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fix scout stats applicant counts

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This commit is contained in:
-Puter
2026-07-17 19:47:44 +05:30
parent 19d7e8e04f
commit e30d24dbe1
2 changed files with 130 additions and 25 deletions
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49
app/engine/stats/__init__.py
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@@ -9,9 +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
from datetime import datetime, timezone
@@ -30,7 +32,9 @@ def _match_scores(opps: list[dict]) -> list[int]:
return out
def _histogram(scores: list[int], lo: int = 60, hi: int = 100, bins: int = 11) -> list[int]:
def _histogram(
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:
@@ -57,9 +61,14 @@ 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 {"median_age_days": median, "fresh_share": round(fresh, 2), "urgency": urgency, "dated": len(ages)}
return {
"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:
@@ -78,7 +87,17 @@ async def build_scout_stats(user_id: str, *, user_uuid: str | None = None) -> di
opps = feed.get("opportunities") or []
scores = _match_scores(opps)
apps = [j.get("applicants") for j in opps if j.get("applicants")]
apps = []
for opportunity in opps:
raw_applicants = opportunity.get("applicants")
if isinstance(raw_applicants, bool):
continue
try:
applicants = float(raw_applicants)
except (TypeError, ValueError):
continue
if math.isfinite(applicants) and applicants >= 0:
apps.append(applicants)
matches = len(opps)
return {
@@ -93,22 +112,34 @@ 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 if active.get("samples") else None, # WHEN the user works their search
"activeWindow": active
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"], # cohort engagement percentile (top 100-percentile %)
"percentile": act[
"percentile"
], # cohort engagement percentile (top 100-percentile %)
"cohortSize": act["cohort_size"],
"searchStage": "Applying" if act["applied"] else "Reviewing" if act["saved"] else "Scanning",
"searchStage": "Applying"
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,
}

106
tests/test_stats.py
View File

@@ -1,4 +1,5 @@
"""Dashboard stats — pure-helper and RQ Score client contract tests."""
import asyncio
import httpx
@@ -10,31 +11,100 @@ from app.db.repo import _activity_score
def test_posted_date_per_board():
assert _posted_date({"createdDate": "2026-06-18T10:37:17Z"}) == "2026-06-18T10:37:17Z" # Naukri
assert _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({"createdDate": "2026-06-18T10:37:17Z"}) == "2026-06-18T10:37:17Z"
) # Naukri
assert (
_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 = {
"opportunities": [
{"applicants": "10"},
{"applicants": 30},
{"applicants": "unknown"},
]
}
activity = {
"matches": 3,
"viewed": 0,
"saved": 0,
"applied": 0,
"tailored": 0,
"searches": 1,
"percentile": None,
"cohort_size": 1,
}
monkeypatch.setattr(
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(
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"))
assert result["avgApplicants"] == 20
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([{"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")
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")
)
def test_activity_score_weighting():
# applies weighted highest, then saves, views, searches
assert _activity_score(0, 0, 1, 0) > _activity_score(0, 1, 0, 0) > _activity_score(1, 0, 0, 0)
assert (
_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
@@ -83,7 +153,9 @@ 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({"points": [None, {"rq_score": "bad"}, {"rq_score": 35}, {"rq_score": 40}]})
return _Response(
{"points": [None, {"rq_score": "bad"}, {"rq_score": 35}, {"rq_score": 40}]}
)
monkeypatch.setattr(httpx.AsyncClient, "get", _get)
@@ -92,13 +164,15 @@ 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({
"points": [
{"rq_score": 35, "q_score": 91},
{"rq_score": 44.16, "q_score": 92},
{"q_score": 93},
]
})
return _Response(
{
"points": [
{"rq_score": 35, "q_score": 91},
{"rq_score": 44.16, "q_score": 92},
{"q_score": 93},
]
}
)
monkeypatch.setattr(httpx.AsyncClient, "get", _get)