WEBVTT 00:00:00.001 --> 00:00:05.920 Hello and welcome to Python Bytes, where we deliver Python news and headlines directly to your earbuds. 00:00:05.920 --> 00:00:10.220 This is episode 257, recorded November 3rd, 2021. 00:00:10.220 --> 00:00:12.700 Hey, it's November. Cool. I'm Brian Okken. 00:00:12.700 --> 00:00:13.800 I'm Michael Kennedy. 00:00:13.800 --> 00:00:15.120 I'm Morla Sicarbo. 00:00:15.120 --> 00:00:16.400 Well, welcome, Morla. 00:00:16.400 --> 00:00:21.740 We haven't even really met other than a few seconds ago, so can you tell us who you are? 00:00:21.740 --> 00:00:29.360 Yeah, my name is Morla Sicarbo, and I met Michael Kennedy a couple of weeks ago at a PyBay event. 00:00:29.720 --> 00:00:30.800 In San Francisco. 00:00:30.800 --> 00:00:36.840 A fantastic PyBay event. For people who cannot see it, they should go to pybay.com and just see the graphics. 00:00:36.840 --> 00:00:41.620 This is the conference outside at a food cart area. So awesome. So great to see you there. 00:00:41.620 --> 00:00:46.740 Right. And so I help Grace Law organize that event. 00:00:46.740 --> 00:00:51.120 She and I have been working over the past couple of years, and it's a fantastic community. 00:00:51.120 --> 00:00:57.800 And I've been in San Francisco for the past three years, and I'm actually, I work for the Defense Department. 00:00:59.440 --> 00:01:04.240 I lead a software development team, and we work on optimizing software processes. 00:01:04.240 --> 00:01:06.840 And on the weekends, I'm a commercial pilot. 00:01:06.840 --> 00:01:09.460 So I do fly, and I do teach student pilots. 00:01:09.460 --> 00:01:11.400 So that's, generally speaking, who I am. 00:01:11.400 --> 00:01:12.660 That's so awesome. 00:01:12.660 --> 00:01:13.440 That's cool. 00:01:14.140 --> 00:01:16.020 My side job is a professional pilot. 00:01:16.020 --> 00:01:18.280 Yeah. Including jets, right? 00:01:18.280 --> 00:01:21.740 Yeah, I do fly corporate jets. 00:01:21.740 --> 00:01:24.680 That sounds so fun. I think that's so neat. 00:01:25.680 --> 00:01:33.580 You know, it's good to get away from the keyboard and the offices, especially when, with COVID happening and everything's harder to get out around. 00:01:33.580 --> 00:01:35.600 Like, you really get away. You get up in the sky. 00:01:35.600 --> 00:01:41.820 I do get away, but you got to be careful, right? Because you're going across different ecosystem, right? 00:01:41.840 --> 00:01:48.040 So you got to make sure that you're well protected, that you take in all the precautions that are required to not get sick. 00:01:48.180 --> 00:01:51.140 But it's an adventure. I do like to get around to it. 00:01:51.140 --> 00:01:52.460 Awesome. 00:01:52.460 --> 00:01:56.560 And Teddy, on the live stream, says, you invited James Bond, I think. 00:01:56.560 --> 00:01:58.100 I think we may have, actually. 00:01:58.100 --> 00:01:58.640 Yeah. 00:01:58.640 --> 00:02:00.620 Where do you park your Austin Martin? 00:02:00.620 --> 00:02:01.340 No, seriously. 00:02:01.340 --> 00:02:03.180 Let's kick this off, Brian. 00:02:03.180 --> 00:02:06.640 With something also, Morley, you're also involved with Django stuff, right? 00:02:06.640 --> 00:02:07.220 In San Francisco? 00:02:08.060 --> 00:02:09.500 Yes, just a little bit. 00:02:09.500 --> 00:02:12.960 By the way, first off, I do want to say thank you very much, Michael. 00:02:12.960 --> 00:02:20.300 So many years ago, I was overseas, and I was in Qatar at the time, and I got started learning how to code. 00:02:20.300 --> 00:02:27.980 And Python was the language that was, at least from my perspective, something I could use in my data science perspective. 00:02:27.980 --> 00:02:37.140 And working with you through Talk Python To Me was extremely helpful for me, learning how to code, just being with the community. 00:02:37.480 --> 00:02:38.660 And I think that was extremely helpful. 00:02:38.660 --> 00:02:47.280 It's gotten me in different places, only because I started to learn how to code and got involved with your podcast many years ago. 00:02:47.280 --> 00:02:47.980 So thank you for that. 00:02:47.980 --> 00:02:49.100 That's amazing. 00:02:49.100 --> 00:02:50.080 Thank you so much. 00:02:50.080 --> 00:02:51.340 It really means a lot. 00:02:51.340 --> 00:02:56.300 And it's easy to forget, Brian and I just sit here at our desk and chat about stuff. 00:02:56.300 --> 00:03:03.260 But it really helps connect people, especially if they're new or they're coming from places where there's not a big community they can drop into. 00:03:03.260 --> 00:03:06.620 It helps people get more integrated quicker. 00:03:06.900 --> 00:03:07.460 And I think that's fantastic. 00:03:07.460 --> 00:03:07.480 Yeah. 00:03:07.480 --> 00:03:09.380 And it's just the way you guys talk, right? 00:03:09.380 --> 00:03:18.540 I mean, it's just you're talking to me as opposed to talking to an audience or a group of large crowd or something like that. 00:03:18.540 --> 00:03:22.440 So I'm listening to a podcast, and I'm going, this is relatable. 00:03:22.440 --> 00:03:28.500 And I can actually go out and do a little bit more research on a package on a topic that you guys are talking about. 00:03:28.500 --> 00:03:29.340 So it's really good. 00:03:29.340 --> 00:03:30.200 Nice. 00:03:30.200 --> 00:03:31.120 Yeah, fantastic. 00:03:31.500 --> 00:03:33.400 Speaking of packages, let's talk about Django. 00:03:33.400 --> 00:03:35.880 Yeah, let's start with Django here. 00:03:35.880 --> 00:03:38.340 So I don't do that much Django. 00:03:38.340 --> 00:03:41.960 I do more on the micro framework side of things. 00:03:41.960 --> 00:03:43.840 But Django is super important. 00:03:43.840 --> 00:03:47.220 And when cool stuff happens there, I want to make sure to give it a shout out. 00:03:47.220 --> 00:03:49.000 So we're Django 4. 00:03:49.000 --> 00:03:51.340 I mean, in beta, but still Django 4. 00:03:51.340 --> 00:03:52.780 Morley, have you been tracking this? 00:03:52.780 --> 00:03:53.540 Are you excited about this? 00:03:53.540 --> 00:03:54.580 I am tracking it. 00:03:54.640 --> 00:03:55.700 I'm excited about it. 00:03:55.700 --> 00:03:56.360 Yep, absolutely. 00:03:56.360 --> 00:03:56.700 Yep. 00:03:56.700 --> 00:03:57.980 Yeah, super cool. 00:03:57.980 --> 00:04:01.440 So Django 4.0 beta 1 was released. 00:04:01.440 --> 00:04:06.220 I feel like it was Django 1 for a really long time, and then Django 2, and then, you know what? 00:04:06.220 --> 00:04:07.600 Blow the doors off. 00:04:07.600 --> 00:04:08.840 We'll go 3, 4, 5, 6. 00:04:08.840 --> 00:04:10.620 We're going to be at Django 20 soon enough. 00:04:10.620 --> 00:04:11.120 Right. 00:04:11.440 --> 00:04:12.500 But this is really good news. 00:04:12.500 --> 00:04:17.980 The beta 1, so means feature freeze, bug fixes only type of thing, is out. 00:04:17.980 --> 00:04:21.100 And if you're interested in this, you can try it out now. 00:04:21.100 --> 00:04:25.300 Notable changes here for what's coming along. 00:04:25.300 --> 00:04:31.040 First of all, it's only compatible with Python 3.8 and beyond, which is pretty fantastic. 00:04:31.040 --> 00:04:37.180 And if you want older support, as in all the way back to 3.6, you got to go back to Django 3 series, 3.2. 00:04:37.500 --> 00:04:42.840 So I think that's pretty interesting as well, the rapid adoption of new Python, right? 00:04:42.840 --> 00:04:45.480 This is like two years of Python and not more. 00:04:45.480 --> 00:04:46.840 So things that are new. 00:04:46.840 --> 00:04:50.120 There's stuff about time zones, which I'm not going to bore you with. 00:04:50.120 --> 00:04:52.020 But database stuff is cool, right? 00:04:52.020 --> 00:04:59.560 One of the things that I think Django is really renowned for is its web front end plus database integration, right? 00:04:59.560 --> 00:05:00.720 Wouldn't you say so, Morley? 00:05:00.720 --> 00:05:01.900 Yes, absolutely. 00:05:01.900 --> 00:05:02.340 Yeah. 00:05:02.340 --> 00:05:02.880 Yeah. 00:05:03.220 --> 00:05:10.720 I think it's not just the, well, you have an ORM that's built in, but you've got the admin sections that know about the models and all kinds of stuff. 00:05:10.720 --> 00:05:14.500 We're actually going to come back to that as well later in this episode. 00:05:14.500 --> 00:05:19.060 But one of the new things is functional unique constraints. 00:05:19.060 --> 00:05:24.940 So like I can only insert this record if there's not already one that matches, say, the email address for a user. 00:05:24.940 --> 00:05:32.540 So now what you can do is you can create functionally unique constraints with expressions and database functions. 00:05:32.540 --> 00:05:44.040 So, for example, you could have an index, which is a unique constraint where you have the lowercase of the first name, the lowercase of the second name, descending, I guess, for the index bit. 00:05:44.040 --> 00:05:45.440 But that doesn't really matter for the constraint. 00:05:45.640 --> 00:05:50.100 And then you can give it a name, like first name, last name must be unique constraint. 00:05:50.100 --> 00:05:51.940 And so that's pretty awesome, right? 00:05:51.940 --> 00:05:54.620 You can say, I can't have two users with the same name. 00:05:54.620 --> 00:05:57.680 I'm not sure how practical that is, but, you know, as an example, it makes good sense. 00:05:57.680 --> 00:05:58.240 Yeah. 00:05:58.240 --> 00:06:06.180 Poor Joe Smith or Michael Kennedy, for that matter, like probably going to not make it in after a couple hundred thousand users. 00:06:06.180 --> 00:06:06.860 Let's see. 00:06:06.860 --> 00:06:09.240 They have the script password hasher. 00:06:09.460 --> 00:06:13.820 So you do not, hopefully you are not storing raw passwords. 00:06:13.820 --> 00:06:20.140 Every time I see a website that says your password cannot be more than eight characters, I'm like, that better not be a varchar eight field. 00:06:20.140 --> 00:06:27.260 I don't know what you're doing, but I'm starting to get really worried because the size of the output of a hash is always the same size, regardless of the input. 00:06:27.260 --> 00:06:35.780 Anyway, so new password hasher that's more secure and recommended over what was previously the default of PBKDF2, right? 00:06:36.240 --> 00:06:44.740 It's, however, not the default because you have to now install open SSL 1.0 or above, which is not super high, but it's still not super new version. 00:06:44.740 --> 00:06:45.140 All right. 00:06:45.140 --> 00:06:50.420 Then Redis, there's now a dedicated built-in Redis cache as the caching tier. 00:06:50.420 --> 00:06:53.340 So you can set up caching in Django and say cache here. 00:06:53.340 --> 00:06:55.100 Now one of the options is Redis. 00:06:55.100 --> 00:06:59.980 Yes, you could do that previously, but now it's like a built-in thing. 00:06:59.980 --> 00:07:02.580 So you don't have to do that outside of. 00:07:02.580 --> 00:07:03.000 That's cool. 00:07:03.000 --> 00:07:03.920 Yeah, that's cool, right? 00:07:03.920 --> 00:07:04.780 That's very cool. 00:07:04.780 --> 00:07:05.340 Yeah. 00:07:05.580 --> 00:07:08.860 And then template-based form rendering. 00:07:08.860 --> 00:07:13.600 So enhanced customization of forms, form sets, errors list, and so on using the template engine. 00:07:13.600 --> 00:07:14.660 So pretty cool. 00:07:14.660 --> 00:07:17.800 Not a huge bunch of changes, but they all sound really nice. 00:07:17.800 --> 00:07:18.360 Yeah. 00:07:18.360 --> 00:07:22.860 The support of which Python versions is pretty big, but I mean, come on, people. 00:07:22.860 --> 00:07:24.480 It's an application. 00:07:24.480 --> 00:07:26.340 You can pick your whatever Python version you want. 00:07:26.340 --> 00:07:27.400 Yeah, that's right. 00:07:27.400 --> 00:07:30.580 Out there in the live stream, Alvaro says, 00:07:30.580 --> 00:07:35.940 I guess that dropping versions helps to reduce the number of wheels to build and also to test, right? 00:07:35.940 --> 00:07:37.700 Probably so CI is probably faster. 00:07:37.700 --> 00:07:42.960 You can take advantage of some of the newer things and just count on them being there, which is great. 00:07:43.800 --> 00:07:46.880 Also, speaking of versions, Sam Morley. 00:07:46.880 --> 00:07:47.380 Hey, Sam. 00:07:47.380 --> 00:07:48.240 Great to see you again. 00:07:48.240 --> 00:07:52.020 It says, getting my boss to agree to drop Python 3.4 was a task. 00:07:53.580 --> 00:07:55.260 It's been a while since 3.4 was out. 00:07:55.260 --> 00:07:57.220 I actually remember, I think, where I was. 00:07:57.220 --> 00:07:59.700 I was out in Redlands, California. 00:07:59.700 --> 00:08:01.460 That came out, which is pretty interesting. 00:08:01.460 --> 00:08:03.140 Anyway, I don't know why that came to my mind. 00:08:03.140 --> 00:08:05.060 Is this stuff exciting to you? 00:08:05.060 --> 00:08:07.820 Morley, someone does more Django than probably Brian or me? 00:08:07.820 --> 00:08:09.620 No, it's very exciting to me. 00:08:09.620 --> 00:08:15.920 Just being able to see just the iterations of Django is very, very helpful to the community. 00:08:15.920 --> 00:08:17.500 I started with Django 3. 00:08:17.500 --> 00:08:21.740 So this few iterations have been very helpful, especially Redis. 00:08:21.740 --> 00:08:22.360 Absolutely. 00:08:22.360 --> 00:08:23.780 Yeah, the Redis is exciting. 00:08:23.780 --> 00:08:24.660 Yeah, for sure. 00:08:24.660 --> 00:08:25.100 Brian? 00:08:25.100 --> 00:08:27.400 Well, I have to apologize. 00:08:27.400 --> 00:08:30.560 I don't remember who pushed us this way, but somebody on Twitter said, 00:08:30.560 --> 00:08:37.480 hey, you guys should maybe talk about Py once in a while, like just Py itself, the PY, the application. 00:08:37.480 --> 00:08:42.180 So Py or Py.exe, it's the Python launcher. 00:08:42.180 --> 00:08:45.660 This has been bundled with Python 3.3. 00:08:45.660 --> 00:08:47.480 So it's been there for a while. 00:08:47.480 --> 00:08:52.920 But to be honest, I kind of ignored it because it's a Windows-only thing. 00:08:52.920 --> 00:08:58.920 And I do work on Windows, but I also work in Mac and Linux and multiple environments. 00:08:58.920 --> 00:09:01.920 So I really don't want to change my workflow just for one. 00:09:01.920 --> 00:09:09.480 But the idea is that you just type Py and it picks the latest version that you have installed on your system. 00:09:09.480 --> 00:09:14.880 It's kind of neat, but I didn't really get the feel for it. 00:09:14.880 --> 00:09:29.580 But then Brett Cannon wrote this thing called Py Launcher that is the same thing, but it works on Mac and it works on Linux and it works on a whole bunch of other stuff like Arch Linux. 00:09:30.320 --> 00:09:36.380 Really, anything that Rust can run on, I think it works on, which is like almost everything. 00:09:36.380 --> 00:09:38.560 So this is pretty neat. 00:09:38.560 --> 00:09:39.860 But why is it neat? 00:09:39.860 --> 00:09:43.160 So I'm like, still, why did Brett spend time making this work? 00:09:43.160 --> 00:09:45.920 And so I started changing my workflow for this. 00:09:45.920 --> 00:09:49.140 And I got to say, it's kind of life-changing. 00:09:49.700 --> 00:09:53.160 The big thing is I don't have to care where Python's installed anymore. 00:09:53.160 --> 00:09:56.580 So I have this set up on my Mac. 00:09:56.580 --> 00:10:00.400 I've got it set up on, I included it in the install on Windows. 00:10:00.400 --> 00:10:05.280 And then you just say, like for instance, you can say py-list. 00:10:05.280 --> 00:10:09.680 And you get like all of the, I don't have the example here. 00:10:09.680 --> 00:10:12.280 You get all of the versions listed out. 00:10:12.700 --> 00:10:17.080 And it lists, it tells you where they are too, but you don't really have to care. 00:10:17.080 --> 00:10:23.120 And in the Py Launcher version on Linux or Mac, it shows the paths right away. 00:10:23.120 --> 00:10:28.120 On the Windows version, you have to say list paths, but it's still pretty easy if you want to know where they are. 00:10:28.120 --> 00:10:30.600 But basically, you don't have to care where things are anymore. 00:10:30.600 --> 00:10:36.200 So I also don't have to care where they are in the path, like in my path variable. 00:10:36.200 --> 00:10:40.060 So the Python version I want, is it the first one? 00:10:40.060 --> 00:10:40.800 The second one? 00:10:40.800 --> 00:10:42.500 Did I install something? 00:10:42.660 --> 00:10:43.280 mess it up? 00:10:43.280 --> 00:10:47.280 Like if I install Python 3.10, but I also want to test on 3.6. 00:10:47.280 --> 00:10:48.680 So I installed 3.6 later. 00:10:48.680 --> 00:10:50.640 Where does that show up in the path? 00:10:50.640 --> 00:10:51.980 I don't have to care anymore. 00:10:51.980 --> 00:10:57.080 Because my workflow is mostly around virtual environments. 00:10:57.080 --> 00:11:03.360 So I say like Python-MVNV, and I create a virtual environment. 00:11:03.360 --> 00:11:08.160 And I create it with the most recent Python version, no matter where they are in the path, where they're located. 00:11:08.880 --> 00:11:18.700 And then if I want to test something on 3.8 or 3.9, I can just type pi-3.8 or 3.9. 00:11:18.700 --> 00:11:22.240 And then it just automatically runs that version. 00:11:22.240 --> 00:11:24.920 So I can run a script in Python 3.8 easily like that. 00:11:24.920 --> 00:11:30.240 Or I can run it with, I can create a virtual environment, a 3.8 virtual environment really easily. 00:11:30.740 --> 00:11:35.520 And then I still don't, basically I don't have to care where things are installed anymore. 00:11:35.520 --> 00:11:36.560 And I love that. 00:11:37.000 --> 00:11:50.220 The other thing that I really like, sorry if I missed you hearing you say this, is once you create the virtual environment, subsequent calls to pi will use that environment long as you're either in that directory or in a subdirectory. 00:11:50.220 --> 00:11:53.480 So you don't have to activate the virtual environment. 00:11:53.480 --> 00:11:59.660 Like long as traversing up the hierarchy hits a .ve and vdirectories. 00:11:59.660 --> 00:12:02.880 Like, okay, that's the most appropriate Python. 00:12:02.880 --> 00:12:04.120 Does it work that way? 00:12:04.480 --> 00:12:05.100 That's what it says. 00:12:05.100 --> 00:12:06.280 Like, see the code sample right there? 00:12:06.280 --> 00:12:08.780 Look right underneath the, what's the next paragraph, right? 00:12:08.780 --> 00:12:14.600 It says subsequent uses of pi will then use that virtual environment as long as it is the current or higher directory. 00:12:14.600 --> 00:12:16.480 No environment activation required. 00:12:16.480 --> 00:12:17.540 That's pretty cool. 00:12:17.540 --> 00:12:18.100 Yeah. 00:12:18.100 --> 00:12:18.740 That's very cool. 00:12:18.740 --> 00:12:19.520 That's very cool. 00:12:19.520 --> 00:12:20.400 It's so nice. 00:12:20.400 --> 00:12:22.700 Because that way you can set up your file system. 00:12:22.700 --> 00:12:24.380 You don't have to remember to activate it. 00:12:24.380 --> 00:12:30.200 Like, certainly not common, but it is not also uncommon that I'm like, pip install this. 00:12:30.200 --> 00:12:32.620 Oh, it went to the wrong place. 00:12:32.620 --> 00:12:33.320 You know what I mean? 00:12:34.400 --> 00:12:34.640 Yeah. 00:12:34.640 --> 00:12:36.860 Configuration is extremely important, right? 00:12:36.860 --> 00:12:38.080 So this is, this is very good. 00:12:38.080 --> 00:12:38.300 Yeah. 00:12:38.300 --> 00:12:38.980 Very good. 00:12:38.980 --> 00:12:39.420 Yeah. 00:12:39.420 --> 00:12:39.620 Yeah. 00:12:39.620 --> 00:12:45.420 And Zdocs on Livestream says, what's the main difference from this to pi e and v? 00:12:45.420 --> 00:12:47.180 I think that that's one of them, right? 00:12:47.180 --> 00:12:49.620 Pi e and v, you've got to do pi e and v run. 00:12:49.620 --> 00:12:51.220 You've got to like start the shell. 00:12:51.220 --> 00:12:56.320 And it's kind of, and I think this one is sort of, it's more like node packages or node modules. 00:12:56.320 --> 00:12:59.220 Like as long as it finds something there, like, okay, that's the project I'm in. 00:12:59.220 --> 00:12:59.940 Let's run. 00:13:00.360 --> 00:13:00.480 Yeah. 00:13:00.480 --> 00:13:06.980 And pi e and v does these shim things to change which, which you can set up, which one you find. 00:13:06.980 --> 00:13:08.960 And I just, that, I don't know. 00:13:08.960 --> 00:13:10.220 That makes it weird to me. 00:13:10.220 --> 00:13:14.000 It makes my, my system have state that I have to remember. 00:13:14.000 --> 00:13:14.340 That's true. 00:13:14.340 --> 00:13:14.640 Yeah. 00:13:14.640 --> 00:13:14.820 Yeah. 00:13:14.820 --> 00:13:14.980 Yeah. 00:13:14.980 --> 00:13:16.800 We've activated Python 3.7. 00:13:16.800 --> 00:13:18.580 So now that's, it stays that way. 00:13:18.580 --> 00:13:19.120 Yeah. 00:13:19.120 --> 00:13:20.000 Until you change it, right? 00:13:20.000 --> 00:13:20.200 Okay. 00:13:20.200 --> 00:13:24.620 So anyway, this has changed my life for the better and it's, it's great. 00:13:24.620 --> 00:13:25.840 So thanks Brett. 00:13:25.840 --> 00:13:26.380 Yeah. 00:13:26.380 --> 00:13:28.000 And now I use it on windows too. 00:13:28.000 --> 00:13:28.380 So. 00:13:28.380 --> 00:13:29.200 Fantastic. 00:13:29.200 --> 00:13:30.200 All right. 00:13:30.200 --> 00:13:30.980 Up next. 00:13:30.980 --> 00:13:34.680 Oh, I almost closed, closed what you're talking about more than. 00:13:34.680 --> 00:13:35.580 Yeah. 00:13:35.580 --> 00:13:37.360 You're on the data science side of the world. 00:13:37.360 --> 00:13:37.880 Yeah. 00:13:37.880 --> 00:13:38.260 Now. 00:13:38.260 --> 00:13:39.940 So bring us some data science news. 00:13:39.940 --> 00:13:40.840 No, this is good. 00:13:40.840 --> 00:13:41.040 Right. 00:13:41.040 --> 00:13:43.620 So this is this data of AI report 2021. 00:13:43.620 --> 00:13:46.080 It's a pretty extensive report. 00:13:46.080 --> 00:13:52.920 It comes out every year, just surveying across the world, really just the trends on data science. 00:13:52.920 --> 00:13:56.820 And so at the very top there, it has the actual report. 00:13:56.820 --> 00:14:07.780 It's a, it's a PowerPoint version, but in this report, it highlights just the need for transformers being used, not just for NLP, right? 00:14:07.780 --> 00:14:12.460 So for, you know, looking at texts, but it's also looking at audio. 00:14:12.460 --> 00:14:17.640 It's also looking at video and it's also looking at like, you know, protein transcription, for example. 00:14:17.640 --> 00:14:25.460 So it's transformers are going beyond what they were intended to be, which was just primarily just NLP. 00:14:25.460 --> 00:14:26.120 Right. 00:14:26.120 --> 00:14:26.360 Yeah. 00:14:26.360 --> 00:14:27.920 Give us a quick definition of a transformer. 00:14:27.920 --> 00:14:33.800 This is, yeah, like you say, out of the natural language processing side of ML, right? 00:14:33.800 --> 00:14:34.240 Right. 00:14:34.240 --> 00:14:36.740 So it's, it's, it's, it's basically a sequence to sequence. 00:14:36.740 --> 00:14:45.280 So it's, it's taking a text from say English and converting it into an equivalent text into French or something else. 00:14:45.280 --> 00:14:45.540 Right. 00:14:45.540 --> 00:14:54.100 So, having a natural language processor transformer that can do that in a rather efficient basis, is the whole idea of transformer space. 00:14:54.100 --> 00:15:01.240 So it's basically taken, again, tokens or just sequence from one language to another language. 00:15:01.240 --> 00:15:07.900 And so, what, what this is saying now is that it, it isn't just constrained to just NLP. 00:15:07.900 --> 00:15:08.140 Right. 00:15:08.140 --> 00:15:16.960 So now you can use it for looking at large data sets that are, audio or large data sets that are, you know, imagery. 00:15:16.960 --> 00:15:20.420 And then converting that into something that's, that you intended to do. 00:15:20.420 --> 00:15:27.240 So you're sticking those models, transfer learning, essentially taking the transfer learning from one model into another set of models. 00:15:27.240 --> 00:15:28.140 That's essential. 00:15:28.140 --> 00:15:28.840 What is this talking? 00:15:29.000 --> 00:15:37.560 The idea here is that you're moving away from just NLP that you use in it for computer vision, as it says down there, and even protein structure prediction. 00:15:37.560 --> 00:15:45.520 This is important to me because I actually, Michael, I don't know if we're still in the early, I spent some time in Qatar and I was, I was studying Arabic there. 00:15:45.520 --> 00:15:45.740 Right. 00:15:45.740 --> 00:15:53.480 So we would spend like hours just, just going through like transcription, data sets and stuff. 00:15:53.480 --> 00:16:07.160 So now, you know, having a transformer that can actually do that faster and maybe more accurate than, and in the past, I think it's extremely helpful for somebody like, and, the hug and face transformer from a Python perspective. 00:16:07.400 --> 00:16:17.500 It's an extremely popular, package on, GitHub and that most people it's, it's, it's got about 53,000 likes at this point or stars at this point. 00:16:17.500 --> 00:16:17.780 Wow. 00:16:17.780 --> 00:16:20.900 That's, that's comparable to Django and Flask level of popularity. 00:16:20.900 --> 00:16:21.100 Yes. 00:16:21.100 --> 00:16:21.600 Yes. 00:16:21.600 --> 00:16:22.000 Yes. 00:16:22.000 --> 00:16:22.400 Yes. 00:16:22.400 --> 00:16:22.500 Yes. 00:16:22.500 --> 00:16:25.400 And, they formed partnership with, AWS. 00:16:25.400 --> 00:16:31.840 And so now you can spin up, resources on AWS to use, Huggins face, transformers. 00:16:31.840 --> 00:16:35.500 And again, those transformers have models that you can use for transcription. 00:16:35.500 --> 00:16:42.600 You can use them for a vision, a computer vision, or even like it's saying here for, protein structure predictions. 00:16:42.600 --> 00:16:43.160 Yeah. 00:16:43.160 --> 00:16:43.600 Cool. 00:16:43.600 --> 00:16:48.620 I'm very excited about what ML can do for medicine and biology research. 00:16:48.620 --> 00:16:56.640 I think, you know, machine learning and like recommendation engines and all sorts of stuff have good sides and bad sides and all kinds of things. 00:16:56.640 --> 00:17:00.840 But, on the medical side, it seems like it's mostly good, right? 00:17:00.840 --> 00:17:06.440 If, if you could say, actually we can cure this disease cause we've understand how to create something that will bind to this protein. 00:17:06.440 --> 00:17:07.840 Cause now we know it's actual shape. 00:17:07.840 --> 00:17:08.940 Yeah. 00:17:08.940 --> 00:17:09.600 That's great. 00:17:09.600 --> 00:17:10.640 That's, that's incredible. 00:17:10.640 --> 00:17:10.840 Right. 00:17:10.840 --> 00:17:13.920 So predicting those shapes for protein is extremely important. 00:17:13.920 --> 00:17:14.080 Right. 00:17:14.080 --> 00:17:26.500 I studied chemistry in college and, and a little bit of biochemistry when I was in college and in knowing the structures for proteins, it's like extremely important, but it takes a long time to model those, the structures. 00:17:26.500 --> 00:17:26.760 Right. 00:17:26.760 --> 00:17:29.840 Now you can do that pretty easily on a using transformers. 00:17:29.840 --> 00:17:30.900 It's a, it's a good thing. 00:17:30.900 --> 00:17:31.320 Yeah. 00:17:31.320 --> 00:17:35.720 There's probably less well-known ways around more like physical chemistry as well. 00:17:35.720 --> 00:17:35.960 Right. 00:17:35.960 --> 00:17:41.220 Like trying to understand different kinds of batteries and things like that, potentially, you know, don't get all the press. 00:17:41.220 --> 00:17:47.380 Well, I'm, I'm thinking that maybe we're not too terribly far away from universal translators and in AirPods. 00:17:47.380 --> 00:17:48.360 That would be cool. 00:17:48.360 --> 00:17:48.860 Yes. 00:17:48.860 --> 00:17:49.300 Yeah. 00:17:49.300 --> 00:17:52.060 That would be actually pretty amazing. 00:17:52.060 --> 00:17:53.960 I mean, we're pretty close with Google translate. 00:17:53.960 --> 00:17:56.960 You can speak to it and then show it to someone in their language. 00:17:57.080 --> 00:18:04.280 And then they can, I can think you can even make it read back and like, you can really clumsily do it, but what you're envisioning is just like natural conversation. 00:18:04.280 --> 00:18:04.600 Right. 00:18:04.600 --> 00:18:04.880 Yeah. 00:18:04.880 --> 00:18:05.200 Yeah. 00:18:05.200 --> 00:18:06.820 And have it be in their voice too. 00:18:06.820 --> 00:18:09.720 yeah, that's pretty cool. 00:18:09.720 --> 00:18:10.600 That was pretty cool. 00:18:10.600 --> 00:18:14.080 You know, you got to wait five seconds for it to calculate a deep fake, then you can start talking. 00:18:14.080 --> 00:18:19.060 Well now, but like our, our kids are going to be like using these things probably. 00:18:19.060 --> 00:18:19.660 Yeah, I know. 00:18:19.660 --> 00:18:20.960 I think you're totally right there. 00:18:20.960 --> 00:18:21.380 Absolutely. 00:18:21.380 --> 00:18:22.120 Awesome. 00:18:22.120 --> 00:18:22.360 Yeah. 00:18:22.360 --> 00:18:22.640 Yeah. 00:18:22.640 --> 00:18:23.300 Good pick there. 00:18:23.300 --> 00:18:24.100 More like great. 00:18:24.620 --> 00:18:38.220 Before we thank our sponsor, I want to just give a quick shout out to John Sheehan's comment here that Python launcher, the Pi thing that Brian spoke about, looks like a nice package and a better alternative to the Pi alias I created on my Linux laptop. 00:18:38.220 --> 00:18:39.100 Oh man. 00:18:39.100 --> 00:18:47.620 You and me both, I, my, ZSHRC is full of alias this, alias that many of them starting with P to do something with Python. 00:18:47.760 --> 00:18:48.160 Yeah. 00:18:48.160 --> 00:18:55.780 I mean, I used to list like, like makeup aliases for Pi 3.8, Pi 3.9 just to, and then I couldn't remember if I had a dot in it or not. 00:18:55.780 --> 00:18:56.680 Was it 3.8? 00:18:56.680 --> 00:18:56.880 3.8? 00:18:56.880 --> 00:18:57.580 Yeah. 00:18:57.580 --> 00:18:57.960 Anyway. 00:18:57.960 --> 00:18:58.920 Yeah. 00:18:58.920 --> 00:18:59.300 Yeah. 00:18:59.300 --> 00:18:59.920 Cool. 00:18:59.920 --> 00:19:00.740 All right. 00:19:00.740 --> 00:19:04.360 Before we move on though, I do want to tell you about our sponsor shortcut. 00:19:04.360 --> 00:19:05.160 Thank you. 00:19:05.160 --> 00:19:07.440 Shortcut formerly clubhouse for sponsoring the show. 00:19:07.440 --> 00:19:10.420 Check them out at shortcut.com slash Python bites. 00:19:10.420 --> 00:19:12.800 Or Brian, do you know what else that people can do now? 00:19:12.800 --> 00:19:13.340 What? 00:19:13.660 --> 00:19:18.240 We've started adding chapters, chapter images, chapter links. 00:19:18.240 --> 00:19:23.340 So I guess you could even click the chapter link right here in your podcast player or in the podcast show notes. 00:19:23.340 --> 00:19:24.120 So that's pretty awesome. 00:19:24.120 --> 00:19:28.840 But however you get to them, you know, thank you to shortcut for sponsoring this episode. 00:19:28.840 --> 00:19:38.880 They've built simple project management tools that grow with your engineering team and don't get too complex, but are not too simplistic. 00:19:39.340 --> 00:19:42.460 So some of the highlights include team-based workflows. 00:19:42.460 --> 00:19:46.820 So individual teams can use shortcuts, default workflows, or they can customize them. 00:19:46.820 --> 00:20:00.000 Organizational wide goals and roadmaps led like the overall organization define workflows and then tie these smaller team ones into the larger workflow and kind of get a big organization wide view. 00:20:00.500 --> 00:20:02.000 VCS, version control integration. 00:20:02.000 --> 00:20:05.480 So it works with GitHub, GitLab, and Bitbucket. 00:20:05.480 --> 00:20:13.220 And it can tie them, tie your items in your project management back over into what's happening there. 00:20:13.220 --> 00:20:15.600 And you can even do that from the command line, which is cool. 00:20:15.600 --> 00:20:19.820 As almost all web apps should have, but many don't. 00:20:19.820 --> 00:20:21.700 Shortcut has a bunch of keyboards. 00:20:21.700 --> 00:20:33.680 So you can use their power bar and use hotkeys all over their web app to just zoom around because like someone like Brian, who would rather be in Vim mode and not take his hands off the keyboard, can cruise around. 00:20:33.680 --> 00:20:34.300 Nice. 00:20:34.300 --> 00:20:35.680 It does iteration planning. 00:20:35.680 --> 00:20:39.440 It will automatically schedule how that should go along if you don't want to customize it. 00:20:39.440 --> 00:20:45.600 So give it a try over at shortcut.com slash Python bytes because you shouldn't have to manage your project management. 00:20:45.600 --> 00:20:48.380 So yeah, thank you to Shortcut for sponsoring the show. 00:20:48.380 --> 00:20:50.200 Now, let's go back to Django. 00:20:50.200 --> 00:20:53.520 And I'm going to tie this together. 00:20:53.520 --> 00:20:55.780 So Morley has a background in Django. 00:20:55.780 --> 00:20:58.080 Brian, you have clearly a bunch of testing. 00:20:58.080 --> 00:21:00.560 So let's talk about testing Django models. 00:21:00.560 --> 00:21:01.200 Okay. 00:21:01.200 --> 00:21:01.760 Awesome. 00:21:01.760 --> 00:21:01.900 Okay. 00:21:01.900 --> 00:21:02.480 Yeah. 00:21:02.580 --> 00:21:09.880 So one of the problems you might need to do in your test is you are going to create some data models and then you want to do stuff with them, right? 00:21:09.880 --> 00:21:12.300 You want to pass them off to a function or whatever. 00:21:12.300 --> 00:21:14.580 And so that can be a bit of a hassle. 00:21:14.580 --> 00:21:20.820 So I want to tell you about model bakery, which are smart fixtures for better parentheses Django tests. 00:21:20.820 --> 00:21:24.540 That's not quite there, but for better tests for Django code. 00:21:24.540 --> 00:21:31.340 So the idea is it's like Baker or Makaru or something like that, but for Django or our models. 00:21:31.740 --> 00:21:35.680 And it specifically understands things like relationships and whatnot. 00:21:35.680 --> 00:21:36.700 So pretty cool. 00:21:36.700 --> 00:21:43.640 You can come over here and do things like you've got your Django model defined as it does, right? 00:21:43.640 --> 00:21:49.280 Derivation models has fields, which are columns, like email fields, character fields, and so on. 00:21:49.280 --> 00:21:57.760 And then when you want to use it, you just go to the Baker and say make a, you know, in this case, it's like a shop, like online e-commerce shop. 00:21:57.760 --> 00:22:01.840 So you can say shop.purchase history is the namespace of the class. 00:22:01.840 --> 00:22:02.840 And then guess what? 00:22:02.840 --> 00:22:06.560 It'll populate it with customers and emails and all kinds of stuff. 00:22:06.560 --> 00:22:07.140 That's cool, right? 00:22:07.140 --> 00:22:07.960 Yeah, it is. 00:22:07.960 --> 00:22:08.460 It's very cool. 00:22:08.460 --> 00:22:08.980 Yeah. 00:22:09.080 --> 00:22:11.820 And then you could also set up model to model relationships. 00:22:11.820 --> 00:22:18.780 So you can say, I want you to, when I create a purchase history, for example, it also has a products. 00:22:18.780 --> 00:22:23.140 So you can say, make the model to model relationships for me and mock those out as well. 00:22:23.140 --> 00:22:30.520 So then in your test, you can work with your purchase history object and say dot products and then, you know, loop over them, do account, whatever. 00:22:30.520 --> 00:22:35.700 It's like a collection of sub or related models that were baked up for you. 00:22:35.700 --> 00:22:36.620 Yeah. 00:22:36.620 --> 00:22:40.900 You can even go and say, prepare when, prepare something to bake. 00:22:40.900 --> 00:22:47.760 When, when you ask somebody gives you a product, I want you to, or create me a product of five of these. 00:22:47.760 --> 00:22:56.000 And then as you make a purchase history, also use those five as the related object instead of guessing or randomizing or whatever. 00:22:56.000 --> 00:22:56.700 It's cool, right? 00:22:56.700 --> 00:22:57.580 That's very cool. 00:22:57.580 --> 00:22:58.280 Very cool. 00:22:58.280 --> 00:22:58.760 Yeah. 00:22:58.760 --> 00:23:06.740 So if you're out there writing tests for Django, specifically the relationships, I think is where this is, is pretty interesting, but man, it's kind of interesting all over, right? 00:23:06.740 --> 00:23:09.900 It'll, I suspect it'll do things like create emails. 00:23:09.900 --> 00:23:13.100 If the model says, here's an email field and it'll create integers. 00:23:13.100 --> 00:23:16.000 If it says, here's an integer field and just take care of that for you. 00:23:16.000 --> 00:23:17.040 That's very cool. 00:23:17.400 --> 00:23:24.600 So do you know, is it, is it another, like a, another fake system or is it using a faker or something under the hood? 00:23:24.600 --> 00:23:24.880 Do you know? 00:23:24.880 --> 00:23:26.820 No, that is a good question. 00:23:26.820 --> 00:23:28.660 What kind of project? 00:23:28.660 --> 00:23:31.920 I can go find out, I guess. 00:23:31.920 --> 00:23:32.400 No, no, no. 00:23:32.400 --> 00:23:32.940 Like, all right. 00:23:32.940 --> 00:23:34.640 So let's go check out the requirements here. 00:23:34.640 --> 00:23:35.920 It's just Django. 00:23:35.920 --> 00:23:38.240 It has, its only requirement is Django. 00:23:38.240 --> 00:23:38.700 Django. 00:23:38.700 --> 00:23:39.320 Wow. 00:23:39.320 --> 00:23:42.780 It doesn't use like, faker or anything like that. 00:23:42.780 --> 00:23:44.760 So I'm guessing it's its own thing. 00:23:44.760 --> 00:23:45.340 Nice. 00:23:45.340 --> 00:23:45.780 Cool. 00:23:45.780 --> 00:23:46.300 I seem like it. 00:23:46.300 --> 00:23:46.760 Yeah. 00:23:47.040 --> 00:23:47.220 Cool. 00:23:47.220 --> 00:23:47.500 Cool. 00:23:47.500 --> 00:23:48.160 That's very cool. 00:23:48.160 --> 00:23:48.400 Yeah. 00:23:48.400 --> 00:23:48.940 Thanks. 00:23:48.940 --> 00:23:49.640 All right, Brian. 00:23:49.640 --> 00:23:52.000 you got to cover this next one for us or what? 00:23:52.000 --> 00:23:53.960 Yeah, I'll cover this one. 00:23:53.960 --> 00:23:56.280 that's one of my goals. 00:23:56.280 --> 00:23:59.780 so, well, good comeback. 00:24:00.460 --> 00:24:06.700 so, Ned Batchelder, is, maintainer for, coverage.py. 00:24:06.700 --> 00:24:07.760 Excellent tool. 00:24:07.760 --> 00:24:09.920 And he's a great person to have at the helm there. 00:24:09.920 --> 00:24:16.160 but he, he's says that he's got, had requests for like, one of the things you 00:24:16.160 --> 00:24:21.320 can do with coverage is you can incorporate it in your, your testing tool chain and CI and 00:24:21.320 --> 00:24:24.260 stuff to say that coverage has to be at a certain level. 00:24:24.260 --> 00:24:28.820 So you can say has to be a hundred percent if you want to do that, or you can say, well, 00:24:28.820 --> 00:24:30.740 at least what, what is the current percentage? 00:24:30.740 --> 00:24:32.440 And we want to make sure that we don't drop it. 00:24:32.440 --> 00:24:34.380 So you like, let's say you're at 75. 00:24:34.380 --> 00:24:40.340 You want to make sure that we don't drop below 75, but he's had requests for profile thresholds, 00:24:40.340 --> 00:24:42.100 um, which is an interesting idea. 00:24:42.100 --> 00:24:47.480 But instead of giving us profile thresholds, he's, he's got like this proof, proof of 00:24:47.480 --> 00:24:49.520 concept thing called goals.py. 00:24:49.520 --> 00:24:55.520 And it's just a snippet that you can download yourself and try it out, but it's a little tiny 00:24:55.520 --> 00:24:59.340 script, but it, it uses the coverage data after the fact. 00:24:59.340 --> 00:25:03.300 So coverage, generates a report and then you can do things on it. 00:25:03.300 --> 00:25:07.340 But this, what this, goals thing does is it kind of acts like another stage. 00:25:07.340 --> 00:25:11.040 So you can, you can set up these in your pipeline to, to check for these. 00:25:11.040 --> 00:25:16.300 And if, and it'll have a exit code that, indicates to your CI system that it failed. 00:25:16.300 --> 00:25:20.480 But, for instance, you can say, all of the, I want all my tests to be a hundred 00:25:20.480 --> 00:25:25.280 percent covered, but my source code, maybe 85% for those. 00:25:25.640 --> 00:25:31.340 And, but like maybe the HTML part of it, I want to really want, or like all the code 00:25:31.340 --> 00:25:35.060 that is dealing with HTML that I want to make sure that it's really tested. 00:25:35.060 --> 00:25:39.680 So I want a hundred percent coverage there, but in general, you can 90%. 00:25:39.680 --> 00:25:44.480 So he has an example set up, to do just what I said, of that. 00:25:44.480 --> 00:25:50.400 So there's these glob groups that you can say, you know, the 85% for everything that's 00:25:50.400 --> 00:25:53.900 a Python file, except for the tests and then have a different. 00:25:53.900 --> 00:25:54.340 Interesting. 00:25:54.340 --> 00:25:59.160 So the way you basically do it as a CLI thing, and then you pass in. 00:25:59.160 --> 00:25:59.680 Yeah. 00:25:59.680 --> 00:26:05.120 File patterns like star.py or star HTML star.py or whatever. 00:26:05.120 --> 00:26:05.460 Right. 00:26:05.500 --> 00:26:07.300 And you can even do knots, which is interesting. 00:26:07.300 --> 00:26:07.840 Yeah. 00:26:07.840 --> 00:26:12.580 And one of the things he's talking about is just, he wants to, wants to have people 00:26:12.580 --> 00:26:17.420 try this and say, is this kind of, does this satisfy what you wanted or is there something 00:26:17.420 --> 00:26:18.280 else that's needed? 00:26:18.280 --> 00:26:19.780 Do we really need profile? 00:26:19.780 --> 00:26:21.920 I actually would hate to have profile. 00:26:21.920 --> 00:26:22.520 Cause yeah. 00:26:22.520 --> 00:26:22.740 Yeah. 00:26:22.740 --> 00:26:28.280 One quick way to like accomplish profile is just to put the file name as the pattern. 00:26:28.280 --> 00:26:28.940 Right. 00:26:28.940 --> 00:26:32.640 I mean, so it like, this is a superset of profile testing. 00:26:32.800 --> 00:26:33.240 Yeah. 00:26:33.240 --> 00:26:34.000 Potentially. 00:26:34.000 --> 00:26:38.380 But I believe that he's probably right that there's, and there's a link in here 00:26:38.380 --> 00:26:42.320 to say, if you want to comment on this, go to the original feature request and do a comment, 00:26:42.320 --> 00:26:46.220 but there, it's probably right that like, it's not really a profile thing. 00:26:46.220 --> 00:26:51.000 It's that there's different sections of the system that you want to have, yeah, have 00:26:51.000 --> 00:26:55.440 specifics or like for instance, with a knot, you could say, well, everything except for 00:26:55.440 --> 00:26:59.180 there's this one file that I know it's a problem, but we don't care about it. 00:26:59.180 --> 00:27:00.540 maybe exclude. 00:27:00.540 --> 00:27:00.840 Yeah. 00:27:01.360 --> 00:27:03.280 The developer who wrote it quit. 00:27:03.280 --> 00:27:04.320 Nobody understands it. 00:27:04.320 --> 00:27:05.060 We're not touching it. 00:27:05.060 --> 00:27:06.420 Please don't complain to us about it. 00:27:06.420 --> 00:27:08.000 We have no intention of touching it. 00:27:08.000 --> 00:27:10.340 Or maybe it's the splash screen. 00:27:10.340 --> 00:27:15.020 Like, you know, some things throw up a splash image and, you know, really, if that's wrong, 00:27:15.020 --> 00:27:15.500 who cares? 00:27:15.500 --> 00:27:17.280 sort of thing, but. 00:27:17.280 --> 00:27:18.020 That's very cool. 00:27:18.020 --> 00:27:18.560 Yeah. 00:27:18.560 --> 00:27:19.200 It's a good one. 00:27:19.200 --> 00:27:19.760 Nice find. 00:27:19.760 --> 00:27:22.460 And I like the generalization of it. 00:27:22.460 --> 00:27:23.200 Well done, Ned. 00:27:23.200 --> 00:27:23.880 All right. 00:27:23.880 --> 00:27:24.580 More late. 00:27:24.760 --> 00:27:30.380 So there's a lot of stuff about economic news these days, especially, DeFi and 00:27:30.380 --> 00:27:32.140 Ethereum and Bitcoin. 00:27:32.140 --> 00:27:34.600 And, NFTs. 00:27:34.600 --> 00:27:34.920 Right. 00:27:34.920 --> 00:27:36.280 So it's, it's already out there. 00:27:36.280 --> 00:27:36.840 Yeah. 00:27:36.840 --> 00:27:41.840 So my brother is an artist and, worked for a long time doing just like insurance stuff 00:27:41.840 --> 00:27:46.820 and project management stuff and is now started getting into NFT stuff because finally putting 00:27:46.820 --> 00:27:49.860 his, master's degree in art to use, which is fantastic. 00:27:49.860 --> 00:27:50.160 Yeah. 00:27:50.160 --> 00:27:51.600 It's a crazy world. 00:27:51.600 --> 00:27:52.980 It's a crazy world. 00:27:52.980 --> 00:27:58.140 And just the thought about like, making digital assets. 00:27:58.140 --> 00:28:00.160 Digital scarcity, right? 00:28:00.160 --> 00:28:02.640 Like the thing that was digital was you could copy it. 00:28:02.640 --> 00:28:03.640 Right, right, right, right. 00:28:03.640 --> 00:28:07.820 And, and over the past, I mean, I've been looking at this over the past six months or so, 00:28:07.860 --> 00:28:13.100 and I'm just curious, I'm just, you know, where does this go in terms of like, how can 00:28:13.100 --> 00:28:17.300 you use digital assets as scarcity, but, you know, provide value eventually. 00:28:17.300 --> 00:28:23.960 So artists can actually, you know, get paid or, or, or, or make, make use of their, their 00:28:23.960 --> 00:28:27.900 art, make it, make it available out there and get, and get value from it. 00:28:27.900 --> 00:28:33.820 So Ethereum though, is like one of those blockchains that pretty much, I think about, I want to 00:28:33.820 --> 00:28:37.680 say 80 to 90% of all NFTs reside on Ethereum blockchain. 00:28:37.680 --> 00:28:38.180 Right. 00:28:38.180 --> 00:28:38.680 I think so. 00:28:38.680 --> 00:28:39.180 Yeah. 00:28:39.180 --> 00:28:40.060 I think it's definitely popular. 00:28:40.060 --> 00:28:40.500 Yeah. 00:28:40.500 --> 00:28:46.800 And so of course the language there is, solidity, but to interface with, the 00:28:46.800 --> 00:28:51.280 blockchain, there's this library called web3.py, right? 00:28:51.280 --> 00:28:58.680 So instead of, instead of using, JavaScript, you can use, web3.py to actually interface 00:28:58.680 --> 00:29:00.280 with Ethereum blockchain. 00:29:00.280 --> 00:29:05.460 So basically you can write smart contracts there, but you can also, get information 00:29:05.460 --> 00:29:08.160 from the blockchain itself or post information into the blockchain. 00:29:08.160 --> 00:29:12.320 So I, this is something I've found and I'm actually looking into it and I thought I want 00:29:12.320 --> 00:29:13.720 to share that with the community. 00:29:13.720 --> 00:29:14.500 Yeah. 00:29:14.500 --> 00:29:15.160 It's interesting. 00:29:15.160 --> 00:29:15.540 Yeah. 00:29:15.640 --> 00:29:19.860 So there's an Ethereum.org slash Python for Python tutorials. 00:29:19.860 --> 00:29:21.580 There's a quick start. 00:29:21.580 --> 00:29:22.260 Right. 00:29:22.260 --> 00:29:23.180 And so on. 00:29:23.180 --> 00:29:23.380 Yeah. 00:29:23.380 --> 00:29:23.720 Right. 00:29:23.720 --> 00:29:28.120 If you were allowed and you can see, what it takes to actually get it installed and use 00:29:28.120 --> 00:29:30.400 it for, some of the protocols that are required. 00:29:30.400 --> 00:29:34.700 So it's actually a pretty good, I've used it just a couple of times and I'm still playing 00:29:34.700 --> 00:29:38.360 around with it, but I think it's a, instead of using something else, if you're familiar with 00:29:38.360 --> 00:29:41.020 Python, this is a very comfortable transition. 00:29:41.020 --> 00:29:44.600 If you're curious about blockchain or Ethereum, so, yeah. 00:29:44.600 --> 00:29:49.740 So you could build your own platforms and your own integrations, not just own Ethereum 00:29:49.740 --> 00:29:50.260 coins. 00:29:50.260 --> 00:29:50.860 Right. 00:29:50.860 --> 00:29:52.700 And so you can be the old smart contract, right? 00:29:52.700 --> 00:29:58.740 We should just logic essentially, send ether or receive ether or, or if it's NFTs, 00:29:58.740 --> 00:30:03.320 again, how do you interface with the blockchain with, cartography? 00:30:03.320 --> 00:30:08.580 So, so, web three point web three point PY, I think is extremely helpful. 00:30:08.580 --> 00:30:09.860 Yeah. 00:30:09.860 --> 00:30:10.380 Yeah. 00:30:10.460 --> 00:30:13.080 It's neat to see Python applied in some different places. 00:30:13.080 --> 00:30:13.620 Yeah. 00:30:13.620 --> 00:30:14.180 Everywhere. 00:30:14.180 --> 00:30:15.020 Everywhere. 00:30:15.020 --> 00:30:15.340 Right. 00:30:15.340 --> 00:30:15.800 Yeah. 00:30:15.800 --> 00:30:16.120 Everywhere. 00:30:16.120 --> 00:30:18.020 Yep. 00:30:18.020 --> 00:30:18.500 Cool. 00:30:18.500 --> 00:30:19.140 All right. 00:30:19.140 --> 00:30:19.440 Awesome. 00:30:19.440 --> 00:30:19.620 Yeah. 00:30:19.620 --> 00:30:20.320 That's a great find. 00:30:20.320 --> 00:30:21.440 pretty cool. 00:30:21.440 --> 00:30:21.920 Yeah. 00:30:21.920 --> 00:30:22.300 Pretty cool. 00:30:22.300 --> 00:30:23.980 Brian, it's time for extras. 00:30:23.980 --> 00:30:24.580 Extra. 00:30:24.580 --> 00:30:25.420 What you got for us. 00:30:25.420 --> 00:30:26.320 What'd you line up for us here? 00:30:26.320 --> 00:30:28.780 I actually don't have any extras today. 00:30:28.780 --> 00:30:29.600 No extra. 00:30:29.600 --> 00:30:31.460 There's no extra, extra, extra read all about it. 00:30:31.460 --> 00:30:31.920 No. 00:30:31.920 --> 00:30:32.540 All right. 00:30:32.540 --> 00:30:33.800 I'll take care of it. 00:30:33.800 --> 00:30:36.800 I got you covered here as you might imagine. 00:30:36.800 --> 00:30:39.200 So I want to give people an update on McFly. 00:30:39.400 --> 00:30:42.620 I mentioned McFly a little while ago. 00:30:42.620 --> 00:30:43.520 McFly is sweet. 00:30:43.520 --> 00:30:46.560 it's allows you to install it. 00:30:46.560 --> 00:30:53.180 And it's kind of like reverse search of your shell commands, be that bash, Z shell, fish, 00:30:53.180 --> 00:30:54.700 whatever, but way better. 00:30:54.700 --> 00:30:55.120 Right. 00:30:55.160 --> 00:30:59.360 You get like an Emacs interface to your history and you can delete it. 00:30:59.360 --> 00:31:00.440 You can edit your history. 00:31:00.680 --> 00:31:05.040 So if you mistype something and you want to save it or you see like, Oh geez, put the password 00:31:05.040 --> 00:31:05.320 in there. 00:31:05.320 --> 00:31:06.620 I want to get that out of my history file. 00:31:06.620 --> 00:31:07.320 You can do that. 00:31:07.320 --> 00:31:09.200 So you just hit control R after you install it. 00:31:09.200 --> 00:31:12.120 And it gives you this, this awesome interactive view. 00:31:12.120 --> 00:31:16.600 I just want to tell people that I've been playing with this and totally loving it. 00:31:16.600 --> 00:31:19.800 Like now I've, I've taken it for a spin for a while and I really, really dig it. 00:31:19.800 --> 00:31:22.140 I've even set up the, fuzzy matching. 00:31:22.140 --> 00:31:25.920 So it doesn't have to exactly match what I've done in history, which is pretty cool. 00:31:25.920 --> 00:31:29.340 So I could now with some experience, give that a thumbs up. 00:31:29.340 --> 00:31:29.660 Nice. 00:31:29.660 --> 00:31:30.340 Nice. 00:31:30.340 --> 00:31:31.520 Nice. 00:31:31.520 --> 00:31:34.740 Also a couple of exciting things about Python web conference. 00:31:34.740 --> 00:31:38.380 If you're looking to speak somewhere and you want that somewhere to be on the internet, 00:31:38.380 --> 00:31:40.180 you should check out Python web conf. 00:31:40.180 --> 00:31:41.820 This is like a five day conference. 00:31:41.820 --> 00:31:46.280 It's one of the biggest virtual conferences going these days, I think. 00:31:46.280 --> 00:31:52.880 And it's interactive presentations or live presentations over the internet and then, chat and so 00:31:52.880 --> 00:31:53.040 on. 00:31:53.040 --> 00:31:57.260 So, we've had Calvin, one of the organizers of it on before. 00:31:57.260 --> 00:32:04.260 And the news is they've extended their call for papers out into November, November 15th. 00:32:04.260 --> 00:32:07.220 So you got 12 more days, maybe 11 if I'm slow releasing this one. 00:32:07.420 --> 00:32:11.960 And also I'm going to be talking about flask and HTMX over there. 00:32:11.960 --> 00:32:13.180 Cause I'm still psyched about that. 00:32:13.180 --> 00:32:16.840 So that's the next year, early next year, but now people can check that out. 00:32:16.840 --> 00:32:17.360 Nice. 00:32:17.360 --> 00:32:17.660 All right. 00:32:17.660 --> 00:32:18.960 What else have I got for us, Brian? 00:32:18.960 --> 00:32:24.480 So, the new MacBook pros, like the super expensive MacBook pros have come out. 00:32:24.480 --> 00:32:25.840 there's an interesting review. 00:32:25.840 --> 00:32:31.040 I'm not super thrilled with it, but over at ours, they usually do a pretty good job, but I do want to read a fun quote from it. 00:32:31.040 --> 00:32:37.400 And they say, rest assured if you didn't like the direction that Apple has been taking with the MacBook pro for the last five years, 00:32:37.400 --> 00:32:40.260 this laptop feels like an explicit apology for all that. 00:32:40.260 --> 00:32:45.380 The result is it's the best lot, best laptop money can buy from any use cases, provided you have a lot of money. 00:32:45.380 --> 00:32:52.240 But one of the things that I found pretty interesting is the power supply for that thing is 140 Watts. 00:32:52.240 --> 00:32:53.140 Oh, wow. 00:32:53.140 --> 00:32:56.480 That's insane for a laptop that you carry around the power supply. 00:32:56.480 --> 00:32:57.100 Wow. 00:32:57.100 --> 00:33:01.560 So I came across this thing called anchor nano to 65 watt. 00:33:01.680 --> 00:33:07.780 And it's, it's, if you put it up next to, that's not, it's, it's, well, hold on. 00:33:07.780 --> 00:33:15.620 It's barely bigger than the brick that used to charge an iPhone, like an American brick, not a UK brick, which has got to be giant because the size of the plug. 00:33:15.620 --> 00:33:16.180 Right. 00:33:16.240 --> 00:33:18.320 But it's like super small and light. 00:33:18.320 --> 00:33:19.860 And yeah, it seems like it's not enough. 00:33:19.860 --> 00:33:27.100 But with my, I got a MacBook pro max and I've been using it and this 65 watt thing will charge it just fine. 00:33:27.520 --> 00:33:39.620 So unless you're doing like machine learning or video exporting or something that completely nails it, like this will charge like 25% in an hour, even though it's supposed to take a 140 Watts, you can give it this little tiny thing. 00:33:39.620 --> 00:33:42.020 So I haven't done enough to really give it a hundred percent. 00:33:42.020 --> 00:33:42.860 Like absolutely. 00:33:42.860 --> 00:33:43.940 That's going to work all the time. 00:33:43.940 --> 00:33:49.780 But my new plan is to travel with this tiny little thing and like a long USB, C or Thunderbolt cable. 00:33:49.780 --> 00:33:50.420 Interesting. 00:33:50.420 --> 00:33:50.680 Right. 00:33:50.680 --> 00:33:51.880 That's pretty interesting. 00:33:51.880 --> 00:33:52.500 Yeah. 00:33:52.500 --> 00:33:54.120 Could you put two in there? 00:33:54.120 --> 00:33:57.300 I don't think maybe it'll catch fire if you do that. 00:33:57.340 --> 00:33:58.080 I'm not going to do that. 00:33:58.080 --> 00:34:03.860 But like here you have the picture, like it's like less than half the size of the charger, which is pretty interesting. 00:34:03.860 --> 00:34:04.340 Yeah. 00:34:04.340 --> 00:34:06.360 That's a 60 watt charger right there. 00:34:06.360 --> 00:34:07.940 Not the 140 watt charger. 00:34:07.940 --> 00:34:08.940 140. 00:34:08.940 --> 00:34:09.620 All right. 00:34:09.620 --> 00:34:18.580 And finally, I want to say that if people who have an M1, not an M1 max or pro, you can pretty much not have FOMO about this thing. 00:34:18.580 --> 00:34:23.980 Like as far as I can tell, my Mac mini and my much more expensive MacBook pro are exactly the same speed. 00:34:23.980 --> 00:34:24.700 Oh, really? 00:34:24.700 --> 00:34:25.140 Okay. 00:34:25.140 --> 00:34:26.880 I think almost always. 00:34:27.160 --> 00:34:30.840 Except one thing I found is for outputting video. 00:34:30.840 --> 00:34:36.500 I found that I could re-encode or I could encode the videos for TalkBiz on training more efficiently. 00:34:36.500 --> 00:34:43.900 And I re-encoded the entire library, which is like 220, 230 hours in multiple formats. 00:34:43.900 --> 00:34:46.600 It took 14 days of compute time. 00:34:46.600 --> 00:34:49.160 Not I got around to do it in 14 days. 00:34:49.160 --> 00:34:51.860 Like start, it finished 14 days later. 00:34:51.860 --> 00:34:57.760 And it's actually three over three times faster with the M1 max. 00:34:58.460 --> 00:35:00.240 So just like three or four days. 00:35:00.240 --> 00:35:00.760 Yeah. 00:35:00.760 --> 00:35:05.460 It's only five days, which is still a long time, but it's way better than 13, 14 days. 00:35:05.460 --> 00:35:06.040 Let me tell you. 00:35:06.040 --> 00:35:06.300 13, 14 days. 00:35:06.300 --> 00:35:06.840 Yeah. 00:35:06.840 --> 00:35:11.220 So I think also this will have a really interesting knock-on effect for ML. 00:35:11.220 --> 00:35:11.980 Right. 00:35:12.300 --> 00:35:15.900 It's got like the onboard machine learning block. 00:35:15.900 --> 00:35:17.640 And it's got a 32-core GPU. 00:35:17.640 --> 00:35:20.520 I think there's a lot of stuff that's going to be coming along that's pretty interesting there. 00:35:20.520 --> 00:35:20.860 What do you think? 00:35:20.860 --> 00:35:21.640 No, no, no. 00:35:21.640 --> 00:35:22.920 It's absolutely right. 00:35:22.980 --> 00:35:26.480 I have a friend that works for Google, does the same thing that I do. 00:35:26.480 --> 00:35:28.000 And him and I were talking. 00:35:28.000 --> 00:35:36.520 I have just the little version of MacBook Pro, and I wasn't going to wait for another one to come out. 00:35:36.520 --> 00:35:41.780 But it has a lot of the components and a lot of the capacity that I need to do my works. 00:35:41.780 --> 00:35:47.200 Instead of just putting your stuff on like AWS, and now you can run them locally, and it's extremely powerful. 00:35:47.200 --> 00:35:50.860 So this is extremely good, especially M1. 00:35:51.900 --> 00:35:53.720 The new stuff is quite neat. 00:35:53.720 --> 00:35:56.380 It's seriously impressive, as Sam has said out there. 00:35:56.380 --> 00:35:57.040 I totally agree. 00:35:57.040 --> 00:35:57.680 Fair pressure. 00:35:57.680 --> 00:35:58.280 Yeah. 00:35:58.280 --> 00:36:01.920 Morla, anything else you want to throw out for people while you got the mic? 00:36:01.920 --> 00:36:05.320 No, I just want to say thanks to you and Brian, right? 00:36:05.320 --> 00:36:11.240 So again, I've been listening to you guys for a very long time, and I've come this far partly because I've been listening to you guys. 00:36:11.240 --> 00:36:12.140 Just the encouragement. 00:36:12.140 --> 00:36:18.360 I think you guys every day, every time I listen to you guys, you guys are talking to me, not to a large group of audience. 00:36:18.360 --> 00:36:21.580 I think it's extremely helpful to see you guys be part of the community. 00:36:22.140 --> 00:36:24.660 And shout out to Pi Bay in San Francisco. 00:36:24.660 --> 00:36:26.160 Those guys are real cool. 00:36:26.160 --> 00:36:28.620 And Michael, thanks for coming out there and talking to us. 00:36:28.620 --> 00:36:30.240 Yeah, that was a great trip a few weeks ago. 00:36:30.240 --> 00:36:31.280 That was a few weeks ago. 00:36:31.280 --> 00:36:31.960 So it was really good. 00:36:31.960 --> 00:36:34.280 So I want to thank you guys for the work that you guys do. 00:36:34.280 --> 00:36:38.300 And we'll continue to listen to you guys and be part of the community. 00:36:38.300 --> 00:36:39.160 Yeah, thanks. 00:36:39.160 --> 00:36:40.500 Yeah, I really appreciate that. 00:36:40.500 --> 00:36:40.840 Thank you. 00:36:40.920 --> 00:36:43.900 It's a lot of times we put stuff out there and there's not a lot of feedback. 00:36:43.900 --> 00:36:45.520 But you know, people are out there listening. 00:36:45.520 --> 00:36:47.160 Then you meet folks and talk to them. 00:36:47.160 --> 00:36:50.560 You're like, actually, it has an impact, which is really great. 00:36:50.560 --> 00:36:53.140 You know, for me, it has a particular impact, right? 00:36:53.220 --> 00:36:59.640 So like I took a journey and I am where I'm at today because, again, partly because of the work that you guys do. 00:36:59.640 --> 00:37:04.940 I'm listening to you guys doing a lot of the research and following up on a lot of the topics that you guys have on the show. 00:37:05.060 --> 00:37:09.460 So it's taken me a long way because this is because I listen to you guys a lot. 00:37:09.460 --> 00:37:10.640 Thank you so much. 00:37:10.640 --> 00:37:11.140 Nice. 00:37:11.140 --> 00:37:13.340 All right, Brian, we ready for a joke? 00:37:13.340 --> 00:37:13.940 Yeah. 00:37:13.940 --> 00:37:14.800 To show up with a smile? 00:37:14.800 --> 00:37:26.460 Well, I just wanted to comment that maybe the next version of MacBook Pro, you might have to charge it in the laundry room because that's the only one with a plug that's strong enough. 00:37:26.460 --> 00:37:28.200 Yeah, if it gets a 240 volt. 00:37:28.200 --> 00:37:28.860 Yeah, that's right. 00:37:28.860 --> 00:37:31.360 Yeah. 00:37:31.360 --> 00:37:34.560 But the thing is, it almost never runs at that, right? 00:37:34.560 --> 00:37:36.320 It'll go for like 14, 15 hours. 00:37:36.320 --> 00:37:38.200 It's only if you're doing like insane stuff. 00:37:38.200 --> 00:37:46.680 And also, you can plug in three Thunderbolt USB 3 things and each one of those, it'll provide up to 15 watts of output from the laptop. 00:37:46.680 --> 00:37:47.520 Oh, wow. 00:37:47.520 --> 00:37:49.440 So I think it's also trying to pass. 00:37:49.440 --> 00:37:52.440 Yeah, I think it's trying to pass through 45 watts. 00:37:52.440 --> 00:37:56.800 So it needs a charger that can account for how much does the Mac need plus 45 more watts? 00:37:56.800 --> 00:37:57.200 Right. 00:37:57.200 --> 00:38:00.240 Because you plugged it into all these Thunderbolt thingies. 00:38:00.240 --> 00:38:00.600 Okay. 00:38:00.600 --> 00:38:04.040 Anyway, I've been trying to think about why it really needs someone that's so high. 00:38:04.060 --> 00:38:10.200 Chris May is going to hook us up to like a level three DC fast charger. 00:38:10.200 --> 00:38:12.340 Charge that thing up five minutes on the car. 00:38:12.340 --> 00:38:14.680 All right. 00:38:14.820 --> 00:38:19.460 So this one comes to us from the veritable XK CD. 00:38:20.460 --> 00:38:23.260 And it talks to us about programming standards. 00:38:23.260 --> 00:38:26.640 So how standards proliferate. 00:38:26.640 --> 00:38:28.060 See AC chargers. 00:38:28.060 --> 00:38:29.360 Very timely. 00:38:29.360 --> 00:38:30.980 Character encodings. 00:38:30.980 --> 00:38:31.960 Instant messaging. 00:38:31.960 --> 00:38:32.780 And so on. 00:38:32.780 --> 00:38:35.000 I'm thinking network protocols. 00:38:35.000 --> 00:38:39.140 Remember, this is a follow on from the joke of what is soap? 00:38:40.020 --> 00:38:41.020 And then rest. 00:38:41.020 --> 00:38:42.060 And then rest. 00:38:42.060 --> 00:38:43.560 What the heck was wrong with soap? 00:38:43.560 --> 00:38:46.060 I know GPRC is better than rest. 00:38:46.060 --> 00:38:48.360 Ah, the torture never ends. 00:38:48.360 --> 00:38:48.560 Okay. 00:38:48.560 --> 00:38:49.620 So this is a follow up from that. 00:38:49.620 --> 00:38:54.940 And here is a man and woman developer saying, talking, says situation. 00:38:54.940 --> 00:38:56.720 There are 14 competing standards. 00:38:56.720 --> 00:38:57.260 14. 00:38:57.260 --> 00:38:58.360 Ridiculous. 00:38:58.700 --> 00:39:02.600 We need to develop one universal standard that covers everyone's use cases. 00:39:02.600 --> 00:39:03.140 Yeah. 00:39:03.140 --> 00:39:03.960 Soon. 00:39:03.960 --> 00:39:04.980 Situation. 00:39:04.980 --> 00:39:06.620 There are 15 competing standards. 00:39:06.620 --> 00:39:09.140 Yeah. 00:39:09.140 --> 00:39:10.060 Yeah. 00:39:10.060 --> 00:39:10.740 Yeah. 00:39:10.740 --> 00:39:10.940 Yeah. 00:39:10.940 --> 00:39:14.820 The only thing going in the other direction is cellular standards. 00:39:14.820 --> 00:39:15.600 They seem to be. 00:39:15.600 --> 00:39:16.020 Oh, really? 00:39:16.020 --> 00:39:16.500 Lessing. 00:39:16.500 --> 00:39:17.560 So. 00:39:17.560 --> 00:39:19.160 But Wi-Fi is going crazy. 00:39:19.160 --> 00:39:24.160 But anyway, it's just one standard, but it comes out with a new version about every six months. 00:39:24.160 --> 00:39:27.920 Good thing they don't bake those into hardware and chips and stuff. 00:39:27.920 --> 00:39:28.360 Oh, wait. 00:39:28.360 --> 00:39:30.520 I think they write. 00:39:30.520 --> 00:39:31.540 That's a good thing they do. 00:39:31.540 --> 00:39:32.880 I'd be out of business if they didn't. 00:39:32.880 --> 00:39:33.400 Exactly. 00:39:33.400 --> 00:39:33.780 You got to. 00:39:33.780 --> 00:39:35.260 The testing never ends. 00:39:35.260 --> 00:39:35.680 Fantastic. 00:39:35.680 --> 00:39:36.360 Yeah. 00:39:36.360 --> 00:39:37.140 Thanks, Michael. 00:39:37.140 --> 00:39:38.160 Thanks, Morley. 00:39:38.160 --> 00:39:39.420 This was a really fun episode. 00:39:39.420 --> 00:39:39.980 Yep. 00:39:39.980 --> 00:39:40.620 Thank you very much. 00:39:40.620 --> 00:39:41.240 Thanks for the invite. 00:39:41.240 --> 00:39:42.000 Appreciate it. 00:39:42.000 --> 00:39:46.240 Thanks, everybody on the chat and on the stream for watching. 00:39:46.240 --> 00:39:46.780 Bye. 00:39:46.780 --> 00:39:47.160 Bye. 00:39:47.160 --> 00:39:47.700 Bye. 00:39:47.700 --> 00:39:49.580 Thanks for listening to Python Bytes. 00:39:49.580 --> 00:39:52.400 Follow the show on Twitter via at Python Bytes. 00:39:52.400 --> 00:39:55.520 That's Python Bytes as in B-Y-T-E-S. 00:39:55.520 --> 00:39:58.380 Get the full show notes over at pythonbytes.fm. 00:39:58.380 --> 00:40:03.280 If you have a news item we should cover, just visit pythonbytes.fm and click submit in the 00:40:03.280 --> 00:40:03.700 nav bar. 00:40:03.700 --> 00:40:05.820 We're always on the lookout for sharing something cool. 00:40:05.820 --> 00:40:10.360 If you want to join us for the live recording, just visit the website and click live stream 00:40:10.360 --> 00:40:13.240 to get notified of when our next episode goes live. 00:40:13.240 --> 00:40:17.620 That's usually happening at noon Pacific on Wednesdays over at YouTube. 00:40:17.880 --> 00:40:21.000 On behalf of myself and Brian Okken, this is Michael Kennedy. 00:40:21.000 --> 00:40:24.720 Thank you for listening and sharing this podcast with your friends and colleagues.