WEBVTT 00:00:00.080 --> 00:00:05.300 Hello and welcome to Python Bytes, where we deliver Python news and headlines directly to your earbuds. 00:00:05.300 --> 00:00:10.020 This is episode 46, recorded October 4th, 2017. I'm Michael Kennedy. 00:00:10.020 --> 00:00:10.900 And I'm Brian Okken. 00:00:10.900 --> 00:00:14.060 And we've got a bunch of cool stuff lined up for you, as always. 00:00:14.060 --> 00:00:16.880 But before we get to it, we have some kind of big news, Brian. 00:00:16.880 --> 00:00:17.280 We do. 00:00:17.280 --> 00:00:21.160 Yes, we have a new sponsor, a brand new sponsor for Python Bytes, 00:00:21.160 --> 00:00:24.100 who's come on to actually support a bunch of the show, DigitalOcean. 00:00:24.100 --> 00:00:24.840 Oh, that's awesome. 00:00:24.840 --> 00:00:28.740 Yeah, so they want to let you guys know about this thing called Spaces, 00:00:28.740 --> 00:00:30.740 which is kind of like S3, but 10 times better. 00:00:30.740 --> 00:00:34.220 And the audio you're listening to actually came to you over it. 00:00:34.220 --> 00:00:35.240 So we'll talk more about that later. 00:00:35.240 --> 00:00:36.840 I want to hear about spicy code. 00:00:36.840 --> 00:00:37.900 Spicy? Oh. 00:00:37.900 --> 00:00:40.640 I want to hear about SciPy lectures. 00:00:40.640 --> 00:00:42.760 I misread that, spicy SciPy. 00:00:42.760 --> 00:00:43.420 All the same. 00:00:43.420 --> 00:00:45.280 Yeah, it's all the same. 00:00:45.280 --> 00:00:47.320 You threw me off. 00:00:47.320 --> 00:00:49.460 I'm like, what story are you looking at, man? 00:00:49.460 --> 00:00:52.260 Anyway, SciPy lecture notes. 00:00:52.260 --> 00:00:57.260 I saw, I hadn't come across this before, but they did an update just recently to, 00:00:57.480 --> 00:01:00.780 it looks like they updated about once a year to make sure it's all current. 00:01:00.780 --> 00:01:05.500 You know, for somebody that's doing just-in-time learning for scientific Python usage, 00:01:05.500 --> 00:01:07.200 this is pretty darn cool. 00:01:07.200 --> 00:01:08.460 Their tagline is, 00:01:08.640 --> 00:01:12.040 one document to learn numerics, science, and data with Python. 00:01:12.040 --> 00:01:14.220 And it runs the gamut. 00:01:14.220 --> 00:01:18.020 It starts off with a Python language tutorial if you want to take it. 00:01:18.020 --> 00:01:21.480 You can learn about NumPy, Matplotlib, SciPy. 00:01:21.480 --> 00:01:24.340 It's got topics like debugging and optimizing, 00:01:24.340 --> 00:01:26.120 image manipulation, 00:01:26.520 --> 00:01:30.640 and things like how to deal with statistics and machine learning even. 00:01:30.640 --> 00:01:31.720 Yeah, this is really cool. 00:01:31.720 --> 00:01:35.840 I think a lot of people are getting into data science and getting into Python because of it. 00:01:35.840 --> 00:01:40.360 But also, I just think this is a great way to learn a lot of these techniques, right? 00:01:40.420 --> 00:01:42.540 These little short, focused, 00:01:42.540 --> 00:01:45.460 IPython notebook style of examples. 00:01:45.460 --> 00:01:49.420 Yeah, and for somebody that really needs to just jump in and find, 00:01:49.420 --> 00:01:50.660 the way they have it set up, 00:01:50.660 --> 00:01:53.640 it's almost like a table of contents for a book or a reference book. 00:01:53.900 --> 00:01:59.220 So you can just jump in and try to learn whatever you need today, just right away. 00:01:59.220 --> 00:02:01.860 You know what's cool about the JIT stuff is it has prerequisites. 00:02:01.860 --> 00:02:05.380 It says, like, for example, on the profiling part, 00:02:05.380 --> 00:02:08.600 it says a prerequisite is you must understand line profiler. 00:02:08.600 --> 00:02:09.200 Oh, okay. 00:02:09.200 --> 00:02:09.520 Yeah. 00:02:09.520 --> 00:02:10.420 It's pretty cool. 00:02:10.420 --> 00:02:14.760 I thought it was a great source for people that really aren't patient enough to go through a course 00:02:14.760 --> 00:02:16.460 or really don't know what they need to learn yet. 00:02:16.460 --> 00:02:16.840 What do you think? 00:02:16.840 --> 00:02:18.300 That's like 95% of people. 00:02:18.300 --> 00:02:21.140 Yeah, especially since, like we've talked about before, 00:02:21.140 --> 00:02:25.660 that Python is often a language that people pick up after their primary language. 00:02:25.660 --> 00:02:31.120 Yeah, well, and also I think we're increasingly asked and expected to build 00:02:31.120 --> 00:02:34.740 more and more complicated apps, bringing together more and more different disciplines. 00:02:34.740 --> 00:02:37.020 So would it be unreasonable to say, 00:02:37.020 --> 00:02:40.960 I would like you to write a web application that talks to the database, 00:02:40.960 --> 00:02:44.340 but also uses machine learning and the GPU? 00:02:44.340 --> 00:02:47.400 Like that I can see being a totally normal request now, 00:02:47.400 --> 00:02:49.380 whereas those used to be their own specialties, right? 00:02:49.380 --> 00:02:54.840 So this ability to jump in and pick up a little bit on demand is only going to be more required, I think. 00:02:54.840 --> 00:02:55.160 Yeah. 00:02:55.160 --> 00:03:00.900 And they also split up some of the Python stuff into like some of the beginner stuff 00:03:00.900 --> 00:03:03.120 that you just kind of have to know to start with, 00:03:03.120 --> 00:03:05.360 and then they have some more advanced things a little bit later. 00:03:05.360 --> 00:03:05.840 Yeah. 00:03:05.840 --> 00:03:06.760 Nice. 00:03:06.760 --> 00:03:11.540 So the first thing I want to talk about this week is desktop notifications. 00:03:12.060 --> 00:03:16.260 And this caught my eye because I feel like, I've said this a couple times, 00:03:16.260 --> 00:03:21.860 like one of the weaker points of Python is the whole desktop GUI type of thing, right? 00:03:21.860 --> 00:03:24.580 I know you can do it, but it's just not as easy as it should be. 00:03:24.580 --> 00:03:28.040 And so here's a real simple and easy way to build a notification, 00:03:28.040 --> 00:03:32.840 like a desktop toast type of notification for Linux using Python. 00:03:32.840 --> 00:03:34.000 Well, that's cool. 00:03:34.000 --> 00:03:34.620 Yeah. 00:03:34.620 --> 00:03:36.420 I don't know what you mean by toast. 00:03:36.680 --> 00:03:41.320 Well, so you're sitting there and there's like a little thing that pops out and say on Mac, 00:03:41.320 --> 00:03:43.820 it's in the top right and Windows, it's in the bottom right by the clock. 00:03:43.820 --> 00:03:47.180 It would pop up and say, your friend just liked your thing on Twitter, 00:03:47.180 --> 00:03:52.620 or somebody invited you to connect on LinkedIn, or your server just went down. 00:03:52.620 --> 00:03:54.260 Your boss is paging you. 00:03:54.260 --> 00:03:55.000 They're upset. 00:03:55.000 --> 00:03:57.200 You know, I finally get the toast reference. 00:03:57.200 --> 00:03:59.140 Because it pops up. 00:03:59.140 --> 00:04:00.560 At least in Windows, it pops up. 00:04:00.560 --> 00:04:04.820 I guess if you tilt your toaster on the right, then in macOS, it's also toast. 00:04:04.820 --> 00:04:05.340 I don't know. 00:04:06.360 --> 00:04:10.140 Anyway, here's an example, a little app that says, 00:04:10.140 --> 00:04:15.940 let's write a thing that will do web scraping, I guess, a Bitcoin value location. 00:04:15.940 --> 00:04:20.140 And it'll go to the website and pull that off and give you a periodic notification of the value of Bitcoin. 00:04:20.140 --> 00:04:22.400 While that's not super valuable, 00:04:22.400 --> 00:04:26.880 it does show you a really interesting use case of this package called notify2, 00:04:26.880 --> 00:04:32.180 which if you have something actually practical and interesting you want to notify people about, 00:04:32.180 --> 00:04:33.660 that's a pretty cool little use case. 00:04:33.660 --> 00:04:35.840 Actually, I think I might actually use this. 00:04:36.040 --> 00:04:36.680 This would be great. 00:04:36.680 --> 00:04:36.920 Cool. 00:04:36.920 --> 00:04:37.920 What would you do with it? 00:04:37.920 --> 00:04:39.960 For instance, we've got a bunch of remote machines. 00:04:39.960 --> 00:04:43.520 For me, I've got a bunch of VMs that are dealing with builds and whatever, 00:04:43.520 --> 00:04:46.500 and some way to keep track of them, make sure everything's alive. 00:04:46.500 --> 00:04:47.340 Yeah, that's cool. 00:04:47.340 --> 00:04:52.160 Like a build, pass, build, failed, machine, no longer responsive type of notifications. 00:04:52.480 --> 00:04:53.200 Yeah, that's awesome. 00:04:53.200 --> 00:04:54.360 That'd be really fun. 00:04:54.360 --> 00:04:57.180 It looks like a couple lines of code and you got it going. 00:04:57.180 --> 00:04:58.640 So that's really cool. 00:04:58.640 --> 00:05:05.280 Would you consider performance, like if your app becomes much slower after a check-in, 00:05:05.280 --> 00:05:08.460 like a performance degradation, like a failed build? 00:05:08.460 --> 00:05:09.480 Well, yeah, definitely. 00:05:10.180 --> 00:05:11.320 And how would you test for that? 00:05:11.320 --> 00:05:13.680 Well, funny you should ask. 00:05:14.560 --> 00:05:18.180 The next topic is a tool called pytest Benchmark. 00:05:18.180 --> 00:05:22.900 And this actually came up because, not because of, because I'm actually looking for this. 00:05:22.900 --> 00:05:28.020 I need to have chunks of functionality that we need to know whether or not we need to time them, 00:05:28.020 --> 00:05:32.080 make sure they're not getting slower with successive releases of the software. 00:05:32.780 --> 00:05:38.900 And what's interesting is the much slower or much faster or just very random timing, 00:05:38.900 --> 00:05:41.020 people might actually notice that. 00:05:41.020 --> 00:05:45.520 If you're dogfooding your own application and you're using it, you might notice this. 00:05:45.520 --> 00:05:51.160 It's the subtle things like a measurement is now, it used to be two seconds and now, 00:05:51.160 --> 00:05:54.620 and it was for like lots of releases and now it's two and a half seconds. 00:05:54.620 --> 00:05:59.880 Normal users might not, we're not, might not notice it right then, but it sure be good to check this. 00:05:59.880 --> 00:06:02.040 So this is a pytest Benchmark. 00:06:02.360 --> 00:06:04.340 And it's a very easy little thing. 00:06:04.340 --> 00:06:09.400 You can add into your code and your pytest testing to say, hey, this chunk of code, 00:06:09.400 --> 00:06:11.920 it needs to be at least this fast. 00:06:11.920 --> 00:06:14.660 And at first you don't know how fast it should be. 00:06:14.660 --> 00:06:19.860 So there's a lot of tools within it to do some graphing and table driven, 00:06:19.860 --> 00:06:21.960 showing you what the numbers are right now. 00:06:21.960 --> 00:06:29.420 And then also an ability to have a golden, some golden numbers and save off benchmark data into a JSON file. 00:06:29.860 --> 00:06:32.680 And then on future runs, compare against that. 00:06:32.680 --> 00:06:34.080 So I'm going to use it. 00:06:34.080 --> 00:06:34.320 Yeah. 00:06:34.320 --> 00:06:35.980 That looks super interesting, actually. 00:06:35.980 --> 00:06:39.340 And it has nice graphs over time and things like that. 00:06:39.340 --> 00:06:40.320 Yeah. 00:06:40.320 --> 00:06:41.900 I mean, sometimes timing doesn't matter. 00:06:42.060 --> 00:06:44.780 But other than like how users feel about it. 00:06:44.780 --> 00:06:49.700 But, you know, in certain types of real time systems or trading systems, there are actual numbers. 00:06:49.700 --> 00:06:50.920 You cannot fall below. 00:06:51.200 --> 00:06:56.480 If you're processing inbound data in real time and it's appearing every, you know, 100 milliseconds, 00:06:56.480 --> 00:07:00.120 you have to be lower than 100 milliseconds in the processing time, right? 00:07:00.120 --> 00:07:01.260 Or you won't be able to keep up. 00:07:01.260 --> 00:07:04.000 Often Python's used for other things too. 00:07:04.000 --> 00:07:08.080 Like I've heard that some people use it to control test instruments. 00:07:08.080 --> 00:07:09.200 Yes, that's possible. 00:07:09.700 --> 00:07:16.840 So, for instance, checking to make sure even application turn on and measurement times don't slow down. 00:07:16.840 --> 00:07:23.660 Because these instruments are used in production lines and it'll slow down your customer's production line if you slow down. 00:07:23.660 --> 00:07:24.480 Yeah, absolutely. 00:07:24.480 --> 00:07:27.040 All sorts of factory automation and all kinds of things. 00:07:27.040 --> 00:07:27.860 Cool. 00:07:27.860 --> 00:07:28.720 All right. 00:07:28.760 --> 00:07:29.700 So, that's really nice. 00:07:29.700 --> 00:07:32.480 I definitely, if I had a use case for that, I would definitely use it. 00:07:32.480 --> 00:07:36.140 I just don't have anything that I can say it must be this fast or it's a problem. 00:07:36.140 --> 00:07:39.220 But it still would be cool to actually see the speed over time. 00:07:39.220 --> 00:07:45.800 Now, before we get on to the next one, let me say thanks to DigitalOcean and just let you guys know about Spaces. 00:07:45.800 --> 00:07:48.720 So, you probably heard of Amazon S3, right? 00:07:48.720 --> 00:07:50.220 I think that was their first thing. 00:07:50.220 --> 00:07:56.080 But, like I said, DigitalOcean just released Spaces and I definitely think it's better. 00:07:56.620 --> 00:08:02.440 Soon as I heard about it, before they even said, hey, I want to sponsor the show and have you tell the world about it, I'm like, I'm switching to this thing. 00:08:02.440 --> 00:08:06.120 So, for one, it's like nine times cheaper than AWS. 00:08:06.120 --> 00:08:08.520 It's super predictable pricing. 00:08:08.520 --> 00:08:10.300 There's all kinds of benefits. 00:08:10.300 --> 00:08:14.580 You can use the same tools as you used to manage your S3 thing. 00:08:14.580 --> 00:08:16.200 So, same APIs and everything. 00:08:16.200 --> 00:08:21.640 So, for example, I use this cool program called Transmit for my Mac to manage all my files in S3. 00:08:21.640 --> 00:08:25.160 Just point it at DigitalOcean Spaces and it just keeps working. 00:08:25.160 --> 00:08:25.720 It's awesome. 00:08:25.820 --> 00:08:32.680 So, it's like $5 a month, 250 gigs for free in storage, a terabyte for free in bandwidth. 00:08:32.680 --> 00:08:39.200 That is quite expensive if you pay $0.09 per gigabyte at AWS. 00:08:39.200 --> 00:08:45.640 But it's completely free here and it's a really nice service just as fast but much more predictable. 00:08:45.640 --> 00:08:48.020 And even inbound data is 100% free. 00:08:48.020 --> 00:08:49.300 So, check them out. 00:08:49.380 --> 00:08:51.540 It's really a super simple API. 00:08:51.540 --> 00:08:53.720 It's one you're familiar with, the tools of work. 00:08:53.720 --> 00:09:01.580 And you can actually get, whether you're a new or existing customer, you get two months free if you just go to do.co slash Python. 00:09:01.760 --> 00:09:04.600 So, check it out. 00:09:04.600 --> 00:09:05.180 That's great. 00:09:05.180 --> 00:09:05.500 Cool. 00:09:05.500 --> 00:09:06.800 Yeah, it's a super cool project. 00:09:06.800 --> 00:09:11.700 I'm so happy they came out with it and I'm happy to be using it for this podcast and other stuff. 00:09:12.760 --> 00:09:23.620 So, we've talked, you've talked more than I have, but we've both talked a fair amount about projects, how they do packaging, Python packaging, how you should structure those and so on. 00:09:23.620 --> 00:09:34.680 So, I want to highlight an article that is, it's a fun article, but it's super in-depth and a deep look inside of how Python works and how packages are built and why they're built that way. 00:09:34.680 --> 00:09:40.020 It's an article by Vicky Boykus and it's called Alice in Python Project Land. 00:09:40.640 --> 00:09:48.820 So, it's got some cool little graphics and stuff, but the idea is like, she's a data scientist learning data science and those things. 00:09:48.820 --> 00:09:50.600 So, doing a lot of Java and doing a lot of Python. 00:09:50.600 --> 00:09:56.140 It's like, look, Python is so much better except for it's really hard to package up things. 00:09:56.140 --> 00:10:02.580 Like, how do I take some code that I've written and make it so that I could give it to you and you could use it, for example. 00:10:02.580 --> 00:10:10.360 So, instead of just going, well, these are the four steps you do to create a Python package, she says, let's look at the internals of how Python actually works. 00:10:10.360 --> 00:10:13.080 She said, how it runs, how it understands and links things together. 00:10:13.080 --> 00:10:17.860 And so, you not just know how to put things together, but you understand why. 00:10:17.860 --> 00:10:20.680 So, very, very interesting article. 00:10:20.680 --> 00:10:21.840 Pretty in-depth. 00:10:21.840 --> 00:10:25.040 So, packaging has always been kind of this weird thing that you just follow the steps. 00:10:25.040 --> 00:10:25.740 You can check this out. 00:10:25.740 --> 00:10:26.420 It's a good article. 00:10:26.420 --> 00:10:31.360 Like you said, it's in-depth, which makes it kind of a long article, but the writing is really good. 00:10:31.360 --> 00:10:33.280 So, it moves along pretty fast. 00:10:33.280 --> 00:10:34.400 Yeah, it sure does. 00:10:34.400 --> 00:10:34.880 It sure does. 00:10:34.880 --> 00:10:37.260 And it answers a lot of questions like, should you use setup tools? 00:10:37.260 --> 00:10:37.900 Should you use pip? 00:10:38.140 --> 00:10:41.660 What does __init__().py do? 00:10:41.660 --> 00:10:43.600 Should I mess with Python path? 00:10:43.600 --> 00:10:44.200 Should I not? 00:10:44.200 --> 00:10:47.400 And another thing that I saw that she referenced in there was pretty cool. 00:10:47.400 --> 00:10:48.480 It's called piprex. 00:10:48.480 --> 00:10:49.560 Have you seen this? 00:10:49.560 --> 00:10:49.920 No. 00:10:49.920 --> 00:10:50.220 Yeah. 00:10:50.220 --> 00:10:56.840 So, I think piprex, you pointed at your code and it looks at all your imports and it then knows what to create for your requirements.txt. 00:10:56.840 --> 00:10:57.220 Cool. 00:10:57.360 --> 00:11:04.500 So, instead of remembering like, oh yeah, there was that thing that I used, Colorama or whatever, and I forgot to put it in the requirements file, so it's not going to work. 00:11:04.500 --> 00:11:05.660 Like, this will just discover it. 00:11:05.660 --> 00:11:06.220 It's really cool. 00:11:06.220 --> 00:11:07.560 So, yep. 00:11:07.560 --> 00:11:15.680 If you want to get like an understanding of how Python packaging and assembly of modules at runtime works, definitely check out this article. 00:11:15.820 --> 00:11:17.700 It's super approachable, but well done. 00:11:17.700 --> 00:11:20.840 Next article, how to teach technical concepts with cartoons. 00:11:20.840 --> 00:11:22.440 Love technology. 00:11:22.440 --> 00:11:33.460 So, I personally, since I came from computer science, from the art, fine arts actually, I started out in fine arts, and I actually gave up because I was frustrated with my ability to draw. 00:11:33.460 --> 00:11:39.700 But drawing things to help people understand concepts, it's very, it helps. 00:11:39.700 --> 00:11:44.740 It's easier to understand things, and nobody expects you to draw really great pictures. 00:11:44.740 --> 00:11:50.980 This article starts off, I love this, it starts off with just saying that she draws not that great. 00:11:50.980 --> 00:11:54.740 It has really three horrible pictures of a dog, a cat, and an elephant. 00:11:54.740 --> 00:11:58.160 I don't think I can do better, but they're not great drawings. 00:11:58.160 --> 00:12:07.100 But just then going through and talking about how people should use drawings more when trying to teach things, and some tips on making them more personable. 00:12:07.100 --> 00:12:08.660 I think it's a really cool idea. 00:12:08.660 --> 00:12:14.540 You certainly can personalize and humanize technical concepts if you use pictures. 00:12:14.540 --> 00:12:20.000 Like you said, they don't have to be super fancy, so she has a dog, a cat, and an elephant, and those sorts of things. 00:12:20.180 --> 00:12:25.140 But you know, not far down, she says, oh, let's do something about a mutex. 00:12:25.140 --> 00:12:32.820 And actually represents how mutexes are used to like, for shared memory, or something like that, right? 00:12:32.820 --> 00:12:41.700 And it's completely approachable, but somehow it just makes it much more, if you looked at the formal definition of a mutex, like, oh my gosh, what is that thing? 00:12:41.760 --> 00:12:43.420 But here it's like, oh, okay, well, that's totally simple. 00:12:43.420 --> 00:12:49.680 I think you can really convey a lot and sort of disarm people with some nice drawings. 00:12:49.680 --> 00:13:00.000 One of the things I like about this article as well is it itself is a mix of hand lettering, just her normal printing, and some simple drawings with text. 00:13:00.000 --> 00:13:01.440 That's what the tutorial is. 00:13:01.440 --> 00:13:03.120 And it breaks it up a lot. 00:13:03.120 --> 00:13:13.120 And I think a lot of technical people, when they're trying to teach something, they'll think a drawing is a good idea, but then they'll get out a tool to make all the lines straight and draw it with vector graphics. 00:13:13.640 --> 00:13:17.940 And sometimes I think just a pen and paper might help convey the information better. 00:13:17.940 --> 00:13:18.960 Yeah, yeah, absolutely. 00:13:18.960 --> 00:13:23.860 I think this is really cool and hopefully inspire some people to do a little more freehand stuff. 00:13:23.860 --> 00:13:25.340 It doesn't always have to be perfect. 00:13:25.340 --> 00:13:30.080 So keeping it graphical for our last item, I want to share the Halo with you. 00:13:30.080 --> 00:13:37.700 So Halo is a project called Beautiful Terminal Spinners in Python, which is what it sounds like. 00:13:37.780 --> 00:13:46.460 It's a really simple library that will give you sort of I'm loading or I'm working or I'm thinking type of spinners and a lot of cool features. 00:13:46.460 --> 00:13:49.080 So you can have the little spinner go around and you have different styles. 00:13:49.080 --> 00:13:53.000 You have successful outcomes, failed outcomes. 00:13:53.000 --> 00:13:57.200 So like this little spinner will spin and then it'll go to like a check mark if it succeeds. 00:13:57.200 --> 00:14:01.660 Or if it fails, it'll go to like a cross and you could make it red or something like this, right? 00:14:01.660 --> 00:14:03.560 So that's really cool. 00:14:03.620 --> 00:14:07.020 We talked about progress bars where you have the progress going across. 00:14:07.020 --> 00:14:10.100 You know, I think one of the better ones is TQDM. 00:14:10.100 --> 00:14:14.220 Sometimes you don't know what the progress is going to be, right? 00:14:14.220 --> 00:14:17.220 Like I hate progress bars that go it's 5%, it's 5%. 00:14:17.220 --> 00:14:22.380 It's 90%, 91% and then it goes forever and then finally it's done, right? 00:14:22.380 --> 00:14:23.620 There's a great XKCD. 00:14:23.620 --> 00:14:25.060 I'll put it in the show notes. 00:14:25.060 --> 00:14:28.740 It's really fun about the guy who built the Windows progress bar, file copy progress bar. 00:14:28.740 --> 00:14:31.040 But sometimes progress bars aren't the answers. 00:14:31.040 --> 00:14:31.940 There are reasons why I'm bringing it up. 00:14:31.940 --> 00:14:35.320 But little spinners sort of solve that problem because it doesn't indicate progress. 00:14:35.320 --> 00:14:36.300 It's just like we're busy. 00:14:36.300 --> 00:14:40.820 And so here's a really cool way to put that into your program. 00:14:40.820 --> 00:14:43.360 It's very simple and it really looks nice too. 00:14:43.360 --> 00:14:43.980 Yeah, definitely. 00:14:43.980 --> 00:14:46.540 And it has a unicorn, a colorful unicorn. 00:14:46.540 --> 00:14:47.440 He doesn't want that. 00:14:47.440 --> 00:14:51.000 I'm not sure how the unicorn displays progress though. 00:14:51.000 --> 00:14:52.160 No, maybe in the horn. 00:14:52.160 --> 00:14:55.940 Oh, that would be cool if the horn had like colored. 00:14:55.940 --> 00:14:59.300 Yes, like the horn like flashed like rainbow. 00:14:59.300 --> 00:15:00.060 Yeah. 00:15:00.820 --> 00:15:03.200 I don't know if it does that or not, but it should. 00:15:03.200 --> 00:15:04.160 All right. 00:15:04.160 --> 00:15:06.940 But if you're looking to add some sort of user feedback like, hey, we're busy. 00:15:06.940 --> 00:15:07.780 We're not locked up. 00:15:07.780 --> 00:15:09.480 You know, Halo, super easy. 00:15:09.480 --> 00:15:10.020 Very cool. 00:15:10.020 --> 00:15:10.820 All right. 00:15:10.820 --> 00:15:12.320 That's it, Brian, for our topics. 00:15:12.320 --> 00:15:13.260 You got anything else? 00:15:13.260 --> 00:15:18.040 I don't think they would have made a full story, but I wanted to let people know that the Python, 00:15:18.040 --> 00:15:21.140 I think it's 363, is out now. 00:15:21.140 --> 00:15:22.480 So go upgrade. 00:15:22.480 --> 00:15:24.340 I don't know if there's anything major in it. 00:15:24.440 --> 00:15:26.400 I haven't looked through it, but it's around. 00:15:26.400 --> 00:15:28.060 So keeping current is good. 00:15:28.060 --> 00:15:32.060 And then there's also a bug fix release I noticed in pytest. 00:15:32.060 --> 00:15:32.700 That's around. 00:15:32.700 --> 00:15:36.740 I'm not sure what's in it, but again, it's around so people can pay attention. 00:15:36.740 --> 00:15:37.040 Yep. 00:15:37.040 --> 00:15:37.580 Okay. 00:15:37.580 --> 00:15:38.020 Very cool. 00:15:38.100 --> 00:15:39.520 So check those out. 00:15:39.520 --> 00:15:44.180 And the last thing I wanted to mention is I haven't been, I warned people that I was going 00:15:44.180 --> 00:15:46.620 to start podcasting again, but it took me a while. 00:15:46.620 --> 00:15:47.360 You warned them. 00:15:47.360 --> 00:15:47.780 Look out. 00:15:47.780 --> 00:15:48.360 I'm going to do it. 00:15:48.360 --> 00:15:48.720 Yeah. 00:15:48.720 --> 00:15:49.560 There are a couple. 00:15:49.560 --> 00:15:54.780 So at the end of September and just a couple of days ago, I released a couple different test 00:15:54.780 --> 00:15:56.020 and code episodes. 00:15:56.020 --> 00:15:58.080 One of them related to the testing pyramid. 00:15:58.080 --> 00:16:02.360 And the last one, 32, is an excellent one by an amazing speaker. 00:16:02.360 --> 00:16:05.140 It's with an amazing speaker named David Hussman. 00:16:05.140 --> 00:16:07.240 And he's a brilliant man. 00:16:07.240 --> 00:16:07.440 Yeah. 00:16:07.460 --> 00:16:08.060 That's really cool. 00:16:08.060 --> 00:16:09.340 And I'm glad you got that one out. 00:16:09.340 --> 00:16:09.720 That's awesome. 00:16:09.720 --> 00:16:10.260 How about you? 00:16:10.260 --> 00:16:11.180 Anything new going on? 00:16:11.180 --> 00:16:12.320 No, nothing new. 00:16:12.320 --> 00:16:16.380 I'm working on my courses like crazy, but the announcement's going to have to wait until 00:16:16.380 --> 00:16:20.140 next week for anything to be actually out for anyone to check out. 00:16:20.140 --> 00:16:21.620 Well, thanks a lot for doing this today. 00:16:21.620 --> 00:16:22.080 You bet. 00:16:22.080 --> 00:16:24.980 It was great to catch up with you and share all these ideas with everyone. 00:16:24.980 --> 00:16:25.740 Catch you later. 00:16:25.740 --> 00:16:28.340 Thank you for listening to Python Bytes. 00:16:28.340 --> 00:16:30.900 Follow the show on Twitter via at Python Bytes. 00:16:30.900 --> 00:16:33.800 That's Python Bytes as in B-Y-T-E-S. 00:16:33.800 --> 00:16:36.700 And get the full show notes at pythonbytes.fm. 00:16:36.820 --> 00:16:41.560 If you have a news item you want featured, just visit pythonbytes.fm and send it our way. 00:16:41.560 --> 00:16:44.260 We're always on the lookout for sharing something cool. 00:16:44.260 --> 00:16:47.660 On behalf of myself and Brian Okken, this is Michael Kennedy. 00:16:47.660 --> 00:16:51.260 Thank you for listening and sharing this podcast with your friends and colleagues.