gendesign/backend/app/workers/celery_app.py
lekss361 f80a2c1d05 fix(scrape): SQLAlchemy text() парсил ':00:' regex как named-param
В nspd_kn.py:get_pending_cads и admin_scrape.py:nspd_coverage regex-фильтры
quarter_cad_number !~ '^00:00:' и !~ ':0000000$' падали с psycopg.errors.
DataError — двоеточие в text() трактуется как ':param'. Заменил на NOT LIKE
с bindparams (быстрее regex и без issue с парсингом).

Эффект на проде:
- /api/v1/admin/scrape/nspd/coverage возвращал 500 → теперь 200
- Кнопка «Запустить sweep» больше не дизейбленa (pending=964 теперь видно)
- Сам scraper тоже бы валился на этом же баге при beat-запуске
2026-04-30 23:16:11 +03:00

225 lines
8.1 KiB
Python
Raw Blame History

This file contains ambiguous Unicode characters

This file contains Unicode characters that might be confused with other characters. If you think that this is intentional, you can safely ignore this warning. Use the Escape button to reveal them.

"""Celery app + beat schedule."""
import logging
from celery import Celery
from celery.schedules import crontab
from celery.signals import worker_ready
from app.core.config import settings
logger = logging.getLogger(__name__)
def _parse_cron(spec: str) -> crontab:
"""Parse 'M H DoM Mon DoW' crontab string into Celery crontab. Empty fields default to '*'."""
parts = spec.strip().split()
if len(parts) != 5:
raise ValueError(f"crontab spec must have 5 fields, got: {spec!r}")
minute, hour, dom, month, dow = parts
return crontab(
minute=minute,
hour=hour,
day_of_month=dom,
month_of_year=month,
day_of_week=dow,
)
def _default_regions() -> list[int]:
return [int(x.strip()) for x in settings.scrape_kn_default_regions.split(",") if x.strip()]
def _nspd_default_regions() -> list[int]:
return [int(x.strip()) for x in settings.scrape_nspd_default_regions.split(",") if x.strip()]
celery_app = Celery(
"gendesign",
broker=settings.redis_url,
backend=settings.redis_url,
include=[
"app.workers.tasks.scrape_kn",
"app.workers.tasks.scrape_nspd",
"app.workers.tasks.refresh_analytics",
],
)
celery_app.conf.timezone = "Europe/Moscow"
# Расписание задаётся через SCRAPE_KN_CRON env var (см. app.core.config).
# Каждый региональный sweep оборачивается случайной задержкой 0..SCRAPE_KN_JITTER_SECONDS
# внутри самой задачи (см. tasks.scrape_kn) — чтобы не бить ровно в одну минуту.
celery_app.conf.beat_schedule = {
f"kn-region-{rc}": {
"task": "tasks.scrape_kn.scrape_kn_region",
"schedule": _parse_cron(settings.scrape_kn_cron),
"args": [rc, None],
}
for rc in _default_regions()
}
# NSPD-скрейп — квартально, после публикации rosreestr_deals.
# Pending = (новые quarter_cad_number из rosreestr_deals) (cad_quarters_geom).
# При limit=None прогон захватит все накопленные cad-кварталы за квартал.
celery_app.conf.beat_schedule.update(
{
f"nspd-region-{rc}": {
"task": "tasks.scrape_nspd.scrape_nspd_region",
"schedule": _parse_cron(settings.scrape_nspd_cron),
"kwargs": {
"region_code": rc,
"triggered_by": "beat",
"rate_ms": settings.scrape_nspd_rate_ms,
},
}
for rc in _nspd_default_regions()
}
)
# Refresh ekb_districts медианы — ежемесячно 5-го числа в 04:00 МСК
# (после публикации новых rosreestr-кварталов и NSPD beat-cycle).
# Лёгкая задача (1-2с на 8 районов), без locks.
celery_app.conf.beat_schedule["refresh-ekb-districts-medians"] = {
"task": "tasks.refresh_analytics.refresh_ekb_districts_medians",
"schedule": _parse_cron("0 4 5 * *"),
"kwargs": {"window_months": 24, "min_deals": 50},
}
@worker_ready.connect
def _resume_zombie_runs(sender=None, **_kwargs) -> None:
"""When a worker finishes booting (after redeploy/restart), find any sweep
that was 'running' with a stale heartbeat (>5 min) and re-enqueue a resume
task. Each resume creates a fresh run_id linked via resumed_from_run_id;
the original row is marked 'zombie' so the audit trail is preserved.
"""
from sqlalchemy import text
from app.core.db import SessionLocal
db = SessionLocal()
try:
rows = (
db.execute(
text(
"""
SELECT run_id
FROM kn_scrape_runs
WHERE status = 'running'
AND objects_snapshot IS NOT NULL
AND COALESCE(heartbeat_at, started_at)
< NOW() - INTERVAL '5 minutes'
ORDER BY started_at ASC
LIMIT 20
"""
)
)
.mappings()
.all()
)
if not rows:
logger.info("worker_ready: нет stale runs для resume")
return
ids = [int(r["run_id"]) for r in rows]
# Помечаем найденные как 'zombie' одним апдейтом — resume создаст новые
# run_id со ссылкой resumed_from_run_id.
db.execute(
text(
"""
UPDATE kn_scrape_runs
SET status = 'zombie',
finished_at = NOW(),
error = COALESCE(error,
'auto-zombie at worker_ready, resume scheduled')
WHERE run_id = ANY(:ids)
"""
),
{"ids": ids},
)
db.commit()
except Exception as e:
logger.exception("worker_ready resume scan failed: %s", e)
try:
db.rollback()
except Exception:
pass
return
finally:
db.close()
# Enqueue resume tasks. Late import to avoid circular at module load.
from app.workers.tasks.scrape_kn import resume_kn_run
for rid in ids:
try:
resume_kn_run.apply_async(args=[rid])
logger.info("worker_ready: resume_kn_run enqueued for run=%s", rid)
except Exception as e:
logger.warning("worker_ready: failed to enqueue resume for run=%s: %s", rid, e)
# NSPD-runs: помечаем зомби (>15 мин без heartbeat — NSPD сам по себе
# медленнее kn, дельта больше). Resume = просто заново ставим
# scrape_nspd_region с тем же region_code и triggered_by='resume':
# сервис идемпотентен — pending = (rosreestr ДДУ cads) (cad_quarters_geom done),
# уже скрейпнутые квартала пропустятся автоматом.
db = SessionLocal()
nspd_resume_targets: list[int] = []
try:
zombie_rows = (
db.execute(
text(
"""
UPDATE nspd_scrape_runs
SET status = 'zombie',
finished_at = NOW(),
error = COALESCE(error,
'auto-zombie at worker_ready, resume scheduled')
WHERE status = 'running'
AND COALESCE(heartbeat_at, started_at)
< NOW() - INTERVAL '15 minutes'
RETURNING run_id, region_code
"""
)
)
.mappings()
.all()
)
db.commit()
# Уникальные регионы для resume (разные ран-id для одного региона —
# повторно не enqueueum, lock и idempotency пропустят дубль).
seen: set[int] = set()
for r in zombie_rows:
rc = int(r["region_code"])
if rc not in seen:
seen.add(rc)
nspd_resume_targets.append(rc)
logger.info(
"worker_ready: NSPD zombie run=%s region=%s — resume scheduled",
r["run_id"],
rc,
)
except Exception as e:
logger.warning("worker_ready nspd zombie scan failed: %s", e)
try:
db.rollback()
except Exception:
pass
finally:
db.close()
if nspd_resume_targets:
from app.workers.tasks.scrape_nspd import scrape_nspd_region
for rc in nspd_resume_targets:
try:
scrape_nspd_region.apply_async(
kwargs={"region_code": rc, "triggered_by": "resume"},
)
logger.info("worker_ready: scrape_nspd_region enqueued region=%s", rc)
except Exception as e:
logger.warning(
"worker_ready: failed to enqueue NSPD resume for region=%s: %s",
rc,
e,
)