⚡️ Speed up method MultiDict.popitem by 33%

[codeflash-ai]

📄 33% (0.33x) speedup for MultiDict.popitem in starlette/datastructures.py

⏱️ Runtime : 112 milliseconds → 84.8 milliseconds (best of 73 runs)

📝 Explanation and details

The optimization improves performance by eliminating unnecessary tuple unpacking and reconstruction in the list comprehension.

Key Change: The original code [(k, v) for k, v in self._list if k != key] unpacks each tuple (k, v) from self._list and immediately reconstructs it [(k, v)]. The optimized version [item for item in old_list if item[0] != key] directly filters tuples without unpacking/repacking, accessing the key via item[0].

Why It's Faster: In Python, tuple unpacking and reconstruction adds overhead for each element. By avoiding this double work and instead using direct tuple indexing, the optimization reduces per-element processing cost. The line profiler shows the filtering operation improved from 99139.7ns per hit to 85751.8ns per hit (~13% improvement per operation).

Performance Characteristics: The optimization is most effective for large-scale scenarios, as shown in the test results where operations on 1000+ items see ~32% speedups. For small MultiDict instances (single items), the improvement is minimal (2-7%), but for large datasets or frequent operations, the cumulative benefit is substantial.

The change maintains identical behavior while reducing computational overhead in the core filtering operation that runs on every popitem() call.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	🔘 None Found
🌀 Generated Regression Tests	✅ 5567 Passed
⏪ Replay Tests	🔘 None Found
🔎 Concolic Coverage Tests	🔘 None Found
📊 Tests Coverage	100.0%

🌀 Generated Regression Tests and Runtime

from __future__ import annotations

from typing import Any, TypeVar

# imports
import pytest
from starlette.datastructures import MultiDict


# Minimal stub for ImmutableMultiDict to allow MultiDict to work
class ImmutableMultiDict:
    def __init__(self, items=None):
        self._list = list(items) if items else []
        self._dict = {}
        for k, v in self._list:
            self._dict[k] = v

    def setlist(self, key, values):
        # Remove all existing entries for key
        self._list = [(k, v) for k, v in self._list if k != key]
        # Add new entries
        for v in values:
            self._list.append((key, v))
        # Set in dict
        self._dict[key] = values[-1]
from starlette.datastructures import MultiDict

# unit tests

# ------------------ Basic Test Cases ------------------

def test_popitem_basic_single():
    # Single key-value pair
    md = MultiDict([('a', 1)])
    k, v = md.popitem() # 1.46μs -> 1.36μs (7.50% faster)

def test_popitem_basic_multiple():
    # Multiple key-value pairs
    md = MultiDict([('x', 10), ('y', 20), ('z', 30)])
    # popitem pops the last inserted key-value (dict order)
    k, v = md.popitem() # 1.56μs -> 1.56μs (0.384% slower)
    # Pop again
    k2, v2 = md.popitem() # 787ns -> 805ns (2.24% slower)
    # Pop last
    k3, v3 = md.popitem() # 490ns -> 538ns (8.92% slower)

def test_popitem_basic_setitem():
    # Using __setitem__ to add keys
    md = MultiDict()
    md['foo'] = 'bar'
    md['baz'] = 'qux'
    k, v = md.popitem() # 1.18μs -> 1.25μs (5.45% slower)
    k2, v2 = md.popitem() # 598ns -> 655ns (8.70% slower)

# ------------------ Edge Test Cases ------------------

def test_popitem_empty():
    # Popitem on empty dict should raise KeyError
    md = MultiDict()
    with pytest.raises(KeyError):
        md.popitem() # 1.14μs -> 1.16μs (1.55% slower)

def test_popitem_duplicate_keys():
    # Multiple values for same key, only latest in dict
    md = MultiDict([('dup', 1), ('dup', 2), ('other', 3)])
    k, v = md.popitem() # 1.47μs -> 1.52μs (3.87% slower)
    # Now pop 'dup'
    k2, v2 = md.popitem() # 841ns -> 775ns (8.52% faster)

def test_popitem_after_delitem():
    # __delitem__ should remove key, popitem should not return deleted key
    md = MultiDict([('a', 1), ('b', 2), ('c', 3)])
    del md['c']
    k, v = md.popitem() # 1.17μs -> 1.38μs (15.0% slower)
    k2, v2 = md.popitem() # 654ns -> 628ns (4.14% faster)

def test_popitem_non_string_keys():
    # Keys of various types
    md = MultiDict([(1, 'one'), (2.0, 'two'), ((3, 4), 'tuple')])
    k, v = md.popitem() # 1.61μs -> 1.66μs (3.25% slower)
    k2, v2 = md.popitem() # 1.01μs -> 908ns (11.5% faster)
    k3, v3 = md.popitem() # 562ns -> 568ns (1.06% slower)

def test_popitem_with_none_key_and_value():
    # None as key and value
    md = MultiDict([(None, None), ('x', None)])
    k, v = md.popitem() # 1.49μs -> 1.46μs (2.47% faster)
    k2, v2 = md.popitem() # 790ns -> 705ns (12.1% faster)

def test_popitem_with_mutable_values():
    # Mutable values (lists, dicts)
    md = MultiDict([('a', [1,2]), ('b', {'x':1})])
    k, v = md.popitem() # 1.41μs -> 1.40μs (0.785% faster)
    k2, v2 = md.popitem() # 691ns -> 649ns (6.47% faster)

# ------------------ Large Scale Test Cases ------------------

def test_popitem_large_scale():
    # Large number of items (up to 1000)
    items = [(f'key{i}', i) for i in range(1000)]
    md = MultiDict(items)
    # Pop all items, check order and correctness
    for i in reversed(range(1000)):
        k, v = md.popitem() # 21.3ms -> 16.1ms (32.5% faster)

def test_popitem_large_scale_duplicate_keys():
    # Many duplicate keys, only last value kept in dict
    items = [('dup', i) for i in range(999)] + [('unique', 1000)]
    md = MultiDict(items)
    # Should pop 'unique' first
    k, v = md.popitem() # 41.2μs -> 31.1μs (32.5% faster)
    # Now only 'dup' remains, with value 998
    k2, v2 = md.popitem() # 25.3μs -> 22.4μs (13.0% faster)

def test_popitem_large_scale_with_setitem():
    # Add 500 items with setitem, then pop all
    md = MultiDict()
    for i in range(500):
        md[f'k{i}'] = i
    for i in reversed(range(500)):
        k, v = md.popitem() # 5.63ms -> 4.28ms (31.6% faster)

def test_popitem_performance():
    # Performance: popitem should not be O(n) per call
    # (Not a strict timing test, but checks that popitem works on large input)
    items = [(str(i), i) for i in range(1000)]
    md = MultiDict(items)
    for _ in range(1000):
        md.popitem() # 21.4ms -> 16.2ms (32.3% faster)
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.
#------------------------------------------------
from __future__ import annotations

from typing import Any, TypeVar

# imports
import pytest  # used for our unit tests
from starlette.datastructures import MultiDict


# Minimal stub for ImmutableMultiDict, just enough for MultiDict to work
class ImmutableMultiDict:
    def __init__(self, items=None):
        self._list = list(items) if items else []
        self._dict = {}
        for k, v in self._list:
            self._dict[k] = v

    def setlist(self, key, values):
        # Remove all previous entries for key
        self._list = [(k, v) for k, v in self._list if k != key]
        # Add new values for key
        for v in values:
            self._list.append((key, v))
        # Update dict
        self._dict[key] = values[-1]
from starlette.datastructures import MultiDict

# unit tests

# --- Basic Test Cases ---

def test_popitem_single_pair():
    # Test with a single key-value pair
    md = MultiDict([('a', 1)])
    k, v = md.popitem() # 1.35μs -> 1.32μs (2.05% faster)

def test_popitem_multiple_pairs():
    # Test with multiple key-value pairs
    md = MultiDict([('a', 1), ('b', 2), ('c', 3)])
    codeflash_output = md.popitem(); popped = codeflash_output # 1.49μs -> 1.50μs (0.602% slower)

def test_popitem_after_setitem():
    # Test after using __setitem__
    md = MultiDict([('x', 10), ('y', 20)])
    md['z'] = 30
    codeflash_output = md.popitem(); popped = codeflash_output # 1.30μs -> 1.39μs (6.96% slower)

def test_popitem_returns_tuple():
    # Ensure popitem returns a tuple of length 2
    md = MultiDict([('foo', 'bar')])
    codeflash_output = md.popitem(); result = codeflash_output # 1.33μs -> 1.28μs (3.58% faster)

# --- Edge Test Cases ---

def test_popitem_empty_dict_raises():
    # Test popping from empty MultiDict raises KeyError
    md = MultiDict()
    with pytest.raises(KeyError):
        md.popitem() # 1.17μs -> 1.19μs (1.60% slower)

def test_popitem_key_with_multiple_values():
    # Test when a key has multiple values (should only keep the last one in _dict)
    md = MultiDict([('a', 1), ('a', 2), ('b', 3)])
    # _dict will have 'a': 2, 'b': 3
    codeflash_output = md.popitem(); popped = codeflash_output # 1.52μs -> 1.54μs (0.911% slower)
    # Now pop again
    codeflash_output = md.popitem(); popped2 = codeflash_output # 814ns -> 753ns (8.10% faster)

def test_popitem_after_delitem():
    # Test popitem after deleting a key
    md = MultiDict([('a', 1), ('b', 2)])
    del md['a']
    codeflash_output = md.popitem(); popped = codeflash_output # 1.04μs -> 1.23μs (15.6% slower)

def test_popitem_order():
    # Test order: popitem should remove last inserted key from dict
    md = MultiDict([('x', 1), ('y', 2)])
    md['z'] = 3
    codeflash_output = md.popitem(); popped = codeflash_output # 1.28μs -> 1.39μs (7.84% slower)
    codeflash_output = md.popitem(); popped2 = codeflash_output # 685ns -> 720ns (4.86% slower)
    codeflash_output = md.popitem(); popped3 = codeflash_output # 500ns -> 542ns (7.75% slower)

def test_popitem_with_non_str_keys():
    # Test with non-string keys (int, tuple)
    md = MultiDict([(1, 'one'), ((2, 3), 'tuple')])
    codeflash_output = md.popitem(); popped = codeflash_output # 1.57μs -> 1.59μs (1.57% slower)
    codeflash_output = md.popitem(); popped2 = codeflash_output # 701ns -> 624ns (12.3% faster)

def test_popitem_side_effect_on_list():
    # Ensure _list is updated correctly after popitem
    md = MultiDict([('a', 1), ('b', 2), ('a', 3)])
    # _dict: {'a': 3, 'b': 2}
    codeflash_output = md.popitem(); popped = codeflash_output # 1.47μs -> 1.52μs (2.90% slower)

# --- Large Scale Test Cases ---

def test_popitem_large_multidict():
    # Test with a large MultiDict (1000 items)
    items = [(f'key{i}', i) for i in range(1000)]
    md = MultiDict(items)
    # Pop all items and collect keys
    popped_keys = []
    for _ in range(1000):
        k, v = md.popitem() # 21.4ms -> 16.2ms (32.2% faster)
        popped_keys.append(k)

def test_popitem_performance_large():
    # Test performance: popitem on 1000 items should not be O(n^2)
    # This is a smoke test to ensure it doesn't hang or error
    items = [(str(i), i) for i in range(1000)]
    md = MultiDict(items)
    for _ in range(1000):
        md.popitem() # 21.4ms -> 16.2ms (32.4% faster)

def test_popitem_with_duplicate_keys_large():
    # Test with duplicate keys in a large MultiDict
    items = []
    for i in range(500):
        items.append(('dup', i))
        items.append((f'unique{i}', i))
    md = MultiDict(items)
    # Pop all unique keys first
    for i in reversed(range(500)):
        k, v = md.popitem() # 15.5ms -> 11.4ms (35.3% faster)
    # Only 'dup' remains
    k, v = md.popitem() # 12.8μs -> 11.4μs (12.4% faster)

def test_popitem_after_setlist_large():
    # Test after setlist on large MultiDict
    md = MultiDict([(f'k{i}', i) for i in range(500)])
    md.setlist('special', [1001, 1002, 1003])
    k, v = md.popitem() # 21.8μs -> 16.8μs (29.9% faster)
    # Pop remaining keys
    for i in reversed(range(500)):
        k, v = md.popitem() # 5.59ms -> 4.26ms (31.2% faster)

# --- Determinism Test ---

def test_popitem_deterministic_order():
    # Ensure popitem always pops the last inserted key
    md = MultiDict([('a', 1), ('b', 2), ('c', 3)])
    order = []
    while md._dict:
        k, v = md.popitem() # 2.99μs -> 2.90μs (3.21% faster)
        order.append((k, v))
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.
#------------------------------------------------
from starlette.datastructures import MultiDict

def test_MultiDict_popitem():
    MultiDict.popitem(MultiDict(=0))

To edit these changes git checkout codeflash/optimize-MultiDict.popitem-mhbtc9xf and push.