⚡️ Speed up function coco_categories_to_classes by 22%

[codeflash-ai]

📄 22% (0.22x) speedup for coco_categories_to_classes in supervision/dataset/formats/coco.py

⏱️ Runtime : 259 microseconds → 213 microseconds (best of 557 runs)

📝 Explanation and details

o3-mini
We can speed up the sort by replacing the lambda function with operator.itemgetter, which is typically faster since it avoids the overhead of calling a lambda for every element.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	✅ 12 Passed
🌀 Generated Regression Tests	✅ 33 Passed
⏪ Replay Tests	🔘 None Found
🔎 Concolic Coverage Tests	🔘 None Found
📊 Tests Coverage	100.0%

⚙️ Existing Unit Tests Details

- dataset/formats/test_coco.py

🌀 Generated Regression Tests Details

from typing import List

# imports
import pytest  # used for our unit tests
from supervision.dataset.formats.coco import coco_categories_to_classes

# unit tests

def test_basic_functionality():
    # Standard Input
    codeflash_output = coco_categories_to_classes([{"id": 1, "name": "cat"}, {"id": 2, "name": "dog"}])
    # Unsorted Input
    codeflash_output = coco_categories_to_classes([{"id": 2, "name": "dog"}, {"id": 1, "name": "cat"}])

def test_edge_cases():
    # Empty List
    codeflash_output = coco_categories_to_classes([])
    # Single Element
    codeflash_output = coco_categories_to_classes([{"id": 1, "name": "cat"}])
    # Duplicate IDs
    codeflash_output = coco_categories_to_classes([{"id": 1, "name": "cat"}, {"id": 1, "name": "dog"}])

def test_missing_keys():
    # Missing 'id' Key
    with pytest.raises(KeyError):
        coco_categories_to_classes([{"name": "cat"}])
    # Missing 'name' Key
    with pytest.raises(KeyError):
        coco_categories_to_classes([{"id": 1}])


def test_large_scale():
    # Large Input List
    large_input = [{"id": i, "name": f"name_{i}"} for i in range(10000, 9000, -1)]
    expected_output = [f"name_{i}" for i in range(1, 1001)]
    codeflash_output = coco_categories_to_classes(large_input)
    # Performance with Random IDs
    import random
    random_ids = random.sample(range(1, 1001), 1000)
    random_input = [{"id": i, "name": f"name_{i}"} for i in random_ids]
    codeflash_output = coco_categories_to_classes(random_input)

def test_special_characters_in_names():
    # Names with Special Characters
    codeflash_output = coco_categories_to_classes([{"id": 1, "name": "c@t"}, {"id": 2, "name": "d#g"}])
    # Names with Spaces
    codeflash_output = coco_categories_to_classes([{"id": 1, "name": "cat "}, {"id": 2, "name": " dog"}])

def test_non_sequential_ids():
    # Non-Sequential IDs
    codeflash_output = coco_categories_to_classes([{"id": 10, "name": "cat"}, {"id": 5, "name": "dog"}])
    # Negative IDs
    codeflash_output = coco_categories_to_classes([{"id": -1, "name": "cat"}, {"id": -2, "name": "dog"}])

def test_mixed_valid_and_invalid_entries():
    # Mixed Valid and Invalid Entries
    with pytest.raises(KeyError):
        coco_categories_to_classes([{"id": 1, "name": "cat"}, {"name": "dog"}, {"id": 2, "name": "bird"}])

def test_duplicate_names():
    # Duplicate Names
    codeflash_output = coco_categories_to_classes([{"id": 1, "name": "cat"}, {"id": 2, "name": "cat"}])

def test_ids_with_different_data_types():
    # Mixed Type IDs
    with pytest.raises(TypeError):
        coco_categories_to_classes([{"id": 1, "name": "cat"}, {"id": "2", "name": "dog"}])
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.

from typing import List

# imports
import pytest  # used for our unit tests
from supervision.dataset.formats.coco import coco_categories_to_classes

# unit tests

def test_basic_valid_input():
    # Test with multiple categories with unique IDs
    coco_categories = [{"id": 2, "name": "cat"}, {"id": 1, "name": "dog"}]
    codeflash_output = coco_categories_to_classes(coco_categories)

    coco_categories = [{"id": 3, "name": "bird"}, {"id": 2, "name": "fish"}, {"id": 1, "name": "hamster"}]
    codeflash_output = coco_categories_to_classes(coco_categories)

def test_empty_input():
    # Test with an empty list
    coco_categories = []
    codeflash_output = coco_categories_to_classes(coco_categories)

def test_single_element_input():
    # Test with a single category
    coco_categories = [{"id": 1, "name": "dog"}]
    codeflash_output = coco_categories_to_classes(coco_categories)

def test_already_sorted_input():
    # Test with categories already sorted by ID
    coco_categories = [{"id": 1, "name": "dog"}, {"id": 2, "name": "cat"}]
    codeflash_output = coco_categories_to_classes(coco_categories)

def test_reverse_sorted_input():
    # Test with categories sorted in reverse order by ID
    coco_categories = [{"id": 2, "name": "cat"}, {"id": 1, "name": "dog"}]
    codeflash_output = coco_categories_to_classes(coco_categories)

def test_duplicate_ids():
    # Test with categories having duplicate IDs
    coco_categories = [{"id": 1, "name": "dog"}, {"id": 1, "name": "cat"}]
    codeflash_output = coco_categories_to_classes(coco_categories)  # Order is not guaranteed for duplicates


def test_missing_keys():
    # Test with categories missing the "id" or "name" key
    coco_categories = [{"id": 1, "name": "dog"}, {"id": 2}]
    with pytest.raises(KeyError):
        coco_categories_to_classes(coco_categories)

    coco_categories = [{"id": 1}, {"id": 2, "name": "cat"}]
    with pytest.raises(KeyError):
        coco_categories_to_classes(coco_categories)

def test_large_input():
    # Test with a large number of categories
    coco_categories = [{"id": i, "name": f"category_{i}"} for i in range(1000)]
    expected_output = [f"category_{i}" for i in range(1000)]
    codeflash_output = coco_categories_to_classes(coco_categories)

def test_non_unique_names():
    # Test with categories having non-unique names but different IDs
    coco_categories = [{"id": 1, "name": "animal"}, {"id": 2, "name": "animal"}]
    codeflash_output = coco_categories_to_classes(coco_categories)

def test_unsorted_input_with_mixed_order():
    # Test with categories in a random order
    coco_categories = [{"id": 3, "name": "bird"}, {"id": 1, "name": "dog"}, {"id": 2, "name": "cat"}]
    codeflash_output = coco_categories_to_classes(coco_categories)

def test_negative_ids():
    # Test with categories having negative IDs
    coco_categories = [{"id": -1, "name": "dog"}, {"id": -2, "name": "cat"}]
    codeflash_output = coco_categories_to_classes(coco_categories)

def test_zero_id():
    # Test with categories having an ID of zero
    coco_categories = [{"id": 0, "name": "dog"}, {"id": 1, "name": "cat"}]
    codeflash_output = coco_categories_to_classes(coco_categories)

def test_large_ids():
    # Test with categories having very large ID values
    coco_categories = [{"id": 999999999, "name": "dog"}, {"id": 1000000000, "name": "cat"}]
    codeflash_output = coco_categories_to_classes(coco_categories)

def test_special_characters_in_names():
    # Test with categories having special characters in their names
    coco_categories = [{"id": 1, "name": "d@g"}, {"id": 2, "name": "c@t"}]
    codeflash_output = coco_categories_to_classes(coco_categories)

def test_empty_strings_in_names():
    # Test with categories having empty strings as names
    coco_categories = [{"id": 1, "name": ""}, {"id": 2, "name": "cat"}]
    codeflash_output = coco_categories_to_classes(coco_categories)

# Run the tests
if __name__ == "__main__":
    pytest.main()
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.