Hey folks this is Dave Albert for a quick take. In this quick take, I’m going to talk to you about Jupyter notebooks. That’s J U P Y T E R.
If you’re not familiar with them, they’re very popular in the machine learning community. So Jupyter notebook is kind of like writing code, but instead of it being basically in a program is kind of like an a markdown wiki almost? I probably should have looked up the definition but I’m sure you’re able to do that. So you can write different chunks of code, execute them independently. And by saving that code then it’s always available so each different block of code can also reference any variables or functions that you’ve identified, created in one of the other blocks. And then that allows you did, you know reuse your code, obviously. But instead of having to rerun programs or say you’re using some sort of tool to query your database, you can actually keep your little experiments together. And then say you’ve got ad-hoc queries or reports that you need to run periodically. You can have them all together, run them very easily get the output directly into a web browser so basically spins up a little web server that you access locally you can also do them within datacenters as your has as your Jupiter or as your notebooks I think is what they call it. But it’s I don’t think that like VPN access works very well. So for our situation, we use port forwarding with our Kupernetes to connect directly to our database and can run our queries to understand our data by using the notebooks they’re available very easily.
So that means that I’ve got it on my laptop and my home computer. And if I ever have another device, it would be there as well. So every time I save, it’s immediately synced over to the rest of the devices. I mean, yeah, that’s how syncing software works. But it’s great to have that always available, easy to spin up because we can basically just change that port forward then you can run it against test or production I use environment or not environment but I use a variable define the environment that I’m currently working in. because we use environment within some within our collection names. So it’s easy to make, you know, one one change in that will cascade through all the different code blocks. It’s it’s definitely worth your while to spend maybe an hour learning how to do a Python notebook if that. So just forget that machine learning AI is where you may have heard of it. First, there’s just the bloody useful no matter who you are, what you do if you’re writing code and it’s not necessarily part of a specific application but more experiments or ad hoc things, you’re, you’re probably going to save yourself time. And it’s, it’s nice to use. It’s not, you know, it’s delightful.
Until next time, remember, any sufficiently advanced technology is indistinguishable from magic.