#339: Actual Technical People

00:00 Hello and welcome to Python Bytes, where we deliver Python news and headlines directly to your earbuds.

00:05 This is episode 339, recorded June 6th, 2023.

00:10 Is it the 6th? Yeah.

00:11 I am Brian Okken.

00:12 I'm Michael Kennedy.

00:13 Today's episode is sponsored by InfluxDB from Influx Data.

00:18 Thank you, and we'll talk about them more later in the show.

00:22 If you want to reach any of us or the show, we have a contact form, of course.

00:28 And then also M. Kennedy at Fostadon and Brian Okken and Python Bytes, all Fostadon locations.

00:36 If you're listening to us on a recording or on YouTube or on a podcast player,

00:44 please join us on YouTube at pythonbytes.fm/live, at least occasionally,

00:49 because it's fun to have people hanging around while we're recording.

00:52 It's usually Tuesdays at 11, and you can watch older versions there, too.

00:57 So let's kick it off with something stacky.

01:01 Something stacky.

01:02 You feeling like some pancakes?

01:03 A stack of pancakes?

01:05 Yeah.

01:05 How about a PyStack?

01:07 So the reason I was late to this recording, Brian, was I was just talking with Pablo and Matt,

01:13 maintainers and creators of PyStack.

01:16 Have you heard of PyStack?

01:18 I have not.

01:19 So PyStack is a tool that uses forbidden magic to let people inspect the stack frames of a running Python process,

01:26 or even a core dump that was captured from a Python process that crashed,

01:32 helping you quickly and easily learn what it's doing.

01:35 How cool is that?

01:36 Pretty good.

01:37 Yeah.

01:37 So here's the deal.

01:38 Yeah.

01:39 So here's the deal.

01:39 I've got a Python app.

01:41 This is especially important if you have mixed code.

01:44 So if you're talking with C, C++, Rust, those kinds of things, because it will cross those boundaries as well.

01:50 But let's just say pure Python even.

01:52 I've got a Python web app, and I go to the server, and I try to connect to it.

01:59 It won't really respond.

02:00 It connects, but it just hangs.

02:01 Go to the server.

02:02 It's not 100% CPU.

02:04 In fact, it's 0% CPU usage, so it's not spinning and busy.

02:08 What the heck is it doing?

02:09 Is it a deadlock?

02:10 Is it waiting on the database?

02:12 What is going on?

02:13 So what you can do, even in production, you can go up to that process, and you can say,

02:18 give me a snapshot of exactly what this process is doing.

02:24 And what you see is you see a call stack.

02:27 Let me find an example here of what it looks like.

02:30 It looks like this.

02:31 Silly zoom.

02:32 So what you'll see is like, hey, on this particular thread, we're seeing on this file,

02:38 on this line, this function was called.

02:40 And check it out.

02:41 It even has the arguments passed to the function.

02:44 Oh, wow.

02:44 That's nice.

02:45 Yeah.

02:45 And then you can see what function that's calling with the arguments passed to it, and

02:49 what function that's calling with the arguments passed to it.

02:51 You can do this on a running function without altering its behavior, basically.

02:56 It doesn't inject any code or anything.

02:57 The only behavior it alters is that it freezes it for a second, potentially, which could,

03:02 I guess, make something time out.

03:03 But other than that, you could do this in production even to see what's happening.

03:07 And what's extra cool is if even if the process crashes, you can grab the core dump and it will

03:15 go back and analyze that as if it was a running process.

03:18 Oh, that's pretty cool.

03:20 Yeah.

03:20 So there are a ton of features.

03:22 If you can get to the section where it says, what can PyStack do?

03:26 So it works with both running processes and core dump files.

03:29 It'll tell you if a thread is currently holding onto the gill, if it's waiting to acquire it or

03:36 it's trying to drop it.

03:37 So you can, you know, one of the examples that Matt and Pablo spoke about was they were calling

03:43 into custom C code.

03:45 That was a Python extension.

03:46 That call that was coming in, that was, that was acquiring the GIL.

03:52 But then there in the destructor for some object that it was waiting for it to go away, it

03:58 was like waiting on a background thread to do some cleanup.

04:02 That background thread also was trying to do a callback to let Python know what's happening

04:06 and was trying to acquire the gill, but it couldn't.

04:09 So because the one that was waiting on it was already holding the GIL and wasn't going to

04:14 give it up because that's how the GIL works.

04:15 Right.

04:16 So you can use it for like these deadlock situations and see if it's running a GC, you

04:22 can see both the call stack in intertwined for both Python and C or C++ or Rust altogether.

04:30 And it'll even do things like go out and find the debugging symbols for say your Python runtime.

04:37 Even if you don't have it, it can potentially go and get those and bring that extra information

04:42 in.

04:42 What else should we see here?

04:45 Safe to use on running processes.

04:46 You can run it on a process in memory running process without pausing it at all, which will

04:54 minimize the impact it might have.

04:56 But it'll also potentially have like not 100% precise information.

05:00 It could be out of sync.

05:01 So yeah, it even works on like corrupted process core dumps because the process died because it

05:07 got corrupted memory or something.

05:09 So if you've thought about GDB or some of these other types of things because you're like,

05:14 oh my gosh, I've got to figure out why this crashed.

05:17 Here's a core dump.

05:17 Let me start looking at it.

05:19 Well, PyStack may be the thing you want.

05:21 That's pretty cool.

05:22 And one final bonus for you, Brian.

05:25 Suppose you have a pytest test.

05:28 This one.

05:30 Suppose you have a pytest test and that test while it's running deadlocks or is very slow or

05:38 something like that, you can have PyStack as a pytest plugin.

05:43 And then when you run your code, how do you do it?

05:46 I think it's you just, where is it?

05:49 You know, but anyway, when you run it, you can say basically analyze my test.

05:55 And here's a certain threshold to consider a failure and take a snapshot of that and so on.

06:00 Yeah.

06:01 I like the threshold notion of just like, if it gets this bad, tell me why.

06:05 Yeah.

06:06 Nice.

06:06 Cool.

06:07 Cool.

06:07 So if people want the full details, I suppose they could go check out the YouTube live stream

06:12 channel for Talk Python now or in three weeks, they could listen to the podcast.

06:17 But super, super cool tool.

06:20 If you've got a process that is crashing, that is hanging, maybe it's doing this in production

06:24 and it only gets deadlocked after, you know, 12 hours of being hammered on.

06:29 You can't easily just debug it locally and get this to happen.

06:32 Or if it's completely crashed and you have a core dump, this, these guys are doing lots

06:36 of magic to make it possible.

06:38 Nice.

06:38 Yep.

06:39 Cool.

06:40 Well, next, I kind of want to give everybody some news.

06:44 So last year, actually, it was in July last year.

06:49 So we talked about in episode 293, we talked about some giveaway, some PSF, the PSF saying

06:58 that there's like the top 1% of the critical packages are going to have to use two-factor

07:04 authentication.

07:05 And it was big drama at the time, right?

07:08 Yeah, well, because like there was some confusion over the keys and stuff like that,

07:11 or hardware keys and, and, and, and yeah, some pushback against that or just some confusion

07:17 around it, I think.

07:18 But we've seen some, some even more attacks against Python projects in the last year.

07:25 I mean, it's only, it's only, it's been less than a year since that.

07:28 And so the change is this year, PyPI is going to require everybody to use two-factor authentication,

07:37 not the top 1%, the top 100%.

07:40 So, and it's, you got till the end of the year, I think.

07:45 And it's, let's see, we were linking to an article from the Python package index saying,

07:53 securing PyPI accounts via two-factor authentication.

07:58 And as of today, they're going to require, they're announcing that every account that maintains,

08:05 every account that maintains a project or organization on PyPI will be required to enable two-factor

08:12 authentication on their account by the end of 2023.

08:14 So that's the news, really.

08:16 There's some discussion as to why in this article, but there's some information on how to, how to prepare.

08:25 But it's not, I mean, it's not that bad.

08:27 I did it last year.

08:28 If you've got, especially if you're already using a smartphone, I think that using something like Authy

08:36 or something like that on a smartphone would work just fine.

08:40 So, yeah.

08:41 What else?

08:42 There's, it's kind of, I guess there's not much really more to say.

08:46 about it is that this is happening and you got to kind of do it.

08:49 You got to do it by the end of the year.

08:51 But why not?

08:52 Why wait?

08:53 Just go ahead and do it.

08:54 And it's really everybody.

08:55 So it's, so let's say you've got an open source project and there's like, you know, 20 people

09:00 contributing.

09:00 That would be cool.

09:01 Maybe there's like five, but if only one of you is ever pushing to PyPI, then it's just

09:06 one of, I think it's just one of you, unless you're doing an organization thing.

09:09 I think it's just a person pushing.

09:11 So if other people are on Git and not using two-factor for Git, but they're,

09:16 just pushing to your repo.

09:18 I think that's still fine.

09:20 That doesn't matter.

09:21 It's the people actually actively interacting with PyPI that need to be authenticated.

09:26 Yeah.

09:26 That's what it sounds like to me as well.

09:28 It's kind of, if, if you're actually have an active account on PyPI, right?

09:33 It's not necessarily GitHub.

09:34 Although I think GitHub itself also has a 2FA requirement now.

09:37 And there is some discussion here about like people that don't interact with their, with

09:43 a project, but still have a PyPI account.

09:45 And I'm not exactly sure why.

09:46 Apparently there's some people that need it that, I don't know.

09:50 Why would you have a PyPI account if you're not pushing stuff to?

09:53 Yeah.

09:54 Yeah.

09:54 That's a good point.

09:55 It is a good point.

09:58 Well, so there was so much drama about it and there was that person that deleted their,

10:05 all their packages because they were frustrated as like a thing of protests and it caused some

10:10 issues.

10:11 And well, I'm fine with this.

10:13 This is, this is great.

10:14 I think it's supply chain issues are really, really serious.

10:18 So it's, it's okay with me.

10:20 Yeah.

10:21 Me too.

10:22 So shall we thank our sponsor?

10:25 We shall, but first I just want to point out.

10:28 Yeah.

10:28 I think Authy is a fantastic option for the 2FA stuff that you were pointing out, right?

10:33 As you mentioned, like one of the things that is a huge hassle for, for a lot of the systems

10:39 is guess what?

10:40 You can install this 2FA tool onto your phone and it's completely safe.

10:45 And all that local, that 2FA, it'll never go anywhere until you want to get a new phone.

10:49 And then you're completely out of luck and you've got to somehow reset it or worse, you lose

10:53 your phone, but it's not, there's no way to recover the 2FA code.

10:56 So what I really like about Authy is it will, you can install it in multiple locations.

11:00 Like you can install it on your desktop and your mobile device.

11:05 And they're just in sync.

11:06 If you add one somewhere, it appears elsewhere.

11:09 So if people feel like TFA is a huge pain, I think Authy is one of the choices that's

11:13 pretty good for that.

11:14 I didn't know.

11:14 You can also do like 1Password and so on.

11:17 But to me, having the passwords there and the 2FA thing in the same place seems to violate

11:22 some aspect of security.

11:24 I mean, I know 1Password is pretty safe, but 2FA should be about having the password and

11:29 the thing separated in my mind.

11:31 And so I don't use my password managers 2FA thing.

11:34 Yeah.

11:35 I just thought, I thought I had like just a couple accounts with Authy and I just looked

11:39 and I've got like, I got a scroll.

11:40 I've got a whole bunch of things on Authy right now.

11:43 Yeah.

11:43 I think I have 40 or so myself.

11:45 All right.

11:46 Now let's tell people about our sponsor.

11:47 All right.

11:48 This episode of Python Bytes is brought to you by Influx Data, the makers of Influx

11:53 DB.

11:54 Influx DB is a database purpose built for handling time series data at massive scale for real-time

12:00 analytics.

12:00 Developers can ingest, store, and analyze all types of time series data, metrics, events,

12:05 traces on a single platform.

12:07 So dear listener, let me ask the question, how would boundless cardinality and lightning-fast

12:13 SQL queries impact the way you develop real-time applications?

12:17 Influx DB processes large time series data sets and provides low latency SQL queries,

12:23 making it a go-to choice for developers building real-time applications and seeking crucial insights.

12:29 For developer efficiency, Influx DB helps you create IoT, analytics, and cloud applications

12:35 using timestamp data rapidly and at scale.

12:38 It's designed to ingest billions of data points in real-time with unlimited cardinality.

12:44 Influx DB streamlines building once and deploying across various products and environments from

12:50 the edge, on-premise, and to the cloud.

12:53 Try it for free at pythonbytes.fm/influx DB.

12:57 The links are also in your show notes on the podcast.

13:00 Thanks, Influx DB, for supporting the show.

13:03 Yep.

13:03 Thank you.

13:04 Thank you.

13:04 Everyone check them out to help support the show.

13:07 All right.

13:08 Let's talk about queues, Brian.

13:10 Okay.

13:11 Yeah.

13:11 So I want to talk about Propan.

13:13 Now, Propan is a project that's not, you know, tens of thousands of GitHub stars.

13:19 I think it looks pretty compelling.

13:22 It's put together by Lance Nick, Lance Nick, Lance Nick, Lance Nick, I'm going to go with

13:27 over here on GitHub.

13:28 And it is a powerful and easy to use Python framework for building asynchronous web services

13:34 that interact with any message broker.

13:36 So what are some of the options of the message brokers here?

13:40 We've got RabbitMQ, Redis, Nats, Kafka, SQS, some of the other ones like Redis streams.

13:47 If you're using these and you want a cool declarative way to interact with them, then Propan might

13:54 be your thing.

13:55 So right now what they have is async APIs for you, and they're working on synchronous ones,

14:02 but they don't have them yet.

14:03 So let me just give you an example, Brian.

14:06 Over here, it says, first, let's take the quick start from AIO Pika, which is a way to

14:13 talk, way to listen for events.

14:15 This is the important part.

14:16 Listen for a certain set of events coming into a message queue.

14:20 Okay.

14:20 Okay.

14:21 So what you do is you say, I'm going to connect to the message queue server, and I'm going to

14:27 listen to a particular queue.

14:28 Then you await creating the connection.

14:31 You await creating a channel.

14:33 You await connecting to the queue.

14:35 And once you do it, then you use the iterator.

14:39 You loop over the iterator as messages come in, and then you get them.

14:42 And then you, of course, run that code that does that right.

14:45 That's the imperative way where you do all the steps yourself.

14:49 So this other way is what you do is you go to, you basically create this thing called a

14:54 broker using propan, and you point it at one of these queues, like Redis or something.

15:00 And then you just, kind of like you would in FastAPI or Flask, you say, you put a decorator

15:05 on a function, and you say, at broker.handle, and you give it the name of the queue.

15:09 So if a message comes into that named queue, call this function.

15:13 Oh, I like that better.

15:13 Isn't this nice?

15:14 It's kind of like, I'm listening for this URL, like if, you know, slash courses, slash ID

15:20 of a course.

15:21 I want to get you details about that course, right?

15:23 You would put that in Flask or Pyramid or FastAPI.

15:26 This is the same thing, but for message queue.

15:28 So you say, this function receives stuff that goes to that queue.

15:31 Oh, I like it.

15:32 Yeah.

15:33 That's what those interfaces should be like.

15:34 Yeah, absolutely.

15:36 It totally should.

15:37 So this is pretty interesting already, but it gets a little bit cooler.

15:42 You can go and create one of these apps and just run a server directly, right?

15:47 So you can say, I want to run this as a system daemon on Linux, let's say, and it's just going

15:52 to, you know, use the Propan server to run.

15:55 That's fine, but there's tons of infrastructure around running these types of things as web applications.

16:01 And if you already have a web app that receives like JSON requests, you know, it's got some

16:08 kind of API endpoint, but you also want to have it handle stuff that might be put into the

16:13 message queue.

16:13 Then it has integration with the virtual down into, you can do it manually into any web framework,

16:21 or it's got things like a FastAPI plugin, which is pretty cool.

16:24 Oh, cool.

16:25 Yeah.

16:25 So let's see.

16:27 Actually, if I go to the examples, I'll pull up a Flask one.

16:29 That's probably the best, which you got to use Quart because it's only async.

16:33 That's the Flask async variant.

16:36 So what you can do is in your, let's see, I'll just say in your Quart app, you create this

16:40 broker to sort of listen as well.

16:42 In addition to create your, your Flask or Quart app.

16:45 And then you might have, you know, a function that says app.route, listen for forward slash,

16:51 and that's a JSON endpoint.

16:52 Or you might have broker.handle some queue message, and that's the queue coming in.

16:57 So it's kind of like, well, here's the messages coming in over the web, and here are the ones

17:02 coming over, message queuing.

17:03 But, you know, it's just, it runs in Microwisgee or G Unicorn or whatever.

17:08 Yeah, that's nice.

17:09 Yeah.

17:09 Last thing.

17:10 This is inspired by Pydantic and FastAPI.

17:14 And so let me see about a good example here.

17:19 You can do things like declaring that the body of the message is, is a dictionary, or you can

17:28 have Pydantic base models that are coming in.

17:31 So you can say, here's a Pydantic.

17:32 When a message comes to the message queue, it's going to be represented by, let's say,

17:36 JSON.

17:36 And that JSON, I want to parse into a Pydantic model.

17:40 You can just say, much like FastAPI, in your handler, you say body colon, you know, the name

17:45 of your custom Pydantic class.

17:47 Boom.

17:47 Now it's automatically parsing that based on the type.

17:50 Oh, based on, that's neat.

17:52 And the last thing, they also have this concept of modeling pytest fixtures.

17:59 So you can create functions that will do things like, you know, process requests or give you

18:04 extra information or whatever, you know, what you would do with pytest fixture type things.

18:07 And you can have those as well in here, which is pretty cool.

18:11 So there's a lot of cool, it's like a fusion of interesting Python frameworks for message

18:16 queuing.

18:16 I like it.

18:17 So ask your doctor if propane is right for you.

18:20 Ask your doctor.

18:21 That's right.

18:22 Yeah.

18:22 I, you know, it's, it's interesting because this message queuing type of architecture is

18:27 super powerful at unlocking tons of interesting asynchrony.

18:31 Like, well, if I've got a request come in and I got a, you know, place an order and we

18:35 got to check the warehouse, whether we have them.

18:36 And that's a janky old API call that's slow.

18:40 Like, well, how do I scale that would be one option with threads and async and await.

18:45 The other one would be just like, well, throw that into a queue to say, check that out.

18:49 And then, you know, let it run completely disassociated.

18:52 Right?

18:52 Yeah.

18:53 Scroll to the bottom, the key features.

18:56 So one of the things I want right down there, testability.

19:00 Propane allows you to test your app with without external dependencies.

19:04 You do not have to set up a message broker to test.

19:06 You can have a virtual one.

19:08 That's pretty cool.

19:09 Yeah.

19:09 Yeah.

19:10 This is cool.

19:10 So it's, it's not super popular.

19:12 Like I said, however, it does look pretty neat.

19:15 Sure does.

19:16 All right.

19:17 Over to you.

19:17 So that, that was a little bit of a new thing.

19:20 I want to talk about a little bit of an old thing, which is make files.

19:23 We haven't talked about it for a while, but make files are still fairly popular for Python

19:29 projects.

19:29 I think I I've got them on several internal projects at least.

19:34 And they, they come in handy.

19:36 You got to be careful that a lot of people, sometimes people on your team won't be familiar

19:40 with them, but if it's a common thing for your team to use make files or for you, why not

19:45 use them on a Python project?

19:46 So this, what I'm going to cover is a, an article for getting the author name right now.

19:53 Let's see.

19:53 Ricardo and drag called make file tricks for Python projects.

19:58 And I'm going to hop down to the actual template.

20:01 What it is, it's a, it's a little, it's a small template as a starter template for a Python

20:06 project, but it has some pretty cool features.

20:09 And the actual templates at the bottom of the article, but we kind of go through some

20:14 of the different things that you might want to put in there.

20:17 And so to start off some, a little bit, I always forget to do this.

20:21 These are things I want to, I always want to do, but I forget in my make files, things

20:25 like making sure that it fails.

20:27 If anything throws a incorrect error code.

20:30 And also warning, if you did something wrong, like undefined variables or you're using, you

20:37 can turn off this built-in rules.

20:39 And I don't really know what the built-in rules thing does.

20:41 It's just, I find my make files more pleasant if I disabled them.

20:46 So this is good.

20:47 The virtual environment thing.

20:49 So there's a little snippet that he includes that you can use the PY variable to select which

20:57 Python to run.

20:58 So if you already have a virtual environment, it uses that, which is cool.

21:02 That's pretty clever.

21:03 Yeah.

21:03 Yeah.

21:04 And if you don't, it uses the global one.

21:06 And then also with pip.

21:08 So use the, it uses that PY variable to pick pip if it's there or not.

21:15 And it uses the global one.

21:16 So that's pretty cool.

21:17 Actually, it'd probably be better to just blow up if you didn't have a virtual environment.

21:22 Anyway, some of the, some stuff like PWD and current working directory and work root.

21:29 These are good things to add in because sometimes you'll call a make script from a different directory.

21:36 So your actual current directory is different and it mucks things up.

21:39 So there's some good correction there.

21:41 I do like this.

21:43 There's some little magic stuff about default goal and help message.

21:47 And I had to read this a little bit to understand what's going on.

21:50 But what happens is it, the default goal being help means that if you just type make with

21:57 nothing, no arguments, what should it do?

21:59 And a cool thing to have make do is to print out all the things that you can do with the

22:05 make file, like all the, all the targets and what they do.

22:08 And so that's what this does by having these, having this little greps thing.

22:14 Is it grep?

22:17 I don't know if it's anyway, it's searching through your file.

22:19 And, using awk and saying, Hey, if you've got a comment against, at the site of a target,

22:27 that means that's the help message.

22:29 So it'll print that stuff out.

22:30 Oh, that's cool.

22:31 Yeah.

22:32 some, I don't really muck with my Python path too much, but if you have to muck with

22:37 your Python path for a make file to, to find libraries or something like that, or find

22:43 the code that you're running, there's examples on how to do that, which is nice.

22:48 I guess that's really kind of what I wanted to talk about.

22:51 and I was surprised it's doing all this stuff and it's really, and some examples on how

22:56 you can use the path thing.

22:58 Oh, having, adding a little, create virtual environment within a make file.

23:01 This is nice.

23:02 Just so that people working on the project.

23:04 Yeah.

23:05 Make dot V and V.

23:07 You could have V and V also.

23:08 And it just makes your virtual environment.

23:10 Why do you need a target for that?

23:12 And it's because, and you've, you've discovered this, but sometimes, new Python developers

23:18 kind of forget is that it's, it's kind of annoying to just create a virtual environment.

23:22 It's good to, after you've created it, update the update setup tools and wheel and build.

23:28 And then also if you have a requirements file, why not just install it right away instead

23:33 of having, having that as another command.

23:35 So kind of a fun template for starting make files with Python project.

23:40 Yeah.

23:40 That's, what is that?

23:42 A modern take on an old idea.

23:44 Yeah.

23:45 the, and if you are new to make files, one of the things to be careful about that some

23:50 people don't quite sometimes real remember is spaces matter within make files kind of like

23:56 they do in Python, but spaces and tabs matter.

23:59 So in, in make files, you're using tabs.

24:02 It has to be a tab.

24:03 It cannot be space, unless something's changed that I don't know about, but that,

24:08 that, that has messed me up before.

24:10 So use tabs within make files.

24:12 All right.

24:13 Yep.

24:14 Sounds good.

24:14 Excellent one.

24:15 I guess that's everything.

24:17 Yeah.

24:18 Yeah.

24:18 Any extras?

24:19 no, not really.

24:20 You.

24:21 I got a couple here, just a couple of conference ones.

24:25 So high con Portugal has their call for participation.

24:29 So.

24:30 got, got a little bit of time left on that.

24:34 What is that till the 30th, June.

24:37 And when will it be, it will be September seven to nine, which is cool.

24:43 So if you're in and around or want to go to Portugal, there you go.

24:47 Cool.

24:48 On the other hand, if you happen to be interested in Django and are in, Europe that just got

24:54 announced as well.

24:55 So people can check that out.

24:56 I want to go soon.

24:58 I'm not going, but I want to go.

25:00 Yeah, indeed.

25:01 So that's also announced link to both of those in the show notes.

25:04 Are you ready for a joke?

25:05 Yeah.

25:06 Well, this becomes because apple.com.

25:09 Did you see that they announced this crazy vision thing, Brian?

25:14 Yeah, but it doesn't come with the snorkel.

25:17 It's just the snorkel mask.

25:18 Yeah.

25:19 It's just the snorkel mask.

25:20 It's, it doesn't even come with that little, handheld sub submarine thing that you can

25:26 drag yourself around either.

25:27 So, yeah.

25:28 So they announced if you haven't noticed yet, Apple announced vision pro, which is a $3,500

25:35 ski goggle looking thing.

25:37 That is both augmented reality and virtual reality kind of turn the dial.

25:43 I'm highly suspicious of this.

25:44 I think it's going to not do great, but it does look pretty awesome for certain use cases.

25:51 Like for example, you could sit on the sidelines of a football game and, and get like a 3d view.

25:56 So you could look to the right and see down the sideline and then look ahead and watch

26:00 the game.

26:00 I got that.

26:01 That's pretty epic.

26:02 Is it worth $3,500?

26:03 I don't know.

26:05 We'll see.

26:05 but okay.

26:07 So that's setting the stage for the joke.

26:09 So here's the joke.

26:10 The average pseudo technical person has got like an Oculus Rift in there.

26:15 They got their handheld controllers that they're doing.

26:18 Right.

26:19 And then we have the pseudo, the rich pseudo technical people wearing the Apple one sitting

26:24 there watching TV.

26:25 And then Brian, you want to describe the actual technical people, advanced high tech setup they

26:31 got here.

26:31 That's just a dude at a desk with like, you know, with using a computer, but it's, oh,

26:38 there's important stuff to it though.

26:40 It's dual monitor.

26:41 We will note the dual monitor.

26:43 Yes.

26:44 And the mechanical keyboard.

26:45 These, this is not your average desk worker.

26:48 Yeah.

26:49 Anyway, there's my follow on to WWDC.

26:52 I know I would.

26:53 And that's, that's even, okay.

26:55 I've got the big curved monitor.

26:58 So I don't have two right now, but you have two monitors.

27:01 I have one big monitor for my, my working desk and I have a big curved monitor for my gaming

27:07 PC, but just one for both as well.

27:09 I used to have dual monitors and I would, I was always trying to like juggle them.

27:12 I'm like, you know, I just want big monitor.

27:14 That's better.

27:14 Yeah.

27:15 I actually, when we did the pandemic thing, I went to one big monitor at home and then

27:19 at work, I still had the two split ones, but then I was just tired of doing this all day

27:24 long.

27:24 Yeah.

27:24 So I'm like, oh, we got to just, so I went to a big one, but that's kind of privilege

27:30 speak.

27:30 So I don't know.

27:31 It is a little bad.

27:32 Just for people who are interested, I, if I do need a second monitor, like sometimes when

27:37 I'm recording a course, I want to be able to see what the recording is doing.

27:40 So I want to see my video overlaid with maybe what's on the screen with whatever settings,

27:46 like scale, like exactly what's being recorded as the person's going to see it in case something

27:51 goes weird with that.

27:52 So I'll take my iPad, plug it into my mini and then use Duet.

27:58 Duet is a really cool software that I think works on Mac and Windows and basically turns

28:04 that into a second monitor just periodically when you want it.

28:07 You know?

28:07 So that's, that's what I do if I really feel like I need extra, extra space.

28:11 So, so go back to the Apple vision thing or the eye dork.

28:15 What's it called?

28:15 Apple vision.

28:16 Yeah.

28:16 I think it's, I dork pro.

28:18 there's part of one of the things on there is somebody doing a, like a meeting

28:27 where you can supposedly see other people in the meeting, like as if you were still there,

28:32 they were with you or something and I thought, well, that one go up a little bit.

28:37 Yeah.

28:37 This is like the group FaceTime is what that is.

28:40 Yeah.

28:40 Except for, oh no.

28:41 Yeah.

28:42 Yeah.

28:42 I see it.

28:42 Okay.

28:42 Wouldn't, wouldn't they see you with the goggles on?

28:46 So if everybody's doing it, wouldn't everybody just, you just be able to see people with goggles.

28:50 that's interesting.

28:52 I think it might scan you and put an avatar of you up there.

28:55 Oh yeah.

28:56 It's an AI you.

28:57 It's not really, I think it's, I think it's an AI you actually.

28:59 Yeah.

29:00 I think so.

29:01 I haven't tried this out.

29:03 And where's your camera?

29:04 Where do you put your camera?

29:05 Like for, so anyway.

29:07 Yeah.

29:08 There's a lot of interesting and stuff.

29:10 I'm actually interesting things and stuff.

29:12 I'm actually excited about announced at, at WWDC vision pro.

29:16 yeah, there's, there's like, for example, large language model dictation for iOS and Mac.

29:24 So I don't know how many people know who have tried this, but I, for multiple reasons have tried to do,

29:30 dictation on the Mac.

29:32 Partly because I have like mild grade at this point, RSI issues.

29:36 And so if I can limit typing, that's good.

29:38 And maybe I've got a lot of stuff I need to blaze through, like a bunch of email or something.

29:42 I'd love to dictate to it.

29:44 But the dictation system on Mac is like 10 years old or something.

29:48 It's really bad.

29:49 You can't even say new paragraph, for example.

29:51 Like, nope.

29:52 They don't just write out new paragraph.

29:54 Whereas on iPhone, you can say new paragraph or do this, or like you can navigate around way better.

29:59 They're not the same systems.

30:00 So both of those are being replaced with like ChatGPT level of AIs.

30:05 And so dictation to your computer or your device is going to get way better.

30:10 And so that means less typing, less RSI, just different input modalities.

30:14 If you need a break, like those kinds of things, I'm really psyched about.

30:17 Vision Pro, we'll see.

30:18 Yeah.

30:19 There's potential there, but there's also way more potential for jokes.

30:24 Yes.

30:25 It's going to be good.

30:26 Speaking of jokes, we'll wrap it up with one from Kim in the audience.

30:29 If an avatar is an option, T-Rexes will be meeting with the elves and talking frogs in no time.

30:34 That would be great.

30:36 I'm here for that.

30:37 Let's do it.

30:38 Yeah.

30:38 I'm here for it.

30:39 All right.

30:39 Bye, Brian.

30:41 Bye.

30:41 Bye, everyone.