41 lines
1.2 KiB
Python
41 lines
1.2 KiB
Python
from celery import Celery
|
|
from sqlalchemy.orm import Session
|
|
from models.database import get_db # Note: For workers, might need adjustment
|
|
import hashlib
|
|
from parsers.base import BaseParser
|
|
from proto.unified_point_pb2 import UnifiedPoint
|
|
|
|
celery = Celery('tasks', broker='redis://redis:6379/0')
|
|
|
|
@celery.task
|
|
def process_import(file_path: str, import_id: str):
|
|
\"\"\"Main ingestion pipeline\"\"\"
|
|
# 1. Validation & de-duplication
|
|
with open(file_path, 'rb') as f:
|
|
file_hash = hashlib.sha256(f.read()).hexdigest()
|
|
|
|
# 2. Determine parser
|
|
parser = BaseParser.get_parser(file_path)
|
|
if not parser:
|
|
raise ValueError("Unsupported format")
|
|
|
|
# 3. Parse to UPS
|
|
points = parser.parse(file_path)
|
|
|
|
# 4. Stream to PostGIS (simplified)
|
|
# For each point in points:
|
|
# insert_raw_point(point)
|
|
|
|
# 5. Sub-sample, segment, detect stops, infer modes, enrich
|
|
# ... (implement pipeline steps)
|
|
|
|
# 6. Update heat tiles in Redis
|
|
# 7. Generate day snapshots
|
|
|
|
return {"status": "completed", "points_processed": len(points)}
|
|
|
|
@celery.task
|
|
def detect_spoofing(import_id: str):
|
|
# Implement spoof detection logic
|
|
pass
|