feat(worker): integrate data preparation into run() method

Call _prepare_data before executing trades:
- Download missing data if needed
- Filter completed dates
- Store warnings
- Handle empty date scenarios

Co-Authored-By: Claude <noreply@anthropic.com>

tests/integration/test_async_download.py

@@ -0,0 +1,100 @@
+import pytest
+import time
+from api.database import initialize_database
+from api.job_manager import JobManager
+from api.simulation_worker import SimulationWorker
+from unittest.mock import Mock, patch
+
+def test_worker_prepares_data_before_execution(tmp_path):
+    """Test that worker calls _prepare_data before executing trades."""
+    db_path = str(tmp_path / "test.db")
+    initialize_database(db_path)
+    job_manager = JobManager(db_path=db_path)
+
+    # Create job
+    job_id = job_manager.create_job(
+        config_path="configs/default_config.json",
+        date_range=["2025-10-01"],
+        models=["gpt-5"]
+    )
+
+    worker = SimulationWorker(job_id=job_id, db_path=db_path)
+
+    # Mock _prepare_data to track call
+    original_prepare = worker._prepare_data
+    prepare_called = []
+
+    def mock_prepare(*args, **kwargs):
+        prepare_called.append(True)
+        return (["2025-10-01"], [])  # Return available dates, no warnings
+
+    worker._prepare_data = mock_prepare
+
+    # Mock _execute_date to avoid actual execution
+    worker._execute_date = Mock()
+
+    # Run worker
+    result = worker.run()
+
+    # Verify _prepare_data was called
+    assert len(prepare_called) == 1
+    assert result["success"] is True
+
+def test_worker_handles_no_available_dates(tmp_path):
+    """Test worker fails gracefully when no dates are available."""
+    db_path = str(tmp_path / "test.db")
+    initialize_database(db_path)
+    job_manager = JobManager(db_path=db_path)
+
+    job_id = job_manager.create_job(
+        config_path="configs/default_config.json",
+        date_range=["2025-10-01"],
+        models=["gpt-5"]
+    )
+
+    worker = SimulationWorker(job_id=job_id, db_path=db_path)
+
+    # Mock _prepare_data to return empty dates
+    worker._prepare_data = Mock(return_value=([], []))
+
+    # Run worker
+    result = worker.run()
+
+    # Should fail with descriptive error
+    assert result["success"] is False
+    assert "No trading dates available" in result["error"]
+
+    # Job should be marked as failed
+    job = job_manager.get_job(job_id)
+    assert job["status"] == "failed"
+
+def test_worker_stores_warnings(tmp_path):
+    """Test worker stores warnings from prepare_data."""
+    db_path = str(tmp_path / "test.db")
+    initialize_database(db_path)
+    job_manager = JobManager(db_path=db_path)
+
+    job_id = job_manager.create_job(
+        config_path="configs/default_config.json",
+        date_range=["2025-10-01"],
+        models=["gpt-5"]
+    )
+
+    worker = SimulationWorker(job_id=job_id, db_path=db_path)
+
+    # Mock _prepare_data to return warnings
+    warnings = ["Rate limited", "Skipped 1 date"]
+    worker._prepare_data = Mock(return_value=(["2025-10-01"], warnings))
+    worker._execute_date = Mock()
+
+    # Run worker
+    result = worker.run()
+
+    # Verify warnings in result
+    assert result["warnings"] == warnings
+
+    # Verify warnings stored in database
+    import json
+    job = job_manager.get_job(job_id)
+    stored_warnings = json.loads(job["warnings"])
+    assert stored_warnings == warnings