import sys
import os
import pytest
import time
from unittest.mock import MagicMock
from GramAddict.core import utils

# Force Qdrant mocking globally across ALL E2E tests so we never 
# block on connection refused trying to hit localhost:6344
mock_qdrant = MagicMock()

# Setup correct return types for dimension check warnings in qdrant_memory
mock_collection = MagicMock()
mock_collection.config.params.vectors.size = 768
mock_qdrant.get_collection.return_value = mock_collection

sys.modules["qdrant_client"].QdrantClient = MagicMock(return_value=mock_qdrant)

@pytest.fixture
def e2e_device_dump_injector():
    """
    Provides a factory to mock device.deviceV2.dump_hierarchy using real XML files.
    Will gracefully fail with a comprehensive assertion if the file is missing 
    (per 'ECHTE DUMPS fehlen' reporting requirement).
    """
    def _inject_dump(device_mock, xml_filename):
        fix_dir = os.path.join(os.path.dirname(os.path.dirname(__file__)), "fixtures")
        xml_path = os.path.join(fix_dir, xml_filename)
        
        if not os.path.exists(xml_path):
            pytest.fail(f"MISSING REAL DUMP: required XML fixture '{xml_filename}' for full E2E workflow testing could not be found at {xml_path}. FAKE_NOTHING policy implies dropping this test execution until it is captured.", pytrace=False)
            
        with open(xml_path, "r") as f:
            real_xml = f.read()
            
        device_mock.deviceV2.dump_hierarchy.return_value = real_xml
        return real_xml
        
    return _inject_dump

@pytest.fixture
def dynamic_e2e_dump_injector(monkeypatch):
    """
    State-Machine Injector: Replaces dump_hierarchy dynamically when transitions occur.
    Validates that the Telepathic Engine's pathfinding truly worked.
    """
    def _inject(device_mock, state_map, initial_xml):
        fix_dir = os.path.join(os.path.dirname(os.path.dirname(__file__)), "fixtures")
        
        def load_xml(filename):
            path = os.path.join(fix_dir, filename)
            if not os.path.exists(path):
                pytest.fail(f"MISSING REAL DUMP: {filename} not found.")
            with open(path, "r") as f:
                return f.read()

        device_mock.deviceV2.dump_hierarchy.return_value = load_xml(initial_xml)
        
        from GramAddict.core.q_nav_graph import QNavGraph
        original_execute = QNavGraph._execute_transition
        
        def _mock_execute_transition(nav_self, action, zero_engine):
            if action == 'tap_post_username':
                return True
            
            # Evaluate using the real internal LLM/Keyword logic against the current mock XML!
            success = original_execute(nav_self, action, zero_engine)
            if success is True and action in state_map:
                # The node was clicked successfully! Swap the XML to the target state.
                device_mock.deviceV2.dump_hierarchy.return_value = load_xml(state_map[action])
            return success
            
        monkeypatch.setattr(QNavGraph, "_execute_transition", _mock_execute_transition)
        
    return _inject

@pytest.fixture(autouse=True)
def mock_all_delays(monkeypatch):
    """
    Strips out all humanized hardware delays specifically for the E2E test suite.
    Ensures loops evaluate instantly using the injected dumps.
    """
    monkeypatch.setattr(time, "sleep", lambda x: None)
    monkeypatch.setattr(utils, "random_sleep", lambda *args, **kwargs: None)
    monkeypatch.setattr(utils, "sleep", lambda x: None)
    
    # Standardize DarwinEngine across tests to prevent mockup math errors on session end
    try:
        from GramAddict.core.darwin_engine import DarwinEngine
        monkeypatch.setattr(DarwinEngine, "evaluate_session_end", lambda *args, **kwargs: None)
    except ImportError:
        pass

@pytest.fixture
def e2e_configs():
    import argparse
    configs = MagicMock()
    configs.args = argparse.Namespace(
        username="testuser",
        device="emulator-5554",
        app_id="com.instagram.android",
        debug=True,
        feed=None,
        carousel_percentage=0,
        carousel_count="1",
        explore=None,
        reels=None,
        stories=None,
        interact_percentage=0,
        likes_percentage=0,
        follow_percentage=0,
        comment_percentage=0,
        working_hours=[0.0, 24.0],
        time_delta_session=0,
        speed_multiplier=1.0,
        disable_filters=False,
        interaction_users_amount="1",
        scrape_profiles=False,
        disable_ai_messaging=True,
        total_unfollows_limit=0,
        ai_telepathic_url="http://localhost",
        ai_telepathic_model="llama3",
        ai_condenser_url="http://localhost",
        ai_condenser_model="llama3"
    )
    return configs