⚡️ Speed up function _need_convert by 10%

[codeflash-ai]

📄 10% (0.10x) speedup for _need_convert in pandas/io/pytables.py

⏱️ Runtime : 337 microseconds → 306 microseconds (best of 149 runs)

📝 Explanation and details

The optimized version eliminates redundant tuple operations by restructuring the condition logic. The key change is replacing kind in ("datetime64", "string") with kind == "string", since the substring check "datetime64" in kind already handles all datetime64 cases.

Specific optimizations:

• Removed tuple construction overhead: The original creates a tuple ("datetime64", "string") on every function call and performs membership testing
• Eliminated redundant datetime64 check: Since "datetime64" in kind catches both exact matches and substrings containing "datetime64", the tuple membership test was redundant for that case
• Direct string comparison: kind == "string" is faster than tuple membership for the exact "string" match

Performance characteristics:
The optimization shows consistent improvements across most test cases, with particularly strong gains (20-30% faster) for non-datetime64 strings that fail the first condition early. The "string" exact match case benefits from direct equality comparison rather than tuple membership testing. Only exact "datetime64" matches show slight regression (~10-15% slower) because they now require the substring search instead of the faster tuple membership, but this is offset by gains in all other cases.

The 10% overall speedup comes from eliminating the tuple allocation and membership testing overhead that occurred on every function call, while maintaining identical logical behavior.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	🔘 None Found
🌀 Generated Regression Tests	✅ 2156 Passed
⏪ Replay Tests	🔘 None Found
🔎 Concolic Coverage Tests	🔘 None Found
📊 Tests Coverage	100.0%

🌀 Generated Regression Tests and Runtime

from __future__ import annotations

# imports
import pytest  # used for our unit tests
from pandas.io.pytables import _need_convert

# unit tests

# 1. Basic Test Cases

def test_datetime64_exact():
    # Should return True for exact match "datetime64"
    codeflash_output = _need_convert("datetime64") # 574ns -> 681ns (15.7% slower)

def test_string_exact():
    # Should return True for exact match "string"
    codeflash_output = _need_convert("string") # 508ns -> 428ns (18.7% faster)

def test_int_exact():
    # Should return False for unrelated type "int"
    codeflash_output = _need_convert("int") # 531ns -> 458ns (15.9% faster)

def test_float_exact():
    # Should return False for unrelated type "float"
    codeflash_output = _need_convert("float") # 540ns -> 461ns (17.1% faster)

def test_bool_exact():
    # Should return False for unrelated type "bool"
    codeflash_output = _need_convert("bool") # 568ns -> 471ns (20.6% faster)

# 2. Edge Test Cases

def test_datetime64_with_suffix():
    # Should return True for "datetime64[ns]" (common numpy dtype)
    codeflash_output = _need_convert("datetime64[ns]") # 690ns -> 569ns (21.3% faster)

def test_datetime64_with_prefix():
    # Should return True for "mydatetime64type"
    codeflash_output = _need_convert("mydatetime64type") # 670ns -> 565ns (18.6% faster)

def test_datetime64_in_middle():
    # Should return True for "foo_datetime64_bar"
    codeflash_output = _need_convert("foo_datetime64_bar") # 664ns -> 532ns (24.8% faster)

def test_empty_string():
    # Should return False for empty string
    codeflash_output = _need_convert("") # 559ns -> 449ns (24.5% faster)

def test_case_sensitivity():
    # Should return False for "Datetime64" (case-sensitive)
    codeflash_output = _need_convert("Datetime64") # 624ns -> 525ns (18.9% faster)
    # Should return False for "STRING" (case-sensitive)
    codeflash_output = _need_convert("STRING") # 336ns -> 300ns (12.0% faster)

def test_substring_of_datetime64():
    # Should return False for "datetime" (not full substring)
    codeflash_output = _need_convert("datetime") # 536ns -> 453ns (18.3% faster)
    # Should return False for "date" (not full substring)
    codeflash_output = _need_convert("date") # 245ns -> 248ns (1.21% slower)

def test_string_with_extra_characters():
    # Should return False for "stringy"
    codeflash_output = _need_convert("stringy") # 524ns -> 395ns (32.7% faster)
    # Should return False for "astring"
    codeflash_output = _need_convert("astring") # 258ns -> 222ns (16.2% faster)

def test_special_characters():
    # Should return False for "@datetime64"
    codeflash_output = _need_convert("@datetime64") # 616ns -> 546ns (12.8% faster)
    # Should return False for "string!"
    codeflash_output = _need_convert("string!") # 286ns -> 263ns (8.75% faster)

def test_whitespace():
    # Should return False for " datetime64" (leading space)
    codeflash_output = _need_convert(" datetime64") # 573ns -> 505ns (13.5% faster)
    # Should return False for "string " (trailing space)
    codeflash_output = _need_convert("string ") # 279ns -> 246ns (13.4% faster)

def test_numeric_string():
    # Should return False for "123"
    codeflash_output = _need_convert("123") # 500ns -> 403ns (24.1% faster)

def test_none_input():
    # Should raise TypeError for None input
    with pytest.raises(TypeError):
        _need_convert(None) # 1.75μs -> 1.54μs (13.6% faster)

def test_non_string_input():
    # Should raise TypeError for non-string input (e.g., int)
    with pytest.raises(TypeError):
        _need_convert(123)  # type: ignore
    with pytest.raises(TypeError):
        _need_convert(['datetime64'])  # type: ignore

def test_unicode_string():
    # Should return False for unrelated unicode string
    codeflash_output = _need_convert("时间") # 631ns -> 542ns (16.4% faster)

# 3. Large Scale Test Cases


def test_large_string_input():
    # Should return True if "datetime64" is buried in a very long string
    s = "x" * 500 + "datetime64" + "y" * 500
    codeflash_output = _need_convert(s) # 888ns -> 800ns (11.0% faster)

def test_large_string_without_match():
    # Should return False if "datetime64" is not in a very long string
    s = "x" * 1000
    codeflash_output = _need_convert(s) # 732ns -> 629ns (16.4% faster)



#------------------------------------------------
from __future__ import annotations

# imports
import pytest  # used for our unit tests
from pandas.io.pytables import _need_convert

# unit tests

# -----------------------------
# 1. Basic Test Cases
# -----------------------------

def test_basic_datetime64_exact():
    # Should return True for exact match "datetime64"
    codeflash_output = _need_convert("datetime64") # 597ns -> 657ns (9.13% slower)

def test_basic_string_exact():
    # Should return True for exact match "string"
    codeflash_output = _need_convert("string") # 492ns -> 422ns (16.6% faster)

def test_basic_other_type():
    # Should return False for unrelated type
    codeflash_output = _need_convert("int64") # 570ns -> 466ns (22.3% faster)

def test_basic_float_type():
    # Should return False for unrelated type
    codeflash_output = _need_convert("float32") # 515ns -> 430ns (19.8% faster)

def test_basic_boolean_type():
    # Should return False for unrelated type
    codeflash_output = _need_convert("bool") # 538ns -> 435ns (23.7% faster)

def test_basic_object_type():
    # Should return False for unrelated type
    codeflash_output = _need_convert("object") # 592ns -> 454ns (30.4% faster)

# -----------------------------
# 2. Edge Test Cases
# -----------------------------

def test_edge_datetime64_variant():
    # Should return True for any string containing "datetime64"
    codeflash_output = _need_convert("datetime64[ns]") # 696ns -> 563ns (23.6% faster)
    codeflash_output = _need_convert("foo_datetime64_bar") # 368ns -> 314ns (17.2% faster)
    codeflash_output = _need_convert("prefix_datetime64") # 200ns -> 220ns (9.09% slower)
    codeflash_output = _need_convert("datetime64suffix") # 190ns -> 171ns (11.1% faster)

def test_edge_string_case_sensitivity():
    # Should return False for case mismatch
    codeflash_output = _need_convert("Datetime64") # 614ns -> 474ns (29.5% faster)
    codeflash_output = _need_convert("STRING") # 355ns -> 317ns (12.0% faster)
    codeflash_output = _need_convert("String") # 168ns -> 149ns (12.8% faster)

def test_edge_empty_string():
    # Should return False for empty string
    codeflash_output = _need_convert("") # 536ns -> 408ns (31.4% faster)

def test_edge_whitespace_string():
    # Should return False for whitespace only
    codeflash_output = _need_convert("   ") # 534ns -> 407ns (31.2% faster)

def test_edge_partial_match():
    # Should return False for partial matches that do not contain "datetime64"
    codeflash_output = _need_convert("date") # 528ns -> 421ns (25.4% faster)
    codeflash_output = _need_convert("time") # 250ns -> 213ns (17.4% faster)
    codeflash_output = _need_convert("str") # 158ns -> 139ns (13.7% faster)

def test_edge_substring_string():
    # Should return False for strings containing "string" as a substring unless exact
    codeflash_output = _need_convert("mystring") # 510ns -> 382ns (33.5% faster)
    codeflash_output = _need_convert("stringify") # 239ns -> 241ns (0.830% slower)
    codeflash_output = _need_convert("a_string") # 162ns -> 143ns (13.3% faster)

def test_edge_special_characters():
    # Should return False for special characters
    codeflash_output = _need_convert("@datetime64") # 610ns -> 539ns (13.2% faster)
    codeflash_output = _need_convert("@string") # 279ns -> 242ns (15.3% faster)
    codeflash_output = _need_convert("datetime64!") # 219ns -> 214ns (2.34% faster)
    codeflash_output = _need_convert("!string") # 176ns -> 140ns (25.7% faster)

def test_edge_numeric_string():
    # Should return False for numeric strings
    codeflash_output = _need_convert("12345") # 528ns -> 410ns (28.8% faster)
    codeflash_output = _need_convert("64") # 235ns -> 232ns (1.29% faster)

def test_edge_none_type():
    # Should raise TypeError if None is passed (since str expected)
    with pytest.raises(TypeError):
        _need_convert(None) # 1.66μs -> 1.51μs (10.2% faster)

def test_edge_non_string_type():
    # Should raise TypeError for non-string types
    with pytest.raises(TypeError):
        _need_convert(123)  # type: ignore
    with pytest.raises(TypeError):
        _need_convert(["datetime64"])  # type: ignore
    with pytest.raises(TypeError):
        _need_convert({"kind": "datetime64"})  # type: ignore

# -----------------------------
# 3. Large Scale Test Cases
# -----------------------------

def test_large_scale_datetime64_variants():
    # Test many variants that should all return True
    for i in range(100):
        kind = f"prefix{i}_datetime64_suffix{i}"
        codeflash_output = _need_convert(kind) # 17.8μs -> 16.4μs (8.65% faster)


def test_large_scale_string_exact():
    # Test many exact "string" matches
    for _ in range(1000):
        codeflash_output = _need_convert("string") # 134μs -> 123μs (9.12% faster)

def test_large_scale_false_cases():
    # Test many unrelated types for False
    for i in range(1000):
        kind = f"notdatetime{i}"
        codeflash_output = _need_convert(kind) # 158μs -> 143μs (10.6% faster)

To edit these changes git checkout codeflash/optimize-_need_convert-mhc8ewqx and push.