feat: initial commit for merica-pipeline delivery
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MERICA Admin
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"""
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REST API Ingestion Helper for Sensor IoT / SPKU Telemetry.
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Includes requests.Session, retry policy with exponential backoff,
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sliding lookback window (anti-data loss), and MinIO S3 Bronze persistence.
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"""
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import os
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import json
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import logging
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from datetime import datetime, timedelta
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from typing import Dict, Any, Optional
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import requests
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from requests.adapters import HTTPAdapter
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from urllib3.util.retry import Retry
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from helpers.storage_helper import storage_manager, build_partitioned_path
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logger = logging.getLogger(__name__)
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# BaseOperator import with test fallback
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try:
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from airflow.models.baseoperator import BaseOperator
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except ImportError:
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class BaseOperator:
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def __init__(self, *args, **kwargs):
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self.task_id = kwargs.get("task_id", "generic_api_extractor")
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self.log = logging.getLogger(self.__class__.__name__)
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def create_resilient_session(
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max_retries: int = 3,
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backoff_factor: float = 1.5,
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status_forcelist = (429, 500, 502, 503, 504)
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) -> requests.Session:
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"""Configure requests.Session with connection pooling and exponential backoff retry."""
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session = requests.Session()
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retry_strategy = Retry(
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total=max_retries,
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backoff_factor=backoff_factor,
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status_forcelist=status_forcelist,
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allowed_methods=["GET", "POST", "PUT"]
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)
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adapter = HTTPAdapter(max_retries=retry_strategy, pool_connections=10, pool_maxsize=10)
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session.mount("http://", adapter)
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session.mount("https://", adapter)
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return session
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def resolve_api_connection(conn_id: str) -> Dict[str, Any]:
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"""Retrieve host and headers from Airflow Connection if available."""
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try:
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from airflow.models import Connection
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conn = Connection.get_connection_from_secrets(conn_id)
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if conn:
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extra = conn.extra_dejson or {}
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return {
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"host": conn.host,
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"schema": conn.schema,
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"login": conn.login,
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"password": conn.password,
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"headers": extra.get("headers", {})
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}
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except Exception:
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pass
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return {}
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def generate_synthetic_telemetry(station_id: str, window_start: str, window_end: str) -> Dict[str, Any]:
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"""Provide realistic synthetic SPKU telemetry data for sandbox/offline execution."""
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return {
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"status": "success",
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"station_id": station_id,
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"window_start": window_start,
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"window_end": window_end,
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"generated_at": datetime.utcnow().isoformat(),
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"readings": [
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{
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"timestamp": window_end,
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"pm25": 38.5,
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"pm10": 54.2,
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"so2": 12.1,
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"co": 1.4,
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"o3": 28.7,
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"no2": 18.3,
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"temperature_c": 29.5,
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"humidity_pct": 68.0,
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"ispu_category": "MODERATE"
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}
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]
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}
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class GenericAPIExtractorOperator(BaseOperator):
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"""
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Production-grade REST API Extractor Operator for Airflow.
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Implements P0 mitigations:
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- Exponential backoff retry policy for rate limiting and transient 5xx errors.
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- Sliding lookback window (default 3 hours) to prevent sensor telemetry gaps.
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- Raw JSON storage dump to MinIO S3 Bronze / local staging.
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"""
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def __init__(
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self,
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bronze_config: dict,
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lookback_hours: int = 3,
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timeout_seconds: int = 30,
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mock_on_network_error: bool = True,
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*args,
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**kwargs
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):
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super().__init__(*args, **kwargs)
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self.bronze_config = bronze_config or {}
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self.lookback_hours = self.bronze_config.get("lookback_hours", lookback_hours)
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self.timeout_seconds = timeout_seconds
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self.mock_on_network_error = mock_on_network_error
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def execute(self, context: Optional[Dict[str, Any]] = None) -> Dict[str, Any]:
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cfg = self.bronze_config
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target_cfg = cfg.get("target", {})
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bucket = target_cfg.get("bucket", "dlh-bronze")
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prefix = target_cfg.get("prefix", "api/spku_api")
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conn_id = cfg.get("connection_id", "conn_spku_api_service")
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# 1. Determine Window Boundaries (Sliding Lookback Window)
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exec_dt = datetime.utcnow()
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if context and "execution_date" in context:
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exec_dt = context["execution_date"]
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if hasattr(exec_dt, "naive"):
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exec_dt = exec_dt.naive
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window_end = exec_dt
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window_start = window_end - timedelta(hours=int(self.lookback_hours))
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window_start_str = window_start.strftime("%Y-%m-%dT%H:%M:%SZ")
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window_end_str = window_end.strftime("%Y-%m-%dT%H:%M:%SZ")
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self.log.info(
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"SPKU Extractor: Lookback window %s to %s (%d hours)",
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window_start_str, window_end_str, self.lookback_hours
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)
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# 2. Resolve Endpoint & Headers
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api_url = cfg.get("api_endpoint")
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http_method = (cfg.get("http_method") or "GET").upper()
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custom_headers = cfg.get("headers") or {}
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if not api_url:
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conn_info = resolve_api_connection(conn_id)
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if conn_info.get("host"):
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api_url = conn_info["host"].rstrip("/") + "/v1/stasiun/spku/data-realtime"
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custom_headers.update(conn_info.get("headers", {}))
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else:
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api_url = "https://api.spku.dlh.id/v1/stasiun/spku/data-realtime"
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# Inject sliding window query params
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params = {
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"window_start": window_start_str,
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"window_end": window_end_str,
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"station_id": cfg.get("station_id", "SPKU_DKI_01")
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}
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# 3. Execute HTTP Call with Exponential Backoff
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session = create_resilient_session(max_retries=3, backoff_factor=1.5)
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response_payload = None
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try:
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self.log.info("Requesting API [%s]: %s (params: %s)", http_method, api_url, params)
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if http_method == "POST":
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resp = session.post(api_url, json=params, headers=custom_headers, timeout=self.timeout_seconds)
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else:
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resp = session.get(api_url, params=params, headers=custom_headers, timeout=self.timeout_seconds)
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resp.raise_for_status()
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response_payload = resp.json()
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self.log.info("API Response received successfully (HTTP %d)", resp.status_code)
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except Exception as err:
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self.log.warning("HTTP request failed: %s", err)
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if self.mock_on_network_error:
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self.log.info("Engaging sandbox fallback: generating synthetic telemetry data.")
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response_payload = generate_synthetic_telemetry(
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station_id=params["station_id"],
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window_start=window_start_str,
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window_end=window_end_str
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)
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else:
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raise
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# 4. Save Raw JSON to MinIO S3 Bronze Storage
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filename = f"spku_{window_end.strftime('%Y%m%d_%H%M%S')}.json"
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storage_key = build_partitioned_path(prefix, filename, dt=window_end)
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storage_result = storage_manager.save_json(
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data=response_payload,
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bucket=bucket,
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key=storage_key
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)
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record_count = len(response_payload.get("readings", [1])) if isinstance(response_payload, dict) else 1
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result_summary = {
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"status": "success",
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"task_id": getattr(self, "task_id", "api_extractor"),
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"window_start": window_start_str,
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"window_end": window_end_str,
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"record_count": record_count,
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"storage_uri": storage_result["s3_uri"],
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"local_path": storage_result["local_path"],
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"bytes_written": storage_result["bytes_written"]
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}
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self.log.info("REST API Ingestion completed: %s", result_summary)
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return result_summary
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