⚡️ Speed up function undo by 13%

[codeflash-ai]

📄 13% (0.13x) speedup for undo in gradio/themes/builder_app.py

⏱️ Runtime : 78.3 microseconds → 69.0 microseconds (best of 76 runs)

📝 Explanation and details

The optimization replaces list(old[1]) with *old[1] in the return statement of the undo function, achieving a 13% speedup.

Key change: The original code used + list(old[1]) to concatenate the tuple elements, while the optimized version uses *old[1] (unpacking operator) to expand the tuple elements directly into the list.

Why this is faster: The list() constructor creates an intermediate list object from the tuple, which then gets concatenated with the existing list. The unpacking operator *old[1] directly expands the tuple elements into the list literal [history_var, old[0], *old[1]], eliminating the need for:

1. Creating an intermediate list object
2. The list concatenation operation (+)

Performance impact: Line profiler shows the optimized return statement takes ~881.8 ns per hit vs ~1276.3 ns in the original (31% faster for that specific line). This optimization is particularly effective for larger tuples, as evidenced by test cases with large data showing 50%+ speedups.

When this optimization shines: The test results show the greatest improvements (20-56%) occur with larger tuples or complex data structures, making this optimization valuable for applications that process substantial amounts of historical data through the undo functionality.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	🔘 None Found
🌀 Generated Regression Tests	✅ 45 Passed
⏪ Replay Tests	🔘 None Found
🔎 Concolic Coverage Tests	🔘 None Found
📊 Tests Coverage	100.0%

🌀 Generated Regression Tests and Runtime

import pytest
from gradio.themes.builder_app import undo

# unit tests

# Helper to simulate gr.State for comparison
class DummyState:
    def __init__(self, value):
        self.value = value
    def __eq__(self, other):
        return isinstance(other, DummyState) and self.value == other.value
    def __repr__(self):
        return f"DummyState({self.value!r})"

# --- Basic Test Cases ---



def test_undo_two_element_history():
    # Basic: history_var has two elements
    history_var = [("a", (1, 2)), ("b", (3, 4))]
    # After undo: pop "b", then pop "a", return [[], "a", 1, 2]
    codeflash_output = undo(history_var.copy()); result = codeflash_output # 1.51μs -> 1.36μs (11.1% faster)

def test_undo_three_element_history():
    # Basic: history_var has three elements
    history_var = [("a", (1,)), ("b", (2,)), ("c", (3,))]
    # After undo: pop "c", pop "b", return [[("a", (1,))], "b", 2]
    codeflash_output = undo(history_var.copy()); result = codeflash_output # 1.36μs -> 1.25μs (9.31% faster)

def test_undo_history_with_varied_tuple_lengths():
    # Basic: history_var with tuples of different lengths
    history_var = [("x", ()), ("y", (1,)), ("z", (2, 3, 4))]
    # After undo: pop "z", pop "y", return [[("x", ())], "y", 1]
    codeflash_output = undo(history_var.copy()); result = codeflash_output # 1.37μs -> 1.16μs (17.9% faster)

def test_undo_history_with_single_tuple_element():
    # Basic: history_var with only one tuple element
    history_var = [("foo", ()), ("bar", ())]
    # After undo: pop "bar", pop "foo", return [[], "foo"]
    codeflash_output = undo(history_var.copy()); result = codeflash_output # 1.47μs -> 1.27μs (15.9% faster)

# --- Edge Test Cases ---

def test_undo_history_with_non_tuple_second_elements():
    # Edge: second element is not a tuple
    history_var = [("a", 1), ("b", 2)]
    # After undo: pop "b", pop "a", return [[], "a"] + list(1) -> TypeError
    with pytest.raises(TypeError):
        undo(history_var.copy()) # 2.51μs -> 2.71μs (7.42% slower)

def test_undo_history_with_tuple_second_element_none():
    # Edge: second element is None
    history_var = [("a", None), ("b", None)]
    # After undo: pop "b", pop "a", return [[], "a"] + list(None) -> TypeError
    with pytest.raises(TypeError):
        undo(history_var.copy()) # 2.34μs -> 2.72μs (14.0% slower)

def test_undo_history_with_mixed_types():
    # Edge: history_var with mixed types
    history_var = [("a", (1,)), ("b", ["x", "y"])]
    # After undo: pop "b", pop "a", return [[], "a", 1]
    codeflash_output = undo(history_var.copy()); result = codeflash_output # 1.64μs -> 1.36μs (20.6% faster)

def test_undo_history_with_nested_tuples():
    # Edge: history_var with nested tuples
    history_var = [("a", ((1, 2),)), ("b", ((3, 4),))]
    # After undo: pop "b", pop "a", return [[], "a", (1,2)]
    codeflash_output = undo(history_var.copy()); result = codeflash_output # 1.56μs -> 1.31μs (19.4% faster)

def test_undo_history_with_dict_in_tuple():
    # Edge: tuple contains a dict
    history_var = [("a", ({"x": 1},)), ("b", ({"y": 2},))]
    codeflash_output = undo(history_var.copy()); result = codeflash_output # 1.47μs -> 1.33μs (10.9% faster)

def test_undo_history_with_large_tuple():
    # Edge: tuple with many elements
    history_var = [("a", tuple(range(10))), ("b", tuple(range(10, 20)))]
    codeflash_output = undo(history_var.copy()); result = codeflash_output # 1.57μs -> 1.22μs (28.3% faster)

def test_undo_history_with_non_string_first_element():
    # Edge: first element not a string
    history_var = [(123, (1, 2)), (456, (3, 4))]
    codeflash_output = undo(history_var.copy()); result = codeflash_output # 1.51μs -> 1.28μs (18.5% faster)

def test_undo_history_with_mutable_second_element():
    # Edge: second element is a mutable list
    history_var = [("a", [1, 2]), ("b", [3, 4])]
    codeflash_output = undo(history_var.copy()); result = codeflash_output # 1.55μs -> 1.27μs (21.9% faster)

def test_undo_history_with_non_iterable_second_element():
    # Edge: second element is non-iterable (int)
    history_var = [("a", 1), ("b", 2)]
    with pytest.raises(TypeError):
        undo(history_var.copy()) # 2.38μs -> 2.62μs (9.19% slower)

# --- Large Scale Test Cases ---

def test_undo_large_history():
    # Large: history_var with 1000 elements
    history_var = [(f"item{i}", (i, i+1)) for i in range(1000)]
    # After undo: pop last, pop second last, return with 998 elements
    codeflash_output = undo(history_var.copy()); result = codeflash_output # 1.40μs -> 1.19μs (18.1% faster)

def test_undo_large_history_with_large_tuple():
    # Large: history_var with 1000 elements, each tuple has 10 elements
    history_var = [(f"item{i}", tuple(range(i, i+10))) for i in range(1000)]
    codeflash_output = undo(history_var.copy()); result = codeflash_output # 1.51μs -> 1.24μs (21.7% faster)

def test_undo_multiple_calls_reduces_history():
    # Large: call undo repeatedly to reduce history
    history_var = [(f"item{i}", (i,)) for i in range(10)]
    for _ in range(5):
        codeflash_output = undo(history_var); result = codeflash_output # 3.49μs -> 3.17μs (10.2% faster)
        history_var = result[0]


def test_undo_history_var_mutated_on_undo():
    # Large: ensure undo mutates history_var when undoing
    history_var = [("a", (1,)), ("b", (2,))]
    original = history_var.copy()
    undo(history_var) # 1.57μs -> 1.32μs (19.1% faster)

# --- Determinism Test ---

def test_undo_determinism():
    # Determinism: repeated calls yield same result
    history_var = [("x", (5,)), ("y", (7,))]
    codeflash_output = undo(history_var.copy()); result1 = codeflash_output # 1.45μs -> 1.31μs (11.0% faster)
    codeflash_output = undo(history_var.copy()); result2 = codeflash_output # 630ns -> 610ns (3.28% faster)
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.
#------------------------------------------------
import pytest  # used for our unit tests
from gradio.themes.builder_app import undo

# -------------------------------
# UNIT TESTS FOR THE undo FUNCTION
# -------------------------------

# Basic Test Cases


def test_undo_basic_two_elements():
    # Undo on a history with two elements should return the first one and its associated data
    history = [[1, (2, 3)], [4, (5, 6)]]
    codeflash_output = undo(history.copy()); result = codeflash_output # 1.60μs -> 1.30μs (23.1% faster)

def test_undo_basic_three_elements():
    # Undo on a history with three elements should return the second one and its associated data
    history = [[1, (2, 3)], [4, (5, 6)], [7, (8, 9)]]
    codeflash_output = undo(history.copy()); result = codeflash_output # 1.45μs -> 1.15μs (26.1% faster)

# Edge Test Cases


def test_undo_history_with_non_tuple_data():
    # Undo where the second element is not a tuple but another iterable
    history = [[1, [2, 3]], [4, [5, 6]]]
    codeflash_output = undo(history.copy()); result = codeflash_output # 1.51μs -> 1.25μs (20.5% faster)


def test_undo_history_with_nested_tuples():
    # Undo where the second element is a nested tuple
    history = [[1, ((2, 3), 4)], [5, ((6, 7), 8)]]
    codeflash_output = undo(history.copy()); result = codeflash_output # 1.73μs -> 1.37μs (26.2% faster)

def test_undo_history_with_mixed_types():
    # Undo where the second element contains mixed types
    history = [[1, ("a", 2, None)], [3, ("b", 4, True)]]
    codeflash_output = undo(history.copy()); result = codeflash_output # 1.61μs -> 1.24μs (29.4% faster)



def test_undo_history_with_non_iterable_data():
    # Undo where the second element is not iterable (e.g., int)
    history = [[1, 2], [3, 4]]
    # Should raise TypeError when trying to convert int to list
    with pytest.raises(TypeError):
        undo(history.copy()) # 2.61μs -> 2.78μs (6.12% slower)

# Large Scale Test Cases

def test_undo_large_history():
    # Undo on a large history (1000 elements)
    history = []
    for i in range(1000):
        history.append([i, (i+1, i+2)])
    # After undo, history should have 998 elements, and result should be [history[:998], 998, 999, 1000]
    codeflash_output = undo(history.copy()); result = codeflash_output # 1.44μs -> 1.20μs (20.0% faster)


def test_undo_large_history_edge_case():
    # Undo on a history with exactly two elements, large data in each
    data1 = tuple(range(500))
    data2 = tuple(range(500, 1000))
    history = [[0, data1], [1, data2]]
    codeflash_output = undo(history.copy()); result = codeflash_output # 3.15μs -> 2.01μs (56.2% faster)

def test_undo_large_history_with_non_tuple_data():
    # Undo on a history with large list data instead of tuple
    data1 = list(range(500))
    data2 = list(range(500, 1000))
    history = [[0, data1], [1, data2]]
    codeflash_output = undo(history.copy()); result = codeflash_output # 3.17μs -> 2.04μs (55.4% faster)

# Edge Case: Mutability

def test_undo_does_not_mutate_original_history():
    # Ensure undo does not mutate the original history input
    history = [[1, (2, 3)], [4, (5, 6)]]
    history_copy = history.copy()
    codeflash_output = undo(history_copy); result = codeflash_output # 1.60μs -> 1.24μs (29.1% faster)

# Edge Case: Pop Consistency

def test_undo_pop_removes_last_two_items():
    # Ensure undo removes the last two items from history_var
    history = [[1, (2, 3)], [4, (5, 6)], [7, (8, 9)]]
    history_copy = history.copy()
    codeflash_output = undo(history_copy); result = codeflash_output # 1.43μs -> 1.08μs (31.9% faster)

# Edge Case: Undo on history with None values

def test_undo_history_with_none_values():
    history = [[None, (None,)], [1, (2,)]]
    codeflash_output = undo(history.copy()); result = codeflash_output # 1.61μs -> 1.27μs (26.7% faster)

# Edge Case: Undo on history with empty tuples/lists

def test_undo_history_with_empty_tuple():
    history = [[1, ()], [2, ()]]
    codeflash_output = undo(history.copy()); result = codeflash_output # 1.52μs -> 1.20μs (26.9% faster)

def test_undo_history_with_empty_list():
    history = [[1, []], [2, []]]
    codeflash_output = undo(history.copy()); result = codeflash_output # 1.59μs -> 1.24μs (27.7% faster)

# Edge Case: Undo on history with different length data

def test_undo_history_with_varied_length_data():
    history = [[1, (2,)], [3, (4, 5, 6)]]
    codeflash_output = undo(history.copy()); result = codeflash_output # 1.60μs -> 1.25μs (27.3% faster)

# Edge Case: Undo on history with dict as data

def test_undo_history_with_dict_data():
    history = [[1, {"a": 2}], [3, {"b": 4}]]
    codeflash_output = undo(history.copy()); result = codeflash_output # 1.71μs -> 1.54μs (10.7% faster)

# Edge Case: Undo on history with set as data

def test_undo_history_with_set_data():
    history = [[1, {2, 3}], [4, {5, 6}]]
    codeflash_output = undo(history.copy()); result = codeflash_output # 1.83μs -> 1.60μs (14.3% faster)
# 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-undo-mhlhp9j1 and push.