, nullable=False)
value_type: Mapped[str] = mapped_column(
String(32), nullable=False, default="string"
)
category: Mapped[str] = mapped_column(
String(32), nullable=False, default="general"
)
description: Mapped[Optional[str]] = mapped_column(Text, nullable=True)
is_editable: Mapped[bool] = mapped_column(
Boolean, nullable=False, default=True
)
created_at: Mapped[datetime] = mapped_column(
DateTime(timezone=True), server_default=func.now(), nullable=False
)
updated_at: Mapped[datetime] = mapped_column(
DateTime(timezone=True),
server_default=func.now(),
onupdate=func.now(),
nullable=False,
)
def __repr__(self) -> str:
return f"<ApplicationSetting key={self.key} category={self.category}>"

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models/capex.py
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from sqlalchemy import event, text
from sqlalchemy import Column, Integer, Float, String, ForeignKey
from sqlalchemy.orm import relationship
from config.database import Base
class Capex(Base):
__tablename__ = "capex"
id = Column(Integer, primary_key=True, index=True)
scenario_id = Column(Integer, ForeignKey("scenario.id"), nullable=False)
amount = Column(Float, nullable=False)
description = Column(String, nullable=True)
currency_id = Column(Integer, ForeignKey("currency.id"), nullable=False)
scenario = relationship("Scenario", back_populates="capex_items")
currency = relationship("Currency", back_populates="capex_items")
def __repr__(self):
return (
f"<Capex id={self.id} scenario_id={self.scenario_id} "
f"amount={self.amount} currency_id={self.currency_id}>"
)
@property
def currency_code(self) -> str:
return self.currency.code if self.currency else None
@currency_code.setter
def currency_code(self, value: str) -> None:
# store pending code so application code or migrations can pick it up
setattr(
self, "_currency_code_pending", (value or "USD").strip().upper()
)
# SQLAlchemy event handlers to ensure currency_id is set before insert/update
def _resolve_currency(mapper, connection, target):
# If currency_id already set, nothing to do
if getattr(target, "currency_id", None):
return
code = getattr(target, "_currency_code_pending", None) or "USD"
# Try to find existing currency id
row = connection.execute(
text("SELECT id FROM currency WHERE code = :code"), {"code": code}
).fetchone()
if row:
cid = row[0]
else:
# Insert new currency and attempt to get lastrowid
res = connection.execute(
text(
"INSERT INTO currency (code, name, symbol, is_active) VALUES (:code, :name, :symbol, :active)"
),
{"code": code, "name": code, "symbol": None, "active": True},
)
try:
cid = res.lastrowid
except Exception:
# fallback: select after insert
cid = connection.execute(
text("SELECT id FROM currency WHERE code = :code"),
{"code": code},
).scalar()
target.currency_id = cid
event.listen(Capex, "before_insert", _resolve_currency)
event.listen(Capex, "before_update", _resolve_currency)

22
models/consumption.py
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from sqlalchemy import Column, Integer, Float, String, ForeignKey
from sqlalchemy.orm import relationship
from config.database import Base
class Consumption(Base):
__tablename__ = "consumption"
id = Column(Integer, primary_key=True, index=True)
scenario_id = Column(Integer, ForeignKey("scenario.id"), nullable=False)
amount = Column(Float, nullable=False)
description = Column(String, nullable=True)
unit_name = Column(String(64), nullable=True)
unit_symbol = Column(String(16), nullable=True)
scenario = relationship("Scenario", back_populates="consumption_items")
def __repr__(self):
return (
f"<Consumption id={self.id} scenario_id={self.scenario_id} "
f"amount={self.amount} unit={self.unit_symbol or self.unit_name}>"
)

24
models/currency.py
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from sqlalchemy import Column, Integer, String, Boolean
from sqlalchemy.orm import relationship
from config.database import Base
class Currency(Base):
__tablename__ = "currency"
id = Column(Integer, primary_key=True, index=True)
code = Column(String(3), nullable=False, unique=True, index=True)
name = Column(String(128), nullable=False)
symbol = Column(String(8), nullable=True)
is_active = Column(Boolean, nullable=False, default=True)
# reverse relationships (optional)
capex_items = relationship(
"Capex", back_populates="currency", lazy="select"
)
opex_items = relationship("Opex", back_populates="currency", lazy="select")
def __repr__(self):
return (
f"<Currency code={self.code} name={self.name} symbol={self.symbol}>"
)

14
models/distribution.py
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@@ -1,14 +0,0 @@
from sqlalchemy import Column, Integer, String, JSON
from config.database import Base
class Distribution(Base):
__tablename__ = "distribution"
id = Column(Integer, primary_key=True, index=True)
name = Column(String, nullable=False)
distribution_type = Column(String, nullable=False)
parameters = Column(JSON, nullable=True)
def __repr__(self):
return f"<Distribution id={self.id} name={self.name} type={self.distribution_type}>"

17
models/equipment.py
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from sqlalchemy import Column, Integer, String, ForeignKey
from sqlalchemy.orm import relationship
from config.database import Base
class Equipment(Base):
__tablename__ = "equipment"
id = Column(Integer, primary_key=True, index=True)
scenario_id = Column(Integer, ForeignKey("scenario.id"), nullable=False)
name = Column(String, nullable=False)
description = Column(String, nullable=True)
scenario = relationship("Scenario", back_populates="equipment_items")
def __repr__(self):
return f"<Equipment id={self.id} scenario_id={self.scenario_id} name={self.name}>"

23
models/maintenance.py
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@@ -1,23 +0,0 @@
from sqlalchemy import Column, Date, Float, ForeignKey, Integer, String
from sqlalchemy.orm import relationship
from config.database import Base
class Maintenance(Base):
__tablename__ = "maintenance"
id = Column(Integer, primary_key=True, index=True)
equipment_id = Column(Integer, ForeignKey("equipment.id"), nullable=False)
scenario_id = Column(Integer, ForeignKey("scenario.id"), nullable=False)
maintenance_date = Column(Date, nullable=False)
description = Column(String, nullable=True)
cost = Column(Float, nullable=False)
equipment = relationship("Equipment")
scenario = relationship("Scenario", back_populates="maintenance_items")
def __repr__(self) -> str:
return (
f"<Maintenance id={self.id} equipment_id={self.equipment_id} "
f"scenario_id={self.scenario_id} date={self.maintenance_date} cost={self.cost}>"
)

63
models/opex.py
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@@ -1,63 +0,0 @@
from sqlalchemy import event, text
from sqlalchemy import Column, Integer, Float, String, ForeignKey
from sqlalchemy.orm import relationship
from config.database import Base
class Opex(Base):
__tablename__ = "opex"
id = Column(Integer, primary_key=True, index=True)
scenario_id = Column(Integer, ForeignKey("scenario.id"), nullable=False)
amount = Column(Float, nullable=False)
description = Column(String, nullable=True)
currency_id = Column(Integer, ForeignKey("currency.id"), nullable=False)
scenario = relationship("Scenario", back_populates="opex_items")
currency = relationship("Currency", back_populates="opex_items")
def __repr__(self):
return (
f"<Opex id={self.id} scenario_id={self.scenario_id} "
f"amount={self.amount} currency_id={self.currency_id}>"
)
@property
def currency_code(self) -> str:
return self.currency.code if self.currency else None
@currency_code.setter
def currency_code(self, value: str) -> None:
setattr(
self, "_currency_code_pending", (value or "USD").strip().upper()
)
def _resolve_currency_opex(mapper, connection, target):
if getattr(target, "currency_id", None):
return
code = getattr(target, "_currency_code_pending", None) or "USD"
row = connection.execute(
text("SELECT id FROM currency WHERE code = :code"), {"code": code}
).fetchone()
if row:
cid = row[0]
else:
res = connection.execute(
text(
"INSERT INTO currency (code, name, symbol, is_active) VALUES (:code, :name, :symbol, :active)"
),
{"code": code, "name": code, "symbol": None, "active": True},
)
try:
cid = res.lastrowid
except Exception:
cid = connection.execute(
text("SELECT id FROM currency WHERE code = :code"),
{"code": code},
).scalar()
target.currency_id = cid
event.listen(Opex, "before_insert", _resolve_currency_opex)
event.listen(Opex, "before_update", _resolve_currency_opex)

29
models/parameters.py
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@@ -1,29 +0,0 @@
from typing import Any, Dict, Optional
from sqlalchemy import ForeignKey, JSON
from sqlalchemy.orm import Mapped, mapped_column, relationship
from config.database import Base
class Parameter(Base):
__tablename__ = "parameter"
id: Mapped[int] = mapped_column(primary_key=True, index=True)
scenario_id: Mapped[int] = mapped_column(
ForeignKey("scenario.id"), nullable=False
)
name: Mapped[str] = mapped_column(nullable=False)
value: Mapped[float] = mapped_column(nullable=False)
distribution_id: Mapped[Optional[int]] = mapped_column(
ForeignKey("distribution.id"), nullable=True
)
distribution_type: Mapped[Optional[str]] = mapped_column(nullable=True)
distribution_parameters: Mapped[Optional[Dict[str, Any]]] = mapped_column(
JSON, nullable=True
)
scenario = relationship("Scenario", back_populates="parameters")
distribution = relationship("Distribution")
def __repr__(self):
return f"<Parameter id={self.id} name={self.name} value={self.value}>"

24
models/production_output.py
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@@ -1,24 +0,0 @@
from sqlalchemy import Column, Integer, Float, String, ForeignKey
from sqlalchemy.orm import relationship
from config.database import Base
class ProductionOutput(Base):
__tablename__ = "production_output"
id = Column(Integer, primary_key=True, index=True)
scenario_id = Column(Integer, ForeignKey("scenario.id"), nullable=False)
amount = Column(Float, nullable=False)
description = Column(String, nullable=True)
unit_name = Column(String(64), nullable=True)
unit_symbol = Column(String(16), nullable=True)
scenario = relationship(
"Scenario", back_populates="production_output_items"
)
def __repr__(self):
return (
f"<ProductionOutput id={self.id} scenario_id={self.scenario_id} "
f"amount={self.amount} unit={self.unit_symbol or self.unit_name}>"
)

13
models/role.py
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@@ -1,13 +0,0 @@
from sqlalchemy import Column, Integer, String
from sqlalchemy.orm import relationship
from config.database import Base
class Role(Base):
__tablename__ = "roles"
id = Column(Integer, primary_key=True, index=True)
name = Column(String, unique=True, index=True)
users = relationship("User", back_populates="role")

36
models/scenario.py
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@@ -1,36 +0,0 @@
from sqlalchemy import Column, Integer, String, DateTime, func
from sqlalchemy.orm import relationship
from models.simulation_result import SimulationResult
from models.capex import Capex
from models.opex import Opex
from models.consumption import Consumption
from models.production_output import ProductionOutput
from models.equipment import Equipment
from models.maintenance import Maintenance
from config.database import Base
class Scenario(Base):
__tablename__ = "scenario"
id = Column(Integer, primary_key=True, index=True)
name = Column(String, unique=True, nullable=False)
description = Column(String)
created_at = Column(DateTime(timezone=True), server_default=func.now())
updated_at = Column(DateTime(timezone=True), onupdate=func.now())
parameters = relationship("Parameter", back_populates="scenario")
simulation_results = relationship(
SimulationResult, back_populates="scenario"
)
capex_items = relationship(Capex, back_populates="scenario")
opex_items = relationship(Opex, back_populates="scenario")
consumption_items = relationship(Consumption, back_populates="scenario")
production_output_items = relationship(
ProductionOutput, back_populates="scenario"
)
equipment_items = relationship(Equipment, back_populates="scenario")
maintenance_items = relationship(Maintenance, back_populates="scenario")
# relationships can be defined later
def __repr__(self):
return f"<Scenario id={self.id} name={self.name}>"

14
models/simulation_result.py
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@@ -1,14 +0,0 @@
from sqlalchemy import Column, Integer, Float, ForeignKey
from sqlalchemy.orm import relationship
from config.database import Base
class SimulationResult(Base):
__tablename__ = "simulation_result"
id = Column(Integer, primary_key=True, index=True)
scenario_id = Column(Integer, ForeignKey("scenario.id"), nullable=False)
iteration = Column(Integer, nullable=False)
result = Column(Float, nullable=False)
scenario = relationship("Scenario", back_populates="simulation_results")

15
models/theme_setting.py
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@@ -1,15 +0,0 @@
from sqlalchemy import Column, Integer, String
from config.database import Base
class ThemeSetting(Base):
__tablename__ = "theme_settings"
id = Column(Integer, primary_key=True, index=True)
theme_name = Column(String, unique=True, index=True)
primary_color = Column(String)
secondary_color = Column(String)
accent_color = Column(String)
background_color = Column(String)
text_color = Column(String)

23
models/user.py
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from sqlalchemy import Column, Integer, String, ForeignKey
from sqlalchemy.orm import relationship
from config.database import Base
from services.security import get_password_hash, verify_password
class User(Base):
__tablename__ = "users"
id = Column(Integer, primary_key=True, index=True)
username = Column(String, unique=True, index=True)
email = Column(String, unique=True, index=True)
hashed_password = Column(String)
role_id = Column(Integer, ForeignKey("roles.id"))
role = relationship("Role", back_populates="users")
def set_password(self, password: str):
self.hashed_password = get_password_hash(password)
def check_password(self, password: str) -> bool:
return verify_password(password, str(self.hashed_password))

1
requirements-dev.txt
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@@ -1 +0,0 @@
black

4
requirements-test.txt
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@@ -1,7 +1,7 @@
playwright
pytest
pytest-cov
pytest-httpx
pytest-playwright
python-jose
ruff
black
mypy

2
requirements.txt
View File

@@ -1,5 +1,5 @@
fastapi
pydantic>=2.0,<3.0
pydantic
uvicorn
sqlalchemy
psycopg2-binary

52
routes/consumption.py
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@@ -1,52 +0,0 @@
from typing import List, Optional
from fastapi import APIRouter, Depends, status
from pydantic import BaseModel, ConfigDict, PositiveFloat, field_validator
from sqlalchemy.orm import Session
from models.consumption import Consumption
from routes.dependencies import get_db
router = APIRouter(prefix="/api/consumption", tags=["Consumption"])
class ConsumptionBase(BaseModel):
scenario_id: int
amount: PositiveFloat
description: Optional[str] = None
unit_name: Optional[str] = None
unit_symbol: Optional[str] = None
@field_validator("unit_name", "unit_symbol")
@classmethod
def _normalize_text(cls, value: Optional[str]) -> Optional[str]:
if value is None:
return None
stripped = value.strip()
return stripped or None
class ConsumptionCreate(ConsumptionBase):
pass
class ConsumptionRead(ConsumptionBase):
id: int
model_config = ConfigDict(from_attributes=True)
@router.post(
"/", response_model=ConsumptionRead, status_code=status.HTTP_201_CREATED
)
def create_consumption(item: ConsumptionCreate, db: Session = Depends(get_db)):
db_item = Consumption(**item.model_dump())
db.add(db_item)
db.commit()
db.refresh(db_item)
return db_item
@router.get("/", response_model=List[ConsumptionRead])
def list_consumption(db: Session = Depends(get_db)):
return db.query(Consumption).all()

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routes/costs.py
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from typing import List, Optional
from fastapi import APIRouter, Depends
from pydantic import BaseModel, ConfigDict, field_validator
from sqlalchemy.orm import Session
from models.capex import Capex
from models.opex import Opex
from routes.dependencies import get_db
router = APIRouter(prefix="/api/costs", tags=["Costs"])
# Pydantic schemas for CAPEX and OPEX
class _CostBase(BaseModel):
scenario_id: int
amount: float
description: Optional[str] = None
currency_code: Optional[str] = "USD"
currency_id: Optional[int] = None
@field_validator("currency_code")
@classmethod
def _normalize_currency(cls, value: Optional[str]) -> str:
code = (value or "USD").strip().upper()
return code[:3] if len(code) > 3 else code
class CapexCreate(_CostBase):
pass
class CapexRead(_CostBase):
id: int
# use from_attributes so Pydantic reads attributes off SQLAlchemy model
model_config = ConfigDict(from_attributes=True)
# optionally include nested currency info
currency: Optional["CurrencyRead"] = None
class OpexCreate(_CostBase):
pass
class OpexRead(_CostBase):
id: int
model_config = ConfigDict(from_attributes=True)
currency: Optional["CurrencyRead"] = None
class CurrencyRead(BaseModel):
id: int
code: str
name: Optional[str] = None
symbol: Optional[str] = None
is_active: Optional[bool] = True
model_config = ConfigDict(from_attributes=True)
# forward refs
CapexRead.model_rebuild()
OpexRead.model_rebuild()
# Capex endpoints
@router.post("/capex", response_model=CapexRead)
def create_capex(item: CapexCreate, db: Session = Depends(get_db)):
payload = item.model_dump()
# Prefer explicit currency_id if supplied
cid = payload.get("currency_id")
if not cid:
code = (payload.pop("currency_code", "USD") or "USD").strip().upper()
currency_cls = __import__(
"models.currency", fromlist=["Currency"]
).Currency
currency = db.query(currency_cls).filter_by(code=code).one_or_none()
if currency is None:
currency = currency_cls(code=code, name=code, symbol=None)
db.add(currency)
db.flush()
payload["currency_id"] = currency.id
db_item = Capex(**payload)
db.add(db_item)
db.commit()
db.refresh(db_item)
return db_item
@router.get("/capex", response_model=List[CapexRead])
def list_capex(db: Session = Depends(get_db)):
return db.query(Capex).all()
# Opex endpoints
@router.post("/opex", response_model=OpexRead)
def create_opex(item: OpexCreate, db: Session = Depends(get_db)):
payload = item.model_dump()
cid = payload.get("currency_id")
if not cid:
code = (payload.pop("currency_code", "USD") or "USD").strip().upper()
currency_cls = __import__(
"models.currency", fromlist=["Currency"]
).Currency
currency = db.query(currency_cls).filter_by(code=code).one_or_none()
if currency is None:
currency = currency_cls(code=code, name=code, symbol=None)
db.add(currency)
db.flush()
payload["currency_id"] = currency.id
db_item = Opex(**payload)
db.add(db_item)
db.commit()
db.refresh(db_item)
return db_item
@router.get("/opex", response_model=List[OpexRead])
def list_opex(db: Session = Depends(get_db)):
return db.query(Opex).all()

193
routes/currencies.py
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@@ -1,193 +0,0 @@
from typing import List, Optional
from fastapi import APIRouter, Depends, HTTPException, Query, status
from pydantic import BaseModel, ConfigDict, Field, field_validator
from sqlalchemy.orm import Session
from sqlalchemy.exc import IntegrityError
from models.currency import Currency
from routes.dependencies import get_db
router = APIRouter(prefix="/api/currencies", tags=["Currencies"])
DEFAULT_CURRENCY_CODE = "USD"
DEFAULT_CURRENCY_NAME = "US Dollar"
DEFAULT_CURRENCY_SYMBOL = "$"
class CurrencyBase(BaseModel):
name: str = Field(..., min_length=1, max_length=128)
symbol: Optional[str] = Field(default=None, max_length=8)
@staticmethod
def _normalize_symbol(value: Optional[str]) -> Optional[str]:
if value is None:
return None
value = value.strip()
return value or None
@field_validator("name")
@classmethod
def _strip_name(cls, value: str) -> str:
return value.strip()
@field_validator("symbol")
@classmethod
def _strip_symbol(cls, value: Optional[str]) -> Optional[str]:
return cls._normalize_symbol(value)
class CurrencyCreate(CurrencyBase):
code: str = Field(..., min_length=3, max_length=3)
is_active: bool = True
@field_validator("code")
@classmethod
def _normalize_code(cls, value: str) -> str:
return value.strip().upper()
class CurrencyUpdate(CurrencyBase):
is_active: Optional[bool] = None
class CurrencyActivation(BaseModel):
is_active: bool
class CurrencyRead(CurrencyBase):
id: int
code: str
is_active: bool
model_config = ConfigDict(from_attributes=True)
def _ensure_default_currency(db: Session) -> Currency:
existing = (
db.query(Currency)
.filter(Currency.code == DEFAULT_CURRENCY_CODE)
.one_or_none()
)
if existing:
return existing
default_currency = Currency(
code=DEFAULT_CURRENCY_CODE,
name=DEFAULT_CURRENCY_NAME,
symbol=DEFAULT_CURRENCY_SYMBOL,
is_active=True,
)
db.add(default_currency)
try:
db.commit()
except IntegrityError:
db.rollback()
existing = (
db.query(Currency)
.filter(Currency.code == DEFAULT_CURRENCY_CODE)
.one()
)
return existing
db.refresh(default_currency)
return default_currency
def _get_currency_or_404(db: Session, code: str) -> Currency:
normalized = code.strip().upper()
currency = (
db.query(Currency).filter(Currency.code == normalized).one_or_none()
)
if currency is None:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND, detail="Currency not found"
)
return currency
@router.get("/", response_model=List[CurrencyRead])
def list_currencies(
include_inactive: bool = Query(
False, description="Include inactive currencies"
),
db: Session = Depends(get_db),
):
_ensure_default_currency(db)
query = db.query(Currency)
if not include_inactive:
query = query.filter(Currency.is_active.is_(True))
currencies = query.order_by(Currency.code).all()
return currencies
@router.post(
"/", response_model=CurrencyRead, status_code=status.HTTP_201_CREATED
)
def create_currency(payload: CurrencyCreate, db: Session = Depends(get_db)):
code = payload.code
existing = db.query(Currency).filter(Currency.code == code).one_or_none()
if existing is not None:
raise HTTPException(
status_code=status.HTTP_409_CONFLICT,
detail=f"Currency '{code}' already exists",
)
currency = Currency(
code=code,
name=payload.name,
symbol=CurrencyBase._normalize_symbol(payload.symbol),
is_active=payload.is_active,
)
db.add(currency)
db.commit()
db.refresh(currency)
return currency
@router.put("/{code}", response_model=CurrencyRead)
def update_currency(
code: str, payload: CurrencyUpdate, db: Session = Depends(get_db)
):
currency = _get_currency_or_404(db, code)
if payload.name is not None:
setattr(currency, "name", payload.name)
if payload.symbol is not None or payload.symbol == "":
setattr(
currency,
"symbol",
CurrencyBase._normalize_symbol(payload.symbol),
)
if payload.is_active is not None:
code_value = getattr(currency, "code")
if code_value == DEFAULT_CURRENCY_CODE and payload.is_active is False:
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail="The default currency cannot be deactivated.",
)
setattr(currency, "is_active", payload.is_active)
db.add(currency)
db.commit()
db.refresh(currency)
return currency
@router.patch("/{code}/activation", response_model=CurrencyRead)
def toggle_currency_activation(
code: str, body: CurrencyActivation, db: Session = Depends(get_db)
):
currency = _get_currency_or_404(db, code)
code_value = getattr(currency, "code")
if code_value == DEFAULT_CURRENCY_CODE and body.is_active is False:
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail="The default currency cannot be deactivated.",
)
setattr(currency, "is_active", body.is_active)
db.add(currency)
db.commit()
db.refresh(currency)
return currency

13
routes/dependencies.py
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@@ -1,13 +0,0 @@
from collections.abc import Generator
from sqlalchemy.orm import Session
from config.database import SessionLocal
def get_db() -> Generator[Session, None, None]:
db = SessionLocal()
try:
yield db
finally:
db.close()

38
routes/distributions.py
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@@ -1,38 +0,0 @@
from typing import Dict, List
from fastapi import APIRouter, Depends
from pydantic import BaseModel, ConfigDict
from sqlalchemy.orm import Session
from models.distribution import Distribution
from routes.dependencies import get_db
router = APIRouter(prefix="/api/distributions", tags=["Distributions"])
class DistributionCreate(BaseModel):
name: str
distribution_type: str
parameters: Dict[str, float | int]
class DistributionRead(DistributionCreate):
id: int
model_config = ConfigDict(from_attributes=True)
@router.post("/", response_model=DistributionRead)
async def create_distribution(
dist: DistributionCreate, db: Session = Depends(get_db)
):
db_dist = Distribution(**dist.model_dump())
db.add(db_dist)
db.commit()
db.refresh(db_dist)
return db_dist
@router.get("/", response_model=List[DistributionRead])
async def list_distributions(db: Session = Depends(get_db)):
dists = db.query(Distribution).all()
return dists

38
routes/equipment.py
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@@ -1,38 +0,0 @@
from typing import List, Optional
from fastapi import APIRouter, Depends
from pydantic import BaseModel, ConfigDict
from sqlalchemy.orm import Session
from models.equipment import Equipment
from routes.dependencies import get_db
router = APIRouter(prefix="/api/equipment", tags=["Equipment"])
# Pydantic schemas
class EquipmentCreate(BaseModel):
scenario_id: int
name: str
description: Optional[str] = None
class EquipmentRead(EquipmentCreate):
id: int
model_config = ConfigDict(from_attributes=True)
@router.post("/", response_model=EquipmentRead)
async def create_equipment(
item: EquipmentCreate, db: Session = Depends(get_db)
):
db_item = Equipment(**item.model_dump())
db.add(db_item)
db.commit()
db.refresh(db_item)
return db_item
@router.get("/", response_model=List[EquipmentRead])
async def list_equipment(db: Session = Depends(get_db)):
return db.query(Equipment).all()

91
routes/maintenance.py
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@@ -1,91 +0,0 @@
from datetime import date
from typing import List, Optional
from fastapi import APIRouter, Depends, HTTPException, status
from pydantic import BaseModel, ConfigDict, PositiveFloat
from sqlalchemy.orm import Session
from models.maintenance import Maintenance
from routes.dependencies import get_db
router = APIRouter(prefix="/api/maintenance", tags=["Maintenance"])
class MaintenanceBase(BaseModel):
equipment_id: int
scenario_id: int
maintenance_date: date
description: Optional[str] = None
cost: PositiveFloat
class MaintenanceCreate(MaintenanceBase):
pass
class MaintenanceUpdate(MaintenanceBase):
pass
class MaintenanceRead(MaintenanceBase):
id: int
model_config = ConfigDict(from_attributes=True)
def _get_maintenance_or_404(db: Session, maintenance_id: int) -> Maintenance:
maintenance = (
db.query(Maintenance).filter(Maintenance.id == maintenance_id).first()
)
if maintenance is None:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail=f"Maintenance record {maintenance_id} not found",
)
return maintenance
@router.post(
"/", response_model=MaintenanceRead, status_code=status.HTTP_201_CREATED
)
def create_maintenance(
maintenance: MaintenanceCreate, db: Session = Depends(get_db)
):
db_maintenance = Maintenance(**maintenance.model_dump())
db.add(db_maintenance)
db.commit()
db.refresh(db_maintenance)
return db_maintenance
@router.get("/", response_model=List[MaintenanceRead])
def list_maintenance(
skip: int = 0, limit: int = 100, db: Session = Depends(get_db)
):
return db.query(Maintenance).offset(skip).limit(limit).all()
@router.get("/{maintenance_id}", response_model=MaintenanceRead)
def get_maintenance(maintenance_id: int, db: Session = Depends(get_db)):
return _get_maintenance_or_404(db, maintenance_id)
@router.put("/{maintenance_id}", response_model=MaintenanceRead)
def update_maintenance(
maintenance_id: int,
payload: MaintenanceUpdate,
db: Session = Depends(get_db),
):
db_maintenance = _get_maintenance_or_404(db, maintenance_id)
for field, value in payload.model_dump().items():
setattr(db_maintenance, field, value)
db.commit()
db.refresh(db_maintenance)
return db_maintenance
@router.delete("/{maintenance_id}", status_code=status.HTTP_204_NO_CONTENT)
def delete_maintenance(maintenance_id: int, db: Session = Depends(get_db)):
db_maintenance = _get_maintenance_or_404(db, maintenance_id)
db.delete(db_maintenance)
db.commit()

90
routes/parameters.py
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@@ -1,90 +0,0 @@
from typing import Any, Dict, List, Optional
from fastapi import APIRouter, Depends, HTTPException
from pydantic import BaseModel, ConfigDict, field_validator
from sqlalchemy.orm import Session
from models.distribution import Distribution
from models.parameters import Parameter
from models.scenario import Scenario
from routes.dependencies import get_db
router = APIRouter(prefix="/api/parameters", tags=["parameters"])
class ParameterCreate(BaseModel):
scenario_id: int
name: str
value: float
distribution_id: Optional[int] = None
distribution_type: Optional[str] = None
distribution_parameters: Optional[Dict[str, Any]] = None
@field_validator("distribution_type")
@classmethod
def normalize_type(cls, value: Optional[str]) -> Optional[str]:
if value is None:
return value
normalized = value.strip().lower()
if not normalized:
return None
if normalized not in {"normal", "uniform", "triangular"}:
raise ValueError(
"distribution_type must be normal, uniform, or triangular"
)
return normalized
@field_validator("distribution_parameters")
@classmethod
def empty_dict_to_none(
cls, value: Optional[Dict[str, Any]]
) -> Optional[Dict[str, Any]]:
if value is None:
return None
return value or None
class ParameterRead(ParameterCreate):
id: int
model_config = ConfigDict(from_attributes=True)
@router.post("/", response_model=ParameterRead)
def create_parameter(param: ParameterCreate, db: Session = Depends(get_db)):
scen = db.query(Scenario).filter(Scenario.id == param.scenario_id).first()
if not scen:
raise HTTPException(status_code=404, detail="Scenario not found")
distribution_id = param.distribution_id
distribution_type = param.distribution_type
distribution_parameters = param.distribution_parameters
if distribution_id is not None:
distribution = (
db.query(Distribution)
.filter(Distribution.id == distribution_id)
.first()
)
if not distribution:
raise HTTPException(
status_code=404, detail="Distribution not found"
)
distribution_type = distribution.distribution_type
distribution_parameters = distribution.parameters or None
new_param = Parameter(
scenario_id=param.scenario_id,
name=param.name,
value=param.value,
distribution_id=distribution_id,
distribution_type=distribution_type,
distribution_parameters=distribution_parameters,
)
db.add(new_param)
db.commit()
db.refresh(new_param)
return new_param
@router.get("/", response_model=List[ParameterRead])
def list_parameters(db: Session = Depends(get_db)):
return db.query(Parameter).all()

56
routes/production.py
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@@ -1,56 +0,0 @@
from typing import List, Optional
from fastapi import APIRouter, Depends, status
from pydantic import BaseModel, ConfigDict, PositiveFloat, field_validator
from sqlalchemy.orm import Session
from models.production_output import ProductionOutput
from routes.dependencies import get_db
router = APIRouter(prefix="/api/production", tags=["Production"])
class ProductionOutputBase(BaseModel):
scenario_id: int
amount: PositiveFloat
description: Optional[str] = None
unit_name: Optional[str] = None
unit_symbol: Optional[str] = None
@field_validator("unit_name", "unit_symbol")
@classmethod
def _normalize_text(cls, value: Optional[str]) -> Optional[str]:
if value is None:
return None
stripped = value.strip()
return stripped or None
class ProductionOutputCreate(ProductionOutputBase):
pass
class ProductionOutputRead(ProductionOutputBase):
id: int
model_config = ConfigDict(from_attributes=True)
@router.post(
"/",
response_model=ProductionOutputRead,
status_code=status.HTTP_201_CREATED,
)
def create_production(
item: ProductionOutputCreate, db: Session = Depends(get_db)
):
db_item = ProductionOutput(**item.model_dump())
db.add(db_item)
db.commit()
db.refresh(db_item)
return db_item
@router.get("/", response_model=List[ProductionOutputRead])
def list_production(db: Session = Depends(get_db)):
return db.query(ProductionOutput).all()

73
routes/reporting.py
View File

@@ -1,73 +0,0 @@
from typing import Any, Dict, List, cast
from fastapi import APIRouter, HTTPException, Request, status
from pydantic import BaseModel
from services.reporting import generate_report
router = APIRouter(prefix="/api/reporting", tags=["Reporting"])
def _validate_payload(payload: Any) -> List[Dict[str, float]]:
if not isinstance(payload, list):
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail="Invalid input format",
)
typed_payload = cast(List[Any], payload)
validated: List[Dict[str, float]] = []
for index, item in enumerate(typed_payload):
if not isinstance(item, dict):
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail=f"Entry at index {index} must be an object",
)
value = cast(Dict[str, Any], item).get("result")
if not isinstance(value, (int, float)):
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail=f"Entry at index {index} must include numeric 'result'",
)
validated.append({"result": float(value)})
return validated
class ReportSummary(BaseModel):
count: int
mean: float
median: float
min: float
max: float
std_dev: float
variance: float
percentile_10: float
percentile_90: float
percentile_5: float
percentile_95: float
value_at_risk_95: float
expected_shortfall_95: float
@router.post("/summary", response_model=ReportSummary)
async def summary_report(request: Request):
payload = await request.json()
validated_payload = _validate_payload(payload)
summary = generate_report(validated_payload)
return ReportSummary(
count=int(summary["count"]),
mean=float(summary["mean"]),
median=float(summary["median"]),
min=float(summary["min"]),
max=float(summary["max"]),
std_dev=float(summary["std_dev"]),
variance=float(summary["variance"]),
percentile_10=float(summary["percentile_10"]),
percentile_90=float(summary["percentile_90"]),
percentile_5=float(summary["percentile_5"]),
percentile_95=float(summary["percentile_95"]),
value_at_risk_95=float(summary["value_at_risk_95"]),
expected_shortfall_95=float(summary["expected_shortfall_95"]),
)

42
routes/scenarios.py
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@@ -1,42 +0,0 @@
from datetime import datetime
from typing import Optional
from fastapi import APIRouter, Depends, HTTPException
from pydantic import BaseModel, ConfigDict
from sqlalchemy.orm import Session
from models.scenario import Scenario
from routes.dependencies import get_db
router = APIRouter(prefix="/api/scenarios", tags=["scenarios"])
# Pydantic schemas
class ScenarioCreate(BaseModel):
name: str
description: Optional[str] = None
class ScenarioRead(ScenarioCreate):
id: int
created_at: datetime
updated_at: Optional[datetime] = None
model_config = ConfigDict(from_attributes=True)
@router.post("/", response_model=ScenarioRead)
def create_scenario(scenario: ScenarioCreate, db: Session = Depends(get_db)):
db_s = db.query(Scenario).filter(Scenario.name == scenario.name).first()
if db_s:
raise HTTPException(status_code=400, detail="Scenario already exists")
new_s = Scenario(name=scenario.name, description=scenario.description)
db.add(new_s)
db.commit()
db.refresh(new_s)
return new_s
@router.get("/", response_model=list[ScenarioRead])
def list_scenarios(db: Session = Depends(get_db)):
return db.query(Scenario).all()

110
routes/settings.py
View File

@@ -1,110 +0,0 @@
from typing import Dict, List
from fastapi import APIRouter, Depends, HTTPException, status
from pydantic import BaseModel, Field, model_validator
from sqlalchemy.orm import Session
from routes.dependencies import get_db
from services.settings import (
CSS_COLOR_DEFAULTS,
get_css_color_settings,
list_css_env_override_rows,
read_css_color_env_overrides,
update_css_color_settings,
get_theme_settings,
save_theme_settings,
)
router = APIRouter(prefix="/api/settings", tags=["Settings"])
class CSSSettingsPayload(BaseModel):
variables: Dict[str, str] = Field(default_factory=dict)
@model_validator(mode="after")
def _validate_allowed_keys(self) -> "CSSSettingsPayload":
invalid = set(self.variables.keys()) - set(CSS_COLOR_DEFAULTS.keys())
if invalid:
invalid_keys = ", ".join(sorted(invalid))
raise ValueError(
f"Unsupported CSS variables: {invalid_keys}."
" Accepted keys align with the default theme variables."
)
return self
class EnvOverride(BaseModel):
css_key: str
env_var: str
value: str
class CSSSettingsResponse(BaseModel):
variables: Dict[str, str]
env_overrides: Dict[str, str] = Field(default_factory=dict)
env_sources: List[EnvOverride] = Field(default_factory=list)
@router.get("/css", response_model=CSSSettingsResponse)
def read_css_settings(db: Session = Depends(get_db)) -> CSSSettingsResponse:
try:
values = get_css_color_settings(db)
env_overrides = read_css_color_env_overrides()
env_sources = [
EnvOverride(**row) for row in list_css_env_override_rows()
]
except ValueError as exc:
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail=str(exc),
) from exc
return CSSSettingsResponse(
variables=values,
env_overrides=env_overrides,
env_sources=env_sources,
)
@router.put(
"/css", response_model=CSSSettingsResponse, status_code=status.HTTP_200_OK
)
def update_css_settings(
payload: CSSSettingsPayload, db: Session = Depends(get_db)
) -> CSSSettingsResponse:
try:
values = update_css_color_settings(db, payload.variables)
env_overrides = read_css_color_env_overrides()
env_sources = [
EnvOverride(**row) for row in list_css_env_override_rows()
]
except ValueError as exc:
raise HTTPException(
status_code=status.HTTP_422_UNPROCESSABLE_CONTENT,
detail=str(exc),
) from exc
return CSSSettingsResponse(
variables=values,
env_overrides=env_overrides,
env_sources=env_sources,
)
class ThemeSettings(BaseModel):
theme_name: str
primary_color: str
secondary_color: str
accent_color: str
background_color: str
text_color: str
@router.post("/theme")
async def update_theme(theme_data: ThemeSettings, db: Session = Depends(get_db)):
data_dict = theme_data.model_dump()
save_theme_settings(db, data_dict)
return {"message": "Theme updated", "theme": data_dict}
@router.get("/theme")
async def get_theme(db: Session = Depends(get_db)):
return get_theme_settings(db)

126
routes/simulations.py
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@@ -1,126 +0,0 @@
from typing import Dict, List, Optional
from fastapi import APIRouter, Depends, HTTPException, status
from pydantic import BaseModel, PositiveInt
from sqlalchemy.orm import Session
from models.parameters import Parameter
from models.scenario import Scenario
from models.simulation_result import SimulationResult
from routes.dependencies import get_db
from services.reporting import generate_report
from services.simulation import run_simulation
router = APIRouter(prefix="/api/simulations", tags=["Simulations"])
class SimulationParameterInput(BaseModel):
name: str
value: float
distribution: Optional[str] = "normal"
std_dev: Optional[float] = None
min: Optional[float] = None
max: Optional[float] = None
mode: Optional[float] = None
class SimulationRunRequest(BaseModel):
scenario_id: int
iterations: PositiveInt = 1000
parameters: Optional[List[SimulationParameterInput]] = None
seed: Optional[int] = None
class SimulationResultItem(BaseModel):
iteration: int
result: float
class SimulationRunResponse(BaseModel):
scenario_id: int
iterations: int
results: List[SimulationResultItem]
summary: Dict[str, float | int]
def _load_parameters(
db: Session, scenario_id: int
) -> List[SimulationParameterInput]:
db_params = (
db.query(Parameter)
.filter(Parameter.scenario_id == scenario_id)
.order_by(Parameter.id)
.all()
)
return [
SimulationParameterInput(
name=item.name,
value=item.value,
)
for item in db_params
]
@router.post("/run", response_model=SimulationRunResponse)
async def simulate(
payload: SimulationRunRequest, db: Session = Depends(get_db)
):
scenario = (
db.query(Scenario).filter(Scenario.id == payload.scenario_id).first()
)
if scenario is None:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="Scenario not found",
)
parameters = payload.parameters or _load_parameters(db, payload.scenario_id)
if not parameters:
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail="No parameters provided",
)
raw_results = run_simulation(
[param.model_dump(exclude_none=True) for param in parameters],
iterations=payload.iterations,
seed=payload.seed,
)
if not raw_results:
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail="Simulation produced no results",
)
# Persist results (replace existing values for scenario)
db.query(SimulationResult).filter(
SimulationResult.scenario_id == payload.scenario_id
).delete()
db.bulk_save_objects(
[
SimulationResult(
scenario_id=payload.scenario_id,
iteration=item["iteration"],
result=item["result"],
)
for item in raw_results
]
)
db.commit()
summary = generate_report(raw_results)
response = SimulationRunResponse(
scenario_id=payload.scenario_id,
iterations=payload.iterations,
results=[
SimulationResultItem(
iteration=int(item["iteration"]),
result=float(item["result"]),
)
for item in raw_results
],
summary=summary,
)
return response

784
routes/ui.py
View File

@@ -1,784 +0,0 @@
from collections import defaultdict
from datetime import datetime, timezone
from typing import Any, Dict, Optional
from fastapi import APIRouter, Depends, Request
from fastapi.responses import HTMLResponse, JSONResponse
from fastapi.templating import Jinja2Templates
from sqlalchemy.orm import Session
from models.capex import Capex
from models.consumption import Consumption
from models.equipment import Equipment
from models.maintenance import Maintenance
from models.opex import Opex
from models.parameters import Parameter
from models.production_output import ProductionOutput
from models.scenario import Scenario
from models.simulation_result import SimulationResult
from routes.dependencies import get_db
from services.reporting import generate_report
from models.currency import Currency
from routes.currencies import DEFAULT_CURRENCY_CODE, _ensure_default_currency
from services.settings import (
CSS_COLOR_DEFAULTS,
get_css_color_settings,
list_css_env_override_rows,
read_css_color_env_overrides,
)
CURRENCY_CHOICES: list[Dict[str, Any]] = [
{"id": "USD", "name": "US Dollar (USD)"},
{"id": "EUR", "name": "Euro (EUR)"},
{"id": "CLP", "name": "Chilean Peso (CLP)"},
{"id": "RMB", "name": "Chinese Yuan (RMB)"},
{"id": "GBP", "name": "British Pound (GBP)"},
{"id": "CAD", "name": "Canadian Dollar (CAD)"},
{"id": "AUD", "name": "Australian Dollar (AUD)"},
]
MEASUREMENT_UNITS: list[Dict[str, Any]] = [
{"id": "tonnes", "name": "Tonnes", "symbol": "t"},
{"id": "kilograms", "name": "Kilograms", "symbol": "kg"},
{"id": "pounds", "name": "Pounds", "symbol": "lb"},
{"id": "liters", "name": "Liters", "symbol": "L"},
{"id": "cubic_meters", "name": "Cubic Meters", "symbol": "m3"},
{"id": "kilowatt_hours", "name": "Kilowatt Hours", "symbol": "kWh"},
]
router = APIRouter()
# Set up Jinja2 templates directory
templates = Jinja2Templates(directory="templates")
def _context(
request: Request, extra: Optional[Dict[str, Any]] = None
) -> Dict[str, Any]:
payload: Dict[str, Any] = {
"request": request,
"current_year": datetime.now(timezone.utc).year,
}
if extra:
payload.update(extra)
return payload
def _render(
request: Request,
template_name: str,
extra: Optional[Dict[str, Any]] = None,
):
context = _context(request, extra)
return templates.TemplateResponse(request, template_name, context)
def _format_currency(value: float) -> str:
return f"${value:,.2f}"
def _format_decimal(value: float) -> str:
return f"{value:,.2f}"
def _format_int(value: int) -> str:
return f"{value:,}"
def _load_scenarios(db: Session) -> Dict[str, Any]:
scenarios: list[Dict[str, Any]] = [
{
"id": item.id,
"name": item.name,
"description": item.description,
}
for item in db.query(Scenario).order_by(Scenario.name).all()
]
return {"scenarios": scenarios}
def _load_parameters(db: Session) -> Dict[str, Any]:
grouped: defaultdict[int, list[Dict[str, Any]]] = defaultdict(list)
for param in db.query(Parameter).order_by(
Parameter.scenario_id, Parameter.id
):
grouped[param.scenario_id].append(
{
"id": param.id,
"name": param.name,
"value": param.value,
"distribution_type": param.distribution_type,
"distribution_parameters": param.distribution_parameters,
}
)
return {"parameters_by_scenario": dict(grouped)}
def _load_costs(db: Session) -> Dict[str, Any]:
capex_grouped: defaultdict[int, list[Dict[str, Any]]] = defaultdict(list)
for capex in db.query(Capex).order_by(Capex.scenario_id, Capex.id).all():
capex_grouped[int(getattr(capex, "scenario_id"))].append(
{
"id": int(getattr(capex, "id")),
"scenario_id": int(getattr(capex, "scenario_id")),
"amount": float(getattr(capex, "amount", 0.0)),
"description": getattr(capex, "description", "") or "",
"currency_code": getattr(capex, "currency_code", "USD")
or "USD",
}
)
opex_grouped: defaultdict[int, list[Dict[str, Any]]] = defaultdict(list)
for opex in db.query(Opex).order_by(Opex.scenario_id, Opex.id).all():
opex_grouped[int(getattr(opex, "scenario_id"))].append(
{
"id": int(getattr(opex, "id")),
"scenario_id": int(getattr(opex, "scenario_id")),
"amount": float(getattr(opex, "amount", 0.0)),
"description": getattr(opex, "description", "") or "",
"currency_code": getattr(opex, "currency_code", "USD") or "USD",
}
)
return {
"capex_by_scenario": dict(capex_grouped),
"opex_by_scenario": dict(opex_grouped),
}
def _load_currencies(db: Session) -> Dict[str, Any]:
items: list[Dict[str, Any]] = []
for c in (
db.query(Currency)
.filter_by(is_active=True)
.order_by(Currency.code)
.all()
):
items.append(
{"id": c.code, "name": f"{c.name} ({c.code})", "symbol": c.symbol}
)
if not items:
items.append({"id": "USD", "name": "US Dollar (USD)", "symbol": "$"})
return {"currency_options": items}
def _load_currency_settings(db: Session) -> Dict[str, Any]:
_ensure_default_currency(db)
records = db.query(Currency).order_by(Currency.code).all()
currencies: list[Dict[str, Any]] = []
for record in records:
code_value = getattr(record, "code")
currencies.append(
{
"id": int(getattr(record, "id")),
"code": code_value,
"name": getattr(record, "name"),
"symbol": getattr(record, "symbol"),
"is_active": bool(getattr(record, "is_active", True)),
"is_default": code_value == DEFAULT_CURRENCY_CODE,
}
)
active_count = sum(1 for item in currencies if item["is_active"])
inactive_count = len(currencies) - active_count
return {
"currencies": currencies,
"currency_stats": {
"total": len(currencies),
"active": active_count,
"inactive": inactive_count,
},
"default_currency_code": DEFAULT_CURRENCY_CODE,
"currency_api_base": "/api/currencies",
}
def _load_css_settings(db: Session) -> Dict[str, Any]:
variables = get_css_color_settings(db)
env_overrides = read_css_color_env_overrides()
env_rows = list_css_env_override_rows()
env_meta = {row["css_key"]: row for row in env_rows}
return {
"css_variables": variables,
"css_defaults": CSS_COLOR_DEFAULTS,
"css_env_overrides": env_overrides,
"css_env_override_rows": env_rows,
"css_env_override_meta": env_meta,
}
def _load_consumption(db: Session) -> Dict[str, Any]:
grouped: defaultdict[int, list[Dict[str, Any]]] = defaultdict(list)
for record in (
db.query(Consumption)
.order_by(Consumption.scenario_id, Consumption.id)
.all()
):
record_id = int(getattr(record, "id"))
scenario_id = int(getattr(record, "scenario_id"))
amount_value = float(getattr(record, "amount", 0.0))
description = getattr(record, "description", "") or ""
unit_name = getattr(record, "unit_name", None)
unit_symbol = getattr(record, "unit_symbol", None)
grouped[scenario_id].append(
{
"id": record_id,
"scenario_id": scenario_id,
"amount": amount_value,
"description": description,
"unit_name": unit_name,
"unit_symbol": unit_symbol,
}
)
return {"consumption_by_scenario": dict(grouped)}
def _load_production(db: Session) -> Dict[str, Any]:
grouped: defaultdict[int, list[Dict[str, Any]]] = defaultdict(list)
for record in (
db.query(ProductionOutput)
.order_by(ProductionOutput.scenario_id, ProductionOutput.id)
.all()
):
record_id = int(getattr(record, "id"))
scenario_id = int(getattr(record, "scenario_id"))
amount_value = float(getattr(record, "amount", 0.0))
description = getattr(record, "description", "") or ""
unit_name = getattr(record, "unit_name", None)
unit_symbol = getattr(record, "unit_symbol", None)
grouped[scenario_id].append(
{
"id": record_id,
"scenario_id": scenario_id,
"amount": amount_value,
"description": description,
"unit_name": unit_name,
"unit_symbol": unit_symbol,
}
)
return {"production_by_scenario": dict(grouped)}
def _load_equipment(db: Session) -> Dict[str, Any]:
grouped: defaultdict[int, list[Dict[str, Any]]] = defaultdict(list)
for record in (
db.query(Equipment).order_by(Equipment.scenario_id, Equipment.id).all()
):
record_id = int(getattr(record, "id"))
scenario_id = int(getattr(record, "scenario_id"))
name_value = getattr(record, "name", "") or ""
description = getattr(record, "description", "") or ""
grouped[scenario_id].append(
{
"id": record_id,
"scenario_id": scenario_id,
"name": name_value,
"description": description,
}
)
return {"equipment_by_scenario": dict(grouped)}
def _load_maintenance(db: Session) -> Dict[str, Any]:
grouped: defaultdict[int, list[Dict[str, Any]]] = defaultdict(list)
for record in (
db.query(Maintenance)
.order_by(Maintenance.scenario_id, Maintenance.maintenance_date)
.all()
):
record_id = int(getattr(record, "id"))
scenario_id = int(getattr(record, "scenario_id"))
equipment_id = int(getattr(record, "equipment_id"))
equipment_obj = getattr(record, "equipment", None)
equipment_name = (
getattr(equipment_obj, "name", "") if equipment_obj else ""
)
maintenance_date = getattr(record, "maintenance_date", None)
cost_value = float(getattr(record, "cost", 0.0))
description = getattr(record, "description", "") or ""
grouped[scenario_id].append(
{
"id": record_id,
"scenario_id": scenario_id,
"equipment_id": equipment_id,
"equipment_name": equipment_name,
"maintenance_date": (
maintenance_date.isoformat() if maintenance_date else ""
),
"cost": cost_value,
"description": description,
}
)
return {"maintenance_by_scenario": dict(grouped)}
def _load_simulations(db: Session) -> Dict[str, Any]:
scenarios: list[Dict[str, Any]] = [
{
"id": item.id,
"name": item.name,
}
for item in db.query(Scenario).order_by(Scenario.name).all()
]
results_grouped: defaultdict[int, list[Dict[str, Any]]] = defaultdict(list)
for record in (
db.query(SimulationResult)
.order_by(SimulationResult.scenario_id, SimulationResult.iteration)
.all()
):
scenario_id = int(getattr(record, "scenario_id"))
results_grouped[scenario_id].append(
{
"iteration": int(getattr(record, "iteration")),
"result": float(getattr(record, "result", 0.0)),
}
)
runs: list[Dict[str, Any]] = []
sample_limit = 20
for item in scenarios:
scenario_id = int(item["id"])
scenario_results = results_grouped.get(scenario_id, [])
summary = (
generate_report(scenario_results)
if scenario_results
else generate_report([])
)
runs.append(
{
"scenario_id": scenario_id,
"scenario_name": item["name"],
"iterations": int(summary.get("count", 0)),
"summary": summary,
"sample_results": scenario_results[:sample_limit],
}
)
return {
"simulation_scenarios": scenarios,
"simulation_runs": runs,
}
def _load_reporting(db: Session) -> Dict[str, Any]:
scenarios = _load_scenarios(db)["scenarios"]
runs = _load_simulations(db)["simulation_runs"]
summaries: list[Dict[str, Any]] = []
runs_by_scenario = {run["scenario_id"]: run for run in runs}
for scenario in scenarios:
scenario_id = scenario["id"]
run = runs_by_scenario.get(scenario_id)
summary = run["summary"] if run else generate_report([])
summaries.append(
{
"scenario_id": scenario_id,
"scenario_name": scenario["name"],
"summary": summary,
"iterations": run["iterations"] if run else 0,
}
)
return {
"report_summaries": summaries,
}
def _load_dashboard(db: Session) -> Dict[str, Any]:
scenarios = _load_scenarios(db)["scenarios"]
parameters_by_scenario = _load_parameters(db)["parameters_by_scenario"]
costs_context = _load_costs(db)
capex_by_scenario = costs_context["capex_by_scenario"]
opex_by_scenario = costs_context["opex_by_scenario"]
consumption_by_scenario = _load_consumption(db)["consumption_by_scenario"]
production_by_scenario = _load_production(db)["production_by_scenario"]
equipment_by_scenario = _load_equipment(db)["equipment_by_scenario"]
maintenance_by_scenario = _load_maintenance(db)["maintenance_by_scenario"]
simulation_context = _load_simulations(db)
simulation_runs = simulation_context["simulation_runs"]
runs_by_scenario = {run["scenario_id"]: run for run in simulation_runs}
def sum_amounts(
grouped: Dict[int, list[Dict[str, Any]]], field: str = "amount"
) -> float:
total = 0.0
for items in grouped.values():
for item in items:
value = item.get(field, 0.0)
if isinstance(value, (int, float)):
total += float(value)
return total
total_capex = sum_amounts(capex_by_scenario)
total_opex = sum_amounts(opex_by_scenario)
total_consumption = sum_amounts(consumption_by_scenario)
total_production = sum_amounts(production_by_scenario)
total_maintenance_cost = sum_amounts(maintenance_by_scenario, field="cost")
total_parameters = sum(
len(items) for items in parameters_by_scenario.values()
)
total_equipment = sum(
len(items) for items in equipment_by_scenario.values()
)
total_maintenance_events = sum(
len(items) for items in maintenance_by_scenario.values()
)
total_simulation_iterations = sum(
run["iterations"] for run in simulation_runs
)
scenario_rows: list[Dict[str, Any]] = []
scenario_labels: list[str] = []
scenario_capex: list[float] = []
scenario_opex: list[float] = []
activity_labels: list[str] = []
activity_production: list[float] = []
activity_consumption: list[float] = []
for scenario in scenarios:
scenario_id = scenario["id"]
scenario_name = scenario["name"]
param_count = len(parameters_by_scenario.get(scenario_id, []))
equipment_count = len(equipment_by_scenario.get(scenario_id, []))
maintenance_count = len(maintenance_by_scenario.get(scenario_id, []))
capex_total = sum(
float(item.get("amount", 0.0))
for item in capex_by_scenario.get(scenario_id, [])
)
opex_total = sum(
float(item.get("amount", 0.0))
for item in opex_by_scenario.get(scenario_id, [])
)
consumption_total = sum(
float(item.get("amount", 0.0))
for item in consumption_by_scenario.get(scenario_id, [])
)
production_total = sum(
float(item.get("amount", 0.0))
for item in production_by_scenario.get(scenario_id, [])
)
run = runs_by_scenario.get(scenario_id)
summary = run["summary"] if run else generate_report([])
iterations = run["iterations"] if run else 0
mean_value = float(summary.get("mean", 0.0))
scenario_rows.append(
{
"scenario_name": scenario_name,
"parameter_count": param_count,
"parameter_display": _format_int(param_count),
"equipment_count": equipment_count,
"equipment_display": _format_int(equipment_count),
"capex_total": capex_total,
"capex_display": _format_currency(capex_total),
"opex_total": opex_total,
"opex_display": _format_currency(opex_total),
"production_total": production_total,
"production_display": _format_decimal(production_total),
"consumption_total": consumption_total,
"consumption_display": _format_decimal(consumption_total),
"maintenance_count": maintenance_count,
"maintenance_display": _format_int(maintenance_count),
"iterations": iterations,
"iterations_display": _format_int(iterations),
"simulation_mean": mean_value,
"simulation_mean_display": _format_decimal(mean_value),
}
)
scenario_labels.append(scenario_name)
scenario_capex.append(capex_total)
scenario_opex.append(opex_total)
activity_labels.append(scenario_name)
activity_production.append(production_total)
activity_consumption.append(consumption_total)
scenario_rows.sort(key=lambda row: row["scenario_name"].lower())
all_simulation_results = [
{"result": float(getattr(item, "result", 0.0))}
for item in db.query(SimulationResult).all()
]
overall_report = generate_report(all_simulation_results)
overall_report_metrics = [
{
"label": "Runs",
"value": _format_int(int(overall_report.get("count", 0))),
},
{
"label": "Mean",
"value": _format_decimal(float(overall_report.get("mean", 0.0))),
},
{
"label": "Median",
"value": _format_decimal(float(overall_report.get("median", 0.0))),
},
{
"label": "Std Dev",
"value": _format_decimal(float(overall_report.get("std_dev", 0.0))),
},
{
"label": "95th Percentile",
"value": _format_decimal(
float(overall_report.get("percentile_95", 0.0))
),
},
{
"label": "VaR (95%)",
"value": _format_decimal(
float(overall_report.get("value_at_risk_95", 0.0))
),
},
{
"label": "Expected Shortfall (95%)",
"value": _format_decimal(
float(overall_report.get("expected_shortfall_95", 0.0))
),
},
]
recent_simulations: list[Dict[str, Any]] = [
{
"scenario_name": run["scenario_name"],
"iterations": run["iterations"],
"iterations_display": _format_int(run["iterations"]),
"mean_display": _format_decimal(
float(run["summary"].get("mean", 0.0))
),
"p95_display": _format_decimal(
float(run["summary"].get("percentile_95", 0.0))
),
}
for run in simulation_runs
if run["iterations"] > 0
]
recent_simulations.sort(key=lambda item: item["iterations"], reverse=True)
recent_simulations = recent_simulations[:5]
upcoming_maintenance: list[Dict[str, Any]] = []
for record in (
db.query(Maintenance)
.order_by(Maintenance.maintenance_date.asc())
.limit(5)
.all()
):
maintenance_date = getattr(record, "maintenance_date", None)
upcoming_maintenance.append(
{
"scenario_name": getattr(
getattr(record, "scenario", None), "name", "Unknown"
),
"equipment_name": getattr(
getattr(record, "equipment", None), "name", "Unknown"
),
"date_display": (
maintenance_date.strftime("%Y-%m-%d")
if maintenance_date
else "—"
),
"cost_display": _format_currency(
float(getattr(record, "cost", 0.0))
),
"description": getattr(record, "description", "") or "—",
}
)
cost_chart_has_data = any(value > 0 for value in scenario_capex) or any(
value > 0 for value in scenario_opex
)
activity_chart_has_data = any(
value > 0 for value in activity_production
) or any(value > 0 for value in activity_consumption)
scenario_cost_chart: Dict[str, list[Any]] = {
"labels": scenario_labels,
"capex": scenario_capex,
"opex": scenario_opex,
}
scenario_activity_chart: Dict[str, list[Any]] = {
"labels": activity_labels,
"production": activity_production,
"consumption": activity_consumption,
}
summary_metrics = [
{"label": "Active Scenarios", "value": _format_int(len(scenarios))},
{"label": "Parameters", "value": _format_int(total_parameters)},
{"label": "CAPEX Total", "value": _format_currency(total_capex)},
{"label": "OPEX Total", "value": _format_currency(total_opex)},
{"label": "Equipment Assets", "value": _format_int(total_equipment)},
{
"label": "Maintenance Events",
"value": _format_int(total_maintenance_events),
},
{"label": "Consumption", "value": _format_decimal(total_consumption)},
{"label": "Production", "value": _format_decimal(total_production)},
{
"label": "Simulation Iterations",
"value": _format_int(total_simulation_iterations),
},
{
"label": "Maintenance Cost",
"value": _format_currency(total_maintenance_cost),
},
]
return {
"summary_metrics": summary_metrics,
"scenario_rows": scenario_rows,
"overall_report_metrics": overall_report_metrics,
"recent_simulations": recent_simulations,
"upcoming_maintenance": upcoming_maintenance,
"scenario_cost_chart": scenario_cost_chart,
"scenario_activity_chart": scenario_activity_chart,
"cost_chart_has_data": cost_chart_has_data,
"activity_chart_has_data": activity_chart_has_data,
"report_available": overall_report.get("count", 0) > 0,
}
@router.get("/", response_class=HTMLResponse)
async def dashboard_root(request: Request, db: Session = Depends(get_db)):
"""Render the primary dashboard landing page."""
return _render(request, "Dashboard.html", _load_dashboard(db))
@router.get("/ui/dashboard", response_class=HTMLResponse)
async def dashboard(request: Request, db: Session = Depends(get_db)):
"""Render the legacy dashboard route for backward compatibility."""
return _render(request, "Dashboard.html", _load_dashboard(db))
@router.get("/ui/dashboard/data", response_class=JSONResponse)
async def dashboard_data(db: Session = Depends(get_db)) -> JSONResponse:
"""Expose dashboard aggregates as JSON for client-side refreshes."""
return JSONResponse(_load_dashboard(db))
@router.get("/ui/scenarios", response_class=HTMLResponse)
async def scenario_form(request: Request, db: Session = Depends(get_db)):
"""Render the scenario creation form."""
context = _load_scenarios(db)
return _render(request, "ScenarioForm.html", context)
@router.get("/ui/parameters", response_class=HTMLResponse)
async def parameter_form(request: Request, db: Session = Depends(get_db)):
"""Render the parameter input form."""
context: Dict[str, Any] = {}
context.update(_load_scenarios(db))
context.update(_load_parameters(db))
return _render(request, "ParameterInput.html", context)
@router.get("/ui/costs", response_class=HTMLResponse)
async def costs_view(request: Request, db: Session = Depends(get_db)):
"""Render the costs view with CAPEX and OPEX data."""
context: Dict[str, Any] = {}
context.update(_load_scenarios(db))
context.update(_load_costs(db))
context.update(_load_currencies(db))
return _render(request, "costs.html", context)
@router.get("/ui/consumption", response_class=HTMLResponse)
async def consumption_view(request: Request, db: Session = Depends(get_db)):
"""Render the consumption view with scenario consumption data."""
context: Dict[str, Any] = {}
context.update(_load_scenarios(db))
context.update(_load_consumption(db))
context["unit_options"] = MEASUREMENT_UNITS
return _render(request, "consumption.html", context)
@router.get("/ui/production", response_class=HTMLResponse)
async def production_view(request: Request, db: Session = Depends(get_db)):
"""Render the production view with scenario production data."""
context: Dict[str, Any] = {}
context.update(_load_scenarios(db))
context.update(_load_production(db))
context["unit_options"] = MEASUREMENT_UNITS
return _render(request, "production.html", context)
@router.get("/ui/equipment", response_class=HTMLResponse)
async def equipment_view(request: Request, db: Session = Depends(get_db)):
"""Render the equipment view with scenario equipment data."""
context: Dict[str, Any] = {}
context.update(_load_scenarios(db))
context.update(_load_equipment(db))
return _render(request, "equipment.html", context)
@router.get("/ui/maintenance", response_class=HTMLResponse)
async def maintenance_view(request: Request, db: Session = Depends(get_db)):
"""Render the maintenance view with scenario maintenance data."""
context: Dict[str, Any] = {}
context.update(_load_scenarios(db))
context.update(_load_equipment(db))
context.update(_load_maintenance(db))
return _render(request, "maintenance.html", context)
@router.get("/ui/simulations", response_class=HTMLResponse)
async def simulations_view(request: Request, db: Session = Depends(get_db)):
"""Render the simulations view with scenario information and recent runs."""
return _render(request, "simulations.html", _load_simulations(db))
@router.get("/ui/reporting", response_class=HTMLResponse)
async def reporting_view(request: Request, db: Session = Depends(get_db)):
"""Render the reporting view with scenario KPI summaries."""
return _render(request, "reporting.html", _load_reporting(db))
@router.get("/ui/settings", response_class=HTMLResponse)
async def settings_view(request: Request, db: Session = Depends(get_db)):
"""Render the settings landing page."""
context = _load_css_settings(db)
return _render(request, "settings.html", context)
@router.get("/ui/currencies", response_class=HTMLResponse)
async def currencies_view(request: Request, db: Session = Depends(get_db)):
"""Render the currency administration page with full currency context."""
context = _load_currency_settings(db)
return _render(request, "currencies.html", context)
@router.get("/login", response_class=HTMLResponse)
async def login_page(request: Request):
return _render(request, "login.html")
@router.get("/register", response_class=HTMLResponse)
async def register_page(request: Request):
return _render(request, "register.html")
@router.get("/profile", response_class=HTMLResponse)
async def profile_page(request: Request):
return _render(request, "profile.html")
@router.get("/forgot-password", response_class=HTMLResponse)
async def forgot_password_page(request: Request):
return _render(request, "forgot_password.html")
@router.get("/theme-settings", response_class=HTMLResponse)
async def theme_settings_page(request: Request, db: Session = Depends(get_db)):
"""Render the theme settings page."""
context = _load_css_settings(db)
return _render(request, "theme_settings.html", context)

107
routes/users.py
View File

@@ -1,107 +0,0 @@
from fastapi import APIRouter, Depends, HTTPException, status
from sqlalchemy.orm import Session
from config.database import get_db
from models.user import User
from services.security import create_access_token, get_current_user
from schemas.user import (
PasswordReset,
PasswordResetRequest,
UserCreate,
UserInDB,
UserLogin,
UserUpdate,
)
router = APIRouter(prefix="/users", tags=["users"])
@router.post("/register", response_model=UserInDB, status_code=status.HTTP_201_CREATED)
async def register_user(user: UserCreate, db: Session = Depends(get_db)):
db_user = db.query(User).filter(User.username == user.username).first()
if db_user:
raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST,
detail="Username already registered")
db_user = db.query(User).filter(User.email == user.email).first()
if db_user:
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST, detail="Email already registered")
# Get or create default role
from models.role import Role
default_role = db.query(Role).filter(Role.name == "user").first()
if not default_role:
default_role = Role(name="user")
db.add(default_role)
db.commit()
db.refresh(default_role)
new_user = User(username=user.username, email=user.email,
role_id=default_role.id)
new_user.set_password(user.password)
db.add(new_user)
db.commit()
db.refresh(new_user)
return new_user
@router.post("/login")
async def login_user(user: UserLogin, db: Session = Depends(get_db)):
db_user = db.query(User).filter(User.username == user.username).first()
if not db_user or not db_user.check_password(user.password):
raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED,
detail="Incorrect username or password")
access_token = create_access_token(subject=db_user.username)
return {"access_token": access_token, "token_type": "bearer"}
@router.get("/me")
async def read_users_me(current_user: User = Depends(get_current_user)):
return current_user
@router.put("/me", response_model=UserInDB)
async def update_user_me(user_update: UserUpdate, current_user: User = Depends(get_current_user), db: Session = Depends(get_db)):
if user_update.username and user_update.username != current_user.username:
existing_user = db.query(User).filter(
User.username == user_update.username).first()
if existing_user:
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST, detail="Username already taken")
setattr(current_user, "username", user_update.username)
if user_update.email and user_update.email != current_user.email:
existing_user = db.query(User).filter(
User.email == user_update.email).first()
if existing_user:
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST, detail="Email already registered")
setattr(current_user, "email", user_update.email)
if user_update.password:
current_user.set_password(user_update.password)
db.add(current_user)
db.commit()
db.refresh(current_user)
return current_user
@router.post("/forgot-password")
async def forgot_password(request: PasswordResetRequest):
# In a real application, this would send an email with a reset token
return {"message": "Password reset email sent (not really)"}
@router.post("/reset-password")
async def reset_password(request: PasswordReset, db: Session = Depends(get_db)):
# In a real application, the token would be verified
user = db.query(User).filter(User.username ==
request.token).first() # Use token as username for test
if not user:
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST, detail="Invalid token or user")
user.set_password(request.new_password)
db.add(user)
db.commit()
return {"message": "Password has been reset successfully"}

41
schemas/user.py
View File

@@ -1,41 +0,0 @@
from pydantic import BaseModel, ConfigDict
class UserCreate(BaseModel):
username: str
email: str
password: str
class UserInDB(BaseModel):
id: int
username: str
email: str
role_id: int
model_config = ConfigDict(from_attributes=True)
class UserLogin(BaseModel):
username: str
password: str
class UserUpdate(BaseModel):
username: str | None = None
email: str | None = None
password: str | None = None
class PasswordResetRequest(BaseModel):
email: str
class PasswordReset(BaseModel):
token: str
new_password: str
class Token(BaseModel):
access_token: str
token_type: str

157
scripts/backfill_currency.py
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@@ -1,157 +0,0 @@
"""
Backfill script to populate currency_id for capex and opex rows using existing currency_code.
Usage:
python scripts/backfill_currency.py --dry-run
python scripts/backfill_currency.py --create-missing
This script is intentionally cautious: it defaults to dry-run mode and will refuse to run
if database connection settings are missing. It supports creating missing currency rows when `--create-missing`
is provided. Always run against a development/staging database first.
"""
from __future__ import annotations
import argparse
import importlib
import sys
from pathlib import Path
from sqlalchemy import text, create_engine
PROJECT_ROOT = Path(__file__).resolve().parent.parent
if str(PROJECT_ROOT) not in sys.path:
sys.path.insert(0, str(PROJECT_ROOT))
def load_database_url() -> str:
try:
db_module = importlib.import_module("config.database")
except RuntimeError as exc:
raise RuntimeError(
"Database configuration missing: set DATABASE_URL or provide granular "
"variables (DATABASE_DRIVER, DATABASE_HOST, DATABASE_PORT, DATABASE_USER, "
"DATABASE_PASSWORD, DATABASE_NAME, optional DATABASE_SCHEMA)."
) from exc
return getattr(db_module, "DATABASE_URL")
def backfill(
db_url: str, dry_run: bool = True, create_missing: bool = False
) -> None:
engine = create_engine(db_url)
with engine.begin() as conn:
# Ensure currency table exists
if db_url.startswith("sqlite:"):
conn.execute(
text(
"SELECT name FROM sqlite_master WHERE type='table' AND name='currency';"
)
)
else:
conn.execute(text("SELECT to_regclass('public.currency');"))
# Note: we don't strictly depend on the above - we assume migration was already applied
# Helper: find or create currency by code
def find_currency_id(code: str):
r = conn.execute(
text("SELECT id FROM currency WHERE code = :code"),
{"code": code},
).fetchone()
if r:
return r[0]
if create_missing:
# insert and return id
conn.execute(
text(
"INSERT INTO currency (code, name, symbol, is_active) VALUES (:c, :n, NULL, TRUE)"
),
{"c": code, "n": code},
)
r2 = conn.execute(
text("SELECT id FROM currency WHERE code = :code"),
{"code": code},
).fetchone()
if not r2:
raise RuntimeError(
f"Unable to determine currency ID for '{code}' after insert"
)
return r2[0]
return None
# Process tables capex and opex
for table in ("capex", "opex"):
# Check if currency_id column exists
try:
cols = (
conn.execute(
text(
f"SELECT 1 FROM information_schema.columns WHERE table_name = '{table}' AND column_name = 'currency_id'"
)
)
if not db_url.startswith("sqlite:")
else [(1,)]
)
except Exception:
cols = [(1,)]
if not cols:
print(f"Skipping {table}: no currency_id column found")
continue
# Find rows where currency_id IS NULL but currency_code exists
rows = conn.execute(
text(
f"SELECT id, currency_code FROM {table} WHERE currency_id IS NULL OR currency_id = ''"
)
)
changed = 0
for r in rows:
rid = r[0]
code = (r[1] or "USD").strip().upper()
cid = find_currency_id(code)
if cid is None:
print(
f"Row {table}:{rid} has unknown currency code '{code}' and create_missing=False; skipping"
)
continue
if dry_run:
print(
f"[DRY RUN] Would set {table}.currency_id = {cid} for row id={rid} (code={code})"
)
else:
conn.execute(
text(
f"UPDATE {table} SET currency_id = :cid WHERE id = :rid"
),
{"cid": cid, "rid": rid},
)
changed += 1
print(f"{table}: processed, changed={changed} (dry_run={dry_run})")
def main() -> None:
parser = argparse.ArgumentParser(
description="Backfill currency_id from currency_code for capex/opex tables"
)
parser.add_argument(
"--dry-run",
action="store_true",
default=True,
help="Show actions without writing",
)
parser.add_argument(
"--create-missing",
action="store_true",
help="Create missing currency rows in the currency table",
)
args = parser.parse_args()
db = load_database_url()
backfill(db, dry_run=args.dry_run, create_missing=args.create_missing)
if __name__ == "__main__":
main()

50
scripts/check_docs_links.py
View File

@@ -1,50 +0,0 @@
"""Simple Markdown link checker for local docs/ files.
Checks only local file links (relative paths) and reports missing targets.
Run from the repository root using the project's Python environment.
"""
import re
from pathlib import Path
ROOT = Path(__file__).resolve().parent.parent
DOCS = ROOT / "docs"
MD_LINK_RE = re.compile(r"\[([^\]]+)\]\(([^)]+)\)")
errors = []
for md in DOCS.rglob("*.md"):
text = md.read_text(encoding="utf-8")
for m in MD_LINK_RE.finditer(text):
label, target = m.groups()
# skip URLs
if (
target.startswith("http://")
or target.startswith("https://")
or target.startswith("#")
):
continue
# strip anchors
target_path = target.split("#")[0]
# if link is to a directory index, allow
candidate = (md.parent / target_path).resolve()
if candidate.exists():
continue
# check common implicit index: target/ -> target/README.md or target/index.md
candidate_dir = md.parent / target_path
if candidate_dir.is_dir():
if (candidate_dir / "README.md").exists() or (
candidate_dir / "index.md"
).exists():
continue
errors.append((str(md.relative_to(ROOT)), target, label))
if errors:
print("Broken local links found:")
for src, tgt, label in errors:
print(f"- {src} -> {tgt} ({label})")
exit(2)
print("No broken local links detected.")

92
scripts/format_docs_md.py
View File

@@ -1,92 +0,0 @@
"""Lightweight Markdown formatter: normalizes first-line H1, adds code-fence language hints for common shebangs, trims trailing whitespace.
This is intentionally small and non-destructive; it touches only files under docs/ and makes safe changes.
"""
import re
from pathlib import Path
DOCS = Path(__file__).resolve().parents[1] / "docs"
CODE_LANG_HINTS = {
"powershell": ("powershell",),
"bash": ("bash", "sh"),
"sql": ("sql",),
"python": ("python",),
}
def add_code_fence_language(match):
fence = match.group(0)
inner = match.group(1)
# If language already present, return unchanged
if fence.startswith("```") and len(fence.splitlines()[0].strip()) > 3:
return fence
# Try to infer language from the code content
code = inner.strip().splitlines()[0] if inner.strip() else ""
lang = ""
if (
code.startswith("$")
or code.startswith("PS")
or code.lower().startswith("powershell")
):
lang = "powershell"
elif (
code.startswith("#")
or code.startswith("import")
or code.startswith("from")
):
lang = "python"
elif re.match(r"^(select|insert|update|create)\b", code.strip(), re.I):
lang = "sql"
elif (
code.startswith("git")
or code.startswith("./")
or code.startswith("sudo")
):
lang = "bash"
if lang:
return f"```{lang}\n{inner}\n```"
return fence
def normalize_file(path: Path):
text = path.read_text(encoding="utf-8")
orig = text
# Trim trailing whitespace and ensure single trailing newline
text = "\n".join(line.rstrip() for line in text.splitlines()) + "\n"
# Ensure first non-empty line is H1
lines = text.splitlines()
for i, ln in enumerate(lines):
if ln.strip():
if not ln.startswith("#"):
lines[i] = "# " + ln
break
text = "\n".join(lines) + "\n"
# Add basic code fence languages where missing (simple heuristic)
text = re.sub(r"```\n([\s\S]*?)\n```", add_code_fence_language, text)
if text != orig:
path.write_text(text, encoding="utf-8")
return True
return False
def main():
changed = []
for p in DOCS.rglob("*.md"):
if p.is_file():
try:
if normalize_file(p):
changed.append(str(p.relative_to(Path.cwd())))
except Exception as e:
print(f"Failed to format {p}: {e}")
if changed:
print("Formatted files:")
for c in changed:
print(" -", c)
else:
print("No formatting changes required.")
if __name__ == "__main__":
main()

189
scripts/migrations/000_base.sql
View File

@@ -1,189 +0,0 @@
-- Baseline migration for CalMiner database schema
-- Date: 2025-10-25
-- Purpose: Consolidate foundational tables and reference data
BEGIN;
-- Currency reference table
CREATE TABLE IF NOT EXISTS currency (
id SERIAL PRIMARY KEY,
code VARCHAR(3) NOT NULL UNIQUE,
name VARCHAR(128) NOT NULL,
symbol VARCHAR(8),
is_active BOOLEAN NOT NULL DEFAULT TRUE
);
INSERT INTO currency (code, name, symbol, is_active)
VALUES
('USD', 'United States Dollar', 'USD$', TRUE),
('EUR', 'Euro', 'EUR', TRUE),
('CLP', 'Chilean Peso', 'CLP$', TRUE),
('RMB', 'Chinese Yuan', 'RMB', TRUE),
('GBP', 'British Pound', 'GBP', TRUE),
('CAD', 'Canadian Dollar', 'CAD$', TRUE),
('AUD', 'Australian Dollar', 'AUD$', TRUE)
ON CONFLICT (code) DO UPDATE
SET name = EXCLUDED.name,
symbol = EXCLUDED.symbol,
is_active = EXCLUDED.is_active;
-- Application-level settings table
CREATE TABLE IF NOT EXISTS application_setting (
id SERIAL PRIMARY KEY,
key VARCHAR(128) NOT NULL UNIQUE,
value TEXT NOT NULL,
value_type VARCHAR(32) NOT NULL DEFAULT 'string',
category VARCHAR(32) NOT NULL DEFAULT 'general',
description TEXT,
is_editable BOOLEAN NOT NULL DEFAULT TRUE,
created_at TIMESTAMPTZ NOT NULL DEFAULT NOW(),
updated_at TIMESTAMPTZ NOT NULL DEFAULT NOW()
);
CREATE UNIQUE INDEX IF NOT EXISTS ux_application_setting_key
ON application_setting (key);
CREATE INDEX IF NOT EXISTS ix_application_setting_category
ON application_setting (category);
-- Measurement unit reference table
CREATE TABLE IF NOT EXISTS measurement_unit (
id SERIAL PRIMARY KEY,
code VARCHAR(64) NOT NULL UNIQUE,
name VARCHAR(128) NOT NULL,
symbol VARCHAR(16),
unit_type VARCHAR(32) NOT NULL,
is_active BOOLEAN NOT NULL DEFAULT TRUE,
created_at TIMESTAMPTZ NOT NULL DEFAULT NOW(),
updated_at TIMESTAMPTZ NOT NULL DEFAULT NOW()
);
INSERT INTO measurement_unit (code, name, symbol, unit_type, is_active)
VALUES
('tonnes', 'Tonnes', 't', 'mass', TRUE),
('kilograms', 'Kilograms', 'kg', 'mass', TRUE),
('pounds', 'Pounds', 'lb', 'mass', TRUE),
('liters', 'Liters', 'L', 'volume', TRUE),
('cubic_meters', 'Cubic Meters', 'm3', 'volume', TRUE),
('kilowatt_hours', 'Kilowatt Hours', 'kWh', 'energy', TRUE)
ON CONFLICT (code) DO UPDATE
SET name = EXCLUDED.name,
symbol = EXCLUDED.symbol,
unit_type = EXCLUDED.unit_type,
is_active = EXCLUDED.is_active;
-- Consumption and production measurement metadata
ALTER TABLE consumption
ADD COLUMN IF NOT EXISTS unit_name VARCHAR(64);
ALTER TABLE consumption
ADD COLUMN IF NOT EXISTS unit_symbol VARCHAR(16);
ALTER TABLE production_output
ADD COLUMN IF NOT EXISTS unit_name VARCHAR(64);
ALTER TABLE production_output
ADD COLUMN IF NOT EXISTS unit_symbol VARCHAR(16);
-- Currency integration for CAPEX and OPEX
ALTER TABLE capex
ADD COLUMN IF NOT EXISTS currency_id INTEGER;
ALTER TABLE opex
ADD COLUMN IF NOT EXISTS currency_id INTEGER;
DO $$
DECLARE
usd_id INTEGER;
BEGIN
-- Ensure currency_id columns align with legacy currency_code values when present
IF EXISTS (
SELECT 1 FROM information_schema.columns
WHERE table_name = 'capex' AND column_name = 'currency_code'
) THEN
UPDATE capex AS c
SET currency_id = cur.id
FROM currency AS cur
WHERE c.currency_code = cur.code
AND (c.currency_id IS DISTINCT FROM cur.id);
END IF;
IF EXISTS (
SELECT 1 FROM information_schema.columns
WHERE table_name = 'opex' AND column_name = 'currency_code'
) THEN
UPDATE opex AS o
SET currency_id = cur.id
FROM currency AS cur
WHERE o.currency_code = cur.code
AND (o.currency_id IS DISTINCT FROM cur.id);
END IF;
SELECT id INTO usd_id FROM currency WHERE code = 'USD';
IF usd_id IS NOT NULL THEN
UPDATE capex SET currency_id = usd_id WHERE currency_id IS NULL;
UPDATE opex SET currency_id = usd_id WHERE currency_id IS NULL;
END IF;
END $$;
ALTER TABLE capex
ALTER COLUMN currency_id SET NOT NULL;
ALTER TABLE opex
ALTER COLUMN currency_id SET NOT NULL;
DO $$
BEGIN
IF NOT EXISTS (
SELECT 1 FROM information_schema.table_constraints
WHERE table_schema = current_schema()
AND table_name = 'capex'
AND constraint_name = 'fk_capex_currency'
) THEN
ALTER TABLE capex
ADD CONSTRAINT fk_capex_currency FOREIGN KEY (currency_id)
REFERENCES currency (id) ON DELETE RESTRICT;
END IF;
IF NOT EXISTS (
SELECT 1 FROM information_schema.table_constraints
WHERE table_schema = current_schema()
AND table_name = 'opex'
AND constraint_name = 'fk_opex_currency'
) THEN
ALTER TABLE opex
ADD CONSTRAINT fk_opex_currency FOREIGN KEY (currency_id)
REFERENCES currency (id) ON DELETE RESTRICT;
END IF;
END $$;
ALTER TABLE capex
DROP COLUMN IF EXISTS currency_code;
ALTER TABLE opex
DROP COLUMN IF EXISTS currency_code;
-- Role-based access control tables
CREATE TABLE IF NOT EXISTS roles (
id SERIAL PRIMARY KEY,
name VARCHAR(255) UNIQUE NOT NULL
);
CREATE TABLE IF NOT EXISTS users (
id SERIAL PRIMARY KEY,
username VARCHAR(255) UNIQUE NOT NULL,
email VARCHAR(255) UNIQUE NOT NULL,
hashed_password VARCHAR(255) NOT NULL,
role_id INTEGER NOT NULL REFERENCES roles (id) ON DELETE RESTRICT
);
CREATE INDEX IF NOT EXISTS ix_users_username ON users (username);
CREATE INDEX IF NOT EXISTS ix_users_email ON users (email);
-- Theme settings configuration table
CREATE TABLE IF NOT EXISTS theme_settings (
id SERIAL PRIMARY KEY,
theme_name VARCHAR(255) UNIQUE NOT NULL,
primary_color VARCHAR(7) NOT NULL,
secondary_color VARCHAR(7) NOT NULL,
accent_color VARCHAR(7) NOT NULL,
background_color VARCHAR(7) NOT NULL,
text_color VARCHAR(7) NOT NULL
);
COMMIT;

268
scripts/seed_data.py
View File

@@ -1,268 +0,0 @@
"""Seed baseline data for CalMiner in an idempotent manner.
Usage examples
--------------
```powershell
# Use existing environment variables (or load from setup_test.env.example)
python scripts/seed_data.py --currencies --units --defaults
# Dry-run to preview actions
python scripts/seed_data.py --currencies --dry-run
```
"""
from __future__ import annotations
import argparse
import logging
from typing import Optional
import psycopg2
from psycopg2 import errors
from psycopg2.extras import execute_values
from scripts.setup_database import DatabaseConfig
logger = logging.getLogger(__name__)
CURRENCY_SEEDS = (
("USD", "United States Dollar", "USD$", True),
("EUR", "Euro", "EUR", True),
("CLP", "Chilean Peso", "CLP$", True),
("RMB", "Chinese Yuan", "RMB", True),
("GBP", "British Pound", "GBP", True),
("CAD", "Canadian Dollar", "CAD$", True),
("AUD", "Australian Dollar", "AUD$", True),
)
MEASUREMENT_UNIT_SEEDS = (
("tonnes", "Tonnes", "t", "mass", True),
("kilograms", "Kilograms", "kg", "mass", True),
("pounds", "Pounds", "lb", "mass", True),
("liters", "Liters", "L", "volume", True),
("cubic_meters", "Cubic Meters", "m3", "volume", True),
("kilowatt_hours", "Kilowatt Hours", "kWh", "energy", True),
)
THEME_SETTING_SEEDS = (
("--color-background", "#f4f5f7", "color",
"theme", "CSS variable --color-background", True),
("--color-surface", "#ffffff", "color",
"theme", "CSS variable --color-surface", True),
("--color-text-primary", "#2a1f33", "color",
"theme", "CSS variable --color-text-primary", True),
("--color-text-secondary", "#624769", "color",
"theme", "CSS variable --color-text-secondary", True),
("--color-text-muted", "#64748b", "color",
"theme", "CSS variable --color-text-muted", True),
("--color-text-subtle", "#94a3b8", "color",
"theme", "CSS variable --color-text-subtle", True),
("--color-text-invert", "#ffffff", "color",
"theme", "CSS variable --color-text-invert", True),
("--color-text-dark", "#0f172a", "color",
"theme", "CSS variable --color-text-dark", True),
("--color-text-strong", "#111827", "color",
"theme", "CSS variable --color-text-strong", True),
("--color-primary", "#5f320d", "color",
"theme", "CSS variable --color-primary", True),
("--color-primary-strong", "#7e4c13", "color",
"theme", "CSS variable --color-primary-strong", True),
("--color-primary-stronger", "#837c15", "color",
"theme", "CSS variable --color-primary-stronger", True),
("--color-accent", "#bff838", "color",
"theme", "CSS variable --color-accent", True),
("--color-border", "#e2e8f0", "color",
"theme", "CSS variable --color-border", True),
("--color-border-strong", "#cbd5e1", "color",
"theme", "CSS variable --color-border-strong", True),
("--color-highlight", "#eef2ff", "color",
"theme", "CSS variable --color-highlight", True),
("--color-panel-shadow", "rgba(15, 23, 42, 0.08)", "color",
"theme", "CSS variable --color-panel-shadow", True),
("--color-panel-shadow-deep", "rgba(15, 23, 42, 0.12)", "color",
"theme", "CSS variable --color-panel-shadow-deep", True),
("--color-surface-alt", "#f8fafc", "color",
"theme", "CSS variable --color-surface-alt", True),
("--color-success", "#047857", "color",
"theme", "CSS variable --color-success", True),
("--color-error", "#b91c1c", "color",
"theme", "CSS variable --color-error", True),
)
def parse_args() -> argparse.Namespace:
parser = argparse.ArgumentParser(description="Seed baseline CalMiner data")
parser.add_argument(
"--currencies", action="store_true", help="Seed currency table"
)
parser.add_argument("--units", action="store_true", help="Seed unit table")
parser.add_argument(
"--theme", action="store_true", help="Seed theme settings"
)
parser.add_argument(
"--defaults", action="store_true", help="Seed default records"
)
parser.add_argument(
"--dry-run", action="store_true", help="Print actions without executing"
)
parser.add_argument(
"--verbose",
"-v",
action="count",
default=0,
help="Increase logging verbosity",
)
return parser.parse_args()
def _configure_logging(args: argparse.Namespace) -> None:
level = logging.WARNING - (10 * min(args.verbose, 2))
logging.basicConfig(
level=max(level, logging.INFO), format="%(levelname)s %(message)s"
)
def main() -> None:
args = parse_args()
run_with_namespace(args)
def run_with_namespace(
args: argparse.Namespace,
*,
config: Optional[DatabaseConfig] = None,
) -> None:
if not hasattr(args, "verbose"):
args.verbose = 0
if not hasattr(args, "dry_run"):
args.dry_run = False
_configure_logging(args)
currencies = bool(getattr(args, "currencies", False))
units = bool(getattr(args, "units", False))
theme = bool(getattr(args, "theme", False))
defaults = bool(getattr(args, "defaults", False))
dry_run = bool(getattr(args, "dry_run", False))
if not any((currencies, units, theme, defaults)):
logger.info("No seeding options provided; exiting")
return
config = config or DatabaseConfig.from_env()
with psycopg2.connect(config.application_dsn()) as conn:
conn.autocommit = True
with conn.cursor() as cursor:
if currencies:
_seed_currencies(cursor, dry_run=dry_run)
if units:
_seed_units(cursor, dry_run=dry_run)
if theme:
_seed_theme(cursor, dry_run=dry_run)
if defaults:
_seed_defaults(cursor, dry_run=dry_run)
def _seed_currencies(cursor, *, dry_run: bool) -> None:
logger.info("Seeding currency table (%d rows)", len(CURRENCY_SEEDS))
if dry_run:
for code, name, symbol, active in CURRENCY_SEEDS:
logger.info("Dry run: would upsert currency %s (%s)", code, name)
return
execute_values(
cursor,
"""
INSERT INTO currency (code, name, symbol, is_active)
VALUES %s
ON CONFLICT (code) DO UPDATE
SET name = EXCLUDED.name,
symbol = EXCLUDED.symbol,
is_active = EXCLUDED.is_active
""",
CURRENCY_SEEDS,
)
logger.info("Currency seed complete")
def _seed_units(cursor, *, dry_run: bool) -> None:
total = len(MEASUREMENT_UNIT_SEEDS)
logger.info("Seeding measurement_unit table (%d rows)", total)
if dry_run:
for code, name, symbol, unit_type, _ in MEASUREMENT_UNIT_SEEDS:
logger.info(
"Dry run: would upsert measurement unit %s (%s - %s)",
code,
name,
unit_type,
)
return
try:
execute_values(
cursor,
"""
INSERT INTO measurement_unit (code, name, symbol, unit_type, is_active)
VALUES %s
ON CONFLICT (code) DO UPDATE
SET name = EXCLUDED.name,
symbol = EXCLUDED.symbol,
unit_type = EXCLUDED.unit_type,
is_active = EXCLUDED.is_active
""",
MEASUREMENT_UNIT_SEEDS,
)
except errors.UndefinedTable:
logger.warning(
"measurement_unit table does not exist; skipping unit seeding."
)
cursor.connection.rollback()
return
logger.info("Measurement unit seed complete")
def _seed_theme(cursor, *, dry_run: bool) -> None:
logger.info("Seeding theme settings (%d rows)", len(THEME_SETTING_SEEDS))
if dry_run:
for key, value, _, _, _, _ in THEME_SETTING_SEEDS:
logger.info(
"Dry run: would upsert theme setting %s = %s", key, value)
return
try:
execute_values(
cursor,
"""
INSERT INTO application_setting (key, value, value_type, category, description, is_editable)
VALUES %s
ON CONFLICT (key) DO UPDATE
SET value = EXCLUDED.value,
value_type = EXCLUDED.value_type,
category = EXCLUDED.category,
description = EXCLUDED.description,
is_editable = EXCLUDED.is_editable
""",
THEME_SETTING_SEEDS,
)
except errors.UndefinedTable:
logger.warning(
"application_setting table does not exist; skipping theme seeding."
)
cursor.connection.rollback()
return
logger.info("Theme settings seed complete")
def _seed_defaults(cursor, *, dry_run: bool) -> None:
logger.info("Seeding default records")
_seed_theme(cursor, dry_run=dry_run)
logger.info("Default records seed complete")
if __name__ == "__main__":
main()

1233
scripts/setup_database.py
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File diff suppressed because it is too large Load Diff

79
services/reporting.py
View File

@@ -1,79 +0,0 @@
from statistics import mean, median, pstdev
from typing import Any, Dict, Iterable, List, Mapping, Union, cast
def _extract_results(simulation_results: Iterable[object]) -> List[float]:
values: List[float] = []
for item in simulation_results:
if not isinstance(item, Mapping):
continue
mapping_item = cast(Mapping[str, Any], item)
value = mapping_item.get("result")
if isinstance(value, (int, float)):
values.append(float(value))
return values
def _percentile(values: List[float], percentile: float) -> float:
if not values:
return 0.0
sorted_values = sorted(values)
if len(sorted_values) == 1:
return sorted_values[0]
index = (percentile / 100) * (len(sorted_values) - 1)
lower = int(index)
upper = min(lower + 1, len(sorted_values) - 1)
weight = index - lower
return sorted_values[lower] * (1 - weight) + sorted_values[upper] * weight
def generate_report(
simulation_results: List[Dict[str, float]],
) -> Dict[str, Union[float, int]]:
"""Aggregate basic statistics for simulation outputs."""
values = _extract_results(simulation_results)
if not values:
return {
"count": 0,
"mean": 0.0,
"median": 0.0,
"min": 0.0,
"max": 0.0,
"std_dev": 0.0,
"variance": 0.0,
"percentile_10": 0.0,
"percentile_90": 0.0,
"percentile_5": 0.0,
"percentile_95": 0.0,
"value_at_risk_95": 0.0,
"expected_shortfall_95": 0.0,
}
summary: Dict[str, Union[float, int]] = {
"count": len(values),
"mean": mean(values),
"median": median(values),
"min": min(values),
"max": max(values),
"percentile_10": _percentile(values, 10),
"percentile_90": _percentile(values, 90),
"percentile_5": _percentile(values, 5),
"percentile_95": _percentile(values, 95),
}
std_dev = pstdev(values) if len(values) > 1 else 0.0
summary["std_dev"] = std_dev
summary["variance"] = std_dev**2
var_95 = summary["percentile_5"]
summary["value_at_risk_95"] = var_95
tail_values = [value for value in values if value <= var_95]
if tail_values:
summary["expected_shortfall_95"] = mean(tail_values)
else:
summary["expected_shortfall_95"] = var_95
return summary

59
services/security.py
View File

@@ -1,59 +0,0 @@
from datetime import datetime, timedelta
from typing import Any, Union
from fastapi import HTTPException, status, Depends
from fastapi.security import OAuth2PasswordBearer
from jose import jwt, JWTError
from passlib.context import CryptContext
from sqlalchemy.orm import Session
from config.database import get_db
ACCESS_TOKEN_EXPIRE_MINUTES = 30
SECRET_KEY = "your-secret-key" # Change this in production
ALGORITHM = "HS256"
pwd_context = CryptContext(schemes=["pbkdf2_sha256"], deprecated="auto")
oauth2_scheme = OAuth2PasswordBearer(tokenUrl="users/login")
def create_access_token(
subject: Union[str, Any], expires_delta: Union[timedelta, None] = None
) -> str:
if expires_delta:
expire = datetime.utcnow() + expires_delta
else:
expire = datetime.utcnow() + timedelta(minutes=ACCESS_TOKEN_EXPIRE_MINUTES)
to_encode = {"exp": expire, "sub": str(subject)}
encoded_jwt = jwt.encode(to_encode, SECRET_KEY, algorithm=ALGORITHM)
return encoded_jwt
def verify_password(plain_password: str, hashed_password: str) -> bool:
return pwd_context.verify(plain_password, hashed_password)
def get_password_hash(password: str) -> str:
return pwd_context.hash(password)
async def get_current_user(token: str = Depends(oauth2_scheme), db: Session = Depends(get_db)):
from models.user import User
credentials_exception = HTTPException(
status_code=status.HTTP_401_UNAUTHORIZED,
detail="Could not validate credentials",
headers={"WWW-Authenticate": "Bearer"},
)
try:
payload = jwt.decode(token, SECRET_KEY, algorithms=[ALGORITHM])
username = payload.get("sub")
if username is None:
raise credentials_exception
except JWTError:
raise credentials_exception
user = db.query(User).filter(User.username == username).first()
if user is None:
raise credentials_exception
return user

230
services/settings.py
View File

@@ -1,230 +0,0 @@
from __future__ import annotations
import os
import re
from typing import Dict, Mapping
from sqlalchemy.orm import Session
from models.application_setting import ApplicationSetting
from models.theme_setting import ThemeSetting # Import ThemeSetting model
CSS_COLOR_CATEGORY = "theme"
CSS_COLOR_VALUE_TYPE = "color"
CSS_ENV_PREFIX = "CALMINER_THEME_"
CSS_COLOR_DEFAULTS: Dict[str, str] = {
"--color-background": "#f4f5f7",
"--color-surface": "#ffffff",
"--color-text-primary": "#2a1f33",
"--color-text-secondary": "#624769",
"--color-text-muted": "#64748b",
"--color-text-subtle": "#94a3b8",
"--color-text-invert": "#ffffff",
"--color-text-dark": "#0f172a",
"--color-text-strong": "#111827",
"--color-primary": "#5f320d",
"--color-primary-strong": "#7e4c13",
"--color-primary-stronger": "#837c15",
"--color-accent": "#bff838",
"--color-border": "#e2e8f0",
"--color-border-strong": "#cbd5e1",
"--color-highlight": "#eef2ff",
"--color-panel-shadow": "rgba(15, 23, 42, 0.08)",
"--color-panel-shadow-deep": "rgba(15, 23, 42, 0.12)",
"--color-surface-alt": "#f8fafc",
"--color-success": "#047857",
"--color-error": "#b91c1c",
}
_COLOR_VALUE_PATTERN = re.compile(
r"^(#([0-9a-fA-F]{3}|[0-9a-fA-F]{6}|[0-9a-fA-F]{8})|rgba?\([^)]+\)|hsla?\([^)]+\))$",
re.IGNORECASE,
)
def ensure_css_color_settings(db: Session) -> Dict[str, ApplicationSetting]:
"""Ensure the CSS color defaults exist in the settings table."""
existing = (
db.query(ApplicationSetting)
.filter(ApplicationSetting.key.in_(CSS_COLOR_DEFAULTS.keys()))
.all()
)
by_key = {setting.key: setting for setting in existing}
created = False
for key, default_value in CSS_COLOR_DEFAULTS.items():
if key in by_key:
continue
setting = ApplicationSetting(
key=key,
value=default_value,
value_type=CSS_COLOR_VALUE_TYPE,
category=CSS_COLOR_CATEGORY,
description=f"CSS variable {key}",
is_editable=True,
)
db.add(setting)
by_key[key] = setting
created = True
if created:
db.commit()
for key, setting in by_key.items():
db.refresh(setting)
return by_key
def get_css_color_settings(db: Session) -> Dict[str, str]:
"""Return CSS color variables, filling missing values with defaults."""
settings = ensure_css_color_settings(db)
values: Dict[str, str] = {
key: settings[key].value if key in settings else default
for key, default in CSS_COLOR_DEFAULTS.items()
}
env_overrides = read_css_color_env_overrides(os.environ)
if env_overrides:
values.update(env_overrides)
return values
def update_css_color_settings(
db: Session, updates: Mapping[str, str]
) -> Dict[str, str]:
"""Persist provided CSS color overrides and return the final values."""
if not updates:
return get_css_color_settings(db)
invalid_keys = sorted(set(updates.keys()) - set(CSS_COLOR_DEFAULTS.keys()))
if invalid_keys:
invalid_list = ", ".join(invalid_keys)
raise ValueError(f"Unsupported CSS variables: {invalid_list}")
normalized: Dict[str, str] = {}
for key, value in updates.items():
normalized[key] = _normalize_color_value(value)
settings = ensure_css_color_settings(db)
changed = False
for key, value in normalized.items():
setting = settings[key]
if setting.value != value:
setting.value = value
changed = True
if setting.value_type != CSS_COLOR_VALUE_TYPE:
setting.value_type = CSS_COLOR_VALUE_TYPE
changed = True
if setting.category != CSS_COLOR_CATEGORY:
setting.category = CSS_COLOR_CATEGORY
changed = True
if not setting.is_editable:
setting.is_editable = True
changed = True
if changed:
db.commit()
for key in normalized.keys():
db.refresh(settings[key])
return get_css_color_settings(db)
def read_css_color_env_overrides(
env: Mapping[str, str] | None = None,
) -> Dict[str, str]:
"""Return validated CSS overrides sourced from environment variables."""
if env is None:
env = os.environ
overrides: Dict[str, str] = {}
for css_key in CSS_COLOR_DEFAULTS.keys():
env_name = css_key_to_env_var(css_key)
raw_value = env.get(env_name)
if raw_value is None:
continue
overrides[css_key] = _normalize_color_value(raw_value)
return overrides
def _normalize_color_value(value: str) -> str:
if not isinstance(value, str):
raise ValueError("Color value must be a string")
trimmed = value.strip()
if not trimmed:
raise ValueError("Color value cannot be empty")
if not _COLOR_VALUE_PATTERN.match(trimmed):
raise ValueError(
"Color value must be a hex code or an rgb/rgba/hsl/hsla expression"
)
_validate_functional_color(trimmed)
return trimmed
def _validate_functional_color(value: str) -> None:
lowered = value.lower()
if lowered.startswith("rgb(") or lowered.startswith("hsl("):
_ensure_component_count(value, expected=3)
elif lowered.startswith("rgba(") or lowered.startswith("hsla("):
_ensure_component_count(value, expected=4)
def _ensure_component_count(value: str, expected: int) -> None:
if not value.endswith(")"):
raise ValueError(
"Color function expressions must end with a closing parenthesis"
)
inner = value[value.index("(") + 1: -1]
parts = [segment.strip() for segment in inner.split(",")]
if len(parts) != expected:
raise ValueError(
"Color function expressions must provide the expected number of components"
)
if any(not component for component in parts):
raise ValueError("Color function components cannot be empty")
def css_key_to_env_var(css_key: str) -> str:
sanitized = css_key.lstrip("-").replace("-", "_").upper()
return f"{CSS_ENV_PREFIX}{sanitized}"
def list_css_env_override_rows(
env: Mapping[str, str] | None = None,
) -> list[Dict[str, str]]:
overrides = read_css_color_env_overrides(env)
rows: list[Dict[str, str]] = []
for css_key, value in overrides.items():
rows.append(
{
"css_key": css_key,
"env_var": css_key_to_env_var(css_key),
"value": value,
}
)
return rows
def save_theme_settings(db: Session, theme_data: dict):
theme = db.query(ThemeSetting).first() or ThemeSetting()
for key, value in theme_data.items():
setattr(theme, key, value)
db.add(theme)
db.commit()
db.refresh(theme)
return theme
def get_theme_settings(db: Session):
theme = db.query(ThemeSetting).first()
if theme:
return {c.name: getattr(theme, c.name) for c in theme.__table__.columns}
return {}

144
services/simulation.py
View File

@@ -1,144 +0,0 @@
from __future__ import annotations
from dataclasses import dataclass
from random import Random
from typing import Dict, List, Literal, Optional, Sequence
DEFAULT_STD_DEV_RATIO = 0.1
DEFAULT_UNIFORM_SPAN_RATIO = 0.15
DistributionType = Literal["normal", "uniform", "triangular"]
@dataclass
class SimulationParameter:
name: str
base_value: float
distribution: DistributionType
std_dev: Optional[float] = None
minimum: Optional[float] = None
maximum: Optional[float] = None
mode: Optional[float] = None
def _ensure_positive_span(span: float, fallback: float) -> float:
return span if span and span > 0 else fallback
def _compile_parameters(
parameters: Sequence[Dict[str, float]],
) -> List[SimulationParameter]:
compiled: List[SimulationParameter] = []
for index, item in enumerate(parameters):
if "value" not in item:
raise ValueError(f"Parameter at index {index} must include 'value'")
name = str(item.get("name", f"param_{index}"))
base_value = float(item["value"])
distribution = str(item.get("distribution", "normal")).lower()
if distribution not in {"normal", "uniform", "triangular"}:
raise ValueError(
f"Parameter '{name}' has unsupported distribution '{distribution}'"
)
span_default = abs(base_value) * DEFAULT_UNIFORM_SPAN_RATIO or 1.0
if distribution == "normal":
std_dev = item.get("std_dev")
std_dev_value = (
float(std_dev)
if std_dev is not None
else abs(base_value) * DEFAULT_STD_DEV_RATIO or 1.0
)
compiled.append(
SimulationParameter(
name=name,
base_value=base_value,
distribution="normal",
std_dev=_ensure_positive_span(std_dev_value, 1.0),
)
)
continue
minimum = item.get("min")
maximum = item.get("max")
if minimum is None or maximum is None:
minimum = base_value - span_default
maximum = base_value + span_default
minimum = float(minimum)
maximum = float(maximum)
if minimum >= maximum:
raise ValueError(
f"Parameter '{name}' requires 'min' < 'max' for {distribution} distribution"
)
if distribution == "uniform":
compiled.append(
SimulationParameter(
name=name,
base_value=base_value,
distribution="uniform",
minimum=minimum,
maximum=maximum,
)
)
else: # triangular
mode = item.get("mode")
if mode is None:
mode = base_value
mode_value = float(mode)
if not (minimum <= mode_value <= maximum):
raise ValueError(
f"Parameter '{name}' mode must be within min/max bounds for triangular distribution"
)
compiled.append(
SimulationParameter(
name=name,
base_value=base_value,
distribution="triangular",
minimum=minimum,
maximum=maximum,
mode=mode_value,
)
)
return compiled
def _sample_parameter(rng: Random, param: SimulationParameter) -> float:
if param.distribution == "normal":
assert param.std_dev is not None
return rng.normalvariate(param.base_value, param.std_dev)
if param.distribution == "uniform":
assert param.minimum is not None and param.maximum is not None
return rng.uniform(param.minimum, param.maximum)
# triangular
assert (
param.minimum is not None
and param.maximum is not None
and param.mode is not None
)
return rng.triangular(param.minimum, param.maximum, param.mode)
def run_simulation(
parameters: Sequence[Dict[str, float]],
iterations: int = 1000,
seed: Optional[int] = None,
) -> List[Dict[str, float]]:
"""Run a lightweight Monte Carlo simulation using configurable distributions."""
if iterations <= 0:
return []
compiled_params = _compile_parameters(parameters)
if not compiled_params:
return []
rng = Random(seed)
results: List[Dict[str, float]] = []
for iteration in range(1, iterations + 1):
total = 0.0
for param in compiled_params:
sample = _sample_parameter(rng, param)
total += sample
results.append({"iteration": iteration, "result": total})
return results

146
static/css/main.css
View File

@@ -1,25 +1,29 @@
:root {
--color-background: #f4f5f7;
--color-surface: #ffffff;
--color-text-primary: #2a1f33;
--color-text-secondary: #624769;
--color-text-muted: #64748b;
--color-text-subtle: #94a3b8;
--bg: #0b0f14;
--bg-2: #0f141b;
--card: #151b23;
--text: #e6edf3;
--muted: #a9b4c0;
--brand: #f1b21a;
--brand-2: #f6c648;
--brand-3: #f9d475;
--accent: #2ba58f;
--danger: #d14b4b;
--shadow: 0 10px 30px rgba(0, 0, 0, 0.35);
--radius: 14px;
--radius-sm: 10px;
--container: 1180px;
--muted: var(--muted);
--color-text-subtle: rgba(169, 180, 192, 0.6);
--color-text-invert: #ffffff;
--color-text-dark: #0f172a;
--color-text-strong: #111827;
--color-primary: #5f320d;
--color-primary-strong: #7e4c13;
--color-primary-stronger: #837c15;
--color-accent: #bff838;
--color-border: #e2e8f0;
--color-border-strong: #cbd5e1;
--color-highlight: #eef2ff;
--color-panel-shadow: rgba(15, 23, 42, 0.08);
--color-panel-shadow-deep: rgba(15, 23, 42, 0.12);
--color-surface-alt: #f8fafc;
--color-success: #047857;
--color-error: #b91c1c;
--color-border: rgba(255, 255, 255, 0.08);
--color-border-strong: rgba(255, 255, 255, 0.12);
--color-highlight: rgba(241, 178, 26, 0.08);
--color-panel-shadow: rgba(0, 0, 0, 0.25);
--color-panel-shadow-deep: rgba(0, 0, 0, 0.35);
--color-surface-alt: rgba(21, 27, 35, 0.7);
--space-2xs: 0.25rem;
--space-xs: 0.5rem;
--space-sm: 0.75rem;
@@ -33,15 +37,30 @@
--font-size-lg: 1.25rem;
--font-size-xl: 1.5rem;
--font-size-2xl: 2rem;
--panel-radius: 12px;
--table-radius: 10px;
--panel-radius: var(--radius);
--table-radius: var(--radius-sm);
}
* {
box-sizing: border-box;
}
html,
body {
height: 100%;
}
body {
margin: 0;
font-family: "Segoe UI", Tahoma, Geneva, Verdana, sans-serif;
background-color: var(--color-background);
color: var(--color-text-primary);
font-family: ui-sans-serif, system-ui, -apple-system, 'Segoe UI', 'Roboto',
Helvetica, Arial, 'Apple Color Emoji', 'Segoe UI Emoji';
color: var(--text);
background: linear-gradient(180deg, var(--bg) 0%, var(--bg-2) 100%);
line-height: 1.45;
}
a {
color: var(--brand);
}
.app-layout {
@@ -51,7 +70,7 @@ body {
.app-sidebar {
width: 264px;
background-color: var(--color-primary);
background-color: var(--card);
color: var(--color-text-invert);
display: flex;
flex-direction: column;
@@ -59,6 +78,7 @@ body {
position: sticky;
top: 0;
height: 100vh;
border-right: 1px solid var(--color-border);
}
.sidebar-inner {
@@ -82,11 +102,7 @@ body {
width: 44px;
height: 44px;
border-radius: 12px;
background: linear-gradient(
0deg,
var(--color-primary-stronger),
var(--color-accent)
);
background: linear-gradient(0deg, var(--brand-3), var(--accent));
color: var(--color-text-invert);
font-weight: 700;
font-size: 1.1rem;
@@ -207,7 +223,7 @@ body {
}
.app-main {
background-color: var(--color-background);
background-color: var(--bg);
display: flex;
flex-direction: column;
flex: 1;
@@ -240,7 +256,7 @@ body {
.dashboard-subtitle {
margin: 0.35rem 0 0;
color: var(--color-text-muted);
color: var(--muted);
}
.dashboard-actions {
@@ -259,7 +275,7 @@ body {
.page-subtitle {
margin-top: 0.35rem;
color: var(--color-text-muted);
color: var(--muted);
font-size: 0.95rem;
}
@@ -271,13 +287,14 @@ body {
}
.settings-card {
background: var(--color-surface);
border-radius: 12px;
background: var(--card);
border-radius: var(--radius);
padding: 1.5rem;
box-shadow: 0 4px 14px var(--color-panel-shadow);
box-shadow: var(--shadow);
display: flex;
flex-direction: column;
gap: 0.75rem;
border: 1px solid var(--color-border);
}
.settings-card h2 {
@@ -287,7 +304,7 @@ body {
.settings-card p {
margin: 0;
color: var(--color-text-muted);
color: var(--muted);
}
.settings-card-note {
@@ -311,7 +328,7 @@ body {
.color-form-field.is-env-override {
background: rgba(191, 248, 56, 0.12);
border-color: var(--color-accent);
border-color: var(--accent);
}
.color-field-header {
@@ -319,13 +336,13 @@ body {
justify-content: space-between;
gap: var(--space-sm);
font-weight: 600;
color: var(--color-text-strong);
font-family: "Fira Code", "Consolas", "Courier New", monospace;
color: var(--text);
font-family: 'Fira Code', 'Consolas', 'Courier New', monospace;
font-size: 0.85rem;
}
.color-field-default {
color: var(--color-text-muted);
color: var(--muted);
font-weight: 500;
}
@@ -337,7 +354,7 @@ body {
.color-env-flag {
font-size: 0.78rem;
font-weight: 600;
color: var(--color-accent);
color: var(--accent);
text-transform: uppercase;
letter-spacing: 0.04em;
}
@@ -349,7 +366,7 @@ body {
}
.color-value-input {
font-family: "Fira Code", "Consolas", "Courier New", monospace;
font-family: 'Fira Code', 'Consolas', 'Courier New', monospace;
}
.color-value-input[disabled] {
@@ -378,7 +395,7 @@ body {
}
.env-overrides-table code {
font-family: "Fira Code", "Consolas", "Courier New", monospace;
font-family: 'Fira Code', 'Consolas', 'Courier New', monospace;
font-size: 0.85rem;
}
@@ -391,7 +408,7 @@ body {
border-radius: 999px;
font-weight: 600;
text-decoration: none;
background: var(--color-primary);
background: var(--brand);
color: var(--color-text-invert);
transition: transform 0.2s ease, box-shadow 0.2s ease;
}
@@ -410,26 +427,27 @@ body {
}
.metric-card {
background: var(--color-surface);
border-radius: 12px;
background: var(--card);
border-radius: var(--radius);
padding: 1.2rem 1.4rem;
box-shadow: 0 4px 14px var(--color-panel-shadow);
box-shadow: var(--shadow);
display: flex;
flex-direction: column;
gap: 0.35rem;
border: 1px solid var(--color-border);
}
.metric-label {
font-size: 0.82rem;
text-transform: uppercase;
letter-spacing: 0.04em;
color: var(--color-text-muted);
color: var(--muted);
}
.metric-value {
font-size: 1.45rem;
font-weight: 700;
color: var(--color-text-dark);
color: var(--muted);
}
.dashboard-charts {
@@ -522,7 +540,7 @@ body {
}
.list-detail {
color: var(--color-text-secondary);
color: var(--muted);
font-size: 0.95rem;
}
@@ -532,7 +550,7 @@ body {
}
.btn.is-loading::after {
content: "";
content: '';
width: 0.85rem;
height: 0.85rem;
border: 2px solid rgba(255, 255, 255, 0.6);
@@ -550,7 +568,7 @@ body {
}
.panel {
background-color: var(--color-surface);
background-color: var(--card);
border-radius: var(--panel-radius);
padding: var(--space-xl);
box-shadow: 0 2px 8px var(--color-panel-shadow);
@@ -560,7 +578,7 @@ body {
.panel h2,
.panel h3 {
font-weight: 700;
color: var(--color-text-dark);
color: var(--text);
margin: 0 0 var(--space-sm);
}
@@ -583,7 +601,7 @@ body {
flex-direction: column;
gap: var(--space-sm);
font-weight: 600;
color: var(--color-text-strong);
color: var(--text);
}
.form-grid input,
@@ -598,7 +616,7 @@ body {
.form-grid input:focus,
.form-grid textarea:focus,
.form-grid select:focus {
outline: 2px solid var(--color-primary-strong);
outline: 2px solid var(--brand-2);
outline-offset: 1px;
}
@@ -624,13 +642,13 @@ body {
}
.btn.primary {
background-color: var(--color-primary-strong);
background-color: var(--brand-2);
color: var(--color-text-invert);
}
.btn.primary:hover,
.btn.primary:focus {
background-color: var(--color-primary-stronger);
background-color: var(--brand-3);
}
.result-output {
@@ -638,14 +656,14 @@ body {
color: var(--color-surface-alt);
padding: 1rem;
border-radius: 8px;
font-family: "Fira Code", "Consolas", "Courier New", monospace;
font-family: 'Fira Code', 'Consolas', 'Courier New', monospace;
overflow-x: auto;
margin-top: 1.5rem;
}
.monospace-input {
width: 100%;
font-family: "Fira Code", "Consolas", "Courier New", monospace;
font-family: 'Fira Code', 'Consolas', 'Courier New', monospace;
min-height: 120px;
}
@@ -670,7 +688,7 @@ table {
}
thead {
background-color: var(--color-primary);
background-color: var(--brand);
color: var(--color-text-invert);
}
@@ -687,7 +705,7 @@ tbody tr:nth-child(even) {
.empty-state {
margin-top: 1.5rem;
color: var(--color-text-muted);
color: var(--muted);
font-style: italic;
}
@@ -701,15 +719,15 @@ tbody tr:nth-child(even) {
}
.feedback.success {
color: var(--color-success);
color: var(--accent);
}
.feedback.error {
color: var(--color-error);
color: var(--danger);
}
.site-footer {
background-color: var(--color-primary);
background-color: var(--brand);
color: var(--color-text-invert);
margin-top: 3rem;
}

205
static/js/consumption.js
View File

@@ -1,205 +0,0 @@
document.addEventListener("DOMContentLoaded", () => {
const dataElement = document.getElementById("consumption-data");
let data = { scenarios: [], consumption: {}, unit_options: [] };
if (dataElement) {
try {
const parsed = JSON.parse(dataElement.textContent || "{}");
if (parsed && typeof parsed === "object") {
data = {
scenarios: Array.isArray(parsed.scenarios) ? parsed.scenarios : [],
consumption:
parsed.consumption && typeof parsed.consumption === "object"
? parsed.consumption
: {},
unit_options: Array.isArray(parsed.unit_options)
? parsed.unit_options
: [],
};
}
} catch (error) {
console.error("Unable to parse consumption data", error);
}
}
const consumptionByScenario = data.consumption;
const filterSelect = document.getElementById("consumption-scenario-filter");
const tableWrapper = document.getElementById("consumption-table-wrapper");
const tableBody = document.getElementById("consumption-table-body");
const emptyState = document.getElementById("consumption-empty");
const form = document.getElementById("consumption-form");
const feedbackEl = document.getElementById("consumption-feedback");
const unitSelect = document.getElementById("consumption-form-unit");
const unitSymbolInput = document.getElementById(
"consumption-form-unit-symbol"
);
const showFeedback = (message, type = "success") => {
if (!feedbackEl) {
return;
}
feedbackEl.textContent = message;
feedbackEl.classList.remove("hidden", "success", "error");
feedbackEl.classList.add(type);
};
const hideFeedback = () => {
if (!feedbackEl) {
return;
}
feedbackEl.classList.add("hidden");
feedbackEl.textContent = "";
};
const formatAmount = (value) =>
Number(value).toLocaleString(undefined, {
minimumFractionDigits: 2,
maximumFractionDigits: 2,
});
const formatMeasurement = (amount, symbol, name) => {
if (symbol) {
return `${formatAmount(amount)} ${symbol}`;
}
if (name) {
return `${formatAmount(amount)} ${name}`;
}
return formatAmount(amount);
};
const renderConsumptionRows = (scenarioId) => {
if (!tableBody || !tableWrapper || !emptyState) {
return;
}
const key = String(scenarioId);
const records = consumptionByScenario[key] || [];
tableBody.innerHTML = "";
if (!records.length) {
emptyState.textContent = "No consumption records for this scenario yet.";
emptyState.classList.remove("hidden");
tableWrapper.classList.add("hidden");
return;
}
emptyState.classList.add("hidden");
tableWrapper.classList.remove("hidden");
records.forEach((record) => {
const row = document.createElement("tr");
row.innerHTML = `
<td>${formatMeasurement(
record.amount,
record.unit_symbol,
record.unit_name
)}</td>
<td>${record.description || "—"}</td>
`;
tableBody.appendChild(row);
});
};
if (filterSelect) {
filterSelect.addEventListener("change", (event) => {
const value = event.target.value;
if (!value) {
if (emptyState && tableWrapper && tableBody) {
emptyState.textContent =
"Choose a scenario to review its consumption records.";
emptyState.classList.remove("hidden");
tableWrapper.classList.add("hidden");
tableBody.innerHTML = "";
}
return;
}
renderConsumptionRows(value);
});
}
const submitConsumption = async (event) => {
event.preventDefault();
hideFeedback();
if (!form) {
return;
}
const formData = new FormData(form);
const scenarioId = formData.get("scenario_id");
const unitName = formData.get("unit_name");
const unitSymbol = formData.get("unit_symbol");
const payload = {
scenario_id: scenarioId ? Number(scenarioId) : null,
amount: Number(formData.get("amount")),
description: formData.get("description") || null,
unit_name: unitName ? String(unitName) : null,
unit_symbol: unitSymbol ? String(unitSymbol) : null,
};
try {
const response = await fetch("/api/consumption/", {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify(payload),
});
if (!response.ok) {
const errorDetail = await response.json().catch(() => ({}));
throw new Error(
errorDetail.detail || "Unable to add consumption record."
);
}
const result = await response.json();
const mapKey = String(result.scenario_id);
if (!Array.isArray(consumptionByScenario[mapKey])) {
consumptionByScenario[mapKey] = [];
}
consumptionByScenario[mapKey].push(result);
form.reset();
syncUnitSelection();
showFeedback("Consumption record saved.", "success");
if (filterSelect && filterSelect.value === String(result.scenario_id)) {
renderConsumptionRows(filterSelect.value);
}
} catch (error) {
showFeedback(error.message || "An unexpected error occurred.", "error");
}
};
if (form) {
form.addEventListener("submit", submitConsumption);
}
const syncUnitSelection = () => {
if (!unitSelect || !unitSymbolInput) {
return;
}
if (!unitSelect.value && unitSelect.options.length > 0) {
const firstOption = Array.from(unitSelect.options).find(
(option) => option.value
);
if (firstOption) {
firstOption.selected = true;
}
}
const selectedOption = unitSelect.options[unitSelect.selectedIndex];
unitSymbolInput.value = selectedOption
? selectedOption.getAttribute("data-symbol") || ""
: "";
};
if (unitSelect) {
unitSelect.addEventListener("change", syncUnitSelection);
syncUnitSelection();
}
if (filterSelect && filterSelect.value) {
renderConsumptionRows(filterSelect.value);
}
});

339
static/js/costs.js
View File

@@ -1,339 +0,0 @@
document.addEventListener("DOMContentLoaded", () => {
const dataElement = document.getElementById("costs-payload");
let capexByScenario = {};
let opexByScenario = {};
let currencyOptions = [];
if (dataElement) {
try {
const parsed = JSON.parse(dataElement.textContent || "{}");
if (parsed && typeof parsed === "object") {
if (parsed.capex && typeof parsed.capex === "object") {
capexByScenario = parsed.capex;
}
if (parsed.opex && typeof parsed.opex === "object") {
opexByScenario = parsed.opex;
}
if (Array.isArray(parsed.currency_options)) {
currencyOptions = parsed.currency_options;
}
}
} catch (error) {
console.error("Unable to parse cost data", error);
}
}
const filterSelect = document.getElementById("costs-scenario-filter");
const costsEmptyState = document.getElementById("costs-empty");
const costsDataWrapper = document.getElementById("costs-data");
const capexTableBody = document.getElementById("capex-table-body");
const opexTableBody = document.getElementById("opex-table-body");
const capexEmpty = document.getElementById("capex-empty");
const opexEmpty = document.getElementById("opex-empty");
const capexTotal = document.getElementById("capex-total");
const opexTotal = document.getElementById("opex-total");
const capexForm = document.getElementById("capex-form");
const opexForm = document.getElementById("opex-form");
const capexFeedback = document.getElementById("capex-feedback");
const opexFeedback = document.getElementById("opex-feedback");
const capexFormScenario = document.getElementById("capex-form-scenario");
const opexFormScenario = document.getElementById("opex-form-scenario");
const capexCurrencySelect = document.getElementById("capex-form-currency");
const opexCurrencySelect = document.getElementById("opex-form-currency");
// If no currency options were injected server-side, fetch from API
const fetchCurrencyOptions = async () => {
try {
const resp = await fetch("/api/currencies/");
if (!resp.ok) return;
const list = await resp.json();
if (Array.isArray(list) && list.length) {
currencyOptions = list;
populateCurrencySelects();
}
} catch (err) {
console.warn("Unable to fetch currency options", err);
}
};
const populateCurrencySelects = () => {
const selectElements = [capexCurrencySelect, opexCurrencySelect].filter(Boolean);
selectElements.forEach((sel) => {
if (!sel) return;
// Clear non-empty options except the empty placeholder
const placeholder = sel.querySelector("option[value='']");
sel.innerHTML = "";
if (placeholder) sel.appendChild(placeholder);
currencyOptions.forEach((opt) => {
const option = document.createElement("option");
option.value = opt.id;
option.textContent = opt.name || opt.id;
sel.appendChild(option);
});
});
};
// populate from injected options first, then fetch to refresh
if (currencyOptions && currencyOptions.length) populateCurrencySelects();
else fetchCurrencyOptions();
const showFeedback = (element, message, type = "success") => {
if (!element) {
return;
}
element.textContent = message;
element.classList.remove("hidden", "success", "error");
element.classList.add(type);
};
const hideFeedback = (element) => {
if (!element) {
return;
}
element.classList.add("hidden");
element.textContent = "";
};
const formatAmount = (value) =>
Number(value).toLocaleString(undefined, {
minimumFractionDigits: 2,
maximumFractionDigits: 2,
});
const formatCurrencyAmount = (value, currencyCode) => {
if (!currencyCode) {
return formatAmount(value);
}
try {
return new Intl.NumberFormat(undefined, {
style: "currency",
currency: currencyCode,
minimumFractionDigits: 2,
maximumFractionDigits: 2,
}).format(Number(value));
} catch (error) {
return `${currencyCode} ${formatAmount(value)}`;
}
};
const sumAmount = (records) =>
records.reduce((total, record) => total + Number(record.amount || 0), 0);
const describeTotal = (records) => {
if (!records || records.length === 0) {
return "—";
}
const total = sumAmount(records);
const currencyCodes = Array.from(
new Set(
records
.map((record) => (record.currency_code || "").trim().toUpperCase())
.filter(Boolean)
)
);
if (currencyCodes.length === 1) {
return formatCurrencyAmount(total, currencyCodes[0]);
}
return `${formatAmount(total)} (mixed)`;
};
const renderCostTables = (scenarioId) => {
if (
!capexTableBody ||
!opexTableBody ||
!capexEmpty ||
!opexEmpty ||
!capexTotal ||
!opexTotal
) {
return;
}
const capexRecords = capexByScenario[String(scenarioId)] || [];
const opexRecords = opexByScenario[String(scenarioId)] || [];
capexTableBody.innerHTML = "";
opexTableBody.innerHTML = "";
if (!capexRecords.length) {
capexEmpty.classList.remove("hidden");
} else {
capexEmpty.classList.add("hidden");
capexRecords.forEach((record) => {
const row = document.createElement("tr");
row.innerHTML = `
<td>${formatCurrencyAmount(record.amount, record.currency_code)}</td>
<td>${record.description || "—"}</td>
`;
capexTableBody.appendChild(row);
});
}
if (!opexRecords.length) {
opexEmpty.classList.remove("hidden");
} else {
opexEmpty.classList.add("hidden");
opexRecords.forEach((record) => {
const row = document.createElement("tr");
row.innerHTML = `
<td>${formatCurrencyAmount(record.amount, record.currency_code)}</td>
<td>${record.description || "—"}</td>
`;
opexTableBody.appendChild(row);
});
}
capexTotal.textContent = describeTotal(capexRecords);
opexTotal.textContent = describeTotal(opexRecords);
};
const toggleCostView = (show) => {
if (
!costsEmptyState ||
!costsDataWrapper ||
!capexTableBody ||
!opexTableBody
) {
return;
}
if (show) {
costsEmptyState.classList.add("hidden");
costsDataWrapper.classList.remove("hidden");
} else {
costsEmptyState.classList.remove("hidden");
costsDataWrapper.classList.add("hidden");
capexTableBody.innerHTML = "";
opexTableBody.innerHTML = "";
if (capexTotal) {
capexTotal.textContent = "—";
}
if (opexTotal) {
opexTotal.textContent = "—";
}
if (capexEmpty) {
capexEmpty.classList.add("hidden");
}
if (opexEmpty) {
opexEmpty.classList.add("hidden");
}
}
};
const syncFormSelections = (value) => {
if (capexFormScenario) {
capexFormScenario.value = value || "";
}
if (opexFormScenario) {
opexFormScenario.value = value || "";
}
};
const ensureCurrencySelection = (selectElement) => {
if (!selectElement || selectElement.value) {
return;
}
const firstOption = selectElement.querySelector(
"option[value]:not([value=''])"
);
if (firstOption && firstOption.value) {
selectElement.value = firstOption.value;
}
};
if (filterSelect) {
filterSelect.addEventListener("change", (event) => {
const value = event.target.value;
if (!value) {
toggleCostView(false);
syncFormSelections("");
return;
}
toggleCostView(true);
renderCostTables(value);
syncFormSelections(value);
});
}
const submitCostEntry = async (event, targetUrl, storageMap, feedbackEl) => {
event.preventDefault();
hideFeedback(feedbackEl);
const formData = new FormData(event.target);
const scenarioId = formData.get("scenario_id");
const currencyCode = formData.get("currency_code");
const payload = {
scenario_id: scenarioId ? Number(scenarioId) : null,
amount: Number(formData.get("amount")),
description: formData.get("description") || null,
currency_code: currencyCode ? String(currencyCode).toUpperCase() : null,
};
if (!payload.scenario_id) {
showFeedback(feedbackEl, "Select a scenario before submitting.", "error");
return;
}
if (!payload.currency_code) {
showFeedback(feedbackEl, "Choose a currency before submitting.", "error");
return;
}
try {
const response = await fetch(targetUrl, {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify(payload),
});
if (!response.ok) {
const errorDetail = await response.json().catch(() => ({}));
throw new Error(errorDetail.detail || "Unable to save cost entry.");
}
const result = await response.json();
const mapKey = String(result.scenario_id);
if (!Array.isArray(storageMap[mapKey])) {
storageMap[mapKey] = [];
}
storageMap[mapKey].push(result);
event.target.reset();
ensureCurrencySelection(event.target.querySelector("select[name='currency_code']"));
showFeedback(feedbackEl, "Entry saved successfully.", "success");
if (filterSelect && filterSelect.value === mapKey) {
renderCostTables(mapKey);
}
} catch (error) {
showFeedback(
feedbackEl,
error.message || "An unexpected error occurred.",
"error"
);
}
};
if (capexForm) {
ensureCurrencySelection(capexCurrencySelect);
capexForm.addEventListener("submit", (event) =>
submitCostEntry(event, "/api/costs/capex", capexByScenario, capexFeedback)
);
}
if (opexForm) {
ensureCurrencySelection(opexCurrencySelect);
opexForm.addEventListener("submit", (event) =>
submitCostEntry(event, "/api/costs/opex", opexByScenario, opexFeedback)
);
}
if (filterSelect && filterSelect.value) {
toggleCostView(true);
renderCostTables(filterSelect.value);
syncFormSelections(filterSelect.value);
}
});

537
static/js/currencies.js
View File

@@ -1,537 +0,0 @@
document.addEventListener("DOMContentLoaded", () => {
const dataElement = document.getElementById("currencies-data");
const editorSection = document.getElementById("currencies-editor");
const tableBody = document.getElementById("currencies-table-body");
const tableEmptyState = document.getElementById("currencies-table-empty");
const metrics = {
total: document.getElementById("currency-metric-total"),
active: document.getElementById("currency-metric-active"),
inactive: document.getElementById("currency-metric-inactive"),
};
const form = document.getElementById("currency-form");
const existingSelect = document.getElementById("currency-form-existing");
const codeInput = document.getElementById("currency-form-code");
const nameInput = document.getElementById("currency-form-name");
const symbolInput = document.getElementById("currency-form-symbol");
const statusSelect = document.getElementById("currency-form-status");
const resetButton = document.getElementById("currency-form-reset");
const feedbackElement = document.getElementById("currency-form-feedback");
const saveButton = form ? form.querySelector("button[type='submit']") : null;
const uppercaseCode = (value) =>
(value || "").toString().trim().toUpperCase();
const normalizeSymbol = (value) => {
if (value === undefined || value === null) {
return null;
}
const trimmed = String(value).trim();
return trimmed ? trimmed : null;
};
const normalizeApiBase = (value) => {
if (!value || typeof value !== "string") {
return "/api/currencies";
}
return value.endsWith("/") ? value.slice(0, -1) : value;
};
let currencies = [];
let apiBase = "/api/currencies";
let defaultCurrencyCode = "USD";
const buildCurrencyRecord = (record) => {
if (!record || typeof record !== "object") {
return null;
}
const code = uppercaseCode(record.code);
return {
id: record.id ?? null,
code,
name: record.name || "",
symbol: record.symbol || "",
is_active: Boolean(record.is_active),
is_default: code === defaultCurrencyCode,
};
};
const findCurrencyIndex = (code) => {
return currencies.findIndex((item) => item.code === code);
};
const upsertCurrency = (record) => {
const normalized = buildCurrencyRecord(record);
if (!normalized) {
return null;
}
const existingIndex = findCurrencyIndex(normalized.code);
if (existingIndex >= 0) {
currencies[existingIndex] = normalized;
} else {
currencies.push(normalized);
}
currencies.sort((a, b) => a.code.localeCompare(b.code));
return normalized;
};
const replaceCurrencyList = (records) => {
if (!Array.isArray(records)) {
return;
}
currencies = records
.map((record) => buildCurrencyRecord(record))
.filter((record) => record !== null)
.sort((a, b) => a.code.localeCompare(b.code));
};
const applyPayload = () => {
if (!dataElement) {
return;
}
try {
const parsed = JSON.parse(dataElement.textContent || "{}");
if (parsed && typeof parsed === "object") {
if (parsed.default_currency_code) {
defaultCurrencyCode = uppercaseCode(parsed.default_currency_code);
}
if (parsed.currency_api_base) {
apiBase = normalizeApiBase(parsed.currency_api_base);
}
if (Array.isArray(parsed.currencies)) {
replaceCurrencyList(parsed.currencies);
}
}
} catch (error) {
console.error("Unable to parse currencies payload", error);
}
};
const showFeedback = (message, type = "success") => {
if (!feedbackElement) {
return;
}
feedbackElement.textContent = message;
feedbackElement.classList.remove("hidden", "success", "error");
feedbackElement.classList.add(type);
};
const hideFeedback = () => {
if (!feedbackElement) {
return;
}
feedbackElement.classList.add("hidden");
feedbackElement.classList.remove("success", "error");
feedbackElement.textContent = "";
};
const setButtonLoading = (button, isLoading) => {
if (!button) {
return;
}
button.disabled = isLoading;
button.classList.toggle("is-loading", isLoading);
};
const updateMetrics = () => {
const total = currencies.length;
const active = currencies.filter((item) => item.is_active).length;
const inactive = total - active;
if (metrics.total) {
metrics.total.textContent = String(total);
}
if (metrics.active) {
metrics.active.textContent = String(active);
}
if (metrics.inactive) {
metrics.inactive.textContent = String(inactive);
}
};
const renderExistingOptions = (
selectedCode = existingSelect ? existingSelect.value : ""
) => {
if (!existingSelect) {
return;
}
const placeholder = existingSelect.querySelector("option[value='']");
const placeholderClone = placeholder ? placeholder.cloneNode(true) : null;
existingSelect.innerHTML = "";
if (placeholderClone) {
existingSelect.appendChild(placeholderClone);
}
const fragment = document.createDocumentFragment();
currencies.forEach((currency) => {
const option = document.createElement("option");
option.value = currency.code;
option.textContent = currency.name
? `${currency.name} (${currency.code})`
: currency.code;
if (selectedCode === currency.code) {
option.selected = true;
}
fragment.appendChild(option);
});
existingSelect.appendChild(fragment);
if (
selectedCode &&
!currencies.some((item) => item.code === selectedCode)
) {
existingSelect.value = "";
}
};
const renderTable = () => {
if (!tableBody) {
return;
}
tableBody.innerHTML = "";
if (!currencies.length) {
if (tableEmptyState) {
tableEmptyState.classList.remove("hidden");
}
return;
}
if (tableEmptyState) {
tableEmptyState.classList.add("hidden");
}
const fragment = document.createDocumentFragment();
currencies.forEach((currency) => {
const row = document.createElement("tr");
const codeCell = document.createElement("td");
codeCell.textContent = currency.code;
row.appendChild(codeCell);
const nameCell = document.createElement("td");
nameCell.textContent = currency.name || "—";
row.appendChild(nameCell);
const symbolCell = document.createElement("td");
symbolCell.textContent = currency.symbol || "—";
row.appendChild(symbolCell);
const statusCell = document.createElement("td");
statusCell.textContent = currency.is_active ? "Active" : "Inactive";
if (currency.is_default) {
statusCell.textContent += " (Default)";
}
row.appendChild(statusCell);
const actionsCell = document.createElement("td");
const editButton = document.createElement("button");
editButton.type = "button";
editButton.className = "btn";
editButton.dataset.action = "edit";
editButton.dataset.code = currency.code;
editButton.textContent = "Edit";
editButton.style.marginRight = "0.5rem";
const toggleButton = document.createElement("button");
toggleButton.type = "button";
toggleButton.className = "btn";
toggleButton.dataset.action = "toggle";
toggleButton.dataset.code = currency.code;
toggleButton.textContent = currency.is_active ? "Deactivate" : "Activate";
if (currency.is_default && currency.is_active) {
toggleButton.disabled = true;
toggleButton.title = "The default currency must remain active.";
}
actionsCell.appendChild(editButton);
actionsCell.appendChild(toggleButton);
row.appendChild(actionsCell);
fragment.appendChild(row);
});
tableBody.appendChild(fragment);
};
const refreshUI = (selectedCode) => {
currencies.sort((a, b) => a.code.localeCompare(b.code));
renderTable();
renderExistingOptions(selectedCode);
updateMetrics();
};
const findCurrency = (code) =>
currencies.find((item) => item.code === code) || null;
const setFormForCurrency = (currency) => {
if (!form || !codeInput || !nameInput || !symbolInput || !statusSelect) {
return;
}
if (!currency) {
form.reset();
if (existingSelect) {
existingSelect.value = "";
}
codeInput.readOnly = false;
codeInput.value = "";
nameInput.value = "";
symbolInput.value = "";
statusSelect.disabled = false;
statusSelect.value = "true";
statusSelect.title = "";
return;
}
if (existingSelect) {
existingSelect.value = currency.code;
}
codeInput.readOnly = true;
codeInput.value = currency.code;
nameInput.value = currency.name || "";
symbolInput.value = currency.symbol || "";
statusSelect.value = currency.is_active ? "true" : "false";
if (currency.is_default) {
statusSelect.disabled = true;
statusSelect.value = "true";
statusSelect.title = "The default currency must remain active.";
} else {
statusSelect.disabled = false;
statusSelect.title = "";
}
};
const resetFormState = () => {
setFormForCurrency(null);
};
const parseError = async (response, fallbackMessage) => {
try {
const detail = await response.json();
if (detail && typeof detail === "object" && detail.detail) {
return detail.detail;
}
} catch (error) {
// ignore JSON parse errors
}
return fallbackMessage;
};
const fetchCurrenciesFromApi = async () => {
const url = `${apiBase}/?include_inactive=true`;
try {
const response = await fetch(url);
if (!response.ok) {
return;
}
const list = await response.json();
if (Array.isArray(list)) {
replaceCurrencyList(list);
refreshUI(existingSelect ? existingSelect.value : undefined);
}
} catch (error) {
console.warn("Unable to refresh currency list", error);
}
};
const handleSubmit = async (event) => {
event.preventDefault();
hideFeedback();
if (!form || !codeInput || !nameInput || !statusSelect) {
return;
}
const editingCode = existingSelect
? uppercaseCode(existingSelect.value)
: "";
const codeValue = uppercaseCode(codeInput.value);
const nameValue = (nameInput.value || "").trim();
const symbolValue = normalizeSymbol(symbolInput ? symbolInput.value : "");
const isActive = statusSelect.value !== "false";
if (!nameValue) {
showFeedback("Provide a currency name.", "error");
return;
}
if (!editingCode) {
if (!codeValue || codeValue.length !== 3) {
showFeedback("Provide a three-letter currency code.", "error");
return;
}
}
const payload = editingCode
? {
name: nameValue,
symbol: symbolValue,
is_active: isActive,
}
: {
code: codeValue,
name: nameValue,
symbol: symbolValue,
is_active: isActive,
};
const targetCode = editingCode || codeValue;
const url = editingCode
? `${apiBase}/${encodeURIComponent(editingCode)}`
: `${apiBase}/`;
setButtonLoading(saveButton, true);
try {
const response = await fetch(url, {
method: editingCode ? "PUT" : "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify(payload),
});
if (!response.ok) {
const message = await parseError(
response,
editingCode
? "Unable to update the currency."
: "Unable to create the currency."
);
throw new Error(message);
}
const result = await response.json();
const updated = upsertCurrency(result);
defaultCurrencyCode = uppercaseCode(defaultCurrencyCode);
refreshUI(updated ? updated.code : targetCode);
if (editingCode) {
showFeedback("Currency updated successfully.");
if (updated) {
setFormForCurrency(updated);
}
} else {
showFeedback("Currency created successfully.");
resetFormState();
}
} catch (error) {
showFeedback(error.message || "An unexpected error occurred.", "error");
} finally {
setButtonLoading(saveButton, false);
}
};
const handleToggle = async (code, button) => {
const record = findCurrency(code);
if (!record) {
return;
}
hideFeedback();
const nextState = !record.is_active;
const url = `${apiBase}/${encodeURIComponent(code)}/activation`;
setButtonLoading(button, true);
try {
const response = await fetch(url, {
method: "PATCH",
headers: { "Content-Type": "application/json" },
body: JSON.stringify({ is_active: nextState }),
});
if (!response.ok) {
const message = await parseError(
response,
nextState
? "Unable to activate the currency."
: "Unable to deactivate the currency."
);
throw new Error(message);
}
const result = await response.json();
const updated = upsertCurrency(result);
refreshUI(updated ? updated.code : code);
if (existingSelect && existingSelect.value === code && updated) {
setFormForCurrency(updated);
}
const actionMessage = nextState
? `Currency ${code} activated.`
: `Currency ${code} deactivated.`;
showFeedback(actionMessage);
} catch (error) {
showFeedback(error.message || "An unexpected error occurred.", "error");
} finally {
setButtonLoading(button, false);
}
};
const handleTableClick = (event) => {
const button = event.target.closest("button[data-action]");
if (!button) {
return;
}
const code = uppercaseCode(button.dataset.code);
const action = button.dataset.action;
if (!code || !action) {
return;
}
if (action === "edit") {
const currency = findCurrency(code);
if (currency) {
setFormForCurrency(currency);
hideFeedback();
if (nameInput) {
nameInput.focus();
}
}
} else if (action === "toggle") {
handleToggle(code, button);
}
};
applyPayload();
if (editorSection && editorSection.dataset.defaultCode) {
defaultCurrencyCode = uppercaseCode(editorSection.dataset.defaultCode);
currencies = currencies.map((record) => {
return record
? {
...record,
is_default: record.code === defaultCurrencyCode,
}
: record;
});
}
apiBase = normalizeApiBase(apiBase);
refreshUI();
if (form) {
form.addEventListener("submit", handleSubmit);
}
if (existingSelect) {
existingSelect.addEventListener("change", (event) => {
const selectedCode = uppercaseCode(event.target.value);
if (!selectedCode) {
hideFeedback();
resetFormState();
return;
}
const currency = findCurrency(selectedCode);
if (currency) {
setFormForCurrency(currency);
hideFeedback();
}
});
}
if (resetButton) {
resetButton.addEventListener("click", (event) => {
event.preventDefault();
hideFeedback();
resetFormState();
});
}
if (codeInput) {
codeInput.addEventListener("input", () => {
const value = uppercaseCode(codeInput.value).slice(0, 3);
codeInput.value = value;
});
}
if (tableBody) {
tableBody.addEventListener("click", handleTableClick);
}
fetchCurrenciesFromApi();
});

289
static/js/dashboard.js
View File

@@ -1,289 +0,0 @@
(() => {
const dataElement = document.getElementById("dashboard-data");
if (!dataElement) {
return;
}
let state = {};
try {
state = JSON.parse(dataElement.textContent || "{}");
} catch (error) {
console.error("Failed to parse dashboard data", error);
return;
}
const statusElement = document.getElementById("dashboard-status");
const summaryContainer = document.getElementById("summary-metrics");
const summaryEmpty = document.getElementById("summary-empty");
const scenarioTableBody = document.querySelector("#scenario-table tbody");
const scenarioEmpty = document.getElementById("scenario-table-empty");
const overallMetricsList = document.getElementById("overall-metrics");
const overallMetricsEmpty = document.getElementById("overall-metrics-empty");
const recentList = document.getElementById("recent-simulations");
const recentEmpty = document.getElementById("recent-simulations-empty");
const maintenanceList = document.getElementById("upcoming-maintenance");
const maintenanceEmpty = document.getElementById(
"upcoming-maintenance-empty"
);
const refreshButton = document.getElementById("refresh-dashboard");
const costChartCanvas = document.getElementById("cost-chart");
const costChartEmpty = document.getElementById("cost-chart-empty");
const activityChartCanvas = document.getElementById("activity-chart");
const activityChartEmpty = document.getElementById("activity-chart-empty");
let costChartInstance = null;
let activityChartInstance = null;
const setStatus = (message, variant = "success") => {
if (!statusElement) {
return;
}
if (!message) {
statusElement.hidden = true;
statusElement.textContent = "";
statusElement.classList.remove("success", "error");
return;
}
statusElement.textContent = message;
statusElement.hidden = false;
statusElement.classList.toggle("success", variant === "success");
statusElement.classList.toggle("error", variant !== "success");
};
const renderSummaryMetrics = () => {
if (!summaryContainer || !summaryEmpty) {
return;
}
summaryContainer.innerHTML = "";
const metrics = Array.isArray(state.summary_metrics)
? state.summary_metrics
: [];
metrics.forEach((metric) => {
const card = document.createElement("article");
card.className = "metric-card";
card.innerHTML = `
<span class="metric-label">${metric.label}</span>
<span class="metric-value">${metric.value}</span>
`;
summaryContainer.appendChild(card);
});
summaryEmpty.hidden = metrics.length > 0;
};
const renderScenarioTable = () => {
if (!scenarioTableBody || !scenarioEmpty) {
return;
}
scenarioTableBody.innerHTML = "";
const rows = Array.isArray(state.scenario_rows) ? state.scenario_rows : [];
rows.forEach((row) => {
const tr = document.createElement("tr");
tr.innerHTML = `
<td>${row.scenario_name}</td>
<td>${row.parameter_display}</td>
<td>${row.equipment_display}</td>
<td>${row.capex_display}</td>
<td>${row.opex_display}</td>
<td>${row.production_display}</td>
<td>${row.consumption_display}</td>
<td>${row.maintenance_display}</td>
<td>${row.iterations_display}</td>
<td>${row.simulation_mean_display}</td>
`;
scenarioTableBody.appendChild(tr);
});
scenarioEmpty.hidden = rows.length > 0;
};
const renderOverallMetrics = () => {
if (!overallMetricsList || !overallMetricsEmpty) {
return;
}
overallMetricsList.innerHTML = "";
const items = Array.isArray(state.overall_report_metrics)
? state.overall_report_metrics
: [];
items.forEach((item) => {
const li = document.createElement("li");
li.className = "metric-list-item";
li.textContent = `${item.label}: ${item.value}`;
overallMetricsList.appendChild(li);
});
overallMetricsEmpty.hidden = items.length > 0;
};
const renderRecentSimulations = () => {
if (!recentList || !recentEmpty) {
return;
}
recentList.innerHTML = "";
const runs = Array.isArray(state.recent_simulations)
? state.recent_simulations
: [];
runs.forEach((run) => {
const item = document.createElement("li");
item.className = "metric-list-item";
item.textContent = `${run.scenario_name} · ${run.iterations_display} iterations · ${run.mean_display}`;
recentList.appendChild(item);
});
recentEmpty.hidden = runs.length > 0;
};
const renderMaintenanceReminders = () => {
if (!maintenanceList || !maintenanceEmpty) {
return;
}
maintenanceList.innerHTML = "";
const items = Array.isArray(state.upcoming_maintenance)
? state.upcoming_maintenance
: [];
items.forEach((item) => {
const li = document.createElement("li");
li.innerHTML = `
<span class="list-title">${item.equipment_name} · ${item.scenario_name}</span>
<span class="list-detail">${item.date_display} · ${item.cost_display} · ${item.description}</span>
`;
maintenanceList.appendChild(li);
});
maintenanceEmpty.hidden = items.length > 0;
};
const buildChartConfig = (dataset, overrides = {}) => ({
type: dataset.type || "bar",
data: {
labels: dataset.labels || [],
datasets: dataset.datasets || [],
},
options: Object.assign(
{
responsive: true,
maintainAspectRatio: false,
plugins: {
legend: { position: "top" },
tooltip: { enabled: true },
},
scales: {
x: { stacked: dataset.stacked ?? false },
y: { stacked: dataset.stacked ?? false, beginAtZero: true },
},
},
overrides.options || {}
),
});
const renderCharts = () => {
if (costChartInstance) {
costChartInstance.destroy();
}
if (activityChartInstance) {
activityChartInstance.destroy();
}
const costData = state.scenario_cost_chart || {};
const activityData = state.scenario_activity_chart || {};
if (costChartCanvas && state.cost_chart_has_data) {
costChartInstance = new Chart(
costChartCanvas,
buildChartConfig(costData, {
options: {
scales: {
y: {
beginAtZero: true,
ticks: {
callback: (value) =>
typeof value === "number"
? value.toLocaleString(undefined, {
maximumFractionDigits: 0,
})
: value,
},
},
},
},
})
);
if (costChartEmpty) {
costChartEmpty.hidden = true;
}
costChartCanvas.classList.remove("hidden");
} else if (costChartEmpty && costChartCanvas) {
costChartEmpty.hidden = false;
costChartCanvas.classList.add("hidden");
}
if (activityChartCanvas && state.activity_chart_has_data) {
activityChartInstance = new Chart(
activityChartCanvas,
buildChartConfig(activityData, {
options: {
scales: {
y: {
beginAtZero: true,
ticks: {
callback: (value) =>
typeof value === "number"
? value.toLocaleString(undefined, {
maximumFractionDigits: 0,
})
: value,
},
},
},
},
})
);
if (activityChartEmpty) {
activityChartEmpty.hidden = true;
}
activityChartCanvas.classList.remove("hidden");
} else if (activityChartEmpty && activityChartCanvas) {
activityChartEmpty.hidden = false;
activityChartCanvas.classList.add("hidden");
}
};
const renderView = () => {
renderSummaryMetrics();
renderScenarioTable();
renderOverallMetrics();
renderRecentSimulations();
renderMaintenanceReminders();
renderCharts();
};
const refreshDashboard = async () => {
setStatus("Refreshing dashboard…", "success");
if (refreshButton) {
refreshButton.classList.add("is-loading");
}
try {
const response = await fetch("/ui/dashboard/data", {
headers: { "X-Requested-With": "XMLHttpRequest" },
});
if (!response.ok) {
throw new Error("Unable to refresh dashboard data.");
}
const payload = await response.json();
state = payload || {};
renderView();
setStatus("Dashboard updated.", "success");
} catch (error) {
console.error(error);
setStatus(error.message || "Failed to refresh dashboard.", "error");
} finally {
if (refreshButton) {
refreshButton.classList.remove("is-loading");
}
}
};
renderView();
if (refreshButton) {
refreshButton.addEventListener("click", refreshDashboard);
}
})();

145
static/js/equipment.js
View File

@@ -1,145 +0,0 @@
document.addEventListener("DOMContentLoaded", () => {
const dataElement = document.getElementById("equipment-data");
let equipmentByScenario = {};
if (dataElement) {
try {
const parsed = JSON.parse(dataElement.textContent || "{}");
if (parsed && typeof parsed === "object") {
if (parsed.equipment && typeof parsed.equipment === "object") {
equipmentByScenario = parsed.equipment;
}
}
} catch (error) {
console.error("Unable to parse equipment data", error);
}
}
const filterSelect = document.getElementById("equipment-scenario-filter");
const tableWrapper = document.getElementById("equipment-table-wrapper");
const tableBody = document.getElementById("equipment-table-body");
const emptyState = document.getElementById("equipment-empty");
const form = document.getElementById("equipment-form");
const feedbackEl = document.getElementById("equipment-feedback");
const showFeedback = (message, type = "success") => {
if (!feedbackEl) {
return;
}
feedbackEl.textContent = message;
feedbackEl.classList.remove("hidden", "success", "error");
feedbackEl.classList.add(type);
};
const hideFeedback = () => {
if (!feedbackEl) {
return;
}
feedbackEl.classList.add("hidden");
feedbackEl.textContent = "";
};
const renderEquipmentRows = (scenarioId) => {
if (!tableBody || !tableWrapper || !emptyState) {
return;
}
const key = String(scenarioId);
const records = equipmentByScenario[key] || [];
tableBody.innerHTML = "";
if (!records.length) {
emptyState.textContent = "No equipment recorded for this scenario yet.";
emptyState.classList.remove("hidden");
tableWrapper.classList.add("hidden");
return;
}
emptyState.classList.add("hidden");
tableWrapper.classList.remove("hidden");
records.forEach((record) => {
const row = document.createElement("tr");
row.innerHTML = `
<td>${record.name || "—"}</td>
<td>${record.description || "—"}</td>
`;
tableBody.appendChild(row);
});
};
if (filterSelect) {
filterSelect.addEventListener("change", (event) => {
const value = event.target.value;
if (!value) {
if (emptyState && tableWrapper && tableBody) {
emptyState.textContent =
"Choose a scenario to review the equipment list.";
emptyState.classList.remove("hidden");
tableWrapper.classList.add("hidden");
tableBody.innerHTML = "";
}
return;
}
renderEquipmentRows(value);
});
}
const submitEquipment = async (event) => {
event.preventDefault();
hideFeedback();
if (!form) {
return;
}
const formData = new FormData(form);
const scenarioId = formData.get("scenario_id");
const payload = {
scenario_id: scenarioId ? Number(scenarioId) : null,
name: formData.get("name"),
description: formData.get("description") || null,
};
try {
const response = await fetch("/api/equipment/", {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify(payload),
});
if (!response.ok) {
const errorDetail = await response.json().catch(() => ({}));
throw new Error(
errorDetail.detail || "Unable to add equipment record."
);
}
const result = await response.json();
const mapKey = String(result.scenario_id);
if (!Array.isArray(equipmentByScenario[mapKey])) {
equipmentByScenario[mapKey] = [];
}
equipmentByScenario[mapKey].push(result);
form.reset();
showFeedback("Equipment saved.", "success");
if (filterSelect && filterSelect.value === String(result.scenario_id)) {
renderEquipmentRows(filterSelect.value);
}
} catch (error) {
showFeedback(error.message || "An unexpected error occurred.", "error");
}
};
if (form) {
form.addEventListener("submit", submitEquipment);
}
if (filterSelect && filterSelect.value) {
renderEquipmentRows(filterSelect.value);
}
});

243
static/js/maintenance.js
View File

@@ -1,243 +0,0 @@
document.addEventListener("DOMContentLoaded", () => {
const dataElement = document.getElementById("maintenance-data");
let equipmentByScenario = {};
let maintenanceByScenario = {};
if (dataElement) {
try {
const parsed = JSON.parse(dataElement.textContent || "{}");
if (parsed && typeof parsed === "object") {
if (parsed.equipment && typeof parsed.equipment === "object") {
equipmentByScenario = parsed.equipment;
}
if (parsed.maintenance && typeof parsed.maintenance === "object") {
maintenanceByScenario = parsed.maintenance;
}
}
} catch (error) {
console.error("Unable to parse maintenance data", error);
}
}
const filterSelect = document.getElementById("maintenance-scenario-filter");
const tableWrapper = document.getElementById("maintenance-table-wrapper");
const tableBody = document.getElementById("maintenance-table-body");
const emptyState = document.getElementById("maintenance-empty");
const form = document.getElementById("maintenance-form");
const feedbackEl = document.getElementById("maintenance-feedback");
const formScenarioSelect = document.getElementById(
"maintenance-form-scenario"
);
const equipmentSelect = document.getElementById("maintenance-form-equipment");
const equipmentEmptyState = document.getElementById(
"maintenance-equipment-empty"
);
const showFeedback = (message, type = "success") => {
if (!feedbackEl) {
return;
}
feedbackEl.textContent = message;
feedbackEl.classList.remove("hidden", "success", "error");
feedbackEl.classList.add(type);
};
const hideFeedback = () => {
if (!feedbackEl) {
return;
}
feedbackEl.classList.add("hidden");
feedbackEl.textContent = "";
};
const formatCost = (value) =>
Number(value).toLocaleString(undefined, {
minimumFractionDigits: 2,
maximumFractionDigits: 2,
});
const formatDate = (value) => {
if (!value) {
return "—";
}
const parsed = new Date(value);
if (Number.isNaN(parsed.getTime())) {
return value;
}
return parsed.toLocaleDateString();
};
const renderMaintenanceRows = (scenarioId) => {
if (!tableBody || !tableWrapper || !emptyState) {
return;
}
const key = String(scenarioId);
const records = maintenanceByScenario[key] || [];
tableBody.innerHTML = "";
if (!records.length) {
emptyState.textContent =
"No maintenance entries recorded for this scenario yet.";
emptyState.classList.remove("hidden");
tableWrapper.classList.add("hidden");
return;
}
emptyState.classList.add("hidden");
tableWrapper.classList.remove("hidden");
records.forEach((record) => {
const row = document.createElement("tr");
row.innerHTML = `
<td>${formatDate(record.maintenance_date)}</td>
<td>${record.equipment_name || "—"}</td>
<td>${formatCost(record.cost)}</td>
<td>${record.description || "—"}</td>
`;
tableBody.appendChild(row);
});
};
const populateEquipmentOptions = (scenarioId) => {
if (!equipmentSelect) {
return;
}
equipmentSelect.innerHTML =
'<option value="" disabled selected>Select equipment</option>';
equipmentSelect.disabled = true;
if (equipmentEmptyState) {
equipmentEmptyState.classList.add("hidden");
}
if (!scenarioId) {
return;
}
const list = equipmentByScenario[String(scenarioId)] || [];
if (!list.length) {
if (equipmentEmptyState) {
equipmentEmptyState.textContent =
"Add equipment for this scenario before scheduling maintenance.";
equipmentEmptyState.classList.remove("hidden");
}
return;
}
list.forEach((item) => {
const option = document.createElement("option");
option.value = item.id;
option.textContent = item.name || `Equipment ${item.id}`;
equipmentSelect.appendChild(option);
});
equipmentSelect.disabled = false;
};
if (filterSelect) {
filterSelect.addEventListener("change", (event) => {
const value = event.target.value;
if (!value) {
if (emptyState && tableWrapper && tableBody) {
emptyState.textContent =
"Choose a scenario to review upcoming or completed maintenance.";
emptyState.classList.remove("hidden");
tableWrapper.classList.add("hidden");
tableBody.innerHTML = "";
}
return;
}
renderMaintenanceRows(value);
});
}
if (formScenarioSelect) {
formScenarioSelect.addEventListener("change", (event) => {
const value = event.target.value;
populateEquipmentOptions(value);
});
}
const submitMaintenance = async (event) => {
event.preventDefault();
hideFeedback();
if (!form) {
return;
}
const formData = new FormData(form);
const scenarioId = formData.get("scenario_id");
const equipmentId = formData.get("equipment_id");
const payload = {
scenario_id: scenarioId ? Number(scenarioId) : null,
equipment_id: equipmentId ? Number(equipmentId) : null,
maintenance_date: formData.get("maintenance_date"),
cost: Number(formData.get("cost")),
description: formData.get("description") || null,
};
if (!payload.scenario_id || !payload.equipment_id) {
showFeedback(
"Select a scenario and equipment before submitting.",
"error"
);
return;
}
try {
const response = await fetch("/api/maintenance/", {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify(payload),
});
if (!response.ok) {
const errorDetail = await response.json().catch(() => ({}));
throw new Error(
errorDetail.detail || "Unable to add maintenance entry."
);
}
const result = await response.json();
const mapKey = String(result.scenario_id);
if (!Array.isArray(maintenanceByScenario[mapKey])) {
maintenanceByScenario[mapKey] = [];
}
const equipmentList = equipmentByScenario[mapKey] || [];
const matchedEquipment = equipmentList.find(
(item) => Number(item.id) === Number(result.equipment_id)
);
result.equipment_name = matchedEquipment ? matchedEquipment.name : "";
maintenanceByScenario[mapKey].push(result);
form.reset();
populateEquipmentOptions(null);
showFeedback("Maintenance entry saved.", "success");
if (filterSelect && filterSelect.value === String(result.scenario_id)) {
renderMaintenanceRows(filterSelect.value);
}
} catch (error) {
showFeedback(error.message || "An unexpected error occurred.", "error");
}
};
if (form) {
form.addEventListener("submit", submitMaintenance);
}
if (filterSelect && filterSelect.value) {
renderMaintenanceRows(filterSelect.value);
}
if (formScenarioSelect && formScenarioSelect.value) {
populateEquipmentOptions(formScenarioSelect.value);
}
});

124
static/js/parameters.js
View File

@@ -1,124 +0,0 @@
document.addEventListener("DOMContentLoaded", () => {
const dataElement = document.getElementById("parameters-data");
let parametersByScenario = {};
if (dataElement) {
try {
const parsed = JSON.parse(dataElement.textContent || "{}");
if (parsed && typeof parsed === "object") {
parametersByScenario = parsed;
}
} catch (error) {
console.error("Unable to parse parameter data", error);
}
}
const form = document.getElementById("parameter-form");
const scenarioSelect = /** @type {HTMLSelectElement | null} */ (
document.getElementById("scenario_id")
);
const nameInput = /** @type {HTMLInputElement | null} */ (
document.getElementById("name")
);
const valueInput = /** @type {HTMLInputElement | null} */ (
document.getElementById("value")
);
const feedback = document.getElementById("parameter-feedback");
const tableBody = document.getElementById("parameter-table-body");
const setFeedback = (message, variant) => {
if (!feedback) {
return;
}
feedback.textContent = message;
feedback.classList.remove("success", "error");
if (variant) {
feedback.classList.add(variant);
}
};
const renderTable = (scenarioId) => {
if (!tableBody) {
return;
}
tableBody.innerHTML = "";
const rows = parametersByScenario[String(scenarioId)] || [];
if (!rows.length) {
const emptyRow = document.createElement("tr");
emptyRow.id = "parameter-empty-state";
emptyRow.innerHTML =
'<td colspan="4">No parameters recorded for this scenario yet.</td>';
tableBody.appendChild(emptyRow);
return;
}
rows.forEach((row) => {
const tr = document.createElement("tr");
tr.innerHTML = `
<td>${row.name}</td>
<td>${row.value}</td>
<td>${row.distribution_type ?? "—"}</td>
<td>${
row.distribution_parameters
? JSON.stringify(row.distribution_parameters)
: "—"
}</td>
`;
tableBody.appendChild(tr);
});
};
if (scenarioSelect) {
renderTable(scenarioSelect.value);
scenarioSelect.addEventListener("change", () =>
renderTable(scenarioSelect.value)
);
}
if (!form || !scenarioSelect || !nameInput || !valueInput) {
return;
}
form.addEventListener("submit", async (event) => {
event.preventDefault();
const scenarioId = scenarioSelect.value;
const payload = {
scenario_id: Number(scenarioId),
name: nameInput.value.trim(),
value: Number(valueInput.value),
};
if (!payload.name) {
setFeedback("Parameter name is required.", "error");
return;
}
if (!Number.isFinite(payload.value)) {
setFeedback("Enter a numeric value.", "error");
return;
}
const response = await fetch("/api/parameters/", {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify(payload),
});
if (!response.ok) {
const errorText = await response.text();
setFeedback(`Error saving parameter: ${errorText}`, "error");
return;
}
const data = await response.json();
const scenarioKey = String(scenarioId);
parametersByScenario[scenarioKey] = parametersByScenario[scenarioKey] || [];
parametersByScenario[scenarioKey].push(data);
form.reset();
scenarioSelect.value = scenarioKey;
renderTable(scenarioKey);
nameInput.focus();
setFeedback("Parameter saved.", "success");
});
});

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