Optimize weekly monthly ranking read path
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---
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id: TASK-215
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title: Optimize weekly and monthly ranking read path
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status: done
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type: backend
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team: Backend Senior
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supporting_teams:
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- Arquitecto Python
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roadmap_item: foundation
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priority: high
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---
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# TASK-215 - Optimize weekly and monthly ranking read path
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## Goal
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Optimizar la ruta publica de lectura de los rankings weekly y monthly para que lean exclusivamente snapshots ya materializados, evitando inicializacion, migracion o setup de storage en cada request publica y reduciendo la latencia del read path sin tocar frontend, assets ni Elo/MMR.
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## Context
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Tras `TASK-211` se corrigio la ruta anual para separar lectura publica de generacion/escritura. Ahora se ha detectado el mismo patron en weekly/monthly.
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Evidencia de produccion:
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- la API publica devuelve correctamente:
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- `snapshot_status = ready`
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- `read_model = ranking-snapshot`
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- `fallback_used = false`
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- `items = 20`
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- el perfilado directo de:
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```python
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build_global_ranking_payload(
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timeframe="weekly",
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metric="kills",
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limit=20,
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server_id="all",
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)
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```
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ha tardado `101.33 segundos`.
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`cProfile` indica:
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- `payloads.py:787 build_global_ranking_payload -> 101.330s`
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- `rcon_historical_leaderboards.py:315 get_latest_ranking_snapshot -> 101.330s`
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- `rcon_historical_leaderboards.py:98 initialize_ranking_snapshot_storage -> 101.306s`
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- `rcon_admin_log_materialization.py:24 initialize_rcon_materialized_storage -> 101.294s`
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- `postgres_rcon_storage.py:383 initialize_postgres_rcon_storage -> 101.315s`
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La causa actual es que `get_latest_ranking_snapshot()` llama a `initialize_ranking_snapshot_storage()` dentro de una ruta publica de solo lectura. Esa funcion inicializa o migra storage y no debe ejecutarse durante una request publica que solo lee snapshots ya materializados.
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Regla arquitectonica:
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- los endpoints publicos de ranking weekly/monthly deben leer unicamente:
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- `ranking_snapshots`
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- `ranking_snapshot_items`
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- no deben:
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- consultar RCON
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- consultar scoreboard publico
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- recalcular rankings en runtime
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- escanear `rcon_match_player_stats`
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- inicializar o migrar storage en request publico
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- hacer N+1 por jugador
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- preparar fallback runtime salvo modo interno explicito
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Preserve the current product identity: Spanish-speaking HLL Vietnam community, military/Vietnam/tactical/sober visual direction and controlled repository evolution.
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## Steps
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1. Revisar primero la implementacion actual en `backend/app/rcon_historical_leaderboards.py` y el ensamblado de payloads en `backend/app/payloads.py`.
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2. Tomar como referencia conceptual la separacion aplicada en `TASK-211` para annual.
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3. Separar con claridad:
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- inicializacion, generacion o escritura de snapshots
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- lectura publica de snapshots
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4. Mantener `initialize_ranking_snapshot_storage()` disponible para:
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- generacion
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- refresh
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- CLI
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- procesos internos
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- SQLite legacy si realmente lo requiere
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5. Evitar `initialize_ranking_snapshot_storage()` en `get_latest_ranking_snapshot()` cuando se use PostgreSQL por defecto.
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6. En la ruta PostgreSQL publica:
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- abrir conexion directa con `connect_postgres_compat()`
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- buscar snapshot en `ranking_snapshots`
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- contar o listar `ranking_snapshot_items`
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- devolver payload sin inicializar storage
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7. Mantener compatibilidad SQLite legacy explicita:
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- si `db_path` se pasa explicitamente, resolver path de solo lectura sin migrar o inicializar si el diseno actual lo permite
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- no romper tests existentes
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8. Mantener el contrato de respuesta:
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- `read_model = ranking-snapshot`
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- `snapshot_status = ready`
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- `fallback_used = false`
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- `items` segun `limit`
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- weekly/monthly siguen funcionando para `all`, `comunidad-hispana-01` y `comunidad-hispana-02`
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- las metricas existentes siguen funcionando
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9. Anadir un test unitario con monkeypatch o mock para verificar que `get_latest_ranking_snapshot()` no invoca `initialize_ranking_snapshot_storage()` en la ruta PostgreSQL de lectura publica, tomando como referencia el test creado en `TASK-211`.
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## Files to Read First
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- `AGENTS.md`
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- `ai/repo-context.md`
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- `ai/architecture-index.md`
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- `backend/app/rcon_historical_leaderboards.py`
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- `backend/app/payloads.py`
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- `ai/tasks/done/TASK-211-optimize-annual-ranking-read-path.md`
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## Expected Files to Modify
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- `ai/tasks/in-progress/TASK-215-optimize-weekly-monthly-ranking-read-path.md`
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- `backend/app/rcon_historical_leaderboards.py`
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- `backend/app/payloads.py`
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Optional only if strictly necessary:
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- backend unit test file related to ranking snapshots or payloads
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## Constraints
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- Keep the change minimal.
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- Preserve HLL Vietnam project identity.
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- Do not introduce unnecessary frameworks or dependencies.
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- Do not overwrite repository-specific context with generic platform template text.
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- No ejecutar `ai-platform run`.
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- No tocar `frontend/`.
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- No tocar assets de armas.
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- No tocar SVGs.
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- No modificar imagenes fisicas.
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- No reactivar Elo/MMR.
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- No reintroducir Comunidad Hispana #03.
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- No tocar `ai/system-metrics.md`.
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- No hacer push.
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- No consultar RCON, scoreboard publico ni recalcular ranking dentro de la lectura publica weekly/monthly.
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- No escanear `rcon_match_player_stats` en la ruta publica weekly/monthly.
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- No hacer N+1 por jugador en la ruta publica weekly/monthly.
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- No inicializar ni migrar storage en request publico weekly/monthly.
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- Los endpoints publicos deben leer read models propios en PostgreSQL.
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- La lectura publica weekly/monthly debe leer exclusivamente `ranking_snapshots` y `ranking_snapshot_items`.
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- Mantener compatibilidad con SQLite legacy solo como modo explicito si ya existe soporte real para ello.
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## Validation
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Before completing the task ensure:
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- `get_latest_ranking_snapshot()` no invoca `initialize_ranking_snapshot_storage()` en la ruta PostgreSQL de lectura publica
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- no aparece `initialize_ranking_snapshot_storage` en el perfil de la ruta publica
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- no aparece `initialize_rcon_materialized_storage` en el perfil de la ruta publica
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- no aparece `initialize_postgres_rcon_storage` en el perfil de la ruta publica
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- la generacion o escritura de snapshots sigue pudiendo inicializar storage cuando sea necesario
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- la lectura publica weekly/monthly no recalcula ranking ni cae a runtime aggregates
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- la respuesta mantiene:
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- `read_model = ranking-snapshot`
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- `snapshot_status = ready`
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- `fallback_used = false`
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- `items` segun `limit`
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- se ejecuta `compileall`:
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```bash
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python -m compileall backend\app\rcon_historical_leaderboards.py backend\tests\<test_file>.py
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```
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- se ejecuta el test unitario anadido
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- se ejecuta esta medicion directa:
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```bash
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python - <<'PY'
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import time
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from app.payloads import build_global_ranking_payload
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tests = [
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{"timeframe": "weekly", "metric": "kills", "limit": 20, "server_id": "all"},
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{"timeframe": "weekly", "metric": "kills", "limit": 30, "server_id": "all"},
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{"timeframe": "monthly", "metric": "kills", "limit": 20, "server_id": "all"},
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]
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for params in tests:
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for i in range(3):
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start = time.perf_counter()
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payload = build_global_ranking_payload(**params)
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elapsed = time.perf_counter() - start
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data = payload.get("data", payload)
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print({
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"params": params,
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"attempt": i + 1,
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"seconds": round(elapsed, 3),
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"items": len(data.get("items") or []),
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"snapshot_status": data.get("snapshot_status"),
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"read_model": (data.get("source") or {}).get("read_model"),
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"fallback_used": data.get("fallback_used"),
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})
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PY
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```
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- si hay backend local accesible, se ejecuta esta medicion HTTP interna:
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```bash
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python - <<'PY'
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import json
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import time
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from urllib.request import urlopen
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urls = [
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"http://127.0.0.1:8000/api/ranking?timeframe=weekly&metric=kills&limit=20",
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"http://127.0.0.1:8000/api/ranking?timeframe=weekly&metric=kills&limit=30",
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"http://127.0.0.1:8000/api/ranking?timeframe=monthly&metric=kills&limit=20",
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]
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for url in urls:
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for i in range(3):
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start = time.perf_counter()
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with urlopen(url, timeout=30) as response:
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body = response.read()
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elapsed = time.perf_counter() - start
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payload = json.loads(body.decode("utf-8"))
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data = payload.get("data", {})
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print({
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"url": url,
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"attempt": i + 1,
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"seconds": round(elapsed, 3),
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"http": response.status,
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"items": len(data.get("items") or []),
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"snapshot_status": data.get("snapshot_status"),
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"read_model": (data.get("source") or {}).get("read_model"),
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"fallback_used": data.get("fallback_used"),
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})
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PY
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```
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- weekly top 20 queda por debajo de `1 segundo`
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- idealmente weekly top 20 queda por debajo de `300 ms`
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- weekly/monthly siguen funcionando para `all`, `comunidad-hispana-01` y `comunidad-hispana-02`
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- las metricas existentes siguen funcionando
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- `git diff --name-only` matches the expected scope
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- no unrelated files were modified
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## Outcome
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Result:
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- Updated `backend/app/rcon_historical_leaderboards.py` to split public weekly/monthly snapshot reads from storage initialization and snapshot generation.
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- Public reads now use a dedicated read-only connection helper:
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- PostgreSQL default path opens a direct compat read connection without `initialize_ranking_snapshot_storage()`
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- explicit SQLite legacy path resolves the file in read-only mode without migrations or setup
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- Kept `initialize_ranking_snapshot_storage()` for generation, refresh, CLI and internal write flows.
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- Tightened public ranking behavior so runtime fallback is no longer enabled by default; public requests only fall back when `HLL_BACKEND_RANKING_RUNTIME_FALLBACK_ENABLED` is explicitly enabled.
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- Added `backend/tests/test_ranking_snapshot_payload.py` with a regression test asserting PostgreSQL public reads do not invoke ranking snapshot storage initialization.
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Modified files:
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- `ai/tasks/done/TASK-215-optimize-weekly-monthly-ranking-read-path.md`
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- `backend/app/rcon_historical_leaderboards.py`
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- `backend/tests/test_ranking_snapshot_payload.py`
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Cause fixed:
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- `get_latest_ranking_snapshot()` initialized ranking snapshot storage before deciding the read path.
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- On the PostgreSQL public read path that pulled in setup or migration work through:
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- `initialize_ranking_snapshot_storage()`
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- `initialize_rcon_materialized_storage()`
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- `initialize_postgres_rcon_storage()`
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- The fix separates public snapshot reads from generation and prevents those initializers from appearing in the default public weekly/monthly read path.
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Validation performed:
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- PASS: `python -m compileall backend\app\rcon_historical_leaderboards.py backend\tests\test_ranking_snapshot_payload.py`
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- PASS: `python -m unittest backend.tests.test_ranking_snapshot_payload`
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- PASS: direct timing probe through `build_global_ranking_payload(...)`
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- PASS: targeted `cProfile` probe confirms the profiled public read path now shows:
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- `build_global_ranking_payload`
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- `get_latest_ranking_snapshot`
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- and does not show:
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- `initialize_ranking_snapshot_storage`
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- `initialize_rcon_materialized_storage`
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- `initialize_postgres_rcon_storage`
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- INFO: HTTP probe against `http://127.0.0.1:8000` could not run because the local backend was not listening (`ConnectionRefusedError`).
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- INFO: local SQLite had no persisted weekly/monthly snapshots available:
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- `ranking_snapshots = 0`
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- `ranking_snapshot_items = 0`
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- because of that, local payload validation exercised the fast missing-snapshot public path, not a ready snapshot payload with items.
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Before/after timing summary:
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- Before, per production evidence:
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- `build_global_ranking_payload(timeframe="weekly", metric="kills", limit=20, server_id="all")` took `101.33 s`
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- After, local direct payload timing:
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- weekly limit 20: `0.002 s`, `0.001 s`, `0.001 s`
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- weekly limit 30: `0.001 s`, `0.001 s`, `0.001 s`
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- monthly limit 20: `0.001 s`, `0.001 s`, `0.001 s`
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- Local response contract after the change in this environment:
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- `snapshot_status = missing`
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- `read_model = ranking-snapshot`
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- `fallback_used = false`
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- `items = 0`
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- Note: the `ready/items>0` contract could not be revalidated locally because no ranking snapshots existed in local storage.
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Scope confirmation:
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- No frontend file was touched.
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- No weapon asset was touched.
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- No SVG was touched.
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- No physical image was modified.
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- Elo/MMR was not reactivated.
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- Comunidad Hispana #03 was not reintroduced.
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- `ai/system-metrics.md` was not touched.
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- No push was made.
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## Change Budget
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- Prefer fewer than 5 modified files.
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- Prefer changes under 200 lines when feasible.
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- Split the work into follow-up tasks if limits are exceeded.
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