WEBVTT 00:00:00.001 --> 00:00:05.200 Hello and welcome to Python Bytes, where we deliver Python news and headlines directly to your earbuds. 00:00:05.200 --> 00:00:10.620 This is episode 39, recorded August 14th, 2017. 00:00:10.620 --> 00:00:18.280 I'm Brian Okken, and again, Michael is on vacation, and we have a guest host, and this week we have Mahmoud Hashemi. 00:00:18.280 --> 00:00:19.740 Hey, Mahmoud. 00:00:19.740 --> 00:00:20.200 Hi there. 00:00:20.200 --> 00:00:22.520 Great to be here. 00:00:22.520 --> 00:00:27.460 Yeah, you've been on Testing Code, and you've been on Talk Python a couple times. 00:00:27.460 --> 00:00:28.960 Yeah, a couple of my faves, for sure. 00:00:28.960 --> 00:00:34.760 Yeah, well, when I was looking up Talk Python, I noticed that you were on episode 4 in 54. 00:00:34.760 --> 00:00:41.940 Yeah, and I don't know, when Guido was on, you know, Michael was kind enough to ask my question, and I did like a panel thing. 00:00:41.940 --> 00:00:46.780 I don't know, I guess, yeah, it's been really nice to have repeat appearances. 00:00:46.780 --> 00:00:49.380 People recognize me by my voice now. 00:00:49.380 --> 00:00:52.660 It's kind of strange, but like, I'm very appreciative at the same time. 00:00:52.660 --> 00:00:53.340 That's good. 00:00:53.340 --> 00:00:54.140 That's great. 00:00:54.140 --> 00:00:56.560 And so, thanks a lot for helping to do this today. 00:00:56.560 --> 00:00:59.220 Yeah, hopefully I can do Michael Wright taking his spot here. 00:00:59.220 --> 00:01:00.580 Well, let's just jump right in. 00:01:00.580 --> 00:01:02.320 I'm really excited about your first topic. 00:01:02.320 --> 00:01:02.800 Oh, sure. 00:01:02.980 --> 00:01:04.000 So, let's see. 00:01:04.000 --> 00:01:08.800 First up, I mean, one thing that's been on my radar, I'm not sure if you guys talk about this before. 00:01:08.800 --> 00:01:12.680 Like, sometimes I'm listening to Python bytes, and it's a little bit garbled or something. 00:01:12.680 --> 00:01:14.700 Have you guys tried calling decode? 00:01:14.960 --> 00:01:17.740 I'm kind of curious, like, why it's not Python stirs. 00:01:17.740 --> 00:01:22.800 But one thing that's been on my radar is the new PyPI. 00:01:22.800 --> 00:01:32.820 So, if you haven't been on Distutils, SIG, you may have not seen that there's actually a new PyPI, pypi.org. 00:01:32.820 --> 00:01:37.420 And this is going to be the Python package index going forward. 00:01:37.600 --> 00:01:40.200 So, this is what we've been calling Warehouse before. 00:01:40.200 --> 00:01:40.840 Is that right? 00:01:40.840 --> 00:01:45.300 So, Warehouse is the software that runs PyPI, you know? 00:01:45.300 --> 00:01:45.540 Okay. 00:01:45.940 --> 00:01:48.600 And so, yeah, it's a package index. 00:01:48.600 --> 00:01:52.140 It's going to be where all of your wheels and SDISTs live. 00:01:52.140 --> 00:01:55.500 And there's basically a lot of development that's happening here. 00:01:55.500 --> 00:01:59.740 My friend Donald Stuffed is doing an amazing job with his team. 00:01:59.740 --> 00:02:05.080 Basically, yeah, we're up to 114,598 projects at the moment. 00:02:05.080 --> 00:02:12.120 This even lists the number of files, almost a million files with 230,000 users. 00:02:12.220 --> 00:02:15.980 And so, yeah, I would definitely check out this pypi.org for yourself. 00:02:15.980 --> 00:02:21.140 But for the most part, I wanted to talk about how they're deprecating the old PyPI. 00:02:21.140 --> 00:02:26.800 So, pypi.python.org is now basically just a read-only interface. 00:02:26.800 --> 00:02:33.020 And if you've tried to upload a package recently, then you may have seen an error, HTTP 4.10, 00:02:33.020 --> 00:02:37.940 which is like a 4.04, but this is 4.10 gone, meaning it was here, but now it's gone. 00:02:38.240 --> 00:02:42.480 And so, yeah, you basically make sure to use a new version of setup tools, 00:02:42.480 --> 00:02:45.000 and it'll automatically start using the new one. 00:02:45.000 --> 00:02:48.960 As long as your configs don't state otherwise, you might have to update a config. 00:02:48.960 --> 00:02:52.440 But this is a tremendous leap forward in a lot of ways. 00:02:52.440 --> 00:02:55.460 And they need some help doing it too, you know? 00:02:55.460 --> 00:02:57.140 So, it's all open source on GitHub. 00:02:57.140 --> 00:02:58.500 There are issues. 00:02:58.500 --> 00:02:59.960 I'm working on one right now. 00:02:59.960 --> 00:03:02.900 Yeah, it's got a lot of cool features. 00:03:02.900 --> 00:03:04.100 Have you taken a look, Brian? 00:03:04.100 --> 00:03:05.500 I've looked around a little bit. 00:03:05.500 --> 00:03:09.980 Now, one of the things I've noticed, like right off the bat, is it says up at the top, 00:03:09.980 --> 00:03:11.500 there's a big red bar that says... 00:03:11.500 --> 00:03:12.480 I know, it's kind of scary. 00:03:12.480 --> 00:03:12.980 Yeah. 00:03:12.980 --> 00:03:16.740 So, do you know, I'm guessing eventually at some point they'll, 00:03:16.740 --> 00:03:20.820 the other interface will just redirect to here, or is there... 00:03:20.820 --> 00:03:22.920 I mean, you know, cool URLs don't change. 00:03:22.920 --> 00:03:27.500 Personally, in my view, I'd like it if they just kept it up and put the red bar over there, 00:03:27.500 --> 00:03:31.140 that this is a, you know, archive version of PyPI. 00:03:31.440 --> 00:03:34.280 But for now, all those URLs are still working. 00:03:34.280 --> 00:03:39.880 And if you ask me, pypi.org has been in use for so long, because actually, if you've paid 00:03:39.880 --> 00:03:44.500 close attention, a lot of your downloads, pip is downloading from the new one. 00:03:44.500 --> 00:03:45.000 Oh, okay. 00:03:45.000 --> 00:03:47.280 So, yeah, it's been in production a long time. 00:03:47.280 --> 00:03:51.540 In fact, they just hit, I think, a petabyte a month in bandwidth downloads. 00:03:52.000 --> 00:03:57.080 So, yeah, just for a sense of the cost there, I think it's like in the tens of thousands, 00:03:57.080 --> 00:04:00.840 like 30, 40,000 a month to host PyPI. 00:04:00.840 --> 00:04:04.980 And that's kindly donated by the Fastly CDN. 00:04:04.980 --> 00:04:10.640 Should they stop feeling so generous, you know, we got to support our community somehow. 00:04:10.640 --> 00:04:13.140 So, there is a donate button here. 00:04:13.180 --> 00:04:18.580 But I think that right now, what they need most is sort of like people to work on cool 00:04:18.580 --> 00:04:24.520 features, like one that I saw has been working on that I'm very excited for, not strictly PyPI.org, 00:04:24.520 --> 00:04:27.280 but same team, the Python Packaging Authority. 00:04:27.280 --> 00:04:31.540 They are working on making a dependency graph between all packages. 00:04:31.540 --> 00:04:37.760 So, if you've ever wondered what depends on what ahead of time, then this would enable that. 00:04:37.760 --> 00:04:39.160 So, yeah. 00:04:39.460 --> 00:04:40.600 How do I start working on it? 00:04:40.600 --> 00:04:42.240 Do I go to the GitHub page? 00:04:42.240 --> 00:04:42.600 Yeah. 00:04:42.600 --> 00:04:48.560 So, I think it's github.com forward slash PyPA or I think it might be forward slash warehouse. 00:04:48.560 --> 00:04:49.000 Yeah. 00:04:49.000 --> 00:04:49.360 Okay. 00:04:49.360 --> 00:04:55.140 So, and, you know, Donald has been very candid about like, you know, the areas that need 00:04:55.140 --> 00:04:57.660 development and he's been working very hard. 00:04:57.660 --> 00:05:02.260 He's at Amazon now and he spends some time working on stuff there. 00:05:02.260 --> 00:05:04.720 Oh, one last thing, like distutils, right? 00:05:04.720 --> 00:05:10.960 So, so they still, there's an email list called distutils-sig, which stands for special interest 00:05:10.960 --> 00:05:11.320 group. 00:05:11.320 --> 00:05:16.840 And so, distutils-sig, you can just go join the listserv and you can read the archive and 00:05:16.840 --> 00:05:18.040 see the conversations they're having. 00:05:18.040 --> 00:05:20.960 If you care about packaging, you're probably already on there. 00:05:20.960 --> 00:05:23.480 But if you aren't, definitely subscribe. 00:05:23.480 --> 00:05:24.640 Oh, I didn't know about it. 00:05:24.640 --> 00:05:25.000 Yeah. 00:05:25.000 --> 00:05:28.300 So, we'll try to drop a link in the show notes for that. 00:05:28.300 --> 00:05:29.960 So, okay. 00:05:30.060 --> 00:05:31.600 Well, that's, that's really cool. 00:05:31.600 --> 00:05:33.580 Pretty good for first topic, you know, I don't know. 00:05:33.580 --> 00:05:35.180 Yeah, definitely. 00:05:35.180 --> 00:05:41.620 And I, and the one, one thing I want to add is I know that Donald has been vocal before about 00:05:41.620 --> 00:05:43.680 how awful the previous code was. 00:05:43.680 --> 00:05:44.260 Yeah. 00:05:44.260 --> 00:05:46.580 I mean, it's, it's pretty old code, right? 00:05:46.580 --> 00:05:47.580 Like, I don't even know. 00:05:47.580 --> 00:05:50.820 I, it may not predate WSGI, but it's pretty old. 00:05:50.820 --> 00:05:52.100 You've looked at the new code. 00:05:52.100 --> 00:05:52.900 I've looked at the new code. 00:05:52.900 --> 00:05:54.720 I can talk about the new code if we got a second. 00:05:54.720 --> 00:05:55.940 So, I've, I've looked at it. 00:05:55.940 --> 00:05:56.620 I've used it. 00:05:56.620 --> 00:05:58.420 It's got 100% coverage. 00:05:58.740 --> 00:06:00.540 It's got a lot of CI stuff set up. 00:06:00.540 --> 00:06:01.740 It uses Docker. 00:06:01.740 --> 00:06:07.740 I had a little bit of trouble, like, you know, with the make-based approach to running the 00:06:07.740 --> 00:06:09.080 thing, but it's pretty complex. 00:06:09.080 --> 00:06:12.000 Like, it runs, I think, an elastic search and all this stuff. 00:06:12.000 --> 00:06:14.060 So, basically, yeah, you just. 00:06:14.060 --> 00:06:17.940 People shouldn't be afraid to help out just because they've heard bad things about the 00:06:17.940 --> 00:06:18.320 old code. 00:06:18.320 --> 00:06:21.320 No, the new code is, it's pretty idiomatic, I think. 00:06:21.320 --> 00:06:26.620 And, you know, if you're familiar with SQLAlchemy, and I think it uses also maybe like 00:06:26.620 --> 00:06:28.080 Pyramid, I think. 00:06:28.360 --> 00:06:31.040 And it looks like the tests are in pytest, too. 00:06:31.040 --> 00:06:36.720 Yeah, the test is definitely in pytest, which is, frankly, the only way I've heard and have 00:06:36.720 --> 00:06:38.120 also found myself. 00:06:38.120 --> 00:06:40.280 So, yeah, it's been good. 00:06:40.280 --> 00:06:44.100 Oh, I could talk about this for a long time, but let's move on to the next topic. 00:06:44.100 --> 00:06:44.600 Absolutely. 00:06:44.820 --> 00:06:47.540 So, one of the things I just read about this yesterday. 00:06:47.540 --> 00:06:54.440 There's a, I read about it on Make, I think it's the Make website, but it's CircuitPython 00:06:54.440 --> 00:06:59.540 is now going to be, is supported by a whole bunch of Adafruit hardware. 00:06:59.700 --> 00:07:03.500 It's great news for hardware hackers and also tinkerers like myself. 00:07:03.500 --> 00:07:06.280 And so, we'll put a link in the show notes to the Make article. 00:07:06.280 --> 00:07:12.520 But there's also, so I had heard Adafruit announced CircuitPython in January. 00:07:12.520 --> 00:07:16.680 And it's a, it's an open source, it's based on MicroPython. 00:07:16.680 --> 00:07:21.540 So, CircuitPython is also open source, but it's, so I'm not quite sure how they differ. 00:07:22.080 --> 00:07:25.560 But they've added some things to make it easier to control hardware. 00:07:25.560 --> 00:07:35.740 And they already had, like, two devices, Metro M0 and Feather M0 express versions that support 00:07:35.740 --> 00:07:37.220 CircuitPython right off the bat. 00:07:37.220 --> 00:07:41.280 And they're, I guess they're working on a Circuit Playground Express. 00:07:41.280 --> 00:07:43.500 All of these look like really fun things. 00:07:43.500 --> 00:07:49.480 But the thing that really caught my attention was Gemma M0 that was announced at the end of 00:07:49.480 --> 00:07:49.860 July. 00:07:50.300 --> 00:07:52.600 And this thing is, like, the size of a quarter. 00:07:52.600 --> 00:07:58.000 It's a little small thing that you can make wearable software projects with, like LEDs and 00:07:58.000 --> 00:07:58.300 whatever. 00:07:58.300 --> 00:08:02.300 And you just plug it in into your computer. 00:08:02.300 --> 00:08:04.640 And you instantly, it's like an extra drive. 00:08:04.640 --> 00:08:09.960 You can see a main.py and it just, you can just start programming Python right away. 00:08:09.960 --> 00:08:10.440 Yeah, right. 00:08:10.440 --> 00:08:13.800 So, basically, it just, like, it sort of functions kind of like a USB drive. 00:08:13.800 --> 00:08:16.080 And there's a single main entry point in there. 00:08:16.080 --> 00:08:17.400 And you can just modify it. 00:08:17.400 --> 00:08:20.200 And then, you know, you don't need to install anything. 00:08:20.200 --> 00:08:21.800 Or anything like that. 00:08:21.800 --> 00:08:22.960 Yeah, there's no loading. 00:08:22.960 --> 00:08:24.980 Apparently, it does support Arduino. 00:08:24.980 --> 00:08:28.520 But you don't, like, right off the bat, you don't have to install anything. 00:08:28.520 --> 00:08:29.660 You can just start programming. 00:08:29.660 --> 00:08:32.720 And these are, they, right now, they're currently out of stock. 00:08:32.720 --> 00:08:35.480 But I'm sure they get new stuff in pretty quick. 00:08:35.480 --> 00:08:39.480 But they're, it's under 10 bucks to start programming some wearable programming. 00:08:39.700 --> 00:08:41.540 So, I definitely have to get one of these. 00:08:41.540 --> 00:08:41.780 Yeah. 00:08:41.780 --> 00:08:43.720 I can't wait to start wearing some running Python. 00:08:43.720 --> 00:08:45.880 That'd be taking it to the next level. 00:08:45.880 --> 00:08:51.220 And I'm also going to link to what I thought was great was they realized that, I mean, they 00:08:51.220 --> 00:08:55.100 are encouraging people to use Python if they can for programming hardware. 00:08:55.380 --> 00:08:58.760 But they realized that a lot of people are new to the Python community. 00:08:58.760 --> 00:09:04.320 So, there's a page called Creating and Sharing Circuit Python, a Circuit Python library. 00:09:05.060 --> 00:09:09.840 And it's got a whole bunch of great links, like, basically just telling people what, what 00:09:09.840 --> 00:09:15.300 we, when we call it, say library, we mean a package or a module with a setup file and doing 00:09:15.300 --> 00:09:15.880 it all right. 00:09:15.880 --> 00:09:20.220 And there's little intros to GitHub and Read the Docs and Travis. 00:09:20.220 --> 00:09:24.440 So, is it like, when you say package or module, is this their own format? 00:09:24.440 --> 00:09:27.180 Or is this like Python packages, wheels, that sort of thing? 00:09:27.180 --> 00:09:28.620 Yeah, it's just Python stuff. 00:09:28.620 --> 00:09:32.560 But it's just really quick tutorials to get people up to speed fast. 00:09:32.560 --> 00:09:32.900 Sure. 00:09:33.080 --> 00:09:36.740 So, it's like sort of a full, it's got like an end-to-end thing. 00:09:36.740 --> 00:09:39.620 It doesn't just send you left and right to other sites. 00:09:39.620 --> 00:09:40.400 Yeah, right. 00:09:40.400 --> 00:09:42.100 It's really telling you everything. 00:09:42.100 --> 00:09:43.760 And it's, they're pretty condensed. 00:09:43.760 --> 00:09:47.580 Actually, they're pretty good job condensing all that information. 00:09:47.580 --> 00:09:51.080 Yeah, you don't need the whole context and history of Python packaging. 00:09:51.080 --> 00:09:55.100 It's been, we've come a long way since, you know, eggs and that sort of stuff. 00:09:55.100 --> 00:09:55.440 Yeah. 00:09:55.440 --> 00:10:02.680 And then one of the things that is kind of interesting is they have a concept of bundles. 00:10:02.680 --> 00:10:10.340 And really, all the bundle is, is a bunch of installable Python packages that are zipped up into a bundle. 00:10:10.340 --> 00:10:11.440 Hmm, sure. 00:10:11.440 --> 00:10:18.400 We normally don't really care about that because on a larger computer, it's not that big of a deal. 00:10:18.580 --> 00:10:22.920 But these little tiny devices, you still have to care about how big it is. 00:10:22.920 --> 00:10:28.560 So, you're only, you might want to get everything that somebody cool has made, but you don't need it all. 00:10:28.560 --> 00:10:32.280 You just need like the little part that, you know, blinks the LED for you or whatever. 00:10:32.280 --> 00:10:32.600 Sure. 00:10:32.700 --> 00:10:34.240 So, it sort of freezes it all together. 00:10:34.240 --> 00:10:34.700 Yeah. 00:10:34.700 --> 00:10:36.440 These embedded applications are interesting. 00:10:36.440 --> 00:10:39.820 So, now that, so I maintain this one library called hyperlink. 00:10:39.820 --> 00:10:43.340 And I guess it's pretty widely used because twisted depends on it. 00:10:43.340 --> 00:10:47.960 And so, I've gotten some interesting feedback of a few things. 00:10:47.960 --> 00:10:49.620 Like one code review I just went through. 00:10:49.620 --> 00:10:51.160 I promise this is related. 00:10:51.640 --> 00:10:55.820 Basically, I'm using pytest and I'm writing my assert statements. 00:10:55.820 --> 00:10:59.600 And, you know, I love that pytest rewriting with the great error messages and so forth. 00:10:59.600 --> 00:11:05.320 But I got a comment on my code review that these tests are not runnable in an embedded environment 00:11:05.320 --> 00:11:10.260 because they will run with dash OO, which elides all of those assert statements. 00:11:10.260 --> 00:11:15.420 And I'm like, well, you're kind of running the tests wrong if you're not using pytest. 00:11:15.420 --> 00:11:19.240 But in these embedded environments, I don't know, maybe the convention is different. 00:11:20.020 --> 00:11:22.520 So, when you get yours, definitely like test it out. 00:11:22.520 --> 00:11:30.300 Maybe you'll have to put a little caveat on your pytest recommendation if that's not what we can do on hardware. 00:11:30.300 --> 00:11:30.760 I don't know. 00:11:30.760 --> 00:11:31.600 Oh, that's interesting. 00:11:31.600 --> 00:11:32.660 Yeah. 00:11:32.660 --> 00:11:34.660 Yeah, I'll definitely have to check that out. 00:11:34.660 --> 00:11:38.140 So, I don't want the hardware people to not buy my book. 00:11:38.140 --> 00:11:38.860 That would be terrible. 00:11:38.860 --> 00:11:40.000 Well, that's the thing. 00:11:40.000 --> 00:11:47.480 With something like hyperlink, which is for URLs, I'm like 99.9% sure it's going to run exactly the same everywhere. 00:11:48.060 --> 00:11:52.780 So, I'm confident that if it runs on my machine, it runs on Travis CI, it runs on CodeVayer or whatever. 00:11:52.780 --> 00:11:55.500 It's going to AppVayer, I think. 00:11:55.500 --> 00:11:56.580 It'll be fine. 00:11:56.580 --> 00:12:01.760 But at the same time, hardware people can be sticklers, as I'm sure you know. 00:12:01.760 --> 00:12:03.940 So, I respect that. 00:12:03.940 --> 00:12:04.580 I respect that. 00:12:04.580 --> 00:12:04.760 Cool. 00:12:04.760 --> 00:12:05.820 Yeah, neat. 00:12:06.400 --> 00:12:08.340 Well, what do we got next, Mahmoud? 00:12:08.340 --> 00:12:08.820 Oh, right. 00:12:08.820 --> 00:12:09.600 It's back to me. 00:12:09.600 --> 00:12:10.540 So, I don't know. 00:12:10.540 --> 00:12:18.280 I mean, so I spend a lot of my time pretty deep into development of all sorts of infrastructural sorts. 00:12:18.840 --> 00:12:24.100 And I find myself subscribed to Python Dev, Python Ideas, Distutils SIG. 00:12:24.100 --> 00:12:27.960 And, you know, you can't read everything there and still have a life. 00:12:27.960 --> 00:12:30.020 So, only a few things catch my eye. 00:12:30.020 --> 00:12:34.900 But this one in particular caught my eye because my friend Hinek has this great library called Adders. 00:12:34.900 --> 00:12:43.600 If you haven't heard of it, my other friend Glyph has a whole blog post that tells you why you have to use this library, ATTRS. 00:12:43.600 --> 00:12:50.360 And it's basically class decorators that make writing high-level classes very easy. 00:12:50.360 --> 00:12:55.840 So, it sort of derives from this sort of tradition of name tuples, right? 00:12:55.840 --> 00:13:03.320 Raymond Hedinger had this great idea to make name tuples, which let us define a class-like structured thing within just one line. 00:13:03.860 --> 00:13:09.260 But the problem with name tuples is that if you want to add methods to it, then you have to inherit from it. 00:13:09.260 --> 00:13:10.960 And they're immutable by default. 00:13:10.960 --> 00:13:17.780 And they don't really, even though they generate a __init__() for you, they don't do a whole heck of a lot of validation. 00:13:17.780 --> 00:13:23.800 So, Adders comes along, fixes all these things, adds a bunch of other cool functionality, and does it with class decorators. 00:13:23.800 --> 00:13:27.800 It doesn't pollute your final object with anything you don't want, right? 00:13:27.800 --> 00:13:29.800 It doesn't, because you don't inherit from anything. 00:13:29.800 --> 00:13:31.680 So, you just inherit from object. 00:13:31.920 --> 00:13:38.080 After Glyph's post took off or something, the core Python devs sat up, took some notice of this, and said, 00:13:38.080 --> 00:13:42.740 maybe we have been neglecting a higher-level interface for quickly defining classes. 00:13:42.740 --> 00:13:47.720 You know, you just want to have four or five fields all sort of batched together. 00:13:48.280 --> 00:13:52.980 And you don't want to have a lot of functions that everywhere have to define 15 arguments. 00:13:52.980 --> 00:13:59.320 So, like, how can we quickly, in a nice, concise, Pythonic way, define a Python class? 00:13:59.960 --> 00:14:13.460 And they came up with this new thing, which is still, I guess, kind of, this is what I mean, like, I don't know if this is a little bit too deep underground, but there's this kind of, there's this GitHub that Eric V. Smith, who is a Python core dev, has called Data Classes. 00:14:13.980 --> 00:14:23.960 And the issues of this have been really interesting to watch because Hynek and a bunch of core devs have been kind of debating, like, hey, should we just use attrs? 00:14:23.960 --> 00:14:27.400 If attrs is getting so popular, should it just be part of the core Python? 00:14:28.400 --> 00:14:30.160 And, you know, people seem to like it. 00:14:30.160 --> 00:14:33.600 Why make something that's so close to it that sort of thing? 00:14:33.600 --> 00:14:40.440 There's sort of a draft PEP inside of the Data Classes repo, and there's some examples of how it's used. 00:14:40.440 --> 00:14:43.140 Has some semantic differences, has some syntactic differences. 00:14:43.140 --> 00:14:45.940 I think that it's pretty interesting to watch. 00:14:45.940 --> 00:14:50.620 And, in fact, they seem to be encouraging more experimentation in this area. 00:14:50.620 --> 00:14:55.420 Even though I like attrs, they seem to want even more options, at least from themselves. 00:14:56.120 --> 00:14:57.360 So, I don't know. 00:14:57.360 --> 00:14:58.940 I had a good time reading the issues. 00:14:58.940 --> 00:15:00.340 Maybe other people enjoy it too. 00:15:00.340 --> 00:15:00.600 Yeah. 00:15:00.600 --> 00:15:03.300 So, is this, it's similar to attrs then? 00:15:03.300 --> 00:15:03.560 Yeah. 00:15:03.560 --> 00:15:05.440 It's pretty similar to attrs. 00:15:05.440 --> 00:15:11.240 There are, the differences are sort of fine enough that you have to kind of look closely. 00:15:11.240 --> 00:15:18.120 Basically, I think that what it is, is like, there's actually an issue called, why not just attrs? 00:15:18.120 --> 00:15:26.000 And they sort of explain that they want to use, like, the new, I think, type hint syntax type stuff. 00:15:26.000 --> 00:15:26.340 Okay. 00:15:26.340 --> 00:15:27.500 So, yeah. 00:15:27.500 --> 00:15:42.100 Other people, like, kind of said that, hey, maybe, like, naming-wise, data classes is a little bit clearer than attrs, because someone who is a new Python programmer doesn't know that adder is an attribute or something like that. 00:15:42.100 --> 00:15:42.820 That's true. 00:15:42.820 --> 00:15:45.440 So, it has some syntactic differences, yeah. 00:15:45.440 --> 00:15:48.280 And there are some big names in this discussion. 00:15:48.280 --> 00:15:49.280 There are, there are. 00:15:49.280 --> 00:15:50.120 So, that's what I mean. 00:15:50.120 --> 00:15:52.660 It's sort of like the inner circle, right? 00:15:52.660 --> 00:15:56.080 This is kind of like the sort of stuff that I have to follow. 00:15:56.080 --> 00:15:56.940 Oh, that's awesome. 00:15:56.940 --> 00:15:58.240 To be on the edge here. 00:15:58.240 --> 00:16:00.500 And it happens kind of behind the scenes. 00:16:00.500 --> 00:16:05.840 But I really do encourage people to join these email lists if you want to see the action happening. 00:16:05.840 --> 00:16:07.680 You know, you don't have to be a spectator. 00:16:07.680 --> 00:16:12.800 Or you don't have to sit maybe in the nosebleed section of the arena on open source, right? 00:16:12.840 --> 00:16:16.820 You can get up close on the, on, like, you know, get the, get the front row seats. 00:16:16.820 --> 00:16:18.600 And before you know it, you'll actually get involved. 00:16:18.600 --> 00:16:19.220 It'll be fun. 00:16:19.220 --> 00:16:20.180 Yeah, that's great. 00:16:20.180 --> 00:16:21.320 Oh, thanks for bringing that up. 00:16:21.320 --> 00:16:21.740 That's cool. 00:16:21.740 --> 00:16:28.800 Well, speaking of trying to get involved, unless you've had your head under a rock, data science is a thing. 00:16:28.800 --> 00:16:31.200 Is it, really? 00:16:31.200 --> 00:16:37.280 It isn't something that I have to do, use on a daily basis, but it's definitely something I want to pay attention to. 00:16:37.960 --> 00:16:44.220 And I ran across, there's a lot of books and tutorials that are huge because it's a huge topic. 00:16:44.220 --> 00:16:48.980 And I ran across a article called Pandas in a Nutshell. 00:16:48.980 --> 00:16:53.940 And it's, I like it because it's a, it's a Jupyter Notebook style post. 00:16:53.940 --> 00:16:55.620 So you can just see the code working. 00:16:55.620 --> 00:17:01.260 And it's mostly tutorial by example with, it's just a little bit of extra code for explanation. 00:17:01.260 --> 00:17:05.780 And the big part of it is really just talking about a couple of data structures. 00:17:05.780 --> 00:17:11.740 It's just talking about the series data structure, which is a one-dimensional array with indices. 00:17:11.740 --> 00:17:14.180 So just kind of like a vector. 00:17:14.180 --> 00:17:17.960 And then the data frame, which is like a two-dimensional array. 00:17:18.700 --> 00:17:36.000 And all the sort of common things that you need to do with it, like specifying a custom index or adding, combining two series or with matrix stuff, adding columns, adding a column that's based on another column. 00:17:36.000 --> 00:17:40.560 Then this sort of stuff sort of seems like Excel, like working on a spreadsheet. 00:17:40.740 --> 00:17:46.360 I think for a lot of people, like that is the natural next step, you know, when they want to get into programming. 00:17:46.360 --> 00:17:54.220 It's either going to be doing visual or is it like, you know, basic script of some sort inside of Excel or, you know, maybe move into Python. 00:17:54.460 --> 00:18:10.960 Yeah, and I guess that's one of the things I like about this little nutshell article is that it's, if somebody is already doing some things in spreadsheets and they want to switch to working with pandas, this might be a pretty good stepping point to try to get things going. 00:18:10.960 --> 00:18:19.900 And it's actually something I'm going to grab some of the concepts in here to try to deal with some of the large amounts of data that I deal with on a daily basis as well. 00:18:19.900 --> 00:18:20.920 Oh, for sure. 00:18:20.920 --> 00:18:23.880 So I haven't used, and I bring this up because I'm just starting. 00:18:23.880 --> 00:18:27.180 I'm trying to use pandas on a daily basis now. 00:18:27.180 --> 00:18:30.400 And it is, like, I've actually faced a lot of the same challenges. 00:18:30.400 --> 00:18:37.200 It's just because it's Python doesn't mean that it, you know, doesn't require some sort of kind of paradigm shift in your thought. 00:18:37.740 --> 00:18:43.720 It's like thinking about data frames is very different than thinking about lists in Python or dictionaries in Python. 00:18:43.720 --> 00:18:48.440 It's somewhere between Python and, like, full-blown relational databases. 00:18:48.440 --> 00:18:58.780 And so you do have to change the way you think how to approach a problem, especially if you want to get some performance out of the thing, because it has all this great broadcasting logic that it can perform. 00:18:58.780 --> 00:19:02.400 But it's not going to work if you just iterate over it in four loops. 00:19:02.400 --> 00:19:13.360 Yeah, and I guess that's where the data frames and series stuff comes in is because you want to do some computation on everything and or, you know, searching on stuff. 00:19:13.360 --> 00:19:19.780 So it's kind of like a combination of a database and an in-memory database and something else. 00:19:19.780 --> 00:19:23.740 Where I work, some of our data scientists are, you know, coming from an R background. 00:19:24.080 --> 00:19:27.240 And the data frame is based on R construct, I believe. 00:19:27.240 --> 00:19:30.340 So they, you know, find it quite natural. 00:19:30.340 --> 00:19:33.340 And the Python is what they sort of struggle with. 00:19:33.340 --> 00:19:34.480 And they come to me for that. 00:19:34.480 --> 00:19:38.240 But a Python person would want to ramp up on the data frame itself. 00:19:38.240 --> 00:19:41.460 And so this notebook seems like a great option to do that quickly. 00:19:41.460 --> 00:19:41.740 Yeah. 00:19:41.740 --> 00:19:43.480 So that's just a quickie. 00:19:43.480 --> 00:19:45.260 So that's it. 00:19:45.260 --> 00:19:46.280 Your last topic. 00:19:46.420 --> 00:19:47.340 Oh, already. 00:19:47.340 --> 00:19:54.520 So, yeah, basically, just yesterday I was at this conference, PyBay 2017. 00:19:54.520 --> 00:19:58.320 It's sort of the Bay Area, Silicon Valley, regional Python conference. 00:19:58.320 --> 00:19:59.720 Only the second annual one. 00:19:59.720 --> 00:20:02.760 There's, it's surprising how long it took to spin up here. 00:20:02.760 --> 00:20:05.480 Meanwhile, PyOhio has been going for who knows how long. 00:20:05.480 --> 00:20:08.120 So anyways, but it was a great conference. 00:20:08.120 --> 00:20:11.960 Almost 500 developers, pretty good turnout. 00:20:12.380 --> 00:20:17.980 And a lot of great topics covered the, I gave a packaging talk. 00:20:17.980 --> 00:20:24.800 But the thing I'm going to talk about today is actually the opening panel was on static typing. 00:20:24.800 --> 00:20:27.880 And it was quite an interesting mix. 00:20:27.880 --> 00:20:30.120 They had, first of all, it was very international. 00:20:30.120 --> 00:20:33.960 They had people from Germany, Russia, Poland, USA, and Netherlands. 00:20:33.960 --> 00:20:38.360 It seems like Europeans are big fans of static typing for whatever reason. 00:20:38.360 --> 00:20:39.340 Guido included. 00:20:39.980 --> 00:20:47.520 So, yeah, they had people from, I think, let's see, PyCharm, University of California, Berkeley. 00:20:47.520 --> 00:20:52.360 Then also Quora, Google, and I think another guy too. 00:20:52.360 --> 00:20:58.220 So it was a really nice cross-section of the industry and also the world. 00:20:58.220 --> 00:21:02.020 And they just talked about the state of static typing. 00:21:02.160 --> 00:21:06.880 So right now, just to bring you up to date, I'm not sure how recently you covered this stuff on the podcast. 00:21:06.880 --> 00:21:12.740 But there are currently three or four static type checkers. 00:21:12.740 --> 00:21:17.240 So in Python 3, you can specify your types however you'd like. 00:21:17.240 --> 00:21:23.180 Built into the language, it's not going to do a lot of complaining in case types don't match. 00:21:23.180 --> 00:21:25.800 First of all, at runtime, nothing is checked. 00:21:26.300 --> 00:21:30.240 So if you want to check it, it would be at a compile time step. 00:21:30.240 --> 00:21:33.300 The annotations are still there at runtime. 00:21:33.300 --> 00:21:40.200 And then you have a static type checker, the most popular of which is mypy, run over that and check it. 00:21:40.200 --> 00:21:44.100 Kind of like a linter or any other, I mean, static analysis tool. 00:21:44.920 --> 00:21:48.120 And so there are other ones too, though. 00:21:48.120 --> 00:21:54.060 Google has one that is not super well documented, but they use it internally. 00:21:54.060 --> 00:22:00.420 Then PyCharm has this functionality as well, which is also kind of built from scratch. 00:22:00.420 --> 00:22:05.760 And they made a pretty good case why you would want one built into PyCharm, 00:22:05.760 --> 00:22:08.800 which is that basically it can do incremental checking. 00:22:08.800 --> 00:22:13.940 So while you're still writing, it can do sort of partial checks, maybe a little bit better than mypy. 00:22:13.940 --> 00:22:14.720 Oh, right. 00:22:14.720 --> 00:22:18.940 The last person on the panel, Ukash Langa from Facebook. 00:22:18.940 --> 00:22:20.300 He also comes to my meetup. 00:22:20.300 --> 00:22:23.280 Anyways, so yeah, he's very opinionated about types. 00:22:23.280 --> 00:22:24.220 We'll get to that in a second. 00:22:24.220 --> 00:22:27.140 One that wasn't talked about was PyLint. 00:22:27.140 --> 00:22:28.600 So I was actually blown away. 00:22:28.600 --> 00:22:34.240 I updated my Emacs config recently, and I sort of integrated some more linting stuff. 00:22:34.240 --> 00:22:38.760 And the default PyLint these days can do an amazing amount of inference. 00:22:38.760 --> 00:22:41.460 It'll tell you you have the wrong number of arguments. 00:22:41.460 --> 00:22:45.160 It'll tell you that, like, oh, this default doesn't match that type. 00:22:45.160 --> 00:22:54.620 It'll do so many different things, in addition to its standard, very opinionated idea of how many arguments a function should even have and that sort of thing. 00:22:55.280 --> 00:22:59.480 Anyways, so those are our four sort of type inference engines. 00:22:59.480 --> 00:23:01.980 And they all are slightly different. 00:23:01.980 --> 00:23:04.640 But everyone seemed to get along pretty well on stage. 00:23:04.640 --> 00:23:14.800 And they talked about, you know, potentially in the future actually merging these things and making a PEP that would allow them to all sort of comply together, maybe even turn into a single project. 00:23:15.500 --> 00:23:17.420 So that was really nice to see. 00:23:17.420 --> 00:23:24.180 And one of the most interesting questions was basically from the audience. 00:23:24.180 --> 00:23:28.840 They said, like, well, what is the real point behind the static typing? 00:23:28.840 --> 00:23:31.180 Like, what is the biggest benefit that you see? 00:23:31.180 --> 00:23:33.440 And there was a little bit of divergence on this, right? 00:23:33.440 --> 00:23:41.100 Some people like it for the strictness of it all, being, you know, kind of the dictator of your own code base or whatever, right? 00:23:41.100 --> 00:23:48.700 But everyone else seemed to be pretty much on the same page that this is for human readability. 00:23:48.700 --> 00:23:54.840 This is a sort of documentation that can then be checked automatically at a rather large scale. 00:23:54.840 --> 00:23:59.340 So it's attached to the function, but it's more than just a doc test. 00:23:59.340 --> 00:24:10.520 And so the interesting side effect of this is that they, even though they all work on static typing stuff, they have a pretty nuanced view of how much static typing you should apply. 00:24:10.520 --> 00:24:17.500 So they say that, like, you know, maybe a list of a certain type, right? 00:24:17.500 --> 00:24:21.920 But actually defining, say, a completely recursive type is, one, not supported. 00:24:22.120 --> 00:24:28.680 And two, maybe not even that desirable because you don't want your function signatures to get super, super complex. 00:24:28.680 --> 00:24:40.800 So, yeah, I mean, it was interesting that they thought the human side of this was the most important part as opposed to, say, like a Haskell programmer or something where they want the mathematical correctness of it all. 00:24:40.800 --> 00:24:47.340 It's also interesting that there's, I would have liked to listen to the discussion of how much you should use of it. 00:24:47.340 --> 00:24:48.040 Well, it was at LinkedIn. 00:24:48.040 --> 00:24:49.460 I think that they recorded it. 00:24:49.460 --> 00:24:50.640 It should go up pretty soon. 00:24:50.860 --> 00:24:56.480 Yeah, I'll definitely, you know, it was only a couple of days ago, but once the video is available, I'll maybe send it to you. 00:24:56.480 --> 00:24:57.560 You can add it to the show notes. 00:24:57.560 --> 00:24:58.020 Yeah. 00:24:58.020 --> 00:25:01.440 Some interesting side effects of this, by the way, like some things to consider. 00:25:01.440 --> 00:25:06.840 So Cython does not support the new Python type syntax. 00:25:06.840 --> 00:25:19.220 So even though all these guys are kind of on the same page and buddy-buddy, like, you know, for us, people who really like Cython and have used it to achieve a lot of performance and type correctness to some degree, are a little bit out of luck at the moment. 00:25:19.220 --> 00:25:24.620 There, I think that people are working on making a pull request to it or something that would support, add support for this. 00:25:24.620 --> 00:25:27.000 But it's such a big change to the syntax. 00:25:27.000 --> 00:25:42.740 And Cython has its own type syntax, which is less focused on semantic types as this is, and more focused on being in line with C types, which allows you to have more compact memory, memory-like usage. 00:25:42.960 --> 00:25:48.500 And the people on the panel were actually pretty clear that the static types advantage is not in performance. 00:25:48.500 --> 00:25:59.340 So a project like PyPy, which actually can use types to achieve higher performance, they find that the JIT is faster without taking hints from the user in the code. 00:25:59.340 --> 00:26:00.700 So it just disregards this stuff. 00:26:00.700 --> 00:26:01.280 Oh, interesting. 00:26:01.280 --> 00:26:01.520 Yeah. 00:26:01.520 --> 00:26:03.640 Because the JIT has the actual types. 00:26:03.640 --> 00:26:06.280 So just a real quick thought experiment. 00:26:06.280 --> 00:26:10.540 Like, imagine that I say, I'm going to pass you a list of integers. 00:26:10.860 --> 00:26:13.180 That list is three integers long. 00:26:13.180 --> 00:26:13.520 Okay. 00:26:13.520 --> 00:26:14.480 I can just check them. 00:26:14.480 --> 00:26:15.340 One, two, three. 00:26:15.340 --> 00:26:16.060 All integers. 00:26:16.060 --> 00:26:16.700 Good to go. 00:26:16.700 --> 00:26:17.380 No type error. 00:26:17.380 --> 00:26:18.060 Right. 00:26:18.060 --> 00:26:25.780 But if I pass you a list of 20,000 integers, right, every time I pass that to you, I have to check that every single one is an integer. 00:26:25.780 --> 00:26:27.900 Otherwise, like, you know, I want to have a type error. 00:26:27.900 --> 00:26:35.920 That sort of thing is going a little bit against the spirit of Python and being like sort of practical and duck typey and whatnot. 00:26:36.220 --> 00:26:44.000 So a friend of mine from Intel, you know, was sitting next to me and he was saying how we call he came to Python so he wouldn't have to type everything. 00:26:44.000 --> 00:26:46.120 But thankfully, you don't have to type everything. 00:26:46.120 --> 00:26:57.840 Like the standard library itself, for instance, is all the type definitions for that are available in this joint type shed repo that all of these static type people sort of built together. 00:26:58.000 --> 00:26:59.880 And I'll link to that in the show notes for sure. 00:26:59.880 --> 00:27:00.180 Yeah. 00:27:00.180 --> 00:27:11.180 My favorite use so far that I've come across for my own work is putting type hints in interface areas like an API module to that. 00:27:11.180 --> 00:27:12.780 That's how you interact with the package. 00:27:12.780 --> 00:27:14.940 So those are great places for type hints. 00:27:14.940 --> 00:27:15.640 Oh, for sure. 00:27:15.640 --> 00:27:20.340 And so wait, are you saying that so there is this old thing like they're trying to get rid of it. 00:27:20.340 --> 00:27:23.420 Basically, Python has these sort of stub files, these interface files. 00:27:23.540 --> 00:27:26.100 Some people call them the header files for Python. 00:27:26.100 --> 00:27:28.220 Like I think it's a .py file. 00:27:28.220 --> 00:27:28.500 Okay. 00:27:28.500 --> 00:27:29.540 .py. 00:27:29.540 --> 00:27:42.380 I was just thinking like I've got a package that has a whole bunch of internal code, but it has like an API module that you should people interact with from the outside world. 00:27:42.800 --> 00:27:50.160 That's a great place for pretty much any interfaces that are not you that's going to use it, that somebody else is going to use it. 00:27:50.160 --> 00:27:52.880 Those are great places to put type hints if it matters. 00:27:52.880 --> 00:27:53.520 Oh, definitely. 00:27:53.520 --> 00:27:53.960 Definitely. 00:27:53.960 --> 00:27:55.200 Cool. 00:27:55.200 --> 00:27:56.600 But I'm pretty new to it too. 00:27:56.600 --> 00:27:58.160 So thanks for bringing that up. 00:27:58.160 --> 00:27:58.960 That was very interesting. 00:27:58.960 --> 00:27:59.240 Yeah. 00:27:59.240 --> 00:27:59.460 Yeah. 00:27:59.460 --> 00:28:02.860 And I mean, I think that they're still changing this stuff quite a bit, right? 00:28:03.040 --> 00:28:05.800 So I, you know, early adopters go nuts. 00:28:05.800 --> 00:28:13.180 But for the rest of us that like a little bit more boring technologies, you know, I'm going to go ahead and let the auto inference engine of Pilot figure things out for me. 00:28:13.180 --> 00:28:16.000 I'm not going to, you know, jump on the bandwagon so quickly. 00:28:16.000 --> 00:28:17.860 And I'm glad you brought Pilot up. 00:28:17.860 --> 00:28:21.880 I've been sort of dismissing it because I've been using FlightGate. 00:28:22.220 --> 00:28:24.460 But I'll have to take a look at Pilot again. 00:28:24.460 --> 00:28:24.760 Oh, yeah. 00:28:24.760 --> 00:28:27.740 They've definitely ramped up development on that again. 00:28:27.740 --> 00:28:30.220 I mean, you have to, for me anyways, right? 00:28:30.220 --> 00:28:35.460 I just blacklist a lot of the errors because I kind of don't agree with every single thing that they test for. 00:28:35.460 --> 00:28:37.400 But they make it pretty easy to do. 00:28:37.400 --> 00:28:38.720 You just change it in an I and I file. 00:28:38.720 --> 00:28:39.280 No big deal. 00:28:39.280 --> 00:28:46.320 Last topic, again, comes back to me finally getting my head out of thinking about pytest 24 hours a day. 00:28:47.440 --> 00:28:55.320 And one of the things I want to start looking at is some of the web frameworks like Django and Flask. 00:28:55.320 --> 00:28:57.220 I haven't played with them much personally. 00:28:57.220 --> 00:29:01.140 And there's a bunch of personal projects and work projects I'd like to do with them. 00:29:01.140 --> 00:29:07.360 And also quite a few people that listen to testing code are web people. 00:29:07.360 --> 00:29:12.600 And so just to kind of get more understanding of that, I'm trying to learn more frameworks. 00:29:12.600 --> 00:29:18.940 And one of the things that I've had a hard time getting my head around is ORMs or object relational mappers. 00:29:18.940 --> 00:29:26.120 So luckily I ran across an article on Fullstack Python, which is Matt Makai's site. 00:29:26.120 --> 00:29:26.780 Amazing site. 00:29:26.780 --> 00:29:27.060 Yeah. 00:29:27.060 --> 00:29:30.560 And basically it's Fullstack Python. 00:29:30.560 --> 00:29:34.740 I don't remember what it's called, but I think it's just object relational mappers. 00:29:35.600 --> 00:29:38.540 And it goes through what they are. 00:29:38.540 --> 00:29:50.380 So a norm is some code that automates the transfer of data from your internal Python objects and classes to database tables. 00:29:50.380 --> 00:29:55.540 And they're useful so that you can write Python code instead of writing SQL queries. 00:29:56.440 --> 00:30:01.400 And he talks about that and then also talks about why you need them and some downsides. 00:30:01.400 --> 00:30:03.200 And yeah. 00:30:03.200 --> 00:30:05.240 So the downsides actually were interesting. 00:30:05.240 --> 00:30:09.080 I didn't think that anybody would talk about what's wrong with using ORMs. 00:30:09.080 --> 00:30:09.400 Yeah. 00:30:09.400 --> 00:30:13.260 I mean, realistically, there are some definite engineering trade-offs. 00:30:13.260 --> 00:30:13.880 So what did he say? 00:30:13.880 --> 00:30:22.520 Well, he said, well, a few things are impedance mismatch, which coming from electrical world, I was like impedance mismatch. 00:30:22.520 --> 00:30:25.060 So that's like 50 ohms to 75 ohms, right? 00:30:25.060 --> 00:30:25.340 Yeah. 00:30:25.340 --> 00:30:25.560 Yeah. 00:30:25.560 --> 00:30:36.820 But it's basically the way a developer is using the objects is different from how, can be different from how the data is stored and joined in the tables in your database. 00:30:36.820 --> 00:30:44.820 And especially if you've set up the tables in a way that's not like, it's contradictory to how it's being used all the time. 00:30:44.820 --> 00:30:50.020 It might be slow and you can maybe reshaping your data might speed that up. 00:30:50.880 --> 00:30:53.080 And then potential for reduced performance. 00:30:53.080 --> 00:30:55.220 And this isn't surprising to me. 00:30:55.220 --> 00:30:59.280 If you stick some code in the middle, it's not free. 00:30:59.280 --> 00:31:00.160 It's got to run. 00:31:00.160 --> 00:31:09.000 And then also shifting complexity from database to the application code, which this is something that I didn't quite understand right off the bat. 00:31:09.080 --> 00:31:10.700 But if you think about it, it's not too bad. 00:31:10.700 --> 00:31:21.020 But there's databases are complex thing pieces of software that have things like stored procedures, stored procedures and a whole bunch of fancy join math and stuff. 00:31:21.020 --> 00:31:21.340 Right. 00:31:21.340 --> 00:31:21.640 Right. 00:31:21.640 --> 00:31:24.340 That might not be supported by an ORM. 00:31:24.540 --> 00:31:29.360 So you're going to, you have to, if you had to do that stuff, you have to do it in your application instead. 00:31:29.360 --> 00:31:36.900 So it's, it's using, using a database in a simpler way, but that complexity has to go somewhere and it'll go in your application code. 00:31:36.900 --> 00:31:37.100 Yeah. 00:31:37.100 --> 00:31:37.700 Almost certainly. 00:31:37.920 --> 00:31:46.580 But I mean, until you get like database specialists, then, you know, it makes it a little bit easier for you as, you know, a sole developer, for instance. 00:31:46.580 --> 00:31:47.100 Yeah. 00:31:47.200 --> 00:31:53.360 So I punted at first and used a document databases because I didn't have to think about ORMs right off the bat. 00:31:53.360 --> 00:31:57.660 But, but I mean, so, so, but the thing is that an ORM, like he's correct. 00:31:57.660 --> 00:32:05.480 Like a database is definitely a very advanced, complex tool, but a lot of that advances in complexity you retain even when using an ORM. 00:32:05.480 --> 00:32:12.320 For instance, a lot of document databases don't have great transaction models, don't have great, you know, sort of multi-version concurrency models. 00:32:13.100 --> 00:32:27.780 And, you know, so when they put all that work into Postgres or even like MariaDB or something like that, you can, just by using an ORM, it seems almost as simple as a document database, but you get that operational, you know, feature. 00:32:27.780 --> 00:32:28.060 Yeah. 00:32:28.060 --> 00:32:39.260 I'd definitely heard of SQLAlchemy or SQLAlchemy, but I hadn't heard of a couple of the others that he listed here, PeeWee and Pony and SQL Object. 00:32:39.260 --> 00:32:41.140 Have you used any of these? 00:32:41.320 --> 00:32:47.200 Yeah, so SQLAlchemy is definitely my go-to and I'll talk about why in a second. 00:32:47.200 --> 00:32:53.200 But yeah, I mean, I've used Django's ORM because I did the Django tutorial and that's one of the first things they teach you. 00:32:53.200 --> 00:33:00.040 Django has a serviceable ORM, but there are some issues with it that SQLAlchemy actually does a much better job with. 00:33:00.040 --> 00:33:02.620 And I have used PeeWee, in fact. 00:33:02.620 --> 00:33:03.440 I like PeeWee. 00:33:03.440 --> 00:33:05.800 It's sort of like a simplified version of Django. 00:33:06.140 --> 00:33:12.620 In my opinion, it basically says like, look, if you're not going to be SQLAlchemy, then, you know, you can just be plain simple. 00:33:13.340 --> 00:33:15.260 And it does a pretty good job. 00:33:15.260 --> 00:33:24.020 But these days, SQLAlchemy has gotten so good that, you know, I just reach for that every single time I'm going to work with a relational database in Python. 00:33:24.020 --> 00:33:24.460 Okay. 00:33:24.660 --> 00:33:35.240 So one thing that SQLAlchemy has is that it sort of has this working copy of all the models and they end up being kind of like singletons within a given process space. 00:33:35.780 --> 00:33:45.660 So with Django, you can actually get two copies of the same thing from the database within the same request or the same process. 00:33:45.660 --> 00:33:51.500 And that means that basically concurrently somewhere else in your program, it could change something, save it. 00:33:51.500 --> 00:34:00.000 And then when you change it in your request handler you're actually trying to work on, that will overwrite the previous change. 00:34:00.000 --> 00:34:09.460 You know, like if you change column A in one thread and column B in another thread, whichever thread saves first is going to overwrite the other unchanged value. 00:34:09.460 --> 00:34:15.300 So there's a setting that's off by default, I think, in Django called atomic requests. 00:34:15.300 --> 00:34:18.620 And you have to enable that to prevent that sort of situation. 00:34:18.620 --> 00:34:19.880 But Django is not alone in this. 00:34:19.880 --> 00:34:23.960 I think that Rails, at least for a very long time, did the same thing. 00:34:23.960 --> 00:34:26.800 And Django, of course, is sort of Python's response to Ruby on Rails. 00:34:26.800 --> 00:34:28.600 So, yeah. 00:34:28.600 --> 00:34:31.600 Does SQLAlchemy not have this problem? 00:34:31.600 --> 00:34:36.740 So SQLAlchemy doesn't have this problem because basically, yeah, you only get one copy of that thing in your system. 00:34:36.740 --> 00:34:44.920 It has this sort of local index of primary key to the object version of that row that you're representing, for instance. 00:34:44.920 --> 00:34:45.600 Okay. 00:34:45.600 --> 00:34:46.620 So, yeah. 00:34:46.620 --> 00:34:46.640 So, yeah. 00:34:46.640 --> 00:34:51.760 SQLAlchemy sort of has, it adds a lot of machinery, makes SQLAlchemy a little bit more complex. 00:34:51.760 --> 00:34:56.780 But I had a friend who I think spent days tracking down this issue with Django. 00:34:56.780 --> 00:34:59.220 And SQLAlchemy never would have happened. 00:34:59.220 --> 00:35:01.820 So you pay some upfront costs with setup with SQLAlchemy. 00:35:01.940 --> 00:35:03.460 But I think it's definitely worth it. 00:35:03.460 --> 00:35:12.900 When it comes to this sort of ORM thing, though, like if I can provide some general advice, ORMs are sort of the tools of applications. 00:35:13.500 --> 00:35:21.780 And if you want to see, if you want to form a real opinion on object relational mappers, you should look at and compare applications. 00:35:21.780 --> 00:35:28.460 So I spent a fair amount of time reading Reddit source code, which does, I think, use SQLAlchemy. 00:35:28.460 --> 00:35:31.260 And it uses it without the declarative object mapper. 00:35:31.260 --> 00:35:36.660 It uses it with the sort of legacy or lower level SQLAlchemy tools. 00:35:36.840 --> 00:35:41.320 But you still get a real sense for where they use an ORM and where they don't. 00:35:41.320 --> 00:35:45.860 And SQLAlchemy actually makes it very easy to pass through normal SQL text. 00:35:45.860 --> 00:35:47.900 That's another thing I really like about it. 00:35:47.900 --> 00:35:51.800 It understands that ORMs are an abstraction that's useful 90% of the time. 00:35:51.800 --> 00:35:58.220 And for that last 10%, you really want the full power of the driver or the database itself. 00:35:58.220 --> 00:35:59.160 Okay, cool. 00:35:59.160 --> 00:36:02.940 I don't have any opinion on these extra couple links that I put in here. 00:36:02.940 --> 00:36:07.620 Matt has some dedicated pages for SQLAlchemy and PeeWee. 00:36:07.620 --> 00:36:15.620 And one of the things I like about Matt's site anyway, the Fullstack Python, is he gives his opinion and information when he has it. 00:36:15.620 --> 00:36:22.360 And when somebody else has already explained it well enough or better, he just links to their stuff and says, go read that. 00:36:22.360 --> 00:36:23.020 Yeah, absolutely. 00:36:23.020 --> 00:36:24.920 No, I mean, he's a real team player in that regard. 00:36:24.920 --> 00:36:27.680 But I also, I just got to, you know, give a shout out to him. 00:36:27.780 --> 00:36:30.540 Like he so consistently adds to the site. 00:36:30.540 --> 00:36:34.600 It's become such a tremendous resource for someone who wants to develop an application. 00:36:34.600 --> 00:36:39.620 I'm sure that listeners of this podcast are, for the most part, like already aware of it. 00:36:39.620 --> 00:36:41.120 But yeah, definitely check it out. 00:36:41.120 --> 00:36:41.500 Definitely. 00:36:41.500 --> 00:36:44.620 Well, that's all of our topics so far. 00:36:44.620 --> 00:36:50.580 We didn't address what you're up to lately other than helping out with podcasts. 00:36:51.880 --> 00:36:53.440 Yeah, no, it's funny. 00:36:53.440 --> 00:36:59.600 I'm also like prepping for another podcast as well, but partially examined life, I guess. 00:36:59.600 --> 00:37:02.620 But basically, yeah, what am I up to lately? 00:37:02.620 --> 00:37:07.360 Well, I had a talk at PiBay and because it was based on a blog post, I thought it'd be easy to put together slides. 00:37:07.360 --> 00:37:09.760 Now, it still took like just full disclosure. 00:37:09.760 --> 00:37:14.320 It took like another 40, 50 hours to make slides from that blog post. 00:37:14.320 --> 00:37:15.560 But it seemed really well received. 00:37:15.560 --> 00:37:17.360 And so I'm very relieved right now. 00:37:17.360 --> 00:37:22.420 I got some nice life events coming through, parents coming to town, keeping me real busy. 00:37:22.420 --> 00:37:27.780 I also am working on this hyperlink library, like I mentioned earlier, URLs in Python. 00:37:27.780 --> 00:37:31.120 And it's used by Twisted and some other big projects. 00:37:31.120 --> 00:37:40.300 So fixing bugs in there is always kind of contentious, which is why I got a lot of support for people who work on things like setup tools, which is even more widely used. 00:37:41.000 --> 00:37:44.600 So then beyond this, let's see. 00:37:44.600 --> 00:37:46.000 Yeah, writing blog posts. 00:37:46.000 --> 00:37:49.260 I got I think my draft count is up to like 100 now. 00:37:49.260 --> 00:37:53.160 But yeah, maybe more conferences, more talks. 00:37:53.160 --> 00:37:56.640 I don't know why I keep signing up for these things, but it's great meeting people out there. 00:37:56.640 --> 00:38:01.000 People out there should really look into PiBay and regional conferences, meetups. 00:38:01.000 --> 00:38:07.900 Oh, well, I run a meetup to the Peninsula meetup, the hottest new meetup in the Bay Area, Silicon Valley. 00:38:08.520 --> 00:38:12.620 And so, yeah, like, yeah, yeah, we were a pun. 00:38:12.620 --> 00:38:14.340 Hey, this is programming, man. 00:38:14.340 --> 00:38:16.180 It's all about the terrible puns. 00:38:16.180 --> 00:38:19.640 So we but yeah, Peninsula. 00:38:19.640 --> 00:38:23.180 Yeah, I think we even have the site now, Peninsula dot org. 00:38:23.180 --> 00:38:25.400 And, you know, we're on Twitter and so forth. 00:38:25.400 --> 00:38:27.180 I do my best to record the talks. 00:38:27.520 --> 00:38:35.520 But for people who want to break into this type of, you know, speaking and that sort of thing, just look at look no further than your local meetup. 00:38:35.520 --> 00:38:35.820 Right. 00:38:35.820 --> 00:38:38.660 Go make a 15 minute, 30 minute talk. 00:38:38.660 --> 00:38:39.920 See how it goes. 00:38:39.920 --> 00:38:41.020 Iterate on it. 00:38:41.020 --> 00:38:41.260 Right. 00:38:41.260 --> 00:38:43.160 Have a brown bag at your company. 00:38:43.160 --> 00:38:44.680 Just keep iterating on it. 00:38:44.680 --> 00:38:46.260 And, you know, something will stick. 00:38:46.260 --> 00:38:50.240 And then you can submit it to something like PyCon or whatever. 00:38:50.240 --> 00:38:51.240 That's a great idea. 00:38:51.240 --> 00:38:57.380 I think a lot of people think that you could you just have to work really hard on a talk and give it once and then it's done. 00:38:57.380 --> 00:38:59.340 But a lot of people give them several times. 00:38:59.340 --> 00:38:59.620 Yeah. 00:38:59.660 --> 00:39:03.180 And also, like if there's not a meetup in your area, just maybe start one. 00:39:03.180 --> 00:39:05.700 Python programmers are literally everywhere. 00:39:05.700 --> 00:39:16.260 So we like, you know, even though there's a South Bay Python meetup, which is sort of like more towards Sunnyvale, like kind of south of Mountain View area. 00:39:16.260 --> 00:39:20.540 And there's this SF Python meetup, which is up in San Francisco. 00:39:20.540 --> 00:39:22.420 We put one right in the middle. 00:39:22.420 --> 00:39:27.000 I guess California traffic is bad enough that we sort of have a captive audience, literally. 00:39:27.440 --> 00:39:32.360 But we'll get like, you know, I think when Guido came, there were almost 100 people at the meetup. 00:39:32.360 --> 00:39:34.060 And normally we get like 50. 00:39:34.060 --> 00:39:38.100 But it's great because everyone can socialize and something a little bit more intimate. 00:39:38.100 --> 00:39:40.920 It's a little bit less stressful when you're trying to give the talk yourself, too. 00:39:40.920 --> 00:39:41.220 Yeah. 00:39:41.220 --> 00:39:45.600 So it wouldn't be a Python Bytes episode if I didn't plug my book. 00:39:45.600 --> 00:39:46.120 By all means. 00:39:46.120 --> 00:39:52.520 So one of the things I want to bring up is the Python testing with pytest has a nice discussion forum. 00:39:52.520 --> 00:39:56.540 It's kind of built into what Pragmatic offers for all the books. 00:39:57.120 --> 00:40:02.680 But if you ever ask a question on there, it pings me and emails me and says there's a question. 00:40:02.680 --> 00:40:05.020 Just this morning, I answered a question. 00:40:05.020 --> 00:40:08.860 Somebody got on and said that they were actually... 00:40:08.860 --> 00:40:09.720 I love this. 00:40:09.720 --> 00:40:13.700 They said that the book is helping them understand testing better. 00:40:13.700 --> 00:40:16.040 And I love comments like that. 00:40:16.040 --> 00:40:20.240 But he had a question about Monkey Patch versus Mock. 00:40:20.240 --> 00:40:23.420 And I'm not going to get into it too much here. 00:40:23.420 --> 00:40:24.900 But I did reply to him. 00:40:24.900 --> 00:40:27.500 And it's all up there for everybody else to read, too. 00:40:27.500 --> 00:40:29.680 So I'll have a link in the show notes to that. 00:40:29.680 --> 00:40:30.580 That's great. 00:40:30.580 --> 00:40:31.380 Yeah. 00:40:31.380 --> 00:40:32.800 Those sorts of comments really keep you going. 00:40:32.800 --> 00:40:36.500 I wish that my O'Reilly thing had had such a discussion forum. 00:40:36.500 --> 00:40:38.080 Instead, I have to... 00:40:38.080 --> 00:40:40.140 I got my feedback through reviews for a while. 00:40:40.140 --> 00:40:42.040 Oh, yeah. 00:40:42.040 --> 00:40:42.400 Yeah. 00:40:42.400 --> 00:40:43.720 I mean, emails, too. 00:40:43.720 --> 00:40:44.460 People email. 00:40:44.460 --> 00:40:45.320 And I appreciate it. 00:40:45.320 --> 00:40:45.480 Yeah. 00:40:45.480 --> 00:40:46.720 I get them from all over the place. 00:40:46.720 --> 00:40:48.500 I get it through the discussion forum. 00:40:48.500 --> 00:40:50.260 I get it from Twitter. 00:40:50.260 --> 00:40:51.080 And from... 00:40:51.080 --> 00:40:52.080 We've got a Slack channel. 00:40:52.080 --> 00:40:55.440 So people come and tell me what's wrong in the Slack. 00:40:55.440 --> 00:40:55.840 So... 00:40:55.840 --> 00:40:56.020 Yeah. 00:40:56.120 --> 00:40:56.440 Definitely. 00:40:56.440 --> 00:40:57.260 I don't know. 00:40:57.260 --> 00:40:58.640 For just like sort of chatting here, right? 00:40:58.640 --> 00:41:06.440 I've been really into like Riot.im, which is a Python-based open source Slack sort of thing. 00:41:06.440 --> 00:41:09.600 And there's also Zulip, which is just everywhere these days. 00:41:09.600 --> 00:41:10.820 They're doing an amazing job. 00:41:10.820 --> 00:41:12.360 So what's the first one, Riot? 00:41:12.360 --> 00:41:12.680 Yeah. 00:41:12.680 --> 00:41:16.880 So Riot.im, and it runs a sort of protocol called Matrix. 00:41:16.880 --> 00:41:20.780 And it's a very, very large thing. 00:41:20.780 --> 00:41:25.200 It's basically like you can have end-to-end encrypted chats with people who are on it. 00:41:25.420 --> 00:41:28.020 But I use it because it's an IRC bridge. 00:41:28.020 --> 00:41:33.320 Like I said, if you want to be sort of in this inner circle, see the goings-ons, IRC is still 00:41:33.320 --> 00:41:34.220 very much alive. 00:41:34.220 --> 00:41:39.040 So you've got your list serves and IRC and so forth. 00:41:39.040 --> 00:41:43.360 And Riot makes that pretty easy to get into. 00:41:43.360 --> 00:41:46.900 You know, there's a free node bridge and you just join a free node thing and you can look 00:41:46.900 --> 00:41:51.440 at IRC through your browser while having end-to-end encrypted chats with your other friends. 00:41:51.440 --> 00:41:55.400 It also has a like sort of peer-to-peer video chat that works really, really well. 00:41:55.400 --> 00:41:59.520 Because it's just the WebRTC open source protocol. 00:41:59.520 --> 00:42:00.940 Works great in Firefox. 00:42:00.940 --> 00:42:03.460 Well, I'm going to cut you off because we're right. 00:42:03.460 --> 00:42:04.800 But oh, wait. 00:42:04.800 --> 00:42:05.520 Yeah, we're way long. 00:42:05.520 --> 00:42:06.400 Anyways, that's great. 00:42:06.400 --> 00:42:08.880 Also, I think this is an awesome topic. 00:42:08.880 --> 00:42:15.300 I think that you should come on to Test and Code and we can talk about IRC and communication 00:42:15.300 --> 00:42:15.780 channels. 00:42:15.780 --> 00:42:16.480 That'd be fun. 00:42:16.480 --> 00:42:17.540 That's actually a great idea. 00:42:17.540 --> 00:42:18.420 Yeah, for sure. 00:42:18.640 --> 00:42:22.760 I'm always like coming up short with topics when the, when the, but yeah, here we are 00:42:22.760 --> 00:42:23.300 just chatting. 00:42:23.300 --> 00:42:23.720 That's great. 00:42:23.720 --> 00:42:24.460 That's a great idea. 00:42:24.460 --> 00:42:26.460 Again, thank you so much for coming on. 00:42:26.460 --> 00:42:28.900 I love having new voices on, on here. 00:42:28.900 --> 00:42:30.560 And it's been my pleasure. 00:42:30.560 --> 00:42:31.620 And thank Michael. 00:42:31.620 --> 00:42:33.520 You know, when he gets back, I'll send him an email. 00:42:33.520 --> 00:42:34.300 This has been great. 00:42:34.440 --> 00:42:34.640 Yeah. 00:42:34.640 --> 00:42:36.200 And we'll keep in touch. 00:42:36.200 --> 00:42:40.020 Thank you for listening to Python Bytes. 00:42:40.020 --> 00:42:43.400 Follow the show on Twitter via at Python Bytes. 00:42:43.400 --> 00:42:46.920 That's Python Bytes as in B-Y-T-E-S. 00:42:46.920 --> 00:42:51.020 Get the full show notes, including links at pythonbytes.fm. 00:42:51.020 --> 00:42:56.420 If you have a news story you'd like featured, visit pythonbytes.fm and send it our way. 00:42:56.420 --> 00:42:58.860 We're always on the lookout for sharing something cool. 00:42:58.860 --> 00:43:02.900 This is Brian Okken on behalf of myself and Michael Kennedy. 00:43:03.160 --> 00:43:06.420 Thank you for listening and sharing this podcast with your friends and colleagues.