WEBVTT 00:00:00.001 --> 00:00:05.060 Hello and welcome to Python Bytes, where we deliver Python news and headlines directly to your earbuds. 00:00:05.060 --> 00:00:10.400 This is episode 194, recorded August 5th, 2020. 00:00:10.400 --> 00:00:11.880 I'm Brian Okken. 00:00:11.880 --> 00:00:12.860 And I'm Michael Kennedy. 00:00:12.860 --> 00:00:18.760 And this episode is brought to you by us, and we'll tell you more about what we're shilling later in the day. 00:00:18.760 --> 00:00:21.400 I want to talk to you about mutants. 00:00:21.400 --> 00:00:26.160 Mutants? Like mutant ninja turtle type things? Or what are we looking at here? 00:00:26.160 --> 00:00:27.860 Sure, mutant ninja turtles. 00:00:27.860 --> 00:00:29.740 No. So mutation testing. 00:00:29.740 --> 00:00:35.380 So I really kind of, I think, I'm warming to mutation testing, and it's kind of a neat thing. 00:00:35.380 --> 00:00:42.860 And I think we've covered it before, but this article is from Mosh Zadka, and it's called An Introduction to Mutation Testing in Python. 00:00:42.860 --> 00:00:48.180 There are a few, a handful of, I think there's like two or three different mutation testing libraries. 00:00:48.180 --> 00:00:52.440 MuttMutt is one of them, and that's what this article uses. 00:00:52.440 --> 00:00:57.020 And so if people are not familiar with mutation testing, here's the problem. 00:00:57.160 --> 00:01:04.760 So you can use code coverage tools like coverage.py to show how much of your code your tests are covering. 00:01:04.760 --> 00:01:09.560 But even if you get to 100% coverage, it doesn't mean that you're really testing everything. 00:01:09.560 --> 00:01:16.980 And so mutation testing, what it does is it takes your code under test, and it does some modifications. 00:01:16.980 --> 00:01:21.480 So it modifies portions of your source code to simulate potential bugs. 00:01:21.480 --> 00:01:30.800 Like, for example, it'll replace the greater than comparison with greater than equal, or replacing it with those sorts of edge cases and stuff are often where we muck up. 00:01:30.800 --> 00:01:35.100 If there's no boundary test around the boundary condition, you know, there'll be a problem. 00:01:35.360 --> 00:01:38.180 So every little change is considered a mutant. 00:01:38.180 --> 00:01:43.160 And it generates all these different mutants, and it does it in a fairly smart way. 00:01:43.160 --> 00:01:47.340 It can test your code fairly quickly with not too many mutants. 00:01:47.340 --> 00:01:50.420 So, and then it runs your test suite on the mutant. 00:01:50.420 --> 00:01:54.280 And the idea is your test suite should kill all of the mutants. 00:01:54.640 --> 00:02:01.760 So in this article, he shows an example of three methods and one test case and 100% code coverage. 00:02:01.760 --> 00:02:08.920 But he runs mutt-mutt, and 16 of them survive, and then talks about how to fix that. 00:02:08.920 --> 00:02:11.300 So it's a really good, quick article. 00:02:11.300 --> 00:02:12.480 Yeah, this is interesting. 00:02:12.480 --> 00:02:17.380 And I like the emoji legend use for the output. 00:02:17.380 --> 00:02:19.480 Yeah, it's a cute library. 00:02:19.480 --> 00:02:19.960 Yeah, it is. 00:02:19.960 --> 00:02:24.040 You know, one thing that I don't understand about mutation testing is, like, I understand, okay, well, 00:02:24.580 --> 00:02:30.360 we're going to change, like, a value of a variable, or, like, the way if we're doing a test, 00:02:30.360 --> 00:02:34.140 make it, it was less than, we're going to make it greater than, and see if your tests still pass, 00:02:34.140 --> 00:02:35.280 and, like, those kind of things. 00:02:35.280 --> 00:02:36.500 That totally seems reasonable. 00:02:36.500 --> 00:02:40.740 But if it goes in, I don't know if it does, maybe, you know, if it goes and, like, says, 00:02:40.740 --> 00:02:44.100 well, you're doing a print statement, so we changed part of the print string. 00:02:44.100 --> 00:02:46.580 Like, who's testing for that, right? 00:02:46.580 --> 00:02:48.880 Like, that seems like it would survive. 00:02:48.880 --> 00:02:50.160 Yeah, I'm not sure. 00:02:50.160 --> 00:02:54.520 So it seems like there's certain things, like, I would just never care to test for the output 00:02:54.520 --> 00:02:58.180 of the print statement where the static string changes. 00:02:58.180 --> 00:03:01.260 Like, to me, that just is not something I care to test, right? 00:03:01.260 --> 00:03:02.400 Yeah. 00:03:02.400 --> 00:03:07.180 But I feel like the sort of general case of mutation testing, you go, well, here's a piece of variable 00:03:07.180 --> 00:03:08.520 that I need to change around. 00:03:08.520 --> 00:03:11.240 Let's change a string and see if the tests still pass. 00:03:11.240 --> 00:03:14.880 So, I don't know, maybe it's just inappropriate for those types of scenarios. 00:03:14.880 --> 00:03:18.760 Maybe you only test stuff, like, at a lower level where you don't have, like, a bunch of print statements. 00:03:18.760 --> 00:03:20.860 But, you know, you've got logging and all kinds of things. 00:03:20.860 --> 00:03:21.520 So, I don't know. 00:03:21.520 --> 00:03:23.000 But still, I do like the idea. 00:03:23.000 --> 00:03:29.620 I think MutMut and some of the others have ways to specify which kinds of mutants to generate. 00:03:29.620 --> 00:03:30.460 I see. 00:03:30.460 --> 00:03:34.580 So, I don't know if it does the print statement sort of example, but I'm sure that there's ways 00:03:34.580 --> 00:03:37.220 to say, yeah, I don't really care about. 00:03:37.220 --> 00:03:39.680 Don't modify string values, for instance. 00:03:39.680 --> 00:03:40.040 Yeah. 00:03:40.040 --> 00:03:40.500 Yeah. 00:03:40.500 --> 00:03:40.540 Yeah. 00:03:41.120 --> 00:03:43.940 Like, don't modify constants or something, maybe. 00:03:43.940 --> 00:03:44.400 Who knows? 00:03:44.400 --> 00:03:44.720 Yeah. 00:03:44.720 --> 00:03:45.440 Yeah. 00:03:45.440 --> 00:03:45.680 Cool. 00:03:45.680 --> 00:03:46.560 All right. 00:03:46.560 --> 00:03:47.720 Well, you know, that looks really interesting. 00:03:47.720 --> 00:03:50.640 And Masha does a great job writing up these types of things. 00:03:50.640 --> 00:03:51.840 We feature him a lot. 00:03:51.840 --> 00:03:52.260 Very cool. 00:03:52.260 --> 00:03:56.800 Next up, I want to talk about asynchronous programming. 00:03:56.800 --> 00:03:57.440 Oh, nice. 00:03:57.440 --> 00:03:57.740 Yeah. 00:03:57.740 --> 00:03:59.640 So, maybe we've covered this before. 00:03:59.640 --> 00:04:03.860 No, we've covered this a lot, but I don't believe we've covered async Q. 00:04:03.860 --> 00:04:04.780 I don't think so. 00:04:04.780 --> 00:04:05.620 I don't think so either. 00:04:05.620 --> 00:04:10.220 So, this is from Quora, and it is not brand new. 00:04:10.520 --> 00:04:11.960 So, I just want to be really upfront. 00:04:11.960 --> 00:04:16.320 Like, this has been around since 2016, but it's pretty interesting. 00:04:16.320 --> 00:04:22.740 And the idea is, so much of what asynchronous programming, especially asyncio type of async 00:04:22.740 --> 00:04:26.940 and await programming is about, is scaling while you're waiting. 00:04:26.940 --> 00:04:28.640 Scaling the latencies, right? 00:04:28.640 --> 00:04:29.540 Okay. 00:04:29.540 --> 00:04:34.060 So, you know, like, I'm going to call the Stripe service, and it's going to take, you 00:04:34.060 --> 00:04:35.800 know, half a second to return. 00:04:35.800 --> 00:04:39.220 And so, I want my web server to be able to go and just do stuff. 00:04:39.920 --> 00:04:43.240 You know, other requests instead of waiting for half a second while we're checking out 00:04:43.240 --> 00:04:44.560 some person or whatever, right? 00:04:44.560 --> 00:04:46.720 But they've got a different use case. 00:04:46.720 --> 00:04:50.520 What they're doing is they're running, I don't know if I said this is from Quora. 00:04:50.520 --> 00:04:54.420 They're running Quora.com, which is a really cool Q&A site. 00:04:54.420 --> 00:04:59.380 I actually think Quora does a great job of having, like, solid, thoughtful answers. 00:04:59.380 --> 00:05:02.280 Not always right, but thoughtful at least, which is pretty cool. 00:05:02.600 --> 00:05:07.140 But what they do is they don't talk directly to their database because that would be too 00:05:07.140 --> 00:05:07.520 slow. 00:05:07.520 --> 00:05:09.300 Don't give me started on that. 00:05:09.960 --> 00:05:15.400 But what they're doing is they're talking to Memcached or Redis or whatever, but they're 00:05:15.400 --> 00:05:22.920 using Memcached to store a bunch of pre-computed query results so they don't have to keep going 00:05:22.920 --> 00:05:23.600 back to the database. 00:05:23.600 --> 00:05:29.240 Like, for example, when you go view a question, they want to see the names of the people who 00:05:29.240 --> 00:05:30.940 upvoted the question, right? 00:05:31.420 --> 00:05:33.580 So it's kind of a complicated query, right? 00:05:33.580 --> 00:05:35.380 I need to go, here's the IDs. 00:05:35.380 --> 00:05:37.660 We store the IDs of the upvoter. 00:05:37.660 --> 00:05:42.580 Then we're going to do a query, a join over on the user table and get their names back. 00:05:42.580 --> 00:05:43.420 And then we're going to show it. 00:05:43.420 --> 00:05:45.440 Like, that sounds expensive for lots of data. 00:05:45.440 --> 00:05:48.260 So what they do is they basically store those answers. 00:05:48.260 --> 00:05:52.000 Like, this user goes to this thing in Memcached. 00:05:52.000 --> 00:05:56.660 But a lot of the latency around this has to do actually with the network call. 00:05:56.660 --> 00:05:58.040 Like, it's pretty close. 00:05:58.180 --> 00:06:01.980 It's like, you know, one millisecond or something, but they've got to go get those 00:06:01.980 --> 00:06:03.460 names over and over, right? 00:06:03.460 --> 00:06:07.700 Because the way that you store stuff in Memcached is this ID has this name. 00:06:07.700 --> 00:06:09.480 You've got 50 upvoters. 00:06:09.480 --> 00:06:11.660 It's like, give me the name of this person, give me the name of that person. 00:06:11.660 --> 00:06:15.760 So there's a way to do like a, you know, a batch get like, here's all these IDs. 00:06:15.760 --> 00:06:17.540 Go get me all the associated names. 00:06:17.540 --> 00:06:22.920 And they've got like this dependency tree of these sorts of questions they have to answer. 00:06:22.920 --> 00:06:25.600 So what they've done is they've come up with this thing called AsyncQ. 00:06:25.720 --> 00:06:30.880 And it's all about batching asynchronous requests and converting them from a bunch of individual 00:06:30.880 --> 00:06:32.940 calls into like one massive call. 00:06:32.940 --> 00:06:33.660 Oh, okay. 00:06:33.660 --> 00:06:37.140 So they can like do what looks like asynchronous programming. 00:06:37.140 --> 00:06:38.680 Say, go get me all these things. 00:06:38.680 --> 00:06:43.400 And instead of doing a bunch of individual async and await type calls, the system looks that 00:06:43.400 --> 00:06:48.280 goes, okay, what that means is turn that into one giant query where it's like all of these 00:06:48.280 --> 00:06:51.120 IDs go to all those things and then return them back. 00:06:51.120 --> 00:06:51.620 Oh, that's right. 00:06:51.700 --> 00:06:51.820 Yeah. 00:06:51.820 --> 00:06:52.240 It's pretty neat. 00:06:52.240 --> 00:06:57.380 So it's basically this way to write code that will take a, what would be a bunch of small 00:06:57.380 --> 00:07:03.500 independent requests and turn it into like a one shot request for talking to things like 00:07:03.500 --> 00:07:04.860 caching servers and whatnot. 00:07:04.860 --> 00:07:05.260 Yeah. 00:07:05.260 --> 00:07:05.640 Yeah. 00:07:05.640 --> 00:07:11.480 So apparently this is like a core component of core's architecture and yeah, it's all about 00:07:11.480 --> 00:07:13.000 batching up these calls. 00:07:13.000 --> 00:07:15.540 I didn't know core was Python on the backend. 00:07:15.540 --> 00:07:16.140 Oh yeah. 00:07:16.140 --> 00:07:16.580 Yeah. 00:07:16.580 --> 00:07:20.680 They've got a really interesting Python blog where they, like an engineering blog where they 00:07:20.680 --> 00:07:21.780 talk about all sorts of stuff. 00:07:21.780 --> 00:07:26.880 So this was like written up on their engineering blog about sort of how they went from what they 00:07:26.880 --> 00:07:30.700 were doing before this, which was, you'd have to like write several functions that would 00:07:30.700 --> 00:07:31.760 prepare the things. 00:07:31.760 --> 00:07:35.180 And then you could ask for it because they would be cached locally and all sorts of funky 00:07:35.180 --> 00:07:35.460 stuff. 00:07:35.620 --> 00:07:39.240 So there's a great writeup on sort of the whole use case of this. 00:07:39.240 --> 00:07:41.340 So this, like I said, is from 2016. 00:07:41.340 --> 00:07:43.560 So it predates async and await. 00:07:43.560 --> 00:07:50.840 And so they use the yield keyword, which is a sort of a more foundational way to get, to 00:07:50.840 --> 00:07:52.960 break up functions into parts that run. 00:07:52.960 --> 00:07:57.500 So basically you decorate a function and then you yield out the various steps. 00:07:57.500 --> 00:08:01.600 And then before it executes all those, it looks at them, figures out what it has to do. 00:08:01.600 --> 00:08:04.000 And then it like batches it up and then does it all at once. 00:08:04.000 --> 00:08:04.640 Pretty wild. 00:08:04.640 --> 00:08:05.080 Yeah. 00:08:05.080 --> 00:08:05.840 Yeah. 00:08:05.840 --> 00:08:08.620 So I thought this was, you know, kind of interesting. 00:08:08.620 --> 00:08:12.520 I think it's a little bit just looking at the patterns here. 00:08:12.520 --> 00:08:19.220 I feel like it's a little tiny bit limited because it's targeted at, I believe they're still at 00:08:19.220 --> 00:08:20.240 least then, right? 00:08:20.240 --> 00:08:25.280 So when they came up with it and it's still active, I think they built it for running a 00:08:25.280 --> 00:08:26.340 Python two, right? 00:08:26.340 --> 00:08:28.860 Remember this 2016, they'd been running for a while. 00:08:28.860 --> 00:08:34.300 So some of their APIs, I don't think like, for example, they don't use the async and await 00:08:34.300 --> 00:08:35.300 keyword. 00:08:35.300 --> 00:08:38.140 I think because that didn't exist. 00:08:38.140 --> 00:08:43.300 Like they supported Python three, four where asyncio was, but async and await didn't come 00:08:43.300 --> 00:08:44.820 along until just a tiny bit later. 00:08:44.820 --> 00:08:45.440 I don't think so. 00:08:45.440 --> 00:08:50.580 Anyway, a bit of a grain of salt, but I think, you know, this will be a pretty interesting thing 00:08:50.580 --> 00:08:53.740 that people can adopt and use for these types of scenarios. 00:08:53.740 --> 00:08:57.140 Certainly if it powers Quora, it's probably pretty good. 00:08:57.140 --> 00:08:57.480 Yeah. 00:08:57.480 --> 00:08:58.240 Neat. 00:08:58.240 --> 00:08:58.800 Cool. 00:08:58.800 --> 00:08:59.360 Absolutely. 00:08:59.360 --> 00:08:59.720 Yep. 00:08:59.720 --> 00:09:02.500 Another thing that's cool is Talk Python Training. 00:09:02.500 --> 00:09:03.020 Thank you. 00:09:03.020 --> 00:09:04.540 We got a lot of stuff going on over there. 00:09:04.540 --> 00:09:06.240 Actually, we've got a ton of new courses coming. 00:09:06.740 --> 00:09:11.300 course for people who generally live in Excel and should be adopting the Python data science 00:09:11.300 --> 00:09:11.680 tools. 00:09:11.680 --> 00:09:13.680 So that's coming really soon. 00:09:13.680 --> 00:09:15.160 We've got a getting started with data science. 00:09:15.160 --> 00:09:18.460 I just actually, last time we spoke, I said, hey, I'm writing this course. 00:09:18.460 --> 00:09:21.340 I started writing a course called Python Memory Management. 00:09:21.900 --> 00:09:22.760 I finished it. 00:09:22.760 --> 00:09:23.500 I recorded it. 00:09:23.500 --> 00:09:24.420 It's like a five hour course. 00:09:24.420 --> 00:09:24.920 It's going to be awesome. 00:09:24.920 --> 00:09:28.420 So now I'm on to writing a new course, Python design patterns. 00:09:28.420 --> 00:09:29.080 Oh, nice. 00:09:29.080 --> 00:09:29.360 Yeah. 00:09:29.360 --> 00:09:31.040 So that'll be out in a few weeks as well. 00:09:31.040 --> 00:09:32.100 How about you? 00:09:32.100 --> 00:09:32.460 Yeah. 00:09:32.460 --> 00:09:35.040 I just wanted to highlight again. 00:09:35.040 --> 00:09:42.420 I have the URL pytestbook.com set up to go directly to Arata because I get a lot of people 00:09:42.420 --> 00:09:48.780 asking, hey, your pytest book, is it still good for, it was like in 2017, still valid? 00:09:48.780 --> 00:09:50.160 Yes, it's still valid. 00:09:50.160 --> 00:09:53.720 But there's a few gotchas and I list them out. 00:09:53.720 --> 00:09:56.420 Very easy to read at pytestbook.com. 00:09:56.420 --> 00:09:59.180 It directs you to an Arata page to show you. 00:09:59.180 --> 00:10:02.820 It's just a couple tweaks to the source code you got to make. 00:10:02.820 --> 00:10:05.440 You got to pin TinyDB and a couple other things. 00:10:05.440 --> 00:10:11.660 And we'll try to get those changes out to the download link on Pragmatic as soon as possible. 00:10:11.660 --> 00:10:13.060 That's still in the works. 00:10:13.060 --> 00:10:18.420 But there's also a link to, if you have any issues, there's a link to the official Pragmatic 00:10:18.420 --> 00:10:21.000 Arata page where you can ask questions. 00:10:21.000 --> 00:10:24.120 And if you haven't run into anything, I'd love to hear about it. 00:10:24.120 --> 00:10:26.240 And I'm excited to get a lot. 00:10:26.240 --> 00:10:31.420 Lately, a lot of the people that have been contacting me said they're excited about reading the book 00:10:31.420 --> 00:10:32.540 are machine learning people. 00:10:32.820 --> 00:10:38.240 So it's kind of neat to see data science and machine learning people add testing to their workflows. 00:10:38.240 --> 00:10:39.020 That's exciting. 00:10:39.020 --> 00:10:39.520 Absolutely. 00:10:39.520 --> 00:10:42.020 So I have a final call to action for people out there. 00:10:42.020 --> 00:10:48.200 If you want to make sure that we have the time and energy to keep creating stuff like this podcast and the other things we're doing, 00:10:48.460 --> 00:10:52.600 you don't necessarily have to get our stuff, but how about recommending it, right? 00:10:52.600 --> 00:10:59.960 If your company needs to get up to speed on Python, recommend that your company buy the courses for that team. 00:10:59.960 --> 00:11:06.700 Or if a company is doing a bunch of testing, have everyone on that team or the engineering group get Brian's book. 00:11:06.700 --> 00:11:07.660 That would be great. 00:11:07.660 --> 00:11:12.880 Yeah, and then individually to remind people that we do have a Patreon campaign going. 00:11:12.880 --> 00:11:16.480 So people can contribute a buck or two a month. 00:11:16.480 --> 00:11:17.120 That would be great. 00:11:17.120 --> 00:11:17.440 Yeah. 00:11:17.440 --> 00:11:19.460 Now that we go anywhere, we don't buy coffee. 00:11:19.460 --> 00:11:20.580 Yeah. 00:11:20.580 --> 00:11:21.980 Next, I want to talk. 00:11:21.980 --> 00:11:24.140 This sort of ties into your async thing. 00:11:24.140 --> 00:11:25.400 Yeah, yeah, for sure. 00:11:25.400 --> 00:11:26.560 That's interesting. 00:11:26.560 --> 00:11:28.340 But they use Memcached. 00:11:28.340 --> 00:11:30.780 But I wanted to talk about Redis. 00:11:30.780 --> 00:11:37.420 So I've not used Redis myself, but I know that a lot of people do for caching and for other things. 00:11:38.240 --> 00:11:39.760 And so this is an article. 00:11:39.760 --> 00:11:48.340 It's actually on the Redis site, but it's an article called Redis Beyond the Cache in Python by Guy Royce, I think. 00:11:48.340 --> 00:11:53.600 I knew that Redis did more than just a cache for a backend database. 00:11:53.600 --> 00:11:55.160 But this is kind of neat. 00:11:55.160 --> 00:12:00.980 So these are good, clear examples of Python code using Redis for more than just caching. 00:12:00.980 --> 00:12:04.680 So the first example talks about how to use it as a queue. 00:12:04.840 --> 00:12:07.780 So you can set it up as a fast queuing system. 00:12:07.780 --> 00:12:12.400 And apparently there's a couple calls called rpush and blpop. 00:12:12.400 --> 00:12:16.440 And actually, to tell you the truth, I picked this article because of blpop. 00:12:16.440 --> 00:12:19.060 I think that's one of the best function names ever. 00:12:19.060 --> 00:12:22.300 I don't know what it means, but maybe back of the list pop? 00:12:22.300 --> 00:12:23.280 Not sure. 00:12:23.280 --> 00:12:24.360 But it's good. 00:12:24.360 --> 00:12:31.840 I thought you picked it because of the various, from the code example about putting stuff into queues here. 00:12:31.840 --> 00:12:34.020 That felt close to home. 00:12:34.020 --> 00:12:34.420 Did it? 00:12:34.420 --> 00:12:34.760 Yeah. 00:12:34.760 --> 00:12:36.160 It's about Bigfoot sightings. 00:12:36.160 --> 00:12:42.180 We've got a sighting near the Columbia River and people were chased by a tall, hairy creature and so on. 00:12:42.180 --> 00:12:42.220 Oh, yeah. 00:12:42.220 --> 00:12:46.900 So like asynchronously adding Bigfoot sightings from the general Pacific Northwest. 00:12:46.900 --> 00:12:48.800 Yeah, that's good. 00:12:48.800 --> 00:12:50.760 Sorry, carry on. 00:12:50.760 --> 00:12:51.660 Didn't mean to derail you. 00:12:51.660 --> 00:12:52.380 No, no. 00:12:52.380 --> 00:12:52.840 It's good. 00:12:53.040 --> 00:12:56.740 So using it as a queue, using it in a PubSub model. 00:12:56.740 --> 00:13:00.440 Apparently there's functions like publish and psubscribe. 00:13:00.440 --> 00:13:03.020 So you can do publish and subscribe models. 00:13:03.020 --> 00:13:06.440 Data streaming, using it as a search engine. 00:13:06.440 --> 00:13:12.940 The search engine seems like a little more hardcore because it looks like they're, it's almost like SQL queries that you're using. 00:13:12.940 --> 00:13:14.220 But apparently you can do that. 00:13:14.220 --> 00:13:21.500 And of course, you can also use it as your primary in-memory database if you want to, as long as you don't need to store it somewhere. 00:13:21.920 --> 00:13:24.860 So, or use some later thing. 00:13:24.860 --> 00:13:26.700 You know, I guess I'm just winging it here. 00:13:26.700 --> 00:13:31.200 I don't know how you get, how you hook up a Redis database to a normal database. 00:13:31.200 --> 00:13:34.440 But I know you database people know how to do that. 00:13:34.440 --> 00:13:42.780 But I probably use, I like the idea of using it as a queue system for like multi-threads and multi-processes. 00:13:42.780 --> 00:13:43.660 That sounds kind of fun. 00:13:43.660 --> 00:13:47.960 This is a really cool article because I just often think of Redis as cache, right? 00:13:47.960 --> 00:13:49.920 But yeah, there's a bunch of neat stuff here. 00:13:49.920 --> 00:13:51.060 And yeah. 00:13:51.060 --> 00:13:55.060 So often you think like, oh, I'll just write this cool data structure. 00:13:55.060 --> 00:13:55.980 We'll just do this thing. 00:13:55.980 --> 00:13:56.660 And it's great. 00:13:56.660 --> 00:13:59.140 And you're like, oh, wait, but hold on. 00:13:59.140 --> 00:14:03.820 When I deploy that to the web server, it forks off like 10 copies of micro whiskey. 00:14:04.120 --> 00:14:08.840 And so I'm going to have like 10 separate DB copies and all this, like, there's just certain 00:14:08.840 --> 00:14:10.960 times you're like, I just need a thing to hold this stuff. 00:14:10.960 --> 00:14:12.480 And like Redis seems pretty cool for that. 00:14:12.480 --> 00:14:12.680 Yeah. 00:14:12.680 --> 00:14:17.260 And the examples use, apparently there's a bunch of different Python libraries to access Redis. 00:14:17.260 --> 00:14:23.680 And this one uses AIO Redis because there's async and await calls to access everything. 00:14:23.680 --> 00:14:23.980 Yeah. 00:14:23.980 --> 00:14:24.360 It's beautiful. 00:14:24.360 --> 00:14:26.860 It's a real nice example of async and await as well there. 00:14:26.860 --> 00:14:27.140 Yeah. 00:14:27.200 --> 00:14:30.700 So I'm sure, Brian, you've heard of little Bobby tables. 00:14:30.700 --> 00:14:33.380 Yeah, of course. 00:14:33.380 --> 00:14:34.380 I don't know. 00:14:34.380 --> 00:14:35.540 I think we've brought it up on the show. 00:14:35.540 --> 00:14:35.920 Yeah. 00:14:35.920 --> 00:14:38.860 I don't know if we've actually, have we featured it as a proper joke? 00:14:38.860 --> 00:14:40.100 I don't know what we have. 00:14:40.100 --> 00:14:42.740 Nonetheless, this one is no joke. 00:14:42.740 --> 00:14:44.400 This is just little table. 00:14:44.400 --> 00:14:45.780 I don't know what I was thinking. 00:14:45.780 --> 00:14:46.900 I know what I was thinking. 00:14:46.900 --> 00:14:47.560 I was curious. 00:14:47.720 --> 00:14:53.520 I didn't want to commit as much effort as it turned out to be into having like a broad discussion about this. 00:14:53.520 --> 00:14:55.920 But I thought, okay, well, we have dictionaries. 00:14:55.920 --> 00:15:01.960 And so I can go and find a single key, pass in a certain key, and then get the thing back or not. 00:15:01.960 --> 00:15:02.180 Right? 00:15:02.180 --> 00:15:07.080 So if I've got like, I don't know, users, I could have the user ID. 00:15:07.080 --> 00:15:11.980 And then the user object comes back if I index the dictionary like that. 00:15:11.980 --> 00:15:12.740 Totally simple, right? 00:15:12.740 --> 00:15:13.040 Yeah. 00:15:13.040 --> 00:15:16.540 What if we wanted to ask that question two ways on the same data structure? 00:15:16.700 --> 00:15:22.180 What if I wanted to say, give me the user by ID and give me the user by email? 00:15:22.180 --> 00:15:29.680 So one possible way, I guess, you could just cram all the IDs and all the emails into the dictionary. 00:15:29.680 --> 00:15:38.820 But then things like, you know, enumerate over dict.items breaks because you get, you know, every now and then it's integers or it's strings. 00:15:38.820 --> 00:15:43.080 And then it's a duplicate of the users like in .items or .values. 00:15:43.080 --> 00:15:45.000 So it's not really a great one. 00:15:45.020 --> 00:15:49.500 So I said, does Python have like a structure that is not a database? 00:15:49.500 --> 00:15:52.700 Because I do not want to do database stuff. 00:15:52.700 --> 00:15:54.960 Like if I wanted to do that, I would just use a database. 00:15:54.960 --> 00:16:05.220 A thing that is lightweight and in memory and easy to use that lets me put something like a user in there, but then be able to ask, give me the user by ID. 00:16:05.220 --> 00:16:06.600 Give me the user by email. 00:16:07.120 --> 00:16:08.160 That is fast. 00:16:08.160 --> 00:16:08.760 Right. 00:16:08.760 --> 00:16:18.460 So dictionaries work because they're indexed and they're insanely like near, you know, oh, one type of performance on getting back the content that's in there. 00:16:18.460 --> 00:16:18.660 Right. 00:16:18.660 --> 00:16:18.920 Yeah. 00:16:18.980 --> 00:16:21.900 So I want to be able to do that both with email and ID not. 00:16:21.900 --> 00:16:24.580 I'm going to go on this rant some more later. 00:16:24.580 --> 00:16:29.060 I'm actually trying to pull together all the responses I got because I got a bunch of things given back to me. 00:16:29.460 --> 00:16:33.120 A lot of people suggested pandas, but I want to store non-tabular data. 00:16:33.120 --> 00:16:37.420 So I'm not sure pandas, which is tabular-ish makes sense. 00:16:37.420 --> 00:16:45.560 Nonetheless, one thing I did come up with that's probably the closest to what I was asking for without me doing any work, which I'm not against doing work. 00:16:45.620 --> 00:16:47.760 But if something exists, you know, let me pip install it. 00:16:47.760 --> 00:16:47.940 Right. 00:16:47.940 --> 00:16:50.580 Is this thing called light table by Paul McGuire. 00:16:50.580 --> 00:16:52.140 Sorry, not light table. 00:16:52.140 --> 00:16:52.740 Little table. 00:16:52.740 --> 00:16:54.580 Little table. 00:16:54.580 --> 00:17:04.320 And it gives you a schema-less in-memory thing that's kind of like a dictionary, but gives you ORM-like access to the objects. 00:17:04.320 --> 00:17:04.840 Okay. 00:17:04.840 --> 00:17:17.500 Okay, so it's like, think of like an in-memory database, basically, that you don't have to go create table, you know, set column type, name this to, you know, var char 16 type. 00:17:17.500 --> 00:17:22.040 And like, you don't have to actually define the table like a full-on database, right? 00:17:22.040 --> 00:17:28.280 You just say it has, you know, put these things in it like you would a dictionary, and then you can access all the elements. 00:17:28.280 --> 00:17:29.140 What do you think? 00:17:29.140 --> 00:17:31.320 I think I'd like to try to solve your problem also. 00:17:31.320 --> 00:17:33.880 It's a fun programming problem, right? 00:17:34.220 --> 00:17:38.060 But this thing is pretty cool because it lets you do like greater than queries. 00:17:38.060 --> 00:17:42.680 It has indexes on all of the columns or the columns that you say you want them on. 00:17:42.680 --> 00:17:46.780 Like, all you do is say, it's like create a dictionary and say, I'm going to put in a thing by ID. 00:17:46.780 --> 00:17:47.940 I'm going to put in a thing by email. 00:17:47.940 --> 00:17:49.220 I'm going to put in a thing by city. 00:17:49.220 --> 00:17:51.600 And I want to index for all of those. 00:17:51.600 --> 00:17:54.840 So it's like dictionary-like speed, which is pretty cool. 00:17:54.840 --> 00:17:59.160 It even does like in-memory joins and all sorts of stuff. 00:17:59.160 --> 00:18:01.040 So, yeah. 00:18:01.040 --> 00:18:01.500 Okay. 00:18:01.500 --> 00:18:02.440 That's neat. 00:18:02.440 --> 00:18:05.600 And the result of like a query can be like another little table. 00:18:05.600 --> 00:18:09.840 So I could like do a filter and select only a couple of columns. 00:18:09.840 --> 00:18:11.780 And then out comes a little baby little table. 00:18:11.780 --> 00:18:13.580 A little, even littler little table. 00:18:13.580 --> 00:18:21.780 Anyway, I thought this was a pretty cool thing because it lets you kind of do database-like stuff without the effort. 00:18:21.780 --> 00:18:22.340 Right? 00:18:22.340 --> 00:18:23.340 Do it dynamically. 00:18:23.580 --> 00:18:26.300 Some people said, hey, you should just use SQLite. 00:18:26.300 --> 00:18:28.000 I'm like, yeah, SQLite's cool. 00:18:28.000 --> 00:18:32.400 But then I've got to come up with a full-on schema for defining the thing. 00:18:32.400 --> 00:18:34.220 And that gets to be a pain. 00:18:34.220 --> 00:18:36.220 There's also some other options. 00:18:36.220 --> 00:18:38.020 But little table looks good. 00:18:38.020 --> 00:18:38.360 Yeah. 00:18:38.360 --> 00:18:40.240 I'll have to get an example. 00:18:40.240 --> 00:18:43.160 Get your actual problem statement again and try it. 00:18:43.160 --> 00:18:44.000 But this looks neat. 00:18:44.000 --> 00:18:44.340 Yeah. 00:18:44.340 --> 00:18:45.040 Yeah, absolutely. 00:18:45.040 --> 00:18:47.780 Yeah, well, I'll come back to that for sure as well. 00:18:47.780 --> 00:18:54.520 So because I want to bring together, like I got so many good recommendations and ideas that I think is probably worth just doing a segment on that. 00:18:54.520 --> 00:18:55.340 But little table. 00:18:55.340 --> 00:18:55.740 Nice. 00:18:56.040 --> 00:18:58.780 This is something I'm surprised we didn't talk about already. 00:18:58.780 --> 00:19:00.500 Maybe we have, but I've forgotten. 00:19:00.500 --> 00:19:02.180 pytest Timeout. 00:19:02.180 --> 00:19:03.880 This was a listener's suggestion. 00:19:03.880 --> 00:19:14.360 And I think it's pretty much an essential plugin for any test suite that you're running, especially if it's not something you're running where you're watching it. 00:19:14.360 --> 00:19:23.800 So if it's something running on a server or continuous integration or something, or if it's a long-running test suite, it's a very simple-to-use plugin. 00:19:23.800 --> 00:19:29.080 And what you want to make sure is that none of your tests run longer than a certain number of seconds. 00:19:29.080 --> 00:19:35.980 All the people out there that are, like, scratching their head thinking, wow, there's a test that runs longer than a second. 00:19:35.980 --> 00:19:38.360 Yes, there are tests that run longer than a second. 00:19:38.360 --> 00:19:42.100 Especially if they're trying to talk to hardware or external things. 00:19:42.100 --> 00:19:42.460 Yeah. 00:19:42.460 --> 00:19:44.520 And that thing might not be there and it's just waiting. 00:19:44.520 --> 00:19:46.660 Yeah, there's more to testing than unit testing. 00:19:46.660 --> 00:19:48.040 There's also system testing. 00:19:48.040 --> 00:19:53.020 But anyway, this one's great because you can set up a configuration in the config file. 00:19:53.160 --> 00:19:58.680 You can throw one number in to say, like, say you have, like, you know, five minutes or something like that. 00:19:58.680 --> 00:20:01.020 Or even just down to, like, three minutes. 00:20:01.020 --> 00:20:05.100 I want to make sure nothing runs longer than this. 00:20:05.100 --> 00:20:09.520 And just to make sure that the server doesn't just sit spinning all night long. 00:20:10.080 --> 00:20:16.180 And then, well, let's say you even tighten it closer to try to kill off a test if it's running longer than a certain amount. 00:20:16.180 --> 00:20:21.000 But there's, like, maybe two of your tests that are longer or a few of them that are longer. 00:20:21.000 --> 00:20:25.200 You can put a decorator on those particular tests and give them more time. 00:20:25.200 --> 00:20:27.000 And then the rest of them shorter. 00:20:27.520 --> 00:20:32.480 It's very easy to operate and just kind of a must-have for long test suites. 00:20:32.480 --> 00:20:33.380 Yeah, that's super cool. 00:20:33.380 --> 00:20:39.100 Yeah, I mean, sometimes you'd just rather have the test fail if it's taking way, way, way too long. 00:20:39.100 --> 00:20:41.820 And you're like, I'm pretty sure this is going to fail, but not right away. 00:20:41.920 --> 00:20:46.860 I would recommend just trying it out and kind of, like, look at the time of your tests and stuff. 00:20:46.860 --> 00:20:51.600 And then set it so that it actually kills one of your tests in the middle. 00:20:51.600 --> 00:20:54.360 Or stick a spin in there or something like that. 00:20:54.360 --> 00:20:55.920 Just to verify it does. 00:20:55.920 --> 00:20:58.020 Because it is sort of operating system dependent. 00:20:58.020 --> 00:21:05.960 And there's some configuration allowed in the plug-in to be able to use either signals or kill commands or process killing. 00:21:05.960 --> 00:21:10.980 There's different ways to stop a test that's going too long. 00:21:11.420 --> 00:21:13.780 So test it before you deploy it. 00:21:13.780 --> 00:21:15.040 But it's a good thing. 00:21:15.040 --> 00:21:15.820 Do a meta test. 00:21:15.820 --> 00:21:16.160 Yeah. 00:21:16.160 --> 00:21:17.480 Test of your test. 00:21:17.480 --> 00:21:17.900 Exactly. 00:21:17.900 --> 00:21:19.140 Super cool. 00:21:19.140 --> 00:21:20.220 Okay, that's a great one. 00:21:20.220 --> 00:21:22.720 And, you know, use case is super straightforward. 00:21:22.720 --> 00:21:26.280 I have got one for you that has got me really, really excited. 00:21:26.280 --> 00:21:27.520 It's called events. 00:21:27.520 --> 00:21:32.020 So in Python, we have functions as first class objects, right? 00:21:32.020 --> 00:21:35.620 You can pass a function around super easy, right? 00:21:35.620 --> 00:21:41.180 Like if there's some part of your program that's going to run and you want to get a function called when it's done, 00:21:41.180 --> 00:21:44.400 you can pass that function, it'll do its work, you can call it, right? 00:21:44.400 --> 00:21:48.300 You have this kind of observer style programming, right? 00:21:48.300 --> 00:21:48.560 Yeah. 00:21:48.560 --> 00:21:53.920 What requires programming on your behalf is to have that happen for more than one thing. 00:21:53.920 --> 00:22:03.240 Like I would like parts of my program to subscribe to being notified about events and one or more of them get called when this thing happens. 00:22:03.800 --> 00:22:10.400 So a friend of mine, Nicola Aroshi put together a really cool project called events. 00:22:10.920 --> 00:22:15.540 And the idea is that it adds event subscription and callback to the Python language. 00:22:15.540 --> 00:22:16.160 Oh, cool. 00:22:16.160 --> 00:22:17.560 In like a super simple way. 00:22:17.560 --> 00:22:20.500 So go to a function that is an event. 00:22:20.700 --> 00:22:32.000 If I want my function to be called by it, I would say like, like if I want the event on change, I would say my class dot on change plus equals some function to call. 00:22:32.000 --> 00:22:37.300 And if there's already one there, it's just going to add it to the list of all the functions that will be called when that event fires. 00:22:37.700 --> 00:22:47.000 And if at some point I decide I don't want to hear about it anymore, I just go to my class dot or my object dot on change minus equals the function I want to take out of that subscription list. 00:22:47.000 --> 00:22:48.040 And that's it. 00:22:48.040 --> 00:22:48.920 Oh, that's neat. 00:22:48.920 --> 00:22:49.560 Isn't that slick? 00:22:49.560 --> 00:22:56.500 And then to call it, you just say object dot on change and you pass the arguments and then all those functions get called in order. 00:22:56.500 --> 00:22:57.400 Oh, this is cool. 00:22:57.400 --> 00:22:57.720 Yeah. 00:22:57.720 --> 00:23:05.380 So it's if you have to do any sort of observer design pattern event subscription stuff like this is super, super nice. 00:23:05.520 --> 00:23:11.480 And it's inspired on the C# language base event keyword, which is based on delegates, basically function pointers. 00:23:11.480 --> 00:23:14.400 It doesn't really matter if you know about that or care about it. 00:23:14.400 --> 00:23:18.120 But if you know about the C# version, this basically brings that to the Python language. 00:23:18.120 --> 00:23:18.380 Yeah. 00:23:18.380 --> 00:23:21.640 I kind of want to build up a finite state machine using this. 00:23:21.640 --> 00:23:22.340 It's cool, right? 00:23:22.340 --> 00:23:22.800 Yeah. 00:23:22.800 --> 00:23:25.340 I mean, it could make it really readable. 00:23:25.340 --> 00:23:25.660 Yeah. 00:23:25.660 --> 00:23:29.540 I have a gist that I'm working on or I have some code I'm working on. 00:23:29.540 --> 00:23:35.100 I'll post as a gist that people can check out that is like a lot better than what they have in the documentation. 00:23:35.740 --> 00:23:40.880 So the documentation takes like this raw event source and shows you how you can subscribe and unsubscribe to it. 00:23:40.880 --> 00:23:44.880 But what I've got is something that's like here's how you have a class, right? 00:23:44.880 --> 00:23:47.040 Like, you know, a thing on the screen. 00:23:47.040 --> 00:23:52.820 And then you could have like subscribe to when the location changes or the size changes or, you know, those kinds of things. 00:23:52.820 --> 00:23:56.500 And it's more of like a natural programming analogy. 00:23:56.500 --> 00:23:57.820 So I'll put up the gist for that. 00:23:57.820 --> 00:24:01.020 I'm just working on a few things to see if I can make it even slightly better. 00:24:01.020 --> 00:24:08.320 I'm seeing if I can use descriptors so that the event triggering happens behind the scenes without you even have to program it as well. 00:24:08.320 --> 00:24:12.200 So like right now the from the outside using it is really easy. 00:24:12.200 --> 00:24:17.100 But you do have to sort of like know when something's changed and then call that raise that event. 00:24:17.100 --> 00:24:20.520 I think I can use descriptors to maybe make it seamless on both sides. 00:24:20.520 --> 00:24:21.880 But I'm still playing with that. 00:24:22.820 --> 00:24:29.440 Now, do you know if this if all of the events get called by the thing changing the making the event happen? 00:24:29.440 --> 00:24:29.800 Yes. 00:24:29.800 --> 00:24:30.080 They do? 00:24:30.080 --> 00:24:30.340 Yeah. 00:24:30.340 --> 00:24:30.560 Okay. 00:24:30.560 --> 00:24:30.780 Yeah. 00:24:30.780 --> 00:24:30.960 Yeah. 00:24:30.960 --> 00:24:35.680 So they get called by the thing that whatever decides to raise the event. 00:24:35.680 --> 00:24:37.900 That's the thing that's doing the calling. 00:24:37.900 --> 00:24:43.320 The events just basically manage what are the functions to be called in what order. 00:24:43.320 --> 00:24:46.560 And then like you call it and it just like delegates onto them. 00:24:46.560 --> 00:24:51.540 Also, you get to just arbitrarily pick the parameters that gets passed that get passed along. 00:24:51.940 --> 00:24:56.980 But it seems like a good idea to say this event always takes these kinds of arguments and whatever. 00:24:56.980 --> 00:24:58.960 There's not a lot of structure there. 00:24:58.960 --> 00:25:09.000 You do get the only real safety is you can say when you create it, you can say these are the only allowed events because it's kind of just full on dynamic programming. 00:25:09.000 --> 00:25:14.800 But you can say these three things you can subscribe and unsubscribe and call anything else. 00:25:14.800 --> 00:25:16.000 We're going to say it doesn't exist. 00:25:16.000 --> 00:25:17.460 So that's pretty nice. 00:25:17.460 --> 00:25:17.820 Yeah. 00:25:17.820 --> 00:25:18.380 Yeah. 00:25:18.380 --> 00:25:18.860 Yeah. 00:25:18.860 --> 00:25:19.760 It provides a little safety. 00:25:19.760 --> 00:25:20.040 Cool. 00:25:20.040 --> 00:25:20.380 Yeah. 00:25:20.620 --> 00:25:22.040 Well, that's our six items. 00:25:22.040 --> 00:25:23.660 Do you have any extras for us? 00:25:23.660 --> 00:25:24.200 Not really. 00:25:24.200 --> 00:25:25.660 Just I sort of talked about it. 00:25:25.660 --> 00:25:26.760 I was going to talk about it here. 00:25:26.760 --> 00:25:30.300 But I talked about it in the we talked about what we're doing, how people can support us. 00:25:30.300 --> 00:25:32.560 I finished the Python memory management course. 00:25:32.560 --> 00:25:34.000 The thing is so cool. 00:25:34.000 --> 00:25:39.360 It's a five hour course just diving into the internals of like Python memory management algorithms. 00:25:39.360 --> 00:25:44.740 And what I thought I would create was something that was like understanding Python memory management. 00:25:44.740 --> 00:25:54.020 But there's actually a ton of techniques I discovered that actually let you run your code in ways that are like, well, now it uses half as much memory and it's 30% faster and stuff like that. 00:25:54.020 --> 00:25:56.940 So I didn't think there would be a lot of actionable stuff coming out of it. 00:25:56.940 --> 00:25:59.680 But there is, which I think is pretty cool, actually. 00:25:59.680 --> 00:26:00.240 Oh, nice. 00:26:00.240 --> 00:26:00.560 Yeah. 00:26:00.560 --> 00:26:01.160 How about you? 00:26:01.160 --> 00:26:04.060 I'm pretty excited that pytest 6 is out. 00:26:04.060 --> 00:26:10.380 A couple weeks ago, we talked about the 6 being in sort of a beta release, but it's out now. 00:26:10.560 --> 00:26:16.820 And I wanted to mention that episode 125 of Testing Code walks through those changes. 00:26:16.820 --> 00:26:19.900 This is due to the miracles of time travel. 00:26:19.900 --> 00:26:25.160 This has not been recorded yet, but it will be recorded and released by last week. 00:26:25.160 --> 00:26:27.060 Perfect. 00:26:27.060 --> 00:26:28.160 Time travel. 00:26:28.160 --> 00:26:28.700 I love it. 00:26:28.700 --> 00:26:31.620 You've chosen the perfect joke. 00:26:31.620 --> 00:26:38.900 So the only question I have for you before we do the joke is, am I the school administrator IT person or am I the mom? 00:26:38.900 --> 00:26:40.120 Oh, you be the mom. 00:26:40.120 --> 00:26:40.560 Okay. 00:26:40.560 --> 00:26:40.960 Okay. 00:26:40.960 --> 00:26:41.920 So the phone rings. 00:26:41.920 --> 00:26:42.520 I pick it up. 00:26:42.520 --> 00:26:42.740 Yeah. 00:26:42.740 --> 00:26:44.620 Hi, this is your son's school. 00:26:44.620 --> 00:26:46.520 We're having some computer trouble. 00:26:46.520 --> 00:26:47.380 Oh, dear. 00:26:47.380 --> 00:26:48.680 Did he break something? 00:26:48.680 --> 00:26:49.460 In a way. 00:26:49.460 --> 00:26:52.560 Did you really name your son Robert? 00:26:52.560 --> 00:27:01.120 Robert single quote, parentheses, semicolon, drop table, students, semicolon, minus, minus? 00:27:01.120 --> 00:27:01.920 Oh, yes. 00:27:01.920 --> 00:27:03.400 Little Bobby Tables, we call them. 00:27:03.400 --> 00:27:05.960 Well, we've lost this year's student records. 00:27:05.960 --> 00:27:06.880 I hope you're happy. 00:27:06.880 --> 00:27:09.680 And I hope you've learned to sanitize your database inputs. 00:27:10.400 --> 00:27:12.300 Be on the lookout for that sequel injection, baby. 00:27:12.300 --> 00:27:14.580 I love it. 00:27:14.580 --> 00:27:15.420 This is so good. 00:27:15.420 --> 00:27:18.520 This is absolutely one of the most classic computer jokes there is. 00:27:18.520 --> 00:27:19.600 Yeah. 00:27:19.600 --> 00:27:20.340 I love it. 00:27:20.340 --> 00:27:22.500 Because it probably would actually work. 00:27:22.500 --> 00:27:32.240 It reminds me of the guy who said that he got his license plate to be the characters N-U-L-L, 00:27:32.240 --> 00:27:32.800 null. 00:27:32.800 --> 00:27:33.240 Yeah. 00:27:33.400 --> 00:27:34.240 I heard about that. 00:27:34.240 --> 00:27:34.540 Yeah. 00:27:34.540 --> 00:27:43.380 And he ended up getting all the like automated, you know, you drove through a traffic light sort of thing, tickets for all the records that were null. 00:27:43.380 --> 00:27:44.740 Yeah. 00:27:44.740 --> 00:27:46.580 Anytime they didn't have data, it went to him. 00:27:47.080 --> 00:27:51.080 Any police officer that forgot to enter the license plate, it would go to him. 00:27:53.080 --> 00:27:55.640 He thought he would get out of it because they wouldn't be able to send it to him. 00:27:55.640 --> 00:27:56.280 But oh, no. 00:27:56.280 --> 00:27:59.500 That's hilarious. 00:27:59.500 --> 00:28:00.080 Awesome. 00:28:00.080 --> 00:28:00.380 Awesome. 00:28:00.380 --> 00:28:01.220 All right. 00:28:01.220 --> 00:28:02.820 Well, great to chat with you as always. 00:28:02.820 --> 00:28:03.280 All right. 00:28:03.280 --> 00:28:03.700 You too. 00:28:03.700 --> 00:28:04.000 Bye. 00:28:04.000 --> 00:28:04.340 Bye. 00:28:04.800 --> 00:28:06.460 Thank you for listening to Python Bytes. 00:28:06.460 --> 00:28:08.920 Follow the show on Twitter at Python Bytes. 00:28:08.920 --> 00:28:11.960 That's Python Bytes as in B-Y-T-E-S. 00:28:11.960 --> 00:28:14.840 And get the full show notes at Python Bytes.fm. 00:28:14.840 --> 00:28:19.900 If you have a news item you want featured, just visit Python Bytes.fm and send it our way. 00:28:19.900 --> 00:28:21.960 We're always on the lookout for sharing something cool. 00:28:21.960 --> 00:28:23.120 This is Brian Okken. 00:28:23.120 --> 00:28:28.440 And on behalf of myself and Michael Kennedy, thank you for listening and sharing this podcast with your friends and colleagues. 00:28:28.440 --> 00:28:29.440 Thanks.