"""
Benchmark for cache key computation in odoo/tools/cache.py
Focuses on the determine_key() and key() methods which are pure Python.
"""

import time
from inspect import Parameter, signature


# Simulate the key computation logic from ormcache
def build_cache_key_eval(method, cache_args):
    """Current implementation using eval - generates lambda from string"""
    args = ", ".join(
        str(params.replace(annotation=Parameter.empty))
        for params in signature(method).parameters.values()
    )
    values = ["self._name", "method", *cache_args]
    code = (
        f"lambda {args}: ({''.join(a for arg in values for a in (arg, ','))})"
    )
    return eval(code, {"method": method})


# Test methods with various signatures
class MockModel:
    _name = "test.model"

    def simple_method(self, arg1, arg2):
        return arg1 + arg2

    def complex_method(self, model_name, mode="read", limit=None, offset=0):
        return f"{model_name}:{mode}:{limit}:{offset}"

    def many_args_method(self, a, b, c, d, e, f, g, h):
        return sum([a, b, c, d, e, f, g, h])


def benchmark_key_computation():
    """Benchmark the key computation overhead"""
    model = MockModel()

    print("=== Cache Key Computation Benchmark ===\n")

    # Scenario 1: Simple method, many lookups
    print("Scenario 1: Simple method (2 args), 100k lookups")
    key_func = build_cache_key_eval(MockModel.simple_method, ["arg1", "arg2"])

    start = time.perf_counter()
    for i in range(100_000):
        _ = key_func(model, i, i * 2)
    elapsed = time.perf_counter() - start
    print(f"  Total: {elapsed:.3f}s")
    print(f"  Per call: {elapsed / 100_000 * 1e6:.2f} µs\n")

    # Scenario 2: Complex method with defaults, many lookups
    print("Scenario 2: Complex method (4 args with defaults), 100k lookups")
    key_func = build_cache_key_eval(
        MockModel.complex_method, ["model_name", "mode", "limit", "offset"]
    )

    start = time.perf_counter()
    for i in range(100_000):
        _ = key_func(model, "res.partner", "read", 10, i)
    elapsed = time.perf_counter() - start
    print(f"  Total: {elapsed:.3f}s")
    print(f"  Per call: {elapsed / 100_000 * 1e6:.2f} µs\n")

    # Scenario 3: Many args method
    print("Scenario 3: Many args method (8 args), 100k lookups")
    key_func = build_cache_key_eval(
        MockModel.many_args_method, ["a", "b", "c", "d", "e", "f", "g", "h"]
    )

    start = time.perf_counter()
    for i in range(100_000):
        _ = key_func(model, 1, 2, 3, 4, 5, 6, 7, 8)
    elapsed = time.perf_counter() - start
    print(f"  Total: {elapsed:.3f}s")
    print(f"  Per call: {elapsed / 100_000 * 1e6:.2f} µs\n")

    # Scenario 4: Key function creation overhead
    print("Scenario 4: Key function creation (determine_key), 10k methods")
    start = time.perf_counter()
    for i in range(10_000):
        _ = build_cache_key_eval(MockModel.simple_method, ["arg1", "arg2"])
    elapsed = time.perf_counter() - start
    print(f"  Total: {elapsed:.3f}s")
    print(f"  Per call: {elapsed / 10_000 * 1e6:.2f} µs\n")


if __name__ == "__main__":
    benchmark_key_computation()