WEBVTT 00:00:00.001 --> 00:00:03.880 Hey there, thanks for listening. Before we jump into this episode, I just want to remind you 00:00:03.880 --> 00:00:09.680 that this episode is brought to you by us over at Talk Python Training and Brian through his pytest 00:00:09.680 --> 00:00:14.940 book. So if you want to get hands-on and learn something with Python, be sure to consider our 00:00:14.940 --> 00:00:21.720 courses over at Talk Python Training. Visit them via pythonbytes.fm/courses. And if you're 00:00:21.720 --> 00:00:27.320 looking to do testing and get better with pytest, check out Brian's book at pythonbytes.fm slash 00:00:27.320 --> 00:00:31.980 pytest. Enjoy the episode. Hello and welcome to Python Bytes, where we deliver Python news and 00:00:31.980 --> 00:00:39.340 headlines directly to your earbuds. This is episode 252, recorded September 29th, 2021. I'm 00:00:39.340 --> 00:00:45.580 Michael Kennedy. And I'm Brian Okken. And I'm Ethan Swan. Ethan, welcome to Python Bytes. You've been 00:00:45.580 --> 00:00:50.220 over on Talk Python, where you talked about some really cool data science stuff, and now you're 00:00:50.220 --> 00:00:54.900 over here. So thanks for being here. Tell people a bit about yourself. Yeah, I was on Talk Python 00:00:54.900 --> 00:01:00.300 236. So it was a while ago, but that was really cool. I work for a company called 8451. It's the 00:01:00.300 --> 00:01:05.840 data science subsidiary of Kroger. And I'm a data scientist, but basically what I do is build tools, 00:01:05.840 --> 00:01:11.220 mostly which are in Python, for our data science department. So we have like 250 data scientists, 00:01:11.220 --> 00:01:15.860 pretty large department. And I build like packages and some dashboard sort of things, 00:01:15.860 --> 00:01:18.500 just like various technology helper stuff for data science. 00:01:18.500 --> 00:01:23.140 Yeah, it sounds really fun. And you all run what we were talking about before we hit record. 00:01:23.560 --> 00:01:28.240 Probably one of the larger data science groups out there, right? I think of data science as being 00:01:28.240 --> 00:01:32.620 like, there's a couple of folks that are embedded with like a marketing team or a product team or the 00:01:32.620 --> 00:01:37.860 software development team a lot of times, but you are a properly large group of data scientists. 00:01:37.860 --> 00:01:42.460 I mean, in theory, that's what the whole company does. So it's a very cool experience. And often, 00:01:42.460 --> 00:01:47.480 I think that's nice for the team I'm on, because you don't usually get so many customers on internal 00:01:47.480 --> 00:01:51.680 tools. You know, we're building stuff for literally hundreds of people to use. And it's a little bit 00:01:51.680 --> 00:01:55.240 like releasing software externally. So it's yeah, it's a lot of fun. 00:01:55.240 --> 00:02:00.120 Yeah, fantastic. All right. Well, we're definitely looking forward to having your insights here 00:02:00.120 --> 00:02:05.520 for the show. Now, Brian, I do want to start off here. I want to talk about some deck staining. 00:02:05.520 --> 00:02:06.740 Thanks. Yeah. 00:02:06.800 --> 00:02:14.620 So because those of us who are very attentive on Twitter saw that Brian kindly responded to somebody 00:02:14.620 --> 00:02:18.900 who sent us a message and said, Oh, I see you were talking about pallets. We should also talk about 00:02:18.900 --> 00:02:24.600 deck stain and other DIY project resources. And maybe you could put that stupid article on your 00:02:24.600 --> 00:02:29.140 blog. You're like, we're not a blog. We talk about pallets because it's on Flask. And then 00:02:29.140 --> 00:02:34.200 Twitter decided, Oh, you are now classified under the home improvement category. So are we changing 00:02:34.200 --> 00:02:35.020 our theme or what? 00:02:35.020 --> 00:02:42.380 Apparently just me. That's most of you. I've got a few new followers now. And most of them are people 00:02:42.380 --> 00:02:43.840 that like to make things. So. 00:02:43.840 --> 00:02:48.920 Well, it's fun to make things as well. But maybe we'll maybe we'll talk more about SQL and stuff 00:02:48.920 --> 00:02:49.740 like that. What do you think? 00:02:50.080 --> 00:02:56.200 Yeah. So this, this was sent to us by Dave Cochesa. Thanks, Dave. I want to talk about 00:02:56.200 --> 00:03:03.560 SQL fluff. So I had never heard of this, but it looks pretty cool. So SQL fluff is a Python, 00:03:03.560 --> 00:03:10.760 a Python package that is basically a linter for SQL. So that's how interesting. I haven't really 00:03:10.760 --> 00:03:13.920 thought about linting SQL code, but it makes perfect sense. 00:03:14.380 --> 00:03:19.580 Yeah. Well, I mean, there, there is like, I don't really think about it too much either, 00:03:19.580 --> 00:03:23.800 but there's like things like, should you capitalize all the keywords? And some people just like it 00:03:23.800 --> 00:03:30.480 like that. So there is style. There's like both style guides around a SQL. I assume there's style 00:03:30.480 --> 00:03:36.680 guides. And this lets you help, helps you enforce it. Not, not just style guides, but just, you know, 00:03:36.680 --> 00:03:43.240 looking for mistakes and things. The, the page looks really slick for, I like the logo, 00:03:43.380 --> 00:03:48.300 the fluff logo, but, but the, one of the things that's great about it is the documentation. So 00:03:48.300 --> 00:03:55.240 the documentation looks wonderful. And there's one of the neat things about this is there's a 00:03:55.240 --> 00:04:01.500 different rules or different dialects set up so that it treats different things like ANSI and 00:04:01.500 --> 00:04:09.100 Postgres and MySQL different. And, and I'm not sure if these are, or if these are style differences or, 00:04:09.100 --> 00:04:14.380 or, or, or what they're doing different, but, but it's kind of interesting that they'll, they'll, 00:04:14.380 --> 00:04:15.980 there is a difference there. 00:04:16.020 --> 00:04:20.580 Well, one of the things that comes to mind for me, if this reports errors and I suspect it probably 00:04:20.580 --> 00:04:24.900 does, one of the things that comes to mind for me is if using like Microsoft SQL server and you're 00:04:24.900 --> 00:04:30.260 using a parameterized query, because you don't want little Bobby tables in your school, you would say 00:04:30.260 --> 00:04:35.920 at parameter name, whereas in with like MySQL or Oracle, it'd be like a question mark. Right. And I think 00:04:35.940 --> 00:04:41.560 one is illegal in the other syntax. So at least in that regard, I think, I don't know for sure it's 00:04:41.560 --> 00:04:46.600 illegal, but I'm pretty sure like it may be, and it could be that you've got to say what type of 00:04:46.600 --> 00:04:51.300 parameterized specifications and other extensions are valid. And even, I think there's some keywords, 00:04:51.300 --> 00:04:55.480 right? Aren't there some different keywords in some cases? So it would make sense to have to know 00:04:55.480 --> 00:05:00.280 the dialect. Yeah. Yeah. And also like you were saying, if, if there are really are big differences 00:05:00.280 --> 00:05:05.140 differences or even minor differences, there might be some queries that you don't run all the time. 00:05:05.140 --> 00:05:10.520 And so you're not sure if you switch databases that they might be broken if you're trying to port. So 00:05:10.520 --> 00:05:16.400 kind of cool. There's a list of, so it has rules, like a lot of linters, rules for failure. And I like 00:05:16.400 --> 00:05:23.280 the rules page because it talks about the rules, but also shows you the anti-pattern and best practice. 00:05:23.280 --> 00:05:29.180 I kind of like that style. I don't know if I like the terms anti-pattern and I really don't like the 00:05:29.180 --> 00:05:35.600 term best practice, but nonetheless, the, what it's looking for and what you should do different is, 00:05:35.600 --> 00:05:38.540 is a good thing to have in the documentation. It's pretty cool. 00:05:38.540 --> 00:05:43.300 Yeah. I do like the anti-pattern aspect. I, maybe pattern. You're going to have an anti-pattern, 00:05:43.300 --> 00:05:44.260 just have the pattern. I don't know. 00:05:44.260 --> 00:05:48.340 I'm not sure. One of the things that's in the documentation, I can't remember where, 00:05:48.340 --> 00:05:53.540 there it is, that people should be aware of. Supposedly this, even though it has like 00:05:53.540 --> 00:06:02.240 1982. That's interesting. Stars. It's still in alpha phase. So there's a note here that says, 00:06:02.240 --> 00:06:05.960 expect significant changes. So just be aware of that. 00:06:05.960 --> 00:06:11.200 Cool. It doesn't seem major because you're not doing runtime behavior on it, right? It's a thing 00:06:11.200 --> 00:06:13.280 you run against your code and then you look at the output. 00:06:13.280 --> 00:06:20.000 I mean, maybe it's in your CI system or something, but. Yeah. But it's not in production. Right. So like 00:06:20.000 --> 00:06:26.460 you are, you won't get called on a weekend because the site went down because this thing got automatically 00:06:26.460 --> 00:06:31.640 updated or something to that effect. Yep. I guess it could have broken your, your queries, but you know, 00:06:31.640 --> 00:06:38.400 whatever. and it's good to have an audience because, we did have a Paul from the chat say, 00:06:38.460 --> 00:06:43.200 Ethan's correct. There are different keywords between different SQL dialects. Yeah. We use a, 00:06:43.200 --> 00:06:47.940 Oh, sorry, Michael. No, go ahead. Go ahead. No, we, we use a lot of SQL as I would assume most data 00:06:47.940 --> 00:06:53.980 science shops do. but one, what this made me think of was, one contentious topic in people 00:06:53.980 --> 00:06:57.840 who write a lot of SQL is, especially when you have a bunch of column names and you're selecting 00:06:57.840 --> 00:07:03.040 regularly, you know, five to 10 columns, the comma first, I don't know if you've seen the 00:07:03.040 --> 00:07:08.040 approach where you do a new line, comma, column, comma, column. So it lines up really nicely and it 00:07:08.040 --> 00:07:13.420 makes it easier to delete things. that's a very common thing that people feel strongly about. 00:07:13.420 --> 00:07:17.560 So I could imagine linter as being very handy to at least enforce one style throughout a company 00:07:17.560 --> 00:07:23.220 because you know, we don't have that. Yeah. Nice. And then I was going to add that Pamphil Roy on the 00:07:23.220 --> 00:07:30.020 audience says it would be a cool if there was a plugin for D Beaver and Sam Morley asks, I wonder if it 00:07:30.020 --> 00:07:35.700 checks if inputs are sanitized. I don't know if it should, but Paul also asks if it validates for 00:07:35.700 --> 00:07:41.300 syntactical correctness beyond just style. He does say that it catches errors and bad SQL before it 00:07:41.300 --> 00:07:45.540 hits your database. So I'm going to go with the yes. That's pretty cool. Yeah. Ethan, I was thinking 00:07:45.540 --> 00:07:51.520 as I was watching Brian present this, that you probably do way more SQL than I do, even though I 00:07:51.520 --> 00:07:56.800 run in production websites that are backed by databases, not just because there's no SQL, but 00:07:56.800 --> 00:08:02.280 because I use ORMs and the data structure doesn't change. But for, data science, 00:08:02.280 --> 00:08:06.720 you're kind of in a more exploratory mode, right? Yeah. I think it's pretty interesting because, 00:08:06.720 --> 00:08:11.200 um, you know, like listening to this podcast, people talk about using ORMs a lot, but in data science, 00:08:11.200 --> 00:08:16.840 you don't really think of data in that relational model as much. I mean, you can, but like thinking of, 00:08:16.840 --> 00:08:21.980 as of rows as objects is really not common. So I feel like my relationship with databases is totally 00:08:21.980 --> 00:08:27.340 different. My first couple of years, I was mostly writing SQL, but it was, it was literally just 00:08:27.340 --> 00:08:31.060 asking questions for analyses, which is such a different use case than what people use it for, 00:08:31.060 --> 00:08:34.820 for web development. Right. Yeah, absolutely. It's, it's super different, super different. 00:08:34.820 --> 00:08:41.520 But if you were to explore data, wouldn't it be nice to have a desktop application instead of a web 00:08:41.520 --> 00:08:46.880 browser for doing so? So Jupyter and JupyterLab have got to be the most popular way that people 00:08:46.880 --> 00:08:50.820 interact with data on the data science side. It's certainly an exploration stage anyway. 00:08:50.820 --> 00:08:58.160 So super big news that is old news is new again, but better. JupyterLab desktop app is a thing. 00:08:58.160 --> 00:09:04.600 Like I can download JupyterLab. It's an icon on my doc or on my task bar. I click it, 00:09:04.600 --> 00:09:10.060 it runs like an app, but inside of it is Jupyter notebook, like the whole JupyterLab with terminal 00:09:10.060 --> 00:09:15.320 and Python consoles and kernels and all those things. That's cool. That's, that's very nice. 00:09:15.740 --> 00:09:20.980 Yeah. Have you played with this yet, Ethan? No, we, so I don't know how common this is, 00:09:20.980 --> 00:09:25.560 but I think for us, at least mostly people aren't working on their local machines. They're really 00:09:25.560 --> 00:09:31.460 connecting to a session of Python on a remote server. So mostly what we do is we fire up Jupyter 00:09:31.460 --> 00:09:36.320 on, on a remote server. And then from our laptops, we hit that URL to actually look at the notebook. 00:09:36.320 --> 00:09:40.620 So I'm not sure a desktop app would work as well for us, although maybe it's, it's definitely 00:09:40.620 --> 00:09:45.140 interesting. And I wonder if there's some native features of desktop apps that are available, 00:09:45.140 --> 00:09:46.620 that are going to be a reason to switch. 00:09:46.620 --> 00:09:53.660 Well, what I would say right now is it's a really nice self-contained thing. So I'll just 00:09:53.660 --> 00:09:58.740 read the description real quick. JupyterLab app is a cross-platform standalone application. 00:09:58.740 --> 00:10:03.920 Distribution of JupyterLab is a self-contained desktop application, which bundles the Python 00:10:03.920 --> 00:10:09.740 environment and several popular libraries to use and scientific computing, like surely pandas and 00:10:09.740 --> 00:10:14.980 NumPy and those kinds of things. So what you get is you get just an app that's, it's ready to go that 00:10:14.980 --> 00:10:19.340 you could just have somebody install and you can say, here, open this notebook and run it. And long 00:10:19.340 --> 00:10:23.640 as you're using core libraries and stuff like that, you don't have to think, okay, go to the terminal, 00:10:24.080 --> 00:10:30.500 you know, set up the environment and then type JupyterLab. Oh, you need to activate the kernel 00:10:30.500 --> 00:10:35.120 and you got to do this and that, you know, it's just like, it's, it's a real simple, here's, here's the 00:10:35.120 --> 00:10:36.980 thing. No nonsense type of app. 00:10:37.560 --> 00:10:40.500 And you lost a whole bunch of people with just open the command line. 00:10:40.500 --> 00:10:41.900 Yeah. That's so true. 00:10:41.900 --> 00:10:45.460 Yeah. Yeah. So you don't have to hear, right? You just, it's on your doc. You click it just like, 00:10:45.460 --> 00:10:51.460 like you would with Word or Firefox or whatever. And it's, you're there. It starts and manages the 00:10:51.460 --> 00:10:58.080 Jupyter server in the background. There may be a whole host of command line arguments. You can give 00:10:58.080 --> 00:11:04.140 it to say like run, but use that server and other things along those lines or run and use this conda 00:11:04.140 --> 00:11:10.140 environment. I didn't see any of those. And so from what I can tell is it's kind of a local version 00:11:10.140 --> 00:11:14.080 of Jupyter. So it might be super interesting for you all in your workflow. 00:11:14.080 --> 00:11:19.880 One place where I think this would be really handy is teaching beginners. So I actually teach some 00:11:19.880 --> 00:11:24.420 Python, especially for data science classes at the university of Cincinnati. And one thing that 00:11:24.420 --> 00:11:28.420 regularly is really confusing to people is that you can't double click on a notebook file and have it 00:11:28.420 --> 00:11:32.440 open because that's such a typical experience of files on a computer, double click. And there's an 00:11:32.440 --> 00:11:37.600 application that opens that file. Oh, interesting. Yeah. And there are workarounds. If you have 00:11:37.600 --> 00:11:43.540 Anaconda Navigator, it kind of works, although it's, it's a little hitchy. But I would assume 00:11:43.540 --> 00:11:47.080 that if you have a desktop app, you'd be able to register that with the operating system, whatever 00:11:47.080 --> 00:11:53.740 that process is to say, like when I click on .ipynbs, open it. Because I find I have to teach students, 00:11:53.740 --> 00:11:58.500 no, start up Jupyter, open your browser, navigate to that file in the browser. 00:11:58.500 --> 00:12:02.520 Were you in the wrong folder in the terminal when you ran Jupyter? Which is, well, sorry, 00:12:02.520 --> 00:12:06.000 you're now locked out of that tree, that, that part of the tree of the folders. 00:12:06.000 --> 00:12:10.320 And then suddenly you're having a conversation about paths. Yeah. You go down. It really is like 00:12:10.320 --> 00:12:14.380 something I don't like to deal with. So maybe this is what I should recommend for people when I teach. 00:12:14.380 --> 00:12:20.020 What I would recommend is just check it out and try. So I do have a bit of a comment here from Dean 00:12:20.020 --> 00:12:25.040 out in the audience. I like the concept of JupyterLab app, but I'm afraid it'll be a V in V in V, 00:12:25.040 --> 00:12:31.760 V in V, virtual environment nightmare. So what I found interesting is it's discovered, you know, 00:12:31.760 --> 00:12:38.140 when you're creating kernels for Jupyter, you have to run a command. I always forget it and always have 00:12:38.140 --> 00:12:43.860 to duck, duck, go or search this to figure out how to do it again. But I have to get the command to say, 00:12:43.860 --> 00:12:50.000 create this environment and then register that as, so Jupyter finds that content environment, 00:12:50.100 --> 00:12:55.080 that V in V, right? It's IPI kernel install. I have to do this all the time. 00:12:55.080 --> 00:12:59.340 Yeah, exactly. And I know that it's basically that, but the exact command, I always forget. 00:12:59.340 --> 00:13:05.680 So that command, it seems like it picked up the ones that I had run previously for standalone 00:13:05.680 --> 00:13:13.260 terminal JupyterLab. So the virtual environment story is the same as Jupyter itself without that. 00:13:13.260 --> 00:13:19.480 I think all we're getting here is we're getting the libraries plus Python plus the server starting 00:13:19.480 --> 00:13:24.220 all bundled together. And it's basically the same as if you just run it on the command prompt. 00:13:24.220 --> 00:13:30.220 I think as long as was it Dean, as long as Dean doesn't want to be starting Jupyter from the virtual 00:13:30.220 --> 00:13:33.760 environment, it should be fine. Like when you said, Michael, about the kernels, that's the much more, 00:13:33.760 --> 00:13:37.660 I recommend people do it that way. Cause some people do like to just install Jupyter in whatever 00:13:37.660 --> 00:13:42.440 environment they work in and launch it there. But I have a hard time imagining how that would work in this 00:13:42.440 --> 00:13:47.740 case. Yeah, I do as well. And Dean makes the point that once you have to go and register all that kind 00:13:47.740 --> 00:13:51.340 of stuff on you, like when you're down in the terminal doing this, you've kind of lost those 00:13:51.340 --> 00:13:57.100 same people. And that may well be the case, but I can see, you know, this is sort of a first version 00:13:57.100 --> 00:14:01.420 of this. I can see that those are some of the desktop things that could add, right? It could add a 00:14:01.420 --> 00:14:06.600 setting section where you, you have a dialogue for managing these things and creating new ones and so on. 00:14:06.600 --> 00:14:10.420 So it could be pretty neat. Yeah. Definitely something to watch. All right. Before we move on, 00:14:10.700 --> 00:14:17.240 Paul out in the audience has a quick question for you, Ethan, a tangential one. Python has some 00:14:17.240 --> 00:14:23.280 really great SAST tools like Bandit, but I'm not able to find good options for R. And I know that 00:14:23.280 --> 00:14:28.300 you live in a world that does both R and Python. Yeah. Do you have any thoughts on this? I have no 00:14:28.300 --> 00:14:35.980 ideas. I'm going to come off as a fraud, but I don't know what SAST is. I have to, I have to admit, 00:14:36.080 --> 00:14:40.500 like what I do. I know I said, I'm, I'm a data scientist, but in some ways that's nominal. 00:14:40.500 --> 00:14:43.920 Like really a lot of what I do is software development for the data scientists. 00:14:43.920 --> 00:14:48.140 Data scientists are your customer in a sense, or your, your target user. Yeah. 00:14:48.140 --> 00:14:53.040 Yeah. So I think a lot of what I hear from users is that there are certain measurement tools and 00:14:53.040 --> 00:14:57.180 certain statistical tools that are available in R that take longer to get to Python. So I wouldn't 00:14:57.180 --> 00:15:01.220 be surprised if that really is what's happening here, but I don't personally have any suggestions. 00:15:01.220 --> 00:15:07.780 Yeah. Okay. Yeah. So Bandit, is like a tool that will scan for known security vulnerabilities, 00:15:07.780 --> 00:15:12.240 like leaving debug settings on in Django. Oh, see, I was wondering if that was okay. Then, 00:15:12.240 --> 00:15:15.820 then that I also don't know. That's a little different than what I was imagining. 00:15:15.820 --> 00:15:21.900 Yeah. Awesome. All right. Well, since you got the floor, tell us about your first item. 00:15:21.900 --> 00:15:28.840 Sure. So, I found this requests cache package, in a newsletter recently, 00:15:28.840 --> 00:15:32.260 and this might be a little bit of a shorter one because unfortunately I haven't had a reason to 00:15:32.260 --> 00:15:38.460 use it yet. but basically what this does, scrolling down here is you can instantiate 00:15:38.460 --> 00:15:44.580 sessions just like you would with the traditional requests library. So probably, request is one 00:15:44.580 --> 00:15:48.440 of the most commonly used Python packages, I would guess. Yeah. For anybody who's not familiar, 00:15:48.440 --> 00:15:53.660 you use it to make HTTP requests, which is basically to bring anything back from me. And, the tagline, 00:15:53.660 --> 00:15:58.680 I think is HTTP for humans, but it's just known for being easy to use and you can access the internet. 00:15:58.680 --> 00:16:04.360 But one thing that I have found is that, especially if I'm, if I'm testing something in an interactive 00:16:04.360 --> 00:16:09.760 way, not mocking, but I really want to see if my code pulls back what I expect. sometimes I rerun 00:16:09.760 --> 00:16:15.080 the same request over and over and I say, go get this, go get this, go get this often the same data. 00:16:15.080 --> 00:16:20.280 And sometimes that data is large. and that takes a really long time. So requests cache is a way of 00:16:20.280 --> 00:16:26.760 creating a session object that looks and acts the same. But when you call, a get or a post 00:16:26.760 --> 00:16:32.820 request on the same URL, what, with the same data, what you get back is actually just the cached 00:16:32.820 --> 00:16:37.640 version of that data. so you're not waiting every time the first time you incur the network 00:16:37.640 --> 00:16:42.680 latency. And if the server has to do anything to like compute the data, or if it's enough data that 00:16:42.680 --> 00:16:46.760 it takes some time to get to you, you wait for that. But the second time everything runs instantly, 00:16:46.760 --> 00:16:51.360 which is really a big advantage. So I've done some things with web scraping where I'm 00:16:51.360 --> 00:16:55.520 building some kind of, I want to build like a function that pulls some things down and makes, 00:16:55.520 --> 00:17:00.280 uh, or pull some things out of that, but just waiting every time to run the function for it to 00:17:00.280 --> 00:17:05.200 pull from several different pages and, you know, do some computation on that actually makes it pretty 00:17:05.200 --> 00:17:08.000 slow. But if you were able to cache it like this, that'd be a lot faster. 00:17:08.000 --> 00:17:12.360 Yeah. This is nice. I love the fact that it's just a stand in replacement for the request 00:17:12.360 --> 00:17:17.440 session itself. Yeah. And if you scroll down a little more, it actually shows a way to do that 00:17:17.440 --> 00:17:21.500 with the regular requests library. And this actually scares me a little bit. This is kind of, 00:17:21.500 --> 00:17:25.900 kind of magical what's going on here. You just run a one-liner with requests cache, 00:17:25.900 --> 00:17:30.180 and then suddenly the requests library itself works differently. So I wonder if that's a monkey 00:17:30.180 --> 00:17:36.000 patching or what's going on. It probably is, but it is, it is really slick. so I would imagine I'll, 00:17:36.000 --> 00:17:40.000 I'll have a reason to use this soon, but I haven't tested that yet. It does offer a lot of 00:17:40.000 --> 00:17:45.800 configuration options. And one thing I thought was, was a good, idea to look at is an expiration 00:17:45.800 --> 00:17:50.500 date. and that's sort of like, when should you invalidate the cache and actually pull again? 00:17:50.500 --> 00:17:53.880 Cause you maybe should trust that the website is sending you all the same stuff today, but if you 00:17:53.880 --> 00:17:58.480 rerun your code in a week, make sure that it still responds the same way. So it's got some nice options 00:17:58.480 --> 00:18:02.760 like that. I really like that. That's interesting. So you could use it not even just for testing. It could 00:18:02.760 --> 00:18:07.340 be for, actual data, but you know, it's not getting updated very often. So. 00:18:07.720 --> 00:18:12.280 Yeah. For large data is what I was imagining. So I, yeah, like I said, there's, there's been some 00:18:12.280 --> 00:18:15.760 times where I've like pulled things from APIs where they send back a lot of data and you don't want to 00:18:15.760 --> 00:18:20.720 be waiting for that. Yeah. Or even you just want to make sure that, multiple calls to it are 00:18:20.720 --> 00:18:25.720 getting the same data, even if it does change. that's true. Yeah. So keep consistency. 00:18:25.720 --> 00:18:30.440 Interesting. This reminded me a little bit of the, I don't know if people are familiar with the 00:18:30.440 --> 00:18:35.440 at cache, or LRU cache. It used to be another, there's a new one just called at cache in the func 00:18:35.440 --> 00:18:40.720 tools module built into Python. And that's very, very handy once you know, it's there because often 00:18:40.720 --> 00:18:44.420 you have a function that you don't want to recompute the work for. And this is almost like somebody 00:18:44.420 --> 00:18:46.960 rewrote requests with cache in it, which is pretty cool. 00:18:46.960 --> 00:18:52.660 Yeah. It's got a lot of nice features. You know, I think a question from handful out in the audience, 00:18:52.660 --> 00:18:58.800 can it cache to redis because production in memory production caching, you could blow it up, 00:18:58.800 --> 00:19:02.960 right? Blow up the memory. So a couple of things that stood out to me that were interesting there 00:19:02.960 --> 00:19:10.080 was, yeah, you could throw a func tools, LRU cache decorator onto an expensive thing, which is fine, 00:19:10.080 --> 00:19:14.780 but that's in memory, right? And plus things have to be hashable and whatnot, but you could do that. 00:19:14.960 --> 00:19:19.640 but it's in memory. And a lot of times if you have scale out as you do on web apps, 00:19:19.640 --> 00:19:26.540 like in production, as in, Brian was talking about, you have web farms, like five or 10 copies 00:19:26.540 --> 00:19:31.200 of micro whiskey or something running. So then there's still five times you got to do it before 00:19:31.200 --> 00:19:38.100 it really gets cached. And then also it goes to SQLite. So it gets stored to disc, right? So it's 00:19:38.100 --> 00:19:42.500 not even in memory. It's, it's on disc. So like you said, there's other backends as well, but I think 00:19:42.500 --> 00:19:48.120 having just by default going to a SQLite file with an possible expiration means you could just turn 00:19:48.120 --> 00:19:53.020 this on and leave it expire after a day. Go tell us about the backends. There's more than just SQLite. 00:19:53.020 --> 00:19:57.140 Yeah. It does seem like you have some options. I mean, like I said, I haven't had a reason to use 00:19:57.140 --> 00:20:01.140 this. So I haven't toyed around with all these, but it, this, the way this is documented leads me to 00:20:01.140 --> 00:20:05.180 believe that it really is just a drop in replacement, that you can configure what you want to use as 00:20:05.180 --> 00:20:09.040 your backend. And I do wonder, so yeah, what you were saying, Michael, about having multiple instances, 00:20:09.040 --> 00:20:13.700 I do wonder how that would work. Would it check to see if any of the instances had cached this yet? 00:20:13.700 --> 00:20:18.280 would it like proactively go reach out to the cache or? Yeah. Well, I think if you have some 00:20:18.280 --> 00:20:22.880 memory one, it's going to be a hassle, right? Like one of the options is memory. but all the other 00:20:22.880 --> 00:20:29.260 ones, file system, grid FS, Redis, SQLite, those are all support, you know, concurrency. They support. 00:20:29.260 --> 00:20:32.780 Yeah, exactly. So, so then it will scale across process seamlessly. 00:20:33.280 --> 00:20:36.820 Yeah. So that, that could be actually really helpful for something like that, where you have 00:20:36.820 --> 00:20:42.720 a distributed set of workers. Yeah. Yeah, for sure. let's see some fun stuff about your monkey 00:20:42.720 --> 00:20:46.880 patching comment. And Dean says monkey patch is like having a real monkey. It's very cool when other 00:20:46.880 --> 00:20:53.180 people have it, but having it in my house is scary. And yeah, Sam just, has a too much experience at 00:20:53.180 --> 00:20:58.100 the zoo, I think, with that as well. So yeah, monkey patching is a little sketch. 00:20:58.440 --> 00:21:06.820 Oh, nice. All right, Brian, you're up next. Okay. What do we got next? I, so I did something, 00:21:06.820 --> 00:21:14.780 uh, kind of dumb the other day. so I went ahead and I needed, I pushed a new package 00:21:14.780 --> 00:21:21.160 out on PyPI. Really. I was just trying to, to remember how to, the whole process, because I 00:21:21.160 --> 00:21:25.860 wanted to just remind myself of like, if I have something new, something cool I wanted to share, 00:21:26.040 --> 00:21:30.980 how do I get it out there to PyPI? So I was walking through that process and I was doing it 00:21:30.980 --> 00:21:37.580 for a plugin. You did your own typo squatting. Apparently. so I published pytest Slow, 00:21:37.580 --> 00:21:46.120 uh, and then, but who was it? Brian Skin said, cool, but, maybe pytest Skip Slow would be 00:21:46.120 --> 00:21:51.080 better. And I'm like, oh man, that is a better name. cause that's what it does. It skips the slow 00:21:51.080 --> 00:21:56.580 tests by default. So, and this is totally lifted from the pytest documentation about, 00:21:56.580 --> 00:22:01.480 um, they have this example, but nobody's written a plugin for it. So I did this. It's a little tiny 00:22:01.480 --> 00:22:07.720 thing, but so I renamed it, but how do you rename it? So I went out and searched. So how do you rename 00:22:07.720 --> 00:22:14.280 something in PyPI? You can't really do it, but you can create another one. And then, so this is nice. 00:22:14.280 --> 00:22:21.200 Well, who was it? Simon Willison wrote this up. It's a PyPI renamed cookie cutter template. 00:22:21.200 --> 00:22:27.460 And I didn't actually use the template, but I did use these steps. So the steps really are create a 00:22:27.460 --> 00:22:33.640 renamed version of the package, which I did then publish it to PyPI under the new name and create a 00:22:33.640 --> 00:22:40.140 final release for the old name that points to the new one and, depends on it and have dependencies 00:22:40.140 --> 00:22:44.760 so that if somebody installed the old one, they'll really get the new one. it sounds more 00:22:44.760 --> 00:22:49.440 complicated than it is. It's just a few steps, but, there's a cookie cutter you can use. 00:22:49.440 --> 00:22:55.940 The cookie cutter uses setup tools and I didn't want to do that, but, so I used, I did basically 00:22:55.940 --> 00:23:02.220 copied his, the entire thing. and then he's got a demo. So if you, you look at it, so if you go to 00:23:02.220 --> 00:23:07.960 the old one, old version, it'll just have a thing that says, Hey, I'm going to the new one now. 00:23:08.380 --> 00:23:15.420 so I did that and, and it was neat. I really appreciate the steps. and it's, 00:23:15.420 --> 00:23:16.160 it's all good. 00:23:16.160 --> 00:23:16.580 Yeah. 00:23:16.580 --> 00:23:22.140 That's cool. You can also use it for aliases. Like you can install BS for or beautiful soup for, 00:23:22.140 --> 00:23:23.960 right. And it's kind of the same. 00:23:23.960 --> 00:23:26.460 Oh, is that how, is that how they do that? 00:23:26.460 --> 00:23:29.660 I I'm guessing, I don't know, but it sounds like the same. 00:23:29.660 --> 00:23:30.080 I didn't know that. 00:23:31.040 --> 00:23:36.640 So now, so now when I go to pytest, if you go to the old one, it just shows it's now a new name, 00:23:36.640 --> 00:23:37.600 go to the other one instead. 00:23:37.600 --> 00:23:41.180 So, but if I install the old one, it, it kind of just pulls in the new one. 00:23:41.180 --> 00:23:41.780 Yes. 00:23:41.780 --> 00:23:42.400 Yeah. 00:23:42.400 --> 00:23:43.400 Yeah. Very cool. 00:23:43.400 --> 00:23:48.320 Yeah. Brian, you were, you were refreshing on PyPI, but I actually just pushed my first ever 00:23:48.320 --> 00:23:52.060 package to PyPI a couple of weeks ago. And so that was, you know, a bit of a trial, but I was 00:23:52.060 --> 00:23:55.960 amazed at how straightforward it is. The documentation is excellent. It really is, 00:23:55.960 --> 00:23:59.840 is pretty seamless actually for somebody who's never done it before. So who knows, hopefully I 00:23:59.840 --> 00:24:03.460 don't make any mistakes on the one package I have and need to read. Yeah. But we'll see. 00:24:03.460 --> 00:24:05.600 The immutability of it is a little scary, but yeah. 00:24:05.600 --> 00:24:12.400 So for me, the hard part was just understanding that it really was pretty simple. and then also, 00:24:12.400 --> 00:24:16.940 uh, getting the hashes right. So you have to like, you have to get like, you know, 00:24:16.940 --> 00:24:22.000 signatures and stuff to make sure that you can push to the PyPI correctly. So, yeah. 00:24:22.000 --> 00:24:25.040 Yeah. But even the documentation there, it's a little intimidating, but it actually 00:24:25.040 --> 00:24:28.980 turned out to be only a few minutes of work. So that was, that was pretty nice. Good for them. 00:24:28.980 --> 00:24:31.720 I guess PyPI is the people to praise for that. 00:24:31.720 --> 00:24:33.280 Yeah. So what was your package? 00:24:33.280 --> 00:24:40.900 Oh, I, it, it's called pre-mark. It's, it's a spinoff of a JavaScript library for making 00:24:40.900 --> 00:24:46.400 slides. And I just make a lot of slides for teaching. And I actually found, an existing 00:24:46.400 --> 00:24:51.980 package by man. I want to, I mean, yeah, here it is. It is not ready. That's why 00:24:51.980 --> 00:24:57.740 it's a release candidate. but I, I, yeah, I based it on this existing package by 00:24:57.740 --> 00:25:01.880 at Tyler Dave on GitHub, and talk to him a little bit about it. He had already built a really 00:25:01.880 --> 00:25:05.960 lightweight tool and I just expanded on it, but I like to write my slides in Markdown, which is really 00:25:05.960 --> 00:25:09.720 what this is for. You write your slides in Markdown and a bunch of different files. It stitches them 00:25:09.720 --> 00:25:14.720 together and creates a, what's called remark JS presentation. so I use this for my own teaching. 00:25:14.720 --> 00:25:16.420 Nice. I'll check it out. 00:25:16.740 --> 00:25:21.720 But it's, it really is largely a sample project to just like learn how to use PyPI and things like 00:25:21.720 --> 00:25:22.000 that. 00:25:22.000 --> 00:25:28.800 Yeah. Very cool. All right. Up next we have caching. Oh wait, we just talked about caching. No, I have 00:25:28.800 --> 00:25:35.980 more caching. So Django, I have two, two pieces of news on Django. this one comes from Carlton 00:25:35.980 --> 00:25:42.700 Gibson. I'm one of the Django guys and also, one of the hosts at Django chat, the podcast. So 00:25:42.700 --> 00:25:51.800 they are adding a Redis cache backend to Django. So traditionally Django has shipped with Memcache, 00:25:51.800 --> 00:25:57.860 Memcached D, that cache backend with multiple implementations, I think even. So you can go 00:25:57.860 --> 00:26:02.800 there like Django as an ORM, it can talk to stuff. So it has a cache backend as well. And it could talk 00:26:02.800 --> 00:26:08.660 to Memcache, but it couldn't talk to Redis. And they found that the vast majority of people are using 00:26:08.660 --> 00:26:12.780 Redis and they said, well, why don't we have a backend for it? Well, guess what? It's going to. 00:26:12.780 --> 00:26:18.540 So this was merged and this whole conversation here around the PR and the issue is pretty interesting. 00:26:18.540 --> 00:26:25.300 So it starts out and says, this PR aims to support, to add support for Redis to be used as a caching 00:26:25.300 --> 00:26:30.720 backend with Django as Redis is the most popular caching backend. Adding it to Django core dot, 00:26:30.720 --> 00:26:36.220 the Django dot core dot cache module would be a great addition for developers who previously had to rely 00:26:36.220 --> 00:26:40.760 on third party packages and check out how they've got this little checklist and progress. 00:26:40.760 --> 00:26:47.080 These are the things for this PR to come along and work. So create the Redis cache class, do a pickle 00:26:47.080 --> 00:26:51.940 serializer, et cetera, et cetera. Waiting for this other task. Here's some open-ended documentation. 00:26:51.940 --> 00:26:57.620 So I don't think I've seen this really before, like this project tracking in the PR. 00:26:57.620 --> 00:26:58.880 I like it's really cool. 00:26:58.880 --> 00:27:03.480 Yeah, I do too. The other thing to note that this came in on May 23rd and there's a 00:27:03.480 --> 00:27:09.780 large conversation. If you go there, there's 30 pages of conversation about it and you can see 00:27:09.780 --> 00:27:13.640 it evolving. Like, okay, we finally got the test pass and we finally got it implemented. Now let's 00:27:13.640 --> 00:27:19.160 move on to the documentation now, et cetera, et cetera. And then finally, boom, September 15th, 00:27:19.160 --> 00:27:23.380 that's three, three and a half months, something like that. It's closed. So you can actually sort of 00:27:23.380 --> 00:27:29.260 track what the Django team is doing for adding features, like core important features to Django. 00:27:29.340 --> 00:27:34.060 It's always so interesting to watch open source communities like this, especially on somewhat 00:27:34.060 --> 00:27:38.120 contentious issues where people disagree and how they manage these things. I think it's really 00:27:38.120 --> 00:27:43.700 impressive because a lot of teams that even meet in person regularly in our small teams still struggle 00:27:43.700 --> 00:27:48.280 with that kind of stuff, but these huge open source projects manage it. Somehow they implemented the 00:27:48.280 --> 00:27:49.840 feature at the end. So pretty impressive. 00:27:49.840 --> 00:28:16.820 Yeah, absolutely. It's very impressive. Also, I said this was from Carlton. He participated a lot. I'm not 100% sure that he was the originator. This might be Daniel Abasi. So sorry if I misattributed credit there, but for whoever did this, the original issue, I think Carlton had put up. So I'm not sure who was really sort of the initiator there, but I think it's cool. And it's also neat how out in the open, this whole thing is. 00:28:16.820 --> 00:28:19.020 Yeah. Putting the open in open source. 00:28:19.020 --> 00:28:21.540 That's right. Hi, Brian. What you got? 00:28:21.540 --> 00:28:26.380 It's me again. Are we done with our things? 00:28:26.380 --> 00:28:28.840 All right. No, I think I got one more. 00:28:28.840 --> 00:28:33.020 Oh, no, sorry. I totally, I was for some reason in wrong order. Yes, Ethan, you're up next. Sorry. 00:28:33.020 --> 00:28:44.000 Totally fine. So yeah, so I wanted to highlight PEP 612. So I happened upon this, I forget, there was some other PEP I was looking at and they'd linked off to this one. 00:28:44.540 --> 00:28:53.460 But a little bit of background. A PEP is a Python enhancement proposal. It's basically like how ideas are proposed in terms of what to do with Python as a community or as a language. 00:28:54.400 --> 00:29:05.240 And I recently have been really kind of diving into type hinting Python. So there's a surprising number of PEPs about type hinting. And what this one does is something I guess I didn't really realize I needed. 00:29:05.240 --> 00:29:08.320 It was a bit of an annoyance, but I didn't realize there was a fix coming. 00:29:08.980 --> 00:29:18.040 Basically, what it comes down to is quite often you write functions that take in a function and return another function. So there's this example. 00:29:18.540 --> 00:29:26.800 And this, where's the first case where they use it? I think here, param spec. I'll find it while I talk about this. 00:29:26.800 --> 00:29:28.400 But basically... 00:29:28.400 --> 00:29:29.660 A lot of decorator time, yeah. 00:29:29.800 --> 00:29:41.940 Yeah. What you do with decorators is you write functions that take in other functions and return a function that has the same signature, which is to say it takes in the same parameters of the same types and returns the same return type. 00:29:42.520 --> 00:29:45.480 It may have some other modifications of the function, but that's very frequent. 00:29:45.480 --> 00:29:55.520 And so sometimes what you want to say is my decorator, if I want to type the decorator, say what types of things it takes in, it takes in something that is essentially a generic function type. 00:29:55.520 --> 00:30:02.720 Any kind of function is fine that takes in any parameters and returns any return type, as long as it returns the same thing. 00:30:02.720 --> 00:30:04.820 So it's like generics, which you would do with type bars. 00:30:05.860 --> 00:30:14.140 But in this case, you create something called a param spec, and then you pass that as the... 00:30:14.140 --> 00:30:15.940 Oh, man, I lost it where it is in here. 00:30:15.940 --> 00:30:18.200 Oh, here we go. This is what I wanted. 00:30:18.200 --> 00:30:27.620 So you pass it as the type of callable when you type the function that's taken in, and then you say you're returning a callable with the same parameter specification. 00:30:27.620 --> 00:30:29.840 This P is a parameter specification. 00:30:30.280 --> 00:30:38.260 And you make essentially your callables generic on both this parameter specification and on the return value. 00:30:38.260 --> 00:30:40.280 So I know there's a lot to that. 00:30:40.280 --> 00:30:46.200 And I think for people who are typing everything every day, maybe this doesn't seem terribly pertinent. 00:30:46.200 --> 00:30:57.420 What I do, I said I write a lot of Python packages for people to use, and it's important both for quality control and so people know what the return values are and what they should pass into functions to have a lot of typing. 00:30:57.420 --> 00:31:03.880 But really, what this got me thinking about a little bit is just that the Python typing ecosystem is still really evolving. 00:31:03.880 --> 00:31:09.880 Like for somebody who's not super close to following it, it appears that like this is how Python works now. 00:31:09.880 --> 00:31:12.020 And maybe it's always been this way, but it really hasn't. 00:31:12.020 --> 00:31:14.040 And there's a lot of holes in how it works. 00:31:14.040 --> 00:31:15.500 There was no way to do this before. 00:31:15.500 --> 00:31:16.740 And this isn't finished yet. 00:31:16.740 --> 00:31:18.340 This is a pep, but it isn't implemented. 00:31:19.040 --> 00:31:22.680 And so right now, you don't have a way to do typing for this particular feature. 00:31:22.680 --> 00:31:23.760 And that... 00:31:23.760 --> 00:31:27.000 Yeah, flowing type information through different things. 00:31:27.000 --> 00:31:29.260 That is something we haven't done a lot of in Python. 00:31:29.260 --> 00:31:32.720 But as you called out generics and templates, that's like all you do. 00:31:32.720 --> 00:31:34.640 That's the bread and butter of those things. 00:31:34.640 --> 00:31:35.240 Yeah. 00:31:35.240 --> 00:31:37.720 And it's the same idea, but features that aren't there yet. 00:31:37.720 --> 00:31:41.380 So it's just kind of interesting to remember that this stuff is still being added. 00:31:41.500 --> 00:31:45.280 Keeping an eye on when this stuff comes in, it can really make things easier. 00:31:45.280 --> 00:31:49.640 And in the meantime, don't lose too much sleep not being able to type certain things. 00:31:49.640 --> 00:31:52.100 If you can't type it perfectly, that's okay. 00:31:52.100 --> 00:31:55.720 I've actually been reading Luciano Romajo's book, Fluent Python. 00:31:55.720 --> 00:32:00.220 And he makes that point really well, that Python isn't a statically typed language. 00:32:00.220 --> 00:32:02.780 And you shouldn't get too carried away trying to type things. 00:32:02.780 --> 00:32:05.180 As much as is possible, it helps you is worth it. 00:32:05.180 --> 00:32:06.760 But you shouldn't be religious about it. 00:32:06.760 --> 00:32:07.280 Right. 00:32:07.280 --> 00:32:10.800 But if you are building tools and you put this into there eventually. 00:32:11.040 --> 00:32:11.480 Yeah. 00:32:11.480 --> 00:32:14.140 It might help other people who consume your libraries. 00:32:14.140 --> 00:32:18.400 It might help the editors give better autocomplete and error checking and stuff. 00:32:18.400 --> 00:32:19.980 And we catch bugs all the time. 00:32:19.980 --> 00:32:22.500 So as much as is feasible, I think it's totally worth it. 00:32:22.500 --> 00:32:26.240 And actually, there's a couple other peps on that note of things still changing. 00:32:26.240 --> 00:32:28.460 There's a couple other peps that are worth looking at. 00:32:28.460 --> 00:32:31.900 There's a new, more convenient way to write optional types. 00:32:31.900 --> 00:32:33.840 So right now you can say, I know. 00:32:33.840 --> 00:32:35.120 Oh my gosh. 00:32:35.120 --> 00:32:37.000 I've wanted this for so long. 00:32:37.000 --> 00:32:37.420 Yes. 00:32:37.420 --> 00:32:38.020 Yeah. 00:32:38.020 --> 00:32:40.300 So you have to say optional left bracket. 00:32:40.300 --> 00:32:41.880 Then the thing that is optional. 00:32:41.880 --> 00:32:42.360 And then right. 00:32:42.360 --> 00:32:45.120 Like optional bracket string or optional bracket user or whatever. 00:32:45.120 --> 00:32:45.360 Yeah. 00:32:45.360 --> 00:32:46.420 And you got to import optional. 00:32:46.420 --> 00:32:47.100 Don't forget that. 00:32:47.100 --> 00:32:47.260 Yeah. 00:32:47.260 --> 00:32:47.960 That's true. 00:32:47.960 --> 00:32:48.940 You got to import it too. 00:32:48.940 --> 00:32:52.740 And so now there's, there's a, a pet proposing that you could just put a question mark, which 00:32:52.740 --> 00:32:54.940 I guess isn't a problem for the parser, which is pretty nice. 00:32:55.500 --> 00:32:57.220 This one also is in process. 00:32:57.220 --> 00:32:59.620 Maybe this was something that was needed. 00:32:59.620 --> 00:33:02.380 The peg parser, which recently went into, what was that? 00:33:02.380 --> 00:33:03.200 Three, nine, right? 00:33:03.200 --> 00:33:05.820 Where it couldn't do it before, but maybe that's a good point now. 00:33:05.820 --> 00:33:09.420 But yeah, I, you know, they have that in C# and they have that in Swift. 00:33:09.420 --> 00:33:12.700 And I just love like this thing, question mark, right? 00:33:12.700 --> 00:33:17.740 Rather than a null check or specifying into question mark rather than optional bracket of 00:33:17.740 --> 00:33:18.000 int. 00:33:18.000 --> 00:33:18.800 It's just clear. 00:33:18.800 --> 00:33:20.660 I didn't know that was in other languages that, okay. 00:33:20.660 --> 00:33:21.660 That makes a lot more sense. 00:33:21.660 --> 00:33:22.820 And it's phonetic, right? 00:33:22.820 --> 00:33:25.380 Like if it's, if it's an int, you just say int. 00:33:25.460 --> 00:33:27.800 If it's a question mark, it's int, right? 00:33:27.800 --> 00:33:29.620 So you can even just like speak it out really well. 00:33:29.620 --> 00:33:30.020 Like int? 00:33:30.020 --> 00:33:30.540 Maybe. 00:33:30.540 --> 00:33:30.740 Okay. 00:33:30.740 --> 00:33:31.360 That could be null. 00:33:31.360 --> 00:33:31.640 Maybe. 00:33:31.640 --> 00:33:32.340 Could be none. 00:33:32.340 --> 00:33:34.180 That's not obvious to me. 00:33:34.180 --> 00:33:35.260 Really? 00:33:35.260 --> 00:33:35.780 Oh, interesting. 00:33:35.780 --> 00:33:38.240 I feel like that's a nice, a nice syntax, but maybe it isn't. 00:33:38.240 --> 00:33:38.560 Who knows? 00:33:38.560 --> 00:33:39.740 Maybe that won't get approved. 00:33:39.740 --> 00:33:40.320 Yeah. 00:33:40.320 --> 00:33:43.160 I think, I think it may not, but I do, I do hope it does. 00:33:43.160 --> 00:33:44.240 I mean, it's the question mark. 00:33:44.240 --> 00:33:45.940 There's an int or is there, right? 00:33:45.940 --> 00:33:46.740 Like, is it there? 00:33:46.740 --> 00:33:47.400 You're not sure. 00:33:47.400 --> 00:33:50.200 Like there's, there's some subtle symbolism there. 00:33:50.200 --> 00:33:52.860 See, I prefer the int or none. 00:33:52.860 --> 00:33:55.300 I like that as well. 00:33:55.440 --> 00:33:55.740 I agree. 00:33:55.740 --> 00:33:55.940 Yeah. 00:33:55.940 --> 00:33:56.300 That's not bad. 00:33:56.300 --> 00:33:58.400 Now that that's more convenient to write, but that's what, that's only 310. 00:33:58.400 --> 00:34:01.840 And the other languages that support this, and I don't know, I didn't read that PEP well 00:34:01.840 --> 00:34:06.540 enough to know, there's a runtime behavior, not just a type specification behavior. 00:34:06.540 --> 00:34:12.520 So I could say X equals like user question mark dot name. 00:34:12.520 --> 00:34:17.400 It'll either, if the user is none, the name is none, or it'll follow down that, that path 00:34:17.400 --> 00:34:18.740 and say, okay, user's not none. 00:34:18.740 --> 00:34:19.740 So then I'll say dot name. 00:34:19.740 --> 00:34:22.140 Oh, that avoids the none type has no attribute. 00:34:22.140 --> 00:34:22.400 Yeah. 00:34:22.400 --> 00:34:22.540 Yeah. 00:34:22.540 --> 00:34:22.780 Exactly. 00:34:22.780 --> 00:34:23.360 That's really nice. 00:34:23.360 --> 00:34:23.820 Yeah. 00:34:23.820 --> 00:34:24.700 Wow. 00:34:24.700 --> 00:34:25.280 Very cool. 00:34:25.420 --> 00:34:31.180 So, Will is, in the chat and he's got, Oh, I did the wrong one. 00:34:31.180 --> 00:34:32.700 I love that. 00:34:32.700 --> 00:34:35.820 Hey, Will. 00:34:35.820 --> 00:34:37.960 That was pretty good. 00:34:37.960 --> 00:34:38.560 All right. 00:34:38.560 --> 00:34:41.040 And then Ethan, you want to tell us about one more before we wrap it up? 00:34:41.040 --> 00:34:42.240 Oh, just another pep. 00:34:42.240 --> 00:34:42.400 Yeah. 00:34:42.400 --> 00:34:45.860 I, just another thing that is potentially changed how typing works. 00:34:45.860 --> 00:34:49.960 There's right now, there's no way to specify if you've used a type dict, which is to say, 00:34:49.960 --> 00:34:53.260 um, a dictionary with some keys having certain types. 00:34:53.260 --> 00:34:59.300 there was no way to specify what, what keys were optional and which ones weren't. 00:34:59.300 --> 00:35:02.060 You'd either say they were all optional or they were all required and there was nothing 00:35:02.060 --> 00:35:04.520 in between, but there's also a PEP to do that. 00:35:04.660 --> 00:35:07.320 So just, there's a lot of stuff on the horizon to keep an eye out for. 00:35:07.320 --> 00:35:09.840 And these three peps, I think are a good reminder of that. 00:35:09.840 --> 00:35:10.320 Yeah. 00:35:10.320 --> 00:35:10.860 Yeah. 00:35:10.860 --> 00:35:11.380 Yeah. 00:35:11.380 --> 00:35:11.740 Very cool. 00:35:11.740 --> 00:35:12.280 All right. 00:35:12.280 --> 00:35:13.760 Now, now can we throw it to you, Brian? 00:35:14.340 --> 00:35:14.700 Yeah. 00:35:14.700 --> 00:35:14.820 Yeah. 00:35:14.820 --> 00:35:18.860 Now, so this was, this is a suggestion by John Hagan. 00:35:18.860 --> 00:35:23.620 And I just thought I'd throw it in as a, as a, an extra, just one extra. 00:35:23.620 --> 00:35:28.900 So there, we've talked about, the effort at Microsoft and Guido and others, to make 00:35:28.900 --> 00:35:29.700 Python faster. 00:35:29.700 --> 00:35:36.820 and, like there's a, a whole bunch of ideas up on, on a, in the faster C 00:35:36.820 --> 00:35:37.720 Python ideas. 00:35:37.720 --> 00:35:43.280 and in one of this links to a couple of slide decks, talking about the making C 00:35:43.280 --> 00:35:45.280 faster or making Python faster. 00:35:45.280 --> 00:35:52.100 And, one of the things is a slide deck from Guido in, in it, he mentions, various 00:35:52.100 --> 00:35:55.880 other optimizations like maybe zero overhead exception to handling. 00:35:55.880 --> 00:35:59.640 Well, that's neat because that's already in three 11. 00:35:59.640 --> 00:36:06.320 So in three 11, we have, Mark Shannon implementing, zero cost exceptions. 00:36:06.320 --> 00:36:12.100 so if, if, if you have a try statement that doesn't, doesn't catch anything, there's 00:36:12.100 --> 00:36:13.160 no cost to it. 00:36:13.160 --> 00:36:14.660 So that's, that is very cool. 00:36:14.660 --> 00:36:19.840 I, I did a little playing around with this idea and I wrote a program here that calls 00:36:19.840 --> 00:36:22.500 string upper, like a hundred million times in a loop. 00:36:22.500 --> 00:36:26.260 And it does that also in a try except block with no errors. 00:36:26.260 --> 00:36:32.300 And, and so my understanding of this was that it will make entering the tri block in the case 00:36:32.300 --> 00:36:33.920 there's not an exception cheaper. 00:36:33.920 --> 00:36:39.600 and I ran it a hundred million times and I got, you know, not exactly the same, but it's 00:36:39.600 --> 00:36:40.460 really similar. 00:36:40.600 --> 00:36:44.980 But one of the other things, which I'm not doing in my example here, this is a gist 00:36:44.980 --> 00:36:45.960 I'll, I'll put it in the show notes. 00:36:45.960 --> 00:36:52.940 The looking into this comment, Brian is they talk about the number of the, basically the 00:36:52.940 --> 00:36:54.140 size of the call stack. 00:36:54.140 --> 00:36:59.480 And some of the other things, that happen in there about not pushing the exception onto 00:36:59.480 --> 00:37:03.040 the call stack or something, unless it actually happens and those kinds of things. 00:37:03.040 --> 00:37:05.440 So it's supposed to make function calls faster as well. 00:37:05.440 --> 00:37:10.300 So even if my little example wasn't necessarily faster, maybe, maybe something else, there's 00:37:10.300 --> 00:37:12.560 maybe other situations where it is nice. 00:37:12.560 --> 00:37:13.580 Yeah. 00:37:13.580 --> 00:37:13.980 Cool. 00:37:13.980 --> 00:37:16.520 Ethan, anything else you want to just throw out there for people? 00:37:16.520 --> 00:37:21.200 Well, one thing I did want to mention real fast about, about the zero cost exception handling 00:37:21.200 --> 00:37:25.060 is I think it's always tough to teach people about try except blocks and then introduce to 00:37:25.060 --> 00:37:28.980 them that they're actually pretty slow, especially if you use them in a function that gets called 00:37:28.980 --> 00:37:29.600 many times. 00:37:29.600 --> 00:37:32.520 And to be honest, I don't know the reasons for the internals being like that. 00:37:32.820 --> 00:37:35.980 so it's really nice to feel like that might not be true anymore because they're a 00:37:35.980 --> 00:37:39.720 good practice to have, to be able to say like, yeah, be careful, when you write code, especially 00:37:39.720 --> 00:37:44.000 for people like data scientists who aren't day-to-day programmers to say like, oh, it's good practice 00:37:44.000 --> 00:37:45.800 to use these and you shouldn't have to worry about performance. 00:37:45.800 --> 00:37:47.020 So glad to see that. 00:37:47.020 --> 00:37:47.960 Yeah, absolutely. 00:37:47.960 --> 00:37:50.160 And just following up on that real quick. 00:37:50.160 --> 00:37:55.880 if you look at the issue underlying this, where was it? 00:37:55.880 --> 00:37:56.720 This is the right one. 00:37:56.720 --> 00:37:56.860 Yeah. 00:37:56.860 --> 00:38:01.300 They, there's an issue that's linked in the show notes and it actually shows you the disassembly 00:38:01.300 --> 00:38:06.300 into bytecode of what it currently is and what it, it's going to be. 00:38:06.300 --> 00:38:08.660 And it's really, really similar. 00:38:08.660 --> 00:38:13.160 So you can see currently it does like a, the first thing it does is set up a finally and 00:38:13.160 --> 00:38:18.880 then, stuff right at the beginning, but now just do like a no op and then do a return 00:38:18.880 --> 00:38:19.720 value in the good case. 00:38:19.720 --> 00:38:23.640 Otherwise it'll do a push exception and then work with it and so on. 00:38:23.640 --> 00:38:29.500 So it, it pushes off some of the bytecode operations that add like to the call stack, like pushing 00:38:29.500 --> 00:38:34.300 things onto it and so on at the C eval.c level of CPython. 00:38:34.300 --> 00:38:34.940 Yeah. 00:38:34.940 --> 00:38:35.980 Oh, that's very cool. 00:38:35.980 --> 00:38:36.480 Yeah. 00:38:36.480 --> 00:38:41.460 Well, the one thing I wanted to mention, well, I don't know if people have heard of 00:38:41.460 --> 00:38:41.860 pedal board. 00:38:41.860 --> 00:38:43.700 I think Spotify just announced this recently. 00:38:43.700 --> 00:38:46.900 It's, it's basically a Python package that lets you do some things that you might usually 00:38:46.900 --> 00:38:49.820 do using an audio editing tool and it's cool on its own. 00:38:49.820 --> 00:38:53.720 but I had just listened to, I forgot if it was last week. 00:38:53.720 --> 00:38:57.760 So the weeks before episode where Brett Cannon was on, on Python bytes. 00:38:57.760 --> 00:39:02.560 And he talked about how, you know, anytime you see an issue with documentation, just put 00:39:02.560 --> 00:39:03.200 in a pull request. 00:39:03.200 --> 00:39:04.360 Most of the time it'll get accepted. 00:39:04.360 --> 00:39:09.180 And, and he said he's, he's contributed to like 200 or 300 repositories that way. 00:39:09.180 --> 00:39:10.480 So I found this last week. 00:39:10.480 --> 00:39:13.500 And then in this week I was thinking about what I wanted to talk about on the show. 00:39:13.700 --> 00:39:17.900 So I went back to this link and, lo and behold, the last, the last commit was made 00:39:17.900 --> 00:39:21.500 by Brett Cannon and it's removing a stray back tick in the read me. 00:39:21.500 --> 00:39:23.400 So he really practices what he preaches. 00:39:23.400 --> 00:39:25.080 so he seems to be very active. 00:39:25.080 --> 00:39:29.260 He's one of only, nine contributors to this and probably the rest work at Spotify. 00:39:29.260 --> 00:39:31.100 So good for him. 00:39:31.100 --> 00:39:31.780 Nice. 00:39:31.780 --> 00:39:32.000 Yeah. 00:39:32.000 --> 00:39:32.660 That's fantastic. 00:39:32.660 --> 00:39:35.620 Nice to, for that, a little bit of real time follow-up. 00:39:35.620 --> 00:39:35.960 Fantastic. 00:39:35.960 --> 00:39:36.780 All right. 00:39:36.780 --> 00:39:41.480 So I have a few extras and again, I have my, my, banner for extras, extras, extras. 00:39:41.480 --> 00:39:43.620 So, a couple of things here. 00:39:43.620 --> 00:39:50.560 Let's talk about something that Kelly Schuster-Perdes talked about, you know, she and Sean doing 00:39:50.560 --> 00:39:54.580 the, teaching Python podcasts and they're doing great work over there. 00:39:54.580 --> 00:40:00.240 So one of the things that she found for teaching is this thing called ear sketch. 00:40:00.240 --> 00:40:01.600 You probably haven't heard of this. 00:40:01.600 --> 00:40:02.200 I'm guessing. 00:40:02.200 --> 00:40:09.640 So ear sketch is a project from Georgia tech that teaches coding, but through like a DJ 00:40:09.640 --> 00:40:10.860 type of experience. 00:40:11.020 --> 00:40:12.460 She's got a cool video up there. 00:40:12.460 --> 00:40:14.480 It says five minutes and four lines of code. 00:40:14.480 --> 00:40:16.400 And I got this up there going. 00:40:16.400 --> 00:40:17.100 So, yeah. 00:40:17.100 --> 00:40:18.660 Thanks Tony for pointing that out. 00:40:18.660 --> 00:40:20.880 So here I'll just play what she created for everyone real quick. 00:40:32.960 --> 00:40:34.580 People are teaching. 00:40:34.580 --> 00:40:37.100 I want to get folks involved through music and Python. 00:40:37.100 --> 00:40:38.720 That's a real cool project that ear sketch. 00:40:38.720 --> 00:40:41.820 And I told you good stuff about Django before. 00:40:41.820 --> 00:40:43.060 Let me tell you some bad stuff. 00:40:43.060 --> 00:40:43.820 Oh no. 00:40:43.820 --> 00:40:48.740 You might, you might meet little Bobby tables in the Django ORM. 00:40:48.920 --> 00:40:57.180 If you're, running query set order by, and passing some piece of user input into 00:40:57.180 --> 00:41:03.180 what you might be ordering by, you might be ordering by back tick, semi colon drop table 00:41:03.180 --> 00:41:05.520 --or something like that, which you wouldn't want to. 00:41:05.520 --> 00:41:09.080 So basically there's a SQL injection vulnerability in Django. 00:41:09.080 --> 00:41:10.080 What is it? 00:41:10.080 --> 00:41:17.920 320 up to 325 and 300 up to 313. 00:41:17.920 --> 00:41:20.440 But yeah, less than that, right? 00:41:20.440 --> 00:41:22.780 Less than 325 and less than 313. 00:41:22.780 --> 00:41:25.380 So if you have those, 00:41:25.380 --> 00:41:27.500 you definitely want to patch it straight away. 00:41:27.500 --> 00:41:28.800 That's a critical vulnerability. 00:41:28.800 --> 00:41:30.460 So check that out. 00:41:30.460 --> 00:41:32.560 And also that's on untrusted input. 00:41:32.560 --> 00:41:35.000 Yes, that is untrusted input. 00:41:35.000 --> 00:41:36.740 Don't freak if you're not taking, 00:41:36.740 --> 00:41:38.280 what would you like to sort by? 00:41:38.280 --> 00:41:39.100 Please type here. 00:41:39.100 --> 00:41:46.040 But still, you know, it's easy enough to just do a GitHub update, 00:41:46.040 --> 00:41:47.520 just an update to the requirements. 00:41:47.520 --> 00:41:51.460 Now, if you're on, your code is on GitHub and this is the requirement, 00:41:51.460 --> 00:41:52.760 you pinned your version, 00:41:52.760 --> 00:41:57.020 you probably have already gotten this as a security announcement 00:41:57.020 --> 00:41:58.480 and an email sent to you. 00:41:58.480 --> 00:41:59.720 Yeah, that's such a nice feature. 00:41:59.720 --> 00:42:01.100 It is such a nice feature. 00:42:01.100 --> 00:42:02.240 But if you don't pin your version, 00:42:02.240 --> 00:42:03.420 they're like, well, you're on the latest version. 00:42:03.420 --> 00:42:04.380 You're good, right? 00:42:04.420 --> 00:42:04.900 You won't know. 00:42:04.900 --> 00:42:06.600 So it still may slip through. 00:42:06.600 --> 00:42:07.200 All right. 00:42:07.200 --> 00:42:07.940 Yeah. 00:42:07.940 --> 00:42:11.300 And Chris May on the live stream has some philosophical thoughts for us. 00:42:11.300 --> 00:42:13.620 He says sometimes he doesn't even trust his own input. 00:42:13.620 --> 00:42:15.620 Yes, we all, we've all been there. 00:42:15.620 --> 00:42:17.320 Chris, don't inject yourself. 00:42:17.320 --> 00:42:19.480 All right. 00:42:19.480 --> 00:42:21.820 Shall we wrap this up with some laughs? 00:42:21.820 --> 00:42:22.640 Yes. 00:42:23.080 --> 00:42:25.240 Brian, this is going to take some role-playing again. 00:42:25.240 --> 00:42:26.820 A nice little cartoon for us. 00:42:26.820 --> 00:42:27.860 This is QA101. 00:42:27.860 --> 00:42:30.960 Speaking of the CVE I just spoke about, 00:42:30.960 --> 00:42:33.280 and, you know, if you fix a minor bug, 00:42:33.280 --> 00:42:34.860 you might get credit, like, whatever. 00:42:34.860 --> 00:42:36.780 We fixed a little tiny bug, right? 00:42:36.780 --> 00:42:37.880 Formatting a log file. 00:42:37.880 --> 00:42:41.040 If you fix a critical bug, like, wow, that seems super important. 00:42:41.040 --> 00:42:42.560 You've been doing good work this week, right? 00:42:42.600 --> 00:42:46.340 So here's two developers in an open office sort of space. 00:42:46.340 --> 00:42:47.360 Brian, you be the guy. 00:42:47.360 --> 00:42:48.540 I'll be the woman developer. 00:42:48.540 --> 00:42:49.280 Okay. 00:42:49.280 --> 00:42:51.360 Which priority should I give this bug? 00:42:51.360 --> 00:42:52.980 Well, is it easy to fix? 00:42:52.980 --> 00:42:53.860 Yep. 00:42:53.860 --> 00:42:55.060 I'll fix it immediately. 00:42:55.060 --> 00:42:56.420 Critical. 00:42:56.420 --> 00:42:57.560 Critical. 00:42:57.560 --> 00:43:00.980 Finding the correct bug priority is key, they say. 00:43:00.980 --> 00:43:01.980 So very nice. 00:43:01.980 --> 00:43:03.920 I'll link to that little cartoon in the show notes. 00:43:03.920 --> 00:43:04.980 I don't get it. 00:43:04.980 --> 00:43:07.920 Because you're going to get more credit for fixing critical bugs. 00:43:08.040 --> 00:43:09.200 And if you can fix it right away. 00:43:09.200 --> 00:43:10.880 Yeah, it looks like you did way more work. 00:43:10.880 --> 00:43:12.460 You did so much more work. 00:43:12.460 --> 00:43:15.780 Brian over there only fixed, like, medium bugs. 00:43:15.780 --> 00:43:17.560 Ethan and I took out the critical. 00:43:17.560 --> 00:43:18.000 Exactly. 00:43:18.000 --> 00:43:19.860 You do your T-shirt sizing after you finish. 00:43:19.860 --> 00:43:21.780 After you take all the work, 00:43:21.780 --> 00:43:23.300 you assume everything you took was a large. 00:43:23.300 --> 00:43:24.800 Yeah. 00:43:24.800 --> 00:43:26.120 So, yep. 00:43:26.120 --> 00:43:26.560 Exactly. 00:43:26.560 --> 00:43:28.120 I keep asking people, 00:43:28.120 --> 00:43:30.440 so what are the points equal in hours? 00:43:30.440 --> 00:43:32.320 No, we can't talk about that. 00:43:32.320 --> 00:43:32.840 Okay. 00:43:32.840 --> 00:43:36.080 Do I use powers of two? 00:43:36.080 --> 00:43:36.900 What do I do? 00:43:36.900 --> 00:43:37.460 Yeah. 00:43:37.460 --> 00:43:37.700 Anyway. 00:43:38.060 --> 00:43:38.260 Cool. 00:43:38.260 --> 00:43:40.280 Well, thanks, Ethan, for coming on the show. 00:43:40.280 --> 00:43:40.880 It was fun. 00:43:40.880 --> 00:43:41.700 Yeah, this was great. 00:43:41.700 --> 00:43:42.440 Thanks for having me. 00:43:42.440 --> 00:43:44.060 Yeah, it's been fantastic to have you here. 00:43:44.060 --> 00:43:44.940 Thanks for being here. 00:43:44.940 --> 00:43:46.040 Brian, thanks as always. 00:43:46.040 --> 00:43:46.760 Thanks. 00:43:46.760 --> 00:43:47.500 Bye, everyone. 00:43:47.500 --> 00:43:49.340 Thanks for listening to Python Bytes. 00:43:49.340 --> 00:43:52.160 Follow the show on Twitter via at Python Bytes. 00:43:52.160 --> 00:43:55.280 That's Python Bytes as in B-Y-T-E-S. 00:43:55.280 --> 00:43:58.140 Get the full show notes over at Pythonbytes.fm. 00:43:58.140 --> 00:44:00.240 If you have a news item we should cover, 00:44:00.240 --> 00:44:03.480 just visit Pythonbytes.fm and click Submit in the nav bar. 00:44:03.480 --> 00:44:05.600 We're always on the lookout for sharing something cool. 00:44:05.600 --> 00:44:07.500 If you want to join us for the live recording, 00:44:07.680 --> 00:44:10.140 just visit the website and click Livestream 00:44:10.140 --> 00:44:13.020 to get notified of when our next episode goes live. 00:44:13.020 --> 00:44:17.420 That's usually happening at noon Pacific on Wednesdays over at YouTube. 00:44:17.420 --> 00:44:19.620 On behalf of myself and Brian Okken, 00:44:19.620 --> 00:44:20.800 this is Michael Kennedy. 00:44:20.800 --> 00:44:23.060 Thank you for listening and sharing this podcast 00:44:23.060 --> 00:44:24.520 with your friends and colleagues.