feat(dashboard): time range filter for operational metrics (30d/90d/6m/1y/all)

backend/app/services/operational_metrics_service.py

@@ -61,7 +61,7 @@ def _safe_stats(values: list[float]) -> dict:
 # ── MTTD (Mean Time to Detect) ───────────────────────────────────────
 
 
-def calculate_mttd(db: Session) -> Optional[dict]:
+def calculate_mttd(db: Session, since: Optional[datetime] = None) -> Optional[dict]:
     """Calculate Mean Time to Detect.
 
     Uses direct timestamp fields on the Test record:
@@ -71,14 +71,13 @@ def calculate_mttd(db: Session) -> Optional[dict]:
     MTTD = blue_started_at - red_started_at - red_paused_seconds
     Represents how long Red Team spent executing before Blue received the test.
     """
-    tests = (
-        db.query(Test)
-        .filter(
-            Test.red_started_at.isnot(None),
-            Test.blue_started_at.isnot(None),
-        )
-        .all()
+    q = db.query(Test).filter(
+        Test.red_started_at.isnot(None),
+        Test.blue_started_at.isnot(None),
     )
+    if since:
+        q = q.filter(Test.red_started_at >= since)
+    tests = q.all()
 
     # Assign detection_times = []
     detection_times = []
@@ -95,7 +94,7 @@ def calculate_mttd(db: Session) -> Optional[dict]:
 # ── MTTR (Mean Time to Respond/Remediate) ─────────────────────────────
 
 
-def calculate_mttr(db: Session) -> Optional[dict]:
+def calculate_mttr(db: Session, since: Optional[datetime] = None) -> Optional[dict]:
     """Calculate Mean Time to Respond.
 
     Redefined as total pipeline time from attack start to full validation:
@@ -104,17 +103,14 @@ def calculate_mttr(db: Session) -> Optional[dict]:
     Represents how long the full security testing cycle takes end-to-end.
     Only uses tests that have been fully validated (both sides approved).
     """
-    tests = (
-        db.query(Test)
-        # Chain .filter() call
-        .filter(
-            Test.state == TestState.validated,
-            Test.red_started_at.isnot(None),
-            Test.blue_validated_at.isnot(None),
-        )
-        # Chain .all() call
-        .all()
+    q = db.query(Test).filter(
+        Test.state == TestState.validated,
+        Test.red_started_at.isnot(None),
+        Test.blue_validated_at.isnot(None),
     )
+    if since:
+        q = q.filter(Test.red_started_at >= since)
+    tests = q.all()
 
     # Assign response_times = []
     response_times = []
@@ -132,7 +128,7 @@ def calculate_mttr(db: Session) -> Optional[dict]:
 # ── Detection Efficacy ───────────────────────────────────────────────
 
 
-def calculate_detection_efficacy(db: Session) -> dict:
+def calculate_detection_efficacy(db: Session, since: Optional[datetime] = None) -> dict:
     """Calculate detection efficacy: detected / total validated tests.
 
     Args:
@@ -143,13 +139,10 @@ def calculate_detection_efficacy(db: Session) -> dict:
             ``not_detected``, and ``total``.
     """
     # Assign validated_tests = (
-    validated_tests = (
-        db.query(Test)
-        # Chain .filter() call
-        .filter(Test.state == TestState.validated)
-        # Chain .all() call
-        .all()
-    )
+    _vq = db.query(Test).filter(Test.state == TestState.validated)
+    if since:
+        _vq = _vq.filter(Test.created_at >= since)
+    validated_tests = _vq.all()
 
     # Assign total = len(validated_tests)
     total = len(validated_tests)
@@ -324,7 +317,7 @@ def calculate_coverage_velocity(db: Session) -> dict:
 # ── Validation Throughput ────────────────────────────────────────────
 
 
-def calculate_validation_throughput(db: Session) -> dict:
+def calculate_validation_throughput(db: Session, since: Optional[datetime] = None) -> dict:
     """Pipeline Conversion Rate — activity-based, no time dependency.
 
     Measures what percentage of tests that have entered the validation
@@ -336,21 +329,23 @@ def calculate_validation_throughput(db: Session) -> dict:
     0%   = nothing has been validated yet.
     Lower = backlog or quality issues blocking approvals.
     """
+    _since_filter = [Test.created_at >= since] if since else []
+
     validated_count = (
         db.query(func.count(Test.id))
-        .filter(Test.state == TestState.validated)
+        .filter(Test.state == TestState.validated, *_since_filter)
         .scalar()
     ) or 0
 
     rejected_count = (
         db.query(func.count(Test.id))
-        .filter(Test.state == TestState.rejected)
+        .filter(Test.state == TestState.rejected, *_since_filter)
         .scalar()
     ) or 0
 
     in_review_count = (
         db.query(func.count(Test.id))
-        .filter(Test.state == TestState.in_review)
+        .filter(Test.state == TestState.in_review, *_since_filter)
         .scalar()
     ) or 0
 
@@ -386,7 +381,7 @@ def calculate_validation_throughput(db: Session) -> dict:
 # ── Rejection Rate ──────────────────────────────────────────────────
 
 
-def calculate_rejection_rate(db: Session) -> dict:
+def calculate_rejection_rate(db: Session, since: Optional[datetime] = None) -> dict:
     """Calculate rejection rate, broken down by red_lead and blue_lead.
 
     Args:
@@ -397,65 +392,45 @@ def calculate_rejection_rate(db: Session) -> dict:
             (red-lead rejection percentage), and ``by_blue_lead``
             (blue-lead rejection percentage).
     """
-    # Assign validated_count = (
+    _sf = [Test.created_at >= since] if since else []
+
     validated_count = (
         db.query(func.count(Test.id))
-        # Chain .filter() call
-        .filter(Test.state == TestState.validated)
-        # Chain .scalar() call
+        .filter(Test.state == TestState.validated, *_sf)
         .scalar()
     ) or 0
 
-    # Assign rejected_count = (
     rejected_count = (
         db.query(func.count(Test.id))
-        # Chain .filter() call
-        .filter(Test.state == TestState.rejected)
-        # Chain .scalar() call
+        .filter(Test.state == TestState.rejected, *_sf)
         .scalar()
     ) or 0
 
-    # Assign total = validated_count + rejected_count
     total = validated_count + rejected_count
-    # Assign overall_pct = round((rejected_count / total) * 100, 1) if total > 0 else 0
     overall_pct = round((rejected_count / total) * 100, 1) if total > 0 else 0
 
-    # By red_lead (red_validation_status == "rejected")
     red_rejected = (
         db.query(func.count(Test.id))
-        # Chain .filter() call
-        .filter(Test.red_validation_status == "rejected")
-        # Chain .scalar() call
+        .filter(Test.red_validation_status == "rejected", *_sf)
         .scalar()
     ) or 0
-    # Assign red_total = (
     red_total = (
         db.query(func.count(Test.id))
-        # Chain .filter() call
-        .filter(Test.red_validation_status.in_(["approved", "rejected"]))
-        # Chain .scalar() call
+        .filter(Test.red_validation_status.in_(["approved", "rejected"]), *_sf)
         .scalar()
     ) or 0
-    # Assign red_pct = round((red_rejected / red_total) * 100, 1) if red_total > 0 else 0
     red_pct = round((red_rejected / red_total) * 100, 1) if red_total > 0 else 0
 
-    # By blue_lead
     blue_rejected = (
         db.query(func.count(Test.id))
-        # Chain .filter() call
-        .filter(Test.blue_validation_status == "rejected")
-        # Chain .scalar() call
+        .filter(Test.blue_validation_status == "rejected", *_sf)
         .scalar()
     ) or 0
-    # Assign blue_total = (
     blue_total = (
         db.query(func.count(Test.id))
-        # Chain .filter() call
-        .filter(Test.blue_validation_status.in_(["approved", "rejected"]))
-        # Chain .scalar() call
+        .filter(Test.blue_validation_status.in_(["approved", "rejected"]), *_sf)
         .scalar()
     ) or 0
-    # Assign blue_pct = round((blue_rejected / blue_total) * 100, 1) if blue_total > 0 else 0
     blue_pct = round((blue_rejected / blue_total) * 100, 1) if blue_total > 0 else 0
 
     # Return {
@@ -472,7 +447,7 @@ def calculate_rejection_rate(db: Session) -> dict:
 # ── Aggregated Operational Metrics ───────────────────────────────────
 
 
-def get_all_operational_metrics(db: Session) -> dict:
+def get_all_operational_metrics(db: Session, since: Optional[datetime] = None) -> dict:
     """Return all operational metrics combined in a single response.
 
     Args:
@@ -483,22 +458,14 @@ def get_all_operational_metrics(db: Session) -> dict:
             ``alert_fidelity``, ``coverage_velocity``,
             ``validation_throughput``, and ``rejection_rate`` keys.
     """
-    # Return {
     return {
-        # Literal argument value
-        "mttd": calculate_mttd(db),
-        # Literal argument value
-        "mttr": calculate_mttr(db),
-        # Literal argument value
-        "detection_efficacy": calculate_detection_efficacy(db),
-        # Literal argument value
-        "alert_fidelity": calculate_alert_fidelity(db),
-        # Literal argument value
-        "coverage_velocity": calculate_coverage_velocity(db),
-        # Literal argument value
-        "validation_throughput": calculate_validation_throughput(db),
-        # Literal argument value
-        "rejection_rate": calculate_rejection_rate(db),
+        "mttd": calculate_mttd(db, since),
+        "mttr": calculate_mttr(db, since),
+        "detection_efficacy": calculate_detection_efficacy(db, since),
+        "alert_fidelity": calculate_alert_fidelity(db),  # TestDetectionResult, no created_at filter
+        "coverage_velocity": calculate_coverage_velocity(db),  # uses its own 12-week window
+        "validation_throughput": calculate_validation_throughput(db, since),
+        "rejection_rate": calculate_rejection_rate(db, since),
     }
 
 
@@ -583,7 +550,7 @@ def get_operational_trend(db: Session, period: str = "90d") -> list:
 # ── By Team ──────────────────────────────────────────────────────────
 
 
-def get_metrics_by_team(db: Session) -> dict:
+def get_metrics_by_team(db: Session, since: Optional[datetime] = None) -> dict:
     """Return metrics broken down by Red vs Blue team.
 
     Args:
@@ -594,33 +561,30 @@ def get_metrics_by_team(db: Session) -> dict:
             ``tests_completed``, ``avg_completion_hours``, and
             ``rejection_rate``.
     """
+    _sf = [Test.created_at >= since] if since else []
+
     # Red team metrics
     red_tests_completed = (
         db.query(func.count(Test.id))
-        # Chain .filter() call
         .filter(Test.state.in_([
             TestState.blue_evaluating,
             TestState.in_review,
             TestState.validated,
             TestState.rejected,
-        ]))
-        # Chain .scalar() call
+        ]), *_sf)
         .scalar()
     ) or 0
 
-    # Assign red_avg_time = None
     red_avg_time = None
-    # Assign red_times = []
     red_times = []
     # Red team avg execution time: red_started_at → blue_started_at (net of paused)
-    tests_with_red = (
-        db.query(Test)
-        .filter(
-            Test.red_started_at.isnot(None),
-            Test.blue_started_at.isnot(None),
-        )
-        .all()
+    _rq = db.query(Test).filter(
+        Test.red_started_at.isnot(None),
+        Test.blue_started_at.isnot(None),
     )
+    if since:
+        _rq = _rq.filter(Test.red_started_at >= since)
+    tests_with_red = _rq.all()
     # Iterate over tests_with_red
     for t in tests_with_red:
         gross = (t.blue_started_at - t.red_started_at).total_seconds()
@@ -635,33 +599,23 @@ def get_metrics_by_team(db: Session) -> dict:
     # Blue team: count tests that reached the blue evaluation phase
     blue_tests_completed = (
         db.query(func.count(Test.id))
-        # Chain .filter() call
         .filter(Test.state.in_([
             TestState.in_review,
             TestState.validated,
             TestState.rejected,
-        ]))
-        # Chain .scalar() call
+        ]), *_sf)
         .scalar()
     ) or 0
 
-    # Blue avg evaluation time:
-    # Prefer blue_work_started_at (actual pick-up) → blue_validated_at.
-    # Fall back to blue_started_at if blue_work_started_at is not set.
     blue_avg_time = None
-    # Assign blue_times = []
     blue_times = []
-    # Assign tests_with_blue = (
-    tests_with_blue = (
-        db.query(Test)
-        # Chain .filter() call
-        .filter(
-            Test.blue_started_at.isnot(None),
-            Test.blue_validated_at.isnot(None),
-        )
-        # Chain .all() call
-        .all()
+    _bq = db.query(Test).filter(
+        Test.blue_started_at.isnot(None),
+        Test.blue_validated_at.isnot(None),
     )
+    if since:
+        _bq = _bq.filter(Test.blue_started_at >= since)
+    tests_with_blue = _bq.all()
     # Iterate over tests_with_blue
     for t in tests_with_blue:
         phase_start = t.blue_work_started_at or t.blue_started_at
@@ -685,15 +639,12 @@ def get_metrics_by_team(db: Session) -> dict:
             # Literal argument value
             "avg_completion_hours": red_avg_time,
             "avg_unit": "min" if (red_avg_raw is not None and red_avg_raw < 1) else "hrs",
-            "rejection_rate": calculate_rejection_rate(db)["by_red_lead"],
+            "rejection_rate": calculate_rejection_rate(db, since)["by_red_lead"],
         },
-        # Literal argument value
         "blue_team": {
-            # Literal argument value
             "tests_completed": blue_tests_completed,
-            # Literal argument value
             "avg_completion_hours": blue_avg_time,
             "avg_unit": "min" if (blue_avg_raw is not None and blue_avg_raw < 1) else "hrs",
-            "rejection_rate": calculate_rejection_rate(db)["by_blue_lead"],
+            "rejection_rate": calculate_rejection_rate(db, since)["by_blue_lead"],
         },
     }