Kafka / python set up

.gitignore

+*.tgz
+*.zip
+*.tar.gz
+*.tar
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commands.md

+
+## SETTING UP PYTHON ENVIRONMENT
+
+- Activate venv
+
+[] source virtual-env/bin/activate
+
+- Install packages
+
+[] pip install -r requirements.txt
+
+## SETTING UP KAFKA SERVER
+
+- Download Kafka server
+
+[] wget https://dlcdn.apache.org/kafka/3.9.0/kafka_2.13-3.9.0.tgz
+[] tar -xzf kafka_2.13-3.9.0.tgz
+[] cd kafka_2.13-3.9.0
+
+- Setup env variables
+
+[] KAFKA_CLUSTER_ID="$(bin/kafka-storage.sh dragons-1)"
+[] bin/kafka-storage.sh format --standalone -t $KAFKA_CLUSTER_ID -c config/kraft/reconfig-server.properties
+
+- Start server
+
+[] bin/kafka-server-start.sh config/kraft/reconfig-server.properties
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kafka_consumer.py

+from confluent_kafka import Consumer, KafkaException
+import json
+
+# Create Confluent Kafka consumer
+consumer = Consumer({
+    'bootstrap.servers': 'localhost:9092',
+    'group.id': 'my-group',
+    'auto.offset.reset': 'earliest'
+})
+
+# Subscribe to 'sensor-data' topic
+consumer.subscribe(['sensor-data'])
+
+# Consume messages from 'sensor-data' topic
+try:
+    while True:
+        msg = consumer.poll(1.0)  # Poll for messages with a timeout of 1 second
+
+        if msg is None:
+            continue
+        if msg.error():
+            if msg.error().code() == KafkaError._PARTITION_EOF:
+                # End of partition event
+                print(f"{msg.topic()} [{msg.partition()}] reached end at offset {msg.offset()}")
+            elif msg.error():
+                raise KafkaException(msg.error())
+        else:
+            # Proper message
+            sensor_data = json.loads(msg.value().decode('utf-8'))  # Deserialize the JSON data
+            print(f"Received: {sensor_data}")
+            # You can process the data here (e.g., analyze, store in a DB)
+except KeyboardInterrupt:
+    print("Stopped by user")
+finally:
+    # Close down consumer to commit final offsets.
+    consumer.close()
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kafka_producer.py

+from confluent_kafka import Producer
+import random
+import json
+import time
+
+# Delivery report callback
+def delivery_report(err, msg):
+    if err is not None:
+        print(f"Message delivery failed: {err}")
+    else:
+        print(f"Message delivered to {msg.topic()} [{msg.partition()}]")
+
+# Create Confluent Kafka producer
+producer = Producer({'bootstrap.servers': 'localhost:9092'})
+
+# Generate random sensor data and send to 'sensor-data' topic
+try:
+    while True:
+        sensor_data = {
+            "sensor_id": random.randint(1, 10),  # Simulating sensor ID
+            "temperature": random.uniform(20.0, 30.0),  # Random temperature value
+            "humidity": random.uniform(30.0, 80.0)  # Random humidity value
+        }
+        
+        # Send data to 'sensor-data' topic
+        producer.produce('sensor-data', key=str(sensor_data["sensor_id"]), value=json.dumps(sensor_data), callback=delivery_report)
+        producer.poll(0)  # Serve delivery callback queue
+        
+        time.sleep(2)  # Simulate data being sent every 2 seconds
+except KeyboardInterrupt:
+    print("Stopped by user")
+finally:
+    producer.flush()
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requirements.txt

+confluent-kafka
+prometheus-client
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