split models into individual files for modularity

backend/app/models/artifacts.py

@@ -0,0 +1,35 @@
+from datetime import datetime
+
+from app import db
+from app import ma
+from sqlalchemy.dialects.postgresql import TEXT  # Add this line
+
+# Class for artifacts collected which stores the artifact name, artificat results (json), hostname
+# Path: backend\app\models.py
+class Artifact(db.Model):
+    id = db.Column(db.Integer, primary_key=True)
+    artifact_name = db.Column(db.String(100))
+    artifact_results = db.Column(TEXT)
+    hostname = db.Column(db.String(100))
+
+    def __init__(self, artifact_name, artifact_results, hostname):
+        self.artifact_name = artifact_name
+        self.artifact_results = artifact_results
+        self.hostname = hostname
+
+    def __repr__(self):
+        return f"<Artifact {self.artifact_name}>"
+
+
+class ArtifactSchema(ma.Schema):
+    class Meta:
+        fields = (
+            "id",
+            "artifact_name",
+            "artifact_results",
+            "hostname",
+        )
+
+
+artifact_schema = ArtifactSchema()
+artifacts_schema = ArtifactSchema(many=True)

backend/app/models/cases.py

@@ -0,0 +1,34 @@
+from datetime import datetime
+
+from app import db
+from app import ma
+
+# Class for cases which stores the case ID, case name, list of agents
+# Path: backend\app\models.py
+class Case(db.Model):
+    id = db.Column(db.Integer, primary_key=True)
+    case_id = db.Column(db.Integer)
+    case_name = db.Column(db.String(100))
+    agents = db.Column(db.String(1000))
+
+    def __init__(self, case_id, case_name, agents):
+        self.case_id = case_id
+        self.case_name = case_name
+        self.agents = agents
+
+    def __repr__(self):
+        return f"<Case {self.case_id}>"
+
+
+class CaseSchema(ma.Schema):
+    class Meta:
+        fields = (
+            "id",
+            "case_id",
+            "case_name",
+            "agents",
+        )
+
+
+case_schema = CaseSchema()
+cases_schema = CaseSchema(many=True)

backend/app/models/graylog.py

@@ -0,0 +1,58 @@
+from datetime import datetime
+
+from app import db
+from app import ma
+
+# Class for Graylog allocation which stores throughput metrics
+# Generate timestamp for each entry and invoke every 5 minutes.
+# Path: backend\app\models.py
+class GraylogMetricsAllocation(db.Model):
+    id = db.Column(db.Integer, primary_key=True)
+    input_usage = db.Column(db.Float)
+    output_usage = db.Column(db.Float)
+    processor_usage = db.Column(db.Float)
+    input_1_sec_rate = db.Column(db.Float)
+    output_1_sec_rate = db.Column(db.Float)
+    total_input = db.Column(db.Float)
+    total_output = db.Column(db.Float)
+    timestamp = db.Column(db.DateTime, default=datetime.utcnow)
+
+    def __init__(
+        self,
+        input_usage,
+        output_usage,
+        processor_usage,
+        input_1_sec_rate,
+        output_1_sec_rate,
+        total_input,
+        total_output,
+    ):
+        self.input_usage = input_usage
+        self.output_usage = output_usage
+        self.processor_usage = processor_usage
+        self.input_1_sec_rate = input_1_sec_rate
+        self.output_1_sec_rate = output_1_sec_rate
+        self.total_input = total_input
+        self.total_output = total_output
+
+    def __repr__(self):
+        return f"<GraylogMetricsAllocation {self.id}>"
+
+
+class GraylogMetricsAllocationSchema(ma.Schema):
+    class Meta:
+        fields = (
+            "id",
+            "input_usage",
+            "output_usage",
+            "processor_usage",
+            "input_1_sec_rate",
+            "output_1_sec_rate",
+            "total_input",
+            "total_output",
+            "timestamp",
+        )
+
+
+graylog_metrics_allocation_schema = GraylogMetricsAllocationSchema()
+graylog_metrics_allocations_schema = GraylogMetricsAllocationSchema(many=True)