- prediction/: FastAPI 7단계 분류 파이프라인 + 6개 탐지 알고리즘 - snpdb 궤적 조회 → 인메모리 캐시(13K척) → 분류 → kcgdb 저장 - APScheduler 5분 주기, Python 3.9 호환 - 버그 수정: @property last_bucket, SQL INTERVAL 바인딩, rollback, None 가드 - 보안: DB 비밀번호 하드코딩 제거 → env 환경변수 필수 - deploy/kcg-prediction.service: systemd 서비스 (redis-211, 포트 8001) - deploy.yml: prediction CI/CD 배포 단계 추가 (192.168.1.18:32023) - backend: PredictionProxyController (health/status/trigger 프록시) - backend: AppProperties predictionBaseUrl + AuthFilter 인증 예외 Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
188 lines
5.6 KiB
Python
188 lines
5.6 KiB
Python
import logging
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from contextlib import contextmanager
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from datetime import datetime
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from typing import Optional
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import pandas as pd
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import psycopg2
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from psycopg2 import pool
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from config import settings
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logger = logging.getLogger(__name__)
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_pool: Optional[pool.ThreadedConnectionPool] = None
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def init_pool():
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global _pool
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_pool = pool.ThreadedConnectionPool(
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minconn=1,
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maxconn=3,
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host=settings.SNPDB_HOST,
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port=settings.SNPDB_PORT,
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dbname=settings.SNPDB_NAME,
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user=settings.SNPDB_USER,
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password=settings.SNPDB_PASSWORD,
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)
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logger.info('snpdb connection pool initialized')
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def close_pool():
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global _pool
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if _pool:
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_pool.closeall()
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_pool = None
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logger.info('snpdb connection pool closed')
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@contextmanager
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def get_conn():
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conn = _pool.getconn()
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try:
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yield conn
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finally:
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_pool.putconn(conn)
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def check_health() -> bool:
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try:
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with get_conn() as conn:
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with conn.cursor() as cur:
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cur.execute('SELECT 1')
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return True
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except Exception as e:
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logger.error('snpdb health check failed: %s', e)
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return False
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def fetch_all_tracks(hours: int = 24) -> pd.DataFrame:
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"""한국 해역 전 선박의 궤적 포인트를 조회한다.
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LineStringM 지오메트리에서 개별 포인트를 추출하며,
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한국 해역(124-132E, 32-39N) 내 최근 N시간 데이터를 반환한다.
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"""
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query = f"""
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SELECT
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t.mmsi,
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to_timestamp(ST_M((dp).geom)) as timestamp,
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ST_Y((dp).geom) as lat,
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ST_X((dp).geom) as lon,
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CASE
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WHEN (dp).path[1] = 1 THEN (t.start_position->>'sog')::float
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ELSE COALESCE((t.end_position->>'sog')::float, t.avg_speed::float)
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END as raw_sog
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FROM signal.t_vessel_tracks_5min t,
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LATERAL ST_DumpPoints(t.track_geom) dp
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WHERE t.time_bucket >= NOW() - INTERVAL '{hours} hours'
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AND t.track_geom && ST_MakeEnvelope(124, 32, 132, 39, 4326)
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ORDER BY t.mmsi, to_timestamp(ST_M((dp).geom))
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"""
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try:
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with get_conn() as conn:
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df = pd.read_sql_query(query, conn)
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logger.info(
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'fetch_all_tracks: %d rows, %d vessels (last %dh)',
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len(df),
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df['mmsi'].nunique() if len(df) > 0 else 0,
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hours,
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)
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return df
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except Exception as e:
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logger.error('fetch_all_tracks failed: %s', e)
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return pd.DataFrame(columns=['mmsi', 'timestamp', 'lat', 'lon', 'raw_sog'])
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def fetch_incremental(last_bucket: datetime) -> pd.DataFrame:
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"""last_bucket 이후의 신규 궤적 포인트를 조회한다.
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스케줄러 증분 업데이트에 사용되며, time_bucket > last_bucket 조건으로
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이미 처리한 버킷을 건너뛴다.
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"""
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query = """
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SELECT
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t.mmsi,
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to_timestamp(ST_M((dp).geom)) as timestamp,
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ST_Y((dp).geom) as lat,
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ST_X((dp).geom) as lon,
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CASE
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WHEN (dp).path[1] = 1 THEN (t.start_position->>'sog')::float
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ELSE COALESCE((t.end_position->>'sog')::float, t.avg_speed::float)
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END as raw_sog
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FROM signal.t_vessel_tracks_5min t,
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LATERAL ST_DumpPoints(t.track_geom) dp
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WHERE t.time_bucket > %s
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AND t.track_geom && ST_MakeEnvelope(124, 32, 132, 39, 4326)
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ORDER BY t.mmsi, to_timestamp(ST_M((dp).geom))
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"""
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try:
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with get_conn() as conn:
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df = pd.read_sql_query(query, conn, params=(last_bucket,))
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logger.info(
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'fetch_incremental: %d rows, %d vessels (since %s)',
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len(df),
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df['mmsi'].nunique() if len(df) > 0 else 0,
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last_bucket.isoformat(),
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)
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return df
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except Exception as e:
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logger.error('fetch_incremental failed: %s', e)
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return pd.DataFrame(columns=['mmsi', 'timestamp', 'lat', 'lon', 'raw_sog'])
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def fetch_static_info(mmsi_list: list[str]) -> dict[str, dict]:
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"""MMSI 목록에 해당하는 선박 정적 정보를 조회한다.
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DISTINCT ON (mmsi)로 최신 레코드만 반환한다.
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"""
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query = """
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SELECT DISTINCT ON (mmsi) mmsi, name, vessel_type, length, width
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FROM signal.t_vessel_static
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WHERE mmsi = ANY(%s)
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ORDER BY mmsi, time_bucket DESC
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"""
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try:
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with get_conn() as conn:
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with conn.cursor() as cur:
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cur.execute(query, (mmsi_list,))
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rows = cur.fetchall()
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result = {
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row[0]: {
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'name': row[1],
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'vessel_type': row[2],
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'length': row[3],
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'width': row[4],
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}
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for row in rows
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}
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logger.info('fetch_static_info: %d vessels resolved', len(result))
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return result
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except Exception as e:
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logger.error('fetch_static_info failed: %s', e)
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return {}
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def fetch_permit_mmsis() -> set[str]:
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"""중국 허가어선 MMSI 목록을 조회한다.
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signal.t_chnprmship_positions 테이블에서 DISTINCT mmsi를 반환한다.
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"""
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query = """
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SELECT DISTINCT mmsi FROM signal.t_chnprmship_positions
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"""
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try:
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with get_conn() as conn:
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with conn.cursor() as cur:
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cur.execute(query)
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rows = cur.fetchall()
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result = {row[0] for row in rows}
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logger.info('fetch_permit_mmsis: %d permitted vessels', len(result))
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return result
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except Exception as e:
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logger.error('fetch_permit_mmsis failed: %s', e)
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return set()
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