be921559e7
- get_scout_stats aggregator (app/engine/stats): assembles the REAL Summary metrics —
funnel + cohort engagement rank + active-window (activity timestamps by hour) from our DB,
accumulating salary band (avg of each deck's peak, ₹L), match/competition stats from the
feed, Momentum/QX + Q-Score trend (qscore-service), day streak (user-service). Honest:
unsourced cards return None so the UI omits/locks them, never faked. posted_date extractor.
- Activity tracking: viewed/saved flags + search_count → funnel (Matches→Viewed→Shortlisted→
Applied) + engagement percentile. matchesFound = all-time count.
- Per-board search cursors {board: page} (replaces the single cursor): only boards that truly
paginate (LinkedIn) get one; cursor = LAST page fetched (1st search of a new query → 1).
Resets on query change OR >24h (boards refresh ~daily). Dropped Naukri incremental/stateKey
(opaque, exhausting, cross-account dedup state) — dedup is the PER-USER seen-net only.
- tests: stats helpers (posting-age, histogram, active-window, engagement score).
34 lines
1.6 KiB
Python
34 lines
1.6 KiB
Python
"""Dashboard stats — pure-helper contract tests (no DB / no network)."""
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from app.engine import stats as S
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from app.engine.normalize import _posted_date
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from app.db.repo import _activity_score
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def test_posted_date_per_board():
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assert _posted_date({"createdDate": "2026-06-18T10:37:17Z"}) == "2026-06-18T10:37:17Z" # Naukri
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assert _posted_date({"postedDate": "2026-06-18T12:46:39Z"}) == "2026-06-18T12:46:39Z" # LinkedIn
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assert _posted_date({"date_posted": "2026-06-17T17:38:14Z"}) == "2026-06-17T17:38:14Z" # Foundit
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assert _posted_date({"jobDetails": {"createdDate": "2026-06-18T00:00:00Z"}}) is not None # nested
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assert _posted_date({"nope": "x"}) is None
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def test_match_scores_and_histogram():
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opps = [{"match": {"score": 84}}, {"matchScore": 72}, {"match": {"score": 0}}, {}]
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scores = S._match_scores(opps)
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assert sorted(scores) == [72, 84] # 0 and missing dropped
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h = S._histogram(scores)
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assert sum(h) == 2 and len(h) == 11
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def test_apply_window_freshness():
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# all None when no posting dates (honest — never fabricated)
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assert S._apply_window([{}, {"posted_date": None}])["urgency"] is None
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w = S._apply_window([{"posted_date": "2026-06-19T00:00:00Z"}, {"posted_date": "2026-06-15T00:00:00Z"}])
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assert w["dated"] == 2 and w["median_age_days"] is not None and w["urgency"] in ("high", "medium", "low")
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def test_activity_score_weighting():
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# applies weighted highest, then saves, views, searches
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assert _activity_score(0, 0, 1, 0) > _activity_score(0, 1, 0, 0) > _activity_score(1, 0, 0, 0)
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assert _activity_score(0, 0, 0, 0) == 0
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