Initial project setup: NF Hotel Data Analysis API

- Add project structure with domain-driven design organization
- Implement FastAPI endpoints for hotel booking reports
- Add data cleaning, statistics, and LLM report generation services
- Include configuration management and security utilities
- Add repository layer for bookings and metadata access
- Setup testing framework with conftest.py
- Include example files and documentation

tests/test_statistics.py

@@ -0,0 +1,27 @@
+import json
+
+from nf_hotel_api.services.cleaning import DataCleaningService
+from nf_hotel_api.services.statistics import DescriptiveStatsService
+
+
+def test_compute_drops_booking_id(dirty_bookings_df, hotel_metadata):
+    clean_df = DataCleaningService(hotel_metadata).clean(dirty_bookings_df)
+    stats = DescriptiveStatsService().compute(clean_df)
+
+    assert "booking_id" not in stats
+
+
+def test_compute_output_is_json_serializable(dirty_bookings_df, hotel_metadata):
+    clean_df = DataCleaningService(hotel_metadata).clean(dirty_bookings_df)
+    stats = DescriptiveStatsService().compute(clean_df)
+
+    # Must not raise: every value has to be a plain JSON-compatible type.
+    json.dumps(stats)
+
+
+def test_compute_includes_numeric_and_categorical_columns(dirty_bookings_df, hotel_metadata):
+    clean_df = DataCleaningService(hotel_metadata).clean(dirty_bookings_df)
+    stats = DescriptiveStatsService().compute(clean_df)
+
+    assert "mean" in stats["adults"]
+    assert "top" in stats["meal"] or "unique" in stats["meal"]