128 lines
4.5 KiB
Python
128 lines
4.5 KiB
Python
import os
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import requests
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import json
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from datetime import datetime, timedelta
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from clickhouse_connect import get_client
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from dotenv import load_dotenv
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from requests.auth import HTTPBasicAuth
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load_dotenv()
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# เชื่อมต่อ ClickHouse
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def get_clickhouse_client():
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return get_client(
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host=os.getenv("CLICKHOUSE_HOST").replace("https://", ""),
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port=443,
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username=os.getenv("CLICKHOUSE_USER"),
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password=os.getenv("CLICKHOUSE_PASSWORD"),
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secure=True
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)
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# ดึง record ล่าสุดจาก ClickHouse
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def get_latest_record(client):
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query = """
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SELECT *
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FROM air_quality_db
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ORDER BY record_time DESC
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LIMIT 1
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"""
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result = client.query(query)
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named_results = list(result.named_results()) # แปลง generator เป็น list
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if named_results:
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return named_results[0] # เข้าถึงผลลัพธ์แรก
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return None
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# เรียกใช้งาน MindsDB API
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def predict_aqi(latest_record):
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from requests.auth import HTTPBasicAuth
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# อ่านค่าจาก .env
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mindsdb_api_url = os.getenv("MINDSDB_REST_API_URL", "https://mindsdb.softwarecraft.tech/api/projects/mindsdb/models/aqi_forecaster/predict")
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mindsdb_user = os.getenv("MINDSDB_USER")
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mindsdb_pass = os.getenv("MINDSDB_PASSWORD")
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headers = {"Content-Type": "application/json"}
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auth = HTTPBasicAuth(mindsdb_user, mindsdb_pass)
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record_time = latest_record['record_time']
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if isinstance(record_time, datetime):
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record_time_str = record_time.isoformat()
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else:
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record_time_str = str(record_time)
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# เตรียมข้อมูลในรูปแบบที่ MindsDB คาดหวัง
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input_data = {
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"data": [
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{
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"record_time": record_time_str,
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"pm25": latest_record.get("pm25", 0),
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"pm10": latest_record.get("pm10", 0),
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"o3": latest_record.get("o3", 0),
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"co": latest_record.get("co", 0),
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"no2": latest_record.get("no2", 0),
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"so2": latest_record.get("so2", 0),
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"aqi": latest_record.get("aqi", 0), # หาก aqi เป็น target variable ที่ใช้ train ให้ส่งมาด้วย
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}
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]
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}
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try:
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response = requests.post(
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mindsdb_api_url,
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headers=headers,
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auth=auth,
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timeout=20,
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data=json.dumps(input_data)
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)
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if response.status_code == 200:
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data = response.json()
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if isinstance(data, list) and len(data) > 0:
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return data[0] # สมมุติว่า API คืนผลลัพธ์ใน list
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elif "data" in data and len(data["data"]) > 0:
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return data["data"][0]
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else:
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print("⚠️ No prediction returned.")
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else:
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print("❌ Failed to query MindsDB:", response.status_code, response.text)
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except requests.exceptions.RequestException as e:
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print("❌ Request error:", str(e))
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return None
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# บันทึกผลทำนายลง ClickHouse
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def store_prediction(client, predicted_data, target_date):
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aqi = predicted_data.get('aqi')
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aqi_explain = predicted_data.get('aqi_explain')
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if isinstance(aqi_explain, dict):
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aqi_explain_json = json.dumps(aqi_explain)
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else:
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aqi_explain_json = aqi_explain # assume already JSON string
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insert_query = """
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INSERT INTO air_quality_forecast (predicted_for_date, predicted_aqi, aqi_explain)
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VALUES \
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"""
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client.command(
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insert_query + f"('{target_date}', {aqi}, '{aqi_explain_json}')"
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)
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print(f"✅ Prediction for {target_date} saved to ClickHouse.")
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def run_prediction_pipeline():
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client = get_clickhouse_client()
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latest_record = get_latest_record(client)
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if not latest_record:
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print("❌ No recent data found in air_quality_db.")
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return
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prediction = predict_aqi(latest_record)
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if prediction:
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record_time = latest_record['record_time']
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if isinstance(record_time, str):
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record_time = datetime.fromisoformat(record_time)
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target_date = (record_time + timedelta(days=1)).date()
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store_prediction(client, prediction, target_date)
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if __name__ == "__main__":
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run_prediction_pipeline()
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