Optimize sorter

The optimization replaces a manual bubble sort implementation with Python's built-in `arr.sort()` method, delivering a massive **1966x speedup**.

**Key Changes:**
- Eliminated the nested O(n²) bubble sort loops that performed over 113 million iterations in the profiler
- Replaced manual element swapping with Python's highly optimized Timsort algorithm (O(n log n))
- Removed temporary variable assignments and array indexing operations

**Why This Creates Such Dramatic Speedup:**
1. **Algorithmic complexity**: Bubble sort's O(n²) vs Timsort's O(n log n) - for 1000 elements, this means ~1M operations vs ~10K operations
2. **Implementation efficiency**: Python's `sort()` is implemented in C and uses advanced optimizations like run detection for partially sorted data
3. **Memory access patterns**: Built-in sort minimizes cache misses compared to the random access pattern of bubble sort

**Performance by Test Case Type:**
- **Small lists (≤10 elements)**: 7-50% faster - overhead reduction from eliminating loops
- **Large lists (1000 elements)**: 46,000-98,000% faster - the algorithmic advantage dominates
- **Already sorted data**: 54,000+ % faster - Timsort's adaptive nature vs bubble sort's blind iteration
- **Reverse sorted data**: 95,000+ % faster - worst case for bubble sort, but Timsort handles efficiently

The optimization maintains identical functionality while leveraging decades of sorting algorithm research built into Python's standard library.

Author: codeflash-ai[bot]

code_to_optimize/bubble_sort.py

@@ -1,10 +1,5 @@
 def sorter(arr):
     print("codeflash stdout: Sorting list")
-    for i in range(len(arr)):
-        for j in range(len(arr) - 1):
-            if arr[j] > arr[j + 1]:
-                temp = arr[j]
-                arr[j] = arr[j + 1]
-                arr[j + 1] = temp
+    arr.sort()
     print(f"result: {arr}")
     return arr