WEBVTT 00:00:00.001 --> 00:00:05.360 Hello and welcome to Python Bytes, where we deliver Python news and headlines directly to your earbuds. 00:00:05.360 --> 00:00:11.380 This is episode 334, recorded May 3rd, 2023. 00:00:11.380 --> 00:00:12.380 I'm Michael Kennedy. 00:00:12.380 --> 00:00:13.400 And I'm Brian Ecken. 00:00:13.400 --> 00:00:16.320 This episode is brought to you this time by us. 00:00:16.320 --> 00:00:19.900 Support our work through our courses over at Talk Python Training. 00:00:19.900 --> 00:00:21.400 Check out Brian's pytest course. 00:00:21.400 --> 00:00:23.520 Check out a lot of the other courses I did there. 00:00:23.520 --> 00:00:25.340 Check out the Test and Code podcasts. 00:00:25.340 --> 00:00:27.440 And we have Patreon supporters as well. 00:00:27.440 --> 00:00:29.800 Link on the episode pages on the website. 00:00:30.140 --> 00:00:34.660 Connect with us over on Fosstodon, @mkennedy, @brianokken, at Python Bytes over there. 00:00:34.660 --> 00:00:43.740 And if you're not part of the YouTube live stream and you want to be, we generally do this on Tuesdays at 11 Pacific time in the morning. 00:00:43.740 --> 00:00:45.440 But today we had to move it. 00:00:45.440 --> 00:00:47.380 So plus one, plus 23 hours. 00:00:47.380 --> 00:00:47.860 Yep. 00:00:47.860 --> 00:00:48.440 All right. 00:00:48.440 --> 00:00:49.360 Yeah, Brian. 00:00:49.360 --> 00:00:50.280 Sometimes life happens. 00:00:50.280 --> 00:00:51.780 Life does happen. 00:00:51.780 --> 00:00:53.340 And sometimes PyCons happen. 00:00:53.340 --> 00:00:53.780 Yeah. 00:00:53.780 --> 00:00:55.780 Yeah, that was a lot of fun to see you there. 00:00:55.780 --> 00:00:57.220 It was a blast. 00:00:57.360 --> 00:01:00.240 Did you, I guess, I had a great time. 00:01:00.240 --> 00:01:01.580 How about you? 00:01:01.580 --> 00:01:02.520 You got a lot of work done. 00:01:02.520 --> 00:01:04.340 I got a lot of recording done. 00:01:04.340 --> 00:01:06.700 I'm looking forward to releasing some of those episodes. 00:01:06.700 --> 00:01:08.200 Met a bunch of great people. 00:01:08.200 --> 00:01:09.460 Saw some old friends. 00:01:09.460 --> 00:01:10.480 Got to hang out with you. 00:01:10.780 --> 00:01:20.300 You brought the Python staff of power and battled the snake, which was the episode album art from last time, which was a lot of fun. 00:01:20.300 --> 00:01:23.220 So yeah, it's starting to come back, isn't it? 00:01:23.220 --> 00:01:28.580 I mean, but still quite as many people or as vendors, but it's good to see it coming back to life. 00:01:28.580 --> 00:01:29.040 Yeah. 00:01:29.040 --> 00:01:29.640 Yeah. 00:01:29.640 --> 00:01:30.660 I really enjoyed it. 00:01:30.660 --> 00:01:32.220 So should we kick in? 00:01:32.220 --> 00:01:33.420 Let's do it. 00:01:33.420 --> 00:01:33.980 Yeah. 00:01:33.980 --> 00:01:34.500 Jump in. 00:01:34.660 --> 00:01:41.600 Well, I was actually talking with one of our friends from PyCon that I'm blanking right now. 00:01:41.600 --> 00:01:44.020 So somebody from PyCon. 00:01:44.020 --> 00:01:44.760 So thank you. 00:01:44.760 --> 00:01:47.440 And apologies for forgetting your name right now. 00:01:48.140 --> 00:01:56.020 What I came across actually from several people mentioned Rai because we had talked about Hwak. 00:01:56.020 --> 00:01:57.700 I think Hwak. 00:01:57.700 --> 00:01:59.280 Anyway, H-U-A-K. 00:01:59.280 --> 00:02:03.940 And I think I got corrected that the intended pronunciation is Hwak. 00:02:03.940 --> 00:02:05.200 I think. 00:02:05.200 --> 00:02:05.800 Anyway. 00:02:05.800 --> 00:02:07.680 I'm on board with that. 00:02:07.680 --> 00:02:08.120 Let's do it. 00:02:09.560 --> 00:02:12.320 So a similar, so that's what it is. 00:02:12.320 --> 00:02:16.540 It was, was a Rust-based Python project workflow tool. 00:02:16.540 --> 00:02:17.880 So now we have another one. 00:02:17.880 --> 00:02:18.900 This one's called Rai. 00:02:18.900 --> 00:02:24.060 And I don't know what came first, but actually this doesn't look that old. 00:02:24.060 --> 00:02:26.380 This is from Armin Roeniker. 00:02:26.380 --> 00:02:27.140 Roenicher? 00:02:27.140 --> 00:02:27.560 Roeniker. 00:02:27.560 --> 00:02:28.440 I'm okay. 00:02:28.440 --> 00:02:29.780 I got to practice this stuff. 00:02:29.780 --> 00:02:32.180 The dude from Flask that started Flask. 00:02:32.180 --> 00:02:36.980 So I was curious about it because he usually kind of knows what he's doing. 00:02:36.980 --> 00:02:40.200 And this is a really pretty interesting project. 00:02:40.200 --> 00:02:42.040 So I tried it out this morning. 00:02:42.040 --> 00:02:47.320 Rai, it says it's Armin's personal one-stop shop for all of his Python needs. 00:02:47.320 --> 00:02:52.320 So that, and there's a video, which I didn't watch, but it's a nine-minute intro video. 00:02:52.320 --> 00:02:55.960 So what, what, what, what am I excited about with this? 00:02:55.960 --> 00:03:00.560 So it's, it's, it's more than just project.toml workflow tools. 00:03:00.560 --> 00:03:01.300 It does that. 00:03:01.300 --> 00:03:06.260 So you can do things like initializing a project, adding a dependency, removing, you can, you 00:03:06.260 --> 00:03:07.140 can remove a dependency. 00:03:07.140 --> 00:03:08.200 That's kind of a neat trick. 00:03:08.200 --> 00:03:13.700 And then build a wheel and even add lock files, which is kind of nice. 00:03:13.700 --> 00:03:20.040 The, so the other thing that, one of the things that I thought was really kind of cool is it 00:03:20.040 --> 00:03:25.700 also manages, I'm not going to find all the details here, but it manages Python. 00:03:25.700 --> 00:03:30.420 So you can, what, what are people using for PyEnv or something to install Python? 00:03:30.420 --> 00:03:31.380 To install Python. 00:03:31.380 --> 00:03:33.080 This installs Python also. 00:03:33.080 --> 00:03:42.040 So you can say, you can say what, Rai fetch and then give it like 3.9 and it'll, it'll download 00:03:42.040 --> 00:03:46.640 and install Python 3.9 for you, which like, wow, that's kind of cool. 00:03:46.640 --> 00:03:48.960 And it, it does it in an interesting way. 00:03:48.960 --> 00:03:56.360 So it uses these Indiegreg Python build standalone releases, which I was not familiar with. 00:03:56.360 --> 00:04:01.500 But so there's these, these different standalone distributions builds of Python. 00:04:01.500 --> 00:04:02.380 So neat. 00:04:02.380 --> 00:04:06.620 I forgot to add, this is not a windows thing yet. 00:04:06.620 --> 00:04:08.320 It's just Linux and macOS. 00:04:08.420 --> 00:04:09.340 So I tried it on Mac. 00:04:09.340 --> 00:04:13.140 So installing a bunch of stuff, but where does it install it? 00:04:13.140 --> 00:04:14.760 It doesn't install it in the normal place. 00:04:14.760 --> 00:04:20.320 It installs it in, in your home directory under dot Rai, Rye. 00:04:20.760 --> 00:04:25.400 And that, that was surprising to me at first, but it's kind of neat that everything's there. 00:04:25.400 --> 00:04:26.220 So, okay. 00:04:26.220 --> 00:04:29.140 So it does PyEnv sort of stuff. 00:04:29.140 --> 00:04:32.460 It can install Pythons for you, which is kind of cool with a command line. 00:04:32.460 --> 00:04:33.920 You can install a Python. 00:04:33.920 --> 00:04:35.380 And it's pretty fast. 00:04:35.720 --> 00:04:37.340 It also handles virtual environments. 00:04:37.340 --> 00:04:43.000 So you can do things like add, run, run within your virtual environment. 00:04:43.000 --> 00:04:45.160 You can run a command without actually going into it. 00:04:45.160 --> 00:04:49.620 You can say like Rai run black and it'll run black on your project. 00:04:49.620 --> 00:04:56.700 You can say sync and it'll take all of the dependencies in your project.toml and install them in your virtual environment. 00:04:56.700 --> 00:04:57.440 That's kind of neat. 00:04:57.440 --> 00:05:00.060 And also it's kind of like PipX also. 00:05:00.060 --> 00:05:09.480 So you can do things like install a global tool, like, you know, PipX install cards or PipX install really whatever you want. 00:05:09.480 --> 00:05:11.940 Or black, for instance, if you wanted to. 00:05:11.940 --> 00:05:17.560 If you're going to like have any global tools on, on your, you know, on your machine. 00:05:17.560 --> 00:05:23.140 It confused me at first because I tried it and I couldn't get it in the thing to run. 00:05:23.140 --> 00:05:26.160 But it doesn't really, it doesn't, it isn't invasive. 00:05:26.160 --> 00:05:32.160 So it's not modifying your .zhrc or your RC files itself. 00:05:32.160 --> 00:05:33.300 You have to do that. 00:05:33.300 --> 00:05:38.500 So it's all going into a home directory .ri. 00:05:38.500 --> 00:05:45.060 And then I think there's a, there's a bin directory in there or something like that, that you just add to your path. 00:05:45.060 --> 00:05:46.340 So it's doing that. 00:05:46.340 --> 00:05:55.560 The kind of neat thing about that, that all that isolation in the .ri directory is that if you decide you don't like it, you can just, you can just delete it. 00:05:55.560 --> 00:05:58.060 And then delete that directory and all that stuff's gone. 00:05:58.060 --> 00:05:59.700 So kind of cool. 00:05:59.700 --> 00:06:00.260 Yeah. 00:06:00.260 --> 00:06:05.680 I do like that it just blow away the directory and it's gone or it's reset, you know, that's pretty cool. 00:06:05.680 --> 00:06:12.980 It's also interesting to see that this is not a package or tool within Python, but outside of Python. 00:06:12.980 --> 00:06:13.500 Yeah. 00:06:13.500 --> 00:06:13.740 Right. 00:06:14.060 --> 00:06:22.940 I mean, it does, it says it uses like uses virtual environment and it uses actually uses virtual end, which is a third party package. 00:06:22.940 --> 00:06:25.340 That's a little faster than the V and V. 00:06:25.900 --> 00:06:30.000 But it also uses a pip, but it doesn't expose any of those. 00:06:30.000 --> 00:06:32.200 So it is kind of interesting that it's outside. 00:06:32.200 --> 00:06:37.560 I kind of like that it's outside because you can do things like, like pip X and, and pie and V. 00:06:37.560 --> 00:06:40.240 And for me, it like just worked better. 00:06:40.340 --> 00:06:46.580 I, I've still had trouble getting pie, pie, pie, and V is a cool idea, but it mucks with everything in your environment. 00:06:46.580 --> 00:06:48.080 And I don't like that. 00:06:48.080 --> 00:06:48.520 Exactly. 00:06:48.520 --> 00:06:49.220 Yeah. 00:06:49.220 --> 00:06:49.960 I don't like that either. 00:06:50.520 --> 00:06:58.620 So, I think the trend I've been talking, you know, we, I did the Python packaging discussion on talk Python a while ago. 00:06:58.620 --> 00:07:14.500 And there's, there's been a lot of talk about this, talked, to Ofec about a hatch and it's looking like there's a little more, a little more interest in saying like, okay, what if we had a tool that actually not just manages environments and packages, but actually manages Python. 00:07:14.820 --> 00:07:21.560 Python, like it, for example, like this one, like install the version of Python you want and do a bunch of other things along those lines. 00:07:21.560 --> 00:07:23.680 So, yeah, it's, it's interesting. 00:07:23.680 --> 00:07:29.500 another, just a side note, Simon Willison wrote up some notes on his, when he tried Rye. 00:07:29.500 --> 00:07:31.480 So we're, we'll link that article as well. 00:07:31.480 --> 00:07:31.920 Okay. 00:07:31.920 --> 00:07:32.440 Excellent. 00:07:32.440 --> 00:07:33.140 All right. 00:07:33.140 --> 00:07:34.580 What is next? 00:07:34.580 --> 00:07:35.960 PyPI is next. 00:07:35.960 --> 00:07:37.000 Okay. 00:07:37.000 --> 00:07:37.700 Okay. 00:07:37.700 --> 00:07:45.220 So remarkably, PyPI has 452,000 packages. 00:07:45.220 --> 00:07:46.600 That is insane. 00:07:46.600 --> 00:07:50.060 But what is more insane is the traffic, right? 00:07:50.060 --> 00:07:57.120 So there's some, one of the themes from PyCon this year was about sustainability and kind of building for the future. 00:07:57.120 --> 00:08:09.780 Carol Willing gave a great keynote talking about, you know, let's make sure that, we're investing in the front end story for Python, investing in a mobile and deployment story for Python. 00:08:09.780 --> 00:08:15.200 And, you know, PyPI and the Python packaging authority, it's kind of there as well, right? 00:08:15.260 --> 00:08:27.080 Like as we grow in traffic, we need things like somebody to over watch over the security and some, you know, somebody to make sure all this stuff is developed and polished. 00:08:27.080 --> 00:08:30.600 And people have been doing that, but to a large degree in a volunteer way. 00:08:30.600 --> 00:08:31.080 Right. 00:08:31.080 --> 00:08:34.760 But how does Python pay somebody to work on this? 00:08:34.760 --> 00:08:38.780 Well, there's been some grants, I think, I don't want to say the wrong company. 00:08:38.880 --> 00:08:48.420 It was from, some of the big tech companies are hiring people to do specifically security work, like a supply chain type of security for PyPI, which is great. 00:08:48.420 --> 00:08:48.860 Right. 00:08:48.860 --> 00:08:51.380 But those are year by year things. 00:08:51.380 --> 00:08:53.360 So what, what could be done? 00:08:53.360 --> 00:09:04.660 Well, right now, if I go over here on PyPI and I search for like VotoCore, this is the way to talk to, AWS basically, from Python to a large degree. 00:09:04.660 --> 00:09:05.520 Who's it run by? 00:09:05.620 --> 00:09:08.880 Oh, it's Garnat amongst others. 00:09:08.880 --> 00:09:09.860 Wait a minute. 00:09:09.860 --> 00:09:12.400 This is like the official AWS thing. 00:09:12.400 --> 00:09:16.100 Shouldn't this somehow be kind of more official than that? 00:09:16.100 --> 00:09:19.280 And how do I find the other AWS projects? 00:09:19.280 --> 00:09:21.520 I can like email the person or something. 00:09:21.520 --> 00:09:22.280 I don't know. 00:09:22.280 --> 00:09:32.300 I guess I could go over here and see this, this, the projects if I go to their user account, but it's kind of just, you know, AWS sort of hacked the system by creating an account named AWS. 00:09:32.300 --> 00:09:33.880 But it's not really official. 00:09:34.120 --> 00:09:37.720 You don't get like a branded, sort of story. 00:09:37.720 --> 00:09:37.940 Right. 00:09:37.940 --> 00:09:39.280 You just get a, you know, use your profile. 00:09:39.280 --> 00:09:41.460 So GitHub has something like this. 00:09:41.460 --> 00:09:46.120 Like if you went to GitHub.com slash talk Python, this is the official organization. 00:09:46.120 --> 00:09:48.520 We have 47 repositories. 00:09:48.520 --> 00:09:50.620 We have six people involved. 00:09:50.620 --> 00:09:52.300 And you can sort of see, right? 00:09:52.300 --> 00:09:57.460 You can, you can put this together officially as, as not Michael, but like this group. 00:09:57.460 --> 00:09:57.720 Right. 00:09:57.720 --> 00:10:03.680 So the big announcement is introducing PyPI organizations by Ederbin. 00:10:03.680 --> 00:10:07.500 So today we are rolling out today being a few days ago. 00:10:07.500 --> 00:10:22.060 Today we are rolling out the first step in our plan to build financial support and long-term sustainability for the Python packaging index, while simultaneously giving our users one of the most requested features, organization accounts. 00:10:22.060 --> 00:10:26.920 So these are self-managed teams with their own exclusive branded web addresses. 00:10:27.480 --> 00:10:35.560 And the goal is to make PyPI easier for large community projects, organizations, and companies manage multiple sub teams and multiple packages. 00:10:35.560 --> 00:10:36.240 Right. 00:10:36.340 --> 00:10:42.580 So much like the GitHub org that I was talking about, you can say, okay, this person is an admin of it. 00:10:42.580 --> 00:10:45.880 And this person can have right access to that thing, but not this thing. 00:10:45.880 --> 00:10:46.220 Right. 00:10:46.220 --> 00:10:55.740 So kind of, kind of those types of things instead of, Hey, everyone in the company, here's the one and only username and password for PyPI Go. 00:10:55.740 --> 00:10:56.860 Interesting. 00:10:56.860 --> 00:10:57.840 yeah. 00:10:57.840 --> 00:10:57.940 Yeah. 00:10:57.940 --> 00:10:58.540 Yeah. 00:10:58.540 --> 00:11:03.520 And it's like, I opened this conversation, increase the idea is to increase sustainability. 00:11:03.620 --> 00:11:15.320 This last year, PyPI served 235 billion downloads for those packages and saw 57% year over year growth on download counts and bandwidth alike. 00:11:15.320 --> 00:11:16.260 That's great. 00:11:16.260 --> 00:11:22.040 But it also means costs and effort and infrastructure and all of that is just going up. 00:11:22.040 --> 00:11:24.660 Also, these organizations are not required. 00:11:24.660 --> 00:11:26.380 AWS can still manage it. 00:11:26.380 --> 00:11:28.240 However they are now they want. 00:11:28.240 --> 00:11:30.720 So these are opt-in and it does cost. 00:11:30.720 --> 00:11:32.100 It says a small fee. 00:11:32.100 --> 00:11:36.700 I would love to see small fee equals a hundred dollars a month or a dollar a month. 00:11:36.700 --> 00:11:37.700 I don't know what this is. 00:11:37.700 --> 00:11:39.940 maybe it says somewhere, maybe I got to go. 00:11:39.940 --> 00:11:40.720 It's a sliding scale. 00:11:40.720 --> 00:11:41.860 Yes, exactly. 00:11:41.860 --> 00:11:44.020 If you got to ask, no, just kidding. 00:11:44.020 --> 00:11:44.860 It says small fee. 00:11:44.860 --> 00:11:47.380 If you got to ask, it's not for you. 00:11:47.380 --> 00:11:52.700 Anyway, PyPI organizations, coming now, check it out. 00:11:52.700 --> 00:11:53.160 Okay. 00:11:53.160 --> 00:11:57.900 So is it just, oh, we don't know this yet, but is it just for things like, 00:11:57.940 --> 00:12:01.960 things like, companies or is it, could it be for, like, 00:12:01.960 --> 00:12:03.560 pytest or something like that? 00:12:03.560 --> 00:12:03.820 Sure. 00:12:03.820 --> 00:12:04.780 It could be, like, for pytest. 00:12:04.780 --> 00:12:08.880 I mean, you talked about, it says for large community projects, for example. 00:12:08.880 --> 00:12:09.380 Yeah. 00:12:09.380 --> 00:12:11.080 Like, you talked about Flask. 00:12:11.080 --> 00:12:14.440 well, you talked about Armin, who was the original creator of Flask. 00:12:14.680 --> 00:12:20.100 But that's now under the pallets project, which runs a bunch of different projects and has a bunch of contributors. 00:12:20.100 --> 00:12:24.480 Like, I think a pallets organization would be potentially reasonable, you know? 00:12:24.480 --> 00:12:24.940 Yeah. 00:12:24.940 --> 00:12:25.440 Yeah. 00:12:25.440 --> 00:12:29.340 It's going to be tough to come up with, like, pricing for something like this because, like we said, 00:12:29.340 --> 00:12:34.440 some of it is a bunch of volunteer organizations and some of it is, yeah, companies. 00:12:34.440 --> 00:12:35.600 so, yeah. 00:12:35.600 --> 00:12:36.020 Interesting. 00:12:36.020 --> 00:12:36.580 yeah. 00:12:36.580 --> 00:12:37.200 I don't know. 00:12:37.200 --> 00:12:42.280 I, it probably says somewhere, but I didn't see it in this article on the PyPI. 00:12:42.280 --> 00:12:42.940 Nice. 00:12:42.940 --> 00:12:43.380 Cool. 00:12:43.380 --> 00:12:47.740 Well, should we jump into the next topic? 00:12:47.740 --> 00:12:48.480 Yeah, go. 00:12:48.480 --> 00:12:49.060 Okay. 00:12:49.060 --> 00:12:54.480 Well, I just, we, I like this article by Bob Belderbos. 00:12:54.480 --> 00:12:58.500 It's, five tips to learn any new Python library faster. 00:12:58.500 --> 00:13:04.520 and this is, actually near and dear to my heart because we do this on a weekly basis. 00:13:04.520 --> 00:13:08.680 you know, trying something, trying something new. 00:13:08.680 --> 00:13:12.700 and, I think I have a condensed version of this, 00:13:12.700 --> 00:13:16.800 but let's kind of walk through, these are pretty good tips on, if you're, if you're thinking 00:13:16.800 --> 00:13:20.780 about using something, or just want to learn, you hear, here's something cool. 00:13:20.780 --> 00:13:22.760 You want to want to learn, learn about it. 00:13:22.760 --> 00:13:23.460 What do you do? 00:13:23.460 --> 00:13:28.220 so his first step is, quickly read the main docs. 00:13:28.220 --> 00:13:30.960 So read the manual, RTFM. 00:13:31.240 --> 00:13:36.840 especially I like things like if they have a quick start or getting started, 00:13:36.840 --> 00:13:39.320 uh, like I like to read that. 00:13:39.320 --> 00:13:41.240 If there's a video, go ahead and watch it. 00:13:41.240 --> 00:13:44.840 especially if it's a short video, go ahead and try that. 00:13:44.920 --> 00:13:45.580 So, okay. 00:13:45.580 --> 00:13:47.200 So, so you, so you know what it does great. 00:13:47.200 --> 00:13:51.560 And you kind of know how it works and then install number two is install it. 00:13:51.560 --> 00:13:53.180 I think this is funny. 00:13:53.180 --> 00:13:56.860 I mean, obviously you have to install it in order to play with it, but okay. 00:13:56.860 --> 00:13:57.520 Install it. 00:13:58.200 --> 00:14:00.860 number three is explore the library. 00:14:00.860 --> 00:14:02.180 Essentially play with it. 00:14:02.180 --> 00:14:05.020 play around, see what you do. 00:14:05.020 --> 00:14:10.760 Bob has a great idea of, of doing this within, Jupyter notebooks, to just kind 00:14:10.760 --> 00:14:12.420 of explore what it does. 00:14:12.420 --> 00:14:13.360 That's pretty great. 00:14:13.360 --> 00:14:16.860 and then, and then you have to kind of make it more deliberate. 00:14:16.860 --> 00:14:21.600 So instead of just playing around with like maybe the things it does try to do something 00:14:21.600 --> 00:14:22.860 with it, try to have a task. 00:14:22.860 --> 00:14:28.020 And this, and this is a deliberate called deliberate practice, but, 00:14:28.020 --> 00:14:30.640 this is where I think you're really going to start learning. 00:14:30.640 --> 00:14:36.640 Something is, actually trying to get something done because often there'll be extra features 00:14:36.640 --> 00:14:37.700 you don't need right away. 00:14:37.700 --> 00:14:43.420 with a lot of projects, most people use 20% of the functionality. 00:14:43.420 --> 00:14:46.280 So don't learn a hundred percent of the functionality. 00:14:46.280 --> 00:14:49.520 You learn the 20% that you need to get something done. 00:14:49.520 --> 00:14:55.320 So, deliberate exercise, and then maybe actually build something or change something. 00:14:55.320 --> 00:14:57.340 So, number five is build something. 00:14:57.340 --> 00:15:02.760 So, going into to a deeper level is actually incorporate this library in a project of yours, 00:15:02.760 --> 00:15:07.440 or if it's similar to a, another project that you're already using, and you're just thinking 00:15:07.440 --> 00:15:09.220 about switching, go ahead and try switching it. 00:15:09.220 --> 00:15:14.660 you might not stick with it, but kind of feel how, how, how easy it is to change over 00:15:14.660 --> 00:15:16.760 to this new, new project. 00:15:16.760 --> 00:15:19.420 And you might not publish it, but you might, it might be great. 00:15:19.420 --> 00:15:24.560 build, building something small is a good idea to, to just kind of get your hands dirty. 00:15:24.560 --> 00:15:30.600 And then, the bonus number six, I always like it when the people lie about how many tips 00:15:30.600 --> 00:15:30.980 there are. 00:15:30.980 --> 00:15:34.400 the real bonus is teaching it. 00:15:34.400 --> 00:15:37.400 and this, this is like massive, massive. 00:15:37.400 --> 00:15:43.840 and it just ties a bow on the whole learning process is trying to teach it back to somebody. 00:15:43.840 --> 00:15:50.160 And this could be a today I learned thing on your blog or an actual longer blog post, or maybe a little 00:15:50.160 --> 00:15:54.840 tutorial video or something, or actually just sit down and with somebody and try to talk to them 00:15:54.840 --> 00:15:55.240 about it. 00:15:55.240 --> 00:16:02.740 one of the things that I find even just for ourselves from, for this podcast, trying 00:16:02.740 --> 00:16:06.260 to look at it and go, if I was trying to teach this to somebody or tell somebody why they should 00:16:06.260 --> 00:16:06.700 use it. 00:16:06.780 --> 00:16:07.180 Why? 00:16:07.180 --> 00:16:08.600 I mean, what are the different points? 00:16:08.600 --> 00:16:11.960 So like just earlier when I was talking about Rye, what's different about that? 00:16:11.960 --> 00:16:17.540 Well, it's, it's different because it's, it handles the Python installs also. 00:16:17.540 --> 00:16:19.160 And it also kind of works like Pipex. 00:16:19.160 --> 00:16:23.200 I mean, the different things about it and then think about like, and then actually try it. 00:16:23.200 --> 00:16:23.940 So I tried it out. 00:16:23.940 --> 00:16:29.600 I went through, set up a, an extra little project directory and tried it 00:16:29.600 --> 00:16:32.860 out a few times and saw what it did, looked at the project Toml output. 00:16:32.860 --> 00:16:34.000 so yeah. 00:16:34.000 --> 00:16:36.460 And then, just doing that. 00:16:36.460 --> 00:16:38.720 So, some great things. 00:16:38.720 --> 00:16:39.320 Yeah. 00:16:39.320 --> 00:16:42.440 I, I think, you know, teach it is, is really cool. 00:16:42.440 --> 00:16:46.400 You don't have to be an expert at something to give a presentation on it. 00:16:46.400 --> 00:16:49.780 If you structure, as long as you're genuine about it, right? 00:16:49.780 --> 00:16:54.140 Like if you, you said, Hey, I'm going to teach you everything you need to know and how awesome 00:16:54.140 --> 00:16:54.940 this thing is. 00:16:54.940 --> 00:16:58.840 And really you just learned it last week at a conference talk. 00:16:58.840 --> 00:16:59.860 People might call you out. 00:16:59.860 --> 00:17:02.400 Like you don't seem to really know as much as you came. 00:17:02.400 --> 00:17:07.220 If you say, no, I'm, I'm excited about this thing. 00:17:07.220 --> 00:17:08.180 I just learned it. 00:17:08.180 --> 00:17:12.360 I wanted to share my excitement and, and just, you know, show you a quick getting started 00:17:12.360 --> 00:17:12.660 thing. 00:17:12.660 --> 00:17:15.060 And then people won't go like, well, why does he know it? 00:17:15.060 --> 00:17:15.780 Like you just start out. 00:17:15.780 --> 00:17:17.780 Well, I just learned it, but I'm, I'm excited. 00:17:17.840 --> 00:17:22.020 And I think you'll be excited too, if you, you know, so I do think those presentations 00:17:22.020 --> 00:17:23.120 are awesome. 00:17:23.120 --> 00:17:24.120 I mean, there's plenty of places. 00:17:24.120 --> 00:17:29.900 There's user groups and meetups, regional conferences, like online meetups. 00:17:29.900 --> 00:17:31.960 Those people are always looking for presenters. 00:17:31.960 --> 00:17:35.180 They're like, gosh, it's a week away and we don't have a speaker yet. 00:17:35.180 --> 00:17:35.420 Right. 00:17:35.420 --> 00:17:36.100 So reach out. 00:17:36.100 --> 00:17:39.560 I mean, there's a ton of opportunity to do that or even brown bags at your company. 00:17:39.560 --> 00:17:39.960 Yeah. 00:17:40.380 --> 00:17:43.860 I like the, I like that you brought up that, be honest about it. 00:17:43.860 --> 00:17:49.500 that you like, you can even say, I just, I just got excited about this, learned 00:17:49.500 --> 00:17:52.220 a little bit and I want to show you what it is. 00:17:52.220 --> 00:17:56.920 don't, I, yeah, don't make yourself out to be an expert in the, in the field. 00:17:56.920 --> 00:17:58.920 but that's great. 00:17:59.020 --> 00:18:04.100 That's this, this process actually is like exactly how I got started, blogging about 00:18:04.100 --> 00:18:08.920 testing is just learning, learning something new, writing an article about it and then writing 00:18:08.920 --> 00:18:09.300 a bunch. 00:18:09.300 --> 00:18:15.280 So if you really want to deep dive into a, into a, module or a package, you can write 00:18:15.280 --> 00:18:16.040 a series of them. 00:18:16.040 --> 00:18:16.340 Great. 00:18:16.340 --> 00:18:17.100 You're getting started. 00:18:17.100 --> 00:18:22.740 One of my first thoughts and then move on to like, well, how do I do this other thing 00:18:22.740 --> 00:18:23.120 with it? 00:18:23.120 --> 00:18:24.460 how do I do authentication? 00:18:24.460 --> 00:18:26.300 We'll do a, do a little article on that. 00:18:26.580 --> 00:18:30.180 and it, and then the whole thing could end up being a book. 00:18:30.180 --> 00:18:32.960 I mean, you could make a book or a course or something out of it eventually. 00:18:32.960 --> 00:18:36.880 So, but if you just want to do a quick one, this is a great way to. 00:18:36.880 --> 00:18:37.420 Yeah. 00:18:37.420 --> 00:18:37.880 All right. 00:18:37.880 --> 00:18:42.800 And, and speaking of just like, he opened Bob open his conversation here with like, and 00:18:42.800 --> 00:18:47.160 some of the things I'm learning are PyScript, Flet, PySimple GUI, Pyright, HTMX, Reddit, 00:18:47.160 --> 00:18:47.700 Leaflet. 00:18:47.700 --> 00:18:49.180 Those are all awesome. 00:18:49.180 --> 00:18:51.160 So I can see why you would want to learn those. 00:18:51.160 --> 00:18:56.220 And Liz out there says, I'm an, I'm excited about this type of presentations tend to be more 00:18:56.220 --> 00:18:58.240 to the point, which is indeed. 00:18:58.240 --> 00:18:58.680 Yeah. 00:18:58.680 --> 00:18:59.280 All right. 00:18:59.280 --> 00:19:00.440 What's next. 00:19:00.440 --> 00:19:02.800 We have GPUs next. 00:19:02.800 --> 00:19:03.620 All right. 00:19:03.620 --> 00:19:08.620 I know you heard that, we can do all sorts of amazing things by programming GPUs. 00:19:08.620 --> 00:19:14.180 And if we want to process, you know, tons of data, maybe we're doing medical research 00:19:14.180 --> 00:19:19.320 on protein folding, we're running around a cluster of GPUs and we could, you know, solve 00:19:19.320 --> 00:19:23.580 some kind of huge computational biological problem and make a big impact. 00:19:23.580 --> 00:19:27.660 But if you're going to do that, you sure better hope that you, if you're gonna do something 00:19:27.660 --> 00:19:31.140 like CUDA, you better hope that you have not just GPUs. 00:19:31.140 --> 00:19:32.160 That's way too broad. 00:19:32.160 --> 00:19:32.660 No, no, no. 00:19:32.660 --> 00:19:34.800 You have Nvidia GPUs. 00:19:34.800 --> 00:19:38.500 And Nvidia GPUs are sometimes hard to come by. 00:19:38.500 --> 00:19:42.200 A couple of years ago, they were very hard to come by unless you're using the cloud where 00:19:42.200 --> 00:19:42.880 you can go get them. 00:19:42.880 --> 00:19:43.100 Right. 00:19:43.360 --> 00:19:45.180 I have an awesome Mac here. 00:19:45.180 --> 00:19:54.660 I've got my M two pro Mac mini now, and that thing has 16, GPU cores on it. 00:19:54.660 --> 00:19:57.180 Can I do CUDA or use PI CUDA on it? 00:19:57.180 --> 00:19:59.640 No, that's not an Nvidia one. 00:19:59.640 --> 00:20:06.320 And so like honest on Mac, especially it's been extremely hard to do any sort of GPU computation. 00:20:06.320 --> 00:20:06.720 Right. 00:20:06.720 --> 00:20:07.160 Okay. 00:20:07.160 --> 00:20:11.680 We had the afterburner cards and those like weird external graphics cards on the older 00:20:11.680 --> 00:20:15.280 Intel ones, but those are not even an option in the last four years. 00:20:15.280 --> 00:20:17.740 So, you know, that's, that's a drawback. 00:20:17.740 --> 00:20:24.440 And on Mac, the graphics language like direct X on windows or open GL and a lot of things 00:20:24.440 --> 00:20:25.640 is called metal. 00:20:25.640 --> 00:20:30.920 And so I want to introduce you to a library and an article called Python gets down to the 00:20:30.920 --> 00:20:33.620 metal, not like CPU, but GPU. 00:20:33.620 --> 00:20:36.140 And it says, are you a Mac and Python person? 00:20:36.140 --> 00:20:38.220 Do you have a trillion numbers to multiply together? 00:20:38.220 --> 00:20:39.900 You don't have all day to wait for them. 00:20:40.520 --> 00:20:42.420 It says, well, Python is quite slow. 00:20:42.420 --> 00:20:46.000 Although the person acknowledges, I've been a happy Python user for quite a while. 00:20:46.000 --> 00:20:52.300 you know, for pure number crunching, Python is not as fast as the compiled languages like 00:20:52.300 --> 00:20:53.800 C and rest, which is totally true. 00:20:53.800 --> 00:20:55.880 Is it plenty fast to drive your web API? 00:20:55.880 --> 00:20:56.580 Probably. 00:20:56.580 --> 00:20:57.920 It's probably really fast for that. 00:20:57.920 --> 00:21:01.240 But if you literally have a trillion numbers, you want to just crunch them in a loop. 00:21:01.520 --> 00:21:03.580 The advice is not to do that, right? 00:21:03.580 --> 00:21:09.660 The advice is to use something like pandas or numpy or desk or something like that, which 00:21:09.660 --> 00:21:10.660 are really all C base. 00:21:10.660 --> 00:21:18.060 Or if you had a NVIDIA Jeep, graphics card, maybe you could use some kind of thing 00:21:18.060 --> 00:21:18.780 like PyCuda. 00:21:19.000 --> 00:21:23.940 But again, on the super powerful computer, it is just, you can't do it. 00:21:23.940 --> 00:21:26.020 There's no way to get an NVIDIA graphics card. 00:21:26.020 --> 00:21:32.200 However, if you could somehow program this metal, it says metal does have a way to program it. 00:21:32.200 --> 00:21:34.200 It's just, there's not a lot of things for it. 00:21:34.420 --> 00:21:40.400 And it says there's a language to do on GPU computation that looks very C++ like. 00:21:40.400 --> 00:21:44.960 And it says on a, on an M2, this is not the pro, but the regular one has eight GP cores, 00:21:44.960 --> 00:21:49.280 which means let's see, that gives some numbers here. 00:21:49.280 --> 00:21:49.820 Yeah. 00:21:49.820 --> 00:21:55.600 It says, on the eight GP, GPU core version, you could do about a trillion floating point 00:21:55.600 --> 00:21:56.620 operations a second. 00:21:56.620 --> 00:21:59.460 And that's the base version, right? 00:21:59.460 --> 00:22:04.300 And so the bigger models like mine closer up towards 10 trillion. 00:22:04.300 --> 00:22:04.700 Right. 00:22:04.700 --> 00:22:10.180 So mine's probably like six or seven trillion, but, you know, the high, the ultra 00:22:10.180 --> 00:22:13.040 max, I don't know, whatever the bigger ones can do even more than that. 00:22:13.040 --> 00:22:13.240 Right. 00:22:13.240 --> 00:22:16.160 So that is a ton of power. 00:22:16.160 --> 00:22:19.060 And so we introduce metal compute. 00:22:19.060 --> 00:22:21.340 So pip install metal compute. 00:22:21.340 --> 00:22:28.400 And with this, it's a little bit like doing SQL, like raw SQL database stuff in that you define 00:22:28.400 --> 00:22:32.040 a thing that you want to run on the graphics card. 00:22:32.040 --> 00:22:35.580 That looks a lot like a lot like C++. 00:22:35.580 --> 00:22:37.820 I think you would imagine Brian, what do you say? 00:22:37.820 --> 00:22:38.300 Yeah. 00:22:38.300 --> 00:22:38.820 Yeah. 00:22:38.820 --> 00:22:44.580 It's just hash include metal standard lib using namespace metal, write a function, do the 00:22:44.580 --> 00:22:44.940 operations. 00:22:44.940 --> 00:22:48.000 There's a lot of const device float star buffer. 00:22:48.000 --> 00:22:50.520 I mean, it's not easy, right? 00:22:50.520 --> 00:22:55.620 But it's also not that easy on, on CUDA and other things as well, generally speaking. 00:22:55.780 --> 00:22:58.960 So they come up and say, all right, what we're going to do is going to come up with a bunch 00:22:58.960 --> 00:23:01.280 of, you know, a vector and a matrix. 00:23:01.280 --> 00:23:04.460 And we're going to multiply them and do a bunch of work and get the answers out. 00:23:04.460 --> 00:23:06.340 And boom, off it goes. 00:23:06.340 --> 00:23:07.360 Print out the answer. 00:23:07.360 --> 00:23:08.260 Very cool. 00:23:09.260 --> 00:23:12.860 It's kind of cool that you don't have to, you don't have to compile it or anything though. 00:23:12.860 --> 00:23:15.680 I mean, or it is cool or have it in a separate file. 00:23:15.680 --> 00:23:16.760 It's just a string there. 00:23:16.760 --> 00:23:18.020 That's, that's neat. 00:23:18.020 --> 00:23:18.580 It is. 00:23:18.580 --> 00:23:23.020 And if I was a, if this was my job and someone said, Michael, you're writing this program, 00:23:23.020 --> 00:23:28.320 I would not do what they are doing in this example and put triple quotes and put metal 00:23:28.320 --> 00:23:30.480 code, which is like C++ in there. 00:23:30.480 --> 00:23:37.200 I would write a metal file or a C, call it CPP or whatever's going to give you the best 00:23:37.200 --> 00:23:39.520 autocomplete and color syntax highlighting. 00:23:39.520 --> 00:23:45.160 And then just do, you know, path read text and get that, you know, in one line, get that 00:23:45.160 --> 00:23:47.180 out, but have that in a separate file. 00:23:47.180 --> 00:23:49.920 So you could sort of more, more properly reason about it. 00:23:49.920 --> 00:23:56.720 But anyway, it says, look, we run this together and did a whole bunch of work, took 70 milliseconds 00:23:56.720 --> 00:23:57.980 to do 10 multiplications. 00:23:57.980 --> 00:24:00.100 Not that impressive because there's a startup cost. 00:24:00.100 --> 00:24:05.800 What if we gave it a billion, a billion multiplications to multiply that vector in that matrix? 00:24:05.800 --> 00:24:08.600 Oh, that takes 0.3 seconds, a billion times. 00:24:08.600 --> 00:24:09.280 That's a lot. 00:24:09.280 --> 00:24:09.720 Yeah. 00:24:09.720 --> 00:24:11.340 So, so that's pretty good. 00:24:11.340 --> 00:24:16.520 It does say though, look like part of the speed or part of the challenge is moving 00:24:16.520 --> 00:24:19.580 data into memory and then out of memory. 00:24:19.580 --> 00:24:23.980 And so the more you move stuff in and out rather than kind of loaded up with the data and then 00:24:23.980 --> 00:24:25.480 do operations on it, it will be slower. 00:24:25.480 --> 00:24:30.040 So it talks a bit about some of the performance things that you can do to make it faster. 00:24:30.040 --> 00:24:31.660 It gives some examples on how to do that. 00:24:31.660 --> 00:24:36.800 There's probably some interesting trade-offs with the Apple Silicon having a shared memory 00:24:36.800 --> 00:24:40.040 between memory memory and, and GPU memory, right? 00:24:40.040 --> 00:24:43.820 You don't actually have to copy it between there, but I suspect that you're going from Python 00:24:43.820 --> 00:24:48.060 to C++ memory and back through some kind of serialization, right? 00:24:48.060 --> 00:24:49.960 That that's going to have some kind of cost. 00:24:49.960 --> 00:24:50.300 Who knows? 00:24:50.300 --> 00:24:57.020 Anyway, there's some cool examples of a Mandelbrot set being computed with this or Julia set rather. 00:24:57.020 --> 00:25:02.520 But yeah, people are been dreaming of doing GPU processing on their Macs. 00:25:02.640 --> 00:25:04.020 Well, this might be worth checking out. 00:25:04.020 --> 00:25:04.500 Nice. 00:25:04.500 --> 00:25:09.820 The other thing that's kind of cool about it is it doesn't, you know, it's not like a library 00:25:09.820 --> 00:25:16.160 that takes Python code and compiles it or transpiles it to run on the GPU, which would be awesome. 00:25:16.360 --> 00:25:20.580 But at the same time, if it doesn't quite get it right, how much control do you have? 00:25:20.580 --> 00:25:21.540 How useful is it? 00:25:21.540 --> 00:25:21.860 Right. 00:25:21.860 --> 00:25:22.860 You don't know. 00:25:22.860 --> 00:25:27.940 Like here, you can just, if you can just give it the data as an array, then you're just writing 00:25:27.940 --> 00:25:30.460 straight metal, which is a bit of a pain if you don't know it. 00:25:30.460 --> 00:25:35.760 But at the same time, it's, it means that it's, it's super flexible, kind of like a DB API. 00:25:35.760 --> 00:25:39.660 You open a connection, you say, here's a string, run that on the database. 00:25:39.660 --> 00:25:45.100 You can give it a selector, some kind of query or update, and it's, it kind of gets out of the way. 00:25:45.220 --> 00:25:47.000 So it seems pretty flexible in that regard. 00:25:47.000 --> 00:25:47.500 Yeah. 00:25:47.500 --> 00:25:47.980 Yeah. 00:25:47.980 --> 00:25:49.440 Interesting. 00:25:49.440 --> 00:25:50.800 And this Mac only, right? 00:25:50.800 --> 00:25:51.480 So this is. 00:25:51.480 --> 00:25:52.840 Yeah, it's Mac only. 00:25:52.840 --> 00:25:54.480 But take that NVIDIA. 00:25:54.480 --> 00:25:55.520 You can't run Mac. 00:25:55.520 --> 00:25:56.040 No, just kidding. 00:25:56.040 --> 00:26:00.660 I have both an NVIDIA card and this, but I don't really have, I would like to do more GPU 00:26:00.660 --> 00:26:03.720 stuff, but I just don't have a trillion numbers that need multiplying right now. 00:26:03.720 --> 00:26:06.480 Well, you know, it's not a bad thing. 00:26:06.480 --> 00:26:06.680 Someday. 00:26:06.680 --> 00:26:07.200 No. 00:26:07.200 --> 00:26:08.700 All right. 00:26:08.700 --> 00:26:09.120 Over to you. 00:26:09.120 --> 00:26:11.820 I've got, so we're onto extras. 00:26:12.920 --> 00:26:15.460 I've got just one extra that I wanted to bring up. 00:26:15.460 --> 00:26:18.160 And that was just the textual. 00:26:18.160 --> 00:26:25.780 So Will McGooghan posted like this picture and like with no explanation. 00:26:25.780 --> 00:26:30.860 Apparently it's the, it's the weird, I'm showing a weird bird with a large mouth. 00:26:30.860 --> 00:26:32.700 It's kind of an ugly thing, I think. 00:26:32.700 --> 00:26:35.880 But it's the logo for frog mouth. 00:26:35.880 --> 00:26:37.360 And what is frog mouth? 00:26:37.360 --> 00:26:43.140 Frog mouth is the first, apparently first of possibly more to come applications that the 00:26:43.140 --> 00:26:46.100 textual team is releasing that are built on textual. 00:26:46.100 --> 00:26:49.800 So frog mouth is a markdown viewer and browser for your terminal. 00:26:49.800 --> 00:26:52.580 And it looks pretty clean. 00:26:52.580 --> 00:26:53.860 I tried it out as well. 00:26:54.260 --> 00:26:59.260 I haven't been able to get like these, these, these menu bar thing or the tree things 00:26:59.260 --> 00:26:59.980 on the side. 00:26:59.980 --> 00:27:06.400 But it's like a, it's like a navigation thing with like, you can browse, browse your markdown 00:27:06.400 --> 00:27:08.160 with within textual. 00:27:08.160 --> 00:27:09.280 So it's kind of fun. 00:27:09.280 --> 00:27:10.020 Yeah. 00:27:10.020 --> 00:27:13.160 Continues to impress with what they can build with that stuff. 00:27:13.160 --> 00:27:13.600 Yeah. 00:27:13.600 --> 00:27:16.640 And this is the application that I tried when I was talking about Rye. 00:27:16.640 --> 00:27:21.940 I tried installing this as a global application and then it worked just fine. 00:27:21.940 --> 00:27:22.260 So. 00:27:22.260 --> 00:27:22.700 Yeah. 00:27:22.700 --> 00:27:22.920 Cool. 00:27:22.920 --> 00:27:23.500 All right. 00:27:23.500 --> 00:27:25.800 I would like to serenade the audience, Brian. 00:27:25.800 --> 00:27:26.940 Oh, yay. 00:27:26.940 --> 00:27:27.640 Yeah. 00:27:27.640 --> 00:27:29.320 I was going to talk about this as a main item. 00:27:29.320 --> 00:27:31.600 This thing called serenade at serenade.ai. 00:27:31.600 --> 00:27:34.120 And it's really neat. 00:27:34.120 --> 00:27:42.500 What it does is you install a plugin for your editor where your editor equals VS Code or Jetbrains 00:27:42.500 --> 00:27:42.900 IDs. 00:27:42.900 --> 00:27:43.940 None of them do. 00:27:43.940 --> 00:27:46.940 And then you run this in the background and you can speak to it. 00:27:46.940 --> 00:27:48.560 Like you hit a hot key or whatever. 00:27:48.980 --> 00:27:53.620 And you basically start speaking code oriented operations. 00:27:53.620 --> 00:27:59.400 So there's a cool example that it shows somewhere in here. 00:27:59.400 --> 00:28:00.040 Let's see. 00:28:00.040 --> 00:28:00.460 Yeah. 00:28:00.460 --> 00:28:05.540 If you go and click on the docs, you'll see a bit of a video thing here. 00:28:05.540 --> 00:28:12.820 And basically you can go into it and you can say, you know, teach it to do tests. 00:28:12.820 --> 00:28:14.360 You can navigate around. 00:28:14.360 --> 00:28:15.180 This is kind of cool. 00:28:15.180 --> 00:28:18.380 So if you're typing in the editor, you're kind of good. 00:28:18.380 --> 00:28:21.120 I mean, I know if you have RSI and stuff, that's not ideal. 00:28:21.120 --> 00:28:25.580 But one of the challenges is like, okay, I need to leave this and navigate over there. 00:28:25.580 --> 00:28:31.440 So you can say things like open some file name and it'll actually go through your editor 00:28:31.440 --> 00:28:33.320 and say, oh, that's over in this directory. 00:28:33.320 --> 00:28:35.460 You need to expand the section and it'll jump to it. 00:28:35.460 --> 00:28:40.180 Or you can say, go to this function or, you know, those kinds of things you can speak to 00:28:40.180 --> 00:28:42.080 it and it'll do it. 00:28:42.080 --> 00:28:43.560 So anyway, it's really cool. 00:28:43.560 --> 00:28:45.180 Why is it not the main item? 00:28:45.180 --> 00:28:47.320 Because I'm super excited about these kinds of things. 00:28:47.320 --> 00:28:52.600 The reason it's not is it hasn't really been touched for coming up on a year. 00:28:52.600 --> 00:28:54.620 And that was just a merge of some PR. 00:28:54.620 --> 00:28:56.580 Is it still going? 00:28:56.680 --> 00:28:57.220 I don't know. 00:28:57.220 --> 00:29:02.560 It was kind of working pretty good, but then it was throwing errors when I, so I don't 00:29:02.560 --> 00:29:02.660 know. 00:29:02.660 --> 00:29:03.520 I love the idea. 00:29:03.520 --> 00:29:06.980 If this thing comes back to life, you know, someone out there, let us know. 00:29:06.980 --> 00:29:12.340 Cause this is super cool, but it doesn't quite seem to be getting kept up with the editors 00:29:12.340 --> 00:29:14.040 and tools and so on. 00:29:14.040 --> 00:29:16.220 I liked your comment in the show notes. 00:29:16.220 --> 00:29:19.200 Serenade has seemed to gone silent. 00:29:19.200 --> 00:29:20.420 It has gone silent. 00:29:20.420 --> 00:29:21.700 Oh, thank you. 00:29:21.700 --> 00:29:22.580 It sure has. 00:29:22.580 --> 00:29:24.680 But it's still worth checking out. 00:29:24.680 --> 00:29:25.140 It's kind of cool. 00:29:25.280 --> 00:29:31.940 And then Brian Skin is when I, we've been talking a lot about packaging on this episode 00:29:31.940 --> 00:29:38.920 and I did my packaging discussion and inspired by that, or maybe just the discussion that 00:29:38.920 --> 00:29:41.220 I was also inspired by. 00:29:41.220 --> 00:29:50.540 They're setting up a Python distribution packaging round table, not just of the people inside Python 00:29:50.540 --> 00:29:57.580 core devs world, but in the broader ecosystem for like Anaconda and data science and that. 00:29:57.580 --> 00:29:58.040 All right. 00:29:58.040 --> 00:30:06.020 Do they have 13 maintainers across nine projects lined up for Tuesday, May 9th and a link to 00:30:06.020 --> 00:30:06.720 go attend it. 00:30:07.020 --> 00:30:09.840 So if you're interested, you can go check that out. 00:30:09.840 --> 00:30:11.340 Yeah. 00:30:11.340 --> 00:30:13.780 So I'll put a link in the show notes. 00:30:13.780 --> 00:30:13.980 Yeah. 00:30:13.980 --> 00:30:14.320 Cool. 00:30:14.320 --> 00:30:14.760 Yeah. 00:30:14.760 --> 00:30:16.860 That's it for the extras on my end. 00:30:16.860 --> 00:30:18.060 How about a joke? 00:30:18.060 --> 00:30:19.100 Yeah. 00:30:19.100 --> 00:30:23.700 But before we go there, I just wanted to say, I just remembered the person that like told 00:30:23.700 --> 00:30:25.060 me about Ryan in the first place. 00:30:25.060 --> 00:30:26.220 And now I feel like a dork. 00:30:26.220 --> 00:30:27.500 It was Paul Everitt. 00:30:27.500 --> 00:30:29.440 So thanks Paul from JetBrains. 00:30:29.440 --> 00:30:30.520 Awesome. 00:30:30.520 --> 00:30:31.020 Yeah. 00:30:31.020 --> 00:30:37.000 Paul was quite the host at PyCon and did a bunch of awesome stuff for many people and much 00:30:37.000 --> 00:30:37.400 appreciated. 00:30:37.400 --> 00:30:38.340 All right. 00:30:38.340 --> 00:30:39.080 How about a joke? 00:30:39.080 --> 00:30:39.840 All right. 00:30:39.840 --> 00:30:42.280 Before I put this on the screen, I'll tell you about it. 00:30:42.280 --> 00:30:46.660 You know, sometimes programming is just amazing. 00:30:46.660 --> 00:30:48.980 You just get in the zone and you just go and look what I built. 00:30:48.980 --> 00:30:49.820 Boom, boom, boom, boom. 00:30:50.140 --> 00:30:54.300 Other times you end up with a bald patch where you've been tearing your hair out. 00:30:54.300 --> 00:30:55.680 You're like, no, why? 00:30:55.680 --> 00:30:58.200 You may end up yelling at the computer, right? 00:30:58.200 --> 00:30:59.320 There's just like a bunch of stuff. 00:30:59.320 --> 00:31:04.380 And this joke highlights the small wins you might make in this situation. 00:31:04.380 --> 00:31:04.760 Okay. 00:31:04.760 --> 00:31:12.300 So it's just a person with two monitors, a bunch of energy drinks crushed next to them, 00:31:12.300 --> 00:31:14.500 a bunch of wrappers, empty coffee. 00:31:14.500 --> 00:31:18.020 They've clearly been here for a while and the arms are up like, yes. 00:31:18.660 --> 00:31:20.360 Wow, a different error message. 00:31:20.360 --> 00:31:21.660 Finally, some progress. 00:31:21.660 --> 00:31:24.220 Yes. 00:31:24.220 --> 00:31:31.280 Have I mentioned I've been working with a guy named Lauren on a Flutter mobile app? 00:31:31.280 --> 00:31:34.220 Let me tell you, there are a lot of tools in that tool chain. 00:31:34.220 --> 00:31:39.240 And more than once here, I've been like, yes, that's not the same error. 00:31:39.240 --> 00:31:40.260 We're making progress. 00:31:40.260 --> 00:31:41.500 Yeah. 00:31:44.500 --> 00:31:47.720 This was me yesterday for half the day. 00:31:47.720 --> 00:31:47.960 Yeah. 00:31:47.960 --> 00:31:56.780 Working with a Docker compile that used Docker and Artifactory and a whole bunch of other C++ stuff. 00:31:56.780 --> 00:31:57.900 Indeed. 00:31:57.900 --> 00:31:59.480 All right. 00:31:59.480 --> 00:32:03.780 Well, let's hope for different error messages for anyone out there struggling. 00:32:03.780 --> 00:32:06.280 And then eventually, no more error messages. 00:32:06.280 --> 00:32:08.100 That's a good one. 00:32:08.520 --> 00:32:10.760 Like, may you have a different error message tomorrow. 00:32:10.760 --> 00:32:12.020 Exactly. 00:32:12.020 --> 00:32:16.380 May you live in interesting times and may you have different error messages. 00:32:16.380 --> 00:32:17.540 All right. 00:32:17.540 --> 00:32:18.340 Well, thanks for being here, Brian. 00:32:18.340 --> 00:32:18.940 Thank you. 00:32:18.940 --> 00:32:19.600 Thanks, everyone, for listening. 00:32:19.600 --> 00:32:20.380 All right. 00:32:20.380 --> 00:32:20.880 Bye.