style: Run linter on benchmark script

benchmark/problem_stats.py

@@ -1,9 +1,11 @@
 #!/usr/bin/env python
 
-import yaml
-from pathlib import Path
-from collections import defaultdict
 import json
+from collections import defaultdict
+from pathlib import Path
+
+import yaml
+
 
 def load_results(dirname):
     """Load all result files from a benchmark directory"""
@@ -11,7 +13,7 @@ def load_results(dirname):
     benchmark_dir = Path("tmp.benchmarks") / dirname
     if not benchmark_dir.exists():
         return None
-    
+
     all_results = []
     for fname in benchmark_dir.glob("*/.aider.results.json"):
         try:
@@ -22,61 +24,59 @@ def load_results(dirname):
             continue
     return all_results
 
+
 def analyze_exercise_solutions():
     # Load the leaderboard data
     with open("aider/website/_data/edit_leaderboard.yml") as f:
         leaderboard = yaml.safe_load(f)
-    
+
     # Track which models solved each exercise
     exercise_solutions = defaultdict(list)
-    
+
     for entry in leaderboard:
         dirname = entry["dirname"]
         model = entry["model"]
-        
+
         results = load_results(dirname)
         if not results:
             print(f"Could not load results for {dirname}")
             continue
-            
+
         for result in results:
             testcase = result.get("testcase")
             if not testcase:
                 continue
-                
+
             # Consider it solved if the last test attempt passed
             tests_outcomes = result.get("tests_outcomes", [])
             if tests_outcomes and tests_outcomes[-1]:
                 exercise_solutions[testcase].append(model)
-    
+
     # Print statistics
     print("\nExercise Solution Statistics:")
     print("-" * 40)
-    
+
     # Sort by number of models that solved each exercise
-    sorted_exercises = sorted(
-        exercise_solutions.items(),
-        key=lambda x: len(x[1]),
-        reverse=True
-    )
-    
+    sorted_exercises = sorted(exercise_solutions.items(), key=lambda x: len(x[1]), reverse=True)
+
     for testcase, models in sorted_exercises:
         print(f"{testcase}: solved by {len(models)} models")
-        #print(f"  Models: {', '.join(models)}")
-    
+        # print(f"  Models: {', '.join(models)}")
+
     print("\nSummary:")
     print(f"Total exercises solved at least once: {len(exercise_solutions)}")
     never_solved = 133 - len(exercise_solutions)
     print(f"Never solved by any model: {never_solved}")
-    
+
     # Distribution of solutions
     solved_by_counts = defaultdict(int)
     for models in exercise_solutions.values():
         solved_by_counts[len(models)] += 1
-    
+
     print("\nDistribution of solutions:")
     for count in sorted(solved_by_counts.keys()):
         print(f"Solved by {count} models: {solved_by_counts[count]} exercises")
 
+
 if __name__ == "__main__":
     analyze_exercise_solutions()