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keep applicant count fix surgical

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-Puter
2026-07-17 19:48:35 +05:30
parent e30d24dbe1
commit 7097ec894d
2 changed files with 35 additions and 110 deletions
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107
tests/test_stats.py
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@@ -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 (
_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"},
]
}
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,
"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)
)
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"))
@@ -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(
[
{"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
@@ -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(
{"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)
@@ -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(
{
"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)