keep applicant count fix surgical

app/engine/stats/__init__.py

@@ -9,12 +9,11 @@ Honest sources (SCOUT_UI_SPEC):
 
 Anything without a real source is omitted — the UI cuts or locks it, never fakes it.
 """
-
 from __future__ import annotations
 
 import asyncio
-import math
 import logging
+import math
 from datetime import datetime, timezone
 
 from app.db import repo as _repo
@@ -32,9 +31,7 @@ def _match_scores(opps: list[dict]) -> list[int]:
     return out
 
 
-def _histogram(
+def _histogram(scores: list[int], lo: int = 60, hi: int = 100, bins: int = 11) -> list[int]:
-    scores: list[int], lo: int = 60, hi: int = 100, bins: int = 11
-) -> list[int]:
     h = [0] * bins
     span = (hi - lo) / bins
     for s in scores:
@@ -61,14 +58,9 @@ def _apply_window(opps: list[dict]) -> dict:
         return {"median_age_days": None, "fresh_share": None, "urgency": None}
     ages.sort()
     median = ages[len(ages) // 2]
-    fresh = sum(1 for a in ages if a <= 3) / len(ages)  # posted within 3 days
+    fresh = sum(1 for a in ages if a <= 3) / len(ages)        # posted within 3 days
     urgency = "high" if median <= 3 else "medium" if median <= 7 else "low"
-    return {
+    return {"median_age_days": median, "fresh_share": round(fresh, 2), "urgency": urgency, "dated": len(ages)}
-        "median_age_days": median,
-        "fresh_share": round(fresh, 2),
-        "urgency": urgency,
-        "dated": len(ages),
-    }
 
 
 async def build_scout_stats(user_id: str, *, user_uuid: str | None = None) -> dict:
@@ -112,34 +104,22 @@ async def build_scout_stats(user_id: str, *, user_uuid: str | None = None) -> di
         # salary band = average of each deck's peak salary, accumulated across decks (₹L)
         "salaryMaxL": salary_band,
         "avgApplicants": round(sum(apps) / len(apps)) if apps else None,
-        "activeWindow": active
+        "activeWindow": active if active.get("samples") else None,   # WHEN the user works their search
-        if active.get("samples")
-        else None,  # WHEN the user works their search
         # ── activity-derived (real, this DB) — funnel is all-time so the stages are consistent ──
         "funnel": [
-            {
+            {"label": "Matches", "value": max(act["matches"], matches), "tracked": True},
-                "label": "Matches",
-                "value": max(act["matches"], matches),
-                "tracked": True,
-            },
             {"label": "Viewed", "value": act["viewed"], "tracked": True},
             {"label": "Shortlisted", "value": act["saved"], "tracked": True},
             {"label": "Applied", "value": act["applied"], "tracked": True},
         ],
         "tailoredResumes": act["tailored"],
         "searches": act["searches"],
-        "percentile": act[
+        "percentile": act["percentile"],     # cohort engagement percentile (top 100-percentile %)
-            "percentile"
-        ],  # cohort engagement percentile (top 100-percentile %)
         "cohortSize": act["cohort_size"],
-        "searchStage": "Applying"
+        "searchStage": "Applying" if act["applied"] else "Reviewing" if act["saved"] else "Scanning",
-        if act["applied"]
-        else "Reviewing"
-        if act["saved"]
-        else "Scanning",
         # ── cross-service (real; None → the UI omits the card, never fakes it) ──
         "qxNow": (qx or {}).get("qx"),
         "quotients": (qx or {}).get("quotients"),
-        "qxTrend": qx_trend,  # RQ Score series (qscore-service) → Readiness-trend sparkline
+        "qxTrend": qx_trend,            # RQ Score series (qscore-service) → Readiness-trend sparkline
         "dayStreak": streak,
     }

tests/test_stats.py

@@ -1,5 +1,4 @@
 """Dashboard stats — pure-helper and RQ Score client contract tests."""
-
 import asyncio
 
 import httpx
@@ -11,71 +10,34 @@ from app.db.repo import _activity_score
 
 
 def test_posted_date_per_board():
-    assert (
+    assert _posted_date({"createdDate": "2026-06-18T10:37:17Z"}) == "2026-06-18T10:37:17Z"   # Naukri
-        _posted_date({"createdDate": "2026-06-18T10:37:17Z"}) == "2026-06-18T10:37:17Z"
+    assert _posted_date({"postedDate": "2026-06-18T12:46:39Z"}) == "2026-06-18T12:46:39Z"     # LinkedIn
-    )  # Naukri
+    assert _posted_date({"date_posted": "2026-06-17T17:38:14Z"}) == "2026-06-17T17:38:14Z"    # Foundit
-    assert (
+    assert _posted_date({"jobDetails": {"createdDate": "2026-06-18T00:00:00Z"}}) is not None   # nested
-        _posted_date({"postedDate": "2026-06-18T12:46:39Z"}) == "2026-06-18T12:46:39Z"
-    )  # LinkedIn
-    assert (
-        _posted_date({"date_posted": "2026-06-17T17:38:14Z"}) == "2026-06-17T17:38:14Z"
-    )  # Foundit
-    assert (
-        _posted_date({"jobDetails": {"createdDate": "2026-06-18T00:00:00Z"}})
-        is not None
-    )  # nested
     assert _posted_date({"nope": "x"}) is None
 
 
 def test_match_scores_and_histogram():
     opps = [{"match": {"score": 84}}, {"matchScore": 72}, {"match": {"score": 0}}, {}]
     scores = S._match_scores(opps)
-    assert sorted(scores) == [72, 84]  # 0 and missing dropped
+    assert sorted(scores) == [72, 84]                 # 0 and missing dropped
     h = S._histogram(scores)
     assert sum(h) == 2 and len(h) == 11
 
 
 def test_scout_stats_accepts_numeric_applicant_strings(monkeypatch):
-    feed = {
+    feed = {"opportunities": [{"applicants": "10"}, {"applicants": 30}, {"applicants": "unknown"}]}
-        "opportunities": [
-            {"applicants": "10"},
-            {"applicants": 30},
-            {"applicants": "unknown"},
-        ]
-    }
     activity = {
-        "matches": 3,
+        "matches": 3, "viewed": 0, "saved": 0, "applied": 0, "tailored": 0,
-        "viewed": 0,
+        "searches": 1, "percentile": None, "cohort_size": 1,
-        "saved": 0,
-        "applied": 0,
-        "tailored": 0,
-        "searches": 1,
-        "percentile": None,
-        "cohort_size": 1,
     }
-    monkeypatch.setattr(
+    monkeypatch.setattr(S._repo, "get_feed", lambda _user_id: asyncio.sleep(0, result=feed))
-        S._repo, "get_feed", lambda _user_id: asyncio.sleep(0, result=feed)
+    monkeypatch.setattr(S._repo, "get_activity_stats", lambda _user_id: asyncio.sleep(0, result=activity))
-    )
+    monkeypatch.setattr(S._repo, "get_active_window", lambda _user_id: asyncio.sleep(0, result={}))
-    monkeypatch.setattr(
+    monkeypatch.setattr(S._repo, "get_salary_band", lambda _user_id: asyncio.sleep(0, result=None))
-        S._repo,
+    monkeypatch.setattr(S._clients, "fetch_qx", lambda _user_uuid: asyncio.sleep(0, result=None))
-        "get_activity_stats",
+    monkeypatch.setattr(S._clients, "fetch_qx_trend", lambda _user_uuid: asyncio.sleep(0, result=None))
-        lambda _user_id: asyncio.sleep(0, result=activity),
+    monkeypatch.setattr(S._clients, "fetch_streak", lambda _user_id: asyncio.sleep(0, result=None))
-    )
-    monkeypatch.setattr(
-        S._repo, "get_active_window", lambda _user_id: asyncio.sleep(0, result={})
-    )
-    monkeypatch.setattr(
-        S._repo, "get_salary_band", lambda _user_id: asyncio.sleep(0, result=None)
-    )
-    monkeypatch.setattr(
-        S._clients, "fetch_qx", lambda _user_uuid: asyncio.sleep(0, result=None)
-    )
-    monkeypatch.setattr(
-        S._clients, "fetch_qx_trend", lambda _user_uuid: asyncio.sleep(0, result=None)
-    )
-    monkeypatch.setattr(
-        S._clients, "fetch_streak", lambda _user_id: asyncio.sleep(0, result=None)
-    )
 
     result = asyncio.run(S.build_scout_stats("user-1"))
 
@@ -85,26 +47,13 @@ def test_scout_stats_accepts_numeric_applicant_strings(monkeypatch):
 def test_apply_window_freshness():
     # all None when no posting dates (honest — never fabricated)
     assert S._apply_window([{}, {"posted_date": None}])["urgency"] is None
-    w = S._apply_window(
+    w = S._apply_window([{"posted_date": "2026-06-19T00:00:00Z"}, {"posted_date": "2026-06-15T00:00:00Z"}])
-        [
+    assert w["dated"] == 2 and w["median_age_days"] is not None and w["urgency"] in ("high", "medium", "low")
-            {"posted_date": "2026-06-19T00:00:00Z"},
-            {"posted_date": "2026-06-15T00:00:00Z"},
-        ]
-    )
-    assert (
-        w["dated"] == 2
-        and w["median_age_days"] is not None
-        and w["urgency"] in ("high", "medium", "low")
-    )
 
 
 def test_activity_score_weighting():
     # applies weighted highest, then saves, views, searches
-    assert (
+    assert _activity_score(0, 0, 1, 0) > _activity_score(0, 1, 0, 0) > _activity_score(1, 0, 0, 0)
-        _activity_score(0, 0, 1, 0)
-        > _activity_score(0, 1, 0, 0)
-        > _activity_score(1, 0, 0, 0)
-    )
     assert _activity_score(0, 0, 0, 0) == 0
 
 
@@ -153,9 +102,7 @@ def test_fetch_qx_treats_malformed_payload_as_absent(monkeypatch):
 
 def test_fetch_qx_trend_ignores_malformed_and_absent_points(monkeypatch):
     async def _get(_self, _url, **_kwargs):
-        return _Response(
+        return _Response({"points": [None, {"rq_score": "bad"}, {"rq_score": 35}, {"rq_score": 40}]})
-            {"points": [None, {"rq_score": "bad"}, {"rq_score": 35}, {"rq_score": 40}]}
-        )
 
     monkeypatch.setattr(httpx.AsyncClient, "get", _get)
 
@@ -164,15 +111,13 @@ def test_fetch_qx_trend_ignores_malformed_and_absent_points(monkeypatch):
 
 def test_fetch_qx_trend_reads_strict_rq_score_points(monkeypatch):
     async def _get(_self, _url, **_kwargs):
-        return _Response(
+        return _Response({
-            {
+            "points": [
-                "points": [
+                {"rq_score": 35, "q_score": 91},
-                    {"rq_score": 35, "q_score": 91},
+                {"rq_score": 44.16, "q_score": 92},
-                    {"rq_score": 44.16, "q_score": 92},
+                {"q_score": 93},
-                    {"q_score": 93},
+            ]
-                ]
+        })
-            }
-        )
 
     monkeypatch.setattr(httpx.AsyncClient, "get", _get)