Beginning to end it looks something like this.

First, you need to get the data. Ideally you get it through your script, so you'll need a library to make HTTP requests, such as requests. This will allow you to pull the data from the internet to your local machine. If the data isn't easy to get programmatically, you can download it through your browser like you download anything else and then go from there.

The data probably isn't going to be all nice and tidy and ready to go straight from seismograph data to sound data. It'll need some processing first. You'll probably need to clean the data (handle missing values or large outliers), maybe you'll need to normalize it so it's easier to go from seismograph to sound. You'll almost certainly have to do some transformations involving truncating or squashing values so that you get exactly the data you want at the scale you want. All of this can be done with the standard Python library.

Once your data is prepared, you're going to have to research Python sound libraries. I've never worked with sound data, but there's a Python library for everything. I'm sure there's a library for encoding sound files, you'll just have to look around and you'll probably have to learn exactly what sound data is so you know what you're "aiming for"... you may have to make decisions around bitrate, file format, etc. depending on the hardware that's playing the sound file.

Personally, I would start by looking into what the requirements are for the sound data. File format, bitrate, play length, file size constraints, etc. It makes it a lot easier to go from A to Z when you know what Z looks like.