WEBVTT 00:00:00.001 --> 00:00:05.400 Hello and welcome to Python Bytes, where we deliver Python news and headlines directly to your earbuds. 00:00:05.400 --> 00:00:09.980 This is episode 423, recorded March 10, 2025. 00:00:09.980 --> 00:00:11.420 And I am Brian Okken. 00:00:11.420 --> 00:00:12.460 And I'm Michael Kennedy. 00:00:12.460 --> 00:00:23.440 And thanks everybody again for supporting us through training courses at pythontest.com and at talkpython.fm. 00:00:23.440 --> 00:00:25.600 So lots of great courses there. 00:00:25.600 --> 00:00:28.020 And our Patreon supporters, of course. 00:00:28.020 --> 00:00:28.440 Thank you. 00:00:28.440 --> 00:00:31.940 And for people that'd like to get a hold of us, we'd love to get here. 00:00:31.940 --> 00:00:40.240 If you've got a suggestion for the show or have a question about it or correction, you can reach the show at pythontest.fm. 00:00:40.240 --> 00:00:48.000 And there's also in the show notes, there's links to our Bluesky and Mastodon links. 00:00:48.000 --> 00:00:51.320 And you can also sign up at pythontest.fm. 00:00:51.320 --> 00:00:56.360 You can go to live to see when the next live show is going to go on. 00:00:56.880 --> 00:01:03.840 Or you can sign up for the newsletter and get everything we talked about sent directly to your inbox, which is cool. 00:01:03.840 --> 00:01:04.260 Yeah. 00:01:04.260 --> 00:01:06.480 And they can crush that bell on YouTube, too. 00:01:06.480 --> 00:01:07.220 Oh, yeah. 00:01:07.220 --> 00:01:08.160 Subscribing on YouTube. 00:01:08.160 --> 00:01:09.040 That would be great. 00:01:09.040 --> 00:01:09.760 Yeah. 00:01:09.760 --> 00:01:10.160 Yeah. 00:01:11.020 --> 00:01:16.600 So speaking of subscribing or scribing, what are we talking about first? 00:01:16.600 --> 00:01:20.740 Well, how's your SQL game, Brian? 00:01:20.740 --> 00:01:22.180 A little weak, actually. 00:01:22.180 --> 00:01:22.780 Yeah. 00:01:22.780 --> 00:01:23.660 Mine's a little weak as well. 00:01:23.660 --> 00:01:24.520 It's atrophied a bit. 00:01:24.520 --> 00:01:29.300 You know, I've got its table and I got another table and I want to do a join on that table. 00:01:29.300 --> 00:01:31.640 And then maybe I want to use an aggregation function. 00:01:31.640 --> 00:01:32.940 How do I do that again? 00:01:32.940 --> 00:01:37.140 Well, there's a lot of cool tools and libraries around there to solve that. 00:01:37.140 --> 00:01:44.720 For example, you can use SQLAlchemy or SQL Model and then you just talk in Python terms and classes and stuff. 00:01:44.720 --> 00:01:49.940 And then somehow magically deep down when it docs the database, it'll do that kind of stuff for you. 00:01:49.940 --> 00:01:51.640 You still kind of got to know the queries. 00:01:51.640 --> 00:01:55.100 So it's not perfect, but it doesn't perfectly solve it for you. 00:01:55.100 --> 00:01:59.800 But I want to introduce everyone to a new tool called PySQL Scribe. 00:02:00.140 --> 00:02:04.860 And the idea here is similar to that, except for you use it for real SQL. 00:02:04.860 --> 00:02:17.500 So, for example, if you want to know how to do one of these joins or you want to get some support doing that and you're not already using SQLAlchemy, it's not reasonable to say, well, let me re-implement everything I'm doing in SQLAlchemy. 00:02:17.500 --> 00:02:23.280 So I can ask it a question to get a simple SQL statement that I just want to use outside of SQLAlchemy. 00:02:23.280 --> 00:02:23.500 Right. 00:02:23.500 --> 00:02:24.000 Okay. 00:02:24.000 --> 00:02:24.840 So that's kind of what this is. 00:02:24.840 --> 00:02:30.920 So you can take this thing and you teach it about different things, which database you're using. 00:02:30.920 --> 00:02:37.200 Because even though SQL is a general query language, it does not generally work against any database. 00:02:37.200 --> 00:02:37.820 Right. 00:02:37.820 --> 00:02:40.480 Each database has its own dialect. 00:02:41.020 --> 00:02:41.420 Right. 00:02:41.420 --> 00:02:47.920 So the way you say, for example, specify parameters for MySQL is different than the way you do for Microsoft SQL Server. 00:02:47.920 --> 00:02:50.200 And while they are similar, they're not the same. 00:02:50.200 --> 00:02:53.760 So what you do is with this is you say, I'm working with this particular database. 00:02:53.760 --> 00:02:57.460 And then you say, you give it information about your tables. 00:02:57.460 --> 00:02:57.960 Right. 00:02:57.960 --> 00:02:59.780 So here's a table name. 00:02:59.780 --> 00:03:01.480 Here it's columns and so on. 00:03:01.480 --> 00:03:08.280 And then you can just say, create a little builder and say, builder.select this column, that column from this table build. 00:03:08.280 --> 00:03:13.960 And what it builds is it outputs a select or a SQL statement of some sort. 00:03:13.960 --> 00:03:16.780 So in this case, select the various columns from the table. 00:03:16.780 --> 00:03:17.860 Cool, right? 00:03:17.860 --> 00:03:18.400 Yeah. 00:03:18.400 --> 00:03:18.880 Yeah. 00:03:18.880 --> 00:03:21.860 But you can do more than that. 00:03:21.860 --> 00:03:28.660 You can, let's see, you can create your own class by creating a class that is decorated. 00:03:28.660 --> 00:03:35.840 And then it will know that, you know, basically you can create either your own queries or you can create your own dialect. 00:03:35.840 --> 00:03:38.240 So for example, here's a MySQL table. 00:03:38.240 --> 00:03:41.860 So you don't have to specify the dialect because it's a MySQL table. 00:03:41.860 --> 00:03:42.780 It knows the dialect. 00:03:42.780 --> 00:03:49.000 And if you go further down here, you can see it understands more complicated things like join. 00:03:49.000 --> 00:03:50.840 Like first I want to select this thing. 00:03:50.840 --> 00:03:56.900 Then I want to join on that table on this thing and then build and it'll write the join statement for you. 00:03:56.900 --> 00:03:57.800 Just pretty neat. 00:03:58.080 --> 00:04:00.240 You can also do, like I said, functions. 00:04:00.240 --> 00:04:02.280 Let me scroll down a tad to that. 00:04:02.280 --> 00:04:11.200 So for example, if you wanted to write something that did, you know, uppercase in the select statement or max of some value out of there, right? 00:04:11.200 --> 00:04:13.420 And a group by type of thing. 00:04:13.420 --> 00:04:22.120 So you could just go and write that in terms of the SQL scribe, the PySQL scribe, and then it will actually generate all that for you. 00:04:22.120 --> 00:04:23.100 So that's pretty neat. 00:04:23.360 --> 00:04:29.740 And finally, you can combine them if you have one builder inside of another builder type of thing. 00:04:29.740 --> 00:04:30.860 And it'll join. 00:04:30.860 --> 00:04:32.360 It's a more complicated thing. 00:04:32.360 --> 00:04:36.460 So the more you do with the SQL, you know, probably the more helpful this is. 00:04:36.460 --> 00:04:40.760 If you're just doing real simple select and where statements, maybe not that helpful. 00:04:40.920 --> 00:04:42.580 But that is my first item. 00:04:42.580 --> 00:04:43.720 I think it might help some folks. 00:04:43.720 --> 00:04:43.920 Yeah. 00:04:43.920 --> 00:04:44.940 Yeah. 00:04:44.940 --> 00:04:49.000 I guess you're probably the wrong person to ask, but I was just curious about the use case. 00:04:49.000 --> 00:05:03.180 So like, for instance, I guess if you had an application that the user could select which database they're connecting to, and then you could create the different features based on that and just, I guess. 00:05:03.580 --> 00:05:03.680 Yeah. 00:05:03.680 --> 00:05:06.080 I don't think it's operational in a sense. 00:05:06.080 --> 00:05:09.480 I think it's more, because if you're doing it operationally, just use an ORM. 00:05:09.480 --> 00:05:09.920 Okay. 00:05:09.920 --> 00:05:11.080 Because it does that, right? 00:05:11.080 --> 00:05:18.060 I think it's, I would like this thing to help me write the queries because I'm, sometimes I forget. 00:05:18.060 --> 00:05:21.540 Like if you're doing data science, you might be connecting to different data sources. 00:05:21.540 --> 00:05:25.480 You might be going, oh, I want to ask this question, but oh, that's probably a join. 00:05:25.480 --> 00:05:26.540 How do I do that again? 00:05:26.540 --> 00:05:27.180 And so on. 00:05:27.400 --> 00:05:27.680 Okay. 00:05:27.680 --> 00:05:28.200 Yeah. 00:05:28.200 --> 00:05:33.020 I was actually, because I was just thinking about putting an application together and I was like, it's pretty lightweight. 00:05:33.020 --> 00:05:34.300 I don't really want an ORM. 00:05:34.300 --> 00:05:38.160 So I was going to do raw SQL, but then I. 00:05:38.160 --> 00:05:38.320 Yeah. 00:05:38.320 --> 00:05:49.560 So what you might do is you might run this one, you might give it your specification, run it one time, and then hard code the responses as parameterized queries in your Python code. 00:05:49.560 --> 00:05:56.560 And don't revisit it again until you might need to change the query in a sufficiently complicated way that you can't just like type another column or something. 00:05:56.560 --> 00:05:57.040 You know what I mean? 00:05:57.040 --> 00:05:57.340 Yeah. 00:05:57.340 --> 00:05:57.620 Okay. 00:05:57.620 --> 00:05:58.060 Yeah. 00:05:58.060 --> 00:05:58.620 Interesting. 00:05:58.620 --> 00:05:59.080 Cool. 00:05:59.080 --> 00:06:08.740 One addition that I added here, added sort of an idea I added, I guess, is I just, as getting ready for this, I'd thought, you know what? 00:06:08.740 --> 00:06:15.880 This is like typing in the names of the columns and the available tables seems like that should be automated. 00:06:16.500 --> 00:06:23.960 So I don't know if Daniel, the guy who created it, is any, has any interest in this, but I said, Hey, wouldn't it be cool if you could give it a create script? 00:06:23.960 --> 00:06:32.960 You know, you can go to your database and say, create an entire create script for the entire database with all the columns and the relationships and indexes and all that kind of stuff. 00:06:32.960 --> 00:06:40.760 If you could just point it at that, and then it could generate all the tables as an thing you pull in by table name. 00:06:40.760 --> 00:06:45.020 And then it just automatically knows the structure of everything of all your tables. 00:06:45.020 --> 00:06:51.640 Right. So I said, Hey, maybe you can make it pars a SQL data, create a data definition language, create script sort of thing. 00:06:51.640 --> 00:06:54.800 So I gave a little example of something that you might be able to do there. 00:06:54.800 --> 00:07:00.160 So who knows if that comes around, if he likes the idea or not, but I think there's some cool ways to expand this. 00:07:00.160 --> 00:07:01.060 Cool. Nice. 00:07:01.060 --> 00:07:01.740 Yeah. All right. 00:07:01.740 --> 00:07:02.540 Over to you. 00:07:03.440 --> 00:07:08.960 Well, I'm going to add, I'm going to look at a map of Python. 00:07:08.960 --> 00:07:12.420 So I ran across this article. 00:07:12.420 --> 00:07:14.720 It's kind of cool. 00:07:14.720 --> 00:07:23.780 So the idea is around looking at PyPI has got tons of packages there, but there's a lot of dependencies between them. 00:07:24.260 --> 00:07:30.360 And visualizing kind of how, what would it look like if we visualize all of this? 00:07:30.880 --> 00:07:33.480 So there's a couple of visualizations here. 00:07:33.480 --> 00:07:40.020 And I actually got a little lost in trying to interpret this, but it's pretty dots. 00:07:40.880 --> 00:07:47.260 But you can, you know, you can zoom in a little bit on, on some of these, the scroll wheel works on this to zoom in. 00:07:47.260 --> 00:07:53.320 And I'm not, I couldn't figure out what the spacing meant, but anyway, I, the, why I'm okay. 00:07:53.320 --> 00:07:56.400 So since I don't really know what this is doing, why am I covering it? 00:07:56.400 --> 00:08:02.800 One of the things I thought was great was it was just sort of a discussion around dealing with large data. 00:08:02.800 --> 00:08:08.220 And, you know, the big, the data set of PyPI is a pretty big data set. 00:08:08.720 --> 00:08:22.960 There is big, there's copies in BigQuery so that you can query that instead of, instead of querying PyPI all the time, which is something that I've done with the Python or pytest plugin list as well. 00:08:22.960 --> 00:08:27.080 But the, it's, but then there's some discussions. 00:08:27.080 --> 00:08:28.680 Well, there's, there's some junk in there. 00:08:28.680 --> 00:08:37.860 There's, there's, there's packages that don't have like source code listed or there's, you know, other things that make them really not, 00:08:38.140 --> 00:08:39.300 they're not really open source. 00:08:39.300 --> 00:08:41.700 They're just utilizing PyPI or something. 00:08:41.700 --> 00:08:43.520 Sometimes companies do that. 00:08:43.520 --> 00:08:48.240 Anyway, so there's some discussion around filtering that, which is an interesting discussion. 00:08:48.240 --> 00:08:55.840 And then a little bit of discussion about deciding what graphing mechanism to use and, and how to visualize it. 00:08:55.840 --> 00:08:57.880 So I just really appreciated the discussion. 00:08:57.880 --> 00:09:02.480 So if you're into visualizing data, I think this might be an interesting thing. 00:09:02.480 --> 00:09:04.360 Plus it's just a really fun visualization. 00:09:04.980 --> 00:09:09.880 And then at the end, there's a link that said, oh yeah, by the way, there's a better UI for this. 00:09:09.880 --> 00:09:10.600 I'm like, oh, okay. 00:09:10.600 --> 00:09:11.540 Let's take a look at that. 00:09:11.540 --> 00:09:12.920 And this is just cool. 00:09:12.920 --> 00:09:16.960 It's the spaceship, I don't know, spaceship operating manual. 00:09:16.960 --> 00:09:18.080 Wow. 00:09:18.480 --> 00:09:20.360 So this is like the galaxy of Python. 00:09:20.360 --> 00:09:23.060 And let's see if we have W and S for forward and back. 00:09:23.060 --> 00:09:23.160 Yeah. 00:09:23.160 --> 00:09:26.980 The first one was kind of like, I don't know, old school maps. 00:09:26.980 --> 00:09:27.600 It was really cool. 00:09:27.600 --> 00:09:31.940 But old school maps and like, you know, the days of like sailing and exploring. 00:09:31.940 --> 00:09:32.940 And this is like Hubble. 00:09:33.480 --> 00:09:33.760 Yeah. 00:09:33.760 --> 00:09:35.060 So look, look at this. 00:09:35.060 --> 00:09:36.220 We move forward and back. 00:09:36.220 --> 00:09:36.740 Oops. 00:09:36.740 --> 00:09:38.000 Let's see. 00:09:38.000 --> 00:09:38.440 W. 00:09:38.440 --> 00:09:40.040 See if we can get this to go. 00:09:40.040 --> 00:09:41.000 This is great. 00:09:41.000 --> 00:09:45.840 So for people listening, I'm zooming in and it's like you're going through a star field. 00:09:45.840 --> 00:09:49.200 And these are, these are Python dependencies that we're going around in. 00:09:49.200 --> 00:09:54.140 It's just, it's, it's a fun, I don't know, video game, video visualization thing. 00:09:54.140 --> 00:09:54.560 So. 00:09:54.560 --> 00:09:56.080 I'm going to play with, I haven't seen this before. 00:09:56.080 --> 00:09:56.880 I'm going to play this later. 00:09:57.500 --> 00:09:57.860 Thanks. 00:09:57.860 --> 00:09:59.220 You're just wasting like a half an hour of my day. 00:09:59.220 --> 00:10:00.480 You're welcome. 00:10:00.480 --> 00:10:01.320 Yeah. 00:10:01.320 --> 00:10:07.380 And so this, this is, this is all on, on GitHub also. 00:10:07.380 --> 00:10:12.320 So if you want to take a look at how he did the filtering and I'm, I'm linked to this because 00:10:12.320 --> 00:10:13.920 I'm going to take a look at how he's doing. 00:10:13.920 --> 00:10:18.960 So even a reproduction guide said there's the SQL query. 00:10:18.960 --> 00:10:23.480 So if you, if you'd like to do some big query stuff for around PyPI, there's an example. 00:10:23.480 --> 00:10:25.660 There's a process Jason. 00:10:25.660 --> 00:10:29.740 So how he's using the filters and stuff and then converting it to a graph. 00:10:29.740 --> 00:10:37.540 So some great, nice open source or nice examples of how to do data and visualization and stuff. 00:10:37.540 --> 00:10:37.960 So. 00:10:37.960 --> 00:10:38.500 Yeah. 00:10:38.500 --> 00:10:39.080 I love it. 00:10:39.080 --> 00:10:39.540 It's beautiful. 00:10:39.540 --> 00:10:40.580 Very, very cool. 00:10:40.580 --> 00:10:40.800 Yeah. 00:10:40.800 --> 00:10:43.840 You all have to follow the links to explore it. 00:10:43.840 --> 00:10:44.780 Yeah. 00:10:44.780 --> 00:10:47.560 And play with, play with the space one. 00:10:47.560 --> 00:10:48.160 That's fun. 00:10:48.160 --> 00:10:48.580 So. 00:10:48.580 --> 00:10:48.980 Yeah. 00:10:48.980 --> 00:10:50.480 The space one is the one I was thinking of. 00:10:50.480 --> 00:10:51.240 Awesome. 00:10:51.240 --> 00:10:53.700 I want to talk Rust, C++ and Python. 00:10:53.700 --> 00:10:57.580 I heard Bjorn was saying that C++ is under attack, Brian. 00:10:57.580 --> 00:10:58.520 How do you feel about that? 00:10:58.520 --> 00:10:59.900 It's under attack. 00:10:59.900 --> 00:11:00.660 I think so. 00:11:00.660 --> 00:11:06.040 I heard people say that I've heard a lot of, we really, you know, new software should be 00:11:06.040 --> 00:11:07.480 written in a memory safe language. 00:11:07.480 --> 00:11:10.000 And that's, you know, that doesn't work with C++. 00:11:10.000 --> 00:11:12.020 Anyway, that's not the point of this. 00:11:12.340 --> 00:11:12.480 Yeah. 00:11:12.480 --> 00:11:13.200 The point is. 00:11:13.200 --> 00:11:15.040 I'll have a comment later that we'll have to add. 00:11:15.040 --> 00:11:15.300 So. 00:11:15.300 --> 00:11:15.700 Yeah. 00:11:15.700 --> 00:11:16.620 Okay. 00:11:16.620 --> 00:11:17.740 I'm here for it. 00:11:17.740 --> 00:11:18.360 I'm here for it. 00:11:18.360 --> 00:11:19.400 But that's not what it's about. 00:11:19.400 --> 00:11:21.460 This is by Martin Otsiak. 00:11:21.460 --> 00:11:27.340 And it is Rust, C++ and Python trends in jobs on Hacker News. 00:11:27.340 --> 00:11:28.040 Interesting. 00:11:28.040 --> 00:11:28.660 Yeah. 00:11:29.020 --> 00:11:34.960 So there's, I don't know how he found this data, but somehow, hey, look, maybe just conversations 00:11:34.960 --> 00:11:40.300 on Hacker News might serve as a proxy for programming language job demand. 00:11:40.660 --> 00:11:46.400 So there's two questions, you know, ask Hacker News who is hiring and ask Hacker News who 00:11:46.400 --> 00:11:49.180 wants to be hired for February, 2025. 00:11:49.180 --> 00:11:55.080 And then there's graphs of how many times those appear for Python, Rust and C++. 00:11:55.080 --> 00:12:00.920 So if you look at it and this data actually goes back, I don't know what, I guess it's 00:12:00.920 --> 00:12:03.840 as of February, but this goes all the way back to 2021. 00:12:03.840 --> 00:12:07.300 So this is pretty long-term data, five years, four years. 00:12:08.000 --> 00:12:12.660 And so if you look at Python, it's trending downward pretty sharply. 00:12:12.660 --> 00:12:18.320 So are C++ and Rust, although they're starting to take up, I guess they're all a little bit 00:12:18.320 --> 00:12:19.800 starting to take up here at the very end. 00:12:19.800 --> 00:12:24.480 But the Python one is trending downward faster than the other two. 00:12:24.480 --> 00:12:25.400 So what does that mean? 00:12:25.400 --> 00:12:31.420 Like that people more and more at a higher rate of speed, people are not asking who is 00:12:31.420 --> 00:12:33.540 hiring in a particular language, right? 00:12:33.540 --> 00:12:37.040 Now, if you look at the other one, the inverse, who wants to be hired? 00:12:37.040 --> 00:12:38.460 Hey, we need people. 00:12:38.460 --> 00:12:39.420 We need people in this. 00:12:39.420 --> 00:12:44.080 They're all going up a little bit generally, but Python is going up way faster. 00:12:44.080 --> 00:12:45.960 So fewer people asking to be hired. 00:12:45.960 --> 00:12:48.900 More and more people are going, where do I find Python people? 00:12:48.900 --> 00:12:54.040 It looks like there's more demand for Python people over time. 00:12:54.040 --> 00:12:58.940 There's still more demand for C++ and more demand for Rust people, but at a slower rate 00:12:58.940 --> 00:12:59.440 of speed. 00:12:59.440 --> 00:13:00.320 Interesting, huh? 00:13:00.320 --> 00:13:00.840 Yeah. 00:13:00.840 --> 00:13:00.880 Yeah. 00:13:00.880 --> 00:13:08.140 And I was totally depressed for a while looking at this graph because of the sharp downward 00:13:08.140 --> 00:13:11.820 trend of all programmers, at least for C++, Rust and Python. 00:13:11.820 --> 00:13:12.880 I'm like, oh no. 00:13:12.880 --> 00:13:20.640 But it looks like if you just look at it from 2021 to now, it's a downward slope. 00:13:20.640 --> 00:13:22.100 But if it's kind of... 00:13:22.100 --> 00:13:23.180 Which one though? 00:13:23.180 --> 00:13:25.140 Who's hiring or who wants to be hired? 00:13:25.560 --> 00:13:27.280 Well, I guess I don't get it. 00:13:27.280 --> 00:13:28.300 Like the who's hiring. 00:13:28.300 --> 00:13:34.040 If that's individuals trying to find a job or don't have a job, they either have or want. 00:13:34.040 --> 00:13:34.800 Okay. 00:13:34.800 --> 00:13:35.080 Right. 00:13:35.080 --> 00:13:37.940 They don't have a job at all, or they have a job that they don't want. 00:13:37.940 --> 00:13:40.020 They want one in that technology. 00:13:40.020 --> 00:13:40.640 Okay. 00:13:40.640 --> 00:13:42.100 Who's trying to hire Python? 00:13:42.220 --> 00:13:42.820 Oh, right. 00:13:42.820 --> 00:13:43.160 Okay. 00:13:43.160 --> 00:13:48.080 So the fact that that's going down means fewer people are not in a job that they want, right? 00:13:48.080 --> 00:13:49.540 They're like, they're employed. 00:13:49.540 --> 00:13:50.300 That's a good thing. 00:13:50.300 --> 00:13:51.200 And they're employed kind of happily. 00:13:51.200 --> 00:13:52.820 So the fact that that goes down is good. 00:13:52.820 --> 00:13:53.960 And then you look at the next one. 00:13:53.960 --> 00:13:57.320 I don't know if this is good or bad, but there's fewer people per... 00:13:57.320 --> 00:13:58.840 They're not easily filling the jobs. 00:13:58.840 --> 00:14:03.260 It's getting harder and harder to fill the Python jobs at a faster rate than it is for the others. 00:14:03.260 --> 00:14:06.440 That means basically there's more employer demand, I'm pretty sure. 00:14:06.440 --> 00:14:07.700 That makes sense. 00:14:07.700 --> 00:14:10.120 Per candidate, I guess, if you can somehow... 00:14:10.120 --> 00:14:11.220 That's more optimistic then. 00:14:11.520 --> 00:14:13.660 Yeah, I think it's optimistic on both graphs. 00:14:13.660 --> 00:14:14.740 It just depends how you read it. 00:14:14.740 --> 00:14:15.080 Yeah. 00:14:15.080 --> 00:14:15.560 Yeah. 00:14:15.560 --> 00:14:17.280 I mean, it's hacker news, right? 00:14:17.280 --> 00:14:19.940 But it's still an interesting angle, you know? 00:14:19.940 --> 00:14:20.400 Yeah. 00:14:20.400 --> 00:14:29.340 I guess my take on the C++ versus other things or the demise of C++ or whatever, I don't think 00:14:29.340 --> 00:14:30.900 we're going to see a demise of C++. 00:14:30.900 --> 00:14:33.460 But there's a lot of stuff. 00:14:33.460 --> 00:14:35.800 It is difficult to learn. 00:14:35.800 --> 00:14:38.740 No doubt about it. 00:14:38.740 --> 00:14:40.600 Rust, I think, is difficult to learn too. 00:14:40.820 --> 00:14:46.220 But it's, I think, more manageable for people to come up to speed on a small project with 00:14:46.220 --> 00:14:47.560 Rust than Python. 00:14:47.560 --> 00:14:49.340 But maybe I'm wrong about that. 00:14:49.340 --> 00:14:57.160 But I think one of the gains of Rust is we need a way... 00:14:57.160 --> 00:14:58.180 It's around Python. 00:14:58.180 --> 00:15:03.220 We have this great Python project, but there's a little bit of it here that needs to be sped 00:15:03.220 --> 00:15:03.380 up. 00:15:03.380 --> 00:15:04.060 What do we do? 00:15:04.160 --> 00:15:07.760 Do we jump into C++ that we don't know about or Rust that we don't know about? 00:15:07.760 --> 00:15:09.360 And I think people are choosing Rust. 00:15:09.360 --> 00:15:11.900 So anyway, that's my take on that. 00:15:12.180 --> 00:15:16.100 Yeah, I listen to a couple of cybersecurity, computer security podcasts. 00:15:16.100 --> 00:15:21.300 And there's some really interesting conversations about like, if you're going to, you know, they 00:15:21.300 --> 00:15:30.820 just did one of them just did an analysis and said, I think 70% of all, 70 or 80% of all security problems with 00:15:30.820 --> 00:15:36.700 iOS were memory corruption, memory failure issues, right? 00:15:36.700 --> 00:15:40.480 Off by one on an array, use after free, right? 00:15:40.480 --> 00:15:44.320 Like the whole category of like things that happen because you're in a memory unsafe language. 00:15:44.980 --> 00:15:49.600 Microsoft was something like in the 60 to 70% of all security problems with the software 00:15:49.600 --> 00:15:51.380 has to do with memory issues. 00:15:51.380 --> 00:15:52.240 Oh, yeah. 00:15:52.240 --> 00:15:54.820 And he goes, you can just go through them like one after another. 00:15:54.820 --> 00:15:58.080 And they're all, they've all got that flavor, if not the exact same numbers. 00:15:58.080 --> 00:15:58.640 You know what I mean? 00:15:58.640 --> 00:15:59.080 Yeah. 00:15:59.080 --> 00:16:05.340 And so if you're choosing new, you're choosing new projects to start from scratch and you're 00:16:05.340 --> 00:16:11.440 picking some systems level language like C, C++, Rust, whatever, and you don't choose 00:16:11.440 --> 00:16:16.980 a memory safe language, you're basically choosing to have, you know, two and a half times as 00:16:16.980 --> 00:16:19.060 many vulnerabilities in your software. 00:16:19.060 --> 00:16:25.000 And that, I think that's what the, my language is under attack feel is. 00:16:25.000 --> 00:16:29.560 It's like, yeah, but that fact is still a fact that I'm sorry, but it is, you know? 00:16:29.560 --> 00:16:30.080 Yeah. 00:16:30.080 --> 00:16:33.300 And you can do stuff, you can do stuff in say C++, right? 00:16:33.300 --> 00:16:33.480 Right. 00:16:33.480 --> 00:16:37.700 And you need like smart pointers and things that will automatically free them and so on, but 00:16:37.700 --> 00:16:40.400 probably not for C, but it's still present, you know? 00:16:40.440 --> 00:16:43.940 There's still S print F that was, you know, print F that was wrong or whatever. 00:16:43.940 --> 00:16:44.500 Yeah. 00:16:44.500 --> 00:16:49.540 And I guess I've spent so much of my life in the low level world of like device drivers 00:16:49.540 --> 00:16:55.420 and stuff that that's one of the beautiful things about C++ is a memory mapped hardware 00:16:55.420 --> 00:17:00.760 access system is really easy to put together in C++ and I don't know how to do it somewhere 00:17:00.760 --> 00:17:00.980 else. 00:17:00.980 --> 00:17:05.800 I mean, I'm sure there's ways, but so, and we're always going to have software talk to 00:17:05.800 --> 00:17:06.100 hardware. 00:17:06.340 --> 00:17:11.420 So unless it gets really easy to do that in another language, we'll have C++. 00:17:11.420 --> 00:17:12.660 Yeah. 00:17:12.660 --> 00:17:14.740 Or someone builds a little layer. 00:17:14.740 --> 00:17:16.400 Well, it probably already is. 00:17:16.400 --> 00:17:17.220 We just don't know. 00:17:17.220 --> 00:17:17.980 I don't know Matt. 00:17:17.980 --> 00:17:18.220 Yeah. 00:17:18.220 --> 00:17:18.600 Yeah. 00:17:18.600 --> 00:17:18.780 Yeah. 00:17:18.780 --> 00:17:19.240 I don't either. 00:17:19.240 --> 00:17:21.480 I don't live, I don't live in that world these days. 00:17:21.480 --> 00:17:23.320 Anyway, that's pretty interesting stuff. 00:17:23.320 --> 00:17:23.560 Yeah. 00:17:23.560 --> 00:17:23.960 Yeah. 00:17:23.960 --> 00:17:24.320 All right. 00:17:24.320 --> 00:17:25.680 Over to you for your final thing. 00:17:26.220 --> 00:17:30.920 Well, so there is help and it is only a keyword away. 00:17:30.920 --> 00:17:35.080 So I, you know, occasionally I forget about this. 00:17:35.080 --> 00:17:40.620 So it's so tempting if you have a question about the world of Python or anything is to just 00:17:40.620 --> 00:17:41.680 Google something more. 00:17:41.680 --> 00:17:43.700 I mean, what am I using now? 00:17:43.700 --> 00:17:45.880 Not Google, something else, some Google alternative. 00:17:47.100 --> 00:17:50.620 And, but there's help there and it's pretty good. 00:17:50.620 --> 00:17:55.580 So linking to Trey Hunter's article, features of Python's help function. 00:17:55.580 --> 00:17:59.460 And help is, is really pretty good with Python. 00:17:59.460 --> 00:18:00.580 And it's part of built in. 00:18:00.580 --> 00:18:03.680 I don't know if it was built in from the language at the beginning, but it's been there for as 00:18:03.680 --> 00:18:04.560 long as I've been using it. 00:18:04.900 --> 00:18:09.300 But if you say help, you can give it a string and you can give it a, you can say help on 00:18:09.300 --> 00:18:09.720 a function. 00:18:09.720 --> 00:18:16.100 You can say help on a module, symbols, keywords, topics, objects, and there's useful stuff that 00:18:16.100 --> 00:18:16.860 often comes out. 00:18:16.860 --> 00:18:20.640 So this article is talking through some of the things you can do. 00:18:20.640 --> 00:18:23.260 One of the things that I like is looking at meta help. 00:18:23.260 --> 00:18:24.840 The meta help is pretty interesting. 00:18:24.840 --> 00:18:31.700 You can have basically there's a, if you say help and give it the quote topics, you get a 00:18:31.700 --> 00:18:35.580 list of available topics and you've got stuff like strings. 00:18:35.580 --> 00:18:36.580 I looked up strings. 00:18:36.580 --> 00:18:38.760 I'm like, well, I don't use strings, but I looked it up. 00:18:38.760 --> 00:18:41.780 And one of the things that strings has is all these scapegoats. 00:18:41.780 --> 00:18:45.880 So like, what is a, what does the line feed code look like? 00:18:45.880 --> 00:18:49.340 And what's a, you know, all of those, those are in the. 00:18:49.340 --> 00:18:52.760 Like the backslash T, the backslash N, but there's got to be some that I don't know. 00:18:52.760 --> 00:18:53.340 Yeah. 00:18:53.340 --> 00:18:54.500 There's a bunch of others. 00:18:54.500 --> 00:18:58.380 And so there's, there's a lot of interesting information in here. 00:18:58.380 --> 00:19:05.200 And I think I remember looking at, I don't know, like literals and some of the, some of 00:19:05.200 --> 00:19:06.020 the other things in here. 00:19:06.020 --> 00:19:07.580 Namespaces is a good one. 00:19:07.580 --> 00:19:13.460 Just probably a really good discussion around none and, and numbers and objects. 00:19:13.460 --> 00:19:17.960 And there's a lot of great information around, around Python just available with the help 00:19:17.960 --> 00:19:18.340 utility. 00:19:18.340 --> 00:19:20.200 So here we go. 00:19:20.200 --> 00:19:21.220 Help symbols. 00:19:21.220 --> 00:19:22.880 So here's all the symbols of Python. 00:19:23.540 --> 00:19:28.340 So if you're curious what all the keywords, oh yeah, you can just have a list of all the 00:19:28.340 --> 00:19:28.940 keywords there. 00:19:28.940 --> 00:19:30.740 There's really not that many Python keywords. 00:19:30.740 --> 00:19:31.180 Wow. 00:19:31.180 --> 00:19:32.200 That's pretty interesting. 00:19:32.200 --> 00:19:32.960 Anyway. 00:19:32.960 --> 00:19:33.700 Yeah. 00:19:33.700 --> 00:19:34.760 Don't forget help. 00:19:34.760 --> 00:19:40.720 And those keywords are things that you can't use as variables or functions or let's say symbols 00:19:40.720 --> 00:19:42.080 more broadly in Python. 00:19:42.080 --> 00:19:47.640 I just realized that from this PySQL scribe, I was like, why do you have to say select thing 00:19:47.640 --> 00:19:49.380 than dot from underscore. 00:19:49.380 --> 00:19:50.260 Oh. 00:19:50.260 --> 00:19:54.160 And I, and I knew that the old parser, that would probably be the case, right? 00:19:54.160 --> 00:19:54.580 Yeah. 00:19:54.580 --> 00:19:58.260 Because it's just looks for the word from, but with the new like peg parser forward looking 00:19:58.260 --> 00:20:01.420 thing, I thought, oh, it's going to be smart enough to know that this is being used in an 00:20:01.420 --> 00:20:02.700 expression and not keyword. 00:20:02.700 --> 00:20:03.220 No. 00:20:03.220 --> 00:20:05.920 So you can say help symbols and keywords. 00:20:05.920 --> 00:20:09.800 And those are the things you can't name symbols at all. 00:20:09.800 --> 00:20:10.320 Yeah. 00:20:10.320 --> 00:20:13.360 You don't really have to memorize them though, because Python will not let you. 00:20:13.360 --> 00:20:14.380 Like it's just. 00:20:14.380 --> 00:20:15.860 It's going to be like, Hey, that's a keyword. 00:20:15.860 --> 00:20:16.360 Yeah. 00:20:16.360 --> 00:20:17.020 Don't do that. 00:20:17.180 --> 00:20:17.760 Can't do that. 00:20:17.760 --> 00:20:19.180 Yeah, for sure. 00:20:19.180 --> 00:20:19.780 For sure. 00:20:19.780 --> 00:20:20.300 All right. 00:20:20.300 --> 00:20:20.780 Extras. 00:20:20.780 --> 00:20:21.260 What do you think? 00:20:21.260 --> 00:20:22.080 Yeah. 00:20:22.080 --> 00:20:22.940 Extras would be great. 00:20:22.940 --> 00:20:23.420 Do you got any? 00:20:23.420 --> 00:20:23.800 Got any? 00:20:23.800 --> 00:20:24.240 Yeah. 00:20:24.240 --> 00:20:24.380 Yeah. 00:20:24.380 --> 00:20:25.900 I got one quick, quick, quick. 00:20:25.900 --> 00:20:32.160 So last week I mentioned that granion, granion is going strong. 00:20:32.160 --> 00:20:33.420 How many stars? 00:20:33.420 --> 00:20:34.700 3,200. 00:20:34.700 --> 00:20:36.660 This is the rust based one. 00:20:36.660 --> 00:20:37.220 Oh yeah. 00:20:37.220 --> 00:20:37.620 That is based. 00:20:37.620 --> 00:20:43.340 That basically is like a handy wrapper around hyper, right? 00:20:43.340 --> 00:20:46.900 Which hyper is a rust HTTP engine. 00:20:46.940 --> 00:20:48.440 And that has 15,000 stars. 00:20:48.440 --> 00:20:49.620 So quite popular. 00:20:49.620 --> 00:20:56.400 But that they released 2.0 and that meant FastAPI and probably a lot of starlet stuff as 00:20:56.400 --> 00:20:56.600 well. 00:20:56.600 --> 00:20:58.640 Just stopped working categorically. 00:20:58.640 --> 00:20:59.020 Whoops. 00:20:59.680 --> 00:21:11.140 Well, the next day out rolls patch release 2.0 and that was a good idea. 00:21:11.140 --> 00:21:15.900 And FastAPI makes heavy use of any IO. 00:21:16.560 --> 00:21:18.740 So that seems like that was probably the problem. 00:21:18.740 --> 00:21:20.200 Give it another go. 00:21:20.200 --> 00:21:22.420 And all the FastAPI things are happy again. 00:21:22.420 --> 00:21:22.980 Cool. 00:21:22.980 --> 00:21:25.060 So just as a follow up from last week, really. 00:21:25.060 --> 00:21:25.640 Yeah. 00:21:25.640 --> 00:21:29.700 I wouldn't point it out that normally, but because since I said it didn't work, I'll put it back 00:21:29.700 --> 00:21:30.620 on the checkbox. 00:21:30.620 --> 00:21:31.360 If now it works again. 00:21:31.360 --> 00:21:31.720 All right. 00:21:31.720 --> 00:21:32.220 That's all I got. 00:21:32.220 --> 00:21:33.260 Quick and easy. 00:21:33.260 --> 00:21:34.700 I got no extras. 00:21:34.700 --> 00:21:39.720 Although it just reminded me, I guess I don't have a page for this, but looking at dependencies, 00:21:39.720 --> 00:21:42.040 I had to pull up. 00:21:42.680 --> 00:21:48.680 I was looking for like I had a big, large, large set of packages that work together, internal 00:21:48.680 --> 00:21:49.080 thing. 00:21:49.080 --> 00:21:51.140 And something was using Greenlit. 00:21:51.140 --> 00:21:53.760 And I'm like, what is using Greenlit? 00:21:53.760 --> 00:21:57.220 And I pulled out pip dep tree. 00:21:57.220 --> 00:22:05.100 So I love pip dep tree to quickly take a look at what, if you run that, if you just pip install 00:22:05.100 --> 00:22:11.000 it and run it, and it'll show you in a tree form what all you have installed and what dependencies 00:22:11.000 --> 00:22:11.580 there are. 00:22:12.000 --> 00:22:17.160 And so I searched, easily searched through that and found out that Playwright was using 00:22:17.160 --> 00:22:17.540 Greenlit. 00:22:17.540 --> 00:22:21.140 And I'm like, oh, well, I'll trust them that they have a good reason to use it. 00:22:21.140 --> 00:22:25.280 So I just needed to update my Playwright and we were good to go. 00:22:25.280 --> 00:22:26.900 Excellent. 00:22:26.900 --> 00:22:27.220 Yeah. 00:22:27.220 --> 00:22:28.280 I've used that a lot. 00:22:28.280 --> 00:22:28.920 It's really nice. 00:22:28.920 --> 00:22:36.980 I use the uv pip compile thing, which now embeds that information into the requirements.txt file, 00:22:36.980 --> 00:22:38.200 which is nice as well. 00:22:38.200 --> 00:22:38.960 Oh, yeah. 00:22:38.960 --> 00:22:39.280 Okay. 00:22:39.280 --> 00:22:39.680 Yeah. 00:22:39.680 --> 00:22:39.940 Yeah. 00:22:39.980 --> 00:22:41.800 So I haven't used it that much lately. 00:22:41.800 --> 00:22:46.520 But yeah, if you're in any project that doesn't have one of those generated files, then it's... 00:22:46.520 --> 00:22:51.580 And another problem you can run into with just having it generate the stuff is, I don't know 00:22:51.580 --> 00:22:55.640 about you, but when you add stuff to your requirements file, it'd be that piproject.toml 00:22:55.640 --> 00:22:58.720 or requirements.txt equivalent or whatever. 00:22:58.720 --> 00:23:02.780 It's easy to put stuff in there and then not take it out because it's like, I don't think 00:23:02.780 --> 00:23:05.620 I've used it anymore, but it could break stuff and let's just... 00:23:05.620 --> 00:23:06.460 What's it hurting in there? 00:23:06.460 --> 00:23:09.400 You know, like it can become real easy for that to become stale. 00:23:09.400 --> 00:23:15.060 So, you know, you get a little better look of it from piped up tree maybe. 00:23:15.060 --> 00:23:17.020 Anyway, how about a joke? 00:23:17.020 --> 00:23:18.240 Sounds good. 00:23:18.240 --> 00:23:23.660 I brought a series of battling conspiracy theories to do with technology here. 00:23:23.660 --> 00:23:24.600 That sounds fun, right? 00:23:24.600 --> 00:23:25.260 Yeah. 00:23:25.260 --> 00:23:27.580 So here's a flat earther. 00:23:27.580 --> 00:23:30.680 I'm all here for making fun of flat earthers. 00:23:30.680 --> 00:23:34.240 I'm a computer engineer and I affirm that the earth is flat. 00:23:34.240 --> 00:23:40.800 But apparently John Davis, the secretary of the Flat Earth Society, you are not alone, Brian. 00:23:40.800 --> 00:23:45.020 Just because no one else around you thinks the earth is flat, that doesn't mean there's not 00:23:45.020 --> 00:23:48.100 a whole hive of people on the internet. 00:23:48.100 --> 00:23:49.500 All over the globe. 00:23:49.500 --> 00:23:50.700 All over the globe. 00:23:50.700 --> 00:23:53.240 So what is the response? 00:23:53.240 --> 00:23:53.800 Okay. 00:23:53.800 --> 00:23:58.520 I'm a geologist and I say that computers work because there are very small people inside 00:23:58.520 --> 00:23:59.360 doing all the work. 00:23:59.360 --> 00:24:00.560 Yeah. 00:24:00.560 --> 00:24:01.900 I gotcha. 00:24:01.900 --> 00:24:03.940 I think right back atcha. 00:24:03.940 --> 00:24:08.740 And then the subtitle, or if this is not, but if it weren't, XKCD, the hover, whatever that 00:24:08.740 --> 00:24:13.720 is, says this earth is flat versus computers work because there are very small people inside 00:24:13.720 --> 00:24:14.380 doing all the work. 00:24:14.380 --> 00:24:19.540 Was the geologist inspired by Amazon's just walk out technology? 00:24:19.540 --> 00:24:22.700 Remember, do you know the story behind that? 00:24:22.700 --> 00:24:23.280 No. 00:24:23.280 --> 00:24:27.580 You know the Amazon walk in, pick up wherever you want, you register your card, pick up 00:24:27.580 --> 00:24:29.580 wherever you want, you walk out and they just charge you? 00:24:29.580 --> 00:24:30.020 Yeah. 00:24:30.300 --> 00:24:35.700 I'm pretty sure that, I don't have any good sources off the top of my head right now, 00:24:35.700 --> 00:24:40.800 but that that was actually, instead of being super smart AI, which is what it was billed 00:24:40.800 --> 00:24:45.960 as there were just people in countries where it was cheap enough, just paid to sit there and watch 00:24:45.960 --> 00:24:47.960 a camera and just like mark down what you got. 00:24:47.960 --> 00:24:56.380 And then like, and someday maybe it was supposed to eventually become powered by AI and video 00:24:56.380 --> 00:24:56.940 recognition. 00:24:56.940 --> 00:25:01.780 But the working versions were just people watching you on camera and marking it down 00:25:01.780 --> 00:25:03.220 as you picked up and put down stuff. 00:25:03.220 --> 00:25:03.720 Yeah. 00:25:03.720 --> 00:25:04.440 Interesting. 00:25:04.440 --> 00:25:05.020 Okay. 00:25:05.020 --> 00:25:06.380 Anyway, I think that's the reference there. 00:25:06.380 --> 00:25:07.220 That is funny. 00:25:07.220 --> 00:25:14.460 There was a, somebody posted the other day about some studies that people are doing. 00:25:14.720 --> 00:25:19.220 So a lot of people are using AI for stuff and I'm using it for some things as well, but the, 00:25:19.220 --> 00:25:25.960 but for some things companies are doing like they're putting together lists of tasks and having 00:25:25.960 --> 00:25:30.300 like, if they were going to like hire a person to do this, a person should be able to do this 00:25:30.300 --> 00:25:33.040 task and this is kind of the output they should get. 00:25:33.040 --> 00:25:40.460 And, and then putting that, those tests to AI, like agents and just other ways to use AI 00:25:40.460 --> 00:25:42.620 and rating them that way. 00:25:42.960 --> 00:25:49.120 And if you do that and have, have domain experts come up with these tests, like AI is not doing 00:25:49.120 --> 00:25:49.480 well. 00:25:49.480 --> 00:25:55.420 And, and, but one of the results was about like 16% correct on a lot of these. 00:25:55.420 --> 00:26:01.500 And if the comment was, while impressive and that went on and I'm like, while impressive, 00:26:01.500 --> 00:26:07.680 that's just not, I've never got a 16% score in, in school and had somebody say, wow, that's 00:26:07.680 --> 00:26:10.020 impressive, but you need to grade on a good curve there. 00:26:10.020 --> 00:26:11.980 There you go. 00:26:12.180 --> 00:26:12.880 Business Insider. 00:26:12.880 --> 00:26:14.540 Oh, go away cookies. 00:26:14.540 --> 00:26:18.740 Amazon's just walk out technology relies on hundreds of workers in India watching you 00:26:18.740 --> 00:26:19.020 shop. 00:26:19.020 --> 00:26:23.400 That, that is ridiculous. 00:26:23.400 --> 00:26:24.360 Yeah. 00:26:24.360 --> 00:26:26.620 I thought it was RFID or something like that. 00:26:26.620 --> 00:26:28.680 No, it's magic. 00:26:28.680 --> 00:26:29.560 It's magic. 00:26:29.560 --> 00:26:31.160 Yeah. 00:26:31.160 --> 00:26:33.820 What a boring job or maybe interesting. 00:26:33.960 --> 00:26:34.360 I don't know. 00:26:34.360 --> 00:26:35.740 Watching people shop. 00:26:35.740 --> 00:26:36.300 Yeah. 00:26:36.300 --> 00:26:37.760 Maybe. 00:26:37.760 --> 00:26:40.220 Anyway. 00:26:40.220 --> 00:26:40.880 All right. 00:26:40.880 --> 00:26:43.200 Well, good episode as usual. 00:26:43.200 --> 00:26:44.420 good to talk with you. 00:26:44.420 --> 00:26:47.680 Thanks to everybody for tuning in and we'll see you next week. 00:26:47.680 --> 00:26:48.060 Yeah.