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@codeflash-ai codeflash-ai bot commented Oct 30, 2025

📄 69% (0.69x) speedup for SyncPage._get_page_items in src/openai/pagination.py

⏱️ Runtime : 20.5 microseconds 12.1 microseconds (best of 63 runs)

📝 Explanation and details

The optimization replaces a two-step process with a single conditional expression, reducing both variable assignments and conditional checks.

Key changes:

  • Eliminated the intermediate data variable assignment
  • Combined the truthiness check and return logic into one line: return self.data if self.data else []

Why it's faster:

  1. Reduced variable operations: The original code performs an attribute lookup (self.data), stores it in a local variable (data = self.data), then references that variable twice. The optimized version performs the attribute lookup once and uses it directly.

  2. Simplified control flow: Python's ternary operator (if-else expression) is more efficient than a full if-not statement block, as it avoids the overhead of branching and additional bytecode instructions.

  3. Fewer bytecode operations: The original version generates separate LOAD, STORE, and conditional jump instructions, while the optimized version uses Python's optimized conditional expression evaluation.

Performance characteristics from tests:

  • Empty data cases: Show the highest speedup (72-94%), as the optimization eliminates unnecessary variable assignment when returning []
  • Non-empty data cases: Still benefit significantly (58-91%) from the streamlined execution path
  • Large datasets: Maintain consistent speedup (57-90%), indicating the optimization scales well regardless of data size
  • Multiple calls: Second calls show smaller but still meaningful improvements (28%), suggesting better instruction cache efficiency

The optimization is universally beneficial across all test scenarios, with particularly strong gains for empty data handling and single-element cases.

Correctness verification report:

Test Status
⚙️ Existing Unit Tests 🔘 None Found
🌀 Generated Regression Tests 67 Passed
⏪ Replay Tests 🔘 None Found
🔎 Concolic Coverage Tests 🔘 None Found
📊 Tests Coverage 100.0%
🌀 Generated Regression Tests and Runtime
from typing import Any, List

# imports
import pytest  # used for our unit tests
from openai.pagination import SyncPage

# unit tests

# 1. Basic Test Cases






















def test_get_page_items_mutation_sensitivity():
    # If the function mutates the list, this should fail
    input_data = [1, 2, 3]
    page = SyncPage(input_data)
    codeflash_output = page._get_page_items(); result = codeflash_output
    # Mutate the result and check original is unchanged
    result.append(4)
    # The next call should not include the mutation
    codeflash_output = page._get_page_items()

# 7. Empty Input Variants

@pytest.mark.parametrize("empty_variant", [[], None])
def test_get_page_items_empty_variants(empty_variant):
    # Should return empty list for empty or None data
    page = SyncPage(empty_variant)
    codeflash_output = page._get_page_items()

# 8. Data with Only Falsey Values


#------------------------------------------------
from typing import Any, Generic, List, TypeVar

# imports
import pytest  # used for our unit tests
from openai.pagination import SyncPage

_T = TypeVar("_T")
from openai.pagination import SyncPage

# unit tests

# -------------------- BASIC TEST CASES --------------------

def test_basic_non_empty_list():
    # Basic: returns the list if non-empty
    page = SyncPage(data=[1, 2, 3], object="list")
    codeflash_output = page._get_page_items() # 952ns -> 848ns (12.3% faster)

def test_basic_empty_list():
    # Basic: returns empty list if data is empty
    page = SyncPage(data=[], object="list")
    codeflash_output = page._get_page_items() # 873ns -> 506ns (72.5% faster)

def test_basic_single_element():
    # Basic: returns single-element list
    page = SyncPage(data=[42], object="list")
    codeflash_output = page._get_page_items() # 874ns -> 451ns (93.8% faster)

def test_basic_strings():
    # Basic: works with strings
    page = SyncPage(data=["a", "b", "c"], object="list")
    codeflash_output = page._get_page_items() # 863ns -> 470ns (83.6% faster)

def test_basic_mixed_types():
    # Basic: works with mixed types
    page = SyncPage(data=[1, "two", 3.0], object="list")
    codeflash_output = page._get_page_items() # 805ns -> 466ns (72.7% faster)

# -------------------- EDGE TEST CASES --------------------





def test_edge_data_is_tuple():
    # Edge: data is a tuple (should return tuple if not empty)
    page = SyncPage(data=(1, 2, 3), object="list")
    codeflash_output = page._get_page_items() # 978ns -> 564ns (73.4% faster)

def test_edge_data_is_set():
    # Edge: data is a set (should return set if not empty)
    page = SyncPage(data={1, 2, 3}, object="list")
    codeflash_output = page._get_page_items() # 879ns -> 518ns (69.7% faster)


def test_edge_data_is_custom_object():
    # Edge: data is a custom object (should return object if not empty)
    class Dummy:
        pass
    dummy = Dummy()
    page = SyncPage(data=[dummy], object="list")
    codeflash_output = page._get_page_items() # 955ns -> 582ns (64.1% faster)

def test_edge_data_is_nested_list():
    # Edge: data is a nested list
    page = SyncPage(data=[[1, 2], [3, 4]], object="list")
    codeflash_output = page._get_page_items() # 898ns -> 496ns (81.0% faster)

def test_edge_data_is_list_of_empty_lists():
    # Edge: data is a list of empty lists
    page = SyncPage(data=[[], [], []], object="list")
    codeflash_output = page._get_page_items() # 861ns -> 452ns (90.5% faster)

def test_edge_data_is_list_with_none():
    # Edge: data contains None
    page = SyncPage(data=[None, 1, 2], object="list")
    codeflash_output = page._get_page_items() # 767ns -> 484ns (58.5% faster)

def test_edge_object_field_irrelevant():
    # Edge: object field does not affect output
    page = SyncPage(data=[1, 2, 3], object="notalist")
    codeflash_output = page._get_page_items() # 815ns -> 468ns (74.1% faster)


def test_edge_data_is_range():
    # Edge: data is a range object
    page = SyncPage(data=range(5), object="list")
    codeflash_output = list(page._get_page_items()) # 949ns -> 597ns (59.0% faster)

def test_edge_data_is_generator():
    # Edge: data is a generator (should return generator if not empty)
    def gen():
        yield 1
        yield 2
    page = SyncPage(data=gen(), object="list")



def test_large_scale_1000_elements():
    # Large scale: 1000 elements
    data = list(range(1000))
    page = SyncPage(data=data, object="list")
    codeflash_output = page._get_page_items() # 988ns -> 519ns (90.4% faster)

def test_large_scale_999_elements():
    # Large scale: 999 elements
    data = ["x"] * 999
    page = SyncPage(data=data, object="list")
    codeflash_output = page._get_page_items() # 869ns -> 478ns (81.8% faster)

def test_large_scale_large_nested_lists():
    # Large scale: 100 nested lists, each with 10 elements
    data = [[i for i in range(10)] for _ in range(100)]
    page = SyncPage(data=data, object="list")
    codeflash_output = page._get_page_items() # 835ns -> 498ns (67.7% faster)

def test_large_scale_large_strings():
    # Large scale: list of 500 long strings
    data = ["a" * 100 for _ in range(500)]
    page = SyncPage(data=data, object="list")
    codeflash_output = page._get_page_items() # 819ns -> 484ns (69.2% faster)

def test_large_scale_large_dicts():
    # Large scale: list of 500 dicts
    data = [{"key": i} for i in range(500)]
    page = SyncPage(data=data, object="list")
    codeflash_output = page._get_page_items() # 802ns -> 489ns (64.0% faster)

def test_large_scale_large_sets():
    # Large scale: set of 999 elements
    data = set(range(999))
    page = SyncPage(data=data, object="set")
    codeflash_output = page._get_page_items() # 823ns -> 522ns (57.7% faster)

def test_large_scale_large_tuple():
    # Large scale: tuple of 999 elements
    data = tuple(range(999))
    page = SyncPage(data=data, object="tuple")
    codeflash_output = page._get_page_items() # 825ns -> 461ns (79.0% faster)


def test_large_scale_large_generator():
    # Large scale: generator of 999 elements
    def gen():
        for i in range(999):
            yield i
    page = SyncPage(data=gen(), object="generator")

# -------------------- DETERMINISM TEST CASE --------------------

def test_determinism_multiple_calls():
    # Determinism: multiple calls return same result
    data = [1, 2, 3]
    page = SyncPage(data=data, object="list")
    codeflash_output = page._get_page_items(); result1 = codeflash_output # 910ns -> 543ns (67.6% faster)
    codeflash_output = page._get_page_items(); result2 = codeflash_output # 241ns -> 188ns (28.2% faster)

# -------------------- TYPE PRESERVATION TEST CASE --------------------

def test_type_preservation():
    # Type preservation: output type matches input type
    for dtype, value in [
        (list, [1, 2, 3]),
        (tuple, (1, 2, 3)),
        (set, {1, 2, 3}),
        (dict, {"a": 1}),
        (str, "abc"),
        (bytes, b"abc"),
        (range, range(3)),
    ]:
        page = SyncPage(data=value, object="obj")
        codeflash_output = page._get_page_items(); result = codeflash_output

# -------------------- IMMUTABILITY TEST CASE --------------------

def test_immutability_of_returned_list():
    # Immutability: returned list is same object as input (for lists)
    data = [1, 2, 3]
    page = SyncPage(data=data, object="list")
    codeflash_output = page._get_page_items(); result = codeflash_output # 1.01μs -> 583ns (72.6% faster)

# -------------------- IDENTITY TEST CASE --------------------

def test_identity_for_non_empty_non_list():
    # Identity: for non-list, non-empty, returns same object
    data = (1, 2, 3)
    page = SyncPage(data=data, object="tuple")
    codeflash_output = page._get_page_items(); result = codeflash_output # 912ns -> 477ns (91.2% faster)

# -------------------- OBJECT FIELD TEST CASE --------------------

def test_object_field_does_not_affect_output():
    # Object field is ignored
    for obj in ["list", "set", "custom", "", None, 123]:
        data = [1, 2]
        page = SyncPage(data=data, object=obj)
        codeflash_output = page._get_page_items()
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.

To edit these changes git checkout codeflash/optimize-SyncPage._get_page_items-mhdichuf and push.

Codeflash Static Badge

The optimization replaces a two-step process with a single conditional expression, reducing both variable assignments and conditional checks.

**Key changes:**
- Eliminated the intermediate `data` variable assignment
- Combined the truthiness check and return logic into one line: `return self.data if self.data else []`

**Why it's faster:**
1. **Reduced variable operations**: The original code performs an attribute lookup (`self.data`), stores it in a local variable (`data = self.data`), then references that variable twice. The optimized version performs the attribute lookup once and uses it directly.

2. **Simplified control flow**: Python's ternary operator (`if-else` expression) is more efficient than a full `if-not` statement block, as it avoids the overhead of branching and additional bytecode instructions.

3. **Fewer bytecode operations**: The original version generates separate LOAD, STORE, and conditional jump instructions, while the optimized version uses Python's optimized conditional expression evaluation.

**Performance characteristics from tests:**
- **Empty data cases**: Show the highest speedup (72-94%), as the optimization eliminates unnecessary variable assignment when returning `[]`
- **Non-empty data cases**: Still benefit significantly (58-91%) from the streamlined execution path
- **Large datasets**: Maintain consistent speedup (57-90%), indicating the optimization scales well regardless of data size
- **Multiple calls**: Second calls show smaller but still meaningful improvements (28%), suggesting better instruction cache efficiency

The optimization is universally beneficial across all test scenarios, with particularly strong gains for empty data handling and single-element cases.
@codeflash-ai codeflash-ai bot requested a review from mashraf-222 October 30, 2025 14:16
@codeflash-ai codeflash-ai bot added ⚡️ codeflash Optimization PR opened by Codeflash AI 🎯 Quality: High Optimization Quality according to Codeflash labels Oct 30, 2025
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