WEBVTT 00:00:00.001 --> 00:00:04.660 Hello and welcome to Python Bytes, where we deliver Python news and headlines directly to your earbuds. 00:00:04.660 --> 00:00:09.620 This is episode 262, recorded December 8th, 2021. 00:00:09.620 --> 00:00:11.220 Oh my gosh, it's almost winter. 00:00:11.220 --> 00:00:12.320 I'm Michael Kennedy. 00:00:12.320 --> 00:00:13.540 And I'm Brian Okken. 00:00:13.540 --> 00:00:14.700 And I'm Leah Cole. 00:00:14.700 --> 00:00:15.660 Yay. 00:00:15.660 --> 00:00:19.060 Yay. So great to have you here. Thanks for being here on the show. 00:00:19.060 --> 00:00:20.600 Yeah, happy to be here. 00:00:20.600 --> 00:00:26.820 You and I got a chance to discuss Airflow over on Talk Python a couple months ago, something like that. 00:00:26.820 --> 00:00:27.260 Yeah. 00:00:27.260 --> 00:00:34.360 Yeah, but now we'll probably do a little more Airflow over here for people who aren't familiar with that, but also just whatever you're interested in. 00:00:34.360 --> 00:00:39.260 So great to have you here. Why don't you tell people a quick bit about yourself before we jump into the topics? 00:00:39.260 --> 00:00:45.560 Sure. So I'm Leah and I am a developer relations engineer in Google Cloud. 00:00:45.560 --> 00:00:56.780 And specifically, I work on Cloud Composer, which is our hosted managed product of the popular Apache Airflow project, which we'll talk about a little bit later. 00:00:56.780 --> 00:01:07.480 And in addition to writing samples and content for that, I also work with a group of fellow engineers and we maintain all Python samples for Google Cloud. 00:01:07.880 --> 00:01:13.980 And make sure that they stay tested up to date and are healthy and are getting reviewed for new samples. 00:01:13.980 --> 00:01:17.980 And that's a lot of fun. That kind of fell into my lap and has been a good time. 00:01:17.980 --> 00:01:18.080 Yeah, that's fantastic. 00:01:18.080 --> 00:01:18.680 Yeah. 00:01:18.680 --> 00:01:25.000 I remember Python being one of the original two supported languages on Google Cloud, right? It had sort of a special place. 00:01:25.000 --> 00:01:27.460 Yeah. Now it's one of seven, I think. 00:01:28.200 --> 00:01:40.400 Yeah. Cool. Well, that sounds like such a fun job. I've always imagined dev relations type of jobs to be super fun. Maybe slightly less fun in COVID because the travel and the conferences and, you know, all those kinds of things are part of it. 00:01:40.400 --> 00:01:41.640 But still a fun job, right? 00:01:41.640 --> 00:01:47.420 Still a good time. Every day is a little bit different. You kind of never know what's going to happen. And that's part of what I like about it. 00:01:47.420 --> 00:01:52.940 Yeah. Awesome. Cool. Brian, I don't even know what you're going to cover. So I don't know what's going to happen. Why don't you let us know? 00:01:53.300 --> 00:01:54.340 You don't know what I'm going to cover? 00:01:54.340 --> 00:01:56.520 Well, I'm not looking at my docs yet. 00:01:56.520 --> 00:02:05.360 Oh, okay. Sorry. Fighting it cold. I am super excited. pytest 7, release candidate one, is out. 00:02:05.360 --> 00:02:07.980 Oh, that's excellent. That's big news. 00:02:07.980 --> 00:02:18.780 It is. The last release for pytest was, or six, they've done other dot releases, but the 6.2 or 6.0 came out. 6.2, I don't know. I lost track. 00:02:18.780 --> 00:02:21.860 We use 6.2.4 for our GCP samples. 00:02:21.860 --> 00:02:23.140 Oh, you do? 00:02:23.140 --> 00:02:23.760 We do. 00:02:23.760 --> 00:02:47.500 Well, I think it was, I wrote this down. The 6.2.0 was released on December 2020. So it's been, we're ready for a new one. So 7.0 is out, the release candidate at least. And so because it's a release candidate, to install it, you have to do pip install pytest double equal 7.0.0 RC1. We've got that in the show notes. 00:02:47.700 --> 00:02:59.440 It's also on the release announcement page for pytest. But I wanted to go through some of the cool features that I'm really excited about. There's a lot of great things in there. 00:03:01.320 --> 00:03:16.040 But there's some little improvements with the aprox thing. So one of the things that pytest has is an aprox. So you can say floating point numbers, if you're comparing them, you should never do equal. But you can do equal aprox with pytest. And it's really pretty cool. 00:03:16.380 --> 00:03:24.240 I didn't know that because any science you're doing is so, like double equals is the kiss of death for floating point math comparison. 00:03:24.240 --> 00:03:35.940 Yeah. Well, the pytest of Prox does now the docs reference the NumPy comparisons, which is nice because NumPy has some really cool features around that. 00:03:35.940 --> 00:03:47.400 But pytest out of the box does. And now also with mappings and dicts and other sets, it handles decimal types, which is nice. 00:03:47.400 --> 00:03:53.600 Decimal types, of course, are very useful when working with money and other things that need to be exact decimals. 00:03:53.860 --> 00:04:06.540 One of the things that's really cool is the sequences are compared better. So if you have like a list of numbers and you compare against an approximate list of another numbers, I didn't know you could do this. 00:04:06.540 --> 00:04:12.580 It will tell you which index was wrong and by how much. 00:04:12.580 --> 00:04:17.520 And actually not by how much, but what the expected was. And that's pretty neat. 00:04:17.520 --> 00:04:23.580 So those are the little minor features. Most of these are kind of minor, but major for somebody, right? 00:04:23.740 --> 00:04:31.660 So one of the things I like is that some people have mentioned fixtures or sometimes when people use a lot of fixtures, they don't know where the fixtures are. 00:04:31.660 --> 00:04:40.500 Well, there's a couple of flags, fixtures per test and --fixtures. Both those flags are helpful to find out what fixtures you have available. 00:04:40.500 --> 00:04:46.780 And now by default, they print the location of the path with the fixture name. 00:04:47.220 --> 00:04:52.040 And you can also do a verbose option that prints out the full doc string, which is pretty handy. 00:04:52.040 --> 00:04:57.700 A couple of things that I'm really excited about are a Python path that's been added. 00:04:57.700 --> 00:05:01.180 And that was a feature I added to the project, which is fun. 00:05:01.180 --> 00:05:04.980 Nice. It's cool to see the contributions you're making coming back out. 00:05:04.980 --> 00:05:10.560 Yeah, it's cool. And then there's a bunch of other features that I contributed to by just saying, 00:05:10.700 --> 00:05:14.120 this is a little weird. Can we fix this? And somebody else volunteered to fix it. 00:05:14.120 --> 00:05:15.320 So it's nice. 00:05:15.320 --> 00:05:16.980 That's the best kind of contribution. 00:05:16.980 --> 00:05:18.780 Yeah. 00:05:19.580 --> 00:05:26.100 One of the improvements in the docs, which is kind of fun, is there's an auto-generated list of... 00:05:26.100 --> 00:05:27.880 So I've got the changelog going on here. 00:05:27.880 --> 00:05:30.460 And I got to come back to this. 00:05:30.460 --> 00:05:32.660 There's an auto-generated list of plugins. 00:05:32.660 --> 00:05:35.020 And there's 963 right now. 00:05:35.020 --> 00:05:35.820 We'll refresh it. 00:05:35.820 --> 00:05:37.160 No, still 963. 00:05:37.160 --> 00:05:38.140 But that's a lot. 00:05:38.140 --> 00:05:45.400 When I first started writing the beta or the second edition of the Pi test book, 00:05:45.620 --> 00:05:48.880 I noticed this and I wrote it down, but the number keeps changing. 00:05:48.880 --> 00:05:49.980 So I took out the number. 00:05:49.980 --> 00:05:51.160 I'm like, it's a lot. 00:05:51.160 --> 00:05:53.200 There's a lot of cool plugins. 00:05:53.200 --> 00:05:57.020 One of the things that if you'll notice when you go to the changelog, 00:05:57.020 --> 00:06:00.940 it starts with breaking changes and then deprecations. 00:06:00.940 --> 00:06:04.460 And I think this is around because people, when they upgrade, 00:06:04.460 --> 00:06:06.200 they want to know if it's going to break their code or not. 00:06:06.200 --> 00:06:09.240 I have tested a bunch of stuff and upgraded from 6 to 7. 00:06:09.240 --> 00:06:11.580 And I haven't noticed a lot. 00:06:11.780 --> 00:06:15.600 There was like a 6.1 to 6.2. 00:06:15.600 --> 00:06:17.120 I can't remember what the... 00:06:17.120 --> 00:06:22.200 There was one break a while ago in the 6x that messed some plugin authors. 00:06:22.200 --> 00:06:23.760 But I haven't noticed any problems. 00:06:23.760 --> 00:06:25.000 So please try these out. 00:06:25.000 --> 00:06:29.360 I wish they would do the features first and then not the breaking changes. 00:06:29.360 --> 00:06:29.820 Because that's... 00:06:29.820 --> 00:06:33.240 I suspect it's the people working deep in the guts, 00:06:33.240 --> 00:06:36.040 like the plugin authors that hit these deprecations 00:06:36.040 --> 00:06:39.460 and not just people doing assert this equals that type of work. 00:06:39.800 --> 00:06:39.960 Yep. 00:06:39.960 --> 00:06:40.460 Right. 00:06:40.460 --> 00:06:42.680 One of the things that I didn't list, 00:06:42.680 --> 00:06:45.020 but I think a lot of people are excited about, 00:06:45.020 --> 00:06:48.200 there's more the objects within pytest that people are using. 00:06:48.200 --> 00:06:53.600 More of them are type hinted now so that you can do type hints with objects. 00:06:53.600 --> 00:06:54.620 Oh, that's nice. 00:06:54.620 --> 00:06:55.080 Yeah. 00:06:55.080 --> 00:06:55.800 That's really nice. 00:06:55.800 --> 00:06:57.160 So fun. 00:06:57.160 --> 00:06:59.100 Leah, do you use pytest? 00:06:59.100 --> 00:07:00.340 Some of these changes exciting? 00:07:00.340 --> 00:07:01.240 We do. 00:07:01.240 --> 00:07:03.860 We use pytest on our Python samples. 00:07:03.860 --> 00:07:07.680 And so I actually, the one that was most exciting to me was the fixtures. 00:07:07.680 --> 00:07:12.800 Figuring out where fixtures are is definitely something that comes into play for me, 00:07:12.800 --> 00:07:16.380 especially when we're maintaining something that was written a while ago 00:07:16.380 --> 00:07:19.280 by someone who might not be working on that code anymore. 00:07:19.280 --> 00:07:20.260 Yeah. 00:07:20.260 --> 00:07:20.880 Yeah. 00:07:20.880 --> 00:07:21.520 Nice. 00:07:21.520 --> 00:07:21.940 Yeah. 00:07:21.940 --> 00:07:22.540 This is great. 00:07:22.540 --> 00:07:24.840 I love the pip installable RC1. 00:07:24.840 --> 00:07:25.300 That's great. 00:07:25.300 --> 00:07:28.240 And before we move on, let's take a step back. 00:07:28.240 --> 00:07:29.480 Roman Wright, author of Beanie. 00:07:29.480 --> 00:07:29.960 Hey, Roman. 00:07:29.960 --> 00:07:30.860 Out there in the audience says, 00:07:30.920 --> 00:07:32.400 Hey, I'm a big fan of Google Cloud. 00:07:32.400 --> 00:07:33.340 Oh, thank you. 00:07:33.340 --> 00:07:34.220 For sure. 00:07:34.220 --> 00:07:37.500 Well, I've got some fun stuff to talk about next year. 00:07:37.500 --> 00:07:40.160 I want to talk about this thing that David Smith, 00:07:40.160 --> 00:07:45.560 former guest co-host here on Python Bytes, sent over and said, 00:07:45.560 --> 00:07:46.240 this looks cool. 00:07:46.240 --> 00:07:51.980 Sam Lowe and Philip Guell released this thing called Pandas Tutor. 00:07:51.980 --> 00:07:52.860 This is cool. 00:07:52.860 --> 00:07:53.460 Yeah. 00:07:53.460 --> 00:07:57.800 Previously, Philip had built Python Tutor at pythontutor.com. 00:07:57.800 --> 00:08:00.300 Now there's pandastutor.com. 00:08:00.500 --> 00:08:05.600 And it's all about just helping you understand what the code does. 00:08:05.600 --> 00:08:08.980 So it basically says, look, there's this code here. 00:08:08.980 --> 00:08:13.060 Like imagine you've got a list of dogs that have a breed, a type, a longevity, 00:08:13.060 --> 00:08:15.900 a type is like a herding dog or a toy dog. 00:08:15.900 --> 00:08:16.900 It goes in a purse. 00:08:16.900 --> 00:08:19.320 Longevity, size, weight, and so on. 00:08:19.320 --> 00:08:20.740 And you've got that as a data frame. 00:08:20.740 --> 00:08:27.680 If you wrote dogs with a size equal, equal medium, then sort values on type and then group by, 00:08:27.680 --> 00:08:29.040 by type and then show the median. 00:08:29.040 --> 00:08:30.860 Well, what is that actually doing? 00:08:30.860 --> 00:08:32.220 Like, how do I understand that? 00:08:32.220 --> 00:08:32.480 Right. 00:08:32.520 --> 00:08:36.620 As somebody learning Pandas, imagine I don't really have a database background. 00:08:36.620 --> 00:08:40.720 And so I'm not sort of trying to map that over to like, okay, there's the where clause, there's 00:08:40.720 --> 00:08:41.520 the order by clause. 00:08:41.520 --> 00:08:42.820 And, you know, like that kind of business. 00:08:42.820 --> 00:08:43.060 Right. 00:08:43.360 --> 00:08:48.920 So what is happening when I write that code, either because I'm coming across it for the 00:08:48.920 --> 00:08:53.720 first time or, which happens to me a lot, I wrote it two years ago and understood it perfectly 00:08:53.720 --> 00:08:54.020 then. 00:08:54.020 --> 00:08:55.160 I have no idea what it does now. 00:08:55.160 --> 00:08:56.480 You want to know what it does? 00:08:56.480 --> 00:08:57.080 Yeah. 00:08:57.080 --> 00:08:58.180 That happens way too often. 00:08:58.180 --> 00:08:58.460 Right. 00:08:58.460 --> 00:09:05.820 So what you do is you can go and run this code over in Pandas Tutor and you say visualize 00:09:05.820 --> 00:09:08.040 and says running a code, please wait. 00:09:08.040 --> 00:09:10.920 And so what they do is they put a CSV bit of text in here. 00:09:10.980 --> 00:09:14.580 Like a triple string and then use Pandas read and then just do that one line. 00:09:14.580 --> 00:09:16.320 So that's a nice way to kind of get data in there. 00:09:16.320 --> 00:09:18.940 And the way to think about this is steps. 00:09:18.940 --> 00:09:21.880 It shows you what is the first step and what is the second step and so on. 00:09:21.880 --> 00:09:26.320 So when you go there, you'll see that it has the code that we were talking about. 00:09:26.320 --> 00:09:32.220 But then right now the effective where clause, the filter is regular font and the rest is gray. 00:09:32.220 --> 00:09:33.560 It's like fade into the background. 00:09:33.560 --> 00:09:39.460 And so you can actually see what the starting data frame was and the ending data frame and 00:09:39.460 --> 00:09:40.320 then how it got in there. 00:09:40.340 --> 00:09:44.080 And you can use the mouse over like, so what they're saying is the type is medium. 00:09:44.080 --> 00:09:47.680 So if you hover over like a large or a small dog, there's just no arrow. 00:09:47.680 --> 00:09:52.720 But if you hover over medium, it shows you where in the result that that thing landed. 00:09:52.720 --> 00:09:53.480 Isn't that cool? 00:09:53.480 --> 00:09:54.440 That's wild. 00:09:54.440 --> 00:09:55.600 Isn't that wild? 00:09:55.600 --> 00:10:00.280 And so then you can see size has all the values on the left and then the size is grouped on 00:10:00.280 --> 00:10:03.340 the right and it shows medium, medium, medium, medium, because that's all that's in there. 00:10:03.340 --> 00:10:06.460 Now, when I first looked at this, I'm like, there's a bunch of stuff on the screen. 00:10:06.460 --> 00:10:07.120 What's going on? 00:10:07.620 --> 00:10:11.380 I noticed the arrows, but then what it took me a minute to realize is there's multiple 00:10:11.380 --> 00:10:11.920 steps. 00:10:11.920 --> 00:10:16.200 So the next thing, if you scroll down, shows the same code at the top, but now the sort 00:10:16.200 --> 00:10:18.780 values type is highlighted, right? 00:10:18.780 --> 00:10:21.540 That's the next part of what looks like one expression in pandas. 00:10:21.540 --> 00:10:24.780 And so now it highlights the column that it's sorting on. 00:10:24.780 --> 00:10:29.620 And you can actually see the arrows pointing to how they were reordered in the result because 00:10:29.620 --> 00:10:30.720 you're sorting by type. 00:10:30.720 --> 00:10:34.080 So it's non-sporting, non-sporting, non-sporting, non-sporting, and then sporting, sporting, and 00:10:34.080 --> 00:10:35.580 working, working, and so on. 00:10:35.580 --> 00:10:36.960 So that was step two. 00:10:36.960 --> 00:10:39.440 And we have a group by, this one's interesting. 00:10:39.440 --> 00:10:41.060 It doesn't have arrows as colors. 00:10:41.320 --> 00:10:46.200 So the group by type, again, non-sporting, sporting, and so on, you end up with these 00:10:46.200 --> 00:10:46.560 groups. 00:10:46.560 --> 00:10:52.240 Like here's a blue, a blue box of all the non-sporting dogs, the bulldog, the poodle, the French bulldog 00:10:52.240 --> 00:10:52.980 is so cute. 00:10:52.980 --> 00:10:56.140 Then you've got the golden retriever and the Labrador and the boxer, right? 00:10:56.140 --> 00:10:58.080 So these are grouped into the colors. 00:10:58.080 --> 00:11:03.580 And then finally you do the median and it shows how those groups reduce down to statistics. 00:11:03.660 --> 00:11:08.100 The longevity of a non-sporting dog is less than a sporting dog, apparently, but they're 00:11:08.100 --> 00:11:08.580 also lighter. 00:11:08.580 --> 00:11:10.360 So anyway, what do you all think? 00:11:10.360 --> 00:11:11.540 Oh my gosh. 00:11:11.540 --> 00:11:12.500 I love this. 00:11:12.500 --> 00:11:13.580 This is nice, right? 00:11:13.580 --> 00:11:17.360 I'm a very visual learner, so I really appreciate this. 00:11:17.360 --> 00:11:22.000 And especially if you're working with data that you kind of aren't sure what it does and 00:11:22.000 --> 00:11:24.540 or the code, like that's pretty incredible. 00:11:24.540 --> 00:11:25.720 I'm filing this away. 00:11:25.720 --> 00:11:28.880 It's going to go in my team's group chat pretty much as soon as we're done recording. 00:11:28.880 --> 00:11:30.660 In fact, yeah, it's awesome. 00:11:30.660 --> 00:11:32.240 I think it's really good. 00:11:32.240 --> 00:11:35.800 You know, there's so many people who are presented a notebook or presented some kind 00:11:35.800 --> 00:11:39.800 of result and they're like, I need to understand what that means so I can keep following. 00:11:39.800 --> 00:11:42.720 And I think, you know, throw it into here or something like this would be really helpful. 00:11:42.720 --> 00:11:47.020 Well, and a lot of people that have spent a lot of time with databases might, it might 00:11:47.020 --> 00:11:48.960 be obvious what these things do. 00:11:48.960 --> 00:11:54.420 But for people that don't spend a lot of time with SQL, it's not obvious. 00:11:54.420 --> 00:11:56.860 And so this is really nice. 00:11:56.860 --> 00:11:57.960 Yeah, definitely. 00:11:57.960 --> 00:12:02.080 Or if you're like trying to take some example that you have with their example data 00:12:02.080 --> 00:12:07.440 and trying to translate it to your own data, that's something that customers do all the 00:12:07.440 --> 00:12:07.960 time for us. 00:12:07.960 --> 00:12:09.320 It's something I do a lot too. 00:12:09.820 --> 00:12:12.500 Just seeing how it behaves with your stuff. 00:12:12.500 --> 00:12:13.340 Oh, man. 00:12:13.340 --> 00:12:15.300 You didn't write it, but you want to use it. 00:12:15.300 --> 00:12:16.340 So how much applies. 00:12:16.340 --> 00:12:16.580 Yeah. 00:12:16.580 --> 00:12:16.900 Exactly. 00:12:16.900 --> 00:12:17.300 Yeah. 00:12:17.300 --> 00:12:17.780 Yeah. 00:12:17.780 --> 00:12:19.180 So this is quite cool. 00:12:19.180 --> 00:12:21.220 Dean out in the live stream. 00:12:21.220 --> 00:12:21.860 Hey, Dean. 00:12:21.860 --> 00:12:25.080 Says Pandas Tutor looks awesome. 00:12:25.080 --> 00:12:27.820 And Robert Robertson also loving it. 00:12:27.820 --> 00:12:28.240 It's nice. 00:12:28.240 --> 00:12:29.240 So very cool. 00:12:29.240 --> 00:12:29.880 Indeed. 00:12:29.880 --> 00:12:30.260 All right. 00:12:30.260 --> 00:12:31.420 Over to you, Leah. 00:12:31.420 --> 00:12:32.040 All right. 00:12:32.220 --> 00:12:34.980 So yeah, my first thing today is Apache Airflow. 00:12:34.980 --> 00:12:39.240 So Airflow is a project that is part of the Apache Software Foundation. 00:12:39.240 --> 00:12:45.520 It's a workflow orchestration tool that originated at Airbnb, I want to say in like 2014. 00:12:45.520 --> 00:12:50.500 And then pretty shortly after became part of the ASF. 00:12:50.500 --> 00:12:55.860 And it became a top level Apache project in, I want to say early 2019. 00:12:55.860 --> 00:12:58.460 It's been a little while now, which is very exciting. 00:12:58.460 --> 00:13:05.060 So you can use it to author these workflows as directed acyclic graphs or DAGs of tasks, 00:13:05.060 --> 00:13:06.680 which is pretty cool. 00:13:06.680 --> 00:13:12.300 And it's most commonly used with workflows that are like pretty static, not super frequently 00:13:12.300 --> 00:13:18.440 changing or slowly changing just so that you can see how the workflow goes over time and 00:13:18.440 --> 00:13:22.160 not allows you for some clarity and continuity in your workflows. 00:13:22.160 --> 00:13:28.980 I've always sort of wondered what the role of these workflow type systems were until I realized, 00:13:28.980 --> 00:13:32.340 you know, if you're going to build a full end to end type of workflow without a framework, 00:13:32.340 --> 00:13:34.100 there's a lot of coordination. 00:13:34.100 --> 00:13:35.080 And what if this fails? 00:13:35.080 --> 00:13:36.160 Where do you restart? 00:13:36.160 --> 00:13:36.740 What do you do? 00:13:36.740 --> 00:13:41.940 And then the analogy for me is kind of like Flask or some web, like all I got to do is 00:13:41.940 --> 00:13:45.600 write this little thing and everything else will come together to make sure these four 00:13:45.600 --> 00:13:47.180 lines of my Python code run. 00:13:47.180 --> 00:13:48.000 They run reliably. 00:13:48.000 --> 00:13:49.600 If they fail, it gets dealt with. 00:13:49.600 --> 00:13:50.140 Right. 00:13:50.140 --> 00:13:54.200 It allows people to not have to understand the whole system and just go, I need you to load 00:13:54.200 --> 00:13:56.200 up this file and put it into that database. 00:13:56.200 --> 00:13:57.360 Can you write that code? 00:13:57.360 --> 00:14:00.120 And that's all you got to know to be part of some complex thing. 00:14:00.120 --> 00:14:00.300 Right. 00:14:00.300 --> 00:14:00.660 Yeah. 00:14:00.660 --> 00:14:00.660 Yeah. 00:14:00.660 --> 00:14:06.260 It's I mean, it's not the most glamorous thing, but it is extremely useful. 00:14:06.260 --> 00:14:13.060 I mean, I did a summer internship when I was doing my bachelor's where I wrote a cron job 00:14:13.060 --> 00:14:15.060 that ingested some data every night. 00:14:15.060 --> 00:14:19.620 And the only way I knew if it failed was if I looked in the target folder where it was 00:14:19.620 --> 00:14:20.320 supposed to end up. 00:14:20.320 --> 00:14:22.320 And if the data wasn't there. 00:14:22.320 --> 00:14:23.880 No files. 00:14:23.880 --> 00:14:24.160 Whoops. 00:14:24.160 --> 00:14:25.140 That sucked. 00:14:25.280 --> 00:14:27.380 I'm sure a lot of people have dealt with that. 00:14:27.380 --> 00:14:33.200 And this is actually like a really common Airflow workflow, which is the extract, transform 00:14:33.200 --> 00:14:38.000 and load the ETL workflow, which is where you have data somewhere that you want to get. 00:14:38.000 --> 00:14:40.560 You want to do something to it or maybe not. 00:14:40.560 --> 00:14:42.000 Maybe you just want to extract and load it. 00:14:42.000 --> 00:14:48.020 And you want to put that result somewhere else, either locally or in the cloud for all of that. 00:14:48.020 --> 00:14:50.260 And Airflow lets you do all of that. 00:14:50.260 --> 00:14:52.800 And you can see the history of these jobs. 00:14:53.180 --> 00:14:55.840 There's a UI where you can see, did it fail? 00:14:55.840 --> 00:14:57.520 It has a helpful error message. 00:14:57.520 --> 00:15:00.580 If it failed, it's not just, oh, gosh, the data is not there. 00:15:00.580 --> 00:15:01.260 What do I do? 00:15:01.260 --> 00:15:01.580 Yeah. 00:15:01.580 --> 00:15:06.060 You've got a really cool UI where it shows all the parts of the workflow running and whether 00:15:06.060 --> 00:15:07.940 or not they finished successfully and stuff, right? 00:15:07.940 --> 00:15:08.380 Yeah. 00:15:08.380 --> 00:15:10.700 And it got a makeover fairly recently. 00:15:10.700 --> 00:15:12.460 So it's had a lot of improvements. 00:15:12.460 --> 00:15:14.360 Yeah, that's super cool. 00:15:14.360 --> 00:15:17.980 Another thing maybe you could talk about really quick is the connectors. 00:15:17.980 --> 00:15:20.000 I don't remember exactly the right terminology. 00:15:20.000 --> 00:15:21.740 There's a name for them. 00:15:22.180 --> 00:15:23.220 Tell us, tell people about that. 00:15:23.220 --> 00:15:24.180 That's also good to know. 00:15:24.180 --> 00:15:28.360 So these connectors that you're thinking of, I mean, we can use the word connector to describe 00:15:28.360 --> 00:15:28.880 what it does. 00:15:28.880 --> 00:15:31.600 There are these things called operators in Airflow. 00:15:31.600 --> 00:15:34.640 And an operator executes a single task. 00:15:34.640 --> 00:15:39.420 And so that might be executing a bash script or executing a Python script. 00:15:39.420 --> 00:15:45.140 But we also have these connectors that are grouped by providers, which might be your cloud provider 00:15:45.140 --> 00:15:49.900 or other software providers that allow you to execute code there. 00:15:49.900 --> 00:15:53.420 So for example, we have a ton of GCP operators. 00:15:53.420 --> 00:16:00.540 One example might allow you to create a data prop cluster or then run a job on that data prop 00:16:00.540 --> 00:16:02.900 cluster and maybe tear it down when you're done. 00:16:02.900 --> 00:16:10.020 And there are providers that have operators for all the major clouds and more. 00:16:10.020 --> 00:16:10.700 You can do it. 00:16:10.700 --> 00:16:13.060 There's one that sends a Slack message when it's done. 00:16:13.060 --> 00:16:16.920 So if you can dream it, it might be there. 00:16:16.920 --> 00:16:18.880 And if not, you can make it there. 00:16:18.880 --> 00:16:19.780 That's awesome. 00:16:19.780 --> 00:16:21.100 What's GCP? 00:16:21.620 --> 00:16:24.560 GCP is Google Cloud Platform or Google Cloud. 00:16:24.560 --> 00:16:26.420 GCP might be a dated acronym. 00:16:26.420 --> 00:16:27.020 Sorry. 00:16:27.020 --> 00:16:28.700 Don't know. 00:16:28.700 --> 00:16:29.380 Yeah. 00:16:29.380 --> 00:16:30.620 Yeah. 00:16:30.620 --> 00:16:33.940 So one of the advantages, I think, of that that's really cool is you don't necessarily 00:16:33.940 --> 00:16:35.320 have to know all those APIs. 00:16:35.320 --> 00:16:41.180 Like if I was going to connect Slack to GCP to like Azure Blob Storage to like some hosted 00:16:41.180 --> 00:16:43.340 database, I don't have to learn all those things. 00:16:43.340 --> 00:16:44.640 I can just sort of click it together. 00:16:44.640 --> 00:16:45.080 Yeah. 00:16:45.080 --> 00:16:46.160 You just have to. 00:16:46.160 --> 00:16:50.360 There's a small amount of setup you have to do for auth, which is understandable. 00:16:50.600 --> 00:16:54.200 You can't just like publicly go to your Azure Blob thing to grab your data. 00:16:54.200 --> 00:16:59.420 But once you set up that connection, then your operators can talk to those things. 00:16:59.420 --> 00:17:02.900 And if you use so you can run or host Airflow yourself. 00:17:02.900 --> 00:17:05.720 And there are a few different ways to do that. 00:17:05.720 --> 00:17:10.840 And then Amazon and Google both have managed hosted providers. 00:17:10.840 --> 00:17:14.740 And there's a company, Astronomer, that also does manage hosted ones. 00:17:14.740 --> 00:17:19.920 And so if you're in an Amazon or a Google, the advantage there is that the connections 00:17:19.920 --> 00:17:24.400 with those operators might be a little bit simpler from the auth and networking perspective. 00:17:24.400 --> 00:17:29.700 But other than that, you're you can still like if you're running in Cloud Composer, which 00:17:29.700 --> 00:17:34.740 is Google's Airflow, you can still be using the Amazon or the Microsoft operators to pull 00:17:34.740 --> 00:17:35.820 data from over there. 00:17:35.820 --> 00:17:37.200 That's really common. 00:17:37.960 --> 00:17:42.140 And you see it all the time and bring it do some stuff in Google Cloud and either put 00:17:42.140 --> 00:17:44.640 it back in the other cloud or leave it in Google Cloud. 00:17:44.640 --> 00:17:46.060 That's totally normal. 00:17:46.060 --> 00:17:47.520 And people are doing that all the time. 00:17:47.520 --> 00:17:48.160 Right on. 00:17:48.160 --> 00:17:48.520 Yeah. 00:17:48.520 --> 00:17:49.140 Cool. 00:17:49.140 --> 00:17:49.360 Cool. 00:17:49.360 --> 00:17:50.800 I think this is neat. 00:17:50.800 --> 00:17:53.340 And people for whom that would make sense. 00:17:53.340 --> 00:17:57.020 You're like trying to do these sort of running in the background schedule jobs. 00:17:57.020 --> 00:17:58.100 Or there's triggers as well. 00:17:58.100 --> 00:18:00.380 Like a file has been uploaded or landed here. 00:18:00.380 --> 00:18:00.740 Yeah. 00:18:01.120 --> 00:18:02.120 Let's talk about that. 00:18:02.120 --> 00:18:05.980 So that's actually I had written down this one example, but I'll adapt it slightly since 00:18:05.980 --> 00:18:07.040 you mentioned triggers. 00:18:07.040 --> 00:18:09.760 So that's another common type of operator. 00:18:09.760 --> 00:18:12.980 These sensors where you wait for a certain condition to be true. 00:18:12.980 --> 00:18:16.440 And they're used in data analytics workflows all the time. 00:18:16.440 --> 00:18:22.320 So like one example workflow might be waiting for a particular file to appear in a cloud 00:18:22.320 --> 00:18:23.940 storage or an S3 bucket. 00:18:23.940 --> 00:18:27.640 So you'd use one of those sensors to wait for that to happen. 00:18:27.640 --> 00:18:30.220 And then you want to do something to that data. 00:18:30.220 --> 00:18:38.260 So let's say you then create a data prop cluster that is going to run a PySpark job on that cluster. 00:18:38.260 --> 00:18:43.400 And then you can store the results in BigQuery at the end and then delete the cluster and like 00:18:43.400 --> 00:18:45.620 send a Slack message when the job is done. 00:18:46.040 --> 00:18:50.140 That's a very common ETL thing, including that sensor. 00:18:50.140 --> 00:18:51.940 Yeah, that sounds pretty nice. 00:18:51.940 --> 00:18:54.620 Definitely seems interesting and quite useful. 00:18:54.620 --> 00:18:54.920 Yeah. 00:18:54.920 --> 00:18:57.480 Brian, thoughts before we move on? 00:18:57.480 --> 00:18:58.880 I have a question. 00:18:58.880 --> 00:19:03.560 If you wanted to get started with something like this, I was trying to look for tutorials 00:19:03.560 --> 00:19:05.520 and getting started and stuff like that. 00:19:05.520 --> 00:19:10.240 Does it make sense or is it too confusing if somebody, you said you could run it on your 00:19:10.240 --> 00:19:10.720 own machine. 00:19:10.720 --> 00:19:15.600 Does that make sense to try it that way or should you try it with a? 00:19:15.640 --> 00:19:16.160 Okay. 00:19:16.960 --> 00:19:19.480 You totally can do it on your own machine. 00:19:19.480 --> 00:19:25.400 And there's this really wonderful environment that can be found in the Airflow repository that's 00:19:25.400 --> 00:19:26.420 called Breeze. 00:19:26.540 --> 00:19:29.300 And it's a Dockerized version of it. 00:19:29.300 --> 00:19:30.800 It shouldn't be run in production. 00:19:30.800 --> 00:19:36.020 But if you're looking to try it out or if you're looking to contribute to Airflow, we highly 00:19:36.020 --> 00:19:38.600 recommend that everyone check out the Breeze environment. 00:19:38.600 --> 00:19:44.040 Right now, I have the community page pulled up where you can join the dev list in the Slack 00:19:44.040 --> 00:19:45.260 if you have questions. 00:19:45.260 --> 00:19:49.980 But if you were to go to the GitHub repo, you would see Breeze right on that first page. 00:19:50.420 --> 00:19:50.980 Okay, cool. 00:19:50.980 --> 00:19:51.440 Thanks. 00:19:51.440 --> 00:19:51.820 Yeah. 00:19:51.820 --> 00:19:52.440 Great question. 00:19:52.440 --> 00:19:53.040 Thank you. 00:19:53.040 --> 00:19:53.480 Yeah. 00:19:53.480 --> 00:19:54.220 Very good one. 00:19:54.220 --> 00:19:54.960 All right, Brian. 00:19:54.960 --> 00:19:58.200 Are you going to give us a tutorial on Airflow or what we got going next? 00:19:58.200 --> 00:19:58.420 Yeah. 00:19:58.420 --> 00:20:03.680 So I was looking through the tutorials on Airflow and I noticed that right away one of the examples 00:20:03.680 --> 00:20:04.760 used D-Dent. 00:20:05.940 --> 00:20:08.280 How about that for a connection? 00:20:08.280 --> 00:20:09.300 Nice connection. 00:20:09.300 --> 00:20:10.500 Totally well planned. 00:20:10.500 --> 00:20:11.200 Very cool. 00:20:11.200 --> 00:20:14.480 D-Dent was suggested. 00:20:14.480 --> 00:20:15.840 It's a text wrap tool. 00:20:15.840 --> 00:20:18.140 It's suggested by Michael Rogers-Villet. 00:20:18.140 --> 00:20:21.960 It's a small utility, but it's super useful. 00:20:21.960 --> 00:20:26.040 And I kind of forget that it's, I mean, I use it all the time, but I forget to mention it 00:20:26.040 --> 00:20:26.460 to people. 00:20:26.460 --> 00:20:29.280 But it comes up a lot. 00:20:29.280 --> 00:20:33.780 And the idea around D-Dent is you've got something. 00:20:33.780 --> 00:20:36.780 Oh, I think I lost my D-Dent thing. 00:20:36.780 --> 00:20:39.360 See if I can find it. 00:20:39.360 --> 00:20:39.760 There it is. 00:20:39.760 --> 00:20:42.480 The idea is you've got a multi-line string. 00:20:42.480 --> 00:20:46.340 Like here we've got Hello World and some multiple lines and there's different spacing. 00:20:46.340 --> 00:20:52.280 But I'm, as you notice, I want to define it within a test, within a test function or within 00:20:52.280 --> 00:20:53.380 some other function. 00:20:53.380 --> 00:20:57.760 And that's, so there's this extra like space at the beginning. 00:20:58.140 --> 00:20:59.840 That's, that's in the string. 00:20:59.840 --> 00:21:01.320 It's in the multi-line string. 00:21:01.320 --> 00:21:02.340 And we don't want that. 00:21:02.340 --> 00:21:09.100 We don't, we want it to be just, just no, like nothing at the beginning or the same amount 00:21:09.100 --> 00:21:09.720 chopped off. 00:21:09.720 --> 00:21:14.880 So one of the options that people have used before is to just define a very multi-line string 00:21:14.880 --> 00:21:15.880 out of the function. 00:21:15.880 --> 00:21:17.280 You just do it out of the function. 00:21:17.280 --> 00:21:22.780 Then it's against, then it's just against the left side of your editor or whatever on column 00:21:22.780 --> 00:21:23.140 zero. 00:21:23.140 --> 00:21:27.420 And you don't have to worry about it, but it does bother some people that you've got this, 00:21:27.420 --> 00:21:31.580 this variable defined outside of your function when you're just using it within one function. 00:21:31.580 --> 00:21:33.520 So ddent is the answer. 00:21:33.520 --> 00:21:38.540 So what ddent does is it just takes a multi-line string and strips off all the common white space 00:21:38.540 --> 00:21:39.060 at the beginning. 00:21:39.060 --> 00:21:39.820 That's it. 00:21:39.820 --> 00:21:42.560 But it's a, it's super useful. 00:21:42.560 --> 00:21:48.980 They've got a little example that we're showing here, but I think this is a, not a great example. 00:21:48.980 --> 00:21:50.300 So I wrote a new example. 00:21:50.300 --> 00:21:51.580 Oops, fell asleep. 00:21:52.280 --> 00:21:57.620 and so that the idea really is I've got a function that either, you know, print stuff 00:21:57.620 --> 00:22:02.500 or has some output and I want to be able to compare that string and I want my comparison 00:22:02.500 --> 00:22:03.560 to be in the function. 00:22:04.020 --> 00:22:09.880 so, so I use ddent to just write it right in my function and then I don't have 00:22:09.880 --> 00:22:10.360 the spaces. 00:22:10.360 --> 00:22:15.760 And then, yeah, anyway, so this is a, a high test example of how you could test a output 00:22:15.760 --> 00:22:16.480 string. 00:22:16.640 --> 00:22:21.560 So anyway, this really sounds like a classic example of there's a problem, like the open 00:22:21.560 --> 00:22:23.300 source, this really bothered me. 00:22:23.300 --> 00:22:26.040 And so I wrote something to fix it and it's, it's wonderful. 00:22:26.040 --> 00:22:30.040 Like the time honored open source reason to make something. 00:22:30.040 --> 00:22:35.020 But, I also want to remind people that ddent is not the only thing in text wrap and text 00:22:35.020 --> 00:22:36.640 wrap has a whole bunch of other cool tools. 00:22:36.640 --> 00:22:38.900 So it's, it's not huge. 00:22:38.900 --> 00:22:43.240 It's just, but a five minute read to peruse what's in text wrap so that next time you need 00:22:43.240 --> 00:22:45.540 to manipulate some text, it's useful. 00:22:45.920 --> 00:22:46.380 Nice. 00:22:46.380 --> 00:22:46.580 Yeah. 00:22:46.580 --> 00:22:47.260 Maybe wrapping. 00:22:47.260 --> 00:22:48.380 Yeah. 00:22:48.380 --> 00:22:49.020 Like wrapping. 00:22:49.020 --> 00:22:53.060 Well, it does things like, like if you've got a huge string and you want to be able to 00:22:53.060 --> 00:22:55.520 like, one of the things is to, shorten it. 00:22:55.520 --> 00:22:59.400 So if you, if you've got a huge string, but you really only have like eight characters to 00:22:59.400 --> 00:23:01.320 show something like ellipsize it. 00:23:01.320 --> 00:23:01.720 Yeah. 00:23:01.720 --> 00:23:03.020 It does that for you. 00:23:03.020 --> 00:23:04.260 So that's nice. 00:23:04.260 --> 00:23:05.020 That's there too. 00:23:05.020 --> 00:23:05.800 That's good. 00:23:05.800 --> 00:23:06.640 Cause I've written that code. 00:23:06.640 --> 00:23:07.220 It wasn't fun. 00:23:07.220 --> 00:23:09.180 It didn't feel useful either. 00:23:09.180 --> 00:23:09.820 I'm like, okay, great. 00:23:09.820 --> 00:23:10.140 It works. 00:23:10.140 --> 00:23:11.120 But here we go. 00:23:11.120 --> 00:23:14.220 some audience feedback, Anthony out there. 00:23:14.220 --> 00:23:15.840 Hey, Anthony says it's really useful. 00:23:15.840 --> 00:23:17.940 I've still used it many times. 00:23:17.940 --> 00:23:18.360 Nice. 00:23:18.360 --> 00:23:18.620 Cool. 00:23:18.620 --> 00:23:19.440 Mm hmm. 00:23:19.440 --> 00:23:20.340 All right. 00:23:20.340 --> 00:23:23.000 This next one comes to us from Dan Bader. 00:23:23.000 --> 00:23:25.800 You might know him from a real Python and other things. 00:23:25.800 --> 00:23:30.660 He and I were chatting and he said, Hey, have you heard about pip audit from trailer bits? 00:23:30.760 --> 00:23:35.720 And I was sure that I had, and I thought we had talked about it, but then I realized, no, 00:23:35.720 --> 00:23:36.400 I don't believe we have. 00:23:36.400 --> 00:23:38.680 So I must've just heard about it somewhere else. 00:23:38.680 --> 00:23:39.840 And then we haven't covered it before. 00:23:39.840 --> 00:23:46.820 So the idea is we've heard about a lot of issues with supply chain vulnerabilities, things 00:23:46.820 --> 00:23:50.360 getting into pip, but also Ruby gems and npm and so on. 00:23:50.760 --> 00:23:55.280 Sometimes that's somebody trying to be evil and putting in some typo squatting thing, or, 00:23:55.280 --> 00:24:01.480 you know, worse than that would be if the GitHub account of a maintainer got hacked and somebody 00:24:01.480 --> 00:24:05.460 published a package with like to the real package. 00:24:05.460 --> 00:24:05.680 Right. 00:24:05.780 --> 00:24:10.900 So however things might get into your dependencies, if something is going on bad there, it's better 00:24:10.900 --> 00:24:12.060 to know than to not know. 00:24:12.060 --> 00:24:14.120 So this pip audit is all about that. 00:24:14.120 --> 00:24:19.000 It audits Python environments as in virtual environments and dependency trees for known 00:24:19.000 --> 00:24:19.520 vulnerabilities. 00:24:19.520 --> 00:24:25.720 So that's one of the things that's interesting is when you pip install things, you might be 00:24:25.720 --> 00:24:30.280 very good about saying, Oh, I pip installed flask and I pip installed pandas. 00:24:30.280 --> 00:24:33.560 So those are going into my requirements file or my pyproject.toml. 00:24:33.680 --> 00:24:39.040 But did you remember to pin their versions so that things like GitHub will say your version 00:24:39.040 --> 00:24:39.520 is wrong? 00:24:39.520 --> 00:24:43.240 Because if it just sees flask and the recent version doesn't have a problem, it's not going 00:24:43.240 --> 00:24:43.640 to tell you. 00:24:43.640 --> 00:24:48.560 But the one you have installed may also the transitive closure of the dependencies. 00:24:48.560 --> 00:24:52.900 So flask depends on it's dangerous, which depends on, I don't know. 00:24:52.900 --> 00:24:57.240 But if there's something down that chain that has a problem, you may have not put that in 00:24:57.240 --> 00:24:59.780 your requirements file and you may not be tracking it. 00:24:59.780 --> 00:25:02.360 Like I might be paying careful attention to flask. 00:25:02.360 --> 00:25:06.000 I might not care anything about it's dangerous, but that's where the problem is, right? 00:25:06.000 --> 00:25:06.500 Yeah. 00:25:06.500 --> 00:25:11.340 So this tool from Trail of Bits, which is a security company, basically solves that problem. 00:25:11.340 --> 00:25:14.920 And it lets you just type pip-audit. 00:25:14.920 --> 00:25:19.220 And for me, it's a -r requirements.txt or whatever. 00:25:19.520 --> 00:25:24.340 And from what I can tell, what it does is it will go create its own virtual environment 00:25:24.340 --> 00:25:31.040 where it one by one installs each package, looks at the things that come out of that process 00:25:31.040 --> 00:25:32.460 and then scans those. 00:25:32.460 --> 00:25:35.740 So it's not just looking at, oh, you say you have flask and that's 201. 00:25:35.740 --> 00:25:36.700 Great. 00:25:36.700 --> 00:25:38.180 You're good to go. 00:25:38.480 --> 00:25:43.100 It actually installs it because who knows what the setup.py process is doing and all 00:25:43.100 --> 00:25:43.800 those kinds of things. 00:25:43.800 --> 00:25:46.360 And then it scans that and it gives you a report. 00:25:46.360 --> 00:25:51.940 So for like Talk Python training the site, we have, I don't know, 30 dependencies or something. 00:25:51.940 --> 00:25:56.020 And it sat there and it took, I don't know, it probably took two minutes to go through and 00:25:56.020 --> 00:25:57.440 it said, everything's good to go. 00:25:57.760 --> 00:26:01.120 So that was good to hear, but it's pretty neat, really easy to use. 00:26:01.120 --> 00:26:04.080 It's like an external tool, like black or something. 00:26:04.080 --> 00:26:06.400 So it's very, a good candidate for PIPX. 00:26:06.400 --> 00:26:09.560 And then it's just globally available to point at any environment. 00:26:09.560 --> 00:26:10.340 What do you all think? 00:26:10.340 --> 00:26:11.860 Oh, this is so cool. 00:26:11.860 --> 00:26:16.060 I heard about it because one of my colleagues, Dustin Ingram, I think has been involved with 00:26:16.060 --> 00:26:19.760 it or either it's his Twitter that I found out about it from, but he also has a really 00:26:19.760 --> 00:26:24.340 good talk from PyCon this past year about the supply chain vulnerabilities. 00:26:25.120 --> 00:26:30.320 That's worth checking out if you're wanting to get an idea of why this is important. 00:26:30.320 --> 00:26:31.380 Yeah. 00:26:31.380 --> 00:26:31.960 Yeah. 00:26:31.960 --> 00:26:37.340 We've highlighted a few examples over the years, but it's definitely something you want to pay 00:26:37.340 --> 00:26:37.840 attention to. 00:26:37.840 --> 00:26:39.500 And that's cool that Dustin was talking about it. 00:26:39.500 --> 00:26:46.760 He works, I think he's still working with the PyPA and works on, you know, the PyPI.org 00:26:46.760 --> 00:26:47.600 and all those kinds of things. 00:26:47.600 --> 00:26:48.660 So very cool warehouse. 00:26:48.660 --> 00:26:50.140 Brian, what do you think? 00:26:50.140 --> 00:26:51.400 I think this is cool. 00:26:51.400 --> 00:26:52.520 I'm going to start using it right away. 00:26:52.520 --> 00:26:53.260 This is nice. 00:26:53.260 --> 00:26:53.620 Yeah. 00:26:53.620 --> 00:26:56.500 I already used it once as well and everything seems good. 00:26:56.500 --> 00:26:58.440 So here, look, I even called a flask as an example. 00:26:58.440 --> 00:27:05.800 Say here on this particular version, there was this security vulnerability from 2019 and 00:27:05.800 --> 00:27:07.720 same with, I guess, Jinja and all those were good. 00:27:07.720 --> 00:27:10.600 But yeah, it just, it gives you a nice description of what went wrong. 00:27:10.600 --> 00:27:14.960 And like in this case, it's a denial of service attack and whatnot. 00:27:15.200 --> 00:27:20.180 So I definitely recommend people pin versions definitely in your requirements. 00:27:20.180 --> 00:27:23.960 But what do you all think of including hashes? 00:27:23.960 --> 00:27:26.820 I think that's something Dustin talked about in his talk. 00:27:26.820 --> 00:27:29.720 And at the time I was like, oh, that sounds like a good idea. 00:27:29.720 --> 00:27:32.260 And it's not something I've started doing yet. 00:27:32.260 --> 00:27:33.600 Yeah, exactly. 00:27:33.600 --> 00:27:34.900 That's exactly what I think. 00:27:34.900 --> 00:27:37.160 It sounds like a good idea and I'm not doing it yet. 00:27:37.160 --> 00:27:38.340 So anyway. 00:27:38.380 --> 00:27:42.420 But that sounds like it's a me problem more than anything else. 00:27:42.420 --> 00:27:44.720 Also, it seems like a good idea. 00:27:44.720 --> 00:27:47.580 You know, I might be missing a step. 00:27:47.580 --> 00:27:53.120 It feels like the challenge you're going to run into there, what you're preventing against 00:27:53.120 --> 00:27:54.740 is a man in the middle attack. 00:27:54.740 --> 00:28:01.680 Somebody can intercept what's happening with PyPI.org and sneak in some kind of broken, 00:28:01.680 --> 00:28:03.000 hacked version. 00:28:03.560 --> 00:28:03.960 I don't know. 00:28:03.960 --> 00:28:08.740 I don't necessarily trust what goes into PyPI.org, but I trust PyPI.org. 00:28:08.740 --> 00:28:12.400 So I'm not super, it's not my biggest worry. 00:28:12.400 --> 00:28:16.780 There's like 10 other worries that make me have a hard time sleeping at night about running 00:28:16.780 --> 00:28:18.880 stuff on the internet that precedes that. 00:28:18.880 --> 00:28:20.740 So I haven't worried about it, but maybe I should. 00:28:20.740 --> 00:28:23.880 It's in the queue of things to worry about. 00:28:23.880 --> 00:28:31.720 Well, for instance, with this audit, you can pin your stuff and then have it be, check it 00:28:31.720 --> 00:28:34.820 every once in a while and install everything and check things. 00:28:34.820 --> 00:28:37.120 I don't see why it couldn't be a CI step. 00:28:37.120 --> 00:28:42.160 I was actually just going to say that PipAudit, I need to bring it to my samples maintaining 00:28:42.160 --> 00:28:46.300 group to talk about who wants to implement it and how soon we're going to do it. 00:28:46.300 --> 00:28:48.980 And whose pager rings when it finds a problem. 00:28:48.980 --> 00:28:49.360 Yes. 00:28:49.360 --> 00:28:50.800 Yeah. 00:28:50.800 --> 00:28:51.120 Nice. 00:28:51.120 --> 00:28:52.540 Look at that, pagers from back in the day. 00:28:52.540 --> 00:28:52.820 All right. 00:28:52.820 --> 00:28:54.960 Well, that's all I got for that one. 00:28:54.960 --> 00:28:57.760 We're off to Leah. 00:28:57.760 --> 00:29:01.660 I'm so glad you mentioned pitting requirements because that is actually, that's a great segue 00:29:01.660 --> 00:29:04.060 for managing samples for GCP. 00:29:04.060 --> 00:29:09.340 So what I have open right now for Google Cloud is an example documentation page. 00:29:09.340 --> 00:29:12.020 I picked Cloud Composer because it's what I work on. 00:29:12.020 --> 00:29:17.860 And I want to give an example of where this code lives that I'm talking about that I work 00:29:17.860 --> 00:29:18.940 with this group to maintain. 00:29:19.680 --> 00:29:24.100 So this is a page that's about using a particular Airflow operator. 00:29:24.100 --> 00:29:30.680 And if you were to scroll on it, you will see these code samples and they are all stored 00:29:30.680 --> 00:29:33.480 in GitHub and then embedded in our docs. 00:29:33.480 --> 00:29:38.700 So you can click view on GitHub on any one of them and it will take you to the linked repository. 00:29:38.700 --> 00:29:42.560 You can look at the history, look at everything in context. 00:29:42.560 --> 00:29:50.180 So we have thousands of samples for all of the Google Cloud products just for Python, but 00:29:50.180 --> 00:29:51.600 we have them in other languages too. 00:29:51.600 --> 00:29:54.780 And they're located across hundreds of repos. 00:29:54.780 --> 00:30:00.900 This happens to be one repo that has samples for multiple products, but we have other repos 00:30:00.900 --> 00:30:02.260 where things are stored too. 00:30:02.980 --> 00:30:09.480 So to ensure that there's consistency and that my group of engineers, my colleagues and I 00:30:09.480 --> 00:30:15.180 actually have time to do our work and function as humans outside of work too, we use a lot 00:30:15.180 --> 00:30:15.860 of automation. 00:30:15.860 --> 00:30:21.540 So we use a lot of bots to do things like keep our dependencies up to date, check for license 00:30:21.540 --> 00:30:27.960 headers, auto-assign PRs for reviewing, syncing repositories with centralized configurations, 00:30:27.960 --> 00:30:31.560 and even more, which is pretty great. 00:30:31.560 --> 00:30:34.440 And this is actually where the pinning requirements comes in. 00:30:34.440 --> 00:30:40.020 We very strongly believe in pinning requirements because it makes the samples easier to maintain 00:30:40.020 --> 00:30:41.220 and test against. 00:30:41.220 --> 00:30:46.760 And it's easier to go back to the product and say, hey, you just pushed a release candidate 00:30:46.760 --> 00:30:49.400 for your product and it broke your samples. 00:30:49.400 --> 00:30:51.300 It wasn't supposed to. 00:30:51.300 --> 00:30:52.220 What gives? 00:30:52.220 --> 00:30:56.980 Rather than finding out mysteriously when getting a customer issue. 00:30:57.680 --> 00:31:00.380 So then to keep it up to date, we use a bot. 00:31:00.380 --> 00:31:05.360 And these are some pull requests recently opened by the bot of some dependencies. 00:31:05.360 --> 00:31:09.540 They get double-checked to make sure everything looks good by human and merged. 00:31:09.540 --> 00:31:10.840 It's pretty great. 00:31:10.840 --> 00:31:18.040 And then we actually have a team of engineers in DevRel that works on making GitHub bots that 00:31:18.040 --> 00:31:18.480 we use. 00:31:18.480 --> 00:31:20.300 And that is totally open source. 00:31:20.300 --> 00:31:22.400 So you can see some of the ones that we use. 00:31:22.400 --> 00:31:24.520 Like we have our license header one. 00:31:24.520 --> 00:31:30.380 The sync repo settings allows us to have a single source of truth for our configuration for all 00:31:30.380 --> 00:31:31.740 of our Python repos. 00:31:31.900 --> 00:31:35.640 And then it makes sure it gets synced across all of them. 00:31:35.640 --> 00:31:36.780 It's pretty great. 00:31:36.780 --> 00:31:40.500 I really don't know how I would function without all of my bot friends. 00:31:40.500 --> 00:31:42.020 This is super cool. 00:31:42.020 --> 00:31:47.020 I can just imagine how much work it is to keep all of those different things in sync. 00:31:47.020 --> 00:31:52.920 And I have worked recently on projects where I'm like, okay, I got to integrate this library. 00:31:52.920 --> 00:31:53.840 I'm going to go to the documentation. 00:31:53.840 --> 00:31:58.640 And I try to use the one or two functions that the whole thing does. 00:31:58.640 --> 00:32:00.980 And it's like, nope, that parameter doesn't exist. 00:32:00.980 --> 00:32:02.080 Or you're missing some parameter. 00:32:02.080 --> 00:32:05.060 You're like, come on, at least just keep the signature, right? 00:32:05.060 --> 00:32:05.500 You know? 00:32:05.500 --> 00:32:09.300 And of course, it's something like star args, star star kwrs. 00:32:09.300 --> 00:32:11.720 It's not like, oh, I can just look in my ID and see, oh, yeah. 00:32:11.780 --> 00:32:15.100 It says it takes like, use security, use SSL, yes or no? 00:32:15.100 --> 00:32:18.280 Like, no, it's unknown without the documentation, basically. 00:32:18.280 --> 00:32:18.780 Yeah. 00:32:18.780 --> 00:32:19.700 This is awesome. 00:32:19.700 --> 00:32:20.720 Thank you. 00:32:20.720 --> 00:32:21.580 I think so, too. 00:32:21.580 --> 00:32:22.840 I'm very grateful to it. 00:32:22.840 --> 00:32:26.360 And yeah, for our dependency bot, we do use an external one. 00:32:26.360 --> 00:32:28.640 I think GitHub is the one that does Dependabot. 00:32:28.640 --> 00:32:31.720 We, in particular, use Whitesource Renovate bot. 00:32:31.720 --> 00:32:33.640 It's what we were using when I started. 00:32:33.640 --> 00:32:35.480 And that works very well, too. 00:32:35.480 --> 00:32:38.220 And they're very nice and responsive to issues. 00:32:38.220 --> 00:32:38.980 Oh, that's fantastic. 00:32:38.980 --> 00:32:39.780 Yeah. 00:32:39.780 --> 00:32:41.560 Dependabot was fairly new. 00:32:41.680 --> 00:32:43.840 And then it was bought quite recently by GitHub. 00:32:43.840 --> 00:32:47.320 So I can imagine you were all doing something before then, yeah? 00:32:47.320 --> 00:32:47.780 Probably. 00:32:47.780 --> 00:32:50.040 But I know I have friends who use that, too. 00:32:50.040 --> 00:32:50.620 And they're great. 00:32:50.620 --> 00:32:54.840 Using a dependency bot, I would say, if you need a starter bot for any of them, 00:32:54.840 --> 00:32:57.840 the dependency bot is a great place to start. 00:32:57.840 --> 00:32:59.040 Yeah, that's fantastic. 00:32:59.040 --> 00:33:04.860 I recently switched to pip-tools and PipCompile to generate my requirements with pinned versions and stuff. 00:33:04.860 --> 00:33:05.240 Nice. 00:33:05.240 --> 00:33:10.980 But before that, I was all about Dependabot telling me if something new was up out and seeking that. 00:33:11.580 --> 00:33:11.720 pip-tools rocks. 00:33:11.720 --> 00:33:12.300 Yeah. 00:33:12.300 --> 00:33:13.520 pip-tools rocks. 00:33:13.520 --> 00:33:14.500 I love pip-tools. 00:33:14.500 --> 00:33:15.600 Yeah, it definitely does. 00:33:15.600 --> 00:33:17.300 Brian, there's a lot of cool automation here. 00:33:17.300 --> 00:33:17.700 What do you think? 00:33:18.360 --> 00:33:20.240 I'm excited about looking through all these. 00:33:20.240 --> 00:33:28.360 I love looking at bots because the whole idea about a bot is like the Unix philosophy of do one thing and do it well. 00:33:28.360 --> 00:33:28.940 Yes. 00:33:28.940 --> 00:33:29.480 Yeah. 00:33:29.480 --> 00:33:30.320 I love that. 00:33:30.320 --> 00:33:32.560 Have something else do it and not you do it. 00:33:32.560 --> 00:33:32.940 Oh, yeah. 00:33:33.500 --> 00:33:41.680 All of our bots are based on like, oh, gosh, we're doing this one thing over and over and we're not doing it well because we're doing it manually. 00:33:42.040 --> 00:33:47.560 So how can we like use automation to make sure we're doing it consistently and to save a lot of time? 00:33:47.560 --> 00:33:51.580 Like one of the things you've got in here that's shown right now is label sync. 00:33:51.680 --> 00:33:59.500 So one of the nice things about one of the interesting things about different groups workflows is to have different labels that mean different things. 00:33:59.500 --> 00:34:03.060 But when you open a new repo, it doesn't have all those labels. 00:34:03.060 --> 00:34:06.500 So being able to sync those labels across an organization. 00:34:06.500 --> 00:34:12.240 Like needs triage, good first contribution, all those kind of things, right? 00:34:12.240 --> 00:34:12.640 Yeah. 00:34:12.640 --> 00:34:22.620 As I said, we have hundreds of repos just for Python and we use things like we have labels that say what API something belongs to. 00:34:22.620 --> 00:34:28.980 And that helps with the auto assign bot to make sure that issues and PRs get routed to the right team. 00:34:28.980 --> 00:34:35.760 Otherwise, you're having a human do all that triage, which is fine, but doesn't scale super well in our use case. 00:34:35.760 --> 00:34:36.420 Yeah. 00:34:36.420 --> 00:34:41.760 And adding a label is really easy to an issue or something. 00:34:41.760 --> 00:34:48.100 So having a bot that looks at label changes and just does an action based on that is a brilliant use of time. 00:34:48.100 --> 00:34:48.620 Yep. 00:34:48.620 --> 00:34:49.920 Highly recommend. 00:34:49.920 --> 00:34:50.540 Yeah. 00:34:50.540 --> 00:34:51.100 Fantastic. 00:34:51.100 --> 00:34:51.720 This is great. 00:34:52.040 --> 00:34:54.340 And you have an install link next to all of them. 00:34:54.340 --> 00:34:56.900 Does that mean I just click that and install it into one of my repos? 00:34:56.900 --> 00:34:58.740 I believe that is the intent. 00:34:58.740 --> 00:35:03.040 And if it doesn't work, you should open an issue on this repo because my colleagues are very responsive. 00:35:03.040 --> 00:35:04.400 Fantastic. 00:35:04.400 --> 00:35:04.860 Yeah. 00:35:04.860 --> 00:35:06.940 And we just need bots to generate bots. 00:35:06.940 --> 00:35:12.660 Honestly, if my colleagues told me they were working on that in this repo, I wouldn't be surprised, but I don't know. 00:35:12.660 --> 00:35:14.920 The meta bot. 00:35:14.920 --> 00:35:15.280 Yeah. 00:35:15.280 --> 00:35:16.240 Fantastic. 00:35:16.240 --> 00:35:17.080 All right. 00:35:17.080 --> 00:35:19.760 Well, how about some extras? 00:35:19.760 --> 00:35:21.600 Brian, you got anything extra you want to? 00:35:21.960 --> 00:35:23.740 Share while we're here before we call it a show? 00:35:23.740 --> 00:35:26.080 No, just I'm fighting a cold. 00:35:26.080 --> 00:35:27.520 Hopefully that'll all be over. 00:35:27.520 --> 00:35:28.020 Yeah. 00:35:28.020 --> 00:35:30.560 Well, maybe some sort of audit thing. 00:35:30.560 --> 00:35:31.920 We'll check your health status. 00:35:31.920 --> 00:35:32.880 We can run that against you. 00:35:32.880 --> 00:35:35.720 Leah, anything else you want to share with us? 00:35:35.920 --> 00:35:45.880 Oh, I mean, on Twitter earlier, we were talking about HTTP status codes and it reminded me of still my forever reference for HTTP status codes is HTTP.cat. 00:35:45.880 --> 00:35:48.360 Yes, HTTP.cat is fantastic. 00:35:48.360 --> 00:35:49.540 It's so good. 00:35:49.540 --> 00:35:50.720 It is so good. 00:35:50.720 --> 00:35:54.700 Let me share a few non-funny things and then we'll mix that in with our joke. 00:35:54.700 --> 00:35:55.400 Please do. 00:35:55.400 --> 00:35:56.400 Fantastic. 00:35:56.580 --> 00:35:56.820 All right. 00:35:56.820 --> 00:35:56.820 All right. 00:35:56.820 --> 00:36:02.380 The first one has to do with, speaking of GitHub, another cool GitHub thing. 00:36:02.380 --> 00:36:05.520 You know you could press a dot and that would do certain things. 00:36:05.520 --> 00:36:07.140 This only works if you're signed in. 00:36:07.140 --> 00:36:10.100 But now there's a command palette. 00:36:10.100 --> 00:36:12.860 This idea of command palettes are becoming popular in UIs. 00:36:12.860 --> 00:36:13.940 We've got it in VS Code. 00:36:14.300 --> 00:36:17.220 We've got it in like superhuman, the email. 00:36:17.220 --> 00:36:20.880 And often you get them by pressing command K or control K. 00:36:20.880 --> 00:36:22.380 And now you have that for GitHub. 00:36:22.380 --> 00:36:28.960 So if I were on a repo where I could do stuff to it, I could hit command K and then it will say, what do you want to do? 00:36:28.960 --> 00:36:30.320 Search or jump to. 00:36:30.320 --> 00:36:32.560 I could go to pages, issues. 00:36:32.560 --> 00:36:36.640 I could look for, let's see, look for the app. 00:36:36.640 --> 00:36:38.660 If I just type app, it'll search for those. 00:36:38.660 --> 00:36:40.940 I could search for all sorts of things here. 00:36:40.940 --> 00:36:42.940 And boom, it takes me and shows me all the apps. 00:36:42.940 --> 00:36:43.800 Isn't that cool? 00:36:43.800 --> 00:36:45.000 That's so cool. 00:36:45.000 --> 00:36:45.940 Command palette. 00:36:45.940 --> 00:36:47.520 Yeah, that's now a thing. 00:36:47.520 --> 00:36:48.600 That's beautiful. 00:36:48.600 --> 00:36:50.920 And you could just, I mean, no mouse. 00:36:50.920 --> 00:36:51.700 I'm here. 00:36:51.700 --> 00:36:53.140 I'm in this repo, the top level. 00:36:53.140 --> 00:36:55.600 Command K, down arrow, two times, hit enter. 00:36:55.600 --> 00:36:56.220 I'm on the issues. 00:36:56.220 --> 00:36:57.100 Oh my gosh. 00:36:57.100 --> 00:36:58.500 Love to see it. 00:36:58.500 --> 00:36:59.560 Yeah, so that's a good one. 00:36:59.560 --> 00:37:05.180 The other one, the other extra is Python 310.1 is out. 00:37:05.180 --> 00:37:06.600 Released December 6th. 00:37:06.600 --> 00:37:07.740 So as in two days ago. 00:37:07.740 --> 00:37:08.340 Wow. 00:37:08.340 --> 00:37:11.280 It's got a fun little snake with a hat on. 00:37:11.280 --> 00:37:12.000 Love it. 00:37:12.000 --> 00:37:13.040 That's really about 310. 00:37:13.300 --> 00:37:14.520 So let me describe. 00:37:14.520 --> 00:37:16.540 I can cover the entire release for you. 00:37:16.540 --> 00:37:20.580 So Python 310.1 is the newest major release of the Python programming languages. 00:37:20.580 --> 00:37:22.920 It contains many features and optimizations. 00:37:22.920 --> 00:37:24.660 So now you all know what's in it. 00:37:24.660 --> 00:37:26.760 It's very vague. 00:37:26.760 --> 00:37:27.500 It's very vague. 00:37:29.080 --> 00:37:32.140 Apparently it has 300 commits of changes and fixes. 00:37:32.140 --> 00:37:36.040 One thing I would, I wanted to know, are there security updates? 00:37:36.040 --> 00:37:36.860 Yes or no? 00:37:36.860 --> 00:37:37.860 Should I install this if I'm curious? 00:37:37.860 --> 00:37:42.560 Should I install this now before tomorrow? 00:37:42.560 --> 00:37:45.000 Because someone's going to start poking around. 00:37:45.000 --> 00:37:46.840 I would love if it would say that. 00:37:46.840 --> 00:37:51.140 There's a great thing about the major features, but that's just 310, not the point release. 00:37:51.620 --> 00:37:52.540 Well, we'll have to check it out. 00:37:52.540 --> 00:37:53.660 Anyway, still good. 00:37:53.660 --> 00:37:54.220 Yeah. 00:37:54.220 --> 00:38:00.740 We've been having fun making all of our GCP samples, making sure they're 310 compatible, which we're getting there. 00:38:01.180 --> 00:38:03.840 It's all waiting for certain dependencies to be ready. 00:38:03.840 --> 00:38:05.500 But a lot of fun. 00:38:05.500 --> 00:38:06.360 Very exciting to see. 00:38:06.360 --> 00:38:07.320 Yeah, that's awesome. 00:38:07.320 --> 00:38:09.040 Well, you can look at the changelog. 00:38:09.040 --> 00:38:12.440 So if you look at the 310, the changelog, you can see 310.1 and stuff. 00:38:12.440 --> 00:38:13.820 I can. 00:38:13.820 --> 00:38:15.160 Yeah, go up a little bit. 00:38:15.160 --> 00:38:16.360 Full changelog there, maybe? 00:38:16.360 --> 00:38:16.880 Yeah. 00:38:16.880 --> 00:38:18.000 Yeah, that's true. 00:38:18.000 --> 00:38:19.960 I can go to the changelog there and check that out. 00:38:19.960 --> 00:38:22.920 But having a security thing would be an idea. 00:38:22.920 --> 00:38:23.600 Yeah, just like. 00:38:23.600 --> 00:38:24.240 A TLDR. 00:38:24.240 --> 00:38:25.680 Yeah, exactly. 00:38:25.680 --> 00:38:26.140 Exactly. 00:38:26.140 --> 00:38:26.400 Cool. 00:38:26.400 --> 00:38:31.420 Well, and also a lot of people didn't want to try 310 until we got one patch release. 00:38:31.420 --> 00:38:32.760 So now we have one patch release. 00:38:32.760 --> 00:38:33.620 So there's no excuse. 00:38:33.620 --> 00:38:35.200 So now it's safe. 00:38:35.200 --> 00:38:38.260 I have been running it for a day in production and it seems okay. 00:38:38.260 --> 00:38:41.240 Put it on one site to see if it would hang in there. 00:38:41.240 --> 00:38:41.740 It seems fine. 00:38:41.740 --> 00:38:42.480 So we're all good. 00:38:42.480 --> 00:38:42.800 Yeah. 00:38:42.800 --> 00:38:43.440 All right. 00:38:43.440 --> 00:38:45.260 The samples that are using it are doing fine. 00:38:45.260 --> 00:38:47.080 They've had passing periodic builds for a while. 00:38:47.080 --> 00:38:48.020 Yeah, fantastic. 00:38:48.020 --> 00:38:48.760 All right. 00:38:48.760 --> 00:38:50.480 Are you ready for some cat jokes later? 00:38:50.480 --> 00:38:50.700 Sorry. 00:38:50.700 --> 00:38:51.780 Yes. 00:38:51.780 --> 00:38:55.400 I mean, we started our conversation off today talking about cats. 00:38:55.400 --> 00:38:56.000 It's true. 00:38:56.300 --> 00:38:57.780 Before we hit record. 00:38:57.780 --> 00:38:59.660 So I feel like we should round that out. 00:38:59.660 --> 00:39:00.020 Definitely. 00:39:00.020 --> 00:39:07.180 So first of all, htpstatuses.com is a fantastic place to go learn about the real meaning or 00:39:07.180 --> 00:39:09.660 the official meaning, let's say, of status code. 00:39:09.660 --> 00:39:11.740 So for example, there's 100 continue. 00:39:11.740 --> 00:39:14.420 And if you want details, you click on that and it actually pulls this all up. 00:39:14.420 --> 00:39:17.620 Even shows you like the enum in Python. 00:39:17.620 --> 00:39:18.620 Oh my gosh. 00:39:18.620 --> 00:39:19.440 I love that. 00:39:19.440 --> 00:39:20.220 Isn't that cool? 00:39:20.220 --> 00:39:20.600 Yeah. 00:39:20.600 --> 00:39:22.740 It gives you the meaning like 100 continue. 00:39:22.740 --> 00:39:25.940 The initial part of a request has been received and has not yet been. 00:39:26.200 --> 00:39:27.900 Yet been rejected by the server. 00:39:27.900 --> 00:39:31.420 The server intends to send a final response eventually. 00:39:31.420 --> 00:39:33.180 And so there's other ones like 200. 00:39:33.180 --> 00:39:33.760 Okay. 00:39:33.760 --> 00:39:34.920 201 created. 00:39:34.920 --> 00:39:35.680 Let's see. 00:39:35.680 --> 00:39:36.600 What else should I point out? 00:39:36.600 --> 00:39:39.180 304 cache, not modified. 00:39:39.180 --> 00:39:40.860 400 bad request. 00:39:40.860 --> 00:39:41.760 Bad request. 00:39:41.760 --> 00:39:43.000 404 not found. 00:39:43.000 --> 00:39:43.920 403 forbidden. 00:39:43.920 --> 00:39:46.960 500 internal server error. 00:39:46.960 --> 00:39:47.820 Yeah. 00:39:47.820 --> 00:39:48.260 418. 00:39:48.260 --> 00:39:49.020 I'm a teabot. 00:39:49.020 --> 00:39:49.360 Yeah. 00:39:49.820 --> 00:39:50.960 And 502 bad gateway. 00:39:50.960 --> 00:39:51.240 Okay. 00:39:51.240 --> 00:39:53.520 So let's do yours firstly. 00:39:53.520 --> 00:39:53.940 Please. 00:39:53.940 --> 00:39:54.780 I put it. 00:39:54.780 --> 00:39:58.540 I put out this joke and you said, this is good, but oh my goodness. 00:39:58.540 --> 00:39:59.300 But yeah. 00:39:59.800 --> 00:40:07.180 So when I was doing my computer science degree, a friend shared with me, HTTP.cat, when we 00:40:07.180 --> 00:40:09.140 were learning about HTTP status codes. 00:40:09.140 --> 00:40:16.080 And if you go there, you will find one cat per HTTP status code representing what is going 00:40:16.080 --> 00:40:16.440 on. 00:40:16.440 --> 00:40:19.120 And I'm not going to lie to you in my professional career. 00:40:19.120 --> 00:40:22.460 I still use it as a reference because it's my favorite one. 00:40:22.460 --> 00:40:29.260 And you can even, if you go to like HTTP.cat slash 200, it returns a JPEG of a cat that's 00:40:29.260 --> 00:40:29.780 like, okay. 00:40:29.780 --> 00:40:30.720 Yeah, exactly. 00:40:30.720 --> 00:40:32.660 And you can do that for all of the status codes. 00:40:32.660 --> 00:40:40.000 201, the cat has walked through some wet cement and that's 201 created for footprints. 00:40:40.000 --> 00:40:41.960 Let's see what else we got in here. 00:40:41.960 --> 00:40:42.840 Some good ones. 00:40:42.840 --> 00:40:44.720 404 not modify. 00:40:44.720 --> 00:40:46.020 304, sorry. 00:40:46.640 --> 00:40:49.300 The 404, the cat is hiding under some wrapping. 00:40:49.300 --> 00:40:50.260 Not found. 00:40:50.260 --> 00:40:50.800 Fantastic. 00:40:50.800 --> 00:40:51.200 Yeah. 00:40:51.200 --> 00:40:51.860 I love this. 00:40:51.860 --> 00:40:54.020 I had not heard about this and it's glorious. 00:40:54.020 --> 00:40:54.580 Thank you. 00:40:54.580 --> 00:40:55.380 Well, wait, what's it? 00:40:55.380 --> 00:40:56.520 Does there, is there a 418? 00:40:56.520 --> 00:40:57.420 There is. 00:40:57.420 --> 00:40:57.980 Of course there is. 00:40:57.980 --> 00:40:59.100 I'm a teapot. 00:40:59.100 --> 00:41:00.480 A kitten and a teapot. 00:41:00.480 --> 00:41:00.940 A kitten and a teapot. 00:41:00.940 --> 00:41:02.320 Literally inside of a teapot. 00:41:02.320 --> 00:41:02.900 All right. 00:41:02.900 --> 00:41:10.640 So I saw this joke by Breen, who is John Breen, and thought, that's really funny. 00:41:10.640 --> 00:41:15.520 What he did is he put his own personal take on what status code means. 00:41:15.680 --> 00:41:19.080 And I thought they were hilarious, but I thought, you know, let me take a shot at this as well. 00:41:19.080 --> 00:41:20.420 A little more Python focused. 00:41:20.420 --> 00:41:22.680 So I'll link to my tweet. 00:41:22.680 --> 00:41:27.160 I put this set of colloquial meanings of the HTV status codes. 00:41:27.160 --> 00:41:27.760 All right. 00:41:27.760 --> 00:41:28.560 You all ready for this? 00:41:28.560 --> 00:41:28.940 Yeah. 00:41:28.940 --> 00:41:29.540 Do it. 00:41:29.600 --> 00:41:31.840 So 200 is, what's up? 00:41:31.840 --> 00:41:32.500 All right. 00:41:32.500 --> 00:41:33.720 All good. 00:41:33.720 --> 00:41:35.160 201. 00:41:35.160 --> 00:41:36.080 Hello, creator. 00:41:36.080 --> 00:41:37.040 304. 00:41:37.040 --> 00:41:39.180 Not modified or cached. 00:41:39.180 --> 00:41:40.740 It's same old, same old. 00:41:40.740 --> 00:41:41.820 403. 00:41:41.820 --> 00:41:42.640 Permission denied. 00:41:42.640 --> 00:41:43.880 It's get off my lawn, kids. 00:41:43.880 --> 00:41:44.760 That was my favorite. 00:41:47.000 --> 00:41:49.140 404 is just, there's no message. 00:41:49.140 --> 00:41:49.960 It's just not there. 00:41:49.960 --> 00:41:52.500 It's just not that that's the message, but it's just blank. 00:41:52.500 --> 00:41:54.780 500 is we're bad at APIs. 00:41:54.780 --> 00:41:55.320 I love that. 00:41:55.320 --> 00:41:55.580 Server error. 00:41:55.580 --> 00:41:57.540 400 is you're bad at APIs. 00:41:57.540 --> 00:41:58.020 Yes. 00:41:58.020 --> 00:41:58.400 Yeah. 00:41:58.400 --> 00:42:05.060 The real cardinal sin of APIs is 200, but in the body, there's a JSON that says error 00:42:05.060 --> 00:42:05.780 and a reason. 00:42:05.780 --> 00:42:06.600 Oof. 00:42:06.600 --> 00:42:09.960 200, but with error text, we're really bad at APIs. 00:42:09.960 --> 00:42:10.320 Yeah. 00:42:10.320 --> 00:42:16.060 502, we're bad at deployment or DevOps because part of the infrastructure can't get to the 00:42:16.060 --> 00:42:16.480 other part. 00:42:16.480 --> 00:42:19.660 And Brian's favorite, 418, is it already April again? 00:42:19.660 --> 00:42:19.920 Yeah. 00:42:19.920 --> 00:42:26.440 Because the reason is that was actually put into the spec as an April Fool's joke and they 00:42:26.440 --> 00:42:26.940 left it. 00:42:26.940 --> 00:42:27.580 I'm a teapot. 00:42:27.580 --> 00:42:29.100 I love that they left it. 00:42:29.100 --> 00:42:30.040 I do too. 00:42:30.040 --> 00:42:31.140 I do too. 00:42:31.140 --> 00:42:33.640 It's like import this. 00:42:33.640 --> 00:42:36.820 Just stuff that's fun that should just always be there. 00:42:36.820 --> 00:42:37.240 Yeah. 00:42:37.240 --> 00:42:37.580 Yeah. 00:42:37.580 --> 00:42:38.620 What's the harm? 00:42:38.620 --> 00:42:39.480 What's the harm? 00:42:39.480 --> 00:42:40.240 Just leave it there. 00:42:40.240 --> 00:42:44.380 Anthony, the live stream has some feedback for you, Leah. 00:42:44.380 --> 00:42:46.520 These status codes using cats. 00:42:46.520 --> 00:42:47.320 Well, I never. 00:42:47.320 --> 00:42:50.720 I mean, where there's internet, there is cats, no? 00:42:50.720 --> 00:42:52.240 Oh, of course. 00:42:52.240 --> 00:42:55.420 Why we created the internet in the first place is for cats. 00:42:55.420 --> 00:42:56.220 Exactly. 00:42:56.760 --> 00:42:57.140 All right. 00:42:57.140 --> 00:42:59.060 Well, I think that's it for our show. 00:42:59.060 --> 00:43:01.040 Brian, thanks for being here as always. 00:43:01.040 --> 00:43:01.520 Thank you. 00:43:01.520 --> 00:43:02.060 Leah, thanks for joining us. 00:43:02.060 --> 00:43:02.720 Thank you for having me. 00:43:02.720 --> 00:43:03.680 Thanks for listening, everyone. 00:43:03.680 --> 00:43:04.300 Yeah. 00:43:04.300 --> 00:43:05.000 You bet. 00:43:05.000 --> 00:43:05.620 See you all later.