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e72f783 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 | """
Data enrichment pipeline for anomaly detection
"""
import logging
from typing import Dict, List, Any
logger = logging.getLogger(__name__)
class DataEnricher:
"""
Enriches raw data with additional context and metadata.
"""
def __init__(self):
"""Initialize data enricher."""
logger.info("DataEnricher initialized")
def enrich(self, data: Dict) -> Dict:
"""
Enrich data with metadata and context.
Args:
data: Input data dictionary
Returns:
Enriched data dictionary
"""
enriched = data.copy()
# Add enrichment logic
return enriched
def add_category_metadata(self, data: Dict, category: str) -> Dict:
"""Add category-specific metadata."""
logger.info(f"Adding metadata for category: {category}")
# Implementation
return data
def add_temporal_features(self, data: Dict) -> Dict:
"""Add temporal features to data."""
logger.info("Adding temporal features")
# Implementation
return data
class EnrichmentPipeline:
"""
Complete enrichment pipeline combining multiple enrichment steps.
"""
def __init__(self):
self.enricher = DataEnricher()
def process(self, raw_data: List[Dict]) -> List[Dict]:
"""
Process raw data through enrichment pipeline.
Args:
raw_data: List of raw data items
Returns:
List of enriched data items
"""
logger.info(f"Processing {len(raw_data)} items through enrichment pipeline")
enriched_data = []
for item in raw_data:
enriched_item = self.enricher.enrich(item)
enriched_data.append(enriched_item)
return enriched_data
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