WEBVTT 00:00:00.001 --> 00:00:04.240 This is Python Bytes, Python headlines and news delivered directly to your earbuds. 00:00:04.240 --> 00:00:09.180 It's episode 9, recorded Tuesday, January 17th, 2016. 00:00:09.180 --> 00:00:11.780 This is one of your co-hosts, Michael Kennedy. 00:00:11.780 --> 00:00:14.220 I'm here with my other co-host, Brian Okken. 00:00:14.220 --> 00:00:15.200 Hey, Brian, how's it going, man? 00:00:15.200 --> 00:00:16.680 It's going very good. How are you? 00:00:16.680 --> 00:00:22.640 I'm doing well. I always look forward to our weekly chat about cool stuff going on in the Python ecosystem. 00:00:22.640 --> 00:00:27.380 And I see that you found something quite cool for our first item. 00:00:27.380 --> 00:00:29.260 Actually, it's a series of things. 00:00:29.520 --> 00:00:34.280 The link that we have is to Python asynchronous IO walkthrough. 00:00:34.280 --> 00:00:35.840 And here's the story. 00:00:35.840 --> 00:00:41.020 So in July, there was an open source book published called 500 Lines or Less. 00:00:41.020 --> 00:00:44.660 The Architecture of Open Source Applications is the website. 00:00:44.660 --> 00:00:50.180 But they do various open source free books, which is pretty cool. 00:00:50.180 --> 00:00:59.480 Anyway, the 500 Lines or Less had one chapter in it from Jesse Giro Davis and Guido Van Rossum. 00:00:59.480 --> 00:01:02.820 called A Web Crawler with AsyncIO Coroutines. 00:01:02.820 --> 00:01:11.060 And it's a pretty cool chapter about explaining asynchronous networking, showing how non-blocking sockets work, 00:01:11.060 --> 00:01:15.860 and how Python 3 coroutines improve asynchronous network programs. 00:01:16.240 --> 00:01:16.860 Yeah, that's really cool. 00:01:16.860 --> 00:01:17.120 Yeah, that's really cool. 00:01:17.120 --> 00:01:19.460 I think that that book is amazing. 00:01:19.460 --> 00:01:21.640 It's not just this particular chapter. 00:01:21.640 --> 00:01:22.520 There's many chapters. 00:01:22.520 --> 00:01:28.880 It's also not just Python, but it has a heavy, a lot of pieces which are Python. 00:01:28.880 --> 00:01:35.320 And basically, it's, can you show me something amazing that really, I thought was really hard, 00:01:35.400 --> 00:01:40.100 how it can be explained or written in 500 lines or less, and then discuss the architecture. 00:01:40.100 --> 00:01:43.460 And there's like 20 different projects or something. 00:01:43.460 --> 00:01:44.320 It was very cool. 00:01:44.320 --> 00:01:47.320 Yeah, and the series is pretty neat. 00:01:47.320 --> 00:01:49.420 So this is 500 Lines or Less. 00:01:49.420 --> 00:01:55.740 There's previous books that are like about architecture and about performance issues. 00:01:55.740 --> 00:01:58.200 And it's a neat thing they're doing. 00:01:58.200 --> 00:02:05.020 But this particular chapter for me, since I'm kind of new to the asynchronous world, 00:02:05.020 --> 00:02:07.700 it still was a little bit heavy to get into. 00:02:07.700 --> 00:02:11.520 And so Philip Guo, who I think he interviewed you once. 00:02:11.520 --> 00:02:16.660 Yeah, he's been on my show on Talk Python To Me on episode 22. 00:02:16.660 --> 00:02:19.740 And I also was on his show. 00:02:19.740 --> 00:02:21.220 He started a podcast recently. 00:02:21.220 --> 00:02:23.560 It's got like 25 episodes or something. 00:02:23.560 --> 00:02:25.380 And yeah, I'll be sure to link to that. 00:02:25.380 --> 00:02:26.880 That's a really cool one as well. 00:02:26.880 --> 00:02:30.840 He interviews people just kind of generally in the programming space. 00:02:30.840 --> 00:02:32.960 So what he did was, it's pretty cool. 00:02:32.960 --> 00:02:38.280 He just is walking through this article and talking about it and then also, 00:02:38.280 --> 00:02:43.000 and showing it on video, and then also going through and doing some code examples. 00:02:43.000 --> 00:02:47.380 And he split, it's about 90 minutes total to get through this, 00:02:47.380 --> 00:02:49.120 but he split it up into eight parts. 00:02:49.120 --> 00:02:52.480 So each one is really not that hard to get through. 00:02:53.180 --> 00:02:55.520 And it's a pretty cool idea. 00:02:55.520 --> 00:02:56.680 And I really appreciate it. 00:02:56.680 --> 00:03:04.600 I think it's a good way to learn, to see somebody doing it, to hear them, to use all your senses. 00:03:04.600 --> 00:03:05.560 I really like that. 00:03:05.560 --> 00:03:06.960 I think this is great work. 00:03:06.960 --> 00:03:07.840 Nice work, Philip. 00:03:07.840 --> 00:03:08.540 Way to go. 00:03:08.540 --> 00:03:10.280 He's done stuff like that before. 00:03:10.520 --> 00:03:19.120 The reason I had him on episode 22 of Talk Python was he did this thing called CPython, a 10-hour code walk, 00:03:19.120 --> 00:03:24.360 which was like an exploration through the CPython internals, which I found really enlightening. 00:03:24.360 --> 00:03:29.340 And we actually, I talked to Jesse about his article on episode 69 as well, 00:03:29.340 --> 00:03:32.220 when we talked about writing as a developer. 00:03:32.220 --> 00:03:38.000 He's got some really cool thinking around, like design patterns on technical writing and stuff. 00:03:38.080 --> 00:03:40.000 So this is really cool. 00:03:40.000 --> 00:03:46.840 I think seeing a problem unfold before your eyes in code is much different than seeing the finished product discussed. 00:03:46.840 --> 00:03:49.340 And I find I learn really well that way. 00:03:49.340 --> 00:03:50.920 So I'm happy this is here. 00:03:50.920 --> 00:03:53.040 I haven't had a chance to go through it, but I'm looking forward to it. 00:03:53.420 --> 00:03:59.460 And also, both Jesse and Philip are doing some cool things to help the entire community, which I appreciate. 00:03:59.460 --> 00:04:02.800 Jesse's been supportive of a lot of people, including me. 00:04:02.800 --> 00:04:03.520 Yeah, absolutely. 00:04:03.520 --> 00:04:04.700 Jesse's doing great stuff. 00:04:04.700 --> 00:04:07.200 Do you want to think about the future of Python a little bit? 00:04:07.880 --> 00:04:12.520 I thought I was thinking about the future of Python with switching to 3.6 recently. 00:04:12.520 --> 00:04:15.400 So, but what do you think the future has in store? 00:04:15.400 --> 00:04:22.300 We were living like right on the edge of the front wave, but there's an article I thought was pretty interesting. 00:04:22.660 --> 00:04:28.280 I don't necessarily agree with everything, but I felt that it was certainly, you know, thought provoking. 00:04:28.280 --> 00:04:38.940 A guy named Sirdar Yagulap, I'm sorry, I'm sure I messed up your name, wrote an article and it's called Four Likely Future Twists for Python. 00:04:38.940 --> 00:04:40.940 And I thought that was pretty cool. 00:04:41.300 --> 00:04:43.180 So, let's go through the four twists. 00:04:43.180 --> 00:04:51.680 The first one does not make me happy, but is certainly something that I can see coming into existence as a thing. 00:04:51.680 --> 00:04:52.560 So, we'll see. 00:04:52.560 --> 00:04:56.980 But the first one that they put out there is that Python 2x may live on. 00:04:56.980 --> 00:05:00.360 Yeah, I actually can see that this might happen. 00:05:00.360 --> 00:05:03.780 I mean, it's an open source project, so there's nobody stopping you from doing it. 00:05:03.780 --> 00:05:08.100 The thing that's going to make the difference is what do the core developers do, right? 00:05:08.100 --> 00:05:13.880 So, right now the core developers are all focused on making sure that we make Python 3 as great as possible. 00:05:13.880 --> 00:05:15.660 And they're putting their energy into it and so on. 00:05:15.660 --> 00:05:19.100 So, I think Python 3 is certainly the right place for people to be. 00:05:19.100 --> 00:05:21.200 But I can see like large banks. 00:05:21.200 --> 00:05:23.060 You know, you think of places like Bank of America. 00:05:23.060 --> 00:05:31.100 They've got, gosh, I don't remember the exact stats, but I was talking to Mahmoud Hashemi from one of the Enterprise Python episodes I did. 00:05:31.100 --> 00:05:36.280 And it's something like the number of lines of Python 2, I don't even think it's 2.7. 00:05:36.280 --> 00:05:39.000 It's like 2.6 or 2.5 code is in the millions. 00:05:39.000 --> 00:05:42.560 Like 5 million lines of codes or something crazy like that. 00:05:42.560 --> 00:05:48.640 I can see a company like that forking Python and just making some kind of ongoing effort. 00:05:48.640 --> 00:05:51.800 Supporting your own Python, that just doesn't sound fun. 00:05:51.800 --> 00:05:53.660 It sounds like a really bad idea. 00:05:53.660 --> 00:06:00.140 I would much rather people just upgrade and we can all work together and live together and do great stuff. 00:06:00.140 --> 00:06:01.040 Here's one of the predictions. 00:06:01.040 --> 00:06:05.820 That there'll probably be somebody that forks Python 2 and tries to keep it going. 00:06:05.820 --> 00:06:11.540 Whether that turns out to be beneficial or, you know, trading one set of problems for a worse set of problems, we'll see. 00:06:11.540 --> 00:06:12.840 Yeah. 00:06:12.840 --> 00:06:16.520 The other one was, this one I had no visibility into. 00:06:16.520 --> 00:06:18.120 I didn't see this coming. 00:06:18.120 --> 00:06:23.620 And I read the title and I said, requirements.txt may be replaced with something better. 00:06:24.580 --> 00:06:25.260 I thought, what? 00:06:25.260 --> 00:06:26.360 Okay, well, maybe. 00:06:26.360 --> 00:06:35.220 It turns out the guys over at the Python Packaging Authority, that's the PyPI and pip and all those projects. 00:06:35.220 --> 00:06:38.380 So there's an organization, a group of people that actually work on that. 00:06:38.380 --> 00:06:40.340 They're working on this thing called pip File. 00:06:40.340 --> 00:06:46.520 And it's like a proposed new file format that's supposed to replace requirements.txt. 00:06:46.520 --> 00:06:48.300 That's interesting. 00:06:48.300 --> 00:06:48.960 Isn't it? 00:06:48.960 --> 00:06:49.160 Yeah. 00:06:49.500 --> 00:07:00.040 And so the idea is that pip File is going to be better or superior to requirements and that it has a TML syntax, which is, if I recall correctly, it's a little like YAML. 00:07:00.040 --> 00:07:03.680 There's one pip File that can have multiple configurations in it. 00:07:03.680 --> 00:07:08.200 So you don't have like a dev requirements, a test requirements, a prod requirements, and so on. 00:07:08.200 --> 00:07:09.560 Yeah, it's cool. 00:07:09.560 --> 00:07:13.460 You can do like a pip File freeze on it. 00:07:13.460 --> 00:07:20.680 It'll generate something that is a much richer document instead of just a TXT file with a package name, like a version. 00:07:21.120 --> 00:07:22.740 So there's a lot of configuration and stuff in there. 00:07:22.740 --> 00:07:31.820 Like, for example, one of the things you can do in these pip Files is you can actually set the source of the packages, like right in your requirements file. 00:07:32.600 --> 00:07:35.480 So you can say, I want to use this version of Python. 00:07:35.480 --> 00:07:39.740 I want to use it against this source, like pypi.org. 00:07:39.740 --> 00:07:43.640 Or you could create your own devpy server thing and run it internally. 00:07:43.640 --> 00:07:45.560 And that would be part of your requirements file. 00:07:45.560 --> 00:07:47.560 So lots of cool enhancements there. 00:07:47.560 --> 00:07:49.320 I'm interested to see where it goes. 00:07:49.320 --> 00:07:50.240 But it's out there on GitHub. 00:07:50.240 --> 00:07:51.220 You can actually check it out. 00:07:51.560 --> 00:08:00.100 Yeah, I'd like to make sure it sort of goes along the lines with other packaging issues, like the setup file and stuff. 00:08:00.100 --> 00:08:03.240 Hopefully we have one thing that replaces everything. 00:08:03.240 --> 00:08:04.480 Yeah, definitely. 00:08:04.480 --> 00:08:08.860 Okay, so number three is Python could get more enterprise editions. 00:08:08.860 --> 00:08:12.500 So we've got things like Anaconda and InThot. 00:08:12.500 --> 00:08:20.820 And Intel actually has their own Python implementation that is sort of a repackaging and tweaking of the Anaconda distribution. 00:08:21.200 --> 00:08:29.360 But just talking about how there may be more variations of Python distributions focused on enterprise needs. 00:08:29.360 --> 00:08:30.440 Maybe. 00:08:30.440 --> 00:08:32.820 I certainly see it happening in data science. 00:08:32.820 --> 00:08:34.400 I could see it happening elsewhere. 00:08:34.400 --> 00:08:45.080 I could see it, especially since we have to, I mean, everybody that's relying on Anaconda or something kind of has to wait for them to release something when they're waiting for a new version. 00:08:45.080 --> 00:08:48.820 And the last one is Python's software repository. 00:08:49.320 --> 00:08:53.420 So PyPI basically could get enterprise-friendly package management. 00:08:53.920 --> 00:09:05.720 So Christian Medina wrote a really interesting article as a follow-up to my episode 84 on the problems with PyPI and open source infrastructure funding and stuff. 00:09:05.720 --> 00:09:18.040 And put together a pretty interesting article talking about something called the Python Trusted Registry or Trusted Index or something like that as a way to both fund PyPI and make it more enterprise-friendly. 00:09:18.040 --> 00:09:20.840 I'm actually thinking about this problem as well. 00:09:20.840 --> 00:09:27.240 And I'm probably going to release something like an article and a proof of concept, but I'm not ready to talk about it yet. 00:09:27.240 --> 00:09:27.640 Okay. 00:09:27.640 --> 00:09:28.440 Sounds interesting. 00:09:28.440 --> 00:09:30.100 Well, so that was four predictions. 00:09:30.100 --> 00:09:31.340 Are we done with the future? 00:09:31.340 --> 00:09:32.320 That's the future. 00:09:32.320 --> 00:09:33.460 Let's go back to the present. 00:09:34.220 --> 00:09:34.700 Okay. 00:09:34.700 --> 00:09:39.860 So in the present, NumPy is used for a lot of data science and really just science and engineering. 00:09:39.860 --> 00:09:41.140 A lot of people use NumPy. 00:09:41.140 --> 00:09:46.880 There's a new book, an open source book called From Python to NumPy. 00:09:47.220 --> 00:09:51.780 And it's from, I think this is a French person, Nicolas Rogier. 00:09:51.780 --> 00:09:53.240 The book is pretty interesting. 00:09:53.240 --> 00:09:56.160 It takes the assumption that you already know Python. 00:09:56.160 --> 00:09:57.460 You're an intermediate developer. 00:09:57.460 --> 00:10:05.100 And you just need to get your understanding of NumPy to apply it to whatever problem you're on. 00:10:05.100 --> 00:10:06.380 And it looks well. 00:10:06.380 --> 00:10:08.980 I haven't read a ton of it, but it looks really well formatted. 00:10:08.980 --> 00:10:11.100 I like the topics that are in there. 00:10:11.100 --> 00:10:12.580 Just sounds interesting. 00:10:13.180 --> 00:10:14.040 Yeah, it sounds really cool. 00:10:14.040 --> 00:10:20.840 And if you're looking for scientific computation and you're thinking of like, am I going to shell out $2,000 for MATLAB? 00:10:20.840 --> 00:10:23.680 Well, you know, maybe look at some of the Python tools, right? 00:10:23.680 --> 00:10:24.460 It's definitely growing. 00:10:24.460 --> 00:10:24.820 Yeah. 00:10:24.820 --> 00:10:30.440 You know, it's cool for us to think about the future, but what if like machines could think about the future? 00:10:30.440 --> 00:10:32.680 Machines, yeah. 00:10:32.680 --> 00:10:40.280 I really feel like 2016 and 2017 is the year where AI became not something that's always five years in the future, 00:10:40.460 --> 00:10:43.480 but actually something that's starting to take shape in the present. 00:10:43.480 --> 00:10:44.060 Yeah. 00:10:44.060 --> 00:10:47.760 And it now affects everybody with all of their speaking devices. 00:10:47.760 --> 00:10:48.440 Yeah. 00:10:48.440 --> 00:10:54.160 And, you know, we could be mean and we could say, hey, Amazon thing, order us. 00:10:54.160 --> 00:10:56.020 But we won't do that. 00:10:56.020 --> 00:11:00.660 The thing, the item I want to talk about for number four here is something called universe. 00:11:00.660 --> 00:11:10.580 And it's a way to take games, basically, all sorts of games, and make them available as ways for AIs to experience the world. 00:11:10.580 --> 00:11:12.040 So here's the deal. 00:11:12.040 --> 00:11:18.120 The thing they put together where you can build an AI, put it into a Docker image, give it to their environment, 00:11:18.120 --> 00:11:22.780 and then they will let it play literally thousands of video games. 00:11:22.780 --> 00:11:25.500 And it can learn from playing the games. 00:11:25.500 --> 00:11:30.160 So you can play like flash-based browser games, other types of games, a whole bunch. 00:11:30.160 --> 00:11:31.540 Like I said, over a thousand environments. 00:11:31.540 --> 00:11:37.080 And the way it plays it is the, so you don't have to integrate with like all these different games. 00:11:37.600 --> 00:11:42.320 Your Docker image just is presented the visual screen that the humans look at. 00:11:42.320 --> 00:11:47.180 And then they send mouse and keyboard events to the games. 00:11:47.180 --> 00:11:48.100 Yeah. 00:11:48.100 --> 00:11:52.180 So they basically just play as if they were a person playing the game. 00:11:52.180 --> 00:11:54.140 So they have the same experience of the game as you. 00:11:54.140 --> 00:11:58.820 But here's all these environments in which you can train and test AIs. 00:11:58.820 --> 00:11:59.520 What do you think? 00:11:59.520 --> 00:12:05.140 It sounds like tic-tac-toe and global thermonuclear war to me. 00:12:05.580 --> 00:12:06.740 Hello, Dr. Falcon. 00:12:06.740 --> 00:12:08.240 Would you like to play a game? 00:12:08.240 --> 00:12:16.920 Well, so what's the, so if you have an AI that has learned a whole bunch of stuff about games, like why? 00:12:16.920 --> 00:12:18.280 Why would you care about this, right? 00:12:18.280 --> 00:12:23.960 Like, well, maybe you're working on a robot and you want to teach the robot to walk around and interact with the world. 00:12:23.960 --> 00:12:26.580 But you don't have the robot finished. 00:12:26.580 --> 00:12:37.140 You could take the smarts of the robot and let it play Counter-Strike or, you know, something for until it gets really good at like not bumping into stuff, like making it through paths. 00:12:37.140 --> 00:12:38.780 And then you could just plug that into your robot. 00:12:38.780 --> 00:12:39.420 I don't know. 00:12:39.420 --> 00:12:42.240 Something like, I mean, this is, this is me totally speculating on the spot. 00:12:42.240 --> 00:12:42.680 I don't know. 00:12:42.680 --> 00:12:43.080 Yeah. 00:12:43.080 --> 00:12:44.580 Just don't give your robot a gun. 00:12:44.580 --> 00:12:45.540 Yes, exactly. 00:12:45.540 --> 00:12:47.400 Because it's going to be really good at it at that point. 00:12:47.400 --> 00:12:48.160 Yeah. 00:12:48.540 --> 00:12:49.060 All right. 00:12:49.060 --> 00:12:55.420 So another thing that I've been doing a lot with lately is working with APIs and HTTP services and stuff. 00:12:55.420 --> 00:13:05.700 And your next item is a pretty interesting deep dive into literally the most popular Python package request, which for those of you don't know, is downloaded 7 million times a month. 00:13:05.700 --> 00:13:06.900 Yeah. 00:13:06.900 --> 00:13:10.460 And it's titled Python Request Deep Dive. 00:13:10.460 --> 00:13:14.680 And it came from Anthony Shaw and he put it on Medium. 00:13:14.680 --> 00:13:17.880 And Anthony's been, I don't even know why I know Anthony. 00:13:17.880 --> 00:13:19.660 I've just known about him for a long time. 00:13:19.660 --> 00:13:26.620 But he's, it's, my first thought was it's going to be just teaching people how to use requests. 00:13:26.620 --> 00:13:27.400 But it's not. 00:13:27.400 --> 00:13:29.300 It's, it's a really cool article. 00:13:29.300 --> 00:13:38.860 He took, what happened was he had, he was on a project to convert a large project from HTTP lib. 00:13:38.860 --> 00:13:42.260 So he wasn't even using URL lib2 or anything. 00:13:42.260 --> 00:13:45.040 HTTP lib into requests. 00:13:45.980 --> 00:13:49.120 And this project was Apache lib cloud. 00:13:49.120 --> 00:14:05.080 with, it was handling stuff like HTTP, HTTPS, REST, JSON, XML, whole bunch of bizarre APIs with over, he lists over 80 client libraries to handle different cloud services. 00:14:05.740 --> 00:14:10.440 And had one connection class that did the encoding and decoding of everything. 00:14:10.440 --> 00:14:12.860 And converted this all. 00:14:12.860 --> 00:14:15.420 And this article is about all the stuff he had to deal with. 00:14:15.420 --> 00:14:22.260 Like dealing with sessions, dealing with authentication, how we test it, doing prepared requests, streams. 00:14:22.960 --> 00:14:25.140 It's just a chock full of stuff. 00:14:25.140 --> 00:14:26.640 And it's not even that long of an article. 00:14:26.640 --> 00:14:27.940 So I think he did a good job. 00:14:27.940 --> 00:14:29.220 Yeah, that sounds really cool. 00:14:29.220 --> 00:14:31.580 I haven't had a chance to read it, but I definitely bookmarked it. 00:14:31.580 --> 00:14:33.220 You know, Anthony Shaw is a great guy. 00:14:33.220 --> 00:14:34.100 He's doing cool stuff. 00:14:34.100 --> 00:14:37.080 He talked about lib cloud on podcast init. 00:14:37.080 --> 00:14:40.120 I'm afraid I don't remember the number, but you can listen to him there. 00:14:40.120 --> 00:14:41.360 And that's, that's really cool. 00:14:41.360 --> 00:14:42.680 It's a cool project. 00:14:42.880 --> 00:14:49.260 And this sounds like a pretty serious real world upgrade from one library to another sort of example. 00:14:49.260 --> 00:14:52.180 And I think there's probably a lot of lessons people can get from this. 00:14:52.180 --> 00:14:58.700 And one of the, one of the neat things he has in here is he uses a tool called requests mock. 00:14:58.700 --> 00:15:05.820 And I looked through this, the API for this, and it really is pretty cool. 00:15:05.820 --> 00:15:12.280 So my, my philosophy on mocks is to, to really only mock what you absolutely have to have to do. 00:15:12.280 --> 00:15:18.780 Not everything, but some of your testing should be using mocks when you're dealing with outside resources. 00:15:18.780 --> 00:15:23.740 And, you know, an HTTP request clearly is dealing with an outside resource. 00:15:23.740 --> 00:15:29.120 But the API for this is very, very simple and very powerful. 00:15:29.120 --> 00:15:30.440 And I got to try it out. 00:15:30.440 --> 00:15:30.980 Looks neat. 00:15:30.980 --> 00:15:33.680 I hadn't heard of request mock, requests mock. 00:15:33.680 --> 00:15:35.280 And that sounds like super useful. 00:15:35.280 --> 00:15:35.780 Cause you're right. 00:15:35.780 --> 00:15:41.980 That's one of the places if you're doing testing, you really don't want to have to set up the service and configure it in test mode or whatever. 00:15:41.980 --> 00:15:45.840 Now that was dealing with APIs on the internet. 00:15:45.840 --> 00:15:48.100 How about desktop applications? 00:15:48.100 --> 00:15:48.960 Yeah. 00:15:48.960 --> 00:15:51.320 So let's talk about Python and desktop applications. 00:15:51.320 --> 00:15:55.460 I certainly, you can build interesting desktop applications. 00:15:55.460 --> 00:16:03.620 You know, Dropbox is a real world example of, you know, probably the most widely deployed Python desktop app in the world. 00:16:03.620 --> 00:16:10.260 Cause that client thing that I see spending right now in my little notification bar, that is all Python. 00:16:10.260 --> 00:16:11.040 Okay. 00:16:11.040 --> 00:16:15.180 Python two, seven, I believe they're working on upgrading to Python three, but right now it's two, seven. 00:16:15.180 --> 00:16:16.440 And that's interesting. 00:16:16.440 --> 00:16:27.480 You can use a lot of different technologies, but I kind of feel like there's just something missing to make Python a first class environment for building desktop applications. 00:16:28.000 --> 00:16:37.080 So we've had TK Ender for a long time and that's sort of built in, but I always feel like that looks, I don't know, super out of place, especially on like Mac or windows. 00:16:37.080 --> 00:16:44.320 It looks much more like it belongs in a, and sort of a UNIX, Linux space, but even there, it doesn't look super fabulous. 00:16:44.320 --> 00:16:50.060 It looks like the TK stuff that I was using with TCL when I was in college a long time ago. 00:16:50.060 --> 00:16:50.440 Exactly. 00:16:50.440 --> 00:16:53.020 And it totally works and you can do it and, and so on. 00:16:53.140 --> 00:16:56.960 So there's what the thing I want to highlight is a Reddit conversation. 00:16:56.960 --> 00:16:57.740 It's not a link. 00:16:57.740 --> 00:16:59.720 It's just a back and forth on Reddit. 00:16:59.720 --> 00:17:04.400 What's the community's favorite for developing OS 10 applications with Python? 00:17:04.400 --> 00:17:07.220 So there's a couple of people that weighed in by far. 00:17:07.220 --> 00:17:14.120 I think PyQt came in as the most highly voted up. 00:17:14.120 --> 00:17:16.300 And have you done anything with Qt? 00:17:16.300 --> 00:17:18.720 I did a small project with him a long time ago. 00:17:18.980 --> 00:17:19.180 Yeah. 00:17:19.180 --> 00:17:24.920 The thing I like about Qt is it, the stuff that comes out of it looks native. 00:17:24.920 --> 00:17:26.260 It's based on C++. 00:17:26.260 --> 00:17:27.960 So it starts super fast. 00:17:27.960 --> 00:17:31.160 It feels like an app that belongs wherever it's running. 00:17:31.160 --> 00:17:32.260 And I think that's cool. 00:17:32.260 --> 00:17:37.140 The challenge with this is you've got PyQt, the package, and you've got PySide. 00:17:37.140 --> 00:17:43.100 And these have been sort of competing, not entirely compatible ways of writing this code. 00:17:43.100 --> 00:17:48.960 I think PySide is the better licensing model, but it's, if I recall correctly, 00:17:48.960 --> 00:17:52.100 it only supports Qt4 and Qt is on Qt5. 00:17:52.100 --> 00:17:54.880 And so there's just all this sort of like, oh, it almost works. 00:17:54.880 --> 00:17:58.200 It's kind of hard to deploy Qt on the various machines. 00:17:58.200 --> 00:18:00.440 You've got to, it's sort of a heavyweight install and so on. 00:18:00.440 --> 00:18:01.500 This should be getting better. 00:18:01.500 --> 00:18:08.800 I think Qt, the company that runs Qt is bringing PySide back in and going to modernize it. 00:18:08.800 --> 00:18:11.480 But that's not coming out until the end of this year, probably. 00:18:11.700 --> 00:18:13.580 So one vote was for Qt. 00:18:13.580 --> 00:18:14.220 That was cool. 00:18:14.220 --> 00:18:15.980 Another one was for TK. 00:18:15.980 --> 00:18:19.760 Simple, avoids dependencies, but like we already talked about that. 00:18:19.760 --> 00:18:21.780 Kivy, Kivy definitely got a vote. 00:18:21.780 --> 00:18:25.520 But Kivy is much more, it's not sort of a desktop app feeling. 00:18:25.520 --> 00:18:27.800 It's more like, like almost like games. 00:18:27.800 --> 00:18:29.840 I think its origins were in games. 00:18:29.840 --> 00:18:34.040 So what you get is, is it doesn't really have a native feel, right? 00:18:34.040 --> 00:18:35.780 So that's, that's not that great. 00:18:35.780 --> 00:18:39.060 I think, I think some people are using it for kiosks and stuff. 00:18:39.200 --> 00:18:39.880 Yeah, yeah. 00:18:39.880 --> 00:18:40.820 And that's not bad. 00:18:40.820 --> 00:18:44.460 I know it does a great thing, great stuff on, on mobile as well. 00:18:44.460 --> 00:18:46.520 There's some debate whether that was the right choice. 00:18:46.520 --> 00:18:47.940 There's Toga, which is really cool. 00:18:47.940 --> 00:18:53.640 Toga from the Beware guys, but it's also, Toga is like real early, doesn't have support for all the APIs and stuff. 00:18:54.000 --> 00:19:08.000 So I kind of want to point this out to just say like, you know, to keep raising the issue like, hey, Python community, like it would be awesome if there was something that was really clearly fantastic for building apps. 00:19:08.000 --> 00:19:11.000 It's where, where people say, of course you should use this. 00:19:11.000 --> 00:19:13.860 It's as good as Swift for OS X apps. 00:19:13.860 --> 00:19:17.420 It's as good as WPF for Windows apps or whatever. 00:19:17.420 --> 00:19:18.460 It just, it feels native. 00:19:18.460 --> 00:19:20.400 It's really all coherent. 00:19:20.400 --> 00:19:22.620 And I just don't see that existing yet. 00:19:22.620 --> 00:19:25.160 I think the Beware guys are the closest to it. 00:19:25.160 --> 00:19:26.760 It was an interesting conversation. 00:19:26.940 --> 00:19:32.320 And you've brought it up before that it would, I think you brought it up on Twitter that it'd be cool if we had something kind of like Electron. 00:19:32.320 --> 00:19:33.160 Yeah. 00:19:33.160 --> 00:19:41.120 For those of you who don't know what Electron is, Electron JS is a way to write apps that ship entirely bundled. 00:19:41.120 --> 00:19:43.680 There's just a single thing you run. 00:19:43.680 --> 00:19:47.360 It's an EXE or a binary on Linux or .app on Mac. 00:19:47.360 --> 00:19:55.680 There's zero dependencies and it runs Node.js as the sort of smarts and it embeds its own copy of Chromium, the UI. 00:19:56.440 --> 00:20:02.360 So it's basically you use HTML, JavaScript, and CSS to build your UI and you can use frameworks that make it look native. 00:20:02.360 --> 00:20:05.860 And then you've got Node as the backend to keep this all going. 00:20:05.860 --> 00:20:08.240 There's a few projects that almost do this on Python. 00:20:08.240 --> 00:20:19.720 Like there's one about Django that will let you like ship Django sort of backends that will create GUI looking things where you're doing it with basically Django running locally. 00:20:19.720 --> 00:20:25.360 You know, I don't really want my app to say, do you want this app to act as a server? 00:20:25.940 --> 00:20:26.660 Yeah. 00:20:26.660 --> 00:20:29.800 When I try to run it and they'd be like, this is not supposed to be a server app. 00:20:29.800 --> 00:20:32.560 Like what kind of weird thing have I got a hold of here, right? 00:20:32.560 --> 00:20:37.380 I want something that feels like it drops in and it's basically indistinguishable from a native app. 00:20:37.380 --> 00:20:38.980 And we can dream. 00:20:39.360 --> 00:20:50.920 One step that's a good step in that direction is CX Freeze, which lets you take Python code plus its dependencies and the Python implementation and everything and package it into a redistributable. 00:20:50.920 --> 00:20:53.900 And that just released version 501 in January. 00:20:53.900 --> 00:20:55.580 So that's cool to see that coming along. 00:20:55.580 --> 00:20:57.440 So that's one of the important building blocks at least. 00:20:57.440 --> 00:20:58.100 Okay. 00:20:58.100 --> 00:20:58.800 That's cool. 00:20:58.960 --> 00:21:05.460 Someday I dream of a future where, I don't know, there's some whizzy UI framework with a visual designer for Python. 00:21:05.820 --> 00:21:06.440 It is. 00:21:06.440 --> 00:21:09.200 It's interesting that I don't really think about that that much. 00:21:09.680 --> 00:21:18.920 But the, I mean, you spend so much time in interacting with elements on a desktop, even though we don't develop them very often. 00:21:18.920 --> 00:21:20.040 Not to say it can't be done. 00:21:20.040 --> 00:21:25.160 I just think it could go up a couple levels and it would make a really big difference in the adoption of Python. 00:21:25.160 --> 00:21:25.680 Definitely. 00:21:26.040 --> 00:21:31.940 It's already growing super well, but if you could take over to the desktop market with it as well, then who knows where it would go. 00:21:31.940 --> 00:21:32.520 Yeah. 00:21:32.520 --> 00:21:33.840 Maybe you should do that, Michael. 00:21:33.840 --> 00:21:34.820 You can take it off. 00:21:34.820 --> 00:21:35.220 Yeah. 00:21:35.220 --> 00:21:35.940 I have so much time. 00:21:35.940 --> 00:21:36.900 That seems like a great idea. 00:21:36.900 --> 00:21:37.980 Yeah. 00:21:37.980 --> 00:21:38.400 Okay. 00:21:38.400 --> 00:21:41.020 So if you don't have time for that, what are you doing? 00:21:41.020 --> 00:21:43.200 I'm working on my classes. 00:21:43.200 --> 00:21:47.960 I'm actually working on some stuff that has these things we were talking about in mind. 00:21:47.960 --> 00:21:51.460 It's sort of at the top of my mind, but I'm not ready to announce anything yet. 00:21:51.460 --> 00:21:57.380 But cool, cool projects that I'm working on and I'm, I'm working on a special episode of 00:21:57.380 --> 00:21:58.180 Talk Python To Me. 00:21:58.180 --> 00:22:00.180 We've got episode 100 coming up. 00:22:00.180 --> 00:22:01.180 So I have a special guest. 00:22:01.180 --> 00:22:04.120 I'm not going to announce until I release it, but that one's going to be big. 00:22:04.120 --> 00:22:06.080 I can't believe it's been a hundred already. 00:22:06.080 --> 00:22:06.760 I know. 00:22:06.760 --> 00:22:07.900 Two years. 00:22:07.900 --> 00:22:08.400 I'm amazing. 00:22:08.400 --> 00:22:08.800 Yeah. 00:22:08.800 --> 00:22:14.560 Speaking of, so podcasts, I, I've got a couple coming up, hopefully pretty soon. 00:22:14.560 --> 00:22:15.440 They just need edited. 00:22:15.440 --> 00:22:17.280 Talk to some really great people. 00:22:17.280 --> 00:22:22.720 And then I was interviewed on a podcast called, reflection as a service. 00:22:22.720 --> 00:22:28.120 And, and that was really fun to talk with, somebody else about, test driven 00:22:28.120 --> 00:22:28.560 development. 00:22:28.560 --> 00:22:34.740 And, and, I think I talked about the, testing column that I think I made 00:22:34.740 --> 00:22:36.960 up on the fly while I was talking with you one day. 00:22:36.960 --> 00:22:38.220 We're going to make that a thing. 00:22:38.220 --> 00:22:42.240 So yeah, that's, and then I'm still writing. 00:22:42.240 --> 00:22:43.560 So that's what I'm up to. 00:22:43.560 --> 00:22:43.920 Awesome. 00:22:43.920 --> 00:22:44.160 Yeah. 00:22:44.160 --> 00:22:46.000 You, you got some good reviewers for your book, right? 00:22:46.360 --> 00:22:50.600 Yeah, definitely that most of the, a lot, a big chunk of the pytest, core team has 00:22:50.600 --> 00:22:54.780 helped, agreed to help out and make sure I don't say something stupid. 00:22:54.780 --> 00:22:55.920 So I appreciate that. 00:22:55.920 --> 00:22:56.340 Yeah. 00:22:56.340 --> 00:22:57.340 That's, that's really excellent. 00:22:57.340 --> 00:23:00.560 I feel like we've definitely given people a lot of information this week. 00:23:00.560 --> 00:23:01.620 Definitely. 00:23:01.620 --> 00:23:02.480 It's good. 00:23:02.480 --> 00:23:03.960 And pretty drama free. 00:23:03.960 --> 00:23:05.020 So that's always nice. 00:23:05.020 --> 00:23:06.080 Yeah. 00:23:06.080 --> 00:23:09.320 Well, thanks a lot for talking to me today. 00:23:09.320 --> 00:23:09.800 You bet. 00:23:09.800 --> 00:23:12.740 It was great to share this with you, Brian, and I'll catch up with you next week. 00:23:14.140 --> 00:23:15.940 Thank you for listening to Python Bytes. 00:23:15.940 --> 00:23:18.520 Follow the show on Twitter via at Python Bytes. 00:23:18.520 --> 00:23:21.400 That's Python Bytes as in B-Y-T-E-S. 00:23:21.400 --> 00:23:24.840 And get the full show notes at Pythonbytes.fm. 00:23:24.840 --> 00:23:29.160 If you have a news item you want featured, just visit Pythonbytes.fm and send it our way. 00:23:29.160 --> 00:23:31.880 We're always on the lookout for sharing something cool. 00:23:31.880 --> 00:23:35.260 On behalf of myself and Brian Okken, this is Michael Kennedy. 00:23:35.260 --> 00:23:38.880 Thank you for listening and sharing this podcast with your friends and colleagues.