feat: Enhance project and scenario creation with monitoring metrics

- Added monitoring metrics for project creation success and error handling in `ProjectRepository`.
- Implemented similar monitoring for scenario creation in `ScenarioRepository`.
- Refactored `run_monte_carlo` function in `simulation.py` to include timing and success/error metrics.
- Introduced new CSS styles for headers, alerts, and navigation buttons in `main.css` and `projects.css`.
- Created a new JavaScript file for navigation logic to handle chevron buttons.
- Updated HTML templates to include new navigation buttons and improved styling for buttons.
- Added tests for reporting service and routes to ensure proper functionality and access control.
- Removed unused imports and optimized existing test files for better clarity and performance.

services/simulation.py

@@ -2,7 +2,8 @@ from __future__ import annotations
 
 from dataclasses import dataclass
 from enum import Enum
-from typing import Any, Dict, Iterable, Mapping, Sequence
+from typing import Any, Dict, Mapping, Sequence
+import time
 
 import numpy as np
 from numpy.random import Generator, default_rng
@@ -15,6 +16,7 @@ from .financial import (
     net_present_value,
     payback_period,
 )
+from monitoring.metrics import observe_simulation
 
 
 class DistributionConfigError(ValueError):
@@ -120,60 +122,79 @@ def run_monte_carlo(
         if pct < 0.0 or pct > 100.0:
             raise ValueError("percentiles must be within [0, 100]")
 
-    generator = rng or default_rng(config.seed)
+    start_time = time.time()
+    try:
+        generator = rng or default_rng(config.seed)
 
-    metric_arrays: Dict[SimulationMetric, np.ndarray] = {
-        metric: np.empty(config.iterations, dtype=float)
-        for metric in config.metrics
-    }
+        metric_arrays: Dict[SimulationMetric, np.ndarray] = {
+            metric: np.empty(config.iterations, dtype=float)
+            for metric in config.metrics
+        }
 
-    for idx in range(config.iterations):
-        iteration_flows = [
-            _realise_cash_flow(
-                spec,
-                generator,
-                scenario_context=scenario_context,
-                metadata=metadata,
-            )
-            for spec in cash_flows
-        ]
+        for idx in range(config.iterations):
+            iteration_flows = [
+                _realise_cash_flow(
+                    spec,
+                    generator,
+                    scenario_context=scenario_context,
+                    metadata=metadata,
+                )
+                for spec in cash_flows
+            ]
 
-        if SimulationMetric.NPV in metric_arrays:
-            metric_arrays[SimulationMetric.NPV][idx] = net_present_value(
-                config.discount_rate,
-                iteration_flows,
-                residual_value=config.residual_value,
-                residual_periods=config.residual_periods,
-                compounds_per_year=config.compounds_per_year,
-            )
-        if SimulationMetric.IRR in metric_arrays:
-            try:
-                metric_arrays[SimulationMetric.IRR][idx] = internal_rate_of_return(
+            if SimulationMetric.NPV in metric_arrays:
+                metric_arrays[SimulationMetric.NPV][idx] = net_present_value(
+                    config.discount_rate,
                     iteration_flows,
+                    residual_value=config.residual_value,
+                    residual_periods=config.residual_periods,
                     compounds_per_year=config.compounds_per_year,
                 )
-            except (ValueError, ConvergenceError):
-                metric_arrays[SimulationMetric.IRR][idx] = np.nan
-        if SimulationMetric.PAYBACK in metric_arrays:
-            try:
-                metric_arrays[SimulationMetric.PAYBACK][idx] = payback_period(
-                    iteration_flows,
-                    compounds_per_year=config.compounds_per_year,
-                )
-            except (ValueError, PaybackNotReachedError):
-                metric_arrays[SimulationMetric.PAYBACK][idx] = np.nan
+            if SimulationMetric.IRR in metric_arrays:
+                try:
+                    metric_arrays[SimulationMetric.IRR][idx] = internal_rate_of_return(
+                        iteration_flows,
+                        compounds_per_year=config.compounds_per_year,
+                    )
+                except (ValueError, ConvergenceError):
+                    metric_arrays[SimulationMetric.IRR][idx] = np.nan
+            if SimulationMetric.PAYBACK in metric_arrays:
+                try:
+                    metric_arrays[SimulationMetric.PAYBACK][idx] = payback_period(
+                        iteration_flows,
+                        compounds_per_year=config.compounds_per_year,
+                    )
+                except (ValueError, PaybackNotReachedError):
+                    metric_arrays[SimulationMetric.PAYBACK][idx] = np.nan
 
-    summaries = {
-        metric: _summarise(metric_arrays[metric], config.percentiles)
-        for metric in metric_arrays
-    }
+        summaries = {
+            metric: _summarise(metric_arrays[metric], config.percentiles)
+            for metric in metric_arrays
+        }
 
-    samples = metric_arrays if config.return_samples else None
-    return SimulationResult(
-        iterations=config.iterations,
-        summaries=summaries,
-        samples=samples,
-    )
+        samples = metric_arrays if config.return_samples else None
+        result = SimulationResult(
+            iterations=config.iterations,
+            summaries=summaries,
+            samples=samples,
+        )
+
+        # Record successful simulation
+        duration = time.time() - start_time
+        observe_simulation(
+            status="success",
+            duration_seconds=duration,
+        )
+        return result
+
+    except Exception as e:
+        # Record failed simulation
+        duration = time.time() - start_time
+        observe_simulation(
+            status="error",
+            duration_seconds=duration,
+        )
+        raise
 
 
 def _realise_cash_flow(