WEBVTT 00:00:00.001 --> 00:00:05.640 Hello and welcome to Python Bytes, where we deliver Python news and headlines directly to your earbuds. 00:00:05.640 --> 00:00:10.200 This is episode 260, recorded November 19th, 2021. 00:00:10.200 --> 00:00:11.560 I'm Michael Kennedy. 00:00:11.560 --> 00:00:12.920 And I'm Brian Okken. 00:00:12.920 --> 00:00:13.860 I'm Chris Petty. 00:00:13.860 --> 00:00:15.720 Chris, welcome to the podcast. 00:00:15.720 --> 00:00:20.700 You're a podcast veteran, but the first time here on Python Bytes. 00:00:20.700 --> 00:00:21.400 Happy to have you here. 00:00:21.400 --> 00:00:22.840 Thank you very much. 00:00:22.840 --> 00:00:23.780 It's a pleasure to be here. 00:00:23.780 --> 00:00:24.860 It's good to be back. 00:00:24.860 --> 00:00:29.040 We're going to jump into a bunch of the news, but before we do, you know, tell people a bit about yourself. 00:00:29.040 --> 00:00:29.840 Absolutely. 00:00:30.320 --> 00:00:35.740 I've been in the tech business for about 35 years now, something like that. 00:00:35.740 --> 00:00:42.460 And I've been a self-identifying Pythonista for about the last five or six years. 00:00:42.460 --> 00:00:44.880 I work for these days. 00:00:44.880 --> 00:00:49.040 I work for just recently changed jobs within Amazon. 00:00:49.040 --> 00:00:52.600 I used to work for the Web Services Elastic File System team. 00:00:52.600 --> 00:00:54.060 And I now work. 00:00:54.060 --> 00:00:59.240 I switched gears from, you know, living in the clouds to living in the Amazon Fulfillment 00:00:59.240 --> 00:00:59.640 centers. 00:00:59.640 --> 00:01:01.100 We're now a network. 00:01:01.100 --> 00:01:02.300 So does that mean you're doing what? 00:01:02.300 --> 00:01:04.480 Like programming in COBOL or are we using now? 00:01:04.480 --> 00:01:05.940 Yeah. 00:01:05.940 --> 00:01:07.860 Nothing but COBOL and Fortran. 00:01:07.860 --> 00:01:09.980 Just all the worst, all the most possible. 00:01:09.980 --> 00:01:10.720 You know, not at all. 00:01:10.720 --> 00:01:16.900 We do, my team, OpsTech IT, we do network automation for infrastructure. 00:01:17.400 --> 00:01:19.040 So it's a lot of fun, actually. 00:01:19.040 --> 00:01:24.840 It's really kind of neat going from building microservices and things like that, being infrastructure 00:01:24.840 --> 00:01:30.540 oriented at that level to like working with being responsible for automating things like, 00:01:30.540 --> 00:01:37.580 you know, network protocols, DNS, DHCP, fun stuff like that at scale in the fulfillment centers. 00:01:37.580 --> 00:01:38.720 It's a really cool gig. 00:01:38.720 --> 00:01:39.220 Yeah. 00:01:39.220 --> 00:01:40.360 That sounds really interesting. 00:01:40.360 --> 00:01:44.860 And you get an interface with physical things that go physical places, which is interesting. 00:01:44.860 --> 00:01:46.200 It really is. 00:01:46.200 --> 00:01:46.920 Thank you. 00:01:46.920 --> 00:01:48.140 I only ship beds. 00:01:48.140 --> 00:01:48.620 I don't know. 00:01:48.620 --> 00:01:51.300 Brian, you also, you also work on physical things. 00:01:51.300 --> 00:01:51.960 Yeah. 00:01:52.180 --> 00:01:54.800 I like working with actual, we make things. 00:01:54.800 --> 00:01:55.460 It's nice. 00:01:55.460 --> 00:01:56.260 Yeah, absolutely. 00:01:56.260 --> 00:01:57.760 It's a nice change of pace. 00:01:57.760 --> 00:01:58.400 Yeah. 00:01:58.400 --> 00:01:59.200 It's all I've known. 00:01:59.200 --> 00:02:03.240 Out in the audience, Ned Batchelder. 00:02:03.240 --> 00:02:03.640 Hey, Ned. 00:02:03.640 --> 00:02:04.280 Thanks for being here. 00:02:04.280 --> 00:02:06.040 Does Chris Boston represent? 00:02:06.040 --> 00:02:06.800 Hey, Ned. 00:02:06.800 --> 00:02:06.980 Yeah. 00:02:06.980 --> 00:02:08.960 Ned is amazing. 00:02:08.960 --> 00:02:14.080 He does so much work with Boston Python and I can't wait till we can get back to actually 00:02:14.080 --> 00:02:17.440 like being in a room together with other people again. 00:02:17.440 --> 00:02:19.480 I know. 00:02:19.480 --> 00:02:20.000 Absolutely. 00:02:20.700 --> 00:02:26.560 So, Brian, I used to feel like a cog in the machine, but now I work at a pretty small 00:02:26.560 --> 00:02:29.320 company where I make a lot of the choices, so I don't have to feel like that. 00:02:29.320 --> 00:02:34.320 But, you know, I think we're going to talk about something that I think is awesome because 00:02:34.320 --> 00:02:35.020 Ned is here. 00:02:35.020 --> 00:02:36.820 Yeah, it's kind of nice that Ned's here. 00:02:36.820 --> 00:02:38.300 We picked this just for you, Ned. 00:02:38.300 --> 00:02:43.640 But the, so Ned, one of the, Ned does a lot of stuff for Python. 00:02:43.640 --> 00:02:49.900 And one of the things that he's done is this cool tool called Cog, which I've been watching 00:02:49.900 --> 00:02:54.500 for a while, but I haven't had a really good reason to use. 00:02:54.500 --> 00:03:01.660 But what cog does is you point it, you can have these cog, like these, it's like three 00:03:01.660 --> 00:03:05.200 brackets and the cog word and then some code. 00:03:05.200 --> 00:03:08.480 And then, then another magic incantation at the end. 00:03:08.480 --> 00:03:11.100 It's pretty simple, but it's hard to explain. 00:03:11.240 --> 00:03:12.060 But you have some code. 00:03:12.060 --> 00:03:16.800 And when you point cog at it, it will run the code and then put the output of the code 00:03:16.800 --> 00:03:18.500 somewhere else where you put it to. 00:03:18.500 --> 00:03:20.060 So, seems neat. 00:03:20.060 --> 00:03:21.240 I wanted to use it. 00:03:21.240 --> 00:03:25.460 And, but I didn't know what a use case I would use it for. 00:03:25.460 --> 00:03:32.540 Well, Simon Willison wrote this article called Using Cog to Update Help, the help output for 00:03:32.540 --> 00:03:33.780 a markdown readme file. 00:03:33.940 --> 00:03:35.100 And I think this is brilliant. 00:03:35.100 --> 00:03:37.500 So, this is super awesome use case. 00:03:37.500 --> 00:03:47.100 So, Simon, he even has it going up on his CSVS to SQLite project. 00:03:47.580 --> 00:03:54.040 And the idea is you've got at the end, the end of the project, he actually lists on the 00:03:54.040 --> 00:03:56.220 readme, he lists the help output. 00:03:56.220 --> 00:04:01.340 Now, I actually have a project that the help output is out of date because the way I deal 00:04:01.340 --> 00:04:03.600 with it is I run the help and then copy and paste. 00:04:03.600 --> 00:04:09.600 But this is, Simon's right, this is a great use for cog to just point cog at it. 00:04:09.600 --> 00:04:14.820 So, so he wrote a little snippet of code that goes in his readme. 00:04:14.820 --> 00:04:21.500 And since cog ignores comments, you can put it in an HTML comment block. 00:04:21.500 --> 00:04:25.280 And it, so cog will run that file and took the output and stick it out. 00:04:25.280 --> 00:04:27.160 And then Simon didn't stop there. 00:04:27.160 --> 00:04:32.100 He said, I want to make sure that this gets run when it needs to get run. 00:04:32.100 --> 00:04:39.080 So, he wrote a test in pytest, of course, to check to see if cog needs to be written. 00:04:39.080 --> 00:04:41.200 So, this is just, this is really pretty cool. 00:04:41.200 --> 00:04:41.920 I like it. 00:04:41.920 --> 00:04:44.100 This is the kind of thing that's, it's so cool. 00:04:44.100 --> 00:04:45.520 Pardon me, Mike. 00:04:45.520 --> 00:04:51.540 This is the kind of thing that's so cool because anytime you can eliminate a DIY, right? 00:04:51.540 --> 00:04:57.840 Anytime you can make one thing, the one true source of whatever piece of the puzzle you're 00:04:57.840 --> 00:05:00.340 looking to, to, to, to build you with. 00:05:00.340 --> 00:05:01.940 And this is a great example of that. 00:05:01.940 --> 00:05:02.440 Yeah. 00:05:02.800 --> 00:05:05.540 Out in the audience, a little light, a real-time feedback. 00:05:05.540 --> 00:05:13.060 Ned says, I also just updated the coverage and cog docs to do the same thing and to get help output into the docs. 00:05:13.060 --> 00:05:13.760 Nice. 00:05:13.760 --> 00:05:14.420 Yeah. 00:05:14.420 --> 00:05:14.940 Very cool. 00:05:14.940 --> 00:05:17.260 I love the inception of it. 00:05:17.260 --> 00:05:17.680 Yeah. 00:05:17.680 --> 00:05:19.780 This is definitely a cool project. 00:05:20.060 --> 00:05:22.800 I want to take you all on a journey. 00:05:22.800 --> 00:05:26.880 Come with me into the world of bank Python. 00:05:26.880 --> 00:05:27.620 My drink. 00:05:27.620 --> 00:05:30.660 This, this is an interesting article here. 00:05:30.660 --> 00:05:37.900 It's one of these things that says, I can't exactly tell you precisely where I worked or what we did. 00:05:37.960 --> 00:05:41.440 And I have to make up names for the projects that are not the actual names. 00:05:41.440 --> 00:05:43.400 It's by Cal Patterson. 00:05:43.400 --> 00:05:48.420 And it says the strange world of Python as used by big investment banks. 00:05:48.420 --> 00:05:51.580 So this is quite the read. 00:05:51.580 --> 00:05:57.560 If you go through it, if you click the little reader bit here, it says, you know, 30 minutes of reading time to read it. 00:05:57.560 --> 00:06:06.040 So it's, it is a non-trivial bit of history, but let me see if I can give you some of, some of the highlights that I took from this. 00:06:06.060 --> 00:06:08.460 And you can go read it if you really feel like you want to dive into it. 00:06:08.460 --> 00:06:14.640 So one of the things they talk about is the database and all these things have interesting names. 00:06:14.640 --> 00:06:18.200 I'm sure that they have actual interesting names as well that are not these names. 00:06:18.200 --> 00:06:21.880 So for example, like the database like system is called Barbara. 00:06:21.880 --> 00:06:34.020 And I guess the place to start here with this oral history that Cal talks about is that bank Python implementations are basically forks of the entire Python ecosystem. 00:06:34.300 --> 00:06:42.480 Not just a fork of CPython, but like the libraries that it uses and everything, which are used at many, but not all of the biggest investment banks. 00:06:42.480 --> 00:06:46.380 So it says, let's talk about this system called Minerva. 00:06:46.380 --> 00:06:47.360 Minerva. 00:06:47.760 --> 00:06:51.620 And it's a global database of Python objects. 00:06:51.620 --> 00:06:54.180 And Barbara is this way to talk to it. 00:06:54.180 --> 00:06:54.560 Okay. 00:06:54.560 --> 00:06:57.040 So a lot of interesting keywords to keep it hidden. 00:06:57.040 --> 00:06:57.260 Right. 00:06:57.260 --> 00:07:07.280 But one of the things that's wild, this Barbara thing is it's like a hierarchical database that stores basically zipped pickle objects. 00:07:07.280 --> 00:07:08.600 Wait, wait, what? 00:07:09.160 --> 00:07:14.520 So it's in, when I say hierarchical, I mean, it's in what they call rings. 00:07:14.520 --> 00:07:22.140 So you would talk to a database and there might be like a nearby replica that you talk to that might have a record or it might not. 00:07:22.260 --> 00:07:27.440 And so then there's like a bigger replica, a sort of fallback to go look in this place. 00:07:27.440 --> 00:07:29.380 And if it's not there, go back and look at another one. 00:07:29.380 --> 00:07:30.600 They call these rings. 00:07:30.980 --> 00:07:35.000 And then you would ask for something by its key and then you get it back. 00:07:35.000 --> 00:07:39.940 So first of all, what do you guys think of just pickling all of your data objects? 00:07:39.940 --> 00:08:00.320 It's really, I, that, that bit made me chuckle because it is exactly this, the kind of like at the time, pragmatic engineering trade-off that somebody made right years ago before we all saw pickles as the great villain of the Python ecosystem. 00:08:00.320 --> 00:08:07.040 Before we knew that there could be downsides to pickling all the things and they're like, well, it's perfect. 00:08:07.040 --> 00:08:07.680 Pickle idea. 00:08:07.680 --> 00:08:08.560 What more could you want? 00:08:08.560 --> 00:08:10.000 And now we're all just kind of looking at it. 00:08:10.000 --> 00:08:10.600 It's so simple. 00:08:10.600 --> 00:08:11.380 It's small. 00:08:11.380 --> 00:08:12.160 It's fast. 00:08:12.160 --> 00:08:12.560 Yeah. 00:08:12.560 --> 00:08:13.660 Yeah. 00:08:13.660 --> 00:08:14.720 How do you index something? 00:08:14.720 --> 00:08:16.000 Actual database. 00:08:16.000 --> 00:08:17.220 Just curious. 00:08:17.220 --> 00:08:17.940 Yeah. 00:08:17.940 --> 00:08:19.020 This is a fine question. 00:08:19.020 --> 00:08:20.000 They do. 00:08:20.000 --> 00:08:23.720 If you read it, they do also use databases sometimes. 00:08:23.720 --> 00:08:24.460 Okay. 00:08:24.460 --> 00:08:28.620 So, but the primary way seems to be this, this system called Barbara. 00:08:28.900 --> 00:08:35.020 So one of the things that comes to mind for me here is, oh my gosh, what if you upgrade something? 00:08:35.020 --> 00:08:43.840 What if you change the file, the structure in code of something that you put in the database five years ago? 00:08:43.840 --> 00:08:44.920 Whoops. 00:08:44.920 --> 00:08:46.200 Yeah. 00:08:46.200 --> 00:08:46.980 Yeah. 00:08:46.980 --> 00:08:51.000 That used to be, you know, signed up for the mailing list. 00:08:51.000 --> 00:08:51.580 Yes or no. 00:08:51.580 --> 00:08:55.780 And now when you change the order that yes or no became yes or no is admin. 00:08:55.780 --> 00:08:56.780 Oh, oops. 00:08:56.780 --> 00:09:01.440 Or it just doesn't match anymore and it crashes and you can't read your data because it's incompatible. 00:09:01.440 --> 00:09:06.140 So this would happen with Python, the runtime, but also the libraries you're using, it seems to me. 00:09:06.140 --> 00:09:08.820 And it's just incredibly unstable. 00:09:09.660 --> 00:09:19.420 How much you want to make a bet they also have like some kind of really highly evolved over many years validation system that ensures that the, that's good. 00:09:19.420 --> 00:09:24.920 That the pickles that you think are being used in the way that you think they're being used are actually still used that way. 00:09:24.920 --> 00:09:25.460 Yeah. 00:09:25.460 --> 00:09:26.160 Yeah, exactly. 00:09:26.160 --> 00:09:27.700 There's got to be layers. 00:09:28.300 --> 00:09:32.500 Sam out in the live, in the audience live stream says, good luck upgrading a new Python. 00:09:32.500 --> 00:09:33.540 Yeah, exactly. 00:09:33.540 --> 00:09:34.480 Yeah. 00:09:34.480 --> 00:09:35.580 Like as in never. 00:09:35.580 --> 00:09:40.380 And that's probably why part of it is like, yeah, we just forked it and froze it because that's crazy. 00:09:40.380 --> 00:09:41.580 Let me show you something else. 00:09:41.580 --> 00:09:44.500 I will, try to jump around the article by a search. 00:09:44.500 --> 00:09:45.260 Cause I took notes. 00:09:45.260 --> 00:09:55.360 Applications also commonly store their internal state in Barbara, writing data classes straight into and out of Barbara with very simple locking and transactions. 00:09:55.700 --> 00:10:06.620 If not, and one of the things they decided is there's no file system available to these, to this platform and the little bits of data that the script picks gets picked up and outputs. 00:10:06.620 --> 00:10:11.680 It all just goes back into this key value store pickled database thing called Barbara. 00:10:11.680 --> 00:10:12.860 That's pretty wild, right? 00:10:12.860 --> 00:10:13.520 Yeah. 00:10:13.520 --> 00:10:14.240 Okay. 00:10:14.240 --> 00:10:21.260 they also talk about having these overlay features, which, is pretty wild. 00:10:21.260 --> 00:10:24.700 This has to do with the different rings that I talked about. 00:10:24.780 --> 00:10:30.680 So when you connect, you can say, I want to connect to the middle office ring and then the FICC ring and then the default ring. 00:10:30.680 --> 00:10:37.140 So then when you do a database query, which by the way, it looks like a dictionary index, just bracket key. 00:10:37.140 --> 00:10:40.800 It first is going to look for it in the middle office database. 00:10:40.800 --> 00:10:44.960 And then it's going to look in the FICC database and then the default database. 00:10:44.960 --> 00:10:48.960 So there's like these layers of settings and these layers of specificity. 00:10:49.680 --> 00:10:54.000 And they, they even do things that are to some effect of like monkey patching. 00:10:54.000 --> 00:11:00.240 Like if you, if you need to change it, you can have like your dev ring and then the middle office ring and then the outer ring. 00:11:00.240 --> 00:11:04.060 And you could change the value and kind of like for mocking or something. 00:11:04.060 --> 00:11:08.180 so yeah, to your point, Brian, they say there are some good reasons. 00:11:08.240 --> 00:11:10.080 There are some good reasons not to use Barbara. 00:11:10.080 --> 00:11:14.720 If your data, let me count the ways. 00:11:14.720 --> 00:11:24.520 If your data set is a large, it may be a good idea to look elsewhere, perhaps in a traditional SQL database or a KDB plus, which I have no idea what that is. 00:11:24.840 --> 00:11:33.260 there's a limit on the size of Barbara objects, which is compressed at when it's zipped 16 megs or, smaller, which is pretty interesting. 00:11:33.260 --> 00:11:42.280 And then paired with this is this direct, this thing called dagger, which is a directed acyclic graph that allows you to set up relationships between instruments. 00:11:42.280 --> 00:11:46.280 Like, okay, I've got a bond and then I've got a credit default swap on that bond. 00:11:46.280 --> 00:11:51.980 And then I've got like a fund of default swaps or, you know, like this whole layer of stuff. 00:11:51.980 --> 00:12:03.580 And all of these things are like linked objects through these pickled things that you can ask questions about and like, get sort of like graph database type things. 00:12:03.580 --> 00:12:05.000 That's pretty interesting. 00:12:05.000 --> 00:12:12.020 they talk a lot about how you model these things, like class, like instruments and swaps and stuff and Python. 00:12:12.020 --> 00:12:16.420 And that's not super interesting, but, I wanted to highlight this section and see what y'all thought. 00:12:16.420 --> 00:12:33.180 It says, if you understand, if you understand, Excel, you'll be starting to recognize how a lot of the stuff here works in Excel spreadsheets their cells and they have dependencies, which is like an acyclic graph, like this dagger hierarchy, graph database thing has. 00:12:33.180 --> 00:12:35.200 and it has a lot. 00:12:35.200 --> 00:12:38.940 So they basically modeled so much of the code around how Excel works. 00:12:38.940 --> 00:12:41.900 So you model the data first and then the behavior rather. 00:12:41.900 --> 00:12:45.720 Usually we write code and then we have data that comes out of it. 00:12:45.720 --> 00:12:48.100 So it's, it's pretty interesting. 00:12:48.100 --> 00:12:52.540 There's also this thing called a wall pole, which is a database runner. 00:12:52.540 --> 00:12:56.660 So when you get to this section, it says it's time to drop a bit of a bombshell. 00:12:56.660 --> 00:12:59.780 Let's talk about deployment, versioning, et cetera. 00:13:00.000 --> 00:13:06.460 The source code of the source code of this entire system itself, even including a Barbara is stored in Barbara, not on disk. 00:13:06.460 --> 00:13:07.460 And it remains composed. 00:13:07.460 --> 00:13:11.900 And it's kept in a special Barbara ring called source code. 00:13:11.900 --> 00:13:15.720 All right. 00:13:15.720 --> 00:13:16.700 What do you all think of that? 00:13:18.140 --> 00:13:20.740 My hidden release engineer has left the building. 00:13:20.740 --> 00:13:23.060 Oh man. 00:13:23.060 --> 00:13:23.660 That's frightening. 00:13:23.660 --> 00:13:24.220 Yeah. 00:13:24.220 --> 00:13:27.820 So, not keeping the source code in the file system breaks some assumptions. 00:13:27.820 --> 00:13:29.600 Like how does the program run? 00:13:29.600 --> 00:13:30.100 Yeah. 00:13:30.160 --> 00:13:35.660 So this wall pole thing runs, it's built to basically run source code that originates from a database. 00:13:35.660 --> 00:13:37.980 And you, it's all one huge database. 00:13:37.980 --> 00:13:46.440 So like, if you think mono repo, it's like that because you import from database and it's just like, whatever you need is there. 00:13:46.520 --> 00:13:55.380 So versioning, it's like the anti microservice, basically the entire whole thing is literally there. 00:13:55.380 --> 00:13:59.220 And then the way that you deploy it, let's see there, they talked about vouch. 00:13:59.220 --> 00:14:07.740 So the way that you deploy to it is really interesting in that you, it reminds me of the, it works on my machine certification program. 00:14:07.740 --> 00:14:14.600 So the way you deploy to the system is you just commit it to the database and boom, it's deployed. 00:14:14.600 --> 00:14:15.620 It's running, right? 00:14:15.620 --> 00:14:17.660 Because there's only one place the code lives. 00:14:17.660 --> 00:14:18.340 It's in the database. 00:14:18.340 --> 00:14:21.040 So once you do a commit, that's a full on deployment. 00:14:21.040 --> 00:14:23.520 Now, how does it get into there? 00:14:23.520 --> 00:14:30.220 There's a vouch system where you can get somebody who can code review what you've done and say, yeah, I vouch for this. 00:14:30.220 --> 00:14:35.560 You can commit it unless you have a high reputation for not breaking the system. 00:14:35.560 --> 00:14:38.500 In which case you can directly commit to it without question. 00:14:41.640 --> 00:14:45.240 So I guess the culture of code review is not like a thing there. 00:14:45.240 --> 00:14:47.540 I, I guess. 00:14:47.540 --> 00:14:54.900 so another interesting knock on that comes from storing your code in a database is how do you edit it? 00:14:54.900 --> 00:14:55.060 Right? 00:14:55.060 --> 00:14:56.380 Like what editor to use? 00:14:56.380 --> 00:14:57.800 VI won't work on it. 00:14:57.800 --> 00:14:59.060 PyCharm won't work on it. 00:14:59.060 --> 00:15:02.200 VS Code won't work on it because those work on files. 00:15:02.420 --> 00:15:11.380 So, this Minerva system has its own IDE because most IDEs think you have files, not databases that contain the data. 00:15:11.380 --> 00:15:14.660 Does that make sense? 00:15:14.660 --> 00:15:15.360 It is. 00:15:15.360 --> 00:15:16.180 That makes sense. 00:15:16.180 --> 00:15:16.540 It really is. 00:15:16.540 --> 00:15:20.520 The guy, Cal says, what I can't understand is why does it contain its own web framework? 00:15:20.520 --> 00:15:26.420 Investment banks have a, a one way approach to open source software. 00:15:26.700 --> 00:15:29.560 Some of it can come in, but none of it can go out. 00:15:29.560 --> 00:15:38.540 Well, I, I've seen, I've seen projects that like, like, people building IDEs within a company. 00:15:38.540 --> 00:15:40.980 And I always shake my head. 00:15:40.980 --> 00:15:43.400 It's like, why you, this isn't your business. 00:15:43.400 --> 00:15:46.060 Why are you making an IDE within your company? 00:15:46.060 --> 00:15:47.240 There are a couple of things. 00:15:47.240 --> 00:15:49.380 There are a couple of things that strike me from this article. 00:15:49.540 --> 00:15:52.780 The first is as I read it, cause I really enjoyed it. 00:15:52.780 --> 00:15:54.120 Did you read the whole thing? 00:15:54.120 --> 00:15:56.620 I, most, it's long, right? 00:15:56.620 --> 00:15:57.000 It's the way through. 00:15:57.000 --> 00:15:57.340 It is. 00:15:57.340 --> 00:15:58.080 It's crazy, right? 00:15:58.080 --> 00:15:59.080 It really is. 00:15:59.080 --> 00:15:59.800 It really is. 00:15:59.800 --> 00:16:10.040 The thing that struck me is this is a perfect example of large organization, complex, code base and engineering system. 00:16:10.040 --> 00:16:11.020 And tie. 00:16:11.020 --> 00:16:21.820 Cause this really just smells like something that just got like built up, like, you know, the layers of rings around a tree over time engineer after engineer year after year making decisions. 00:16:21.940 --> 00:16:35.740 And I'm sure like in the modern day, everyone who walks to the door, they probably have to plan for the period of time where the new engineer just freaks out when they tell them all this dumb as they adjust to the new reality that they're being exposed to. 00:16:35.740 --> 00:16:36.380 Yeah. 00:16:36.380 --> 00:16:44.580 And that is in some sense, this is a particular wacky case, but it's that way in kind of every large corporate environment in a, in a way. 00:16:44.580 --> 00:16:44.960 That's true. 00:16:44.960 --> 00:16:46.040 Yeah, that's totally true. 00:16:46.500 --> 00:16:55.140 He actually, Cal actually discusses this a little bit here and says, this fact that you can't do very much of open source, you're stuck on some version of Python. 00:16:55.140 --> 00:16:58.980 That's never going to see, never going to go back to sync with the real Python. 00:16:58.980 --> 00:17:02.240 Cause how do you even do a database migration to that thing? 00:17:02.240 --> 00:17:07.820 Says it could be the biggest disadvantage for you as your profession. 00:17:07.820 --> 00:17:14.780 Every year you spend in the Minerva monoculture, the skills you need to interact with normal software atrophy. 00:17:15.040 --> 00:17:21.680 By the time I left, I had pretty much forgotten how to wrestle pip in virtual EMV into shape essential skills for normal Python. 00:17:21.680 --> 00:17:27.620 When everything is in the same repo and all the code is just an import away, software packaging just does not come up. 00:17:27.620 --> 00:17:36.500 So yeah, there's a lot of, that's one way to deal with retention is to have a system where people, need to be skilled to use it. 00:17:36.500 --> 00:17:40.640 And, it removes all of their other skills so they can't get another job. 00:17:40.640 --> 00:17:47.520 Oh, I was just about to say, this seems like a retention at it pattern to me, but, you know, 00:17:47.520 --> 00:17:54.580 It depends on which side of, of that, leave stay story you're on. 00:17:54.580 --> 00:17:59.140 Because if your job is like, I want job security and I don't want to have to learn new things. 00:17:59.140 --> 00:18:02.780 Like welcome to Minerva, whatever this is, right? 00:18:02.780 --> 00:18:03.700 You're, you're home. 00:18:03.700 --> 00:18:05.380 You can stay here forever. 00:18:05.380 --> 00:18:06.760 They won't replace you. 00:18:06.960 --> 00:18:10.780 On the other hand, if you want to use like FastAPI, you're like, I got to get out of here. 00:18:10.780 --> 00:18:14.280 We can't be on, you know, Python two, three this long. 00:18:14.280 --> 00:18:14.940 I'm out. 00:18:14.940 --> 00:18:16.360 Off. 00:18:16.360 --> 00:18:23.720 So I did want to mention that both Minerva and Barbara are things that you can pip install, but those aren't things we're talking about. 00:18:23.720 --> 00:18:26.080 No, these are like secret code names. 00:18:26.080 --> 00:18:29.440 I suspect the Minerva you installed doesn't have its own ID. 00:18:29.440 --> 00:18:30.780 I'm just guessing. 00:18:30.780 --> 00:18:31.020 Right. 00:18:31.020 --> 00:18:31.500 Yeah. 00:18:31.500 --> 00:18:35.900 there's a lot of, a lot of interesting conversation here about this. 00:18:36.060 --> 00:18:38.080 just a quick little note. 00:18:38.080 --> 00:18:40.180 I actually ended up, I'm like, it was late last night. 00:18:40.180 --> 00:18:43.580 I'm like, I don't want to read this like 30 minute thing, but I do want to talk about it tomorrow. 00:18:43.580 --> 00:18:45.700 So I actually use this thing called natural reader. 00:18:45.700 --> 00:18:48.060 You can just throw this in here and it'll just like read it back. 00:18:48.060 --> 00:18:48.760 Super nice. 00:18:48.760 --> 00:18:49.700 That's so cool. 00:18:49.700 --> 00:18:53.820 So I was, it was like 1130 last night when I started on this. 00:18:53.820 --> 00:18:56.800 I'm like, Oh, I'm a little too tired to focus on this much stuff. 00:18:56.800 --> 00:18:58.760 But, yeah, it's pretty nice. 00:18:58.760 --> 00:19:02.240 You may have just made my day because I actually, you know, being part. 00:19:02.240 --> 00:19:02.460 Yeah. 00:19:02.460 --> 00:19:05.160 Because being partially blind, I feel like, you know, 00:19:05.160 --> 00:19:08.600 like, you know how some people who have like lupus and other kinds, they talk about spoons. 00:19:08.600 --> 00:19:10.240 Like they only have so much energy. 00:19:10.240 --> 00:19:14.040 My eyes only have so much like ice cream spoons. 00:19:14.040 --> 00:19:14.640 Yeah. 00:19:14.640 --> 00:19:17.760 In the course of any one day that I can, I can do it. 00:19:17.760 --> 00:19:21.980 There are times when I'm like, I cannot stare at a screen for even a moment longer. 00:19:21.980 --> 00:19:27.020 And I really love things like audio books or the rare services like pocket that will actually 00:19:27.020 --> 00:19:27.980 read you articles. 00:19:28.160 --> 00:19:32.800 And so this sounds like an awesome tool for those things that don't have that feature 00:19:32.800 --> 00:19:33.140 already. 00:19:33.140 --> 00:19:33.720 Nice. 00:19:33.720 --> 00:19:34.520 It's, it's really neat. 00:19:34.520 --> 00:19:36.940 It has different, different modes. 00:19:36.940 --> 00:19:40.000 I don't know how to make this thing come up without creating an account because I don't 00:19:40.000 --> 00:19:44.580 want to know what my login is here, but it has like, if, if you're dyslexic, it has like 00:19:44.580 --> 00:19:47.560 a dyslexic font you can turn on and it'll highlight as you write. 00:19:47.560 --> 00:19:48.900 It's, it's, it's pretty neat. 00:19:49.140 --> 00:19:50.960 That's so, yeah, cool. 00:19:50.960 --> 00:19:54.340 Not directly related, but I've found it to be useful in doing this research. 00:19:54.340 --> 00:19:55.640 I was too tired. 00:19:55.640 --> 00:19:58.260 A little bit of audience interaction here. 00:19:58.260 --> 00:20:02.220 Brandon says run, run the source code from a database. 00:20:02.220 --> 00:20:04.040 That's a one heck of an injection attack. 00:20:04.040 --> 00:20:04.280 Yeah. 00:20:04.280 --> 00:20:07.000 I mean, little Bobby tables would be just all over this thing, right? 00:20:07.000 --> 00:20:10.300 It's one big injection risk. 00:20:10.300 --> 00:20:15.660 Although on the other hand, I feel there might be some big safety here as well because everything 00:20:15.660 --> 00:20:16.260 is pickled. 00:20:16.640 --> 00:20:21.540 you've got to know what version of Python they forked it from and any variations. 00:20:21.540 --> 00:20:25.480 They may be changed to the object model to even get it, to parse it back. 00:20:25.480 --> 00:20:29.520 So it might be naturally safe as it's just like an opaque, it's almost like encryption. 00:20:29.520 --> 00:20:34.720 Really, really, really weak encryption. 00:20:34.720 --> 00:20:35.660 Yeah. 00:20:35.660 --> 00:20:37.180 And then let's see. 00:20:37.180 --> 00:20:37.760 Yeah. 00:20:37.760 --> 00:20:39.140 David says absolutely. 00:20:39.140 --> 00:20:42.220 Everyone in the live audience has a furrowed brow right now. 00:20:42.220 --> 00:20:46.520 yes, David, or, or some like. 00:20:46.520 --> 00:20:47.580 Nervous laughter. 00:20:47.580 --> 00:20:48.000 Yeah. 00:20:48.000 --> 00:20:50.940 There is one serious, serious aspect of this though. 00:20:50.940 --> 00:20:56.200 We're talking about like retention and, and the article talks about like, as he worked 00:20:56.200 --> 00:21:01.060 up in this, in this private ecosystem, he felt his external skills atrophying. 00:21:01.060 --> 00:21:04.200 That is a common problem that I have heard. 00:21:04.200 --> 00:21:10.680 So many people who work in these large kind of like pocket universes, whether it's an Amazon 00:21:10.680 --> 00:21:16.220 or a Google or a Microsoft or an IBM or whatever people, people, people can kind of feel very 00:21:16.220 --> 00:21:22.500 disconnected from where the field is currently going at the hot leading edge in the outside 00:21:22.500 --> 00:21:23.060 world. 00:21:23.060 --> 00:21:27.940 And, and I think it's a real issue because you can't always justify pulling in the latest, 00:21:27.940 --> 00:21:28.320 greatest. 00:21:28.320 --> 00:21:33.940 Sometimes there are engineering or earing implications to that, that would be really problematic to your 00:21:33.940 --> 00:21:35.520 businesses bottom line. 00:21:35.520 --> 00:21:42.680 And so I say, and I realized time is, is finite and it's, this is hard, but this is where I 00:21:42.680 --> 00:21:48.080 say even dabbling in having side projects, even if it's just the kind of thing you do on weekend, 00:21:48.080 --> 00:21:53.440 every once in a while, when you have time, it's a great way to sort of like feel unconstrained 00:21:53.440 --> 00:21:59.400 by the requirements of your business and to go sort of play on your own terms. 00:21:59.400 --> 00:22:04.020 I mean, write helper scripts for yourself, even for your job in, in modern Python. 00:22:04.020 --> 00:22:04.640 Bingo. 00:22:04.640 --> 00:22:05.820 Yeah, absolutely. 00:22:05.820 --> 00:22:07.120 Good, good advice. 00:22:07.120 --> 00:22:07.460 Indeed. 00:22:07.460 --> 00:22:08.080 All right. 00:22:08.080 --> 00:22:08.940 Over to you, Chris. 00:22:08.940 --> 00:22:09.660 Okay. 00:22:09.660 --> 00:22:10.120 Thank you. 00:22:10.120 --> 00:22:16.400 So I decided I was thinking about this and thinking about the fact that, you know, 00:22:16.400 --> 00:22:22.640 most of the people who come in and our guests here on this podcast are really sort of accomplished 00:22:22.640 --> 00:22:26.400 hardcore Python programmers and they're familiar with the latest and greatest tools. 00:22:26.400 --> 00:22:29.000 There is no way that I'm going to scoop you all. 00:22:29.000 --> 00:22:34.620 So I decided to go a completely different direction and go in the direction. 00:22:34.620 --> 00:22:35.700 That's right. 00:22:35.700 --> 00:22:36.200 Exactly. 00:22:36.200 --> 00:22:41.560 Of, of the whimsical side of computing, because I think we all need to stay in touch with that. 00:22:41.560 --> 00:22:46.880 I know I had a, an issue a number of months ago, before I changed jobs where I was feeling 00:22:46.880 --> 00:22:51.600 very burned out and I felt like I just, I need to sort of get back in touch with like, why am I 00:22:51.600 --> 00:22:55.180 passionate about, about computing and programming in this space? 00:22:55.180 --> 00:23:02.280 And one of the things that really was ball into my, you know, soothed by my burnt out soul was 00:23:02.280 --> 00:23:05.500 these retro consoles up. 00:23:05.500 --> 00:23:08.500 I used one called take 80, which was not Python based. 00:23:08.500 --> 00:23:09.660 It's it's Lua based. 00:23:09.900 --> 00:23:17.560 But the idea here is you can build like basically retro style video games very, very, very easily 00:23:17.560 --> 00:23:24.880 with very few lines of code because these things, they do have some constraints, but the constraints 00:23:24.880 --> 00:23:26.900 are completely artificial, right? 00:23:26.900 --> 00:23:31.400 Like in this case, this one is fixed 16 color palette, 256 by 256. 00:23:31.760 --> 00:23:39.840 you know, like the constraints, the world that you're building in is uncomplicated and small. 00:23:39.840 --> 00:23:48.020 And so as a result, you can sort of like step in and wrap your head around this thing so quickly and come up to speed. 00:23:48.020 --> 00:23:53.400 And suddenly you're like, you know, Oh, I made a flying saucer fly across the screen. 00:23:53.400 --> 00:23:55.700 I built a spray on making music. 00:23:55.700 --> 00:24:02.500 I'm coding, you know, the mean loop of my game and you can do it in a very comparatively speaking, 00:24:02.500 --> 00:24:05.820 short period of time with just a few lines of code. 00:24:05.820 --> 00:24:07.460 I'm just skipping down a little bit here. 00:24:07.460 --> 00:24:09.380 like let's take an example. 00:24:09.380 --> 00:24:14.660 They have the sort of like, you know, sneak eating dots kind of game. 00:24:14.660 --> 00:24:20.160 And it's comparatively speaking, like when you compare it with like one of the modern, 00:24:20.160 --> 00:24:24.540 you know, game, framework code bases. 00:24:24.820 --> 00:24:26.400 Like unreal engine or something. 00:24:26.400 --> 00:24:30.440 Unreal engine or do you think we were talking about like, here's my 60 pages of, 00:24:30.440 --> 00:24:31.740 of coordinate transforms. 00:24:31.740 --> 00:24:35.040 And you just look at it and you're like, I can't, I can't. 00:24:35.040 --> 00:24:38.700 And my a hundred gigs of, textures that we're going to export. 00:24:38.700 --> 00:24:39.120 Yeah. 00:24:39.120 --> 00:24:39.920 Exactly. 00:24:39.920 --> 00:24:40.080 Yeah. 00:24:40.080 --> 00:24:41.960 So this project is called pixel. 00:24:41.960 --> 00:24:44.720 I'm guessing that's how you P Y X E L. 00:24:44.720 --> 00:24:50.480 And it allows you to create extremely simple 2d animated games in Python, right? 00:24:50.480 --> 00:24:51.120 Yes. 00:24:51.120 --> 00:24:51.660 I apologize. 00:24:51.660 --> 00:24:52.600 I shouldn't have said that. 00:24:52.600 --> 00:24:53.600 yes, exactly. 00:24:53.940 --> 00:24:58.980 and so, back when I was using the other one, I kept thinking the entire time, 00:24:58.980 --> 00:24:59.560 like, wow. 00:24:59.560 --> 00:24:59.860 Wow. 00:24:59.860 --> 00:25:02.060 You know, I'm really having fun with this. 00:25:02.060 --> 00:25:06.900 And I'm really, I actually really enjoyed learning Lua and it's a really fun language. 00:25:06.900 --> 00:25:12.100 And it has a lot of, a lot of, you know, characteristics that are wonderful. 00:25:12.100 --> 00:25:13.780 But I kept thinking like, wow. 00:25:13.780 --> 00:25:18.240 I kind of wish I didn't have to get my brain to switch gears, which is not very good at 00:25:18.240 --> 00:25:18.820 doing always. 00:25:18.820 --> 00:25:20.820 I wish I could be coding this in Python. 00:25:20.820 --> 00:25:25.540 And so this framework gives you the opportunity to do just that. 00:25:25.540 --> 00:25:27.300 and so you can use these. 00:25:27.300 --> 00:25:32.320 It almost feels like for those of us who are old enough to remember, it almost feels like 00:25:32.320 --> 00:25:36.700 coding in basic on the microcomputers that some of us grew up with in the eighties. 00:25:36.700 --> 00:25:36.980 Right. 00:25:36.980 --> 00:25:41.180 Like it's that sort of kind of like back, back when you could type it in, you're like, 00:25:41.180 --> 00:25:43.620 I saw it printed and I typed it in and I ran it. 00:25:43.620 --> 00:25:44.860 Exactly. 00:25:44.860 --> 00:25:45.600 Exactly. 00:25:45.600 --> 00:25:46.160 Exactly. 00:25:46.160 --> 00:25:49.500 You know, it's like, yeah, it really, really is. 00:25:49.620 --> 00:25:53.800 And so I really, this one, what's, what's kind of interesting about this one is like, 00:25:53.800 --> 00:25:59.120 this is a great example that the sort of like sounding music section of this snake game here 00:25:59.120 --> 00:26:05.220 is, this one is actually a little bit more Pythonic, which I think is actually really 00:26:05.220 --> 00:26:10.260 kind of cool for Python folks like us, because the other ones that I've seen kind of like 00:26:10.260 --> 00:26:16.040 drifted more back towards the 1980s, like, you know, a little bit lower level of abstraction 00:26:16.040 --> 00:26:16.740 kind of thing. 00:26:16.740 --> 00:26:21.280 Whereas this one really takes advantage of some of the beautiful data structures like 00:26:21.280 --> 00:26:25.080 stats and dictionaries and the like that Python has to offer. 00:26:25.080 --> 00:26:31.080 So you can use this really kind of nice express and tax to, to write you games. 00:26:31.080 --> 00:26:33.120 And I am just super excited. 00:26:33.120 --> 00:26:35.080 I, I played with it a bit. 00:26:35.080 --> 00:26:39.860 I wrote a few lines of it and I, I, you know, kick the tires just to see how it worked, but 00:26:39.860 --> 00:26:45.420 I really have not had the opportunity yet to, to dive deep and kind of rewrite my side 00:26:45.420 --> 00:26:46.300 project in it. 00:26:46.300 --> 00:26:51.360 But I totally intend to, and I'm super psyched about it and I'm really, really glad that it 00:26:51.360 --> 00:26:51.760 exists. 00:26:51.760 --> 00:26:52.420 Yeah. 00:26:52.420 --> 00:26:53.200 I'd love to do this. 00:26:53.200 --> 00:26:59.200 I mean, I got my start typing in games from the back on a TRS 80 from the back of magazines 00:26:59.200 --> 00:27:01.800 and, and have an example. 00:27:01.800 --> 00:27:05.280 So one of the things, something like some engine like this, one of the things I love to do with 00:27:05.280 --> 00:27:09.960 somebody is, is take an existing game and say, let's look at the code and see what, 00:27:09.960 --> 00:27:12.260 what happens if we modify this, this field. 00:27:12.260 --> 00:27:15.020 There's, there's any way we can get the character to run faster. 00:27:15.020 --> 00:27:17.980 does that make it more fun to play the game or less fun? 00:27:17.980 --> 00:27:18.580 Things like that. 00:27:18.580 --> 00:27:19.320 Absolutely. 00:27:19.320 --> 00:27:23.140 And that's, and that kind of thing, that kind of like, well, let's take a look at this and 00:27:23.140 --> 00:27:27.920 tweak it a little bit is so simple with this kind of thing, because it's like, everything 00:27:27.920 --> 00:27:32.220 is so like, uncomplicated and straightforward. 00:27:32.220 --> 00:27:38.080 Like chances are like the, here is the number of frames that we skip as we transition our 00:27:38.080 --> 00:27:39.660 sprite character across the screen. 00:27:39.660 --> 00:27:40.960 Oh, let's just tweak that. 00:27:40.960 --> 00:27:45.040 Now you've done your sort of like, let's make him run a little faster kind of thing. 00:27:45.040 --> 00:27:50.900 It's all so satisfyingly in a world where I don't know about you guys, but my day job, 00:27:50.900 --> 00:27:54.940 especially the old one that I did was like, you know, make a code change or make a configuration 00:27:54.940 --> 00:27:55.600 change. 00:27:55.600 --> 00:27:58.920 And then wait, you know, eight hours for it to deploy through the pipeline. 00:27:58.920 --> 00:28:04.140 Like having something that's immediate instant feedback like this was just a delight. 00:28:04.140 --> 00:28:05.240 Sorry. 00:28:05.240 --> 00:28:08.120 I'm just shocked at the eight hour turnaround time. 00:28:08.120 --> 00:28:08.980 I'm so sorry. 00:28:08.980 --> 00:28:09.900 That was it. 00:28:09.900 --> 00:28:10.420 That was it. 00:28:10.420 --> 00:28:13.220 That was just a really bad example there that, you know, a couple of cases. 00:28:13.220 --> 00:28:15.080 It's not, that's not my day-to-day life. 00:28:15.080 --> 00:28:16.680 I actually love my day-to-day life. 00:28:16.680 --> 00:28:19.000 I'm very happy, but that was just, you know what I mean? 00:28:19.000 --> 00:28:20.720 We all have these like long build times. 00:28:20.880 --> 00:28:21.000 Yep. 00:28:21.000 --> 00:28:21.660 Yep. 00:28:21.660 --> 00:28:22.940 Will McGugan. 00:28:22.940 --> 00:28:23.240 Hey, Will. 00:28:23.240 --> 00:28:28.280 Says, this makes me nostalgic for my ZX Spectrum in the 80s. 00:28:28.280 --> 00:28:30.360 Exactly. 00:28:30.360 --> 00:28:35.040 There's an Atari 800 XL behind my head that I enjoy as well. 00:28:35.040 --> 00:28:36.540 So I feel that. 00:28:36.540 --> 00:28:40.060 Who's not surprised that Will's been coding since the 80s? 00:28:40.060 --> 00:28:41.380 So anyway. 00:28:41.380 --> 00:28:44.280 Now, now. 00:28:44.280 --> 00:28:48.460 And then also a few more follow-up items for your comment on side projects. 00:28:48.460 --> 00:28:50.700 Sam in the audience says, 100% agree, Chris. 00:28:50.800 --> 00:28:53.320 Side projects are a great way to keep yourself sharp. 00:28:53.320 --> 00:28:57.140 And Jose says, plus one for the side projects to try out the latest. 00:28:57.140 --> 00:28:57.480 Indeed. 00:28:57.480 --> 00:29:02.060 So before we move on though, Brian, I want to tell everyone about our sponsor. 00:29:02.060 --> 00:29:04.840 This episode is sponsored by Shortcut. 00:29:04.840 --> 00:29:09.200 Again, thank you Shortcut for sponsoring and supporting Python Bytes. 00:29:09.200 --> 00:29:14.240 So there's a lot of project management tools out there, but they often suffer from either 00:29:14.240 --> 00:29:18.200 being too simple for the engineering teams or too complex. 00:29:18.580 --> 00:29:21.900 And they end up looking like Bugzilla or something insane. 00:29:21.900 --> 00:29:23.380 And you're like, I really don't want to go here. 00:29:23.380 --> 00:29:27.000 So you want something nice and simple, but that actually scales with you. 00:29:27.000 --> 00:29:30.480 Something that's good both for managers and for engineers. 00:29:30.980 --> 00:29:32.600 So that's what Shortcut is. 00:29:32.600 --> 00:29:35.300 It's built to cater to both of these groups. 00:29:35.300 --> 00:29:39.140 So it's built for software teams based on making workflows easy. 00:29:39.140 --> 00:29:44.580 Big scale objectives, goals, roadmaps can be easily tied into a team or individual work 00:29:44.580 --> 00:29:45.120 sprints. 00:29:45.120 --> 00:29:48.460 Progress on those are easily flow back to higher level reports. 00:29:49.100 --> 00:29:52.800 And of course, as all things should be, it's keyboard friendly. 00:29:52.800 --> 00:29:56.340 You don't have to take your hand off and do a bunch of mousing around. 00:29:56.340 --> 00:30:00.940 You can use the UI if you like, but there's a bunch of hotkeys, which is fantastic, as I 00:30:00.940 --> 00:30:01.720 think they all should be. 00:30:01.720 --> 00:30:03.740 So it makes you work faster and just keep going. 00:30:03.740 --> 00:30:05.560 Good version control integration. 00:30:05.560 --> 00:30:08.820 Works with Git, GitHub, GitLab, and so on. 00:30:08.820 --> 00:30:10.560 A lot of the places that you probably already know. 00:30:10.940 --> 00:30:16.060 So you can update your task project just by doing a commit or a PR, which is fantastic. 00:30:16.060 --> 00:30:20.960 The last thing you want to do is update Git and GitHub and then go update your system, right? 00:30:20.960 --> 00:30:26.120 As iteration planning, you can see your team activity when you want to, or just focus on 00:30:26.120 --> 00:30:26.640 what you're doing. 00:30:26.640 --> 00:30:29.460 And you can even let it schedule your project for you. 00:30:29.460 --> 00:30:32.440 So nice burn down charge, cycle time, all that kind of stuff. 00:30:32.440 --> 00:30:37.060 So finally, you can have a project management tool that's both for engineers and managers. 00:30:37.060 --> 00:30:40.220 Give it a try at pythonbytes.fm/shortcut. 00:30:40.460 --> 00:30:42.720 It's a cool project and it helps support the show. 00:30:42.720 --> 00:30:44.360 So thank you for supporting us. 00:30:44.360 --> 00:30:46.300 Brian, what do you got next? 00:30:46.300 --> 00:30:47.260 What are we ditching now? 00:30:47.260 --> 00:30:49.940 We're ditching CodeCov. 00:30:49.940 --> 00:30:52.180 Harsh crowd. 00:30:52.180 --> 00:30:54.540 So, okay. 00:30:54.540 --> 00:30:58.460 So CodeCov has been great for a lot of people who have used it. 00:30:58.460 --> 00:31:05.060 It's a third-party service that you can attach to your repo or something. 00:31:05.060 --> 00:31:10.120 And it makes sure that you, and this has been helpful for merge requests and stuff. 00:31:10.220 --> 00:31:15.280 So if somebody does a PR, it makes sure that the coverage is 100. 00:31:15.280 --> 00:31:18.080 If you've had 100% coverage, it makes sure that they don't degrade it. 00:31:18.080 --> 00:31:21.360 The code they add makes the coverage stay at a high level. 00:31:22.480 --> 00:31:27.220 But so it's not without problems, however. 00:31:27.540 --> 00:31:38.800 And Hinnick mentions that on some of his projects, it's been sometimes a CI pipeline is blocked just because it timed out with CodeCov. 00:31:38.800 --> 00:31:43.580 And that's not a good reason to fail a build. 00:31:44.000 --> 00:31:50.880 So anyway, Hinnick has this project where he said, wait a second. 00:31:50.880 --> 00:31:53.740 I'm just trying to make sure everything goes to 100%. 00:31:53.740 --> 00:31:55.020 Coverage.py. 00:31:55.020 --> 00:31:56.220 Hey, Ned. 00:31:56.220 --> 00:31:58.240 Second thing here for you. 00:31:58.640 --> 00:32:07.560 But coverage.py from Ned Batchelder, maintaining it, of course, has a thing that it says fail if under 100%, under a percent. 00:32:07.560 --> 00:32:11.320 So you can do 100%, but you can do 80% or whatever your current percentage is. 00:32:11.820 --> 00:32:17.760 But anyway, if you want that, something like CodeCov, you can get that with coverage.py. 00:32:17.760 --> 00:32:19.380 But there's some tricks around it. 00:32:19.380 --> 00:32:28.400 So if you've got, one of the things coverage does is let's say you've got a project that has some code that is run, 00:32:28.400 --> 00:32:32.620 like you're trying to take advantage of some of the newer things, but you also, newer Python things, 00:32:32.620 --> 00:32:34.300 but you want to run on older Python too. 00:32:34.300 --> 00:32:37.020 So there's some if statements for Python version, for example. 00:32:37.020 --> 00:32:41.480 But it might be different hardware as well, like Windows versus Mac. 00:32:41.480 --> 00:32:45.420 But there might be code that's run in one test suite and not in the other. 00:32:45.420 --> 00:32:52.600 So in order to do that, you kind of have to run in parallel mode and then combine the coverage reports at the end. 00:32:52.600 --> 00:32:57.100 And it sounds complicated, but mostly we just copy somebody else's work. 00:32:57.100 --> 00:33:00.980 So, and Hinnick has the examples here. 00:33:00.980 --> 00:33:10.500 So Hinnick goes through using GitHub and coverage to do everything that you used to be able, you were doing with CodeCov. 00:33:10.500 --> 00:33:13.500 So this is a nice article with examples. 00:33:13.500 --> 00:33:24.000 So we've got, for each project, we're downloading the coverage report and then combining it at the end with a report with a fail under 100. 00:33:24.000 --> 00:33:25.060 Really cool. 00:33:25.060 --> 00:33:29.440 It's, if this is something you want to do, it's basically, it's a short article with examples. 00:33:29.440 --> 00:33:38.180 He even shows, he's got in his struct log, he shows his main workflow for GitHub pipelines that does all of this. 00:33:38.180 --> 00:33:41.560 So just kind of read his code and make it work. 00:33:41.560 --> 00:33:45.780 And I'm, I was actually thinking of doing this on a couple of projects I've got. 00:33:46.000 --> 00:33:50.220 I wanted to make sure that they were up at 100% and do something like this. 00:33:50.220 --> 00:33:55.820 But I actually, for some reason, I was dragging my feet and I didn't know why, but now I don't need to. 00:33:55.820 --> 00:33:58.500 I'll go ahead and use Hinnick's suggestion. 00:33:58.500 --> 00:33:59.520 Now you don't have to invent it. 00:33:59.520 --> 00:34:00.000 Just do it. 00:34:00.000 --> 00:34:02.560 Just set up that job on GitHub. 00:34:02.940 --> 00:34:06.060 This is actually something I've been, I've been kind of struggling with. 00:34:06.060 --> 00:34:07.020 I shouldn't say struggling with. 00:34:07.020 --> 00:34:18.520 I should say this is a journey that I have been on in that testing and code coverage and that whole class of, of proof of correctness is my weakest suit. 00:34:18.520 --> 00:34:33.300 And one of the things that I've really been sort of try to wrap my head around is I see a lot of like unit test code that seems like it was just, it's just there to keep the coverage percentage up. 00:34:33.300 --> 00:34:47.820 And as far as I can tell, it doesn't actually test anything like we're creating these mocks and like in everything and, but they don't actually like enforce any contracts or prove anything out. 00:34:47.820 --> 00:35:01.800 And I, I, I, I've trying to figure out how we can use these tools in ways that actually sort of raise the bar on code quality without encouraging this kind of like, I don't know, T crossing and I dotting behavior. 00:35:02.300 --> 00:35:15.760 Well, we're kind of getting on a tangent, but I would say that code reviews on tests are important because that's, that's just, I mean, one of the easiest ways to get a hundred percent coverage with no tip failing tests is don't put any asserts in your tests. 00:35:15.760 --> 00:35:20.600 Just saying. 00:35:20.600 --> 00:35:20.880 Good. 00:35:20.880 --> 00:35:21.500 That's it. 00:35:21.500 --> 00:35:23.980 And that makes an excellent point unto itself. 00:35:23.980 --> 00:35:24.380 Yes. 00:35:24.380 --> 00:35:24.740 Thank you. 00:35:24.740 --> 00:35:24.960 Yes. 00:35:24.960 --> 00:35:25.600 Nice. 00:35:25.600 --> 00:35:26.160 All right. 00:35:26.160 --> 00:35:29.920 Well, let's talk about the tippy top, the tip top. 00:35:30.060 --> 00:35:32.320 So I'm sure you all are familiar with top. 00:35:32.320 --> 00:35:39.360 It's like this somewhat dreadful way to tell what's happening on a Unix system, on Linux to see like what's happening. 00:35:39.360 --> 00:35:40.520 Is it, why is it busy? 00:35:40.520 --> 00:35:41.160 Is it not busy? 00:35:41.160 --> 00:35:43.920 I say dreadful because it's so simple and there's better tools. 00:35:43.920 --> 00:35:48.640 One of them being this tip top thing for, so for a long time, I use glances. 00:35:48.640 --> 00:35:49.680 I didn't know. 00:35:49.680 --> 00:35:50.560 I still do use glances. 00:35:50.560 --> 00:35:56.500 I'm not sure if you're all are familiar with the glances, but the UI that it creates is fantastic. 00:35:56.500 --> 00:36:03.080 So you just type glances and you get this sort of progress bars that show in the CPU, the memory, all the processes. 00:36:03.080 --> 00:36:04.480 It has like hotkeys. 00:36:04.480 --> 00:36:10.500 You can sort by CPU or memory, filter by process name or ID, all kinds of stuff going on here. 00:36:10.500 --> 00:36:12.240 And this, this is what I use now. 00:36:12.240 --> 00:36:16.760 But Zach Villers sent in tip top as a competing thing. 00:36:16.760 --> 00:36:19.200 And by the way, glances is Python and tip top is Python. 00:36:19.440 --> 00:36:23.460 So very good candidates for pip X because no project needs them. 00:36:23.460 --> 00:36:25.660 You just want to run them as commands, but they're Python, right? 00:36:25.660 --> 00:36:40.080 So if you look at the same picture over on the tip top page, you can see that you get similar information, but you get a little bit better historical understanding of how your CPU is doing, how your memory is doing. 00:36:40.420 --> 00:36:43.480 It even breaks it down per thread or per core. 00:36:43.480 --> 00:36:49.180 It shows you your memory broken down by what's being used, what's being cached, what's free. 00:36:49.180 --> 00:36:50.760 There's a graph of that over time. 00:36:50.760 --> 00:36:56.060 Something that made me sad is it shows the network over time as well, the in and out flow. 00:36:56.520 --> 00:37:08.920 But what happened to me is one of my servers, I ran this and it only would show the output from like a, some kind of, there were multiple network adapters and would only show the one that's not being used, not the one that's being used. 00:37:08.920 --> 00:37:11.400 So I'm like, well, that's, that part is useless, unfortunately here. 00:37:11.400 --> 00:37:19.960 But, and then it shows all the programs, like the CPU usage, the user it's running as the arguments that were passed to it, how much memory it has and stuff. 00:37:20.160 --> 00:37:28.460 So I don't think I'm going to give up using glances because I really love that, but this feels like a, another tool to get a view of that sort into it. 00:37:28.460 --> 00:37:28.980 What do y'all think? 00:37:28.980 --> 00:37:31.620 I like the visual design on the face of it. 00:37:31.620 --> 00:37:46.500 It, it like, especially comparing it to the glances screenshot that you showed, it feels like it might, it's a little prettier and it might, to me at least it looks a little bit less like dense and maybe a little bit easier to sort of like, maybe it's just the bounding boxes. 00:37:46.500 --> 00:37:54.620 But I also feel like it's the way the screen is laid out a way to visually, an easier way to visually parse the information that's presenting. 00:37:54.620 --> 00:37:57.700 That's always something I look for in the tool that I use. 00:37:57.700 --> 00:37:59.020 Absolutely. 00:37:59.020 --> 00:37:59.760 Brian? 00:37:59.760 --> 00:38:03.320 Why do you need some, I don't use anything like this. 00:38:03.320 --> 00:38:03.920 So. 00:38:03.920 --> 00:38:05.360 All right. 00:38:05.500 --> 00:38:17.840 So for example, if you log into, let's say you logged into a web server that was running a search job and it said, you're running a little bit low on memory as a, over the last few minutes. 00:38:17.840 --> 00:38:23.980 And you've got five different web apps set up running there, web processes with like a bunch of their sub processes running. 00:38:23.980 --> 00:38:25.460 And you wouldn't answer the question. 00:38:25.460 --> 00:38:26.020 Okay. 00:38:26.020 --> 00:38:26.660 Which one is it? 00:38:26.660 --> 00:38:27.880 Which one do I have to restart? 00:38:27.880 --> 00:38:28.660 Okay. 00:38:28.660 --> 00:38:29.200 Yeah. 00:38:29.520 --> 00:38:30.340 Things like that. 00:38:30.340 --> 00:38:38.280 It's easy to see where you might not encounter this or have a need for this when you're working in the world of things, right? 00:38:38.280 --> 00:38:44.540 Like the world of not servers, but embedded devices that might run Python or C or whatever. 00:38:44.540 --> 00:38:47.900 And, you know, this is like managing infrastructure. 00:38:47.900 --> 00:38:49.840 So you don't use this on your desktop? 00:38:50.200 --> 00:38:57.720 No, I don't use this on my Mac, but I use this on all of my, not necessarily tip top, but glances on all of my Linux servers, including the Python bytes one. 00:38:57.720 --> 00:39:02.380 So it's, it's nice to go in there and see what's going on in the servers with all I have is SSH. 00:39:02.380 --> 00:39:03.940 I'm more of a high level person. 00:39:03.940 --> 00:39:05.820 I'd rather pay somebody else to do this for me. 00:39:05.820 --> 00:39:11.420 Well, let's like, but it looks pretty. 00:39:11.420 --> 00:39:15.560 Let's see if I can pull up a picture of top. 00:39:15.560 --> 00:39:18.000 On behalf of my employer, Brian, thank you. 00:39:18.220 --> 00:39:18.600 Thank you. 00:39:18.600 --> 00:39:20.740 Yes, we're happy to take me to do that for you. 00:39:20.740 --> 00:39:21.140 No problem. 00:39:21.140 --> 00:39:30.920 Like this, this is the thing it's replacing, by the way, is it's just a list of processes and it moves around all the time and the stuff shoots off the screen. 00:39:30.920 --> 00:39:32.320 It's like, why is it doing this? 00:39:32.320 --> 00:39:33.760 You know, it's. 00:39:33.760 --> 00:39:37.960 I mean, to be fair, it was also written probably in like 1968 or something. 00:39:37.960 --> 00:39:38.680 Yeah, yeah, absolutely. 00:39:38.680 --> 00:39:39.100 Yeah. 00:39:39.100 --> 00:39:42.240 I'm not knocking on it. 00:39:42.240 --> 00:39:47.560 I'm just saying I would rather use, you know, something like this that gives me way more real time. 00:39:48.060 --> 00:39:50.220 Like graphs, not just snapshot. 00:39:50.220 --> 00:39:51.100 Now it is. 00:39:51.100 --> 00:39:51.840 Now it is. 00:39:51.840 --> 00:39:52.520 Now it is. 00:39:52.520 --> 00:39:56.820 But like, here's, here's what's happening as the things are running and doing their work. 00:39:56.820 --> 00:39:57.040 Right. 00:39:57.040 --> 00:39:58.860 So that, that's super helpful to me to see. 00:39:58.860 --> 00:40:00.160 To be fair. 00:40:00.160 --> 00:40:05.260 I also just, just installed Tiptop just for the heck of it on my Mac and a really quick install. 00:40:05.260 --> 00:40:06.720 And it does look pretty. 00:40:06.720 --> 00:40:07.940 I just don't know what to do with it. 00:40:07.940 --> 00:40:08.620 But yeah. 00:40:08.880 --> 00:40:11.300 And by the way, let's just tie it back to the audience again. 00:40:11.300 --> 00:40:18.920 So Tiptop uses textual for layout, which is based on, which is Wilma Googan's thing also based on rich. 00:40:18.920 --> 00:40:20.380 So it's quite modern. 00:40:20.840 --> 00:40:26.100 I think if we had Ned and Wil in the audience, we would always touch on something they were doing. 00:40:26.100 --> 00:40:26.760 Every year. 00:40:26.760 --> 00:40:30.740 I'll tell you what, Brian, here's a way you could use this totally in your day-to-day life. 00:40:30.740 --> 00:40:33.000 Your Mac is running slow, right? 00:40:33.000 --> 00:40:35.620 And you say, why is my Mac running slow? 00:40:35.940 --> 00:40:39.960 You could totally use this and at a glance say, what's hoovering all my RAM? 00:40:39.960 --> 00:40:41.980 What is throttling my disk? 00:40:41.980 --> 00:40:45.400 What is using up all my CP, et cetera, et cetera. 00:40:45.400 --> 00:40:45.900 Okay. 00:40:45.900 --> 00:40:46.260 Yeah. 00:40:46.260 --> 00:40:51.680 Like, for example, you can run activity monitor, which will show you the process thing. 00:40:51.680 --> 00:40:54.500 And you go to the memory thing, which will show you just a single graph. 00:40:54.500 --> 00:40:55.920 But like, why is it using all that memory? 00:40:55.920 --> 00:40:58.120 Is that actually being used or is that cache? 00:40:58.120 --> 00:41:01.460 Because you loaded a bunch of files and now it's kind of could be free, but it's not. 00:41:01.460 --> 00:41:02.820 What's happening on the network? 00:41:02.820 --> 00:41:04.820 You can't see very well on macOS. 00:41:05.100 --> 00:41:09.880 I don't know why activity monitor is adverse to showing you network traffic, but you could 00:41:09.880 --> 00:41:12.660 see like, am I downloading something or not right now? 00:41:12.660 --> 00:41:14.140 I can be taught new things. 00:41:14.140 --> 00:41:14.420 Okay. 00:41:14.420 --> 00:41:15.020 Thanks. 00:41:15.020 --> 00:41:15.780 Yeah. 00:41:15.780 --> 00:41:16.260 Yeah. 00:41:16.260 --> 00:41:16.420 Yeah. 00:41:16.420 --> 00:41:19.200 Anyway, I'm not excited for that use case. 00:41:19.200 --> 00:41:21.500 I'm excited for using it on the servers to understand them better. 00:41:21.500 --> 00:41:22.040 Yeah. 00:41:22.040 --> 00:41:22.580 Yeah. 00:41:22.580 --> 00:41:23.300 All right. 00:41:23.300 --> 00:41:27.000 Let's bring it home with some more retro, Chris. 00:41:27.000 --> 00:41:29.760 Back in the world of Wibzy. 00:41:31.300 --> 00:41:37.400 I've always been into, well, you know, always, ever since they weren't retro and they were, 00:41:37.400 --> 00:41:38.820 they were just 8-bit machines. 00:41:38.820 --> 00:41:42.260 I have, I grew up, started with, with 8-bit computer. 00:41:42.260 --> 00:41:44.200 I was an Atari kid. 00:41:44.200 --> 00:41:51.880 Never owned a C64, but someone has actually written a Commodore 64 emulator called PyC64 00:41:51.880 --> 00:41:53.360 in pure Python. 00:41:53.360 --> 00:41:55.980 And the reason that I picked this is- 00:41:55.980 --> 00:41:56.500 That's wild. 00:41:56.500 --> 00:41:58.320 It really is, isn't it? 00:41:58.320 --> 00:42:05.360 I think it is so cool because not only do you get this Commodore 64 emulator, it's not 00:42:05.360 --> 00:42:13.580 100% coverage, like he has openly emulated the display to the point where you can display 00:42:13.580 --> 00:42:14.740 Petsiki characters. 00:42:14.740 --> 00:42:19.080 But the bottom line is, it is other than that, a largely full machine emulator. 00:42:19.080 --> 00:42:27.880 It runs on the Pi65 library, which is a 6502 CPU chip emulator also written in pure Python. 00:42:27.880 --> 00:42:28.420 Oh my gosh. 00:42:28.420 --> 00:42:29.180 That's hard work. 00:42:29.660 --> 00:42:30.520 It really is. 00:42:30.520 --> 00:42:31.780 And, and it's so neat. 00:42:31.780 --> 00:42:34.000 I was able to pull this thing down and run it. 00:42:34.000 --> 00:42:40.600 And I was actually writing like Commodore 64 basic that poked bits into screen memory and, 00:42:40.600 --> 00:42:42.580 you know, drew pictures off the screen. 00:42:42.580 --> 00:42:49.160 And, and one of the really cool things is this thing even concludes, you can sort of like pop 00:42:49.160 --> 00:42:54.820 out of your emulator 64 with the gopy command to get a Python repl. 00:42:55.220 --> 00:43:01.400 Skype is actually doing that, like, quality quality, the emulated Commodore 64's memory 00:43:01.400 --> 00:43:05.280 by tweaking the Python data structures inside the repl. 00:43:05.280 --> 00:43:07.040 It is just, it is. 00:43:07.040 --> 00:43:08.400 That's pretty deep. 00:43:08.400 --> 00:43:09.120 Thank you. 00:43:09.120 --> 00:43:10.360 It is, it is really cool. 00:43:10.360 --> 00:43:15.840 And, and it is also from my perspective, one of the reasons I picked it, it's a testament 00:43:15.840 --> 00:43:20.020 to this programming language that we all use and love for our work. 00:43:20.020 --> 00:43:25.020 And, you know, whether it's webby stuff or testing devices or in my case, automating network 00:43:25.020 --> 00:43:27.720 infrastructure, it can do so much. 00:43:27.720 --> 00:43:33.420 You can reach out into all these other really kind of, you know, cool niche areas, whatever 00:43:33.420 --> 00:43:39.300 you're interested in and, and do neat things with Python on your computer. 00:43:39.300 --> 00:43:41.920 So I just thought this was incredibly cool. 00:43:41.920 --> 00:43:46.880 I had enjoyed playing with it and I definitely intend to enjoy playing with it some more. 00:43:46.880 --> 00:43:51.420 It might be some interesting ways to go back and study operating systems back when they were 00:43:51.420 --> 00:43:51.740 simple. 00:43:51.740 --> 00:43:54.220 If you were like a computer science student as well. 00:43:54.220 --> 00:43:55.440 Yeah, for sure. 00:43:55.520 --> 00:43:57.140 I think there's a lot to learn there. 00:43:57.140 --> 00:44:03.560 you know, even if you're not necessarily someone who is keenly interested in writing your 00:44:03.560 --> 00:44:08.760 own operating system, I think there's a lot to learn just in terms of the programming paradigm, 00:44:08.760 --> 00:44:09.240 right? 00:44:09.240 --> 00:44:13.900 Like when, when you wanted to solve a problem and you want it to display something on the 00:44:13.900 --> 00:44:21.040 screen and a perfectly reasonable answer was I'm going to poke the right bits into screen 00:44:21.040 --> 00:44:26.940 memory because that's a more efficient way to display this thing as opposed to using whatever 00:44:26.940 --> 00:44:28.780 my high level language provides. 00:44:28.780 --> 00:44:34.420 It is, it's such a different way of thinking the reality that most of us have it day to day. 00:44:34.420 --> 00:44:38.760 It's just a fun, refresh, refreshing place to visit, at least from my perspective. 00:44:38.760 --> 00:44:39.320 Yeah. 00:44:39.320 --> 00:44:39.920 Very cool. 00:44:39.920 --> 00:44:40.600 It's a good one. 00:44:40.600 --> 00:44:41.220 Thank you. 00:44:41.220 --> 00:44:43.920 Brian, it's time for extra, extra, extra here all about it. 00:44:43.920 --> 00:44:45.220 How many extras do you have? 00:44:45.220 --> 00:44:47.640 I have zero today. 00:44:47.640 --> 00:44:49.200 You have no extras. 00:44:49.200 --> 00:44:50.700 You're not adding to the number of extras. 00:44:50.700 --> 00:44:53.340 Chris, anything else you want to throw out there that people know about? 00:44:53.340 --> 00:44:54.060 Sure. 00:44:54.060 --> 00:44:54.780 Absolutely. 00:44:54.780 --> 00:44:57.040 My, my team at Amazon is hiring. 00:44:57.040 --> 00:44:59.480 Hopefully we can put a link in the show notes. 00:44:59.480 --> 00:45:01.040 I work for OpsTech IT. 00:45:01.040 --> 00:45:08.320 We work with the fulfillment centers and I, the, I cannot say enough how much I love working 00:45:08.320 --> 00:45:08.920 with this team. 00:45:08.920 --> 00:45:14.700 People are incredible and they're sort of like, at least the folks I'm working directly with 00:45:14.700 --> 00:45:21.180 are people who started out in the fulfillment centers and were interested in technology, right? 00:45:21.180 --> 00:45:25.140 And they were able to prove that they could actually walk the walk. 00:45:25.140 --> 00:45:28.620 And now they're being promoted into full on engineering positions. 00:45:28.620 --> 00:45:31.840 And I just find that so incredibly refreshing. 00:45:31.840 --> 00:45:32.400 Yeah. 00:45:32.400 --> 00:45:33.000 That's fantastic. 00:45:33.480 --> 00:45:33.660 Yeah. 00:45:33.660 --> 00:45:35.680 These people just have a very different perspective. 00:45:35.680 --> 00:45:37.240 You know, they're not the jaded. 00:45:37.240 --> 00:45:40.140 Like I've been in the tech industry for 20 years types like me. 00:45:40.140 --> 00:45:42.980 It's, it's really inspiring to work with them. 00:45:42.980 --> 00:45:43.280 Yeah. 00:45:43.280 --> 00:45:46.500 Not, not too many debates of like, why don't we just switch to a functional language? 00:45:46.500 --> 00:45:47.440 Come on. 00:45:49.040 --> 00:45:49.800 More practical. 00:45:49.800 --> 00:45:49.840 More practical. 00:45:49.840 --> 00:45:51.020 We'll just get stuff done. 00:45:51.020 --> 00:45:51.740 I love it. 00:45:51.740 --> 00:45:52.260 Exactly. 00:45:52.260 --> 00:45:52.800 Thank you. 00:45:52.800 --> 00:45:53.300 Before we move. 00:45:53.300 --> 00:45:53.560 Yeah. 00:45:53.560 --> 00:45:54.260 Yeah. 00:45:54.260 --> 00:45:55.340 So we'll put that link in the show notes. 00:45:55.340 --> 00:45:58.300 Before we move on to my extras, which are not many. 00:45:58.300 --> 00:46:02.060 Sam says, it's so helpful to understand how a computer works when you're writing code. 00:46:02.060 --> 00:46:04.460 These kinds of things are a good way to learn that. 00:46:04.460 --> 00:46:06.820 Talking about the Commodore 64 emulator. 00:46:06.820 --> 00:46:07.440 Awesome. 00:46:07.440 --> 00:46:07.800 All right. 00:46:07.800 --> 00:46:14.700 So I just have one and that's, I'm going to be speaking at FlaskCon 2021. 00:46:15.400 --> 00:46:19.800 And so FlaskCon is the first week of December, which has a remote attendance. 00:46:19.800 --> 00:46:24.500 I'm going to be talking about HTMX and Flask once again, because I'm super psyched about 00:46:24.500 --> 00:46:24.980 all that stuff. 00:46:24.980 --> 00:46:30.920 And so if you want to see some really cool apps get built using HTMX and Flask, drop in over 00:46:30.920 --> 00:46:31.140 there. 00:46:31.140 --> 00:46:33.320 There's a whole bunch of other talks going on as well. 00:46:33.320 --> 00:46:35.300 So I'll put the link to that in the show notes. 00:46:35.300 --> 00:46:36.140 All right. 00:46:36.140 --> 00:46:38.240 Shall we finish it off with a joke? 00:46:38.240 --> 00:46:39.080 Yeah. 00:46:39.080 --> 00:46:40.640 Levity is the soul of wit. 00:46:40.640 --> 00:46:41.140 Absolutely. 00:46:41.140 --> 00:46:42.260 It is. 00:46:43.040 --> 00:46:48.980 So we just recently went through the whole daylight savings unraveling and went back 00:46:48.980 --> 00:46:50.180 to normal time. 00:46:50.180 --> 00:46:56.780 And I don't know what it's like for you all, but when I look at the weather and stuff here, 00:46:56.780 --> 00:46:58.960 I suspect Chris, it's similar in Boston. 00:46:58.960 --> 00:47:01.100 I mean, I know it's similar for you, Brian. 00:47:01.100 --> 00:47:01.640 Yes. 00:47:01.640 --> 00:47:06.380 It's like sunset is at 438 PM and we're headed towards the winter solstice. 00:47:06.380 --> 00:47:08.420 So it's only getting earlier in the day. 00:47:08.500 --> 00:47:13.560 It's like, ah, that, that, that doesn't make me, it doesn't spark joy in my, in my heart 00:47:13.560 --> 00:47:15.200 that it's already dark at 430. 00:47:15.200 --> 00:47:16.380 I like it. 00:47:16.380 --> 00:47:16.760 Yeah. 00:47:16.760 --> 00:47:18.260 I like the dark. 00:47:18.260 --> 00:47:20.360 I don't mind that it gets dark. 00:47:20.360 --> 00:47:21.480 I just wish it wouldn't. 00:47:21.480 --> 00:47:22.680 I wish we could just move it. 00:47:22.680 --> 00:47:25.040 So there's a little time at the end of the day where there's still sun. 00:47:25.040 --> 00:47:25.400 I remember. 00:47:25.400 --> 00:47:26.380 I'm with you, Michael. 00:47:26.380 --> 00:47:27.340 I'm solo powered. 00:47:27.340 --> 00:47:28.780 So I enjoy the sunlight. 00:47:28.780 --> 00:47:30.880 I don't like it getting dark earlier either. 00:47:31.960 --> 00:47:32.960 Yeah, absolutely. 00:47:32.960 --> 00:47:33.860 I don't hate the winter. 00:47:33.860 --> 00:47:36.620 I just don't wish it shifted around a little bit. 00:47:36.620 --> 00:47:39.520 So this is a technical take on that. 00:47:39.520 --> 00:47:41.680 Our joke as this comes from the New Yorker. 00:47:41.680 --> 00:47:42.960 I mean, we're pretty highfalutin, right? 00:47:42.960 --> 00:47:46.400 We're not doing like dev jokes.io or whatever it was anymore. 00:47:48.100 --> 00:47:53.980 So this is by Matt Reuter and it's, it's a little cartoon of two people clearly in kind 00:47:53.980 --> 00:47:58.440 of a darker space, a woman sitting in her chair with a laptop and you could just like 00:47:58.440 --> 00:48:00.980 the beaming laptop screen is like a lightener up. 00:48:00.980 --> 00:48:01.200 Right. 00:48:01.200 --> 00:48:05.360 And the guy here on his tablet, same thing glowing on his face. 00:48:05.360 --> 00:48:09.720 And underneath it, it says, I hate how the screens get bright so early this time of year. 00:48:09.720 --> 00:48:11.980 Nice. 00:48:11.980 --> 00:48:14.440 This is so much about our modern world. 00:48:14.440 --> 00:48:17.060 It's both, it's both hilarious and kind of sad. 00:48:17.240 --> 00:48:18.240 All it wouldn't go. 00:48:18.240 --> 00:48:20.000 Absolutely. 00:48:20.000 --> 00:48:21.820 Yeah. 00:48:21.820 --> 00:48:25.240 So welcome to daylight savings or standard time. 00:48:25.240 --> 00:48:29.100 I guess everyone, the screens do get bright this time of year. 00:48:29.100 --> 00:48:30.800 That's funny. 00:48:30.800 --> 00:48:31.400 Nice. 00:48:31.400 --> 00:48:33.980 And Chris, thanks for being on the show. 00:48:33.980 --> 00:48:35.140 Brian, thanks as always. 00:48:35.140 --> 00:48:35.720 Yeah. 00:48:35.720 --> 00:48:36.300 Thanks a lot. 00:48:36.300 --> 00:48:37.200 Thank you so much. 00:48:37.200 --> 00:48:40.300 You know, I really appreciate everything that you guys do for the community. 00:48:40.300 --> 00:48:45.880 It's, it's really, you guys are great examples of why Python is such an amazing place to 00:48:45.880 --> 00:48:46.140 live. 00:48:46.380 --> 00:48:46.760 Thank you. 00:48:46.760 --> 00:48:47.620 Thanks, Chris.