WEBVTT 00:00:00.001 --> 00:00:05.100 Hello and welcome to Python Bytes, where we deliver Python news and headlines directly to your earbuds. 00:00:05.100 --> 00:00:09.720 This is episode 136, recorded June 19, 2019. 00:00:09.720 --> 00:00:10.640 I'm Michael Kennedy. 00:00:10.640 --> 00:00:11.400 And I'm Brian Okken. 00:00:11.400 --> 00:00:13.220 And this episode is brought to you by Datadog. 00:00:13.220 --> 00:00:15.700 Check them out at pythonbytes.fm/datadog. 00:00:15.700 --> 00:00:16.500 Get a cool shirt. 00:00:16.500 --> 00:00:17.380 More on that later. 00:00:17.380 --> 00:00:18.100 Brian, how you been? 00:00:18.100 --> 00:00:19.480 I am doing well. 00:00:19.480 --> 00:00:20.060 Good, good. 00:00:20.060 --> 00:00:21.000 Same here. 00:00:21.000 --> 00:00:22.420 Rolling into summer. 00:00:22.420 --> 00:00:23.420 Kids are home. 00:00:23.420 --> 00:00:26.280 Working from home is now chaos, but it's all right. 00:00:26.280 --> 00:00:26.680 Yeah. 00:00:26.680 --> 00:00:28.360 It's a little cooler today, too. 00:00:28.360 --> 00:00:28.760 It's nice. 00:00:28.760 --> 00:00:29.460 Yeah, it's beautiful. 00:00:30.040 --> 00:00:33.060 So you've got some kind of magic trick lined up for us for this first thing? 00:00:33.060 --> 00:00:33.900 What's going on here? 00:00:33.900 --> 00:00:39.220 Well, actually, I think it's just going to be me trying to pronounce a French word. 00:00:39.220 --> 00:00:42.640 So I think, is it, I know it's not voila. 00:00:42.640 --> 00:00:43.680 Voila? 00:00:43.680 --> 00:00:44.400 Voila? 00:00:44.400 --> 00:00:45.600 Do you pronounce the V? 00:00:45.600 --> 00:00:46.100 I don't know. 00:00:46.100 --> 00:00:46.400 Voila. 00:00:46.400 --> 00:00:47.380 I think so. 00:00:47.380 --> 00:00:47.680 Voila? 00:00:47.680 --> 00:00:48.320 Viola. 00:00:48.320 --> 00:00:48.780 No. 00:00:48.780 --> 00:00:49.780 No. 00:00:49.780 --> 00:00:53.060 Voila is a new project. 00:00:53.060 --> 00:00:56.760 It's a newly announced project from the Jupyter Notebook people. 00:00:56.760 --> 00:00:57.100 Cool. 00:00:57.100 --> 00:01:01.960 So the idea is Jupyter Notebooks in standalone applications or dashboards. 00:01:01.960 --> 00:01:16.500 So people that are used to working with notebooks and they want to share what they found with other people and you want to have people be able to interact with it and have it be a little bit interactive, but not allow people to change your code. 00:01:16.700 --> 00:01:17.720 How do you do that? 00:01:17.720 --> 00:01:20.160 That's where Voila steps in. 00:01:20.160 --> 00:01:22.120 It's a pretty cool project. 00:01:22.120 --> 00:01:24.320 I was playing around with it a little bit. 00:01:24.320 --> 00:01:32.180 You can have custom, or at least reading about it, custom widgets to set up your page and even like templates and grid layouts. 00:01:32.180 --> 00:01:33.800 But you don't have to be a web developer. 00:01:33.800 --> 00:01:35.140 It's like drag and drop stuff. 00:01:35.140 --> 00:01:35.580 This is cool. 00:01:35.580 --> 00:01:48.880 I like the idea of presenting the interactive plots and graphs and stuff and also being able to have people be able to run the code and do selectors and things, but not let people change the code. 00:01:48.880 --> 00:01:50.040 So that's pretty cool. 00:01:50.040 --> 00:01:50.280 Yeah. 00:01:50.280 --> 00:01:53.440 You just take your notebook and you just turn it into a web application. 00:01:53.440 --> 00:01:54.440 That's pretty awesome. 00:01:54.440 --> 00:02:01.860 And it has nice restrictions like does not permit execution of arbitrary code by consumers of the dashboard. 00:02:01.860 --> 00:02:03.140 It's language agnostic. 00:02:03.140 --> 00:02:07.960 So you could have C++ code up there in addition to Python or whatever, you know, Jupyter does. 00:02:07.960 --> 00:02:08.600 That's pretty sweet. 00:02:08.600 --> 00:02:08.840 Yeah. 00:02:08.840 --> 00:02:14.140 I could see a lot of people using this, even for dashboards for like peeking into databases and stuff. 00:02:14.140 --> 00:02:14.460 Nice. 00:02:14.460 --> 00:02:16.420 So Voila, and you have a website. 00:02:16.420 --> 00:02:16.820 Voila. 00:02:16.820 --> 00:02:20.680 I have a Jupyter notebook and here it is. 00:02:20.680 --> 00:02:20.900 Cool. 00:02:20.900 --> 00:02:21.720 Awesome. 00:02:22.720 --> 00:02:24.840 I don't think we covered this. 00:02:24.840 --> 00:02:38.960 I kind of tried to sort of intentionally didn't want to go too far into it because it didn't seem super productive, but there was a presentation back at the language summit called Python, something like cleaning up Python's dead batteries or something to that effect. 00:02:38.960 --> 00:02:39.960 Did you catch that? 00:02:39.960 --> 00:02:40.180 Yeah. 00:02:40.180 --> 00:02:45.520 So the idea was there are some modules and parts of Python that are outdated. 00:02:46.100 --> 00:02:53.780 Their existence puts pressure on the core developers in ways that doesn't let them focus on what they need to be doing. 00:02:53.780 --> 00:02:56.520 It also makes it super hard for people to contribute. 00:02:56.520 --> 00:03:01.460 Like, for example, there's a color sys module in Python in the standard library. 00:03:01.460 --> 00:03:04.260 I'm going to pick on this thing a lot during this little segment. 00:03:04.260 --> 00:03:11.480 And it has the very important purpose of converting CSS colors between coordinate systems. 00:03:12.320 --> 00:03:15.820 Super important to have that in the standard library, right? 00:03:15.820 --> 00:03:17.040 I don't know. 00:03:17.040 --> 00:03:18.700 Maybe, maybe not. 00:03:18.700 --> 00:03:30.380 At one point, you know, Python standard library was really the goal of it was to come with everything you need because installing extra stuff like downloading it, getting it, like running the setup and all that was really tricky. 00:03:30.380 --> 00:03:31.240 Right? 00:03:31.300 --> 00:03:33.960 Now everything's pip install one away. 00:03:33.960 --> 00:03:36.580 So, like, it looks a little bit weird. 00:03:36.580 --> 00:03:43.080 And if, say, you wanted to fix or change the color sys module, it's not the same as if you want to go contribute to some random thing on GitHub. 00:03:43.080 --> 00:03:44.620 No, you've got to be a core developer. 00:03:44.620 --> 00:03:47.220 There's a lot of steps that go through this. 00:03:47.220 --> 00:03:53.140 It only ships every 16 months, or sorry, 18 months for new content and new things, changes. 00:03:53.780 --> 00:03:57.760 So, how much do you really care to make a contribution or change to color sys? 00:03:57.760 --> 00:03:58.180 Right? 00:03:58.180 --> 00:04:00.600 Probably not very much for all those reasons, right? 00:04:00.600 --> 00:04:01.620 It's slow on purpose. 00:04:01.620 --> 00:04:04.760 It's hard to make changes to and so on. 00:04:04.760 --> 00:04:10.300 But the problem is, like, it has things like color sys that probably don't make a lot of sense to be there anymore. 00:04:10.300 --> 00:04:17.920 So, Amber Brown and some other folks were making a case that maybe we should take some stuff away. 00:04:17.920 --> 00:04:19.180 And it was pretty controversial. 00:04:19.180 --> 00:04:23.340 There was some, like, heated disagreements at the actual presentation and stuff. 00:04:23.340 --> 00:04:24.440 And I don't care about that. 00:04:24.440 --> 00:04:25.180 I don't want to go into it. 00:04:25.180 --> 00:04:30.900 But that approach was, we have stuff in Python that maybe shouldn't be there. 00:04:30.900 --> 00:04:33.240 Let's talk about what we can take out. 00:04:33.240 --> 00:04:39.700 And Glyph wrote a cool article called Toward a Kernel Python. 00:04:40.040 --> 00:04:41.660 And I've talked about this before. 00:04:41.660 --> 00:04:44.680 I don't know if I talked about it on Python Bytes or on Talk Python. 00:04:44.680 --> 00:04:55.420 But I think there should be some kind of subset of Python that is defined to be, like, the minimum subset of Python that is guaranteed to be everywhere. 00:04:55.420 --> 00:05:01.740 So, for example, if you work with PyPy, you get one variant of mostly Python. 00:05:01.740 --> 00:05:07.860 If you work with CircuitPython or MicroPython, you get another variant of mostly Python, but not all of it, right? 00:05:07.860 --> 00:05:08.140 Yeah. 00:05:08.220 --> 00:05:16.860 If you work with Python or some of the JavaScript versions that run in the browsers, again, similar subset but not the same. 00:05:17.180 --> 00:05:31.840 So, if we had, like, a smaller sort of essential Python standard language definition and library that was, like, I don't know what's the right number, but a smaller amount that you could guarantee was identical across all those platforms. 00:05:32.220 --> 00:05:34.540 And then opt in to bringing the other stuff in. 00:05:34.540 --> 00:05:44.220 So, Glyph's main idea was, like, could we say, instead of, like, take what we have and hack away a few things that don't make sense, rather trim it down to this kernel, to this essence. 00:05:45.180 --> 00:05:51.260 And then, I don't know, pip install the rest of the libraries or something like that, the rest of the standard library. 00:05:51.260 --> 00:05:53.740 You want the networking stack, you pip install networking. 00:05:53.740 --> 00:05:54.160 I don't know. 00:05:54.160 --> 00:05:56.680 Like, I'm just making up parts that we would do that for. 00:05:57.500 --> 00:06:05.200 But that was his idea, that basically there's a PEP, PEP594, that's about removing, obviously, obsolete and dead stuff from the standard library. 00:06:05.200 --> 00:06:06.900 And that's all well and good. 00:06:07.240 --> 00:06:16.880 But it actually turns out that having things like ColorSys in the standard library mean that the core devs have to deal with a bunch of stuff. 00:06:16.880 --> 00:06:18.460 So, he runs Twisted. 00:06:18.460 --> 00:06:21.440 So, he talks about, like, how is Twisted doing on keeping up with PRs? 00:06:21.440 --> 00:06:23.700 And let's look at CPython over there. 00:06:23.700 --> 00:06:29.020 And they have 429 tickets currently awaiting review over on GitHub. 00:06:29.020 --> 00:06:30.200 I think it's in GitHub. 00:06:30.860 --> 00:06:36.820 It says the oldest PR awaiting review hasn't been touched since February 2nd, 2018. 00:06:36.820 --> 00:06:38.980 It's almost 500 days old. 00:06:38.980 --> 00:06:46.280 But when you look at it, the PRs, there's 25 PRs that are out on address or whatever. 00:06:46.280 --> 00:06:49.900 14 were about the standard library and 10 were about CPython. 00:06:49.900 --> 00:06:54.920 So, why are the core devs having to deal with this stuff when there's typically a replacement? 00:06:54.920 --> 00:06:59.920 Like, there is a built-in HTTP library, but people just use requests or AIOHTP or whatever, right? 00:07:00.320 --> 00:07:05.920 Like, there should be a way to maybe create this essence of it and then bring more in. 00:07:05.920 --> 00:07:06.620 What do you think? 00:07:06.620 --> 00:07:08.700 I definitely think there's an idea there. 00:07:08.700 --> 00:07:12.040 Like you said, there's kind of like a Venn diagram. 00:07:12.040 --> 00:07:17.900 There's a common set that most people need or you'll need for lots of different domains. 00:07:17.900 --> 00:07:28.360 But then for a web domain, for web stuff, you're going to need different stuff than for, like, working with audio files or working with text files. 00:07:28.560 --> 00:07:33.640 Or the different problem domains are going to use different bits and you don't need everything else. 00:07:33.640 --> 00:07:33.920 Yeah. 00:07:33.920 --> 00:07:34.840 Interesting idea. 00:07:34.840 --> 00:07:42.680 The install, the how do beginners install stuff is an interesting, how do you deal with that, though? 00:07:42.680 --> 00:07:43.520 Yeah, absolutely. 00:07:43.520 --> 00:07:44.700 And he does address that. 00:07:44.700 --> 00:07:46.660 And I do think it is a challenge. 00:07:47.020 --> 00:07:57.400 He says, look, probably the stuff you go get when you download off python.org or you brew install Python, that probably should just be everything, right? 00:07:57.400 --> 00:08:04.380 But it doesn't mean that it can't be comprised of smaller things that potentially ship on a different schedule. 00:08:04.380 --> 00:08:11.240 If you're going to install, like, Visual Studio or something like that, you always have options of, do you want to install this stuff and this other stuff also? 00:08:11.240 --> 00:08:11.580 Yeah. 00:08:11.580 --> 00:08:12.600 You can opt out. 00:08:12.600 --> 00:08:18.080 And we could do something similar to that with Python of, like, do you want to install the web stuff? 00:08:18.080 --> 00:08:21.060 Do you want to install the audio stuff and whatever? 00:08:21.060 --> 00:08:21.460 Right. 00:08:21.700 --> 00:08:24.740 You could have these full distributions that you install. 00:08:24.740 --> 00:08:33.600 But if you look at, say, Linux, for example, if you go to an empty Ubuntu machine and you try to create a virtual environment, depending on the version you have, it may not work. 00:08:33.600 --> 00:08:39.640 You may get an error that says, you need to apt install Python 3-venv. 00:08:39.640 --> 00:08:42.160 It's like, wait, that part of Python wasn't shipped? 00:08:42.160 --> 00:08:43.220 Okay, well, we'll do that. 00:08:43.220 --> 00:08:49.520 Or if you try to even pip install something, it might say, you might have to apt install Python 3-pip, right? 00:08:49.520 --> 00:08:51.280 So they've already done this on Linux. 00:08:51.280 --> 00:08:53.380 There's other examples as well. 00:08:53.380 --> 00:08:59.640 For example, the .NET Core in the Microsoft space basically is like this, right? 00:08:59.640 --> 00:09:06.560 Like, you use their package management system to bring in, like, significant parts of what is their standard library. 00:09:06.560 --> 00:09:06.960 Yeah. 00:09:06.960 --> 00:09:08.480 I do think it's a problem for beginners. 00:09:08.480 --> 00:09:10.300 I think it makes it harder, right? 00:09:10.300 --> 00:09:14.620 It's like saying, well, we just run JavaScript over in Node and it's easy. 00:09:14.620 --> 00:09:17.720 But then you see all this require.js and all these, like, patterns. 00:09:17.720 --> 00:09:19.100 You're like, why is this so hard? 00:09:19.100 --> 00:09:20.680 What happened to print hello world? 00:09:20.680 --> 00:09:22.820 You know, like, I do think there's a danger. 00:09:22.820 --> 00:09:34.560 But if the standard way that people get Python is they get this big bundle, but maybe those bundles are not all maintained by the same team, which is the core developers, right? 00:09:34.620 --> 00:09:50.180 And then, like, what can we hack out of the system? 00:09:50.180 --> 00:09:52.040 Could we hack out ColorSys? 00:09:52.040 --> 00:09:52.780 Yes or no? 00:09:52.780 --> 00:09:53.540 Let's talk about that. 00:09:53.640 --> 00:09:53.900 Well, right. 00:09:53.900 --> 00:09:58.500 And also, just there's some stuff, like ColorSys, it's surprising that it needs to be there. 00:09:58.500 --> 00:10:03.900 And then there's stuff that's not in the core or in the standard library that, like, why is that not there? 00:10:03.900 --> 00:10:05.580 Like, set up tools and wheel. 00:10:05.580 --> 00:10:09.220 I'm always surprised that I have to pip install wheel to create a wheel. 00:10:09.320 --> 00:10:14.560 Yeah, and speaking of pip, Cliff did mention that when you get Python, it comes with pip. 00:10:14.560 --> 00:10:17.560 Like, installing Python lets you type pip install a thing. 00:10:17.560 --> 00:10:22.300 But pip is actually maintained by a different group and shipped on a different cycle, right? 00:10:22.300 --> 00:10:25.060 That's PyPA, not the core developers, for example. 00:10:25.180 --> 00:10:26.680 So, it's like that a little bit. 00:10:26.680 --> 00:10:29.540 But if it was more like that, you could make a change. 00:10:29.540 --> 00:10:40.120 You could join the team for, I don't know, the networking or ColorSys or whatever you want, work on that, and maybe push changes more rapidly than the core CPython runtime. 00:10:40.120 --> 00:10:40.640 Right. 00:10:40.640 --> 00:10:46.200 We could do something like the PyPA, but do, like, the Python standard library authority or something like that. 00:10:46.200 --> 00:10:46.800 Yeah, exactly. 00:10:46.800 --> 00:10:54.980 It's a pretty interesting idea, and it definitely seems better than, seems more like the outcome will be better than trying to just hack away at a few dead batteries. 00:10:54.980 --> 00:10:55.600 If you will. 00:10:55.600 --> 00:10:55.860 Yep. 00:10:55.860 --> 00:10:56.060 Cool. 00:10:56.060 --> 00:11:00.120 This next one that you're talking about, I recently ran into this as an error. 00:11:00.120 --> 00:11:01.420 I'm like, wait, what did I type wrong? 00:11:01.420 --> 00:11:03.860 And then I realized, this might be a cool feature. 00:11:03.860 --> 00:11:05.100 Why don't you tell people about this? 00:11:05.100 --> 00:11:09.680 Like, for instance, with pytest, it comes as a standalone script. 00:11:09.680 --> 00:11:12.520 You can say, you can just write pytest on the command line. 00:11:12.520 --> 00:11:16.140 But you can also say Python-M pytest. 00:11:16.140 --> 00:11:19.100 And a lot of pip installable things, you can do that. 00:11:19.100 --> 00:11:23.400 You can say –M, the thing name, and it works. 00:11:23.740 --> 00:11:25.680 I didn't know how to do this, actually. 00:11:25.680 --> 00:11:28.560 I never really thought, how do I do this, and how do I figure it out? 00:11:28.560 --> 00:11:32.920 And all it is to put a Dunder main file in your project. 00:11:32.920 --> 00:11:34.620 I didn't know it was that easy. 00:11:34.620 --> 00:11:44.220 So I'm linking to an article that pretty much says, we use the convention of if Dunder name equals Dunder main, then run the main program or something. 00:11:44.480 --> 00:11:49.460 But you can use the Dunder main.py file itself in your project. 00:11:49.460 --> 00:11:52.300 And that dash M thing just works. 00:11:52.300 --> 00:11:53.400 And that's pretty simple, right? 00:11:53.400 --> 00:11:55.140 I'm like, it can't really be that easy. 00:11:55.140 --> 00:11:59.660 So this morning, I did a little flip project, a flip-based project. 00:11:59.660 --> 00:12:06.440 And then threw a Dunder main in there with just a print statement and installed it and went somewhere else. 00:12:06.440 --> 00:12:08.540 And sure enough, it works just awesome. 00:12:08.540 --> 00:12:09.440 So neat. 00:12:09.440 --> 00:12:10.240 Yeah, that's super cool. 00:12:10.240 --> 00:12:17.780 Yeah, I ran across this by accidentally saying Python and saying run a directory instead of a file. 00:12:18.260 --> 00:12:21.100 I'm like, oh, it said it couldn't find Dunder main. 00:12:21.100 --> 00:12:22.240 I'm like, .py. 00:12:22.240 --> 00:12:24.820 I'm like, wait, it was looking for it? 00:12:24.820 --> 00:12:25.480 That's pretty cool. 00:12:25.480 --> 00:12:26.600 Maybe there's something to be done here. 00:12:26.600 --> 00:12:27.060 Yeah, that's great. 00:12:27.060 --> 00:12:27.860 I'm glad you pointed it out. 00:12:27.860 --> 00:12:33.840 If you have a Dunder main in there, you can just say Python and the directory name and it works? 00:12:33.840 --> 00:12:39.220 I have not verified that, but it seems like the error message would indicate that it might work. 00:12:39.220 --> 00:12:40.480 Yeah, I mean, it was like a full path. 00:12:40.480 --> 00:12:42.660 It wasn't just a standard directory either. 00:12:42.660 --> 00:12:43.260 Okay. 00:12:43.260 --> 00:12:44.600 Yeah, so pretty cool. 00:12:44.600 --> 00:12:44.880 Neat. 00:12:44.880 --> 00:12:46.540 I don't know how useful it is to people, 00:12:46.720 --> 00:12:48.920 but I'll run across it every once in a while. 00:12:48.920 --> 00:12:51.000 Yeah, that and entry points always really nice. 00:12:51.000 --> 00:12:55.040 Now, speaking of nice, Diddy Dog is supporting our show and they got some nice products. 00:12:55.040 --> 00:12:56.620 So let me tell you about them really quickly. 00:12:56.620 --> 00:13:03.740 And so they're a cloud scale monitoring platform that unifies metrics, logs, traces, all that kind of stuff. 00:13:03.740 --> 00:13:06.720 Monitors your Python apps in real time. 00:13:06.720 --> 00:13:13.860 Helps you find bottlenecks with detailed flame graphs, trace requests as they cross over service boundaries. 00:13:13.860 --> 00:13:14.600 All right. 00:13:14.600 --> 00:13:17.960 So if you have microservices, you're talking to database or queuing, things like that. 00:13:17.960 --> 00:13:25.280 Plus, it also does automatic instrumentation for popular frameworks like Django, AsyncIO, and Flask. 00:13:25.280 --> 00:13:27.540 So you can quickly get started without too much setup. 00:13:27.540 --> 00:13:29.600 So get started today. 00:13:29.600 --> 00:13:33.340 There's a 14-day free trial at pythonbytes.fm/datadog. 00:13:33.440 --> 00:13:36.180 And you get a cool Datadog t-shirt, which is always fun. 00:13:36.180 --> 00:13:37.060 Thanks for that, Dom. 00:13:37.060 --> 00:13:38.620 Mine's a nice purple color. 00:13:38.620 --> 00:13:40.560 And my kids always comment when I wear it. 00:13:40.560 --> 00:13:41.600 They like the shirt. 00:13:41.600 --> 00:13:42.140 Yeah, I love it. 00:13:42.140 --> 00:13:47.460 So this next one I want to talk about, the name might sound a little derogatory, but it's not really meant that way. 00:13:47.460 --> 00:13:50.240 So maybe simplistic sounds better. 00:13:50.340 --> 00:13:56.420 But the thing I want to talk about is this article by Chris Wellens entitled, The CPython Byte Compiler is Dumb. 00:13:56.420 --> 00:13:59.200 Simplistic is maybe better. 00:13:59.200 --> 00:14:11.140 But what you might not know, depending on how much you dig into it, is there's excruciatingly small amounts of optimization when CPython runs your code. 00:14:11.220 --> 00:14:14.120 So there's a compilation step, actually, right? 00:14:14.120 --> 00:14:16.480 The bytecode and compiler talks about some kind of compilation. 00:14:16.480 --> 00:14:20.860 So when you run your code, you probably see the __pycache__ folders. 00:14:20.860 --> 00:14:22.460 And in there you have the PYC files. 00:14:22.460 --> 00:14:25.760 So that's taking your source code, turn it into bytecode, and put it there. 00:14:25.760 --> 00:14:37.080 But then instead of, say, compiling that onto machine instructions, the interpreter takes that, feeds it through this ginormous switch statement that's like 3,000 lines long in the CPython runtime. 00:14:37.080 --> 00:14:39.620 And it just goes, well, what case is this? 00:14:39.620 --> 00:14:40.800 We're jumping to that, right? 00:14:40.800 --> 00:14:41.600 It's pretty wild. 00:14:41.600 --> 00:14:43.060 There's a file called cval.c. 00:14:43.060 --> 00:14:43.680 Check it out. 00:14:43.680 --> 00:14:48.060 However, there's very little optimization that happens here. 00:14:48.060 --> 00:14:53.300 So Chris decided to compare this against Lua and one other similar, maybe Ruby. 00:14:53.300 --> 00:14:55.820 I can't remember what the other one that he compared it against was. 00:14:55.820 --> 00:15:00.200 But he talked about, you know, like, if I write this code, what happens to it? 00:15:00.200 --> 00:15:07.360 So there are optimizations like what are called peephole optimizations and a few memory allocation optimizations in CPython. 00:15:07.360 --> 00:15:09.640 But they're pretty limited. 00:15:10.380 --> 00:15:16.440 So if you look at some examples, like let's take an example where we have a function. 00:15:16.440 --> 00:15:17.340 It's called foo. 00:15:17.340 --> 00:15:18.780 Defines two variables. 00:15:18.780 --> 00:15:19.840 X equals zero. 00:15:19.840 --> 00:15:21.180 Y equals one. 00:15:21.180 --> 00:15:22.480 Return X. 00:15:22.480 --> 00:15:23.720 That seems simple, right, Brian? 00:15:23.720 --> 00:15:24.040 Yeah. 00:15:24.040 --> 00:15:25.440 Except for Y is not needed. 00:15:25.440 --> 00:15:26.180 But yeah, sure. 00:15:26.300 --> 00:15:26.620 Exactly. 00:15:26.620 --> 00:15:38.640 So when you see that, if Y is unused and this is not making any change, it's just literally creating a variable which is effectively an entry in, you know, like a module name lookup or a locals lookup, right? 00:15:38.700 --> 00:15:40.500 Like, why does that need to be done? 00:15:41.440 --> 00:15:43.060 Doesn't seem like a whole lot's happening. 00:15:43.060 --> 00:15:47.860 So for example, the CPython bytecode compiler could just go, well, forget that line. 00:15:48.000 --> 00:15:51.220 And it could say, well, X never changes its value. 00:15:51.220 --> 00:15:58.680 So why don't we just inline that to say, basically, the whole function is return zero, right? 00:15:58.680 --> 00:16:00.300 Inline the X, drop the Y. 00:16:00.300 --> 00:16:01.260 It's good to go. 00:16:01.660 --> 00:16:07.160 But if you go and throw that into the disassembler, you'll see that, no, that's not what happens. 00:16:07.160 --> 00:16:10.260 It literally just takes it step by step by step. 00:16:10.260 --> 00:16:10.540 Okay. 00:16:10.540 --> 00:16:11.100 Wild, right? 00:16:11.100 --> 00:16:12.500 So it loads the constant. 00:16:12.500 --> 00:16:14.200 It stores it into a field called X. 00:16:14.200 --> 00:16:15.100 It loads the constant. 00:16:15.100 --> 00:16:16.740 It stores into a field called Y. 00:16:16.740 --> 00:16:20.000 Then it loads the constant again, the value for X again. 00:16:20.000 --> 00:16:23.480 And then it calls return val as the bytecode instructions, right? 00:16:23.480 --> 00:16:26.860 Instead of just load constant zero, return value, right? 00:16:26.860 --> 00:16:28.060 Like, it could be a lot quicker. 00:16:28.680 --> 00:16:32.540 So I find that this is, it's honestly a little bit surprising. 00:16:32.540 --> 00:16:37.260 I mean, Python is 25 years old and it doesn't take steps like this. 00:16:37.260 --> 00:16:44.440 Now, Darius Beacon did point out that Guido himself said Python is about having the simplest, 00:16:44.440 --> 00:16:46.340 dumbest compiler imaginable. 00:16:46.340 --> 00:16:47.800 And there's some links to that. 00:16:47.800 --> 00:16:50.020 So some references there if you want to go check that out. 00:16:50.020 --> 00:16:53.960 So I think, you know, maybe it's by design to keep it simple. 00:16:53.960 --> 00:16:56.040 It's easy for people to contribute to. 00:16:56.340 --> 00:17:04.440 But it certainly seems like there could be a layer, like, between parsing the bytecode and executing the bytecode that says, 00:17:04.440 --> 00:17:07.480 we're not running into debugger or something like that. 00:17:07.480 --> 00:17:12.260 So let's go crazy and, like, just, you know, convert stuff like that to return zero. 00:17:12.260 --> 00:17:15.300 There's also a bunch of other interesting examples in there. 00:17:15.300 --> 00:17:18.620 This is just one that's really obvious that's good for talking that I pulled out. 00:17:18.680 --> 00:17:24.460 And optimization levels is something that CS people have been doing with compilers for a long time. 00:17:24.460 --> 00:17:26.980 So it's not like we'd have to invent it ourselves. 00:17:26.980 --> 00:17:27.480 Right. 00:17:27.480 --> 00:17:28.920 Yeah, yeah. 00:17:28.920 --> 00:17:30.160 C has had plenty of it. 00:17:30.160 --> 00:17:35.180 C#, the JIT compiled languages, their JIT compiler is a place where a lot of that happens. 00:17:35.180 --> 00:17:36.220 Things like this, right? 00:17:36.220 --> 00:17:39.500 Did you say that there was a comparison to other languages? 00:17:39.500 --> 00:17:42.280 Do other languages do more optimization? 00:17:42.600 --> 00:17:43.240 No, not really. 00:17:43.240 --> 00:17:46.560 They're all pretty much the same. 00:17:46.560 --> 00:17:49.540 For better or worse, they're all the same. 00:17:49.540 --> 00:17:53.020 So there's an interesting point that he makes that I do want to, like, just comment on real quick. 00:17:53.020 --> 00:18:00.040 It says, so the consensus seems to be that if you want or need better performance, don't use Python. 00:18:00.040 --> 00:18:01.980 Go use another language. 00:18:02.100 --> 00:18:04.480 I'm like, dude, no, you were, like, so close. 00:18:04.480 --> 00:18:05.860 You were so close as well. 00:18:05.860 --> 00:18:08.840 You could use, maybe don't use CPython, right? 00:18:08.840 --> 00:18:10.700 Maybe use PyPy, P-Y-P-Y. 00:18:10.700 --> 00:18:17.280 But the most obvious optimization to me that just can change the game is Cython. 00:18:17.280 --> 00:18:17.740 Yeah. 00:18:17.740 --> 00:18:24.920 You could write, like, one or two slow functions in Cython, and boom, it goes to machine instructions, and it's, you know, it nears the speed of C. 00:18:24.920 --> 00:18:26.720 So I like the article. 00:18:26.720 --> 00:18:30.180 I don't like that it says, oh, if things are a little bit slow, just run away. 00:18:30.180 --> 00:18:33.940 Like, no, there's probably a package that has a C extension that already works better. 00:18:33.940 --> 00:18:37.560 Or, you know, there's a data structure you should be using that would be better. 00:18:37.560 --> 00:18:40.200 Or there's Cython or, you know, on and on. 00:18:40.200 --> 00:18:43.200 There's a lot of improvements before Python's not the answer. 00:18:43.200 --> 00:18:47.360 Or be aware that this is doing this and do your own optimization. 00:18:47.360 --> 00:18:53.180 And for the most part, use a profiler and really tell where the optimization needs to be. 00:18:53.180 --> 00:18:53.560 Exactly. 00:18:53.560 --> 00:18:58.820 Like, only 10% of your code needs to be fast at all, if that much, most of the time, right? 00:18:58.820 --> 00:19:03.140 It's usually, like, one little bit, like, oh, if this were faster, it would change the game. 00:19:03.140 --> 00:19:03.460 Yeah. 00:19:03.460 --> 00:19:08.040 I mean, I learned assembly in college, and I'm glad I've never had to use it. 00:19:08.040 --> 00:19:10.320 For sure. 00:19:11.060 --> 00:19:13.180 So, final comment here. 00:19:13.180 --> 00:19:19.040 Brett Cannon, when I interviewed him recently, you know, he's on the steering council, core developer, and so on. 00:19:19.040 --> 00:19:24.800 He did talk about, you know, how would adoption of Python 3 change? 00:19:24.800 --> 00:19:30.560 How would adoption of Python in general change if we could make Python two or four times faster than it is today? 00:19:31.300 --> 00:19:32.600 Like, most of the time, it doesn't matter. 00:19:32.600 --> 00:19:37.200 But if it could be faster in some interesting ways, what would that mean, right? 00:19:37.200 --> 00:19:45.220 In terms of upgrading more quickly to the new versions and just general, like, people not saying, oh, I have to use Go because I need AsyncIO or something like this. 00:19:45.620 --> 00:20:00.440 So, it seems like if the compiler is this absent, if optimizations are this absent from the compiler, like, there's some low-hanging fruit to, like, do some simple CS compiler optimizations and make stuff faster, right? 00:20:00.440 --> 00:20:05.320 I mean, you could make this silly foo method, like, probably three times as fast, right? 00:20:05.320 --> 00:20:07.620 Because you could drop most of the bytecode operations. 00:20:07.620 --> 00:20:08.840 Yeah, definitely. 00:20:09.280 --> 00:20:10.280 It's worth looking at. 00:20:10.280 --> 00:20:14.900 It's interesting that there is some people thinking about performance. 00:20:14.900 --> 00:20:15.320 Yeah. 00:20:15.320 --> 00:20:22.620 I mean, we had that conversation around the idea of Rust and maybe what if we used Rust instead of C in certain situations. 00:20:22.620 --> 00:20:25.460 But, like, this seems like low-hanging fruit already right here. 00:20:25.460 --> 00:20:32.420 And regardless of whether it lands in Rust or C, when it's executed, not executing code is a lot faster than executing it. 00:20:32.420 --> 00:20:32.620 Yeah. 00:20:32.620 --> 00:20:32.840 Cool. 00:20:32.840 --> 00:20:33.380 What's the next one? 00:20:33.380 --> 00:20:37.980 EdgeDB is something that came up on my radar a couple years ago. 00:20:38.200 --> 00:20:48.240 I saw the EdgeDB people had a booth at one of the PyCons, and they were talking about it, but at the time, it wasn't around for people to actually play with. 00:20:48.240 --> 00:20:55.420 So the other day, I saw an article called A Path to a 10x Database put out by the EdgeDB people. 00:20:55.420 --> 00:20:59.560 One, there was a download link, which I was happy for. 00:20:59.560 --> 00:21:01.200 There's an alpha one available. 00:21:01.520 --> 00:21:10.280 And people that are following along and are kind of excited about what they're doing, they've published a roadmap of the features they have done, what they're working on. 00:21:10.280 --> 00:21:12.200 And it's kind of cool. 00:21:12.200 --> 00:21:14.460 I'm looking forward to being able to play with it more. 00:21:15.020 --> 00:21:19.900 So people that don't know what it is, they call it a next generation relational database. 00:21:19.900 --> 00:21:22.340 It's based on Postgres. 00:21:22.340 --> 00:21:28.120 I don't know what that means if they're using Postgres or if they're used the design of Postgres as a base. 00:21:28.120 --> 00:21:29.420 I haven't dug that far. 00:21:29.900 --> 00:21:35.020 But it features a different kind of data model and an advanced query language. 00:21:35.020 --> 00:21:40.200 And there are a whole bunch of features built into it already, and I'm pretty excited about a lot of it. 00:21:40.200 --> 00:21:45.300 But the thing that really excites me is that they completely replaced SQL, the query language. 00:21:45.300 --> 00:21:49.800 It's a different kind of language, and it looks more natural to me. 00:21:49.800 --> 00:21:59.580 I mean, people aren't really writing SQL a lot of times because they're using SQLAlchemy or something like that. 00:21:59.580 --> 00:22:03.580 And partly, those things exist because people don't want to write SQL. 00:22:03.580 --> 00:22:08.520 But maybe if we had a better query language, we wouldn't need the middle layer so much. 00:22:08.520 --> 00:22:09.780 Yeah, it definitely looks interesting. 00:22:09.780 --> 00:22:14.700 I don't have a real good sense of how it compares to both of those. 00:22:14.700 --> 00:22:16.920 The query syntax does look nice. 00:22:16.920 --> 00:22:23.300 The joins look super cool, or the subqueries possibly is more like an analogy. 00:22:23.300 --> 00:22:25.300 But yeah, it looks really neat. 00:22:25.520 --> 00:22:32.880 It sort of sells itself as a hybrid between document databases like Mongo and relational ones like Postgres. 00:22:32.880 --> 00:22:35.680 So yeah, it's cool to see innovation there for sure. 00:22:35.680 --> 00:22:41.720 Outside of Mongo, seeing some innovation on the SQL side or the relational side is nice. 00:22:41.720 --> 00:22:45.040 We'll see if it's really a 10x improvement. 00:22:45.040 --> 00:22:47.060 But yeah, we can't just stick around for nothing. 00:22:47.060 --> 00:22:51.460 I did actually try to play with it because I'm like, I want to play with this because it's got Python bindings. 00:22:51.900 --> 00:22:54.200 But I couldn't get it to install on my Mac. 00:22:54.200 --> 00:22:55.440 So yeah. 00:22:55.440 --> 00:22:59.100 Yeah, well, would you have to suffer for being out on the cutting edge, Brian? 00:22:59.100 --> 00:23:00.780 Price you pay. 00:23:00.780 --> 00:23:01.540 Yep. 00:23:01.540 --> 00:23:02.620 All right. 00:23:02.620 --> 00:23:05.460 So this last one is going to be just a quick roundup of some stuff. 00:23:05.460 --> 00:23:07.980 Then maybe this combo will help some folks. 00:23:07.980 --> 00:23:16.300 This guy, Wakwas Jonas, worked for a software, sorry, healthcare startup in the US. 00:23:16.760 --> 00:23:22.740 And he wrote this cool blog post called 16 Python Libraries that Helped a Healthcare Startup Grow. 00:23:22.740 --> 00:23:23.220 Oh, neat. 00:23:23.220 --> 00:23:23.440 Yeah. 00:23:23.440 --> 00:23:32.260 So it's just like a paragraph or two about different packages or even modules that they use to kind of solve some problem within their startup. 00:23:32.260 --> 00:23:39.060 So we have Paramiko, which lets you basically issue commands over SSH to other servers. 00:23:39.060 --> 00:23:48.660 So like on my computer, I could like use Python and talk over SSH to run processes or copy files, stuff between servers. 00:23:48.660 --> 00:23:49.940 Anything I can SSH to. 00:23:49.940 --> 00:23:50.620 That's pretty cool. 00:23:50.620 --> 00:23:52.460 The built-in CSV module. 00:23:52.460 --> 00:23:56.780 You know, that's always good for parsing CSV files. 00:23:56.780 --> 00:23:57.320 Really nice. 00:23:57.320 --> 00:23:58.340 You mentioned SQLAlchemy. 00:23:58.500 --> 00:24:04.340 So they use SQLAlchemy as well, requests and beautiful soup for APIs and web scraping. 00:24:04.340 --> 00:24:09.100 I like to say that every website is an API, even if it doesn't know it. 00:24:09.100 --> 00:24:14.140 So if it doesn't have an API, it has data and you just have to do the right request to it. 00:24:14.140 --> 00:24:15.360 Now it's an API. 00:24:15.360 --> 00:24:16.720 Here's one for you, Brian. 00:24:16.720 --> 00:24:21.420 Test scenarios, which is a PyUnit extension for dependency injection. 00:24:21.420 --> 00:24:23.040 So that's kind of cool. 00:24:23.620 --> 00:24:30.040 Dependency injection is not that huge of a thing that people make use of in Python, but, you know, it has its place, I guess. 00:24:30.040 --> 00:24:30.240 Yeah. 00:24:30.240 --> 00:24:30.940 HL7. 00:24:30.940 --> 00:24:37.740 So a simple library for parsing health level 7 files into Python objects. 00:24:37.740 --> 00:24:38.520 That's cool. 00:24:38.520 --> 00:24:41.100 I suppose like doing that yourself probably is not fun. 00:24:41.100 --> 00:24:43.280 So having a library that does it is great. 00:24:43.280 --> 00:24:49.360 Python phone numbers, which is a library for parsing, formatting, and validating international phone numbers. 00:24:49.360 --> 00:24:50.620 That's pretty sweet. 00:24:50.620 --> 00:24:51.820 It's based on a Google library. 00:24:51.960 --> 00:24:53.000 It's like a Python port of it. 00:24:53.000 --> 00:24:56.900 G event for networking and asynchronous code. 00:24:56.900 --> 00:25:00.780 Python dash date util for parsing date times. 00:25:00.780 --> 00:25:09.460 Like anytime I have to work with date times, I'm like, okay, this project now requires Python dash date util because parsing date time sucks without it, right? 00:25:09.460 --> 00:25:13.840 But this one you just say pars and like that right answer just seems to always come out as great. 00:25:13.840 --> 00:25:15.300 So Matt Plotlev for graphs. 00:25:15.300 --> 00:25:16.760 Python magic. 00:25:16.760 --> 00:25:18.000 Have you heard of Python magic? 00:25:18.000 --> 00:25:19.540 I don't know. 00:25:19.540 --> 00:25:20.260 I hadn't. 00:25:20.360 --> 00:25:27.480 And so what you can do is you can give it a file, some random binary file or even text file, and it'll tell you what file type it is. 00:25:27.480 --> 00:25:27.840 Oh, neat. 00:25:27.900 --> 00:25:32.820 So like suppose somebody gives you an image and they've named it .jpg, but it's really a PNG. 00:25:32.820 --> 00:25:36.140 Like you could feed it something to something like Python magic. 00:25:36.140 --> 00:25:36.840 It would say PNG. 00:25:36.840 --> 00:25:42.820 So you can give it like PDFs or zip files, and it'll tell you like what file it is. 00:25:42.820 --> 00:25:43.800 Okay. 00:25:43.800 --> 00:25:44.940 But magic? 00:25:44.940 --> 00:25:46.660 That seems like a bad name for it. 00:25:46.660 --> 00:25:47.400 But yeah. 00:25:47.400 --> 00:25:48.260 It's Python magic. 00:25:48.380 --> 00:25:51.580 Well, I mean, the reason is it's based on a thing called lib magic. 00:25:51.580 --> 00:25:52.280 But yeah. 00:25:52.280 --> 00:25:56.720 It's just like the criticism just transitively follows to lib magic, I guess. 00:25:56.720 --> 00:25:58.620 All right. 00:25:58.620 --> 00:25:59.260 Another one. 00:25:59.260 --> 00:25:59.660 Django. 00:25:59.860 --> 00:26:02.920 Obviously, that doesn't need a lot of introduction, but yeah, they must use Django. 00:26:02.920 --> 00:26:06.300 Bodo, which is the API for interacting with all things AWS. 00:26:06.300 --> 00:26:09.020 So if you're doing anything with that, that's super cool. 00:26:09.720 --> 00:26:21.100 Like I use Bodo for automatic transcoding, like re-encoding in different formats, videos for my courses, or downloading, say, MP3s to a caching server, stuff like that. 00:26:21.100 --> 00:26:28.940 And then finally, Mailgun for sending email, and Twilio's Python API for sending, both of those were sending reminders, one over email, one over text. 00:26:28.940 --> 00:26:31.960 But it's kind of a cool combo of things, right? 00:26:31.960 --> 00:26:33.400 Mailgun's just a great name. 00:26:33.400 --> 00:26:38.500 We've been starting to use Paramount at work, too, but for the SSH features. 00:26:38.500 --> 00:26:39.220 It's good. 00:26:39.220 --> 00:26:39.620 Oh, yeah. 00:26:39.800 --> 00:26:40.020 Nice. 00:26:40.020 --> 00:26:50.920 Yeah, I feel like this, you know, you don't necessarily have to pick what he picked, but it's cool to see how those all fit together and think of like, well, what packages run this company, basically. 00:26:50.920 --> 00:26:54.340 Articles like this are neat of different people solving different problems. 00:26:54.340 --> 00:26:56.380 What are they using from Python? 00:26:56.380 --> 00:26:57.380 Yeah, exactly. 00:26:57.380 --> 00:26:57.920 Like it. 00:26:57.920 --> 00:26:58.240 All right. 00:26:58.240 --> 00:26:59.940 So that's it for our main items. 00:26:59.940 --> 00:27:01.480 Got any extras you want to share with us? 00:27:01.480 --> 00:27:02.560 No. 00:27:02.560 --> 00:27:03.420 Do you? 00:27:03.420 --> 00:27:05.700 I thought I didn't, but I'm going to share one thing with you all. 00:27:05.700 --> 00:27:11.840 I just recorded an episode with the United States Digital Service for Talk Python. 00:27:11.840 --> 00:27:12.360 Okay. 00:27:12.360 --> 00:27:13.400 What is that? 00:27:13.400 --> 00:27:14.300 I hadn't heard of that either. 00:27:14.720 --> 00:27:18.900 But this is like a little stealth startup type thing inside the government. 00:27:18.900 --> 00:27:29.040 President Obama set it up and it was basically the tech team brought in to solve the healthcare.gov crashing problems like that whole big fail to launch for the Obamacare stuff. 00:27:29.600 --> 00:27:32.200 There was a group of people brought in to fix it and then they did. 00:27:32.200 --> 00:27:35.900 They're like, well, why can't we just apply this to all the other broken things in the government? 00:27:35.900 --> 00:27:45.020 So it's a really cool service where like you can go do like a three month tour of duty at the U.S. Digital Service and like not even have to leave your job. 00:27:45.020 --> 00:27:48.900 Just take a like unpaid leave to go fix something in the government or whatever. 00:27:48.900 --> 00:27:49.680 It's pretty cool. 00:27:49.680 --> 00:27:52.700 I have an episode coming out, but I hadn't heard of it and I thought that was kind of cool. 00:27:52.700 --> 00:27:53.660 So I thought I'd throw it out there. 00:27:53.660 --> 00:27:54.840 Yeah, this is neat. 00:27:54.840 --> 00:27:55.440 It is for sure. 00:27:56.060 --> 00:27:58.240 I have a, it's almost a joke. 00:27:58.240 --> 00:27:59.720 It's not exactly a joke. 00:27:59.720 --> 00:28:06.720 It's more maybe mocking, but how can you tell the difference between machine learning and AI, Brian? 00:28:06.720 --> 00:28:07.900 I don't know. 00:28:07.900 --> 00:28:11.020 If it's written in Python, it's probably machine learning. 00:28:11.020 --> 00:28:13.840 If it's written in PowerPoint, it's probably AI. 00:28:13.840 --> 00:28:14.580 What? 00:28:14.580 --> 00:28:17.280 Written in PowerPoint? 00:28:17.280 --> 00:28:22.520 Like as in it's just like a presentation with ideas, but no code and no implementation yet. 00:28:22.520 --> 00:28:23.540 Oh, okay. 00:28:23.540 --> 00:28:23.900 Yeah. 00:28:23.900 --> 00:28:24.300 Okay. 00:28:24.300 --> 00:28:24.980 Got it. 00:28:24.980 --> 00:28:27.120 So basically if it's real, it's machine learning. 00:28:27.120 --> 00:28:34.160 If it's, if it's like, we're going to use magic, computer magic to solve this problem, it's AI and it's in PowerPoint. 00:28:34.160 --> 00:28:34.860 That's funny. 00:28:34.860 --> 00:28:43.260 I have a question for you when I, it's not a joke, but way back in the dark ages when I was going to college, all the AI work was done in like Lisp. 00:28:43.260 --> 00:28:44.240 Yes, it was. 00:28:44.240 --> 00:28:47.900 Are there still people doing AI in Lisp or is that not a thing anymore? 00:28:47.900 --> 00:28:48.480 Do you know? 00:28:48.640 --> 00:28:50.780 I think people are still doing it. 00:28:50.780 --> 00:28:55.600 I think people are still doing it, but I don't think the neural network people have stayed there. 00:28:55.600 --> 00:28:55.800 Right. 00:28:55.800 --> 00:29:02.580 I think the neural network people mostly have moved to Python and things like TensorFlow and the other GP based things. 00:29:02.580 --> 00:29:07.340 But I'm sure that there's like different kinds of AI. 00:29:07.340 --> 00:29:07.460 Yeah. 00:29:07.460 --> 00:29:07.540 Yeah. 00:29:07.540 --> 00:29:08.060 Because you're right. 00:29:08.060 --> 00:29:12.160 It was all, you had to be a Lisp programmer if you wanted to do anything with AI. 00:29:12.160 --> 00:29:15.380 And AI was always this like amorphous, weird thing. 00:29:15.380 --> 00:29:24.040 Like you don't really know what it is, but probably if we can like set up a blind chat with it over IRC, then it might seem like it's alive and then it'll be AI. 00:29:24.040 --> 00:29:24.420 Right. 00:29:24.420 --> 00:29:28.000 Like that, you know, the whole Turing test and all that, that stuff. 00:29:28.000 --> 00:29:30.220 And now it's like, that's cute. 00:29:30.220 --> 00:29:32.520 Car, drive here. 00:29:32.520 --> 00:29:34.820 The car will go out. 00:29:34.820 --> 00:29:41.960 You know, like that's with Python and like TensorFlow and the Lisp one that's doing the chat. 00:29:41.960 --> 00:29:42.640 Right. 00:29:42.640 --> 00:29:48.760 Like I feel like that's kind of where it is, but I'm sure people are still doing cool stuff with Lisp that I don't know or really want to read the code for. 00:29:48.760 --> 00:29:49.360 Okay. 00:29:49.360 --> 00:29:52.420 I'm glad there's probably not any Lisp programmers that listen to this. 00:29:52.420 --> 00:29:55.780 No, but we're probably going to be posted in a negative way on some Lisp forum. 00:29:55.780 --> 00:29:56.440 Sorry about that. 00:29:56.440 --> 00:29:57.120 Sorry. 00:29:57.120 --> 00:29:58.820 All right. 00:29:58.820 --> 00:30:00.120 Well, thanks for being here, Brian. 00:30:00.120 --> 00:30:01.460 And thanks for sharing everything. 00:30:01.460 --> 00:30:01.940 Thank you. 00:30:01.940 --> 00:30:02.260 You bet. 00:30:02.260 --> 00:30:02.720 Bye, everyone. 00:30:02.720 --> 00:30:03.000 Bye. 00:30:03.000 --> 00:30:04.900 Thank you for listening to Python Bytes. 00:30:04.900 --> 00:30:07.440 Follow the show on Twitter via at Python Bytes. 00:30:07.440 --> 00:30:10.300 That's Python Bytes as in B-Y-T-E-S. 00:30:10.560 --> 00:30:13.540 And get the full show notes at pythonbytes.fm. 00:30:13.540 --> 00:30:17.740 If you have a news item you want featured, just visit pythonbytes.fm and send it our way. 00:30:17.740 --> 00:30:20.440 We're always on the lookout for sharing something cool. 00:30:20.440 --> 00:30:23.560 On behalf of myself and Brian Okken, this is Michael Kennedy. 00:30:23.560 --> 00:30:26.980 Thank you for listening and sharing this podcast with your friends and colleagues.