⚡️ Speed up function _ensure_term by 5%

[codeflash-ai]

📄 5% (0.05x) speedup for _ensure_term in pandas/io/pytables.py

⏱️ Runtime : 20.7 milliseconds → 19.7 milliseconds (best of 57 runs)

📝 Explanation and details

The optimization implements lazy initialization with module-level caching for the operations tuple in maybe_expression().

Key Changes:

• Added a global _operations variable that's initialized to None
• Modified maybe_expression() to check if _operations is None and only create the operations tuple on first call
• Subsequent calls reuse the cached tuple instead of reconstructing it

Why This is Faster:
The original code reconstructed the operations tuple (PyTablesExprVisitor.binary_ops + PyTablesExprVisitor.unary_ops + ("=",)) on every call to maybe_expression(). This tuple concatenation involves memory allocation and copying. The optimization eliminates this overhead by computing it once and reusing the result.

Performance Impact:

• Line profiler shows the operations creation went from 11.3% to 6% of function time
• Most effective for workloads with repeated calls to maybe_expression()
• Test results show 4-8% improvements for expression processing cases, with the largest gains (up to 25%) on non-expression strings that exit early after the isinstance check
• Large-scale tests with 1000+ items show consistent 5-6% speedups, confirming the benefit scales with call frequency

The 5% overall speedup comes from eliminating redundant tuple creation overhead across the many calls to maybe_expression() during pytables query processing.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	🔘 None Found
🌀 Generated Regression Tests	✅ 36 Passed
⏪ Replay Tests	🔘 None Found
🔎 Concolic Coverage Tests	🔘 None Found
📊 Tests Coverage	100.0%

🌀 Generated Regression Tests and Runtime

import pytest
from pandas.io.pytables import _ensure_term


# Simulate the PyTablesExpr class
class PyTablesExpr:
    def __init__(self, expr, scope_level):
        self.expr = expr
        self.scope_level = scope_level

    def __eq__(self, other):
        # For test comparison purposes
        return (
            isinstance(other, PyTablesExpr)
            and self.expr == other.expr
            and self.scope_level == other.scope_level
        )

    def __repr__(self):
        return f"PyTablesExpr(expr={self.expr!r}, scope_level={self.scope_level})"

# Term alias
Term = PyTablesExpr
from pandas.io.pytables import _ensure_term

# --------------------------
# Unit tests for _ensure_term
# --------------------------

# 1. Basic Test Cases

def test_single_expression_string():
    # Should wrap string in Term if it's an expression
    codeflash_output = _ensure_term("x > 5", 0); result = codeflash_output # 18.4μs -> 17.6μs (4.44% faster)



def test_list_of_expressions():
    # Should wrap each expression string in Term
    exprs = ["x > 5", "y < 10"]
    codeflash_output = _ensure_term(exprs, 0); result = codeflash_output # 25.7μs -> 23.8μs (7.75% faster)

def test_list_of_mixed_types():
    # Should wrap expressions, leave other types as is
    items = ["x > 5", 123, None, "y < 10", "plainstring"]
    codeflash_output = _ensure_term(items, 1); result = codeflash_output # 23.7μs -> 22.6μs (4.52% faster)


def test_none_input():
    # Should return None if input is None
    codeflash_output = _ensure_term(None, 0); result = codeflash_output # 1.16μs -> 1.29μs (10.4% slower)

# 2. Edge Test Cases

def test_empty_list_input():
    # Should return None for empty list
    codeflash_output = _ensure_term([], 1); result = codeflash_output # 1.32μs -> 1.39μs (5.18% slower)

def test_list_with_only_none():
    # Should return None for list of None
    codeflash_output = _ensure_term([None, None], 1); result = codeflash_output # 1.34μs -> 1.38μs (3.05% slower)

def test_list_with_one_valid_and_none():
    # Should skip None and process valid
    codeflash_output = _ensure_term([None, "x < 2"], 1); result = codeflash_output # 15.5μs -> 15.1μs (2.73% faster)



def test_empty_tuple_input():
    # Should return None for empty tuple
    codeflash_output = _ensure_term((), 1); result = codeflash_output # 1.28μs -> 1.39μs (8.26% slower)

def test_string_with_only_operator():
    # Should treat as expression
    codeflash_output = _ensure_term(">", 0); result = codeflash_output # 15.7μs -> 14.8μs (5.96% faster)

def test_string_with_equals_operator():
    # Should treat as expression
    codeflash_output = _ensure_term("=", 1); result = codeflash_output # 14.2μs -> 13.2μs (7.83% faster)

def test_list_with_long_expression():
    # Should wrap long valid expression
    expr = "a > 1 & b < 2 | c == 3"
    codeflash_output = _ensure_term([expr], 0); result = codeflash_output # 13.9μs -> 13.7μs (1.09% faster)

def test_list_with_empty_string():
    # Empty string is not an expression, should be left as is
    codeflash_output = _ensure_term([""], 1); result = codeflash_output # 3.83μs -> 3.22μs (18.9% faster)

def test_list_with_falsey_values():
    # Should skip None, keep 0 and False
    codeflash_output = _ensure_term([None, 0, False, "x > 1"], 1); result = codeflash_output # 14.4μs -> 13.6μs (5.86% faster)

# 3. Large Scale Test Cases

def test_large_list_of_expressions():
    # Test with 1000 expressions
    exprs = [f"x > {i}" for i in range(1000)]
    codeflash_output = _ensure_term(exprs, 0); result = codeflash_output # 4.01ms -> 3.77ms (6.27% faster)
    for i, term in enumerate(result):
        pass

def test_large_list_of_mixed_types():
    # 500 expressions, 250 ints, 250 non-expression strings
    exprs = [f"x < {i}" for i in range(500)]
    ints = list(range(250))
    non_exprs = [f"plain_{i}" for i in range(250)]
    mixed = exprs + ints + non_exprs
    codeflash_output = _ensure_term(mixed, 1); result = codeflash_output # 2.97ms -> 2.82ms (5.32% faster)
    for i in range(500):
        pass
    for i in range(500, 750):
        pass
    for i in range(750, 1000):
        pass

def test_large_tuple_of_none():
    # Should return None for tuple of 1000 None
    codeflash_output = _ensure_term(tuple([None] * 1000), 0); result = codeflash_output # 10.7μs -> 10.8μs (0.703% slower)


def test_large_list_with_some_none():
    # Should skip None and process others
    items = [None if i % 2 == 0 else f"x > {i}" for i in range(1000)]
    codeflash_output = _ensure_term(items, 0); result = codeflash_output # 2.03ms -> 1.93ms (4.90% faster)
    for idx, term in enumerate(result):
        i = idx * 2 + 1
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.
#------------------------------------------------
import pytest
from pandas.io.pytables import _ensure_term


class PyTablesExpr:
    def __init__(self, expr, scope_level=None):
        self.expr = expr
        self.scope_level = scope_level
    def __eq__(self, other):
        # For test purposes, equality by expr and scope_level
        return (
            isinstance(other, PyTablesExpr)
            and self.expr == other.expr
            and self.scope_level == other.scope_level
        )
    def __repr__(self):
        return f"PyTablesExpr({self.expr!r}, scope_level={self.scope_level})"

Term = PyTablesExpr
from pandas.io.pytables import _ensure_term

# unit tests

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

def test_basic_string_expression():
    # Basic string expression should be wrapped as Term
    codeflash_output = _ensure_term("x == 5", 0); result = codeflash_output # 16.1μs -> 15.8μs (1.63% faster)

def test_basic_non_expression_string():
    # Non-expression string should not be wrapped
    codeflash_output = _ensure_term("hello", 0); result = codeflash_output # 4.14μs -> 3.30μs (25.7% faster)

def test_basic_list_of_expressions():
    # List of expressions should be wrapped individually
    terms = ["x == 5", "y != 2"]
    codeflash_output = _ensure_term(terms, 0); result = codeflash_output # 21.7μs -> 20.5μs (5.80% faster)

def test_basic_list_mixed():
    # List with expressions and non-expressions
    terms = ["x == 5", 42, "hello", None]
    codeflash_output = _ensure_term(terms, 1); result = codeflash_output # 15.2μs -> 14.6μs (3.99% faster)
    # None should be filtered


def test_basic_none():
    # None input should return None
    codeflash_output = _ensure_term(None, 0); result = codeflash_output # 1.15μs -> 1.24μs (7.56% slower)

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

def test_edge_empty_list():
    # Empty list should return None
    codeflash_output = _ensure_term([], 0); result = codeflash_output # 1.31μs -> 1.36μs (3.89% slower)

def test_edge_list_with_only_none():
    # List with only None should return None
    codeflash_output = _ensure_term([None, None], 0); result = codeflash_output # 1.38μs -> 1.41μs (1.78% slower)

def test_edge_list_with_none_and_expressions():
    # List with None and valid expressions
    codeflash_output = _ensure_term([None, "x > 1", None], 1); result = codeflash_output # 15.3μs -> 15.2μs (0.493% faster)


def test_edge_string_with_no_ops():
    # String with no operation should not be wrapped
    codeflash_output = _ensure_term("just a string", 0); result = codeflash_output # 20.1μs -> 19.3μs (3.97% faster)


def test_edge_expression_with_unary_op():
    # String with unary op should be wrapped
    codeflash_output = _ensure_term("~x", 0); result = codeflash_output # 15.4μs -> 14.2μs (8.62% faster)

def test_edge_list_with_mixed_types():
    # List with various types
    terms = ["x == 1", 3.14, None, True, "y != 2"]
    codeflash_output = _ensure_term(terms, 0); result = codeflash_output # 21.7μs -> 20.6μs (5.59% faster)

def test_edge_tuple_with_none_and_non_expr():
    # Tuple with None and non-expr
    codeflash_output = _ensure_term((None, "hello", None), 0); result = codeflash_output # 4.37μs -> 3.67μs (19.0% faster)

def test_edge_list_with_all_non_expr():
    # List with all non-expr types
    codeflash_output = _ensure_term([1, 2, 3], 0); result = codeflash_output # 1.92μs -> 2.02μs (5.28% slower)

def test_edge_string_with_binary_op_at_end():
    # String with op at end
    codeflash_output = _ensure_term("foo >=", 0); result = codeflash_output # 15.3μs -> 15.6μs (2.24% slower)

def test_edge_string_with_binary_op_inside():
    # String with op inside
    codeflash_output = _ensure_term("a != b", 0); result = codeflash_output # 14.2μs -> 14.3μs (0.497% slower)

# -------- LARGE SCALE TEST CASES --------

def test_large_list_all_expressions():
    # Large list of expressions
    terms = [f"x == {i}" for i in range(1000)]
    codeflash_output = _ensure_term(terms, 0); result = codeflash_output # 4.28ms -> 4.06ms (5.43% faster)
    for i, r in enumerate(result):
        pass


def test_large_tuple_all_non_expr():
    # Large tuple of non-expr ints
    terms = tuple(range(1000))
    codeflash_output = _ensure_term(terms, 0); result = codeflash_output # 79.9μs -> 78.3μs (2.08% faster)

def test_large_list_all_none():
    # Large list of None
    terms = [None] * 1000
    codeflash_output = _ensure_term(terms, 0); result = codeflash_output # 10.5μs -> 10.5μs (0.209% slower)

def test_large_list_some_none_and_expr():
    # Large list, some None, some expr
    terms = [None if i % 2 == 0 else f"x == {i}" for i in range(1000)]
    codeflash_output = _ensure_term(terms, 0); result = codeflash_output # 2.11ms -> 1.98ms (6.26% faster)
    for i, r in enumerate(result):
        # The expr should be for odd i's
        expected_i = 2 * i + 1
# 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-_ensure_term-mhc076v5 and push.