Bernt
aee0f09db8
- Datafabrik: Dockerfile fix, agentorkestrering fungerar - Vision: Identify-modell, FAISS, OCR alla testade - API: Alla 7 integrationstester passerade - Upplösare: Entitetsupplösning verifierad
115 lines
4.1 KiB
Python
115 lines
4.1 KiB
Python
#!/usr/bin/env python3
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"""
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LIFE Multi-Source Pipeline
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Hämtar data kontinuerligt från flera källor
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"""
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import sqlite3
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import json
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import random
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from datetime import datetime, timedelta
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import time
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DB_PATH = "/home/bernt/.openclaw/workspace/rivp-pilot-1/rivp.db"
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def get_db():
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conn = sqlite3.connect(DB_PATH)
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conn.row_factory = sqlite3.Row
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return conn
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def fetch_trafikverket_data():
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"""Simulerar hämtning från Trafikverket"""
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return [
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{"road": "E4", "type": "ice", "severity": "high", "lat": 59.85, "lon": 17.65},
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{"road": "E4", "type": "roadwork", "severity": "medium", "lat": 59.88, "lon": 17.72},
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{"road": "272", "type": "flooding", "severity": "low", "lat": 59.92, "lon": 17.55},
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]
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def fetch_smhi_data():
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"""Simulerar hämtning från SMHI"""
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return [
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{"location": "Uppsala", "weather": "snow", "temperature": -5, "impact": "high"},
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{"location": "Stockholm", "weather": "rain", "temperature": 8, "impact": "medium"},
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]
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def fetch_quixzoom_data():
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"""Simulerar hämtning från quiXzoom contributors"""
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return [
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{"road_id": 1, "type": "pothole", "confidence": 0.92, "lat": 59.85, "lon": 17.65},
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{"road_id": 2, "type": "crack", "confidence": 0.78, "lat": 59.88, "lon": 17.72},
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]
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def process_and_save(source_name, data):
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"""Bearbeta och spara data från varje källa"""
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conn = get_db()
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c = conn.cursor()
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count = 0
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for item in data:
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if source_name == "trafikverket":
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c.execute("SELECT id FROM roads WHERE road_number = ?", (item["road"],))
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result = c.fetchone()
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if result:
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road_id = result[0]
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c.execute('''
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INSERT INTO observations
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(road_id, observation_type, latitude, longitude, confidence, severity, detected_date, source)
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VALUES (?, ?, ?, ?, ?, ?, ?, ?)
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''', (road_id, item["type"], item["lat"], item["lon"], 0.9, item["severity"], datetime.now().strftime('%Y-%m-%d'), source_name))
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count += 1
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elif source_name == "smhi":
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# SMHI-data påverkar alla vägar i området
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c.execute("SELECT id FROM roads WHERE county = ?", (item["location"],))
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roads = c.fetchall()
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for road in roads:
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c.execute('''
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INSERT INTO observations
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(road_id, observation_type, latitude, longitude, confidence, severity, detected_date, source)
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VALUES (?, ?, ?, ?, ?, ?, ?, ?)
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''', (road[0], item["weather"], 0, 0, 0.85, item["impact"], datetime.now().strftime('%Y-%m-%d'), source_name))
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count += 1
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elif source_name == "quixzoom":
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c.execute('''
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INSERT INTO observations
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(road_id, observation_type, latitude, longitude, confidence, severity, detected_date, source)
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VALUES (?, ?, ?, ?, ?, ?, ?, ?)
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''', (item["road_id"], item["type"], item["lat"], item["lon"], item["confidence"], "medium", datetime.now().strftime('%Y-%m-%d'), source_name))
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count += 1
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conn.commit()
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conn.close()
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return count
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def run_pipeline():
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"""Kör komplett pipeline från alla källor"""
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print(f"[{datetime.now().isoformat()}] Running multi-source pipeline...")
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sources = {
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"trafikverket": fetch_trafikverket_data,
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"smhi": fetch_smhi_data,
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"quixzoom": fetch_quixzoom_data
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}
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total = 0
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for source_name, fetch_func in sources.items():
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try:
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data = fetch_func()
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saved = process_and_save(source_name, data)
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total += saved
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print(f" {source_name}: {saved} observations")
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except Exception as e:
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print(f" {source_name}: ERROR - {e}")
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print(f"[{datetime.now().isoformat()}] Pipeline complete: {total} total observations")
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return total
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if __name__ == "__main__":
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print("="*60)
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print("LIFE MULTI-SOURCE PIPELINE")
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print("="*60)
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run_pipeline()
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print("="*60)
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