codeflash/tests/test_pytest_plugin_deterministic_patches.py

"""Test the deterministic patching functionality in pytest_plugin.py.

This test verifies that all sources of randomness and non-determinism are properly
mocked/patched to ensure reproducible test execution for CodeFlash optimization.

Key functionality tested:
- time.time() returns fixed timestamp (1609459200.0 = 2021-01-01 00:00:00 UTC)
- time.perf_counter() returns incrementing values (maintaining relative timing)
- uuid.uuid4() and uuid.uuid1() return fixed UUID (12345678-1234-5678-9abc-123456789012)
- random.random() returns fixed value (0.123456789)
- random module is seeded deterministically (seed=42)
- os.urandom() returns fixed bytes (0x42 repeated)
- numpy.random is seeded if available (seed=42)
- Performance characteristics are maintained (original functions called internally)
- datetime mock functions are properly stored in builtins
- All patches work consistently across multiple calls
- Integration with real optimization scenarios

This ensures that CodeFlash optimization correctness checks will pass by eliminating
all sources of non-determinism that could cause object comparison failures.
"""

import datetime
import os
import random
import time
import uuid
from unittest.mock import patch

import pytest


class TestDeterministicPatches:
    """Test suite for deterministic patching functionality.

    This test isolates the pytest plugin patches to avoid affecting other tests.
    """

    @pytest.fixture(autouse=True)
    def setup_deterministic_environment(self):
        """Setup isolated deterministic environment for testing."""
        # Store original functions before any patching
        original_time_time = time.time
        original_perf_counter = time.perf_counter
        original_uuid4 = uuid.uuid4
        original_uuid1 = uuid.uuid1
        original_random_random = random.random
        original_os_urandom = os.urandom

        # Create deterministic implementations (matching pytest_plugin.py)
        fixed_timestamp = 1761717605.108106
        fixed_datetime = datetime.datetime(2021, 1, 1, 2, 5, 10, tzinfo=datetime.timezone.utc)
        fixed_uuid = uuid.UUID("12345678-1234-5678-9abc-123456789012")

        # Counter for perf_counter
        perf_counter_start = fixed_timestamp
        perf_counter_calls = 0

        def mock_time_time():
            """Return fixed timestamp while preserving performance characteristics."""
            original_time_time()  # Maintain performance characteristics
            return fixed_timestamp

        def mock_perf_counter():
            """Return incrementing counter for relative timing."""
            nonlocal perf_counter_calls
            original_perf_counter()  # Maintain performance characteristics
            perf_counter_calls += 1
            return perf_counter_start + (perf_counter_calls * 0.001)

        def mock_uuid4():
            """Return fixed UUID4 while preserving performance characteristics."""
            original_uuid4()  # Maintain performance characteristics
            return fixed_uuid

        def mock_uuid1(node=None, clock_seq=None):
            """Return fixed UUID1 while preserving performance characteristics."""
            original_uuid1(node, clock_seq)  # Maintain performance characteristics
            return fixed_uuid

        def mock_random():
            """Return deterministic random value while preserving performance characteristics."""
            original_random_random()  # Maintain performance characteristics
            return 0.123456789  # Fixed random value

        def mock_urandom(n):
            """Return fixed bytes while preserving performance characteristics."""
            original_os_urandom(n)  # Maintain performance characteristics
            return b"\x42" * n  # Fixed bytes

        def mock_datetime_now(tz=None):
            """Return fixed datetime while preserving performance characteristics."""
            if tz is None:
                return fixed_datetime
            return fixed_datetime.replace(tzinfo=tz)

        def mock_datetime_utcnow():
            """Return fixed UTC datetime while preserving performance characteristics."""
            return fixed_datetime

        # Apply patches using unittest.mock for proper cleanup
        patches = [
            patch.object(time, "time", side_effect=mock_time_time),
            patch.object(time, "perf_counter", side_effect=mock_perf_counter),
            patch.object(uuid, "uuid4", side_effect=mock_uuid4),
            patch.object(uuid, "uuid1", side_effect=mock_uuid1),
            patch.object(random, "random", side_effect=mock_random),
            patch.object(os, "urandom", side_effect=mock_urandom),
        ]

        # Start all patches
        started_patches = []
        for p in patches:
            started_patches.append(p.start())

        # Seed random module
        random.seed(42)

        # Handle numpy if available
        numpy_patched = False
        try:
            import numpy as np

            np.random.seed(42)
            numpy_patched = True
        except ImportError:
            pass

        # Store mock functions in a way that tests can access them
        import builtins

        builtins._test_mock_datetime_now = mock_datetime_now
        builtins._test_mock_datetime_utcnow = mock_datetime_utcnow

        yield {
            "original_functions": {
                "time_time": original_time_time,
                "perf_counter": original_perf_counter,
                "uuid4": original_uuid4,
                "uuid1": original_uuid1,
                "random_random": original_random_random,
                "os_urandom": original_os_urandom,
            },
            "numpy_patched": numpy_patched,
        }

        # Cleanup: Stop all patches
        for p in patches:
            p.stop()

        # Clean up builtins
        if hasattr(builtins, "_test_mock_datetime_now"):
            delattr(builtins, "_test_mock_datetime_now")
        if hasattr(builtins, "_test_mock_datetime_utcnow"):
            delattr(builtins, "_test_mock_datetime_utcnow")

        # Reset random seed to ensure other tests aren't affected
        random.seed()

    def test_time_time_deterministic(self, setup_deterministic_environment):
        """Test that time.time() returns a fixed deterministic value."""
        expected_timestamp = 1761717605.108106

        # Call multiple times and verify consistent results
        result1 = time.time()
        result2 = time.time()
        result3 = time.time()

        assert result1 == expected_timestamp
        assert result2 == expected_timestamp
        assert result3 == expected_timestamp
        assert result1 == result2 == result3

    def test_perf_counter_incremental(self, setup_deterministic_environment):
        """Test that time.perf_counter() returns incrementing values."""
        # Call multiple times and verify incrementing behavior
        result1 = time.perf_counter()
        result2 = time.perf_counter()
        result3 = time.perf_counter()

        # Verify they're different and incrementing by approximately 0.001
        assert result1 < result2 < result3
        assert abs((result2 - result1) - 0.001) < 1e-6  # Use reasonable epsilon for float comparison
        assert abs((result3 - result2) - 0.001) < 1e-6

    def test_uuid4_deterministic(self, setup_deterministic_environment):
        """Test that uuid.uuid4() returns a fixed deterministic UUID."""
        expected_uuid = uuid.UUID("12345678-1234-5678-9abc-123456789012")

        # Call multiple times and verify consistent results
        result1 = uuid.uuid4()
        result2 = uuid.uuid4()
        result3 = uuid.uuid4()

        assert result1 == expected_uuid
        assert result2 == expected_uuid
        assert result3 == expected_uuid
        assert result1 == result2 == result3
        assert isinstance(result1, uuid.UUID)

    def test_uuid1_deterministic(self, setup_deterministic_environment):
        """Test that uuid.uuid1() returns a fixed deterministic UUID."""
        expected_uuid = uuid.UUID("12345678-1234-5678-9abc-123456789012")

        # Call multiple times with different parameters
        result1 = uuid.uuid1()
        result2 = uuid.uuid1(node=123456)
        result3 = uuid.uuid1(clock_seq=789)

        assert result1 == expected_uuid
        assert result2 == expected_uuid
        assert result3 == expected_uuid
        assert isinstance(result1, uuid.UUID)

    def test_random_random_deterministic(self, setup_deterministic_environment):
        """Test that random.random() returns a fixed deterministic value."""
        expected_value = 0.123456789

        # Call multiple times and verify consistent results
        result1 = random.random()
        result2 = random.random()
        result3 = random.random()

        assert result1 == expected_value
        assert result2 == expected_value
        assert result3 == expected_value
        assert 0.0 <= result1 <= 1.0  # Should still be a valid random float

    def test_random_seed_deterministic(self, setup_deterministic_environment):
        """Test that random module is seeded deterministically."""
        # Note: random.random() is patched to always return the same value
        # So we test that the random module behaves deterministically
        # by testing that random.seed() affects other functions consistently

        # First, test that our patched random.random always returns the same value
        assert random.random() == 0.123456789
        assert random.random() == 0.123456789

        # Test that seeding affects other random functions consistently
        random.seed(42)
        result1_int = random.randint(1, 100)
        result1_choice = random.choice([1, 2, 3, 4, 5])

        # Re-seed and get same results
        random.seed(42)
        result2_int = random.randint(1, 100)
        result2_choice = random.choice([1, 2, 3, 4, 5])

        assert result1_int == result2_int
        assert result1_choice == result2_choice

    def test_os_urandom_deterministic(self, setup_deterministic_environment):
        """Test that os.urandom() returns deterministic bytes."""
        # Test various byte lengths
        for n in [1, 8, 16, 32]:
            result1 = os.urandom(n)
            result2 = os.urandom(n)

            # Should return fixed bytes (0x42 repeated)
            expected = b"\x42" * n
            assert result1 == expected
            assert result2 == expected
            assert len(result1) == n
            assert isinstance(result1, bytes)

    def test_numpy_seeding(self, setup_deterministic_environment):
        """Test that numpy.random is seeded if available."""
        try:
            import numpy as np

            # Generate some random numbers
            result1 = np.random.random(5)

            # Re-seed and generate again
            np.random.seed(42)
            result2 = np.random.random(5)

            # Should be deterministic due to seeding
            assert np.array_equal(result1, result2)

        except ImportError:
            # numpy not available, test should pass
            pytest.skip("NumPy not available")

    def test_performance_characteristics_maintained(self, setup_deterministic_environment):
        """Test that performance characteristics are maintained."""
        # Test that they still execute quickly (performance check)
        start = time.perf_counter()
        for _ in range(1000):
            time.time()
            uuid.uuid4()
            random.random()
        end = time.perf_counter()

        # Should complete quickly (less than 1 second for 1000 calls)
        duration = end - start
        assert duration < 1.0, f"Performance degraded: {duration}s for 1000 calls"

    def test_datetime_mocks_available(self, setup_deterministic_environment):
        """Test that datetime mock functions are available for testing."""
        import builtins

        # Verify that the mock functions are available
        assert hasattr(builtins, "_test_mock_datetime_now")
        assert hasattr(builtins, "_test_mock_datetime_utcnow")

        # Test that the mock functions work
        mock_now = builtins._test_mock_datetime_now
        mock_utcnow = builtins._test_mock_datetime_utcnow

        result1 = mock_now()
        result2 = mock_utcnow()

        expected_dt = datetime.datetime(2021, 1, 1, 2, 5, 10, tzinfo=datetime.timezone.utc)
        assert result1 == expected_dt
        assert result2 == expected_dt

    def test_consistency_across_multiple_calls(self, setup_deterministic_environment):
        """Test that all patched functions remain consistent across many calls."""
        # Store initial results
        initial_time = time.time()
        initial_uuid = uuid.uuid4()
        initial_random = random.random()
        initial_urandom = os.urandom(8)

        # Call functions many times (but not perf_counter since it increments)
        for _ in range(5):
            assert time.time() == initial_time
            assert uuid.uuid4() == initial_uuid
            assert random.random() == initial_random
            assert os.urandom(8) == initial_urandom

    def test_perf_counter_state_management(self, setup_deterministic_environment):
        """Test that perf_counter maintains its own internal state correctly."""
        # Get a baseline
        base = time.perf_counter()

        # Call several times and verify incrementing
        results = [time.perf_counter() for _ in range(5)]

        # Each call should increment by approximately 0.001
        for i, result in enumerate(results):
            expected = base + ((i + 1) * 0.001)
            assert abs(result - expected) < 1e-6, f"Expected {expected}, got {result}"

    def test_different_uuid_functions_same_result(self, setup_deterministic_environment):
        """Test that both uuid4 and uuid1 return the same deterministic UUID."""
        uuid4_result = uuid.uuid4()
        uuid1_result = uuid.uuid1()

        # Both should return the same fixed UUID
        assert uuid4_result == uuid1_result
        assert str(uuid4_result) == "12345678-1234-5678-9abc-123456789012"

    def test_patches_applied_correctly(self, setup_deterministic_environment):
        """Test that patches are applied correctly."""
        # Test that functions return expected deterministic values
        assert time.time() == 1761717605.108106
        assert uuid.uuid4() == uuid.UUID("12345678-1234-5678-9abc-123456789012")
        assert random.random() == 0.123456789
        assert os.urandom(4) == b"\x42\x42\x42\x42"

    def test_edge_cases(self, setup_deterministic_environment):
        """Test edge cases and boundary conditions."""
        # Test uuid functions with edge case parameters
        assert uuid.uuid1(node=0) == uuid.UUID("12345678-1234-5678-9abc-123456789012")
        assert uuid.uuid1(clock_seq=0) == uuid.UUID("12345678-1234-5678-9abc-123456789012")

        # Test urandom with edge cases
        assert os.urandom(0) == b""
        assert os.urandom(1) == b"\x42"

        # Test datetime mock with timezone
        import builtins

        mock_now = builtins._test_mock_datetime_now

        # Test with different timezone
        utc_tz = datetime.timezone.utc
        result_with_tz = mock_now(utc_tz)
        expected_with_tz = datetime.datetime(2021, 1, 1, 2, 5, 10, tzinfo=datetime.timezone.utc)
        assert result_with_tz == expected_with_tz

    def test_integration_with_actual_optimization_scenario(self, setup_deterministic_environment):
        """Test the patching in a scenario similar to actual optimization."""
        # Simulate what happens during optimization - multiple function calls
        # that would normally produce different results but should now be deterministic

        class MockOptimizedFunction:
            """Mock function that uses various sources of randomness."""

            def __init__(self):
                self.id = uuid.uuid4()
                self.created_at = time.time()
                self.random_factor = random.random()
                self.random_bytes = os.urandom(4)

            def execute(self):
                execution_time = time.perf_counter()
                random_choice = random.randint(1, 100)
                return {
                    "id": self.id,
                    "created_at": self.created_at,
                    "execution_time": execution_time,
                    "random_factor": self.random_factor,
                    "random_choice": random_choice,
                    "random_bytes": self.random_bytes,
                }

        # Create two instances and execute them
        func1 = MockOptimizedFunction()
        func2 = MockOptimizedFunction()

        result1 = func1.execute()
        result2 = func2.execute()

        # All values should be identical due to deterministic patching
        assert result1["id"] == result2["id"]
        assert result1["created_at"] == result2["created_at"]
        assert result1["random_factor"] == result2["random_factor"]
        assert result1["random_bytes"] == result2["random_bytes"]

        # Only execution_time should be different (incremental)
        assert result1["execution_time"] != result2["execution_time"]
        assert result2["execution_time"] > result1["execution_time"]

    def test_cleanup_works_properly(self, setup_deterministic_environment):
        """Test that the original functions are properly restored after cleanup."""
        # This test will be validated by other tests running normally
        # The setup_deterministic_environment fixture should restore originals