"""Extended tests for scheduler: job execution flow."""

import os
import pytest
from unittest.mock import patch, MagicMock

from factsdb.config import DatabaseConfig, AIEndpointConfig, FTPServerConfig, SchedulerConfig


class MockConfig:
    def __init__(self, db_path=":memory:"):
        self.database = DatabaseConfig(path=db_path)
        self.ai_endpoint = AIEndpointConfig(url="http://localhost", auth_token="tok")
        self.ftp_server = FTPServerConfig(host="0.0.0.0", port=2121, username="u", password="p")
        self.scheduler = SchedulerConfig(interval_minutes=10)


class TestFactExtractionJobExecute:
    def test_execute_success(self, tmp_path):
        from factsdb.scheduler import FactExtractionJob
        from factsdb.database import DatabaseManager
        from factsdb.file_processor import FileProcessor

        cfg = MockConfig(db_path=str(tmp_path / "sched.db"))
        dm = DatabaseManager(cfg.database)
        fp = FileProcessor()

        dm.create_table("t1")

        # Create a test file
        test_file = tmp_path / "test.txt"
        test_file.write_text("Apple released the iPhone in 2007")

        # Mock AI processor
        mock_ai = MagicMock()
        mock_ai.extract_facts_from_text.return_value = {
            "fact": "Test fact",
            "key_entities": ["Apple"],
            "key_dates": ["2007"],
        }

        job = FactExtractionJob(cfg, dm, fp, mock_ai)
        job.execute(str(tmp_path), "t1", "", "gpt-oss")

        facts = dm.get_facts("t1")
        assert len(facts) == 1
        assert facts[0]["fact"] == "Test fact"

    def test_execute_skip_processed(self, tmp_path):
        from factsdb.scheduler import FactExtractionJob
        from factsdb.database import DatabaseManager
        from factsdb.file_processor import FileProcessor

        cfg = MockConfig(db_path=str(tmp_path / "sched.db"))
        dm = DatabaseManager(cfg.database)
        fp = FileProcessor()
        dm.create_table("t1")

        test_file = tmp_path / "test.txt"
        test_file.write_text("content")
        dm.mark_file_processed(str(test_file), "t1", True)

        mock_ai = MagicMock()
        job = FactExtractionJob(cfg, dm, fp, mock_ai)
        job.execute(str(tmp_path), "t1", "", "gpt-oss")

        mock_ai.extract_facts_from_text.assert_not_called()

    def test_execute_file_error_continues(self, tmp_path):
        from factsdb.scheduler import FactExtractionJob
        from factsdb.database import DatabaseManager
        from factsdb.file_processor import FileProcessor

        cfg = MockConfig(db_path=str(tmp_path / "sched.db"))
        dm = DatabaseManager(cfg.database)
        dm.create_table("t1")
        fp = FileProcessor()

        test_file = tmp_path / "test.txt"
        test_file.write_text("content")

        mock_ai = MagicMock()
        mock_ai.extract_facts_from_text.side_effect = Exception("AI error")

        job = FactExtractionJob(cfg, dm, fp, mock_ai)
        job.execute(str(tmp_path), "t1", "", "gpt-oss")

        facts = dm.get_facts("t1")
        assert len(facts) == 0


class TestSchedulerInitError:
    def test_scheduler_db_init_error(self, tmp_path, monkeypatch):
        from factsdb.scheduler import FactExtractionScheduler

        cfg = MockConfig(db_path=str(tmp_path / "sched.db"))
        with patch("factsdb.scheduler.AIProcessor"):
            with patch("factsdb.scheduler.DatabaseManager", side_effect=Exception("db error")):
                sched = FactExtractionScheduler(cfg)
                assert sched.db_manager is None


class TestSchedulerRunAllJobs:
    def test_run_all_jobs(self, tmp_path, monkeypatch):
        from factsdb.scheduler import FactExtractionScheduler
        from factsdb.database import DatabaseManager

        cfg = MockConfig(db_path=str(tmp_path / "sched.db"))
        dm = DatabaseManager(cfg.database)
        dm.create_table("t1")

        test_file = tmp_path / "test.txt"
        test_file.write_text("content")

        with patch("factsdb.scheduler.AIProcessor") as mock_ai_cls:
            mock_ai = MagicMock()
            mock_ai.extract_facts_from_text.return_value = {
                "fact": "F",
                "key_entities": [],
                "key_dates": [],
            }
            mock_ai_cls.return_value = mock_ai

            with patch("factsdb.scheduler.DatabaseManager", return_value=dm):
                sched = FactExtractionScheduler(cfg)
                sched.add_job(str(tmp_path), "t1", "", "gpt-oss")
                sched._run_all_jobs()

        facts = dm.get_facts("t1")
        assert len(facts) == 1