alvis
d37801806d
Compose and supporting code for four services that had been running or prototyped without their config tracked here, per the repo convention that agap_git holds the compose + config while application source lives in each service's own Gitea repo. Only placeholder credentials are included: mood/.env.example and moodtracker/.env.example ship dummy values, and overleaf/variables.env carries app name and feature flags only. Real values stay in Vaultwarden. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
113 lines
3.8 KiB
Python
113 lines
3.8 KiB
Python
import json
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import os
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import sys
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import tempfile
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sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
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from src import store
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def _fresh_db():
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path = os.path.join(tempfile.mkdtemp(), "t.sqlite")
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conn = store.connect(path)
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store.init_db(conn)
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return conn
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def _row(id_, ts, mood, tags, note="", affirmation=""):
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return {"id": id_, "ts": ts, "mood": mood, "tags": json.dumps(tags),
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"note": note, "affirmation": affirmation}
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def test_upsert_idempotent():
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conn = _fresh_db()
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rows = [
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_row(1, "2026-07-01T08:00:00+00:00", 4, ["calm"]),
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_row(2, "2026-07-02T08:00:00+00:00", 2, ["sad", "tired"]),
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]
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store.upsert_entries(conn, rows)
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store.upsert_entries(conn, rows) # re-run same rows
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count = conn.execute("SELECT COUNT(*) c FROM mood_entries").fetchone()["c"]
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assert count == 2 # no duplication despite double ingest
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def test_upsert_updates_on_conflict():
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conn = _fresh_db()
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rows = [_row(1, "2026-07-01T08:00:00+00:00", 4, ["calm"], note="first")]
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store.upsert_entries(conn, rows)
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rows[0]["note"] = "corrected"
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store.upsert_entries(conn, rows)
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got = conn.execute("SELECT note FROM mood_entries WHERE source_id=1").fetchone()["note"]
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assert got == "corrected"
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def test_sync_state_high_water_mark():
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conn = _fresh_db()
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store.set_sync_state(conn, "moodtracker_entries", 5)
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store.set_sync_state(conn, "moodtracker_entries", 3) # older cursor must not regress
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assert store.get_last_synced_id(conn, "moodtracker_entries") == 5
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store.set_sync_state(conn, "moodtracker_entries", 9)
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assert store.get_last_synced_id(conn, "moodtracker_entries") == 9
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def test_summary_and_daily_mood():
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conn = _fresh_db()
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rows = [
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_row(1, "2026-07-01T08:00:00+00:00", 4, ["calm"]),
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_row(2, "2026-07-01T20:00:00+00:00", 2, ["tired"]),
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_row(3, "2026-07-02T08:00:00+00:00", 5, ["happy"]),
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]
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store.upsert_entries(conn, rows)
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s = store.summary(conn)
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assert s["entries"] == 3
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assert s["coverage"]["earliest"] is not None
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daily = store.daily_mood(conn, days=30)
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by_day = {d["day"]: d for d in daily}
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assert by_day["2026-07-01"]["entries"] == 2
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assert by_day["2026-07-01"]["avg_mood"] == 3.0 # (4+2)/2
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assert by_day["2026-07-02"]["avg_mood"] == 5.0
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def test_tag_breakdown():
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conn = _fresh_db()
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rows = [
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_row(1, "2026-07-01T08:00:00+00:00", 5, ["happy", "energetic"]),
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_row(2, "2026-07-02T08:00:00+00:00", 1, ["sad", "tired"]),
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_row(3, "2026-07-03T08:00:00+00:00", 2, ["tired"]),
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]
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store.upsert_entries(conn, rows)
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tags = store.tag_breakdown(conn, days=90, min_count=2)
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by_tag = {t["tag"]: t for t in tags}
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assert by_tag["tired"]["count"] == 2
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assert by_tag["tired"]["avg_mood"] == 1.5
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assert "happy" not in by_tag # min_count=2 filters singletons
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def test_correlate_with_series():
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conn = _fresh_db()
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rows = [
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_row(1, "2026-07-01T08:00:00+00:00", 5, []),
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_row(2, "2026-07-02T08:00:00+00:00", 4, []),
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_row(3, "2026-07-03T08:00:00+00:00", 2, []),
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_row(4, "2026-07-04T08:00:00+00:00", 1, []),
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]
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store.upsert_entries(conn, rows)
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# perfectly correlated external series (e.g. "hours slept")
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external = {
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"2026-07-01": 8.0, "2026-07-02": 7.0,
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"2026-07-03": 5.0, "2026-07-04": 4.0,
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}
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result = store.correlate_with_series(conn, external, days=30)
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assert result["n"] == 4
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assert result["r"] > 0.99 # near-perfect positive correlation
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def test_correlate_too_few_points():
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conn = _fresh_db()
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store.upsert_entries(conn, [_row(1, "2026-07-01T08:00:00+00:00", 3, [])])
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result = store.correlate_with_series(conn, {"2026-07-01": 5.0}, days=30)
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assert result["n"] == 1
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assert result["r"] is None
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