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:
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
:
{% code lineNumbers="true" %}
from memphis import Memphis, Headers
from memphis.types import Retention, Storage
import asyncio
import zlib
{% endcode %}
Create the message that you want to send to Memphis. For example:
{% code lineNumbers="true" %}
message = "This is the message you want to send to Kafka."
{% endcode %}
Use the compression library to compress the message data:
{% code lineNumbers="true" %}
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
{% endcode %}
{% code lineNumbers="true" %}
await producer.produce(bytearray(compressed_message)) # you can send the message parameter as dict as well
{% endcode %}
{% code lineNumbers="true" %}
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())
{% endcode %}
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.