If you want to compress messages before producing them to Memphis.dev, you can manually compress the messages using a compression library like zlib or gzip and then send the compressed data to Memphis.dev. Here's a step-by-step guide on how to do this:
Step 1: Install the necessary libraries:
You'll need the memphis library for producing messages to Memphis and a compression library like zlib or gzip for message compression. You can install these libraries using pip:
from memphis import Memphis, Headers
from memphis.types import Retention, Storage
import asyncio
import zlib
Step 2: Prepare your message
Create the message that you want to send to Memphis. For example:
message = "This is the message you want to send to Kafka."
Step 3: Compress the message using zlib or gzip
Use the compression library to compress the message data:
compressed_message = zlib.compress(message.encode('utf-8')) # Use zlib for compression
# or
# compressed_message = gzip.compress(message.encode('utf-8')) # Use gzip for compression
Step 4: Produce the compressed message to Memphis.dev
await producer.produce(bytearray(compressed_message)) # you can send the message parameter as dict as well
Full example
from memphis import Memphis, Headers
from memphis.types import Retention, Storage
import asyncio
import zlib
async def main():
try:
memphis = Memphis()
await memphis.connect(host="localhost", username="root", password="memphis")
message = "This is the message you want to send to Kafka."
compressed_message = zlib.compress(message.encode('utf-8')) # Use zlib for compression
producer = await memphis.producer(station_name="memphis-test", producer_name="producer-test")
await producer.produce(bytearray(compressed_message)) # you can send the message parameter as dict as well
except Exception as e:
print(e)
finally:
await memphis.close()
if __name__ == '__main__':
asyncio.run(main())
This code demonstrates how to manually compress messages using zlib or gzip before sending them to Memphis. When consuming messages, you would need to decompress the messages using the same compression library you used for compression before processing the data.
