The AWS CLI Documentation You Really Wanted

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name">C:\Users\feng\Kafka\kraft>ls docker-compose.yml C:\Users\feng\Kafka\kraft>docker-compose up -d [+] Running 2/2

Network kraft_default Created 0.0s
Container kraft-kafka-1 Started

C:\Users\feng\Kafka\kraft>docker ps CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES 54342e49a1f2 bitnami/kafka:latest "/opt/bitnami/script…" 18 seconds ago Up 17 seconds 0.0.0.0:9092->9092/tcp kraft-kafka-1 0.5s</pre></div><h2 id="095a">1.5 Create Kafka topic</h2>We’ll login to the instance and create a test topic in Kafka<div id="aaf2"><pre>## Login to Kafka docker instance C:\Users\feng\Kafka\kraft>docker exec -it kraft-kafka-1 /bin/bash $cd /opt/bitnami/kafka /opt/bitnami/kafka$ ./bin/kafka-topics.sh --version 3.4.0 (Commit:2e1947d240607d53)

## Create topic named "test_topic" /opt/bitnami/kafka$ ./bin/kafka-topics.sh --bootstrap-server localhost:9092 --create --replication-factor 1 --partitions 2 --topic test_topic WARNING: Due to limitations in metric names, topics with a period ('.') or underscore ('_') could collide. To avoid issues it is best to use either, but not both. Created topic test_topic.

## List current topics /opt/bitnami/kafka$ ./bin/kafka-topics.sh --bootstrap-server localhost:9092 --list test_topic</pre></div>So by now we have a Kafka docker instance running successfully.<h1 id="80ee">2 Run sanity checks using simple producer/consumer app codes</h1><h2 id="b504">2.1 Setup producer/consumer Dev ENV</h2><div id="8e5b"><pre>## Create conda env for Kafka producer and cosumer C:\Users\feng\Kafka\kraft>conda create -n kafka_env python=3.10 ... C:\Users\feng\Kafka\kraft>conda activate kafka_env

Install kafka-python package

(kafka_env) C:\Users\feng\Kafka\kraft>pip install kafka-python ... (kafka_env) C:\Users\feng\Kafka\kraft>pip list | grep kafka kafka-python 2.0.2

Install Faker package to generate dummy messages

(kafka_env) C:\Users\feng\Kafka\kraft>pip install Faker ... (kafka_env) C:\Users6119811\Kafka\kraft>pip list | grep Faker Faker 17.3.0</pre></div><h2 id="6701">2.2 Code examples</h2>Now we can use VSCode to create producer/consumer files.Producer generate fake user info as JSON load sending to Kafka topic “test_topic”. producer.py is like following.<div id="8801"><pre>import time import json from datetime import datetime from kafka import KafkaProducer from faker import Faker

# JSON messages needs to be serialized # when sending to Kafka topic def json_serializer(message): return json.dumps(message

Options

).encode('utf-8') # Kafka Producer producer = KafkaProducer( bootstrap_servers=['localhost:9092'], value_serializer=json_serializer ) if name == 'main': fake = Faker() for i in range(0, 3): # Generate a fake JSON message name = fake.name() email = fake.email() city = fake.city() fake_message = { "name": name, "email": email, "city": city }

    <span class="hljs-comment"># Send fake JSON message to Kafka topic</span>
    <span class="hljs-built_in">print</span>(<span class="hljs-string">f'<span class="hljs-subst">{datetime.now()}</span>: Message = <span class="hljs-subst">{<span class="hljs-built_in">str</span>(fake_message)}</span>'</span>)
    producer.send(<span class="hljs-string">'test_topic'</span>, fake_message)
                                                          
    time.sleep(<span class="hljs-number">1</span>)</pre></div><p id="6594">And here is our consumer.py</p><div id="a19b"><pre><span class="hljs-keyword">import</span> json

from kafka import KafkaConsumer

if name == 'main': # Kafka Consumer consumer = KafkaConsumer( 'test_topic', bootstrap_servers='localhost:9092', auto_offset_reset='earliest' ) for message in consumer: print(json.loads(message.value))</pre></div>OK, now let’s start consumer and run producer to send some fake message for a sanity check.<div id="572f"><pre># Run producer (kafka_env) C:\Users\feng\Kafka\kraft>python producer.py 2023-02-25 18:48:41.143953: Message = {'name': 'Susan Best', 'email': '[email protected]', 'city': 'Kellytown'} 2023-02-25 18:48:42.160545: Message = {'name': 'James Wilson', 'email': '[email protected]', 'city': 'Lake Bryanfort'} 2023-02-25 18:48:43.177933: Message = {'name': 'Haley Brooks', 'email': '[email protected]', 'city': 'East Janetburgh'}

# Monitor consumer (kafka_env) C:\Users\feng\Kafka\kraft>python consumer.py {'name': 'Susan Best', 'email': '[email protected]', 'city': 'Kellytown'} {'name': 'James Wilson', 'email': '[email protected]', 'city': 'Lake Bryanfort'} {'name': 'Haley Brooks', 'email': '[email protected]', 'city': 'East Janetburgh'}</pre></div>Great, our Kafka Docker instance and simple applications are working as expected!Happy Reading!<div id="2213" class="link-block"> <a href="https://medium.com/@fengliplatform/membership"> <div> <div> <h2>Join Medium with my referral link - Feng Li</h2> <div><h3>Writing helps ourselves, sharing helps many. It started from study notes for myself with no pressure of perfection…</h3></div> <div>medium.com</div> </div> <div> <div style="background-image: url(https://miro.readmedium.com/v2/resize:fit:320/0*K9psL5RefQfuKkzr)"></div> </div> </div> </a> </div></article></body>

Install kafka-python <span class="hljs-built_in">package</span>

Install Faker <span class="hljs-built_in">package</span> to generate dummy messages

The AWS CLI Documentation You Really Wanted

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