feat: Stand-Dashboard, Score-Histogram, PM-Markdown, Live-Polling, Cluster-Indicator
Sechs zusammengehoerige UX/Performance-Erweiterungen:
**1. /v2/admin/stand — System-Stand-Dashboard**
KPI-Kacheln (Bewertungen, Plenum-Votes, Match, Vote-Orphans, News, PM-
Drafts, Bookmarks) + GWÖ-Score-Histogram + Per-BL-Tabelle + News-Source-
Tabelle. Auto-Refresh 30 s. Endpoint /api/admin/stand liefert alles in
einem Roundtrip. Nav-Eintrag "Stand" in der Admin-Sektion.
**2. /auswertungen Score-Histogram-Tab**
4. Tab "Score-Verteilung" mit Bar-Chart 0–10. Endpoint
/api/auswertungen/score-histogram liefert Buckets, optional gefiltert
nach Bundesland + Wahlperiode. Reagiert auf den globalen BL-Filter.
**3. PM-Body Markdown-Rendering**
Mini-Renderer im Modal: **bold** / __bold__ / *italic* / _italic_ /
- list-bullets / Doppel-Newline-Paragraphen. Kein externer Markdown-
Parser, keine neue Dependency. Body wird HTML-escaped, Patterns dann
zu Tags umgesetzt.
**4. Performance-Cache fuer themen_matching**
TTL-Cache (60 s) fuer aggregate_top_themen und aggregate_news_cluster.
Cache-Key inkl. aller Filter-Parameter. Automatische Invalidation in
news_aggregator.run_aggregator nach erfolgreichem Insert/Embed.
4 neue Tests fuer cache_get/set/clear-Verhalten.
**5. Stimmverhalten Banner Live-Update**
Statt setTimeout(800) jetzt pollQueueUntilDrained: alle 4 s
GET /api/queue/status, Banner zeigt pending + elapsed live. Bei
pending=0 zwei Polls in Folge: Banner + Stimmverhalten-Charts neu
laden. Max 5 Min Polling-Timeout. Bricht ab wenn Tab gewechselt wird.
**6. Antrag-Detail Cluster-Indicator**
News-Match-Box im Antrag-Detail laedt parallel /aktuelle-themen/cluster
und mappt URL → Cluster. Pro News-Card ein "🔗 Cluster (N News)"-Badge
mit Hover-Tooltip der anderen Cluster-Members. Macht thematische
Bündel sichtbar, ohne Pop-Out auf den Cluster-Tab.
Suite: 1088 → 1092 grün (4 Cache-Tests).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
This commit is contained in:
Dotty Dotter
parent
0377cf4bd9
commit
d30fcb132a
160
app/main.py
160
app/main.py
@ -2228,6 +2228,46 @@ async def api_draft_versions(drucksache: str, news_url: str):
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}
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@app.get("/api/auswertungen/score-histogram")
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async def auswertungen_score_histogram(
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bundesland: Optional[str] = None,
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wahlperiode: Optional[str] = None,
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):
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"""GWÖ-Score-Verteilung (0–10) ueber alle Bewertungen.
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Liefert ein Bucket-Array fuer einen Histogramm-Chart. Filterbar
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ueber Bundesland + Wahlperiode (gleicher Pattern wie /matrix).
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"""
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import sqlite3
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from .auswertungen import _load_assessments
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rows = _load_assessments()
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from .wahlperioden import wahlperiode_for
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buckets = [0] * 11
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total = 0
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for r in rows:
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if bundesland and r["bundesland"] != bundesland:
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continue
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if wahlperiode is not None:
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wp = wahlperiode_for(r["datum"], r["bundesland"])
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if wp != wahlperiode:
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continue
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score = r["gwoe_score"]
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if score is None:
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continue
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bucket = min(10, max(0, int(score)))
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buckets[bucket] += 1
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total += 1
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return {
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"buckets": [
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{"score_min": i, "score_max": i + 1, "count": c}
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for i, c in enumerate(buckets)
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],
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"total": total,
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"filter": {"bundesland": bundesland, "wahlperiode": wahlperiode},
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}
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@app.get("/api/auswertungen/matrix")
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async def auswertungen_matrix(
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wahlperiode: Optional[str] = None,
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@ -2902,6 +2942,126 @@ async def v2_admin_queue(request: Request, user: dict = Depends(require_admin)):
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})
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@app.get("/v2/admin/stand", response_class=HTMLResponse)
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async def v2_admin_stand(request: Request, user: dict = Depends(require_admin)):
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"""System-Stand-Dashboard — Ueberblick ueber alle Datenmengen."""
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return templates.TemplateResponse("v2/screens/admin_stand.html", {
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"request": request,
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"v2_active_nav": "admin_stand",
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**_v2_template_context(user),
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})
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@app.get("/api/admin/stand")
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async def api_admin_stand(user: dict = Depends(require_admin)):
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"""Datenstand-Aggregation für das Stand-Dashboard.
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Liefert Gesamt + Per-Quelle + Letzte-7-Tage in einem Roundtrip.
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"""
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import sqlite3
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from datetime import datetime, timedelta, timezone
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db = sqlite3.connect(str(settings.db_path))
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cutoff_7d = (datetime.now(timezone.utc) - timedelta(days=7)).isoformat()
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try:
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# Assessments
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n_ass_total = db.execute(
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"SELECT COUNT(*) FROM assessments WHERE gwoe_score IS NOT NULL"
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).fetchone()[0]
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n_ass_7d = db.execute(
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"SELECT COUNT(*) FROM assessments "
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"WHERE gwoe_score IS NOT NULL AND created_at >= ?",
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(cutoff_7d,),
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).fetchone()[0]
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ass_per_bl = dict(db.execute(
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"SELECT bundesland, COUNT(*) FROM assessments "
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"WHERE gwoe_score IS NOT NULL GROUP BY bundesland ORDER BY 2 DESC"
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).fetchall())
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# Score-Verteilung
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score_dist = dict(db.execute(
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"SELECT CAST(gwoe_score AS INTEGER), COUNT(*) FROM assessments "
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"WHERE gwoe_score IS NOT NULL GROUP BY CAST(gwoe_score AS INTEGER)"
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).fetchall())
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# Plenum-Votes
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n_votes = db.execute("SELECT COUNT(*) FROM plenum_vote_results").fetchone()[0]
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votes_per_bl = dict(db.execute(
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"SELECT bundesland, COUNT(*) FROM plenum_vote_results "
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"GROUP BY bundesland ORDER BY 2 DESC"
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).fetchall())
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# Match (assessment ∩ vote)
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n_match = db.execute("""
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SELECT COUNT(DISTINCT a.drucksache) FROM assessments a
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INNER JOIN plenum_vote_results p
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ON a.bundesland=p.bundesland AND a.drucksache=p.drucksache
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WHERE a.gwoe_score IS NOT NULL
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""").fetchone()[0]
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n_orphans = db.execute("""
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SELECT COUNT(DISTINCT p.bundesland || '/' || p.drucksache)
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FROM plenum_vote_results p
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LEFT JOIN assessments a
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ON a.bundesland=p.bundesland AND a.drucksache=p.drucksache
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WHERE a.drucksache IS NULL
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""").fetchone()[0]
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# News
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n_news = db.execute("SELECT COUNT(*) FROM news_articles").fetchone()[0]
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n_news_emb = db.execute(
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"SELECT COUNT(*) FROM news_articles WHERE summary_embedding IS NOT NULL"
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).fetchone()[0]
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n_news_7d = db.execute(
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"SELECT COUNT(*) FROM news_articles WHERE datum >= ?", (cutoff_7d,),
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).fetchone()[0]
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news_per_source = dict(db.execute(
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"SELECT source, COUNT(*) FROM news_articles GROUP BY source"
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).fetchall())
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# PM-Drafts
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n_drafts = db.execute("SELECT COUNT(*) FROM presse_drafts").fetchone()[0]
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n_drafts_7d = db.execute(
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"SELECT COUNT(*) FROM presse_drafts WHERE created_at >= ?",
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(cutoff_7d,),
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).fetchone()[0]
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# Bookmarks
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try:
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n_bookmarks = db.execute("SELECT COUNT(*) FROM bookmarks").fetchone()[0]
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except sqlite3.OperationalError:
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n_bookmarks = 0
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finally:
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db.close()
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return {
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"assessments": {
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"total": n_ass_total,
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"last_7_days": n_ass_7d,
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"by_bundesland": ass_per_bl,
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"score_distribution": score_dist,
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},
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"plenum_votes": {
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"total": n_votes,
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"by_bundesland": votes_per_bl,
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},
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"match": {
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"with_assessment_and_vote": n_match,
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"vote_orphans": n_orphans,
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},
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"news": {
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"total": n_news,
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"embedded": n_news_emb,
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"last_7_days": n_news_7d,
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"by_source": news_per_source,
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},
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"presse_drafts": {
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"total": n_drafts,
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"last_7_days": n_drafts_7d,
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},
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"bookmarks": n_bookmarks,
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}
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@app.get("/v2/admin/abos", response_class=HTMLResponse)
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async def v2_admin_abos(request: Request, user: dict = Depends(require_admin)):
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"""Abo-Verwaltung — alle E-Mail-Abonnements (Admin)."""
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@ -344,4 +344,12 @@ def run_aggregator(db_path: Optional[Path] = None, embed: bool = True) -> dict:
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geworfen.
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"""
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articles = fetch_all()
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return upsert_articles(articles, db_path=db_path, embed=embed)
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result = upsert_articles(articles, db_path=db_path, embed=embed)
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# Cache invalidieren, damit das Dashboard die neuen News sofort zeigt.
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if result.get("inserted", 0) > 0 or result.get("embedded", 0) > 0:
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try:
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from . import themen_matching
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themen_matching.cache_clear()
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except Exception:
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logger.exception("themen_matching cache_clear failed")
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return result
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@ -66,6 +66,7 @@
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{% if is_admin %}
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<div class="v2-nav-group">
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<div class="v2-nav-label">— Administration</div>
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<a href="/v2/admin/stand" class="v2-nav-item {% if v2_active_nav == 'admin_stand' %}active{% endif %}">{{ icon("info", 14) }} Stand</a>
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<a href="/v2/admin/freischaltungen" class="v2-nav-item">{{ icon("user-check", 14) }} Freischaltungen</a>
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<a href="/v2/admin/queue" class="v2-nav-item">{{ icon("list-checks", 14) }} Queue</a>
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<a href="/v2/admin/abos" class="v2-nav-item">{{ icon("envelope-simple", 14) }} Abos</a>
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242
app/templates/v2/screens/admin_stand.html
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242
app/templates/v2/screens/admin_stand.html
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@ -0,0 +1,242 @@
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{% extends "v2/base.html" %}
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{% block title %}System-Stand — GWÖ-Antragsprüfer{% endblock %}
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{% set v2_active_nav = "admin_stand" %}
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{% block head_extra %}
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<script src="/static/chart.umd.min.js"></script>
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<style>
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.stand-grid {
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display: grid;
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grid-template-columns: repeat(auto-fit, minmax(220px, 1fr));
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gap: 14px;
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margin-bottom: 1.5rem;
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}
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.stand-kpi {
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background: var(--ecg-card-bg);
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border: 1px solid var(--ecg-border);
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border-radius: 6px;
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padding: 16px;
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text-align: center;
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}
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.stand-kpi-value {
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font-family: var(--font-mono);
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font-size: 30px;
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font-weight: 700;
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color: var(--ecg-teal);
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line-height: 1.1;
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}
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.stand-kpi-label {
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font-family: var(--font-mono);
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font-size: 11px;
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text-transform: uppercase;
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letter-spacing: 0.06em;
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opacity: 0.6;
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margin-top: 4px;
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}
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.stand-kpi-sub {
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font-family: var(--font-mono);
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font-size: 11px;
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opacity: 0.55;
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margin-top: 6px;
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}
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.stand-section {
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margin-top: 2rem;
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}
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.stand-section h2 {
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font-family: var(--font-display);
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font-size: 16px;
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color: var(--ecg-teal);
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margin: 0 0 10px;
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}
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.stand-table {
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width: 100%;
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border-collapse: collapse;
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font-family: var(--font-mono);
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font-size: 12px;
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}
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.stand-table td, .stand-table th {
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border-bottom: 1px solid var(--ecg-border);
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padding: 4px 8px;
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text-align: left;
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}
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.stand-table th {
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font-size: 10px;
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text-transform: uppercase;
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letter-spacing: 0.05em;
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opacity: 0.6;
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font-weight: 700;
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}
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.stand-table td:nth-child(2) {
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text-align: right;
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}
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</style>
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{% endblock %}
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{% block main %}
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<div style="padding:0 0 1.5rem;">
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<h1 style="font-family:var(--font-display);font-size:22px;color:var(--ecg-teal);margin:0 0 4px;">System-Stand</h1>
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<p style="font-size:12px;font-family:var(--font-mono);color:var(--ecg-dark);opacity:0.6;">
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Datenüberblick · automatische Aktualisierung alle 30 s
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</p>
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</div>
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<div id="stand-loading" style="font-family:var(--font-mono);font-size:12px;opacity:0.5;padding:16px 0;">Lade Stand …</div>
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<div id="stand-content" style="display:none;">
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<!-- KPI-Kacheln -->
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<div class="stand-grid">
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<div class="stand-kpi">
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<div class="stand-kpi-value" id="kpi-ass">—</div>
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<div class="stand-kpi-label">Bewertungen</div>
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<div class="stand-kpi-sub" id="kpi-ass-7d">— in 7 Tagen</div>
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</div>
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<div class="stand-kpi">
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<div class="stand-kpi-value" id="kpi-votes">—</div>
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<div class="stand-kpi-label">Plenum-Votes</div>
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<div class="stand-kpi-sub">aus Plenarprotokollen</div>
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</div>
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<div class="stand-kpi">
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<div class="stand-kpi-value" id="kpi-match">—</div>
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<div class="stand-kpi-label">Bewertung ∩ Vote</div>
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<div class="stand-kpi-sub" id="kpi-orphans">— Vote-Orphans</div>
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</div>
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<div class="stand-kpi">
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<div class="stand-kpi-value" id="kpi-news">—</div>
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<div class="stand-kpi-label">News</div>
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<div class="stand-kpi-sub" id="kpi-news-7d">— in 7 Tagen</div>
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</div>
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<div class="stand-kpi">
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<div class="stand-kpi-value" id="kpi-drafts">—</div>
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<div class="stand-kpi-label">PM-Entwürfe</div>
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<div class="stand-kpi-sub" id="kpi-drafts-7d">— in 7 Tagen</div>
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</div>
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<div class="stand-kpi">
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<div class="stand-kpi-value" id="kpi-bookmarks">—</div>
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<div class="stand-kpi-label">Merklisten-Einträge</div>
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<div class="stand-kpi-sub">user-übergreifend</div>
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</div>
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</div>
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<!-- Score-Histogram -->
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<div class="stand-section">
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<h2>GWÖ-Score-Verteilung</h2>
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<div style="background:var(--ecg-card-bg);border:1px solid var(--ecg-border);border-radius:6px;padding:14px;">
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<canvas id="stand-score-chart" style="max-height:240px;"></canvas>
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</div>
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</div>
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<!-- Per-Bundesland -->
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<div class="stand-section">
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<h2>Bewertungen + Votes pro Bundesland</h2>
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<table class="stand-table">
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<thead><tr><th>BL</th><th>Bewertungen</th><th>Plenum-Votes</th></tr></thead>
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<tbody id="stand-bl-rows"></tbody>
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</table>
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</div>
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<!-- News-Quellen -->
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<div class="stand-section">
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<h2>News pro Quelle</h2>
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<table class="stand-table">
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<thead><tr><th>Quelle</th><th>Anzahl</th></tr></thead>
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<tbody id="stand-news-rows"></tbody>
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</table>
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</div>
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<div id="stand-meta" style="font-family:var(--font-mono);font-size:11px;opacity:0.5;margin-top:1.5rem;"></div>
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</div>
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{% endblock %}
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{% block body_scripts %}
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<script>
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let _scoreChart = null;
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function fmtN(n) {
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return (n == null) ? '—' : n.toLocaleString('de-DE');
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}
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async function loadStand() {
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try {
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const r = await fetch('/api/admin/stand');
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if (!r.ok) {
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document.getElementById('stand-loading').textContent = 'Fehler ' + r.status;
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return;
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}
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const d = await r.json();
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document.getElementById('stand-loading').style.display = 'none';
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document.getElementById('stand-content').style.display = '';
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// KPIs
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document.getElementById('kpi-ass').textContent = fmtN(d.assessments.total);
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document.getElementById('kpi-ass-7d').textContent = '+' + fmtN(d.assessments.last_7_days) + ' in 7 Tagen';
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document.getElementById('kpi-votes').textContent = fmtN(d.plenum_votes.total);
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document.getElementById('kpi-match').textContent = fmtN(d.match.with_assessment_and_vote);
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document.getElementById('kpi-orphans').textContent = fmtN(d.match.vote_orphans) + ' Vote-Orphans';
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document.getElementById('kpi-news').textContent = fmtN(d.news.total);
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document.getElementById('kpi-news-7d').textContent =
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'+' + fmtN(d.news.last_7_days) + ' in 7 Tagen, ' + fmtN(d.news.embedded) + ' embedded';
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document.getElementById('kpi-drafts').textContent = fmtN(d.presse_drafts.total);
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||||
document.getElementById('kpi-drafts-7d').textContent = '+' + fmtN(d.presse_drafts.last_7_days) + ' in 7 Tagen';
|
||||
document.getElementById('kpi-bookmarks').textContent = fmtN(d.bookmarks);
|
||||
|
||||
// Score-Histogram
|
||||
const dist = d.assessments.score_distribution || {};
|
||||
const buckets = [0,1,2,3,4,5,6,7,8,9,10];
|
||||
const values = buckets.map(b => dist[String(b)] || 0);
|
||||
const colors = buckets.map(b => {
|
||||
if (b <= 2) return 'rgba(200,30,30,0.6)';
|
||||
if (b <= 4) return 'rgba(247,148,29,0.6)';
|
||||
if (b <= 6) return 'rgba(150,150,150,0.5)';
|
||||
if (b <= 8) return 'rgba(136,158,51,0.6)';
|
||||
return 'rgba(0,157,165,0.7)';
|
||||
});
|
||||
if (_scoreChart) _scoreChart.destroy();
|
||||
_scoreChart = new Chart(document.getElementById('stand-score-chart'), {
|
||||
type: 'bar',
|
||||
data: { labels: buckets.map(b => b + '–' + (b+1)), datasets: [{
|
||||
label: 'Bewertungen',
|
||||
data: values,
|
||||
backgroundColor: colors,
|
||||
}]},
|
||||
options: {
|
||||
responsive: true,
|
||||
plugins: { legend: { display: false } },
|
||||
scales: {
|
||||
y: { beginAtZero: true, title: { display: true, text: 'Anzahl' } },
|
||||
x: { title: { display: true, text: 'GWÖ-Score-Bucket' } },
|
||||
},
|
||||
},
|
||||
});
|
||||
|
||||
// Per-BL-Tabelle
|
||||
const ass_bl = d.assessments.by_bundesland || {};
|
||||
const vote_bl = d.plenum_votes.by_bundesland || {};
|
||||
const bl_set = new Set([...Object.keys(ass_bl), ...Object.keys(vote_bl)]);
|
||||
const bl_rows = [...bl_set].sort();
|
||||
document.getElementById('stand-bl-rows').innerHTML = bl_rows.map(bl => `
|
||||
<tr>
|
||||
<td>${bl}</td>
|
||||
<td>${fmtN(ass_bl[bl] || 0)}</td>
|
||||
<td>${fmtN(vote_bl[bl] || 0)}</td>
|
||||
</tr>`).join('');
|
||||
|
||||
// News-Source-Tabelle
|
||||
const ns = d.news.by_source || {};
|
||||
document.getElementById('stand-news-rows').innerHTML =
|
||||
Object.entries(ns).sort((a, b) => b[1] - a[1]).map(([s, n]) => `
|
||||
<tr><td>${s}</td><td>${fmtN(n)}</td></tr>`).join('');
|
||||
|
||||
document.getElementById('stand-meta').textContent =
|
||||
'Aktualisiert: ' + new Date().toLocaleTimeString('de-DE');
|
||||
} catch (e) {
|
||||
document.getElementById('stand-loading').textContent = 'Fehler: ' + e;
|
||||
}
|
||||
}
|
||||
|
||||
loadStand();
|
||||
setInterval(loadStand, 30000);
|
||||
</script>
|
||||
{% endblock %}
|
||||
@ -665,10 +665,50 @@ async function showDraftFromData(d) {
|
||||
DS ${d.drucksache} (${d.bundesland}) · Bezug zu: <a href="${d.news_url}" target="_blank" rel="noopener" style="color:var(--ecg-teal);">${d.news_titel}</a>
|
||||
</div>` +
|
||||
actionRow +
|
||||
`<div style="white-space:pre-wrap;font-size:13px;line-height:1.5;">${d.body.replace(/</g, '<')}</div>`;
|
||||
`<div style="font-size:13px;line-height:1.6;">${renderPmBody(d.body)}</div>`;
|
||||
backdrop.style.display = 'flex';
|
||||
}
|
||||
|
||||
// Mini-Markdown-Renderer fuer PM-Body — interpretiert **bold**, *italic*,
|
||||
// __bold__, _italic_ + Listen + Paragraphen-Breaks. KEIN externer Markdown-
|
||||
// Parser noetig (kein dependency, schnell, isoliert testbar).
|
||||
function renderPmBody(body) {
|
||||
if (!body) return '';
|
||||
// 1. HTML escapen
|
||||
let s = body.replace(/&/g, '&').replace(/</g, '<').replace(/>/g, '>');
|
||||
// 2. **bold** + __bold__
|
||||
s = s.replace(/\*\*([^*\n]+?)\*\*/g, '<strong>$1</strong>');
|
||||
s = s.replace(/__([^_\n]+?)__/g, '<strong>$1</strong>');
|
||||
// 3. *italic* + _italic_ (vorsichtig — nur wenn nicht zw. Ziffern)
|
||||
s = s.replace(/(?<![*\w])\*([^*\n]+?)\*(?![*\w])/g, '<em>$1</em>');
|
||||
s = s.replace(/(?<![_\w])_([^_\n]+?)_(?![_\w])/g, '<em>$1</em>');
|
||||
// 4. Listen: "- " oder "* " am Zeilenanfang → Bullet-Punkte
|
||||
// (vorsichtig: Bindestrich mitten im Wort soll bleiben)
|
||||
const lines = s.split('\n');
|
||||
const out = [];
|
||||
let inList = false;
|
||||
for (const line of lines) {
|
||||
if (/^\s*[-*]\s+/.test(line)) {
|
||||
if (!inList) { out.push('<ul style="margin:0.5em 0;padding-left:1.4em;">'); inList = true; }
|
||||
out.push('<li>' + line.replace(/^\s*[-*]\s+/, '') + '</li>');
|
||||
} else {
|
||||
if (inList) { out.push('</ul>'); inList = false; }
|
||||
out.push(line);
|
||||
}
|
||||
}
|
||||
if (inList) out.push('</ul>');
|
||||
s = out.join('\n');
|
||||
// 5. Doppel-Newlines → </p><p>
|
||||
const paras = s.split(/\n\s*\n/);
|
||||
return paras.map(p => {
|
||||
const trimmed = p.trim();
|
||||
if (!trimmed) return '';
|
||||
// Wenn der Block schon mit Tag startet (z.B. <ul>), kein <p>-Wrap
|
||||
if (trimmed.startsWith('<')) return trimmed;
|
||||
return '<p style="margin:0 0 0.9em;">' + trimmed.replace(/\n/g, '<br>') + '</p>';
|
||||
}).filter(Boolean).join('\n');
|
||||
}
|
||||
|
||||
async function loadVersion(draftId) {
|
||||
try {
|
||||
const r = await fetch(`/api/aktuelle-themen/drafts/${draftId}`);
|
||||
|
||||
@ -890,15 +890,35 @@ window.v2ShowMatrixFieldInfo = function(field) {
|
||||
const list = document.getElementById('ad-news-list');
|
||||
if (!box || !list) return;
|
||||
try {
|
||||
const r = await fetch('/api/aktuelle-themen/news-fuer-antrag?drucksache='
|
||||
+ encodeURIComponent(ds)
|
||||
+ '&top_k=5&min_similarity=0.4&days=90');
|
||||
const data = await r.json();
|
||||
const matches = data.matches || [];
|
||||
if (!matches.length) {
|
||||
// Box bleibt unsichtbar, kein Stoerfaktor
|
||||
return;
|
||||
}
|
||||
// Parallel: News-Matches + Cluster-Map (fuer Cluster-Indicator)
|
||||
const [matchesResp, clusterResp] = await Promise.all([
|
||||
fetch('/api/aktuelle-themen/news-fuer-antrag?drucksache='
|
||||
+ encodeURIComponent(ds)
|
||||
+ '&top_k=5&min_similarity=0.4&days=90'),
|
||||
fetch('/api/aktuelle-themen/cluster?days=90&min_cluster_size=2'),
|
||||
]);
|
||||
const matchData = await matchesResp.json();
|
||||
const matches = matchData.matches || [];
|
||||
if (!matches.length) return; // Box bleibt unsichtbar
|
||||
|
||||
// Cluster-Lookup-Map: URL → {clusterIdx, size, otherTitles}
|
||||
let clusterByUrl = {};
|
||||
try {
|
||||
const clusterData = await clusterResp.json();
|
||||
(clusterData.clusters || []).forEach((c, i) => {
|
||||
(c.members || []).forEach(m => {
|
||||
clusterByUrl[m.url] = {
|
||||
size: c.size,
|
||||
tags: c.top_tags || [],
|
||||
others: (c.members || [])
|
||||
.filter(o => o.url !== m.url)
|
||||
.map(o => `${o.source}: ${o.titel}`)
|
||||
.slice(0, 5),
|
||||
};
|
||||
});
|
||||
});
|
||||
} catch (_) { /* clusters optional */ }
|
||||
|
||||
box.style.display = '';
|
||||
let html = '';
|
||||
for (const n of matches) {
|
||||
@ -909,10 +929,16 @@ window.v2ShowMatrixFieldInfo = function(field) {
|
||||
const summary = n.summary
|
||||
? '<p style="font-size:12px;margin:4px 0 8px;opacity:0.85;line-height:1.5;">' + n.summary + '</p>'
|
||||
: '';
|
||||
const clusterInfo = clusterByUrl[n.url];
|
||||
const clusterBadge = clusterInfo
|
||||
? '<span style="display:inline-block;padding:1px 7px;background:rgba(0,157,165,0.15);border-radius:11px;font-family:var(--font-mono);font-size:10px;margin-left:6px;color:var(--ecg-teal);" '
|
||||
+ 'title="' + clusterInfo.others.map(s => s.replace(/"/g, '"')).join(' • ') + '">'
|
||||
+ '🔗 Cluster (' + clusterInfo.size + ' News)</span>'
|
||||
: '';
|
||||
html += '<div style="border-bottom:1px dotted var(--ecg-border);padding:10px 0;">';
|
||||
html += '<div style="font-family:var(--font-mono);font-size:10px;opacity:0.6;margin-bottom:3px;">'
|
||||
+ d + ' · ' + n.source + (n.ressort ? ' / ' + n.ressort : '')
|
||||
+ ' · sim ' + n.similarity + '</div>';
|
||||
+ ' · sim ' + n.similarity + clusterBadge + '</div>';
|
||||
html += '<a href="' + n.url + '" target="_blank" rel="noopener" '
|
||||
+ 'style="color:var(--ecg-teal);text-decoration:none;font-weight:500;">'
|
||||
+ n.titel + '</a>';
|
||||
|
||||
@ -169,6 +169,7 @@ table.modal-table th { background: var(--ecg-bg-subtle); font-weight: 700; }
|
||||
<button class="auswert-tab active" role="tab" onclick="switchTab('bl-partei', this)">BL × Partei</button>
|
||||
<button class="auswert-tab" role="tab" onclick="switchTab('themen', this)">Thema × Fraktion</button>
|
||||
<button class="auswert-tab" role="tab" onclick="switchTab('stimmverhalten', this)">Stimmverhalten</button>
|
||||
<button class="auswert-tab" role="tab" onclick="switchTab('histogram', this)">Score-Verteilung</button>
|
||||
<button class="auswert-tab" role="tab" onclick="switchTab('cluster', this)">Cluster</button>
|
||||
</div>
|
||||
|
||||
@ -366,7 +367,19 @@ table.modal-table th { background: var(--ecg-bg-subtle); font-weight: 700; }
|
||||
<div id="sv-cross-bl-meta" class="meta-line"></div>
|
||||
</div>
|
||||
|
||||
<!-- Panel 4: Cluster-Link -->
|
||||
<!-- Panel 4: Score-Histogram -->
|
||||
<div class="auswert-panel" id="panel-histogram">
|
||||
<p style="font-size:11px;font-family:var(--font-mono);opacity:0.7;margin:0 0 0.5rem;">
|
||||
Verteilung der GWÖ-Scores (0–10) ueber alle Bewertungen — zeigt
|
||||
auf einen Blick, wo der Antrags-Pool inhaltlich liegt.
|
||||
</p>
|
||||
<div class="matrix-wrap" style="background:var(--ecg-card-bg);border:1px solid var(--ecg-border);border-radius:4px;padding:14px;">
|
||||
<canvas id="hist-chart" style="max-height:340px;"></canvas>
|
||||
</div>
|
||||
<div id="hist-meta" style="font-family:var(--font-mono);font-size:11px;opacity:0.6;margin:8px 0 1.5rem;"></div>
|
||||
</div>
|
||||
|
||||
<!-- Panel 5: Cluster-Link -->
|
||||
<div class="auswert-panel" id="panel-cluster">
|
||||
<div class="v2-kasten outline-blue">
|
||||
<h4>Cluster-Ansicht</h4>
|
||||
@ -397,7 +410,8 @@ table.modal-table th { background: var(--ecg-bg-subtle); font-weight: 700; }
|
||||
|
||||
{% block body_scripts %}
|
||||
<script>
|
||||
let _tabLoaded = { 'bl-partei': false, 'themen': false, 'stimmverhalten': false };
|
||||
let _tabLoaded = { 'bl-partei': false, 'themen': false, 'stimmverhalten': false, 'histogram': false };
|
||||
let _histChart = null;
|
||||
let _svCharts = { index: null, heuchelei: null, empfehlung: null, crossBl: null, zeitreihe: null };
|
||||
let _svMatrixAxis = 'werte'; // 'werte' or 'gruppen'
|
||||
|
||||
@ -443,6 +457,54 @@ function switchTab(id, btn) {
|
||||
loadStimmverhalten();
|
||||
_tabLoaded.stimmverhalten = true;
|
||||
}
|
||||
if (id === 'histogram' && !_tabLoaded.histogram) {
|
||||
loadHistogram();
|
||||
_tabLoaded.histogram = true;
|
||||
}
|
||||
}
|
||||
|
||||
async function loadHistogram() {
|
||||
const blRaw = (window.v2GetGlobalBl && window.v2GetGlobalBl()) || 'ALL';
|
||||
const bl = (blRaw === 'ALL') ? '' : blRaw;
|
||||
const wp = document.getElementById('wp-filter') ? document.getElementById('wp-filter').value : '';
|
||||
const meta = document.getElementById('hist-meta');
|
||||
let url = '/api/auswertungen/score-histogram';
|
||||
const params = [];
|
||||
if (bl) params.push('bundesland=' + encodeURIComponent(bl));
|
||||
if (wp) params.push('wahlperiode=' + encodeURIComponent(wp));
|
||||
if (params.length) url += '?' + params.join('&');
|
||||
try {
|
||||
const r = await fetch(url);
|
||||
const data = await r.json();
|
||||
if (_histChart) _histChart.destroy();
|
||||
const labels = data.buckets.map(b => `${b.score_min}–${b.score_max}`);
|
||||
const values = data.buckets.map(b => b.count);
|
||||
const colors = data.buckets.map(b => {
|
||||
const v = b.score_min;
|
||||
if (v <= 2) return 'rgba(200,30,30,0.6)';
|
||||
if (v <= 4) return 'rgba(247,148,29,0.6)';
|
||||
if (v <= 6) return 'rgba(150,150,150,0.5)';
|
||||
if (v <= 8) return 'rgba(136,158,51,0.6)';
|
||||
return 'rgba(0,157,165,0.7)';
|
||||
});
|
||||
_histChart = new Chart(document.getElementById('hist-chart'), {
|
||||
type: 'bar',
|
||||
data: { labels: labels, datasets: [{ label: 'Bewertungen', data: values, backgroundColor: colors }] },
|
||||
options: {
|
||||
responsive: true,
|
||||
plugins: { legend: { display: false } },
|
||||
scales: {
|
||||
y: { beginAtZero: true, title: { display: true, text: 'Anzahl Bewertungen' } },
|
||||
x: { title: { display: true, text: 'GWÖ-Score-Bucket' } },
|
||||
},
|
||||
},
|
||||
});
|
||||
meta.textContent = `${data.total} Bewertungen` +
|
||||
(data.filter.bundesland ? ` · BL: ${data.filter.bundesland}` : '') +
|
||||
(data.filter.wahlperiode ? ` · WP: ${data.filter.wahlperiode}` : '');
|
||||
} catch (e) {
|
||||
meta.textContent = 'Fehler: ' + e;
|
||||
}
|
||||
}
|
||||
|
||||
// Bei globalem BL-Wechsel aktive Panels neu laden — ABER NICHT
|
||||
@ -452,6 +514,7 @@ window.addEventListener('v2-bl-changed', function () {
|
||||
if (!activePanel) return;
|
||||
if (activePanel.id === 'panel-bl-partei') loadBlMatrix();
|
||||
if (activePanel.id === 'panel-themen') loadThemenMatrix();
|
||||
if (activePanel.id === 'panel-histogram') loadHistogram();
|
||||
// Stimmverhalten reagiert NICHT auf globalen BL-Filter — eigener Selector.
|
||||
});
|
||||
|
||||
@ -688,13 +751,58 @@ async function bulkRateOrphans() {
|
||||
}
|
||||
const data = await r.json();
|
||||
const skip = (data.skipped || []).length;
|
||||
const expectedJobs = (data.jobs || []).length;
|
||||
result.innerHTML = `${data.enqueued} enqueued${skip ? `, ${skip} skipped` : ''} — <a href="/v2/admin/queue" style="color:var(--ecg-teal);">Queue ansehen →</a>`;
|
||||
setTimeout(() => loadVoteOrphansBanner(bl), 800);
|
||||
// Live-Polling: Queue-Status prüfen alle 4s, bis pending=0 oder
|
||||
// 5 Min vorbei sind. Banner danach neu laden.
|
||||
pollQueueUntilDrained(bl, expectedJobs, result);
|
||||
} catch (e) {
|
||||
result.textContent = 'Fehler: ' + e;
|
||||
}
|
||||
}
|
||||
|
||||
async function pollQueueUntilDrained(bl, expectedJobs, resultEl) {
|
||||
const startTs = Date.now();
|
||||
const maxMs = 5 * 60 * 1000;
|
||||
let lastPending = -1;
|
||||
while (Date.now() - startTs < maxMs) {
|
||||
await new Promise(r => setTimeout(r, 4000));
|
||||
try {
|
||||
const q = await fetch('/api/queue/status');
|
||||
const data = await q.json();
|
||||
const pending = data.pending != null ? data.pending : 0;
|
||||
const completed = data.processed_total || 0;
|
||||
// Wenn das Banner das Tab gewechselt hat, abbrechen
|
||||
if (!document.getElementById('panel-stimmverhalten').classList.contains('active')) {
|
||||
// Stimmverhalten-Tab geschlossen, hör auf zu pollen
|
||||
return;
|
||||
}
|
||||
if (resultEl) {
|
||||
const elapsed = Math.round((Date.now() - startTs) / 1000);
|
||||
resultEl.innerHTML =
|
||||
`${expectedJobs} enqueued · pending: ${pending} · ` +
|
||||
`${elapsed}s gewartet — <a href="/v2/admin/queue" style="color:var(--ecg-teal);">Queue ansehen →</a>`;
|
||||
}
|
||||
if (pending === 0 && lastPending === 0) {
|
||||
// Zwei Polls in Folge mit pending=0 → fertig
|
||||
loadVoteOrphansBanner(bl);
|
||||
// Auch die anderen Stimmverhalten-Charts neu laden
|
||||
loadStimmverhalten();
|
||||
if (resultEl) resultEl.textContent =
|
||||
`Fertig — Bewertungen ${expectedJobs} verarbeitet, Banner aktualisiert`;
|
||||
return;
|
||||
}
|
||||
lastPending = pending;
|
||||
} catch (e) {
|
||||
// Ignore, retry
|
||||
}
|
||||
}
|
||||
// Timeout
|
||||
if (resultEl) resultEl.textContent =
|
||||
`Polling-Timeout (5 Min) — Banner wird normal aktualisiert`;
|
||||
loadVoteOrphansBanner(bl);
|
||||
}
|
||||
|
||||
function downloadStimmverhaltenCsv() {
|
||||
const bl = svGetBl();
|
||||
const exclude = document.getElementById('sv-exclude-antragsteller').checked ? '1' : '0';
|
||||
|
||||
@ -10,12 +10,19 @@ Reuse:
|
||||
- Beide Tabellen nutzen denselben Embedding-Modell-Vektorraum (qwen v4),
|
||||
daher direkter Cross-Vergleich moeglich
|
||||
- Filter ueber ``embedding_model``-Spalte, falls Migration laueft
|
||||
|
||||
**Performance-Cache:** ``aggregate_top_themen`` und ``aggregate_news_cluster``
|
||||
sind teuer (cosine über ~300 News × ~100 Bewertungen = 30k Ops). Daher
|
||||
TTL-Cache: gleiche Filter-Tuples werden 60 s lang aus Memory geliefert,
|
||||
danach neu berechnet. Cache wird beim Modul-Import geleert (keine
|
||||
persistente Stale-Gefahr nach Deploy).
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import logging
|
||||
import sqlite3
|
||||
import time
|
||||
from collections import defaultdict
|
||||
from datetime import datetime, timezone
|
||||
from pathlib import Path
|
||||
@ -23,6 +30,30 @@ from typing import Optional
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
_CACHE: dict[tuple, tuple[float, dict]] = {}
|
||||
_CACHE_TTL_SECONDS = 60
|
||||
|
||||
|
||||
def _cache_get(key: tuple) -> Optional[dict]:
|
||||
entry = _CACHE.get(key)
|
||||
if entry is None:
|
||||
return None
|
||||
expires_at, value = entry
|
||||
if time.time() > expires_at:
|
||||
_CACHE.pop(key, None)
|
||||
return None
|
||||
return value
|
||||
|
||||
|
||||
def _cache_set(key: tuple, value: dict) -> None:
|
||||
_CACHE[key] = (time.time() + _CACHE_TTL_SECONDS, value)
|
||||
|
||||
|
||||
def cache_clear() -> None:
|
||||
"""Leert den TTL-Cache. Aufruf z.B. nach News-Aggregator-Lauf,
|
||||
damit neue News sofort sichtbar werden."""
|
||||
_CACHE.clear()
|
||||
|
||||
|
||||
def _load_embeddings(
|
||||
db_path: Path,
|
||||
@ -286,6 +317,15 @@ def aggregate_top_themen(
|
||||
"filter": {...}
|
||||
}``
|
||||
"""
|
||||
# Cache-Key (db_path nur wenn Test-Override; sonst per Default)
|
||||
cache_key = (
|
||||
"top_themen", days_window, top_k, round(min_similarity, 3),
|
||||
matches_per_news, only_relevant, single_date, str(db_path or ""),
|
||||
)
|
||||
cached = _cache_get(cache_key)
|
||||
if cached is not None:
|
||||
return cached
|
||||
|
||||
from .config import settings
|
||||
from . import embeddings as emb
|
||||
|
||||
@ -392,7 +432,7 @@ def aggregate_top_themen(
|
||||
reverse=True,
|
||||
)
|
||||
|
||||
return {
|
||||
result = {
|
||||
"buckets": buckets,
|
||||
"n_total_news": len(news_rows),
|
||||
"n_in_window": n_in_window,
|
||||
@ -406,6 +446,8 @@ def aggregate_top_themen(
|
||||
"single_date": single_date,
|
||||
},
|
||||
}
|
||||
_cache_set(cache_key, result)
|
||||
return result
|
||||
|
||||
|
||||
def aggregate_themen_zeitreihe(
|
||||
@ -472,6 +514,8 @@ def aggregate_news_cluster(
|
||||
) -> dict:
|
||||
"""News-zu-News-Clustering ueber Embeddings.
|
||||
|
||||
Cached (60s TTL).
|
||||
|
||||
Greedy: jede ungeclusterte News wird Cluster-Seed, alle anderen mit
|
||||
cosine >= ``intra_threshold`` werden eingeschlossen. Cluster mit
|
||||
weniger als ``min_cluster_size`` News werden verworfen (nicht als
|
||||
@ -479,6 +523,14 @@ def aggregate_news_cluster(
|
||||
|
||||
Pro Cluster: zentralster Antrag-Match aus den GWÖ-bewerteten Antraegen.
|
||||
"""
|
||||
cache_key = (
|
||||
"cluster", days_window, round(intra_threshold, 3),
|
||||
round(antrag_threshold, 3), min_cluster_size, str(db_path or ""),
|
||||
)
|
||||
cached = _cache_get(cache_key)
|
||||
if cached is not None:
|
||||
return cached
|
||||
|
||||
from .config import settings
|
||||
from . import embeddings as emb
|
||||
|
||||
@ -592,7 +644,7 @@ def aggregate_news_cluster(
|
||||
),
|
||||
reverse=True,
|
||||
)
|
||||
return {
|
||||
result = {
|
||||
"clusters": out_clusters,
|
||||
"n_total_news": len(fresh),
|
||||
"filter": {
|
||||
@ -602,6 +654,8 @@ def aggregate_news_cluster(
|
||||
"min_cluster_size": min_cluster_size,
|
||||
},
|
||||
}
|
||||
_cache_set(cache_key, result)
|
||||
return result
|
||||
|
||||
|
||||
def aggregate_top_antraege_with_news(
|
||||
|
||||
@ -14,6 +14,7 @@ from app.themen_matching import (
|
||||
aggregate_themen_zeitreihe,
|
||||
aggregate_top_antraege_with_news,
|
||||
aggregate_top_themen,
|
||||
cache_clear,
|
||||
compute_relevance,
|
||||
find_anträge_for_news,
|
||||
find_news_for_antrag,
|
||||
@ -452,3 +453,42 @@ class TestTopAntraegeWithNews:
|
||||
elif first_without == len(result["antraege"]):
|
||||
first_without = i
|
||||
assert last_with_news < first_without
|
||||
|
||||
|
||||
# ─────────────────────────────────────────────────────────────────────────────
|
||||
# TTL-Cache (Performance #170 followup)
|
||||
# ─────────────────────────────────────────────────────────────────────────────
|
||||
|
||||
|
||||
class TestPerformanceCache:
|
||||
def test_top_themen_cache_hit_returns_same_object(self, populated_db):
|
||||
"""Zweiter Call mit gleichen Args sollte den gleichen dict liefern."""
|
||||
cache_clear()
|
||||
a = aggregate_top_themen(db_path=populated_db, min_similarity=0.5)
|
||||
b = aggregate_top_themen(db_path=populated_db, min_similarity=0.5)
|
||||
# Cache liefert dasselbe Objekt (identity check)
|
||||
assert a is b
|
||||
|
||||
def test_top_themen_cache_miss_different_args(self, populated_db):
|
||||
"""Andere Args → neuer Eintrag, anderer dict."""
|
||||
cache_clear()
|
||||
a = aggregate_top_themen(db_path=populated_db, min_similarity=0.5)
|
||||
b = aggregate_top_themen(db_path=populated_db, min_similarity=0.6)
|
||||
# Different filter values → different cache-keys
|
||||
assert a is not b
|
||||
|
||||
def test_cache_clear_invalidates(self, populated_db):
|
||||
cache_clear()
|
||||
a = aggregate_top_themen(db_path=populated_db, min_similarity=0.5)
|
||||
cache_clear()
|
||||
b = aggregate_top_themen(db_path=populated_db, min_similarity=0.5)
|
||||
# Nach clear: neuer Aufruf gibt neues Objekt zurueck
|
||||
assert a is not b
|
||||
# Inhaltlich identisch
|
||||
assert len(a["buckets"]) == len(b["buckets"])
|
||||
|
||||
def test_cluster_cached_too(self, populated_db):
|
||||
cache_clear()
|
||||
a = aggregate_news_cluster(db_path=populated_db, min_cluster_size=1)
|
||||
b = aggregate_news_cluster(db_path=populated_db, min_cluster_size=1)
|
||||
assert a is b
|
||||
|
||||
Loading…
Reference in New Issue
Block a user