⚡ Bolt: [performance improvement] Optimize nested loops for exercise-solution lookups

benchmark.py

@@ -0,0 +1,51 @@
+import time
+from typing import List, Dict
+
+def get_all_exercises_original(materials: List[Dict]) -> List[Dict]:
+    all_exercises = []
+    for material in materials:
+        for exercise in material['exercises']:
+            solution = None
+            for sol in material['solutions']:
+                if sol['exercise_label'] == exercise['label']:
+                    solution = sol
+                    break
+
+            exercise_data = {
+                'label': exercise['label'],
+                'solution_label': solution['label'] if solution else None
+            }
+            all_exercises.append(exercise_data)
+    return all_exercises
+
+def get_all_exercises_optimized(materials: List[Dict]) -> List[Dict]:
+    all_exercises = []
+    for material in materials:
+        solutions_by_label = {}
+        for sol in material['solutions']:
+            if sol['exercise_label'] not in solutions_by_label:
+                solutions_by_label[sol['exercise_label']] = sol
+        for exercise in material['exercises']:
+            solution = solutions_by_label.get(exercise['label'])
+
+            exercise_data = {
+                'label': exercise['label'],
+                'solution_label': solution['label'] if solution else None
+            }
+            all_exercises.append(exercise_data)
+    return all_exercises
+
+# Generate dummy data
+materials = []
+for i in range(10):
+    exercises = [{'label': f'ex_{j}'} for j in range(1000)]
+    solutions = [{'exercise_label': f'ex_{j}', 'label': f'sol_{j}'} for j in range(1000)]
+    materials.append({'exercises': exercises, 'solutions': solutions})
+
+start = time.time()
+get_all_exercises_original(materials)
+print(f"Original: {time.time() - start:.4f}s")
+
+start = time.time()
+get_all_exercises_optimized(materials)
+print(f"Optimized: {time.time() - start:.4f}s")