Add initial implementation of CalMiner with project structure, environment setup, and core features

- Create .env.example for environment variables
- Update README with project structure and development setup instructions
- Implement FastAPI application with API routes for scenarios and parameters
- Add database models for scenarios, parameters, and simulation results
- Introduce validation middleware for JSON requests
- Create services for running simulations and generating reports
- Add testing strategy and directory structure in documentation

services/reporting.py

@@ -0,0 +1,15 @@
+from typing import List, Dict
+
+
+def generate_report(simulation_results: List[Dict[str, float]]) -> Dict[str, float]:
+    """
+    Generate summary report from simulation results.
+
+    Args:
+        simulation_results: List of dicts with 'iteration' and 'result'.
+
+    Returns:
+        Dictionary with summary statistics (e.g., mean, median).
+    """
+    # TODO: implement reporting logic (e.g., calculate mean, median, percentiles)
+    return {}

services/simulation.py

@@ -0,0 +1,17 @@
+from typing import Dict, List
+
+
+def run_simulation(parameters: List[Dict[str, float]], iterations: int = 1000) -> List[Dict[str, float]]:
+    """
+    Run Monte Carlo simulation with given parameters.
+
+    Args:
+        parameters: List of parameter dicts with keys 'name' and 'value'.
+        iterations: Number of simulation iterations.
+
+    Returns:
+        List of simulation result dicts for each iteration.
+    """
+    # TODO: implement Monte Carlo logic
+    results: List[Dict[str, float]] = []
+    return results