WEBVTT 00:00:00.040 --> 00:00:05.320 Hello and welcome to Python Bytes, where we deliver Python news and headlines directly to your earbuds. 00:00:05.880 --> 00:00:11.840 This is episode 456, recorded November 3rd, 2025. I am Michael Kennedy. 00:00:12.180 --> 00:00:13.160 And I am Brian Okken. 00:00:13.480 --> 00:00:19.420 And Brian, I'm getting Guns N' Roses vibes. It's raining outside, it's November. Come on. 00:00:20.000 --> 00:00:20.640 Guns N' Roses? 00:00:21.080 --> 00:00:27.760 That's one of their songs. That's like, once they were kind of cool, then they became some other band that was more of like love ballads. 00:00:28.240 --> 00:00:29.580 November Rain, it's a Guns N' Roses song. 00:00:29.760 --> 00:00:34.520 Oh, okay. November rain. Okay. Got it. I'm like, yeah, it's, it's rainy in the Northwest. That's 00:00:34.560 --> 00:00:39.100 just not that much news, but no, that's like, no, I got to go back. We're going to do music 00:00:39.220 --> 00:00:44.860 that completely entirely encompasses all of Pearl Jam, all the Nirvana, all the Soundgarden period. 00:00:46.100 --> 00:00:50.740 November rain or rainy in the Northwest, like the whole grunge movement. Right. Yeah, definitely. 00:00:51.400 --> 00:00:55.920 And I would just, I mean, look, I'm getting some support from the audience here. Rhett out there 00:00:55.940 --> 00:00:57.720 already saying November Rain is one of the greatest 00:00:58.040 --> 00:00:59.840 rock ballads of all time. And I agree. 00:01:00.000 --> 00:01:02.000 Thank you, Rhett. Although I will throw a Tesla out there 00:01:02.080 --> 00:01:04.160 as the greatest rock ballads of all time 00:01:04.320 --> 00:01:05.920 band. Alright. Are we 00:01:06.440 --> 00:01:07.040 off track yet, Brian? 00:01:07.820 --> 00:01:10.020 This episode is brought to you by us. 00:01:10.880 --> 00:01:12.020 We've got a bunch of fun things. 00:01:12.500 --> 00:01:12.980 We have 00:01:14.100 --> 00:01:15.520 Tesla the band. Not the 00:01:15.800 --> 00:01:17.420 scientist. Not the company. 00:01:17.760 --> 00:01:19.980 We both have awesome books. You should check them 00:01:20.160 --> 00:01:22.200 out. Brian, yours has been around for a while. 00:01:22.560 --> 00:01:23.920 I don't know if you're ever going to write another one, 00:01:24.020 --> 00:01:25.900 but we'll see. And how many 00:01:25.920 --> 00:01:27.440 How many people write the second book, right? 00:01:27.740 --> 00:01:30.380 You know, I imagine that you might do something like this. 00:01:30.580 --> 00:01:31.960 And my book's going really well. 00:01:32.100 --> 00:01:33.720 The Talk Python in production. 00:01:34.360 --> 00:01:37.840 Like, hey, maybe we could do simplified, affordable, but still fast and professional. 00:01:38.240 --> 00:01:40.740 Posting of our apps without hyperscale clouds. 00:01:41.120 --> 00:01:43.820 And 100 services and cloud engineers and all that. 00:01:44.060 --> 00:01:49.640 And if you want to be part of this show live, you can join us live. 00:01:50.160 --> 00:01:51.040 Are we changing times, Ryan? 00:01:51.180 --> 00:01:51.900 It's 11. 00:01:52.380 --> 00:01:53.320 We're good now, isn't it? 00:01:53.800 --> 00:01:57.180 Well, as far as my work schedule goes right now, 11 works. 00:01:57.720 --> 00:01:58.160 All right, everyone. 00:01:58.200 --> 00:02:00.000 I just want you to know what I'm out here doing for you. 00:02:00.080 --> 00:02:04.980 So I'm going to have to go back and edit 455 episodes where we said, 00:02:05.260 --> 00:02:07.120 watch the live stream at Monday at 10 a.m. 00:02:07.460 --> 00:02:10.420 I'm going to have to replace that with watch the live stream at Monday at 11 a.m. 00:02:10.500 --> 00:02:11.960 You're not actually going to do that, are you? 00:02:12.180 --> 00:02:13.680 No, I'm not going to do that. 00:02:16.220 --> 00:02:17.580 Nonetheless, AI can do it for me. 00:02:17.720 --> 00:02:18.240 That's not happening. 00:02:18.840 --> 00:02:21.740 But going forward, if you want to join us for the live stream, 00:02:21.780 --> 00:02:24.640 please do so at exactly this time, 11 a.m. 00:02:24.920 --> 00:02:26.580 I'm sure there's some sort of time zone weirdness 00:02:26.620 --> 00:02:27.440 because we just changed time, 00:02:27.620 --> 00:02:31.180 but Pacific Standard Time until it becomes daylight time. 00:02:31.340 --> 00:02:32.060 We'd love to have you. 00:02:32.420 --> 00:02:34.820 We'd love people in the audience with feedback and thoughts 00:02:35.000 --> 00:02:35.840 and all that kind of fun stuff. 00:02:36.120 --> 00:02:36.680 Check out the newsletter. 00:02:37.180 --> 00:02:37.660 It's really great. 00:02:37.780 --> 00:02:38.480 We've been telling you about it. 00:02:38.720 --> 00:02:39.860 Sign up, pythonbytes.fm/. 00:02:40.440 --> 00:02:41.780 I'll just go there and click the newsletter button. 00:02:42.040 --> 00:02:43.460 All right, Brian, what are you clicking first? 00:02:44.800 --> 00:02:48.260 So I want to talk about some news that came out last week. 00:02:49.880 --> 00:02:52.240 There's on the wrong one. 00:02:52.320 --> 00:02:52.700 There we go. 00:02:54.080 --> 00:02:58.800 The PSF, the PSF wanted to try to get, try to get some money from the National Science 00:02:59.060 --> 00:02:59.140 Foundation. 00:02:59.680 --> 00:02:59.760 Actually. 00:03:00.720 --> 00:03:04.280 So this was in January of 20th, January of 2025. 00:03:05.260 --> 00:03:11.040 There was a, a really kind of an interesting grant under the safety, security, and privacy 00:03:11.400 --> 00:03:18.260 of open source ecosystems program, which totally seems like a perfect thing for the PSF to try 00:03:18.260 --> 00:03:20.300 to get some money for Seth and others 00:03:21.100 --> 00:03:22.480 to make sure that the PSF 00:03:23.060 --> 00:03:24.260 and Python code is all secure. 00:03:24.980 --> 00:03:26.560 Yeah, especially I think the supply chain 00:03:26.800 --> 00:03:28.060 side, if I remember correctly. 00:03:28.400 --> 00:03:28.800 Something like that. 00:03:30.000 --> 00:03:32.460 However, and they put in a ton of work 00:03:33.620 --> 00:03:34.220 and then 00:03:36.300 --> 00:03:37.820 our current administration 00:03:38.560 --> 00:03:39.960 says in order to 00:03:40.560 --> 00:03:42.240 get this money, you have to 00:03:43.300 --> 00:03:44.320 agree that 00:03:44.720 --> 00:03:45.900 you will basically 00:03:46.480 --> 00:03:48.220 not have any sort of diversity 00:03:48.240 --> 00:03:55.740 anything is part of your whatever. And, you know, what's going on? You have to affirm that we do not 00:03:55.880 --> 00:04:00.820 and will not during the term of this financial assistance award operate any programs or advance 00:04:01.120 --> 00:04:09.000 any or promote DEI or discriminatory equity, whatever. All that normal, wacky politics stuff 00:04:09.120 --> 00:04:14.340 that's going on in the US right now. Well, that's a tough bite for the PSF because it wouldn't just 00:04:14.360 --> 00:04:19.120 be the security stuff. It would be everything the PSF does. And in the mission statement, 00:04:19.130 --> 00:04:24.520 the mission statement of the Python Software Foundation is to promote, protect, and advance 00:04:24.670 --> 00:04:29.460 the Python programming language and to support and facilitate the growth of a diverse and 00:04:29.700 --> 00:04:34.860 international community of Python programmers. Does that violate? We don't know. So they like, 00:04:35.160 --> 00:04:39.880 you know, checked with a bunch of people and basically said it's too risky because 00:04:39.900 --> 00:04:45.480 if the administration decides you violated it, they can take back the money, even if you've 00:04:45.480 --> 00:04:52.140 already spent it. That's crazy. And I'm glad, basically the PSF said, too high of a risk, 00:04:52.580 --> 00:04:57.980 and we're not going to do that. So they said no, they took back the proposal. 00:04:58.460 --> 00:05:02.320 I think they basically, they were going to win it, it's my understanding, like it was 00:05:03.360 --> 00:05:08.360 turned down 1.5 million, which if you think about it is something like 25% of the revenue, 00:05:08.640 --> 00:05:14.460 that's a really big significant chunk yeah i mean huge amount of money and a small amount of money 00:05:14.510 --> 00:05:20.440 for the national science foundation huge amount of money for the psf um it's a it's unfortunate 00:05:20.720 --> 00:05:28.540 but um anyway uh we're gonna link to the uh the psf announcement but there's also um uh simon 00:05:28.700 --> 00:05:35.680 willison has a a shorter and really good write-up he's um uh he's he's part of the decision too and 00:05:35.700 --> 00:05:41.420 agrees with it. Apparently it was, it was unanimous. So he's on one of the, one of the board members 00:05:41.450 --> 00:05:47.740 who voted to reject the funding. And then there's, there's also articles from Mars Technica about 00:05:47.980 --> 00:05:54.540 this because it's a big news. And also the register has an interesting article on it. So 00:05:54.550 --> 00:05:59.520 we'll link to those, but yeah, that is a little bit more broad coverage of inside baseball and 00:05:59.540 --> 00:06:06.640 python than we usually get yeah uh it's unfortunate too but so i'm um i'm gonna bump up my uh my 00:06:06.820 --> 00:06:13.620 donation to the psf um um and there's a link in most of these are at least in the main article 00:06:13.820 --> 00:06:18.420 and uh simon wilson has a link there also if you'd like to if you think what they're doing is right 00:06:18.580 --> 00:06:24.120 and good stuff and i i actually really love the what what well everybody does but um uh bringing 00:06:24.320 --> 00:06:28.319 seth on board was pretty cool and he's doing some neat things with security and so so are other 00:06:28.300 --> 00:06:33.720 people. So yeah, anyway, that's that. Yeah. More security is good for us, but yeah, it's got to pay 00:06:33.720 --> 00:06:40.000 for it. That's tricky. Talk about serialization and there is no funding or nothing in the serial 00:06:40.100 --> 00:06:44.480 just straight serialization, Brian. So check this out. So one thing that's really popular, 00:06:44.690 --> 00:06:48.780 I don't know if you've heard of them before, but Pydantic, it's pretty popular. Some people use it 00:06:49.020 --> 00:06:52.980 for, they have JSON and they want to get into Python objects. They use this thing called Pydantic. 00:06:53.400 --> 00:06:57.640 Yeah, it's kind of a big deal. It is, but here's what the Pydantic things do. 00:06:58.140 --> 00:06:59.840 they exchange JSON, right? 00:07:00.160 --> 00:07:02.560 And JSON can be extremely verbose, 00:07:03.440 --> 00:07:05.520 aka takes a lot of memory during caching. 00:07:05.920 --> 00:07:08.220 So let's suppose I have a list of a thousand customers. 00:07:08.460 --> 00:07:10.080 Each customer has a street address, 00:07:10.540 --> 00:07:12.580 country, postal code, et cetera, et cetera, right? 00:07:12.820 --> 00:07:15.640 Those words are repeated a thousand times 00:07:15.760 --> 00:07:16.700 for how many customers I said, 00:07:16.800 --> 00:07:18.080 a hundred, a thousand, whatever, right? 00:07:18.300 --> 00:07:20.040 Those are, they're very verbose. 00:07:20.220 --> 00:07:20.860 It's great for humans. 00:07:21.220 --> 00:07:23.160 It's way, way better than XML. 00:07:23.640 --> 00:07:25.940 Thank you for XML mostly going away, 00:07:26.360 --> 00:07:27.840 But it's still pretty verbose. 00:07:27.880 --> 00:07:29.880 So when you say, like, maybe I want to use Pydantic models, 00:07:29.980 --> 00:07:34.900 but then I want to store those things in, like, some kind of cached setup, right? 00:07:35.100 --> 00:07:38.160 Like a Redist or a disk cache. 00:07:38.240 --> 00:07:40.380 Like, man, I'm psyched about disk cache these days. 00:07:41.160 --> 00:07:42.780 So many places I see that I can use it. 00:07:43.120 --> 00:07:45.720 But if you put the JSON in there, then you're taking up a lot of space. 00:07:46.020 --> 00:07:53.660 So this project announced on Reddit by Lucky2Yan is called, 00:07:54.200 --> 00:07:55.280 what's the actual project called? 00:07:55.540 --> 00:08:03.080 It's called PyByntic, is in Pydantic, so binary Pydantic, which is interesting. 00:08:03.200 --> 00:08:13.680 So it says, I built a compact binary serializer for Pydantic models that dramatically reduces the RAM and or disk storage for caches compared to JSON. 00:08:13.880 --> 00:08:17.280 The library is designed for high load systems like Redis caching Valkey. 00:08:17.600 --> 00:08:22.180 If you're doing Redis, you can also look at Valkey, where millions of models are stored in memory and every byte matters. 00:08:22.620 --> 00:08:26.180 It serializes Pydantic models into minimal binary formats 00:08:26.360 --> 00:08:29.080 and deserializes them back with zero extra metadata overhead. 00:08:29.380 --> 00:08:29.480 Cool. 00:08:30.500 --> 00:08:31.860 If you look-- is there a graph here? 00:08:32.180 --> 00:08:33.960 No, there is the graph on the GitHub page. 00:08:34.280 --> 00:08:35.539 So there is a graph about the size, 00:08:35.640 --> 00:08:38.180 but it's something like seven times smaller. 00:08:38.860 --> 00:08:39.360 There's a bunch here. 00:08:39.700 --> 00:08:39.900 Let's look. 00:08:40.180 --> 00:08:44.180 It compares to JSON, which is, let's say, 35 gigs. 00:08:44.560 --> 00:08:46.840 And then Pybantic-- 00:08:46.920 --> 00:08:48.100 I'm having problems here-- 00:08:48.120 --> 00:08:52.860 It is 4.6, which is like nine, eight times smaller than JSON. 00:08:53.280 --> 00:08:54.300 But that's pretty interesting. 00:08:54.740 --> 00:08:56.380 But here's what is actually really crazy. 00:08:56.600 --> 00:08:59.380 It's also four times smaller than MessagePack, 00:08:59.680 --> 00:09:01.600 five times smaller than BinaryJSON, 00:09:02.060 --> 00:09:04.260 and half as big as Protobuf. 00:09:04.520 --> 00:09:05.000 Oh, interesting. 00:09:05.620 --> 00:09:06.900 And Rhett out there is right there. 00:09:07.020 --> 00:09:08.080 Thank you, Rhett, for the handoff. 00:09:08.240 --> 00:09:09.400 So why not just use Protobuf? 00:09:09.580 --> 00:09:10.660 Well, it's twice as small, 00:09:10.880 --> 00:09:14.700 so it depends how much you are really worried about that, right? 00:09:14.860 --> 00:09:17.980 And how much do you want to just serialize your bidentic models? 00:09:18.080 --> 00:09:26.180 So anyway, I thought this was interesting in a way that it would say, look, maybe we don't just necessarily store everything in JSON. 00:09:26.860 --> 00:09:28.160 Maybe it's this Pybantic thing. 00:09:28.480 --> 00:09:34.240 Or maybe, as Rhett is pointing out in the audience, maybe you want something more interchangeable and more well-known. 00:09:34.560 --> 00:09:35.160 Use protobuf. 00:09:35.560 --> 00:09:38.280 So it's a chance to talk about this new project, which is interesting. 00:09:38.560 --> 00:09:43.100 But also just to talk about there's interesting, well-known serialization formats that you can use. 00:09:43.400 --> 00:09:43.660 Yeah. 00:09:44.160 --> 00:09:44.280 Yeah. 00:09:44.560 --> 00:09:46.200 And I think we can get those numbers better. 00:09:46.460 --> 00:09:49.800 If we come up with a benchmark with really long names, 00:09:50.160 --> 00:09:51.080 I'll get repeated. 00:09:51.540 --> 00:09:53.540 Like Boolean objects that are just like, 00:09:53.800 --> 00:09:56.100 the street that I lived on when I was a kid. 00:09:58.239 --> 00:09:59.040 Underscore, yeah. 00:10:00.160 --> 00:10:03.480 Street that I lived on underscore kid as a kid confirmed, 00:10:03.680 --> 00:10:05.080 true or false, and so on, right? 00:10:05.540 --> 00:10:09.500 We could crush it in anything that drops the, drop it. 00:10:09.800 --> 00:10:11.300 So yeah, someone else out there say, 00:10:11.380 --> 00:10:12.780 all these things sound kind of interesting 00:10:12.900 --> 00:10:15.040 until you need to open up a REST client and debug the API. 00:10:15.480 --> 00:10:16.800 I don't believe, yes, that's true. 00:10:16.880 --> 00:10:20.800 And I don't believe that this is necessarily an API exchange format. 00:10:21.040 --> 00:10:23.840 This is a caching story, right? 00:10:24.040 --> 00:10:29.260 Like if I'm going to write it to disk cache or to Redis or Valkey, you know, I'm probably 00:10:29.280 --> 00:10:29.800 not going to look at it. 00:10:29.800 --> 00:10:32.100 I'm just going, is it still there or do I just throw it away, right? 00:10:32.260 --> 00:10:33.580 Maybe you do, but maybe you don't. 00:10:33.740 --> 00:10:33.860 Right. 00:10:33.940 --> 00:10:36.900 Anyway, yes, everyone has pointed out some of that. 00:10:36.920 --> 00:10:40.140 There are certainly trade-offs of binary data, but I think it's pretty interesting. 00:10:40.400 --> 00:10:40.500 Yeah. 00:10:40.640 --> 00:10:46.000 As you know, look, the thing is often the very first limit you hit when you're in any sort 00:10:46.000 --> 00:10:51.120 of cloud computing environment is way, way sooner memory than CPU. 00:10:51.660 --> 00:10:54.300 Memory is so much more expensive than CPU. 00:10:54.760 --> 00:10:58.820 And this can give you, you know, half, five times less scale in that regard. 00:10:58.940 --> 00:11:01.720 So you might be, you know, that's where you start. 00:11:01.880 --> 00:11:03.960 This is not when I'm just like prototyping my app. 00:11:03.960 --> 00:11:04.980 Like, let's start with this, right? 00:11:05.080 --> 00:11:09.240 This is where you're like, we could go from a thousand dollar server to a $50 server. 00:11:09.500 --> 00:11:14.080 If we didn't have to store this much stuff in memory for caching and it would still be faster. 00:11:14.400 --> 00:11:15.180 You know, that kind of thing. 00:11:15.480 --> 00:11:15.600 Yeah. 00:11:15.960 --> 00:11:16.060 Yeah. 00:11:16.140 --> 00:11:23.000 And there's still like, I don't know if this would be useful in those cases, but there's still non-web cases where memory is important. 00:11:23.640 --> 00:11:24.620 Oh, right. 00:11:24.760 --> 00:11:25.600 What are you talking about? 00:11:25.600 --> 00:11:26.560 Internet things and stuff like that. 00:11:26.660 --> 00:11:27.320 Embedded systems. 00:11:27.980 --> 00:11:29.320 There's stuff other than the web? 00:11:29.360 --> 00:11:29.460 No. 00:11:30.660 --> 00:11:31.060 I know. 00:11:31.180 --> 00:11:34.540 I'm an old, old crafty guy that actually programs things. 00:11:36.139 --> 00:11:36.540 Crazy. 00:11:36.840 --> 00:11:37.220 No, here. 00:11:37.560 --> 00:11:38.160 What's your next thing? 00:11:38.180 --> 00:11:38.740 Tell us about it. 00:11:39.060 --> 00:11:39.260 Okay. 00:11:39.360 --> 00:11:41.340 Well, this is t-strings. 00:11:41.450 --> 00:11:41.980 These are new. 00:11:42.640 --> 00:11:44.200 Actually, we've talked about t-strings before, 00:11:44.680 --> 00:11:48.060 but now everybody can play with them because 3.4, 1.4. 00:11:48.620 --> 00:11:49.840 3.14 is out. 00:11:49.990 --> 00:11:51.260 Yeah, they're officially a thing. 00:11:52.300 --> 00:11:53.360 But they're a little, 00:11:53.900 --> 00:11:56.240 I think we're going to cover them probably a few more times 00:11:59.330 --> 00:12:01.680 because they're a little bit harder to get your head around 00:12:01.810 --> 00:12:03.040 than everything else before. 00:12:03.390 --> 00:12:04.220 So I really appreciate, 00:12:04.420 --> 00:12:06.180 there's an article from Trey Hunter, 00:12:06.260 --> 00:12:09.560 t-strings, Python's fifth string formatting technique? 00:12:10.480 --> 00:12:12.980 There should be one and only one way to do things 00:12:13.090 --> 00:12:14.340 unless it has to do with strings. 00:12:14.760 --> 00:12:17.580 Yeah, or lots of other things. 00:12:18.320 --> 00:12:19.920 Or paths, or what else are we talking about? 00:12:20.300 --> 00:12:22.920 So one of the cool things is, 00:12:23.250 --> 00:12:24.780 and I haven't really thought about this, 00:12:24.810 --> 00:12:26.440 is the history of string formatting. 00:12:26.680 --> 00:12:28.440 He goes through a very brief history. 00:12:29.460 --> 00:12:31.220 Percent strings, I kind of remember those. 00:12:31.640 --> 00:12:33.160 Yeah, I totally remember using those, 00:12:33.220 --> 00:12:38.840 like %s and then % and then the tuple to fill them in and stuff. 00:12:39.000 --> 00:12:40.700 So those sorts of template strings. 00:12:41.140 --> 00:12:44.860 You've got string.template, which I actually, to tell you the truth, 00:12:45.620 --> 00:12:47.820 that came in in 2.4, and I don't think I ever used it 00:12:48.160 --> 00:12:51.500 because by 2.6, we had.format. 00:12:51.820 --> 00:12:54.860 So Python.format, we used a lot. 00:12:55.010 --> 00:12:57.020 I used that a lot over the years. 00:12:57.460 --> 00:12:58.880 It's still a useful one, actually. 00:12:59.220 --> 00:13:00.220 Yeah, definitely. 00:13:01.020 --> 00:13:05.020 And also in a lot of places where you might grab t-strings now, 00:13:05.200 --> 00:13:08.020 they're still pretty useful because you can pass those around pretty well 00:13:08.520 --> 00:13:09.720 and then format them later. 00:13:10.380 --> 00:13:14.400 And that's sort of that delayed actually formatting part 00:13:16.100 --> 00:13:17.900 where t-strings are going to be really cool. 00:13:18.180 --> 00:13:20.760 So then we have f-strings, of course, and everybody loves f-strings. 00:13:21.500 --> 00:13:22.020 I love them. 00:13:22.360 --> 00:13:25.300 And what's interesting is I still think of f-strings as a new thing, 00:13:25.580 --> 00:13:26.940 but they came in at 3.6. 00:13:27.100 --> 00:13:27.940 That was so long ago. 00:13:28.280 --> 00:13:28.740 I know. 00:13:28.760 --> 00:13:29.580 That was real long ago. 00:13:29.780 --> 00:13:30.860 It's wacky. 00:13:31.700 --> 00:13:34.020 And then 314 has t-strings. 00:13:34.280 --> 00:13:38.160 And the different thing about t-strings is they return a template. 00:13:38.250 --> 00:13:39.640 They do not return a string. 00:13:40.080 --> 00:13:41.540 So they are different beasts. 00:13:43.520 --> 00:13:46.980 But the cool thing is, well, so why would you use them? 00:13:47.120 --> 00:13:51.860 We've talked about this before, but I kind of like that Trey took a whack at explaining this. 00:13:52.240 --> 00:13:56.340 They're more like you might want to use, I don't remember if he said it or somebody else. 00:13:56.720 --> 00:14:01.060 It'll be very useful for library authors and framework people to be using t-strings. 00:14:01.540 --> 00:14:06.440 Not sure how many people like in your own code you'll use it because f-strings are still pretty cool in format. 00:14:06.900 --> 00:14:22.420 But he gives an example of a dedent function that is the issue with f-strings is the when you like that the interpolation of filling in the variables happens earlier and you can delay it with templates. 00:14:22.860 --> 00:14:24.500 Essentially is what we're talking about. 00:14:24.750 --> 00:14:26.140 And he goes through a dedent example. 00:14:26.400 --> 00:14:30.280 And I actually, I'm going to have to just play with it more because I still got lost. 00:14:30.700 --> 00:14:32.260 But this is a good attempt. 00:14:33.400 --> 00:14:35.000 And I think this is cool. 00:14:35.880 --> 00:14:39.600 And then one of the neat things, I love it when people do this, is why not? 00:14:39.780 --> 00:14:50.140 If you're used to popping things on PyPI, he went ahead and called this better dident and his example and threw it up on PyPI. 00:14:50.290 --> 00:14:53.260 So if you want to play with what he came up with, you can just install it, run it. 00:14:53.860 --> 00:14:54.060 Okay. 00:14:54.700 --> 00:14:55.120 Yeah, very fun. 00:14:55.920 --> 00:15:00.920 i feel like he should create a not not just a bunch of separate little things that are for 00:15:01.060 --> 00:15:06.880 his examples but like a mega like a morsels with a complex cli that like lets you dive into the 00:15:07.000 --> 00:15:12.820 different examples i mean he he would have but the grant got canceled so oh i see well it's only the 00:15:12.920 --> 00:15:18.420 security features that wouldn't make it oh yeah right never mind no that's actually a 00:15:18.470 --> 00:15:22.879 decent idea like because he's got a lot of uh he's got a lot of stuff cool stuff on the python 00:15:22.900 --> 00:15:30.240 the morsel site so yeah for sure okay let's talk about something called ron 00:15:30.300 --> 00:15:36.680 cron board speaking of putting up a like a 2i or a CLI sort of thing so Brian 00:15:37.160 --> 00:15:42.780 how many cron jobs have you done at this time they have weird syntax I don't know 00:15:42.780 --> 00:15:46.400 if you're familiar with it but they have really weird little syntax that you can 00:15:46.460 --> 00:15:51.479 put in I don't know if there's a good example on this thing but like star star 00:15:51.500 --> 00:15:57.460 seven star like it's kind of hard to figure out like all the pieces understand what they mean see 00:15:57.460 --> 00:16:02.780 what ones are on your machine and so on so this thing called cron board is a terminal app written 00:16:02.960 --> 00:16:11.020 with textual and rich that is basically a shell friendly or ssh friendly tool for understanding 00:16:11.340 --> 00:16:16.759 and using like look at telling me like what particular things are on here as a cron job 00:16:17.000 --> 00:16:23.300 what are their settings you can see like it's 10 that 1-10 star star star three star and actually 00:16:23.340 --> 00:16:28.660 the little thing validates the expression how often that actually means that runs and so on 00:16:29.080 --> 00:16:34.000 isn't this cool yeah it is cool yeah yeah i always have to use some sort of tool to figure this out 00:16:34.200 --> 00:16:39.660 because i know i'm like no i'm gonna get it wrong look it's so messy it's so weird i admire the 00:16:39.780 --> 00:16:44.440 old graybeards that used to be able to just do this in their head or on paper but yeah not me 00:16:44.520 --> 00:16:45.260 That's right. 00:16:45.330 --> 00:16:48.380 Like this could definitely qualify for it's some form of Elvish joke. 00:16:49.860 --> 00:16:49.980 Yeah. 00:16:50.340 --> 00:16:50.420 Right. 00:16:50.600 --> 00:16:54.220 I mean, we put it on regular expressions, but it could be on cron job expressions as well. 00:16:54.580 --> 00:16:54.640 Yeah. 00:16:54.940 --> 00:16:56.400 Anyway, that's all there is to it. 00:16:56.500 --> 00:16:58.480 There's not a whole lot to say about it. 00:16:58.580 --> 00:17:00.240 It's written in Python, which is fun. 00:17:00.750 --> 00:17:05.699 So do you have, do you have, I'm thinking about why you chose this, maybe just for the fun of it, 00:17:05.880 --> 00:17:10.079 but do you, do you have cron jobs in what you're doing on Talk Python? 00:17:10.339 --> 00:17:11.220 Not exactly. 00:17:11.240 --> 00:17:14.699 I sort of do, but a lot of it is like background. 00:17:14.990 --> 00:17:18.680 I think it's more like a background task that checks every hour. 00:17:18.870 --> 00:17:21.540 And so I've kind of kept it to that because I don't know. 00:17:21.709 --> 00:17:23.760 I like, I'm sure people get this vibe about me, 00:17:23.860 --> 00:17:26.660 but like I like stuff more cohesive and stuck together 00:17:26.880 --> 00:17:29.460 and just like focused and not all spread out all over the place. 00:17:29.740 --> 00:17:31.700 Like, okay, so this script runs on that cron job 00:17:31.770 --> 00:17:33.880 and then this part checks the database and this thing over here. 00:17:33.890 --> 00:17:34.400 You know what I mean? 00:17:34.480 --> 00:17:36.120 Like, so if I can cram it together and go, 00:17:36.130 --> 00:17:39.400 the part that needs that can also just run like a background thread 00:17:39.420 --> 00:17:43.160 and every now and then just go, does that need checked or rebuilt or reindexed or whatever. 00:17:43.660 --> 00:17:46.640 But I could certainly see places where if I was more comfortable with cron jobs, 00:17:46.710 --> 00:17:49.280 I would do a better job with them and things would probably be simpler. 00:17:49.520 --> 00:17:50.140 So there's that. 00:17:50.880 --> 00:17:51.540 Yeah, cron board. 00:17:51.650 --> 00:17:51.940 Check it out. 00:17:51.970 --> 00:17:52.300 Looks fun. 00:17:52.580 --> 00:17:52.680 Cool. 00:17:53.840 --> 00:17:54.400 We're on to extras. 00:17:54.820 --> 00:17:55.640 You're the only extra. 00:17:56.140 --> 00:17:57.020 I ain't got nothing. 00:17:57.500 --> 00:17:57.860 Okay. 00:17:57.990 --> 00:18:00.940 Well, there's some exciting news. 00:18:00.990 --> 00:18:02.480 I just heard this morning. 00:18:02.770 --> 00:18:04.220 Oh, because it just happened this morning. 00:18:04.600 --> 00:18:10.180 Barry Warsaw announced an 810 explicit lazy imports. 00:18:10.560 --> 00:18:11.940 We've been talking about this for a while, 00:18:12.320 --> 00:18:14.760 and it was not approved yet. 00:18:14.760 --> 00:18:17.240 It was just a draft, but it is approved now. 00:18:17.910 --> 00:18:25.160 So steering council happily and unanimously accepted 810 explicit lazy imports. 00:18:25.560 --> 00:18:27.060 They have some input for the authors, 00:18:27.340 --> 00:18:31.240 but basically a really nice commentary about... 00:18:31.260 --> 00:18:36.560 revise and resubmit and sort of acceptance from the academic side. 00:18:36.810 --> 00:18:38.460 Like we'll take it, but not as it is. 00:18:38.760 --> 00:18:39.360 Yeah, it's okay. 00:18:39.730 --> 00:18:43.540 Well, I mean, but that's kind of one of the cool things about the steering council, 00:18:43.710 --> 00:18:48.120 because you can do things like when you submit something, you can like as this is done. 00:18:48.310 --> 00:18:52.100 Actually, this was a really, really well-written, I thought, well-written PEP. 00:18:52.290 --> 00:18:56.580 But you can say things like there's a few points, like what keyword do you use? 00:18:56.720 --> 00:19:00.640 The PEP authors liked lazy, but there was a couple of other options. 00:19:01.140 --> 00:19:03.540 And the steering council went through and tried to figure out 00:19:03.560 --> 00:19:04.960 if they could come up with a better name. 00:19:05.240 --> 00:19:07.700 I mean, if there's options, why not give it to the steering council 00:19:07.780 --> 00:19:10.340 and say, you guys can decide if you want. 00:19:10.540 --> 00:19:12.440 But yeah, so pretty cool. 00:19:12.640 --> 00:19:15.920 I wonder what that means for anybody that has a global variable 00:19:16.100 --> 00:19:17.580 named lazy in terms of compatibility. 00:19:18.040 --> 00:19:21.600 I mean, it would be fine as long as they don't use it 00:19:21.660 --> 00:19:22.760 in the import statement. 00:19:22.980 --> 00:19:25.700 I think it probably would not do anything at all. 00:19:26.320 --> 00:19:29.040 I know the early Python parser had a hard time 00:19:29.180 --> 00:19:30.660 with disambiguating that kind of stuff. 00:19:30.940 --> 00:19:33.520 but I think maybe the peg parser is more advanced. 00:19:33.980 --> 00:19:35.000 Well, no, the peg parser is more advanced. 00:19:35.140 --> 00:19:35.860 Maybe it can handle it. 00:19:36.140 --> 00:19:40.020 Like in C#, they have certain words 00:19:40.540 --> 00:19:42.820 that they themselves are not keywords, 00:19:43.100 --> 00:19:44.920 but taken as a pair, they are keywords, 00:19:45.520 --> 00:19:47.120 like lazy space import. 00:19:47.320 --> 00:19:51.220 So in C#, you have yield return is a keyword thing, 00:19:51.410 --> 00:19:53.940 but you can have a variable named yield as well, 00:19:53.950 --> 00:19:56.680 and they will be understood as different by the parser. 00:19:56.730 --> 00:19:58.980 And I think that that was not true in early Python, 00:19:59.220 --> 00:20:00.160 but I could be wrong about that. 00:20:00.460 --> 00:20:06.580 Well, luckily we have listeners like, and people, Hugo is listening, which is great. 00:20:06.780 --> 00:20:10.560 And in the, in the chat says lazy will be a soft keyword. 00:20:10.840 --> 00:20:11.740 So you could reuse it later. 00:20:12.120 --> 00:20:12.500 Okay, good. 00:20:12.760 --> 00:20:19.300 And also I forgot to give Hugo a shout out as his post on, on social media that announced 00:20:19.680 --> 00:20:22.600 that I, the reason why I saw the announcement was from Hugo. 00:20:22.840 --> 00:20:23.340 So thanks Hugo. 00:20:23.740 --> 00:20:23.920 Yeah. 00:20:24.020 --> 00:20:24.160 Awesome. 00:20:24.240 --> 00:20:25.440 And thanks for all the stuff, Hugo. 00:20:25.440 --> 00:20:28.760 You give us a lot of good pointers either directly or just by writing. 00:20:28.960 --> 00:20:29.480 Okay, cool. 00:20:29.700 --> 00:20:29.760 Yeah. 00:20:29.880 --> 00:20:31.160