Update sha

Author: stefanDeveloper

README.md

@@ -162,7 +162,7 @@ The full list of configuration parameters is available at the [documentation](ht
 | `pipeline.data_inspection.inspector.models` | List of models to use for data inspection (e.g., anomaly detection).      | Array of model definitions (e.g., `{"model": "ZScoreDetector", "module": "streamad.model", "model_args": {"is_global": false}}`)|
 | `pipeline.data_inspection.inspector.anomaly_threshold` | Threshold for classifying an observation as an anomaly.                     | `0.01`                                                                                                     |
 | `pipeline.data_analysis.detector.model`    | Model to use for data analysis (e.g., DGA detection).                       | `rf` (Random Forest) option: `XGBoost`                                                    |
-| `pipeline.data_analysis.detector.checksum` | Checksum for the model file to ensure integrity.                            | `ba1f718179191348fe2abd51644d76191d42a5d967c6844feb3371b6f798bf06`                                       |
+| `pipeline.data_analysis.detector.checksum` | Checksum for the model file to ensure integrity.                            | `021af76b2385ddbc76f6e3ad10feb0bb081f9cf05cff2e52333e31040bbf36cc`                                       |
 | `pipeline.data_analysis.detector.base_url` | Base URL for downloading the model if not present locally.                  | `https://heibox.uni-heidelberg.de/d/0d5cbcbe16cd46a58021/`                                                  |
 
 <p align="right">(<a href="#readme-top">back to top</a>)</p>

config.yaml

@@ -59,7 +59,7 @@ pipeline:
   data_analysis:
     detector:
       model: rf # XGBoost
-      checksum: ba1f718179191348fe2abd51644d76191d42a5d967c6844feb3371b6f798bf06
+      checksum: 021af76b2385ddbc76f6e3ad10feb0bb081f9cf05cff2e52333e31040bbf36cc
       base_url: https://heibox.uni-heidelberg.de/d/0d5cbcbe16cd46a58021/
       threshold: 0.5
 

tests/detector/test_detector.py

@@ -45,7 +45,7 @@ def setUp(self):
 
     @patch(
         "src.detector.detector.CHECKSUM",
-        "ba1f718179191348fe2abd51644d76191d42a5d967c6844feb3371b6f798bf06",
+        "021af76b2385ddbc76f6e3ad10feb0bb081f9cf05cff2e52333e31040bbf36cc",
     )
     @patch("src.detector.detector.MODEL", "rf")
     @patch(
@@ -70,7 +70,7 @@ def setUp(self):
 
     @patch(
         "src.detector.detector.CHECKSUM",
-        "ba1f718179191348fe2abd51644d76191d42a5d967c6844feb3371b6f798bf06",
+        "021af76b2385ddbc76f6e3ad10feb0bb081f9cf05cff2e52333e31040bbf36cc",
     )
     @patch("src.detector.detector.MODEL", "rf")
     @patch(
@@ -246,7 +246,7 @@ def setUp(self):
 
     @patch(
         "src.detector.detector.CHECKSUM",
-        "ba1f718179191348fe2abd51644d76191d42a5d967c6844feb3371b6f798bf06",
+        "021af76b2385ddbc76f6e3ad10feb0bb081f9cf05cff2e52333e31040bbf36cc",
     )
     @patch("src.detector.detector.MODEL", "rf")
     @patch(
@@ -265,13 +265,13 @@ def test_save_warning(self, mock_clickhouse, mock_kafka_consume_handler):
                 "request": "google.de",
                 "probability": 0.8765,
                 "model": "rf",
-                "sha256": "ba1f718179191348fe2abd51644d76191d42a5d967c6844feb3371b6f798bf06",
+                "sha256": "021af76b2385ddbc76f6e3ad10feb0bb081f9cf05cff2e52333e31040bbf36cc",
             },
             {
                 "request": "request.de",
                 "probability": 0.12388,
                 "model": "rf",
-                "sha256": "ba1f718179191348fe2abd51644d76191d42a5d967c6844feb3371b6f798bf06",
+                "sha256": "021af76b2385ddbc76f6e3ad10feb0bb081f9cf05cff2e52333e31040bbf36cc",
             },
         ]
         sut.messages = [{"logline_id": "test_id"}]
@@ -285,7 +285,7 @@ def test_save_warning(self, mock_clickhouse, mock_kafka_consume_handler):
 
     @patch(
         "src.detector.detector.CHECKSUM",
-        "ba1f718179191348fe2abd51644d76191d42a5d967c6844feb3371b6f798bf06",
+        "021af76b2385ddbc76f6e3ad10feb0bb081f9cf05cff2e52333e31040bbf36cc",
     )
     @patch("src.detector.detector.MODEL", "rf")
     @patch(
@@ -309,7 +309,7 @@ def test_save_empty_warning(self, mock_clickhouse, mock_kafka_consume_handler):
 
     @patch(
         "src.detector.detector.CHECKSUM",
-        "ba1f718179191348fe2abd51644d76191d42a5d967c6844feb3371b6f798bf06",
+        "021af76b2385ddbc76f6e3ad10feb0bb081f9cf05cff2e52333e31040bbf36cc",
     )
     @patch("src.detector.detector.MODEL", "rf")
     @patch(
@@ -328,7 +328,7 @@ def test_save_warning_error(self, mock_clickhouse, mock_kafka_consume_handler):
                 "request": "request.de",
                 "probability": "INVALID",
                 "model": "rf",
-                "sha256": "ba1f718179191348fe2abd51644d76191d42a5d967c6844feb3371b6f798bf06",
+                "sha256": "021af76b2385ddbc76f6e3ad10feb0bb081f9cf05cff2e52333e31040bbf36cc",
             }
         ]
         with self.assertRaises(Exception):