chore: Major codebase cleanup - remove deprecated files and organize structure

- Docker: Delete 23 deprecated Dockerfiles, fix CI/CD to use Dockerfile.foxhunt-build
- Config: Remove 36 .env files, keep 4 essential, delete config/environments/
- Docs: Archive 614 Wave D files to docs/archive/wave_d/, 95% reduction in root
- Scripts: Delete 56 deprecated scripts, keep 58 production-critical (49% reduction)
- Python: Organize 37 scripts into scripts/python/ subdirectories, delete ml/python/
- Build: Remove 1GB artifacts, delete old venvs, clean Python cache from git
- Migrations: Delete deprecated directory (4,432 lines), remove duplicate database/migrations/
- Infrastructure: Delete deployment/ (61 files), docs/scripts/ (8 files)

Total impact: ~2,500 files cleaned, 750MB+ space freed, zero production impact
All deleted scripts backed up to archives. runpod/ and tests/runpod/ preserved.
data_acquisition_service retained per user request.

scripts/python/data/list_datasets.py

@@ -0,0 +1,64 @@
+#!/usr/bin/env python3
+"""
+List available datasets and check symbology rules.
+"""
+import os
+import databento as db
+import sys
+
+def main():
+    # Check for API key
+    api_key = os.environ.get("DATABENTO_API_KEY")
+    if not api_key:
+        print("ERROR: DATABENTO_API_KEY environment variable not set")
+        sys.exit(1)
+
+    # Create client
+    client = db.Historical(api_key)
+
+    print("=" * 70)
+    print("Available Datasets")
+    print("=" * 70)
+
+    # List datasets
+    try:
+        datasets = client.metadata.list_datasets()
+        print(f"\nFound {len(datasets)} datasets:\n")
+
+        for dataset in datasets:
+            print(f"Dataset: {dataset}")
+
+        print()
+        print("=" * 70)
+        print("CME Group Datasets (for futures)")
+        print("=" * 70)
+
+        cme_datasets = [d for d in datasets if 'CME' in str(d) or 'GLBX' in str(d)]
+        if cme_datasets:
+            for ds in cme_datasets:
+                print(f"  - {ds}")
+        else:
+            print("  (filtering by name, showing all)")
+            for ds in datasets:
+                print(f"  - {ds}")
+
+    except Exception as e:
+        print(f"Error listing datasets: {e}")
+
+    # Let's also try to get symbology info
+    print()
+    print("=" * 70)
+    print("Dataset Details for GLBX.MDP3")
+    print("=" * 70)
+
+    try:
+        # Get dataset info
+        dataset_info = client.metadata.list_schemas("GLBX.MDP3")
+        print(f"\nAvailable schemas for GLBX.MDP3:")
+        for schema in dataset_info:
+            print(f"  - {schema}")
+    except Exception as e:
+        print(f"Error getting dataset info: {e}")
+
+if __name__ == "__main__":
+    main()