from pyflink.datastream import StreamExecutionEnvironment
from pyflink.datastream.connectors.kafka import FlinkKafkaConsumer
from pyflink.common.serialization import SimpleStringSchema
import json

def detect_anomalies(transaction):
    transaction_data = json.loads(transaction)
    # Add anomaly detection logic here
    return transaction_data

env = StreamExecutionEnvironment.get_execution_environment()
kafka_consumer = FlinkKafkaConsumer(
    topics='transactions',
    deserialization_schema=SimpleStringSchema(),
    properties={'bootstrap.servers': 'localhost:9092', 'group.id': 'anomaly_detection'}
)

data_stream = env.add_source(kafka_consumer).map(detect_anomalies)
data_stream.print()
env.execute("Anomaly Detection")