⚡️ Speed up function _get_single_group_name by 21%

[codeflash-ai]

📄 21% (0.21x) speedup for _get_single_group_name in pandas/core/strings/accessor.py

⏱️ Runtime : 48.9 microseconds → 40.2 microseconds (best of 236 runs)

📝 Explanation and details

The optimization replaces an explicit if-else branch with a single call to next() using its default parameter. The original code checks if regex.groupindex: and then branches to either return next(iter(regex.groupindex)) or None. The optimized version eliminates this branching by using next(iter(regex.groupindex), None), where the second argument serves as the default value when the iterator is empty.

Key Performance Benefits:

1. Eliminates branch prediction overhead - The CPU no longer needs to predict which branch to take, reducing instruction pipeline stalls
2. Reduces total instructions executed - One function call instead of a conditional check plus branching logic
3. Better instruction cache utilization - Smaller code footprint means better cache hit rates

Why This Optimization Works:
In Python, checking truthiness of regex.groupindex (a dictionary) requires evaluating whether it's non-empty, which has overhead. The next() function with a default argument is designed to handle empty iterators efficiently at the C level, making it faster than Python-level conditional logic.

Performance Characteristics from Tests:

• Best case scenarios: Functions excellently with named groups (30-45% faster), especially beneficial for regex patterns with single or multiple named groups
• Slight regression: Shows 20-30% slowdown when groupindex is empty (no named groups), but this is a minor cost given the overall 21% speedup

Impact on Workloads:
Based on the function reference showing this is used in pandas' str.extract() method, this optimization will significantly benefit string processing workflows that frequently use named capture groups in regex patterns. Since str.extract() is commonly used in data cleaning and text processing pipelines, even small per-call improvements compound to meaningful performance gains across large datasets.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	🔘 None Found
🌀 Generated Regression Tests	✅ 50 Passed
⏪ Replay Tests	🔘 None Found
🔎 Concolic Coverage Tests	🔘 None Found
📊 Tests Coverage	100.0%

🌀 Generated Regression Tests and Runtime

import re
from collections.abc import Hashable

# imports
import pytest  # used for our unit tests
from pandas.core.strings.accessor import _get_single_group_name

# unit tests

# --- Basic Test Cases ---

def test_single_named_group():
    # Test with a regex containing a single named group
    regex = re.compile(r"(?P<foo>\d+)")
    codeflash_output = _get_single_group_name(regex) # 1.43μs -> 1.03μs (38.6% faster)

def test_multiple_named_groups():
    # Test with a regex containing multiple named groups; should return the first group name
    regex = re.compile(r"(?P<foo>\d+)-(?P<bar>\w+)")
    # The order is guaranteed by the dict insertion order (Python 3.6+)
    codeflash_output = _get_single_group_name(regex) # 1.08μs -> 908ns (18.5% faster)

def test_no_named_groups():
    # Test with a regex containing no named groups
    regex = re.compile(r"(\d+)-(\w+)")
    codeflash_output = _get_single_group_name(regex) # 571ns -> 724ns (21.1% slower)

def test_named_and_unnamed_groups():
    # Test with a regex containing both named and unnamed groups
    regex = re.compile(r"(\d+)-(?P<foo>\w+)")
    codeflash_output = _get_single_group_name(regex) # 1.14μs -> 812ns (40.8% faster)

def test_named_group_with_numbers():
    # Named groups can have digits in their names
    regex = re.compile(r"(?P<group1>\d+)")
    codeflash_output = _get_single_group_name(regex) # 1.09μs -> 803ns (36.2% faster)

# --- Edge Test Cases ---

def test_empty_pattern():
    # Test with an empty regex pattern
    regex = re.compile(r"")
    codeflash_output = _get_single_group_name(regex) # 595ns -> 729ns (18.4% slower)

def test_named_group_at_end():
    # Named group is the last in the pattern
    regex = re.compile(r"(\d+)-(\w+)-(?P<last>\d+)")
    codeflash_output = _get_single_group_name(regex) # 1.11μs -> 795ns (39.9% faster)

def test_named_group_with_underscore():
    # Named group with underscores in its name
    regex = re.compile(r"(?P<foo_bar>\d+)")
    codeflash_output = _get_single_group_name(regex) # 1.12μs -> 757ns (48.1% faster)

def test_named_group_with_unicode():
    # Named group with unicode characters in its name
    regex = re.compile(r"(?P<naïve>\w+)")
    codeflash_output = _get_single_group_name(regex) # 1.13μs -> 812ns (39.4% faster)

def test_named_group_with_reserved_word():
    # Named group with a Python reserved word as name
    regex = re.compile(r"(?P<class>\w+)")
    codeflash_output = _get_single_group_name(regex) # 1.06μs -> 802ns (31.8% faster)

def test_named_group_with_special_characters():
    # Named group with special characters (though regex only allows [a-zA-Z0-9_])
    # Should fail to compile, so we catch the error
    with pytest.raises(re.error):
        re.compile(r"(?P<foo-bar>\w+)")

def test_named_group_with_empty_name():
    # Named group with empty name is not allowed, should raise error
    with pytest.raises(re.error):
        re.compile(r"(?P<>\w+)")

def test_named_group_with_duplicate_names():
    # Duplicate group names are not allowed, should raise error
    with pytest.raises(re.error):
        re.compile(r"(?P<foo>\d+)(?P<foo>\w+)")

def test_named_group_with_non_ascii_name():
    # Named group with non-ASCII but valid unicode identifier
    regex = re.compile(r"(?P<π>\d+)")
    codeflash_output = _get_single_group_name(regex) # 1.36μs -> 990ns (37.1% faster)

def test_named_group_with_long_name():
    # Named group with a very long name
    long_name = "a" * 100
    regex = re.compile(rf"(?P<{long_name}>\d+)")
    codeflash_output = _get_single_group_name(regex) # 1.07μs -> 841ns (27.7% faster)

# --- Large Scale Test Cases ---

def test_many_named_groups():
    # Test with a regex containing many named groups (up to 1000)
    pattern = "".join([f"(?P<group{i}>x)" for i in range(1000)])
    regex = re.compile(pattern)
    # Should return the first group name
    codeflash_output = _get_single_group_name(regex) # 1.15μs -> 892ns (28.9% faster)

def test_many_unnamed_groups():
    # Test with a regex containing many unnamed groups (up to 1000)
    pattern = "".join([f"(x)" for _ in range(1000)])
    regex = re.compile(pattern)
    codeflash_output = _get_single_group_name(regex) # 558ns -> 705ns (20.9% slower)

def test_mixed_named_and_unnamed_groups_large():
    # Test with a regex containing a mix of named and unnamed groups (500 each)
    pattern = "".join([f"(?P<group{i}>x)" for i in range(500)]) + "".join([f"(x)" for _ in range(500)])
    regex = re.compile(pattern)
    codeflash_output = _get_single_group_name(regex) # 1.22μs -> 870ns (40.5% faster)

def test_named_group_at_end_large():
    # Test with a regex where the named group is the last among 999 unnamed groups
    pattern = "".join([f"(x)" for _ in range(999)]) + "(?P<last>x)"
    regex = re.compile(pattern)
    codeflash_output = _get_single_group_name(regex) # 1.13μs -> 884ns (28.1% faster)

def test_pattern_with_no_groups_large():
    # Test with a large pattern but no groups
    pattern = "x" * 1000
    regex = re.compile(pattern)
    codeflash_output = _get_single_group_name(regex) # 567ns -> 756ns (25.0% slower)

# --- Additional Robustness Test Cases ---

def test_regex_with_flags():
    # Test with regex containing flags and a named group
    regex = re.compile(r"(?P<foo>\w+)", re.IGNORECASE)
    codeflash_output = _get_single_group_name(regex) # 1.16μs -> 796ns (45.7% faster)

def test_regex_with_nested_named_groups():
    # Test with nested named groups (though regex does not support true nesting, but can be adjacent)
    regex = re.compile(r"(?P<outer>(?P<inner>\d+))")
    # Should return 'outer' as it's the first in groupindex
    codeflash_output = _get_single_group_name(regex) # 1.10μs -> 825ns (33.1% faster)

def test_regex_with_alternation_named_groups():
    # Test with named groups in alternation
    regex = re.compile(r"(?P<foo>\d+)|(?P<bar>\w+)")
    codeflash_output = _get_single_group_name(regex) # 1.11μs -> 785ns (41.3% faster)

def test_regex_with_reused_pattern_objects():
    # Test that function works for reused pattern objects
    regex = re.compile(r"(?P<foo>\d+)")
    codeflash_output = _get_single_group_name(regex) # 1.08μs -> 791ns (36.8% faster)
    codeflash_output = _get_single_group_name(regex) # 383ns -> 307ns (24.8% faster)


def test_regex_with_non_pattern_object():
    # Test with an object that is not a regex pattern (should raise AttributeError)
    with pytest.raises(AttributeError):
        _get_single_group_name("not_a_pattern") # 1.35μs -> 1.55μs (13.1% slower)
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.

import re
from collections.abc import Hashable

# imports
import pytest  # used for our unit tests
from pandas.core.strings.accessor import _get_single_group_name

# unit tests

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

def test_named_group_single():
    # Basic: regex with a single named group
    regex = re.compile(r'(?P<foo>\d+)')
    codeflash_output = _get_single_group_name(regex) # 1.41μs -> 1.05μs (34.0% faster)

def test_named_group_single_with_letters_numbers():
    # Basic: named group with mixed letters and numbers
    regex = re.compile(r'(?P<group1>[a-z]+)')
    codeflash_output = _get_single_group_name(regex) # 1.11μs -> 859ns (29.5% faster)

def test_named_group_single_with_underscore():
    # Basic: named group with underscores
    regex = re.compile(r'(?P<my_group>[A-Z]+)')
    codeflash_output = _get_single_group_name(regex) # 1.12μs -> 823ns (36.6% faster)

def test_no_named_group():
    # Basic: regex with no named groups
    regex = re.compile(r'(\d+)')
    codeflash_output = _get_single_group_name(regex) # 526ns -> 743ns (29.2% slower)

def test_multiple_named_groups():
    # Basic: regex with multiple named groups, should return the first one
    regex = re.compile(r'(?P<foo>\d+)(?P<bar>\w+)')
    # The first named group is 'foo'
    codeflash_output = _get_single_group_name(regex) # 1.14μs -> 848ns (34.9% faster)

def test_named_group_with_special_chars():
    # Basic: named group containing allowed special chars (underscore)
    regex = re.compile(r'(?P<foo_bar>\d+)')
    codeflash_output = _get_single_group_name(regex) # 1.08μs -> 775ns (39.0% faster)

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

def test_named_group_empty_name():
    # Edge: named group with empty name is not allowed by re, so skip
    # Instead, test group names that look odd but valid
    regex = re.compile(r'(?P<_>\d+)')
    codeflash_output = _get_single_group_name(regex) # 1.08μs -> 795ns (35.5% faster)

def test_named_group_numeric_name():
    # Edge: named group with numeric name is not allowed by re, so skip
    # Instead, test group names starting with underscore and numbers
    regex = re.compile(r'(?P<_123>\d+)')
    codeflash_output = _get_single_group_name(regex) # 1.05μs -> 781ns (35.1% faster)

def test_named_group_unicode_name():
    # Edge: named group with unicode characters (if allowed)
    regex = re.compile(r'(?P<naïve>\w+)')
    codeflash_output = _get_single_group_name(regex) # 1.02μs -> 813ns (25.5% faster)

def test_named_group_with_long_name():
    # Edge: named group with a very long name
    long_name = 'a' * 100
    regex = re.compile(rf'(?P<{long_name}>\d+)')
    codeflash_output = _get_single_group_name(regex) # 1.06μs -> 755ns (40.4% faster)

def test_named_group_order_preservation():
    # Edge: ensure that the first named group is returned, even if others exist
    regex = re.compile(r'(?P<first>\d+)(?P<second>\w+)(?P<third>\s+)')
    codeflash_output = _get_single_group_name(regex) # 1.06μs -> 758ns (40.1% faster)

def test_named_group_after_unnamed():
    # Edge: named group after unnamed group
    regex = re.compile(r'(\d+)(?P<foo>\w+)')
    codeflash_output = _get_single_group_name(regex) # 986ns -> 757ns (30.3% faster)

def test_named_group_with_duplicate_names():
    # Edge: duplicate named groups are not allowed by re, so test with similar names
    regex = re.compile(r'(?P<foo>\d+)(?P<foo2>\w+)')
    codeflash_output = _get_single_group_name(regex) # 1.02μs -> 775ns (31.9% faster)

def test_named_group_with_no_match():
    # Edge: regex with named group but no match in the string
    regex = re.compile(r'(?P<foo>\d+)')
    # The function only cares about the regex, not the string, so should return 'foo'
    codeflash_output = _get_single_group_name(regex) # 1.04μs -> 758ns (37.1% faster)

def test_named_group_with_nested_groups():
    # Edge: nested groups, only top-level named group matters
    regex = re.compile(r'(?P<outer>(\d+))')
    codeflash_output = _get_single_group_name(regex) # 1.06μs -> 834ns (26.6% faster)

def test_named_group_with_non_ascii_name():
    # Edge: named group with non-ascii but valid python identifier
    regex = re.compile(r'(?P<привет>\w+)')
    codeflash_output = _get_single_group_name(regex) # 975ns -> 771ns (26.5% faster)

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

def test_large_number_of_named_groups():
    # Large Scale: regex with many named groups, should return the first one
    pattern = ''
    for i in range(1000):
        pattern += f'(?P<group{i}>\\d+)'
    regex = re.compile(pattern)
    codeflash_output = _get_single_group_name(regex) # 1.14μs -> 900ns (27.0% faster)

def test_large_named_group_name():
    # Large Scale: regex with a single named group with a very large name
    large_name = 'g' * 1000
    regex = re.compile(rf'(?P<{large_name}>\d+)')
    codeflash_output = _get_single_group_name(regex) # 1.02μs -> 806ns (26.6% faster)

def test_large_pattern_no_named_groups():
    # Large Scale: large pattern with no named groups
    pattern = r'(\d+)' * 1000
    regex = re.compile(pattern)
    codeflash_output = _get_single_group_name(regex) # 556ns -> 751ns (26.0% slower)

def test_large_pattern_mixed_named_and_unnamed_groups():
    # Large Scale: large pattern with both named and unnamed groups
    pattern = ''
    for i in range(500):
        pattern += r'(\d+)'
    for i in range(500):
        pattern += f'(?P<name{i}>\\w+)'
    regex = re.compile(pattern)
    codeflash_output = _get_single_group_name(regex) # 1.22μs -> 897ns (35.6% faster)

def test_large_pattern_named_group_at_end():
    # Large Scale: large pattern with named group at the end
    pattern = r'(\d+)' * 999 + r'(?P<last>\w+)'
    regex = re.compile(pattern)
    codeflash_output = _get_single_group_name(regex) # 1.08μs -> 825ns (31.5% faster)

# --------------------
# Negative/Type Safety Test Cases
# --------------------

def test_input_not_regex_pattern():
    # Negative: input is not a regex pattern, should raise AttributeError
    with pytest.raises(AttributeError):
        _get_single_group_name("not_a_pattern") # 1.18μs -> 1.35μs (12.5% slower)

def test_input_none():
    # Negative: input is None, should raise AttributeError
    with pytest.raises(AttributeError):
        _get_single_group_name(None) # 1.17μs -> 1.33μs (12.0% slower)

def test_input_integer():
    # Negative: input is an integer, should raise AttributeError
    with pytest.raises(AttributeError):
        _get_single_group_name(12345) # 1.18μs -> 1.30μs (9.46% slower)
# 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-_get_single_group_name-mhx3h75o and push.