#367 A New Cloud Computing Paradigm at Python Bytes

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Hello and welcome to Python Bytes, where we deliver Python news and headlines directly to your earbuds.
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This is episode 367, recorded January 16, 2024. And I am Brian Okken.
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And I'm Michael Kennedy.
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And I guess we do have a sponsor today, so that's awesome.
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But Michael, do you want to tell us why you're not?
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Yeah, for people who are listening, maybe they hear a slightly different setup for me.
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For people who might watch the video, well, that right there in the background is lovely and very icy Portland, Oregon.
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And so I'll go ahead and put this on the screen.
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People can check out if they feel like they can check out the YouTube stream at like one minute, 19 seconds.
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This is the entrance to my house, Brian.
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And it looks like an apocalypse.
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Just every, I would say every block or so, there's like a hundred foot tree that's fallen somewhere.
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And it's just taken out the power in so many ways.
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It's like it was now, it was 13, now it's 18 degrees Fahrenheit.
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So negative nine, something like that Celsius.
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No power, four or five days.
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Not a place for podcasting.
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So I'm hanging out here in a hotel with the family until the power comes back on.
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Hopefully today, fingers crossed.
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Well, hopefully, yeah.
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Hopefully there's actually quite a few people in Portland without power and did experience power outages and pipes bursting and things like that.
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And, you know, for people that are in parts of the country where they get like way colder than us, it might seem like we're just being wusses.
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But what we get here is often very heavy rain, heavy snow or freezing rain.
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And the freezing rain just weighs down trees and breaks power lines and stuff like that.
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Absolutely.
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And this had up to 100 mile an hour winds with these really old trees.
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And also just the city is not really built for it.
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We don't get it enough that they have infrastructures for it.
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So it's like, oh, it snowed three inches.
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So just good luck with that.
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We're not going to do anything, right?
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No salt, no gravel.
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Just hope that works out.
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So anyway, it's been all right.
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But yeah, different setup, Brian.
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So thanks everyone for the understanding.
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Indeed.
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And also I want to say thanks to Bright Data.
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We'll talk more about them for sponsoring the show.
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But let's talk about something contrarian, I guess you would say, Brian.
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Okay.
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You know, many people I'm sure have heard of 37 Signals, right?
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David Hennemeyer Hansen.
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He's the guy who created Ruby on Rails.
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Most notably, but there's also Basecamp and Heymail and all that kind of stuff, right?
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Yeah.
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So needless to say, they run a ton of SaaS products in the cloud.
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And I came across what I guess was more or less some kind of conclusion to a bunch of conversations
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and stuff they've been working on.
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And so I'll work my way backwards just a little bit.
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But it's pretty fascinating.
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And the headline on the post is, we have left the cloud.
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Brian, I thought we were all told to go to the cloud.
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I mean, we saw the picture of what happens when the clouds get angry.
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So I understand why you might leave the clouds.
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But more seriously, like clouds are supposed to save us.
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They save us money.
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They give us agility, et cetera, et cetera.
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Right?
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Yeah.
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So hence the contrarian aspect, right?
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Yeah.
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Like, I guess it's not like 37 Signals is the same sort of place as like a lot of startups.
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But, you know.
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That's true.
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If you're in, they do make that point.
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Like if you are an early stage startup where the costs are low, by all means, cloud it up.
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But as I guess one of the big lessons here is the more that you get like the cloud hooks in the abstract sense into your app, the more it might set you up for a tough time as you get bigger.
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Right?
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So let me get through this and we can talk a bit more about that.
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So they say we stand to save over $7 million in five years from our cloud exit.
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And so why do they not just say, well, that's 1.2 or 1. whatever it is, 1.1 million per year because of our cloud exit?
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Because what they did is they went and they bought.
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So when they said they left the cloud, they didn't mean just like we're not using Kubernetes or we're not using Lambdas and serverless.
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Like they are, they bought physical hardware.
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Okay.
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So they've got these, these big pallets.
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And what they did is they bought this Dell, 20 Dell R7 625 servers, which don't mean a lot to me, maybe due to some people.
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But it basically takes up like two server racks.
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And that means 4,000 CPUs, 7.7 terabytes of RAM and almost a half a petabyte of high speed SSD storage.
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And that cost them $600,000 to buy that, which is a lot of money.
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However, they were paying, like 1.2 million a year in cloud prices and cloud to AWS basically.
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And so after six months it's paid for.
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And the five years part is they expect this hardware to last them five years.
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And apparently it's super, super fast.
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So, it's, it's pretty interesting.
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I would really recommend people go through and read this, what some of the values were.
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And basically what they did is they said, we're going to buy like a really big server.
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I know it's a bunch of kind of CPUs and stuff, but they kind of clustered into like one compute cluster.
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And then they, they came up with this thing called, it's kind of like Kubernetes called Camel, which would work for Python.
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But I think originally they're deploying Rails apps on it and basically gives you zero downtime slices of this giant server.
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And the reason this really fascinates me is this, this whole philosophy here.
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It's, it's also not just, Hey, they're leaving the cloud because, you know, many people are running to the cloud, but it's also, they're getting a really huge server.
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Like one huge server rather than a whole bunch of small distributed servers, which also was like a little bit the way that, the cloud was initially sold, right?
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We'll get commodity hardware.
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You buy a bunch of little small slices all over the place.
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You can buy more small slices with auto scaling if you need.
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And instead they're like, no, this, and sort of along those same lines is I little while ago interviewed Mark Rusinovich, the CTO of Azure at Microsoft.
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Super cool guy, really, really smart, but also CTO of Azure.
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And he talked about how they started out with a bunch of small machines as well.
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And they're just getting bigger and bigger ones and slicing them up for tenants to be using them.
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So I think this is also a really interesting trend that we're going to see more of is like more, more big machines rather than a bunch of small machines that then maybe you slice up with Docker or Kubernetes or other things.
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And Brian, we've hardly even talked about this yet, but that has changed the way I got to type holding, pulling the mic in the wrong hand here for typing.
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That's changed the way that I'm running a lot of our infrastructure.
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So I've been thinking about this for a while and reading this stuff.
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I thought I'd make it the first topic of our show, but also I had eight servers for all the talk Python and Python bytes infrastructure, you know, some database server stuff.
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One that ran Python bytes, a bunch of services and a bunch of small machines.
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Right.
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And I'm like, you know, why am I messing with all these small machines?
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So I ended up consolidating like last week, all of that into one big, big server, just running a bunch of multi-tier Docker setups over there.
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And it's glorious, right?
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One machine runs great.
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There's a single command.
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I typed to upgrade like 13 different web apps all at once.
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That means upgrade their server infrastructure, upgrade their, potentially to ship their new dependencies to rebuild them.
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All of that kind of stuff.
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One command.
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Interesting.
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So yeah, it's really interesting.
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And it's really different.
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It let me like quickly and easily throw in some more things.
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And also I think it's better for security, right?
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Like I had like little, FastAPI apps that were just like little utility things running that I didn't pay this much attention to as I did the other apps.
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And so, you know, they just didn't, they didn't get their dependencies updated as frequently, frequently in their Python versions revved as frequently.
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And if something happened to them, right.
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It's on technically on the same VM, right?
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That's an issue.
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But now they're, they're all locked up behind like a Docker container.
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so it's a little more isolation as well.
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Anyway, it's this whole, I encourage people to read through.
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I put a bunch of different, parts of this story in for the 37 signals.
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We've left the cloud.
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It's worth reading.
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I'll just go through really quick, the five values.
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And then this is kind of a long segment.
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So I'll, I'll move us on.
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But here are the five values guiding our cloud exit.
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We value independence above all else.
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And being trapped in Amazon cloud is not great.
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We serve the internet.
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This business owes its entire existence to societal and economic aberration.
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That is the internet in a positive way.
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And we don't want to just be locked up behind a few hyperscalers.
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We want to be kind of just on the internet on our own terms, spend money wisely.
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Even if you have lots of money, you know, they're getting better value for money.
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leading the way, the cloud has been sold as the answer to SAS companies.
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We're not so sure.
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And they seek adventure and you bet that they do.
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So anyway, it's not leaving data centers.
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They have that in a managed data center.
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They just have it on hardware that they own.
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So anyway, what do you think about all this?
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so a lot of this is, I think it's interesting that, that it affects you even like that you, but you're, you're not okay.
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When you said you, you put them all on one machine, you're not, it's, you don't have like a, a server in your
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basement or something.
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No, no.
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So what I did is I, instead of having a bunch of small VMs at digital ocean, I bought one big VM.
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Okay.
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The one I have right now is like eight gigs, four CPUs, but I'm pretty sure I'm going to
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switch to like 16 gigs and eight CPUs.
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And even that would be cheaper than what I was doing before.
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And it's still, it, and the other thing that's interesting or in danger of going super long in
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this, but, but because all those different apps are sharing, let's say the final destination of
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eight CPUs, there's spikes in performance are not at the same time.
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Like what makes talk Python or Python bytes spike in, in load is not the same that what
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makes the courses spike on load, like a new course release or like black Friday or something
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like that is very unlikely to intersect with when a podcast is released because I'm busy
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doing one or the other.
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Right.
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And so they basically has access to all eight cores instead of that one gets two cores, that
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one gets one core.
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And even though they're sharing like basically in aggregate, it's the same number because the
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spikes don't line up, they get more capacity for whatever they're doing.
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It's pretty interesting.
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Yeah.
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Okay.
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It is interesting.
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Back to you.
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Well, let's, let's completely go to a short topic.
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And I'd like to talk about little tiny scripts or maybe big scripts, but single file applications.
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So single file scripts.
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So I wanted to talk about PEP 723 and that is inline script metadata.
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And one of the things that we've noticed come recently in this, this is authored, it's interesting
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author.
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So the author is Ofec Lev.
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I think that's how you say his name.
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He's the dude from hatch.
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So hatch is, I guess, in packaging.
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So this is around packaging.
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And the idea is that you've got a script has depend, might have dependencies also, and it
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also might depend on Python and how we can't really tell Python currently that a script needs
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a dependency or a particular version of Python.
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So this is an attempt to kind of fix that.
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And there's some, some motivation and stuff at the top that I like, you know, kind of
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skimmed through a little bit.
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No, I read it.
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But the real at the end is we're going to put stuff like pyproject.toml, but
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you can do it in a script.
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And this isn't there yet, but there's an example where you just sort of do a pound sign and then
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like a few slashes and then say script.
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And then after that, you can put a little bit of like toml right in your, as a comment.
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And the idea is something like a pip.
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Right.
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This is like the world's craziest docstring sort of thing.
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Right.
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Almost.
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I don't understand.
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So supposedly there's, there's reasons behind this syntax.
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It's the weirdest syntax I've ever seen, but maybe it's just, it's not quite shebang, but
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it's kind of shebang ish.
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Yeah.
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But like the, in their example, they're saying, okay, well, you've got a little, a little
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script that just requires, you know, and this is going to be common.
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I think actually requires requests and rich.
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So, cause it's going to like grab something off the internet and it's going to print some
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stuff and wants to do it with color and whatever.
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But how do you do that without packaging it?
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And, and here's one way is to just tell Python that it needs these other things.
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So there's a, it's, I don't really completely understand this.
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Like how, what are the backend, what's going to happen?
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What is, I think the different tools will treat this different because my question is really,
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where are these dependencies going to be installed at?
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Is it like, if I just say, I guess it depends on the thing.
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So if you're going to do, if it hatched for instance, or pipX might handle this.
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So if I say pipX, you know, run this script and it finds this, it'll probably create a pipX
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virtual environment area.
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And hatch will do the same thing in a different manner.
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But behind the scenes grab, like create a little virtual environment.
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This kind of, it mostly, it seems like it's hiding virtual environment.
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And dependency installs from users, but it's probably needed.
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So anyway, what do you think of this?
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It gets interesting.
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Similar to installed, as Liz is pointing out, sounds very similar to installed that we talked
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about not too long ago.
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And I think it solves an interesting problem.
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All of these do have that, that little bit of a bootstrap that has to happen, right?
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For, or something for, for this work, it's not built into Python, right?
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And so you've got to have like one library installed that then you can use to run and kick off all the other runs.
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But if, if you somehow make that happen or get a, get your company to agree, like we're all going to have this foundation and then it just runs.
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I think that's pretty cool.
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And I think OFAC is killing it, right?
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He's, he's being really creative and working a lot of different things.
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And this is a PEP, right?
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So if this was built into Python, then, then all of a sudden, yeah, we can have, have it run.
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So I, okay.
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So for some reason I flew right over my head that it's a PEP and not just an extension to Hatch.
00:15:22.480 --> 00:15:28.040
So yeah, this, this is going to be, this could be super, super important.
00:15:28.040 --> 00:15:30.320
And it was last updated in December.
00:15:30.320 --> 00:15:31.880
It's accepted now.
00:15:31.880 --> 00:15:35.680
I'm not sure how long it's been accepted, but it's around the packaging.
00:15:35.680 --> 00:15:44.480
So PEPs with packaging are interesting because we don't really have to wait for, once they're accepted, we don't really have to wait for a release of Python.
00:15:44.480 --> 00:15:52.460
Because things like PEP and Hatch and other things don't have the same, you know, release cadence as Python.
00:15:52.460 --> 00:16:01.920
So this could be like, there's a note here that says it's not going to be declared final until at least a couple of tools utilize it.
00:16:01.920 --> 00:16:04.400
So, so far, there's no tools that utilize it.
00:16:04.400 --> 00:16:08.040
But their example is possibly pip run and pip X.
00:16:08.040 --> 00:16:10.860
So, and, and probably Hatch as well.
00:16:10.860 --> 00:16:13.040
It's considering who wrote it.
00:16:13.040 --> 00:16:17.720
But yeah, yeah, I would imagine it might show up and might get support from Hatch as well.
00:16:17.720 --> 00:16:18.160
Yeah.
00:16:18.160 --> 00:16:18.440
Yeah.
00:16:18.440 --> 00:16:20.280
Funny, funny comments out there in the audience.
00:16:20.400 --> 00:16:23.560
About being Rust inspired indeed.
00:16:23.560 --> 00:16:26.460
Brian, you want to know what else is inspiring?
00:16:26.460 --> 00:16:27.180
What?
00:16:27.180 --> 00:16:29.460
Our sponsor, Bright Data.
00:16:29.460 --> 00:16:30.220
Yeah.
00:16:30.220 --> 00:16:30.980
Indeed.
00:16:30.980 --> 00:16:35.380
So I just want to say thank you to Bright Data for supporting the show.
00:16:35.380 --> 00:16:38.900
Check them out at pythonbytes.fm/bright data.
00:16:38.900 --> 00:16:40.760
And there's, go ahead, yeah.
00:16:40.760 --> 00:16:42.940
Do we want to put their stuff on the?
00:16:42.940 --> 00:16:43.860
We do.
00:16:43.860 --> 00:16:47.880
And somehow I did not quite, we didn't quite do it.
00:16:47.880 --> 00:16:48.440
There we go.
00:16:49.360 --> 00:16:49.760
Awesome.
00:16:49.760 --> 00:16:50.000
Yeah.
00:16:50.000 --> 00:16:54.120
So there's tons and tons of data out on the internet.
00:16:54.120 --> 00:16:56.020
Unimaginable amounts of data, right?
00:16:56.020 --> 00:17:00.220
And we're lucky to live in a time where so much of this is behind structured APIs.
00:17:00.220 --> 00:17:04.480
And you can go and access it with HTTPX or requests or whatever.
00:17:04.480 --> 00:17:08.740
But the truth is that most of the data is not served up over clean APIs.
00:17:08.740 --> 00:17:12.700
It's just sitting there on a web page as gnarly HTML.
00:17:12.700 --> 00:17:14.440
Maybe it's even worse than that.
00:17:14.440 --> 00:17:20.180
Maybe it's obscured behind some front-end framework like React, where when you actually look at the
00:17:20.180 --> 00:17:22.600
HTML, it just says, pull in the React app.
00:17:22.600 --> 00:17:23.500
Good luck with that.
00:17:23.500 --> 00:17:25.740
And then something else happens somewhere along the way, right?
00:17:25.740 --> 00:17:28.000
So getting access to that data can be hard.
00:17:28.000 --> 00:17:28.760
What's the answer?
00:17:28.900 --> 00:17:31.080
Well, web scraping, everyone says.
00:17:31.080 --> 00:17:31.760
Yes.
00:17:31.760 --> 00:17:32.440
True.
00:17:33.220 --> 00:17:36.900
But just like you wouldn't want to set up your production infrastructure in your home office,
00:17:36.900 --> 00:17:42.640
running web scraping jobs on a single computer, even in a data center, can lead to your program
00:17:42.640 --> 00:17:50.160
being potentially unreliable with data pinned to whatever source you're accessing thinks you're
00:17:50.160 --> 00:17:50.800
located, right?
00:17:50.840 --> 00:17:55.800
So maybe there's different data if you're in the EU than if you're in Ohio, but your computer's in Ohio,
00:17:55.800 --> 00:17:56.440
so there you go.
00:17:56.440 --> 00:18:01.220
Or, you know, it gets blocked because of rate limiting or other types of things like that,
00:18:01.220 --> 00:18:01.440
right?
00:18:01.440 --> 00:18:05.300
So if you need to do professional web scraping, check out Bright Data.
00:18:05.300 --> 00:18:11.520
They have award-winning proxy network with millions of different places to access data from.
00:18:11.520 --> 00:18:16.760
And powerful web scrapers, they have even ready-to-go data sets you can download.
00:18:16.760 --> 00:18:20.620
So they've already curated these data sets, and you can just access them.
00:18:20.620 --> 00:18:24.180
And get updates from them and not even do web scraping, which is awesome.
00:18:24.180 --> 00:18:25.720
So they've got a whole marketplace for that.
00:18:25.720 --> 00:18:31.040
And everyone knows, we're probably going to come back to it some more, privacy-conscious
00:18:31.040 --> 00:18:32.540
stuff that I really care about.
00:18:32.540 --> 00:18:36.560
And they are both CCPA and GDPR compliant.
00:18:36.560 --> 00:18:41.620
They have low-code solutions, as well as Python programming models with asyncioM Playwrights.
00:18:41.620 --> 00:18:46.380
So if you have serious data needs and those websites that have the data don't offer an API,
00:18:46.380 --> 00:18:48.160
then you need to check out Bright Data.
00:18:48.480 --> 00:18:52.040
Give them a try at pythonbytes.fm/brightdata.
00:18:52.040 --> 00:18:55.040
And please use that URL so you know that they heard from us.
00:18:55.040 --> 00:18:56.920
Thank you to Bright Data for supporting the show.
00:18:56.920 --> 00:18:59.660
Links in your podcast player show notes.
00:18:59.660 --> 00:19:01.120
So pretty awesome.
00:19:01.120 --> 00:19:02.620
All right.
00:19:02.620 --> 00:19:05.160
Back to the next thing.
00:19:05.740 --> 00:19:07.300
So this is super exciting.
00:19:07.300 --> 00:19:10.300
And it came, I believe this was sent in by Balaz.
00:19:10.300 --> 00:19:10.660
Let me check.
00:19:10.660 --> 00:19:11.600
Yeah, Balaz sent this over.
00:19:11.600 --> 00:19:13.680
Thank you, Balaz, for pointing this out.
00:19:13.680 --> 00:19:17.420
So I've had Fyodor Fitzner on Python before.
00:19:18.480 --> 00:19:21.040
And we've talked about Flet.
00:19:21.040 --> 00:19:27.320
And Flet is basically Flutter, but with a Python programming API, right?
00:19:27.320 --> 00:19:32.000
Flutter is actually how we built the apps at Talk Python, right, for courses.
00:19:32.000 --> 00:19:33.220
Super cool framework.
00:19:33.220 --> 00:19:34.640
But you're writing Dart.
00:19:35.040 --> 00:19:38.160
And Dart is good, but it's not Python, right?
00:19:38.160 --> 00:19:41.820
And so it'd be great to be able to write that kind of code.
00:19:41.820 --> 00:19:43.940
Here's an example, by the way, Brian.
00:19:43.940 --> 00:19:45.520
We talked about fast UI.
00:19:45.520 --> 00:19:52.900
And I said, oh, that reminds me, this sort of hierarchical code structure reminds me of Flutter, right?
00:19:53.040 --> 00:19:58.320
And so here's the same thing, the Flutter UI, but in Python code instead of Dart.
00:19:58.320 --> 00:20:00.520
And the link for this code is in the show notes.
00:20:00.520 --> 00:20:01.680
You can check it out, right?
00:20:01.680 --> 00:20:05.980
So the big news is you can now build APKs for Android.
00:20:05.980 --> 00:20:10.040
And for those of you who have not suffered the indignity of the app stores,
00:20:10.040 --> 00:20:15.860
the way you get something into the Google Play store is you build what's called an APK.
00:20:15.860 --> 00:20:17.440
And then you send them that.
00:20:17.440 --> 00:20:18.520
They process it.
00:20:18.520 --> 00:20:21.780
And then that's what gets shipped out to run on the phones on Android.
00:20:22.000 --> 00:20:27.480
So this means even though Flutter built Flutter apps, you couldn't really deploy it.
00:20:27.480 --> 00:20:31.400
You could kind of get the Flutter app and then put your Python code on there.
00:20:31.400 --> 00:20:32.560
But that's not like your app.
00:20:32.560 --> 00:20:35.200
That's like Jupyter or something like that kind of.
00:20:35.200 --> 00:20:36.720
So this is awesome.
00:20:36.720 --> 00:20:40.800
This means that people can now build apps that go in the app store,
00:20:40.800 --> 00:20:45.780
at least for Android, with Flutter and Flutter and Python in particular.
00:20:45.780 --> 00:20:47.360
We'll see about iOS.
00:20:47.360 --> 00:20:48.080
It's on the roadmap.
00:20:48.080 --> 00:20:49.520
So super exciting.
00:20:49.520 --> 00:20:50.960
Yeah.
00:20:50.960 --> 00:20:59.820
I mean, I would have used Flutter if I was sure I could get it to build and ship and on the different things.
00:20:59.820 --> 00:21:03.500
I'd much rather have done that than use Flutter or a Dart, you know, for Flutter.
00:21:03.500 --> 00:21:06.280
But, you know, you got to work with the building blocks you got.
00:21:06.280 --> 00:21:07.480
And this one just got better.
00:21:07.480 --> 00:21:08.280
So exciting.
00:21:08.280 --> 00:21:08.900
Yeah.
00:21:09.260 --> 00:21:10.180
Oh, also really quick.
00:21:10.180 --> 00:21:15.160
In those show notes, there's a video by this guy called Neural9.
00:21:15.160 --> 00:21:16.260
His channel is called Neural9.
00:21:16.260 --> 00:21:18.840
Walking through the steps to do that, all that build.
00:21:18.840 --> 00:21:19.700
So you want to see how it works.
00:21:19.700 --> 00:21:21.200
You can watch that eight-minute video.
00:21:21.580 --> 00:21:21.680
Cool.
00:21:21.680 --> 00:21:21.680
Cool.
00:21:21.680 --> 00:21:22.160
Neat.
00:21:22.160 --> 00:21:25.420
So that's for Android apps.
00:21:25.420 --> 00:21:30.980
For command line, normal command line stuff, I was going to talk about Harlequin.
00:21:31.400 --> 00:21:39.360
So there's a lot of people that use SQL and SQLite for different purposes, of course, for databases.
00:21:39.840 --> 00:21:46.760
But to take a look at your SQLite data, there is an IDE called Harlequin.
00:21:46.760 --> 00:21:48.420
I don't think we've covered it.
00:21:48.420 --> 00:21:57.380
But it's an open source Python project that it looks like it's pretty cool.
00:21:57.380 --> 00:22:03.620
It's got like on the, we're showing on the screen, the little snippet or screenshot.
00:22:03.620 --> 00:22:08.440
You've got kind of your tables, your data catalog on the left panel.
00:22:08.840 --> 00:22:13.680
They've got a query editor and then some query results at the bottom right.
00:22:13.680 --> 00:22:18.780
And it actually looks pretty slick for like quickly going through some data.
00:22:18.780 --> 00:22:24.940
It looks like it has hooks to go into DuckDB and SQLite.
00:22:24.940 --> 00:22:26.620
That's why I brought up SQLite.
00:22:26.620 --> 00:22:28.800
And I'd probably use it for SQLite.
00:22:28.800 --> 00:22:29.580
I haven't used DuckDB.
00:22:29.580 --> 00:22:35.000
Yeah, for people who don't know, DuckDB is also in process, very much like SQLite,
00:22:35.000 --> 00:22:36.960
but it's columnar instead of row-based.
00:22:36.960 --> 00:22:38.760
So they're kind of in the same way.
00:22:38.760 --> 00:22:39.200
Oh, okay.
00:22:39.200 --> 00:22:39.640
I guess.
00:22:39.640 --> 00:22:40.120
Yeah.
00:22:40.120 --> 00:22:40.600
Okay.
00:22:40.600 --> 00:22:45.020
Yeah, I haven't used it, but definitely SQLite use that a lot.
00:22:45.320 --> 00:22:48.100
So this is kind of fun.
00:22:48.100 --> 00:22:49.600
I like command line tools.
00:22:49.600 --> 00:22:50.580
This looks neat.
00:22:50.580 --> 00:22:52.960
It's kind of a short topic.
00:22:52.960 --> 00:22:57.520
Just, hey, this is a command line interface for SQLite or DuckDB.
00:22:57.520 --> 00:22:59.960
And that's fun.
00:22:59.960 --> 00:23:03.360
It looks like it runs on Linux, Mac, and Windows, which is cool.
00:23:04.980 --> 00:23:11.680
But I was also, one of the things I've noticed is in, like, for instance, a lot of Django tutorials,
00:23:11.680 --> 00:23:14.940
Django starts with SQLite.
00:23:14.940 --> 00:23:17.040
And you, I mean, by default, it does that.
00:23:17.040 --> 00:23:20.120
And I think that you can, and then you can specify other databases.
00:23:20.200 --> 00:23:26.500
But I noticed today a discussion on Mastodon that I wanted to bring up kind of SQLite related.
00:23:26.500 --> 00:23:32.460
Jeff Triplett posted a post by somebody else, Anze.
00:23:33.460 --> 00:23:40.420
But, okay, Jeff's comment is, this is a nice write-up about using SQLite in production with pitfalls and open questions.
00:23:40.420 --> 00:23:46.800
I cringe whenever I see some Django Python luminary recommending people use SQLite in production.
00:23:46.800 --> 00:23:48.880
I don't care how good you are.
00:23:48.880 --> 00:23:51.620
You won't get it right, even if you think you did.
00:23:51.620 --> 00:23:55.380
Anyway, so interesting commentary there.
00:23:55.380 --> 00:24:01.500
So Anze's post was, I wrote a blog post about using SQLite in production and dealing with DB.
00:24:02.040 --> 00:24:03.840
DB is closed errors.
00:24:03.840 --> 00:24:05.580
I'm happy to hear your thoughts.
00:24:05.580 --> 00:24:12.880
So the article is called Django SQLite and Databases Locked Error, and it walks through those.
00:24:12.880 --> 00:24:20.200
And kind of the reality is Django doesn't, I guess, lock the database when it reads correctly.
00:24:20.200 --> 00:24:21.480
The transactions are weird.
00:24:21.480 --> 00:24:34.680
And a lot of the discussion around this really is if you're using SQLite for a database that's mostly read-only, most people are just reading stuff, it'll probably work fine.
00:24:34.680 --> 00:24:35.720
And it might work great.
00:24:35.720 --> 00:24:39.460
And it might be way less hassle than doing Postgres or something else.
00:24:39.680 --> 00:24:47.580
But if there are a lot of transactions that are writing to it, if you have multiple writers, then you've got issues.
00:24:47.580 --> 00:24:51.640
So just thought this was an interesting discussion.
00:24:51.640 --> 00:24:52.580
I wanted to bring it up.
00:24:52.580 --> 00:24:53.540
Yeah.
00:24:53.780 --> 00:24:57.900
I think it really depends on the type of app you got.
00:24:57.900 --> 00:25:00.160
Is it an analytics thing that's writing like crazy?
00:25:00.160 --> 00:25:03.040
Or is it basically like the database here blog?
00:25:03.440 --> 00:25:09.280
Right where it's really just you make an entry once a week if you're a good blogger.
00:25:09.280 --> 00:25:10.160
You know what I mean?
00:25:10.160 --> 00:25:10.820
That kind of thing.
00:25:10.820 --> 00:25:12.460
And then it's all reads.
00:25:12.460 --> 00:25:13.400
Probably fine.
00:25:13.400 --> 00:25:13.840
Right.
00:25:13.840 --> 00:25:23.340
So somewhere in the middle, I guess, like you can sort of turn that bar or watch that gauge turn from green to red as it gets closer to like a full analytics system.
00:25:23.340 --> 00:25:24.660
But yeah, it's pretty interesting.
00:25:24.660 --> 00:25:25.220
Yeah.
00:25:25.220 --> 00:25:26.860
Hey, interesting discussion.
00:25:26.860 --> 00:25:27.840
Indeed.
00:25:27.840 --> 00:25:28.320
All right.
00:25:28.320 --> 00:25:28.980
What you got?
00:25:28.980 --> 00:25:30.360
Oh, we're done.
00:25:30.360 --> 00:25:31.020
We're done.
00:25:31.020 --> 00:25:31.720
We're done.
00:25:31.720 --> 00:25:33.280
But we're not done because I have many extras.
00:25:33.280 --> 00:25:33.920
Do you have extras?
00:25:33.920 --> 00:25:36.360
I've got just a couple extras.
00:25:36.360 --> 00:25:40.340
So since I've got my screen up, I'll run through a couple extras.
00:25:40.340 --> 00:25:42.940
I've been I've kind of start.
00:25:42.940 --> 00:25:51.500
I started Python people podcast last summer and then kind of ran out of time trying to get the pytest course done.
00:25:51.500 --> 00:25:54.580
And so now I'm coming back and cleaning up some things.
00:25:54.580 --> 00:25:58.180
So there's there's a few recent episodes that finally came out.
00:25:58.180 --> 00:26:01.680
So like I stopped in October and then picked it up in January.
00:26:01.680 --> 00:26:06.640
So we've got Will Vincent and Julian Seguera and Pamela Fox episodes out now.
00:26:06.640 --> 00:26:07.740
So check those out.
00:26:07.740 --> 00:26:08.460
Oh, excellent.
00:26:08.460 --> 00:26:09.020
Yeah.
00:26:09.020 --> 00:26:09.900
Those are all great people.
00:26:09.900 --> 00:26:13.600
And many of them have been on this show as well.
00:26:13.600 --> 00:26:14.660
So very cool.
00:26:14.660 --> 00:26:15.880
Nice to see these going there.
00:26:15.880 --> 00:26:21.380
They provide a really interesting look, like really out of bounds looks into what people are doing.
00:26:21.580 --> 00:26:25.640
You know, like you and Paul talked a lot about lacrosse.
00:26:25.640 --> 00:26:26.040
Right.
00:26:26.040 --> 00:26:30.820
And empowering women and and not not the next PEP.
00:26:30.820 --> 00:26:32.060
And that was really interesting.
00:26:32.060 --> 00:26:33.100
So keep it going.
00:26:33.100 --> 00:26:42.080
Some of the fun bits are to try to try to talk to kind of dig deeper into stuff that like I normally don't ask about in.
00:26:42.080 --> 00:26:42.700
Yeah.
00:26:42.700 --> 00:26:44.980
Like, for instance, Julian Seguera.
00:26:44.980 --> 00:26:47.420
Julian's a really pretty positive person.
00:26:47.420 --> 00:26:51.540
So I poked at that a bit and tried to ask him, like, really, how did you get this mindset?
00:26:51.660 --> 00:26:53.580
I mean, clearly bad stuff must happen to you.
00:26:53.580 --> 00:27:00.460
And so we talk about his, you know, how does he get through it and, you know, keep maintaining a positive mindset.
00:27:00.460 --> 00:27:01.400
So it's good.
00:27:01.400 --> 00:27:03.680
Anyway, what are your extras for us?
00:27:03.680 --> 00:27:05.460
Let's see if I can find him here.
00:27:05.460 --> 00:27:05.860
Okay.
00:27:05.860 --> 00:27:06.560
Page find.
00:27:06.560 --> 00:27:07.900
Yes, that's the first one.
00:27:07.900 --> 00:27:08.460
Page find.
00:27:08.460 --> 00:27:11.840
So, Brian, you and I, we both Hugo, right?
00:27:11.840 --> 00:27:12.260
Yeah.
00:27:12.260 --> 00:27:14.140
Hugo is awesome.
00:27:14.140 --> 00:27:17.500
Go Hugo for people who don't know.
00:27:17.500 --> 00:27:18.940
Go Hugo.io.
00:27:18.940 --> 00:27:19.540
That's right.
00:27:20.520 --> 00:27:26.820
Super, super cool way to build static websites, not just blogs, but static websites that are really, really powerful.
00:27:26.820 --> 00:27:30.480
And I learned about this one from Mark Little.
00:27:30.480 --> 00:27:36.720
He also does a ton of stuff with Hugo and said, hey, you should check out page find.
00:27:36.720 --> 00:27:38.540
So what is this?
00:27:38.540 --> 00:27:39.040
I have no idea.
00:27:39.040 --> 00:27:47.020
So page find, this is not just a Hugo thing, but for all static sites, it's a fully static search library, right?
00:27:47.020 --> 00:28:00.940
So for static sites, whether this is Flask Freeze or Hugo or Pelican or whatever, this is like a post build step thing that runs and it indexes all of your HTML or the parts that you tell it to index.
00:28:01.400 --> 00:28:04.800
Or tell it to, you know, you can basically say, don't include this part or whatever.
00:28:04.800 --> 00:28:07.320
And it's no configuration.
00:28:07.320 --> 00:28:08.860
It has rich filtering.
00:28:08.860 --> 00:28:11.320
It has custom sorting attributes.
00:28:11.960 --> 00:28:18.960
And the way it structures, what it does basically is JavaScript and it has an index that then the JavaScript reads in.
00:28:18.960 --> 00:28:21.040
But the index is broken into a bunch of pieces.
00:28:21.040 --> 00:28:26.180
So the front end stuff can like pull just little bits of it and not pull all the results back basically, right?
00:28:26.640 --> 00:28:34.980
So I added this over to my website where if you're over here, like Brian, we could see what I said about AI and check that out.
00:28:34.980 --> 00:28:35.420
Isn't that awesome?
00:28:35.420 --> 00:28:38.780
So it finds all the different things that we could be talking about.
00:28:38.780 --> 00:28:48.640
But it also like in my document, in my markdown, I have like H1, H2, H3, and it will actually subdivide the results into sections.
00:28:48.640 --> 00:28:53.520
Like what is in this section marked by H2 on this one page?
00:28:53.520 --> 00:28:54.620
Oh, that's pretty cool.
00:28:54.900 --> 00:28:55.740
That's really cool, right?
00:28:55.740 --> 00:29:05.180
And it also does things like, I don't know if I can see any examples here, but if you type Y-O, it'll do like you, yourself, et cetera.
00:29:05.180 --> 00:29:07.240
So it's not even just like exact word matching.
00:29:07.240 --> 00:29:09.100
It's like a really smart search engine.
00:29:09.100 --> 00:29:17.820
And all it takes is just running a script for like a couple of seconds after you build your static site and then dropping the output into like a known location.
00:29:17.820 --> 00:29:18.740
Is that cool or what?
00:29:18.740 --> 00:29:19.700
That's very cool.
00:29:19.700 --> 00:29:25.720
It's one of the issues I've had when switching to a static site is not knowing how to deal with the search part.
00:29:25.720 --> 00:29:26.540
Yeah.
00:29:26.540 --> 00:29:27.780
So I was psyched when Mark sent this over.
00:29:27.780 --> 00:29:29.240
I'm like, yes, this is going in.
00:29:29.240 --> 00:29:29.760
Yeah.
00:29:29.980 --> 00:29:34.720
The other part that I'm trying to figure out is how to get a decent contact form.
00:29:34.720 --> 00:29:37.500
So that's still to be determined.
00:29:37.500 --> 00:29:38.280
Yeah.
00:29:38.280 --> 00:29:40.120
I don't think Pagefind is going to help with that, but this is cool.
00:29:40.120 --> 00:29:40.880
This is really cool.
00:29:40.880 --> 00:29:42.100
So I recommend it.
00:29:42.100 --> 00:29:43.340
I'll add it to my stuff too.
00:29:43.340 --> 00:29:43.700
Neat.
00:29:44.040 --> 00:29:45.900
It's incredibly fast.
00:29:45.900 --> 00:29:49.860
Like search for AI and I'm on like hotel Wi-Fi and it's nearly instant.
00:29:49.860 --> 00:29:50.400
Right.
00:29:50.400 --> 00:29:55.380
So that's, that is super, super cool where there's a lot of sites, even static sites.
00:29:55.380 --> 00:29:57.080
You'll be like searching, searching.
00:29:57.080 --> 00:29:58.360
You'll see the little spinner.
00:29:58.360 --> 00:29:59.220
You're like, what is it doing?
00:29:59.220 --> 00:30:00.380
Like, why is this search slow?
00:30:00.380 --> 00:30:01.840
No, it should be instant.
00:30:01.840 --> 00:30:02.360
Right.
00:30:02.360 --> 00:30:08.140
And that's, you know, very much in line with like plugging something like this into Hugo means like it's still instant.
00:30:08.140 --> 00:30:08.420
All right.
00:30:08.420 --> 00:30:09.220
I got a few more.
00:30:09.220 --> 00:30:10.040
Let's, let's blaze them.
00:30:10.500 --> 00:30:10.820
Okay.
00:30:10.820 --> 00:30:16.100
This is not to encourage people like more of a, just an interesting, Hey, careful.
00:30:16.100 --> 00:30:18.540
We've got PyPI and pip.
00:30:18.540 --> 00:30:20.640
The JavaScript world hasnpm.
00:30:20.640 --> 00:30:27.880
There's an article called when everything becomes too much, the npm package chaos of 2024.
00:30:27.880 --> 00:30:37.620
An npm user named Patrick JS launched a troll campaign with a package called everything that depended on every npm package there.
00:30:40.100 --> 00:30:45.800
So when you install it, it tries to install the, you know, millions of npm packages.
00:30:45.800 --> 00:30:48.080
And it just, it destroyed it.
00:30:48.080 --> 00:30:54.540
Like, cause people were installing it and, it was just taking too much resources and so on.
00:30:54.540 --> 00:30:56.600
So the follies of package management.
00:30:56.600 --> 00:30:57.060
How's that?
00:30:57.060 --> 00:30:57.800
Yeah.
00:30:57.800 --> 00:30:58.320
Nice.
00:30:58.320 --> 00:30:59.160
All right.
00:30:59.160 --> 00:31:00.320
I'll get a little out of order here.
00:31:00.480 --> 00:31:11.300
So Matthew Feikert wanted us, and we're happy to do so, announce that the SciPy conference, is coming and will be in beautiful Tacoma, Washington this year.
00:31:11.760 --> 00:31:16.100
So if you're interested, check that out and put a link to that.
00:31:16.100 --> 00:31:24.080
And the last thing is I wrote an essay called unsolicited advice from Mozilla and Firefox about four things.
00:31:24.180 --> 00:31:40.860
I think, you know, three things I think they did wrong and four things I think they could do to like absolutely both change the way that, the place of Firefox in the market and alleviate their, their insane dependency on Google.
00:31:40.860 --> 00:31:42.720
Like I'm not anti-Google.
00:31:42.720 --> 00:31:44.240
I, I do stuff with Google.
00:31:44.240 --> 00:31:53.460
I love YouTube, things like that necessarily, but I don't think they're congruent with Python, with, Firefox's focus on privacy very much.
00:31:53.460 --> 00:32:01.500
And also 95% of your company's revenue from one deal with one company that's kind of at a whim could just change their mind.
00:32:01.500 --> 00:32:02.680
That's not a great place to be.
00:32:02.680 --> 00:32:03.980
I'd like to see Firefox doing well.
00:32:03.980 --> 00:32:09.080
So I thought a lot about it and wrote about it, including they should just lie about their user agent, right?
00:32:09.080 --> 00:32:16.200
Like when a website says this site runs best on Chrome and using this crappy old browser, we don't know about, you know why you never see that on Vivaldi or Brave?
00:32:16.200 --> 00:32:19.260
Because their user agent is identical to Chrome.
00:32:19.260 --> 00:32:21.820
So when you get to the website, like, oh, this is my favorite one.
00:32:21.820 --> 00:32:22.180
Perfect.
00:32:22.180 --> 00:32:23.140
We're good to go.
00:32:23.140 --> 00:32:23.520
Right.
00:32:23.520 --> 00:32:25.400
How many people leave Firefox?
00:32:25.400 --> 00:32:29.300
Cause when they get to a site, it says, this doesn't work well, you need to go get this other browser.
00:32:29.300 --> 00:32:29.840
Yeah.
00:32:29.840 --> 00:32:34.060
It would stop saying that if Firefox just said, Hey, our, we're Chrome, you know, things like that.
00:32:34.060 --> 00:32:34.220
Right.
00:32:34.220 --> 00:32:35.660
And sure.
00:32:35.660 --> 00:32:36.660
It would hurt a little.
00:32:36.660 --> 00:32:37.680
It would hurt their pride.
00:32:37.800 --> 00:32:41.600
But people leave Firefox because the website will refuse to run.
00:32:41.600 --> 00:32:42.140
Right.
00:32:42.140 --> 00:32:42.620
Yeah.
00:32:42.620 --> 00:32:47.960
And if, if it, it probably would work, but if it's going to refuse to work, then it's not going to work.
00:32:47.960 --> 00:32:48.320
Right.
00:32:48.320 --> 00:32:48.940
Things like that.
00:32:48.940 --> 00:32:50.620
So anyway, this is, I think it's a really fun article.
00:32:50.620 --> 00:32:52.180
I had a lot of fun thinking about it.
00:32:52.180 --> 00:32:53.120
So people can check that out.
00:32:53.120 --> 00:32:59.880
And I think, I don't want to dwell on this too much, but the, there are like a lot of internal sites stuff.
00:32:59.880 --> 00:33:05.360
So a lot of people, do internal tools at companies and the, they'll do that.
00:33:05.360 --> 00:33:11.440
They'll be like, it should use Chrome and somebody will try it with Firefox and they'll be like, Oh, it doesn't work.
00:33:11.440 --> 00:33:12.980
And it probably does.
00:33:12.980 --> 00:33:15.520
It just, it just blocks it for the heck of it.
00:33:15.520 --> 00:33:15.880
So.
00:33:15.880 --> 00:33:16.540
Exactly.
00:33:16.540 --> 00:33:17.900
And no one's going to update that site.
00:33:17.900 --> 00:33:18.460
Right.
00:33:18.540 --> 00:33:19.880
It's just, yeah.
00:33:19.880 --> 00:33:24.140
Another thing that's just maybe interesting to put on people's radar is another thing.
00:33:24.140 --> 00:33:37.920
a friend of mine co-founded is this thing called Island, which is like a enterprise browser meant just for like giving enterprises, super interesting control over things like that.
00:33:37.920 --> 00:33:38.600
You're just talking about.
00:33:38.600 --> 00:33:40.120
So this is actually a super interesting.
00:33:40.120 --> 00:33:42.600
One of the things I think Firefox could do, but also it was just really interesting.
00:33:42.600 --> 00:33:43.300
Island.io.
00:33:43.300 --> 00:33:44.080
People can check that out.
00:33:44.080 --> 00:33:45.260
Sounds weird.
00:33:45.260 --> 00:33:46.200
Like, why would you ever want that?
00:33:46.200 --> 00:33:49.000
And then you watch the video or listen to it and you're like, actually, that's awesome.
00:33:49.000 --> 00:33:49.420
So.
00:33:49.420 --> 00:33:51.240
Okay.
00:33:51.240 --> 00:33:52.620
Like installed.
00:33:52.620 --> 00:33:53.640
All right.
00:33:53.640 --> 00:33:53.860
All right.
00:33:53.860 --> 00:33:54.820
Shall we joke?
00:33:54.820 --> 00:33:56.140
Yeah, let's do a joke.
00:33:56.140 --> 00:33:57.100
All right.
00:33:57.100 --> 00:33:58.780
Well, this is a Linux joke.
00:33:58.780 --> 00:34:00.740
It's more than a Python joke, honestly.
00:34:00.740 --> 00:34:03.380
So Brian, have you ever got a bike lock?
00:34:03.380 --> 00:34:05.320
One of those, really a combination lock for anything.
00:34:05.320 --> 00:34:06.760
But in this case, it's a bike lock, right?
00:34:06.760 --> 00:34:07.360
Okay.
00:34:07.360 --> 00:34:13.040
So here's a little character says my new bicycle lock to keep my new bicycle secure.
00:34:13.040 --> 00:34:14.480
It has three digits.
00:34:14.480 --> 00:34:14.920
Let's see.
00:34:14.980 --> 00:34:17.580
So that's a thousand combinations of what we could have.
00:34:17.580 --> 00:34:21.500
And then they start to rule out what are the ridiculous ones, right?
00:34:21.500 --> 00:34:24.820
Like one, two, three and stuff like, hmm, nine, nine, eight, maybe.
00:34:24.820 --> 00:34:31.000
I am not silly enough to use 666 or 777 to give full access to everyone.
00:34:31.000 --> 00:34:36.980
You know, change mod 777, which gives it full access to the, rewrite access to whatever you
00:34:36.980 --> 00:34:38.020
change modded.
00:34:38.020 --> 00:34:39.700
That is funny.
00:34:39.700 --> 00:34:40.800
Yeah, it's pretty good.
00:34:41.120 --> 00:34:42.760
I mean, obviously you wouldn't use 777.
00:34:42.760 --> 00:34:51.040
I may be the wrong target market for this because it's sort of funny, but also I'm thinking,
00:34:51.040 --> 00:34:55.220
did bike locks really have three combinations, three of those, or were there four?
00:34:55.800 --> 00:34:57.040
You're being way too practical.
00:34:57.040 --> 00:34:58.960
You're like four or six or something like that.
00:35:00.040 --> 00:35:03.760
I had a smartphone smart lock once and it was awesome.
00:35:03.760 --> 00:35:05.700
You would hold your phone up to it and it went lock.
00:35:05.700 --> 00:35:09.680
I got it from my electric bike before my knees decided electric biking wasn't for me.
00:35:10.420 --> 00:35:16.660
And one time I was out biking with a friend and I parked it in the summer in the sun and like the
00:35:16.660 --> 00:35:20.760
electronics bit of it got direct sunlight and it's black because it's a lock, right?
00:35:20.760 --> 00:35:25.820
Got super hot, like so hot you couldn't hardly touch it, but also so hot that like the electronics
00:35:25.820 --> 00:35:27.060
wouldn't run and I couldn't unlock it.
00:35:27.060 --> 00:35:29.500
I had to like put it in the shade for an hour before I could go home.
00:35:29.500 --> 00:35:30.460
I was so frustrated.
00:35:30.460 --> 00:35:33.980
I like covered it with my shirt or something and just sat there till it cooled off so I could
00:35:33.980 --> 00:35:34.400
go home.
00:35:34.760 --> 00:35:35.840
Oh, that's bad.
00:35:35.840 --> 00:35:41.020
And then also I've seen like the combination really kind of doesn't matter.
00:35:41.020 --> 00:35:45.840
It's how thick the rest of the lock is because I've seen people just come up with these like
00:35:45.840 --> 00:35:49.700
battery powered just cutters and just cut the lock off.
00:35:49.700 --> 00:35:51.200
Yeah, exactly.
00:35:51.200 --> 00:35:57.420
It's probably not the combination, but if you do have one, don't use 777 because clearly that's
00:35:57.420 --> 00:36:00.320
going to, it'll just fall right off if you do that.
00:36:00.320 --> 00:36:03.140
Yeah, just go with one, two, three, four.
00:36:03.140 --> 00:36:04.440
Yeah, exactly.
00:36:04.440 --> 00:36:05.060
It's fine.
00:36:05.060 --> 00:36:05.640
Anyway.
00:36:05.640 --> 00:36:07.420
Well, thanks a lot.
00:36:07.420 --> 00:36:09.020
I hope you get power back at your house soon.
00:36:09.020 --> 00:36:09.540
Thanks.
00:36:09.540 --> 00:36:10.220
I hope so too.
00:36:10.220 --> 00:36:15.180
Probably the power people said probably today, but you never know.
00:36:15.180 --> 00:36:15.860
You never know.
00:36:15.860 --> 00:36:16.920
All right.
00:36:16.920 --> 00:36:18.220
Well, good to be here with you.
00:36:18.220 --> 00:36:18.660
Talk to everybody later.
00:36:18.660 --> 00:36:19.080
Bye.
00:36:19.080 --> 00:36:19.460
Yeah.
00:36:19.460 --> 00:36:19.880
Bye everyone.