Harden trading, training, and monitoring

tests/test_training_coordination.py

@@ -4,6 +4,8 @@ import base64
 import hashlib
 import json
 
+import pytest
+
 from crypto_spot_bot.training_coordination import TrainingCoordinator
 
 
@@ -36,9 +38,20 @@ def test_training_coordinator_claims_and_completes_job(tmp_path) -> None:
     assert coordinator.status()["active_job"] is None
 
 
+def test_training_coordinator_preserves_boolean_resume_candidate_parameter(tmp_path) -> None:
+    coordinator = TrainingCoordinator(tmp_path)
+
+    requested = coordinator.request_retrain(
+        {"source": "recovery", "parameters": {"resume_candidate": True}}
+    )
+
+    assert requested["job"]["parameters"] == {"resume_candidate": True}
+
+
 def test_training_coordinator_accepts_chunked_artifact_upload(tmp_path) -> None:
     coordinator = TrainingCoordinator(tmp_path)
     job = coordinator.request_retrain({"source": "test"})["job"]
+    coordinator.claim({"worker_id": "test-worker"})
     payload = b'{"type":"pytorch_recurrent_forecaster","symbols":{}}\n'
     sha256 = hashlib.sha256(payload).hexdigest()
     first = payload[:20]
@@ -67,7 +80,8 @@ def test_training_coordinator_accepts_chunked_artifact_upload(tmp_path) -> None:
 
     assert part_1["complete"] is False
     assert part_2["complete"] is True
-    assert (tmp_path / "lstm_forecaster.json").read_bytes() == payload
+    assert not (tmp_path / "lstm_forecaster.json").exists()
+    assert (tmp_path / ".training_uploads" / job["id"] / "ready" / "lstm_forecaster.json").read_bytes() == payload
     assert coordinator.status()["latest_job"]["artifacts"][0]["sha256"] == sha256
 
 
@@ -86,3 +100,73 @@ def test_running_claimed_job_keeps_agent_online_when_heartbeat_is_stale(tmp_path
     assert status["agent_recently_seen"] is False
     assert status["agent_busy"] is True
     assert status["agent_online"] is True
+
+
+def test_training_upload_rejects_unknown_job(tmp_path) -> None:
+    coordinator = TrainingCoordinator(tmp_path)
+    payload = b"{}"
+
+    with pytest.raises(ValueError, match="not found"):
+        coordinator.save_artifact_chunk(
+            "11111111-1111-4111-8111-111111111111",
+            {
+                "name": "lstm_forecaster.json",
+                "index": 0,
+                "total": 1,
+                "sha256": hashlib.sha256(payload).hexdigest(),
+                "data_base64": base64.b64encode(payload).decode("ascii"),
+            },
+        )
+
+
+def test_training_bundle_promotes_only_after_successful_guard(tmp_path) -> None:
+    coordinator = TrainingCoordinator(tmp_path)
+    job = coordinator.request_retrain({"source": "test"})["job"]
+    coordinator.claim({"worker_id": "worker-1"})
+    model = {
+        "type": "pytorch_recurrent_forecaster",
+        "symbols": {
+            "BTCUSDT": {
+                "model": "torch_gru",
+                "lookback": 4,
+                "input_size": 1,
+                "hidden_size": 1,
+                "state_dict": {"weight_ih_l0": [[0.0]]},
+                "head_weight": [[0.0]],
+                "head_bias": [0.0],
+            }
+        },
+    }
+    model_payload = (json.dumps(model) + "\n").encode()
+    model_sha256 = hashlib.sha256(model_payload).hexdigest()
+    artifacts = {
+        "lstm_forecaster.json": model,
+        "torch_retrain_guard.json": {
+            "accepted": True,
+            "candidate_artifact_sha256": model_sha256,
+        },
+        "torch_threshold_calibration.json": {
+            "artifact_sha256": model_sha256,
+            "validation": {
+                "passed": True,
+                "protocol": "untouched_model_holdout_with_threshold_walk_forward",
+            }
+        },
+    }
+    for name, data in artifacts.items():
+        payload = model_payload if name == "lstm_forecaster.json" else (json.dumps(data) + "\n").encode()
+        coordinator.save_artifact_chunk(
+            job["id"],
+            {
+                "name": name,
+                "index": 0,
+                "total": 1,
+                "sha256": hashlib.sha256(payload).hexdigest(),
+                "data_base64": base64.b64encode(payload).decode("ascii"),
+            },
+        )
+
+    completed = coordinator.complete(job["id"], {"success": True})
+
+    assert completed["job"]["status"] == "completed"
+    assert json.loads((tmp_path / "lstm_forecaster.json").read_text())["symbols"]["BTCUSDT"]