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Dam 100602 reports 87798% storage on some days, overflowing NUMERIC(6,2) and discarding the entire 33-dam daily batch. storage_pct is now NUMERIC(8,2) (auto-migrated on connect for existing Postgres/ MySQL tables) and every measure column is bounds-checked before insert so out-of-capacity junk becomes NULL instead of a batch-killing error. Rerunning the backfill repairs the days the overflow skipped.
390 lines
14 KiB
Python
390 lines
14 KiB
Python
"""Collector for RID large-dam daily status (app.rid.go.th/reservoir).
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The Royal Irrigation Department reservoir app exposes an unauthenticated
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JSON API: ``POST https://app.rid.go.th/reservoir/api/dams`` with form field
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``date=YYYY-MM-DD`` (empty = today) returns a daily snapshot of every large
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dam in Thailand — storage, inflow and outflow in MCM — with archive depth
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back to at least 2009. GET returns 404 ("Unknown method."); the POST body
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may be empty but must carry a Content-Length.
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The reservoir that matters for P.1 flood forecasting is Mae Ngat Somboon
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Chon (DAM_ID 200103), the only large dam upstream of Chiang Mai: during the
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Oct 2024 record flood it reached 113% of usable capacity with inflow spikes
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of ~19 MCM/day. All dams in the payload are stored (same request cost);
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filtering happens at feature-build time.
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See docs/DATA_SOURCES.md for the endpoint catalog.
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"""
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import datetime
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import logging
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import time
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from typing import Any, Dict, List, Optional
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import requests
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logger = logging.getLogger(__name__)
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RID_DAMS_URL = "https://app.rid.go.th/reservoir/api/dams"
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MAE_NGAT_DAM_ID = "200103"
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# Per-column NUMERIC capacity; source junk beyond these becomes NULL instead
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# of overflowing the insert and discarding the whole daily batch.
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_MEASURE_BOUNDS = {
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"storage_mcm": 1e8,
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"storage_pct": 1e6,
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"inflow_mcm": 1e8,
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"outflow_mcm": 1e8,
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"level_msl": 1e6,
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}
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def _bounded(value: Optional[float], limit: float) -> Optional[float]:
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if value is not None and abs(value) >= limit:
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return None
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return value
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def _to_float(value: Any) -> Optional[float]:
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"""API numerics arrive as strings ('222.01'), ' - ' placeholders, or None."""
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if value is None:
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return None
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if isinstance(value, str):
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value = value.replace(",", "").strip()
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if value in ("", "-"):
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return None
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try:
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return float(value)
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except (TypeError, ValueError):
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return None
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def parse_dam_records(payload: Dict) -> List[Dict]:
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"""Flatten the regions/dams payload into per-dam daily rows."""
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records = []
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for region in payload.get("regions") or []:
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for dam in region.get("dams") or []:
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dam_id = dam.get("DAM_ID")
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try:
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date = datetime.date.fromisoformat(dam.get("DMD_Date") or "")
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except ValueError:
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continue
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if not dam_id:
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continue
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records.append(
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{
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"dam_id": dam_id,
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"region": region.get("region_name"),
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"name_th": dam.get("DAM_Name"),
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"latitude": _to_float(dam.get("DAM_Lat")),
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"longitude": _to_float(dam.get("DAM_Lon")),
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"capacity_max_mcm": _to_float(dam.get("DAM_QMax")),
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"capacity_normal_mcm": _to_float(dam.get("DAM_QStore")),
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"date": date,
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"storage_mcm": _to_float(dam.get("DMD_QUse")),
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"storage_pct": _to_float(dam.get("PERCENT_DMD_QUse")),
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"inflow_mcm": _to_float(dam.get("DMD_Inflow")),
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"outflow_mcm": _to_float(dam.get("DMD_Outflow")),
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"level_msl": _to_float(dam.get("DMD_Q")),
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}
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)
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return records
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class RidReservoirClient:
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"""HTTP client for the RID reservoir daily-status API."""
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def __init__(
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self,
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url: str = RID_DAMS_URL,
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session: Optional[requests.Session] = None,
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timeout: int = 60,
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):
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self.url = url
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self.session = session or requests.Session()
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self.timeout = timeout
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def fetch_day(self, date: Optional[datetime.date] = None) -> List[Dict]:
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"""Daily rows for every large dam on `date` (None = today)."""
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data = {"date": date.isoformat()} if date else {"date": ""}
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response = self.session.post(
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self.url,
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data=data,
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headers={"X-Requested-With": "XMLHttpRequest"},
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timeout=self.timeout,
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)
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response.raise_for_status()
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return parse_dam_records(response.json())
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class RidReservoirStore:
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"""SQL persistence for dam metadata + daily measurements.
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Shares the app's relational database; writes rid_dams (metadata) and
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rid_reservoir_daily keyed (dam_id, date) — the composite natural PK keeps
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the table TimescaleDB-hypertable compatible.
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"""
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def __init__(self, connection_string: str, db_type: str):
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self.db_type = db_type.lower()
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if self.db_type not in ("sqlite", "postgresql", "mysql"):
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raise ValueError(
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f"Reservoir collection requires a SQL database, got '{db_type}'"
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)
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self.connection_string = connection_string
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self.engine = None
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def connect(self) -> bool:
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try:
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from sqlalchemy import create_engine
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self.engine = create_engine(self.connection_string, pool_pre_ping=True)
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self._create_tables()
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return True
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except Exception as e:
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logger.error(f"RidReservoirStore failed to connect: {e}")
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self.engine = None
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return False
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def _create_tables(self):
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from sqlalchemy import text
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ddl = [
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"""
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CREATE TABLE IF NOT EXISTS rid_dams (
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dam_id VARCHAR(10) PRIMARY KEY,
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region VARCHAR(40),
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name_th VARCHAR(255),
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latitude NUMERIC(10,6),
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longitude NUMERIC(10,6),
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capacity_max_mcm NUMERIC(10,2),
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capacity_normal_mcm NUMERIC(10,2),
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updated_at TIMESTAMP
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)
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""",
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"""
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CREATE TABLE IF NOT EXISTS rid_reservoir_daily (
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dam_id VARCHAR(10) NOT NULL,
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date DATE NOT NULL,
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storage_mcm NUMERIC(10,2),
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storage_pct NUMERIC(8,2),
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inflow_mcm NUMERIC(10,2),
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outflow_mcm NUMERIC(10,2),
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level_msl NUMERIC(8,2),
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created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
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PRIMARY KEY (dam_id, date)
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)
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""",
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]
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if self.db_type != "mysql":
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ddl.append(
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"CREATE INDEX IF NOT EXISTS idx_rid_reservoir_date "
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"ON rid_reservoir_daily(date)"
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)
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with self.engine.begin() as conn:
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for statement in ddl:
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conn.execute(text(statement))
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# Widen storage_pct on tables created before 2026-08-13: the source
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# publishes junk percents (dam 100602 reports 87798%) that overflowed
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# NUMERIC(6,2) and discarded whole daily batches.
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if self.db_type == "postgresql":
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migrations = (
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"ALTER TABLE rid_reservoir_daily "
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"ALTER COLUMN storage_pct TYPE NUMERIC(8,2)",
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)
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elif self.db_type == "mysql":
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migrations = (
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"ALTER TABLE rid_reservoir_daily MODIFY storage_pct NUMERIC(8,2)",
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)
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else: # sqlite: NUMERIC is affinity only, nothing to widen
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migrations = ()
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for statement in migrations:
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try:
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with self.engine.begin() as conn:
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conn.execute(text(statement))
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except Exception as e:
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logger.warning(f"rid_reservoir_daily migration skipped: {e}")
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def _upsert(self, table: str, key_cols: List[str], value_cols: List[str]) -> str:
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cols = key_cols + value_cols
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col_list = ", ".join(cols)
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params = ", ".join(f":{c}" for c in cols)
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if self.db_type == "sqlite":
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return f"INSERT OR REPLACE INTO {table} ({col_list}) VALUES ({params})"
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if self.db_type == "postgresql":
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updates = ", ".join(f"{c} = EXCLUDED.{c}" for c in value_cols)
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conflict = ", ".join(key_cols)
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return (
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f"INSERT INTO {table} ({col_list}) VALUES ({params}) "
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f"ON CONFLICT ({conflict}) DO UPDATE SET {updates}"
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)
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updates = ", ".join(f"{c} = VALUES({c})" for c in value_cols)
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return (
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f"INSERT INTO {table} ({col_list}) VALUES ({params}) "
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f"ON DUPLICATE KEY UPDATE {updates}"
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)
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def save(self, records: List[Dict]) -> int:
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"""Upsert one day's dam rows (metadata + measurements); idempotent."""
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if not records:
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return 0
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if not self.engine and not self.connect():
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return 0
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from sqlalchemy import text
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dam_cols = [
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"region",
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"name_th",
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"latitude",
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"longitude",
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"capacity_max_mcm",
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"capacity_normal_mcm",
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]
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measure_cols = [
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"storage_mcm",
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"storage_pct",
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"inflow_mcm",
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"outflow_mcm",
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"level_msl",
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]
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dam_sql = self._upsert("rid_dams", ["dam_id"], dam_cols + ["updated_at"])
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measure_sql = self._upsert(
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"rid_reservoir_daily", ["dam_id", "date"], measure_cols
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)
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now = datetime.datetime.now()
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dams = {}
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measurements = []
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for record in records:
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dam_row = {c: record.get(c) for c in dam_cols}
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dam_row.update({"dam_id": record["dam_id"], "updated_at": now})
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dams[record["dam_id"]] = dam_row
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measure_row = {
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c: _bounded(record.get(c), _MEASURE_BOUNDS[c]) for c in measure_cols
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}
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measure_row.update(
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{"dam_id": record["dam_id"], "date": record["date"]}
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)
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measurements.append(measure_row)
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try:
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with self.engine.begin() as conn:
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conn.execute(text(dam_sql), list(dams.values()))
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conn.execute(text(measure_sql), measurements)
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return len(measurements)
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except Exception as e:
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logger.error(f"RidReservoirStore save failed: {e}")
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return 0
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def present_dates(
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self, start: datetime.date, end: datetime.date
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) -> "set[datetime.date]":
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"""Dates in [start, end] that already have rows, for backfill skipping."""
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if not self.engine and not self.connect():
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return set()
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from sqlalchemy import text
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with self.engine.begin() as conn:
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values = conn.execute(
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text(
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"SELECT DISTINCT date FROM rid_reservoir_daily "
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"WHERE date >= :start AND date <= :end"
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),
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{"start": start, "end": end},
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).fetchall()
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dates = set()
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for (value,) in values:
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if isinstance(value, str): # sqlite returns ISO strings
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value = datetime.date.fromisoformat(value[:10])
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if isinstance(value, datetime.datetime):
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value = value.date()
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dates.add(value)
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return dates
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class RidReservoirCollector:
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"""Fetch + persist the daily dam snapshot (today and yesterday)."""
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def __init__(self, db_config: Dict, client: Optional[RidReservoirClient] = None):
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self.client = client or RidReservoirClient()
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self.store = RidReservoirStore(
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connection_string=db_config["connection_string"],
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db_type=db_config["type"],
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)
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def run_cycle(self) -> int:
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"""Collect today's snapshot plus yesterday's (late daily revisions)."""
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saved = 0
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today = datetime.date.today()
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for date in (None, today - datetime.timedelta(days=1)):
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try:
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saved += self.store.save(self.client.fetch_day(date))
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except Exception as e:
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logger.error(f"RID reservoir collection failed for {date}: {e}")
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logger.info(f"RID reservoir collection: {saved} dam-day rows saved")
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return saved
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def backfill(
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store: RidReservoirStore,
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start: datetime.date,
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end: Optional[datetime.date] = None,
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client: Optional[RidReservoirClient] = None,
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throttle_seconds: float = 0.4,
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) -> int:
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"""Fetch every MISSING day in [start, end]; one polite request per day.
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Only dates absent from rid_reservoir_daily are requested, so a rerun
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repairs holes left by transient failures instead of resuming past them
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(the hourly collector writes today's rows immediately, which makes any
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newest-row cursor useless as a resume point). A save that persists
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nothing counts as a failure too — a broken DB must not burn thousands
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of requests against the RID API.
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"""
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client = client or RidReservoirClient()
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end = end or datetime.date.today()
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if not store.engine and not store.connect():
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logger.error("backfill aborted: database connection failed")
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return 0
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span = [
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start + datetime.timedelta(days=i) for i in range((end - start).days + 1)
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]
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present = store.present_dates(start, end)
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targets = [d for d in span if d not in present]
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logger.info(
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f"backfill: {len(targets)} of {len(span)} days missing in [{start}, {end}]"
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)
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total = 0
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failures = 0
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for i, date in enumerate(targets):
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try:
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records = client.fetch_day(date)
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saved = store.save(records)
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if records and not saved:
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raise RuntimeError("database save persisted 0 rows")
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total += saved
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failures = 0
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except Exception as e:
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failures += 1
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logger.warning(f"backfill {date} failed ({failures} in a row): {e}")
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if failures >= 5:
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logger.error("5 consecutive failures — aborting backfill")
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break
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if i % 100 == 0:
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logger.info(f"backfill progress: {date} ({total} rows)")
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time.sleep(throttle_seconds)
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return total
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def create_collector_from_config() -> Optional[RidReservoirCollector]:
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"""Build a collector from app Config; None when disabled or non-SQL DB."""
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from .config import Config
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if not Config.ENABLE_RESERVOIR_COLLECTION:
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return None
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db_config = Config.get_database_config()
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if db_config["type"] not in ("sqlite", "postgresql", "mysql"):
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logger.warning(
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f"Reservoir collection skipped: DB_TYPE '{db_config['type']}' is not SQL"
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)
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return None
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return RidReservoirCollector(db_config)
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