WEBVTT 00:00:00.001 --> 00:00:05.760 Hello and welcome to Python Bytes, where we deliver Python news and headlines directly to your earbuds. 00:00:05.760 --> 00:00:09.820 This is episode 80, recorded May 25th, 2018. 00:00:09.820 --> 00:00:11.180 I'm Michael Kennedy. 00:00:11.180 --> 00:00:12.060 And I'm Brian Okken. 00:00:12.060 --> 00:00:13.600 And Brian, we have a special guest, don't we? 00:00:13.600 --> 00:00:14.180 Yes. 00:00:14.180 --> 00:00:16.080 Hey, hello, Dan Bader. 00:00:16.080 --> 00:00:19.700 Hey, guys. It's me, Dan. Good to be back on the show. 00:00:19.700 --> 00:00:23.340 And it's always so nice to hear you do this intro live, Mike. 00:00:23.340 --> 00:00:24.700 Thank you. 00:00:24.700 --> 00:00:27.860 It's not, it's so unreal. It's like, and you sound so smooth. I love it. 00:00:27.860 --> 00:00:29.500 I guess I've done it 80 times now. 00:00:29.500 --> 00:00:34.520 Maybe 82 or 83 for the few times I screwed up with the wrong date. 00:00:34.520 --> 00:00:36.840 Well, thank you. And it's great to have you. 00:00:36.840 --> 00:00:44.160 For those of you who don't know Dan, Dan's well known from RealPython and dbeta.org and a bunch of Python goodness. 00:00:44.160 --> 00:00:47.460 Before we get to the show, I want to say thank you to DigitalOcean. 00:00:47.460 --> 00:00:55.060 So they're sponsoring this episode and a number of them coming up, as well as the actual infrastructure delivering all this technology to you. 00:00:55.060 --> 00:01:00.220 So pythonbytes.fm/digitalization, get a $100 credit for new users. 00:01:00.220 --> 00:01:01.140 Pretty awesome. 00:01:01.140 --> 00:01:06.880 Brian, I feel like there's a few themes that we touch on frequently in this podcast. 00:01:06.880 --> 00:01:08.140 Yeah, I guess that we do. 00:01:08.140 --> 00:01:09.720 And one of them is packaging. 00:01:10.080 --> 00:01:12.000 So we've talked about packaging a few times. 00:01:12.000 --> 00:01:20.620 And the Python Packaging Authority has their tutorial on how to package Python packages. 00:01:21.400 --> 00:01:26.360 And it used to be out of date, but now they've recently revamped it and rewritten it. 00:01:26.360 --> 00:01:29.120 And it's very user-friendly now. 00:01:29.120 --> 00:01:39.380 It's a short little walkthrough of how to set up a package and push it to both the test server and then to the full Python Package Index, PYPI. 00:01:39.380 --> 00:01:41.020 Yeah, I got that out. 00:01:41.180 --> 00:01:47.360 One of the things that's kind of fun to note that I noted is the readme example is in Markdown. 00:01:47.360 --> 00:01:49.200 And that's cool. 00:01:49.200 --> 00:01:50.660 And that's a new feature, right? 00:01:50.660 --> 00:01:55.820 That's one of the things of them switching to Warehouse and the big release of the new pypi.org. 00:01:55.820 --> 00:01:59.600 I think I remember the old examples for setup.py. 00:01:59.600 --> 00:02:01.400 They were either too small. 00:02:01.400 --> 00:02:03.460 They didn't include everything they needed. 00:02:03.660 --> 00:02:05.820 Or they were too big and kind of scary. 00:02:05.820 --> 00:02:11.160 And now this is a medium-sized example setup.py that is actually pretty nice. 00:02:11.160 --> 00:02:15.540 You know, I read through it and it looked like the same tool set that I used to push up. 00:02:15.540 --> 00:02:17.320 So I think it's pretty accurate now. 00:02:17.320 --> 00:02:18.020 So that's nice. 00:02:18.020 --> 00:02:18.300 Nice. 00:02:18.300 --> 00:02:19.980 You didn't feel like you were super out of date. 00:02:19.980 --> 00:02:21.940 You're like, why am I not using this or using that? 00:02:21.940 --> 00:02:31.680 Yeah, because when I learned how to do it the first time, I think I read both the old tutorial and then like four or five or six different blog articles on how to do it now. 00:02:31.680 --> 00:02:33.840 I don't know how to do it now because it changed. 00:02:33.840 --> 00:02:35.240 But now this is all up to date. 00:02:35.240 --> 00:02:36.140 So it's good. 00:02:36.140 --> 00:02:36.660 Very nice. 00:02:36.660 --> 00:02:38.500 Dan, did you do much packaging? 00:02:38.500 --> 00:02:39.060 Yeah. 00:02:39.060 --> 00:02:48.660 So I run a couple of open source projects and I always felt like, you know, exactly like what you were just saying, Brian, where I had to combine a couple of tutorials just to get it to work. 00:02:48.660 --> 00:02:50.380 And it never really felt all that straightforward. 00:02:50.380 --> 00:02:54.740 And so I think this is a pretty nice and pretty minimal write-up. 00:02:54.740 --> 00:02:55.340 I like that. 00:02:55.340 --> 00:03:00.080 And I'm surprised that the recommendation now seems to be to use Markdown-based readme files. 00:03:00.280 --> 00:03:01.300 Like I really like Markdown. 00:03:01.300 --> 00:03:04.280 I really warmed up to restructured text so much. 00:03:04.280 --> 00:03:07.000 And it's definitely cool that they're supporting that now. 00:03:07.000 --> 00:03:07.600 That's awesome. 00:03:07.600 --> 00:03:09.920 I think restructured text maybe predated Markdown. 00:03:09.920 --> 00:03:15.880 And it was, you know, it was the thing when the original PyPI was created. 00:03:15.880 --> 00:03:18.940 And then just like that thing was, you know, calcified. 00:03:18.940 --> 00:03:20.360 And I go, let's not touch this. 00:03:20.360 --> 00:03:21.940 Let's just not mess with this. 00:03:21.940 --> 00:03:22.900 Let's just keep it running. 00:03:22.900 --> 00:03:23.200 Right. 00:03:24.000 --> 00:03:26.340 It's really good to see that getting a fresh update. 00:03:26.340 --> 00:03:28.640 Also, Brian, you talk about Twine in here. 00:03:28.640 --> 00:03:29.500 What's the story with Twine? 00:03:29.500 --> 00:03:31.100 I don't know if there's a story with it. 00:03:31.100 --> 00:03:36.220 That's just the tool you use to push things up to PyPI. 00:03:36.220 --> 00:03:36.780 Oh, nice. 00:03:36.780 --> 00:03:39.880 I probably used it and didn't realize it or forgot that I used it. 00:03:39.880 --> 00:03:41.960 Maybe there's another way, but that's what I've always used. 00:03:41.960 --> 00:03:42.500 Yeah, cool. 00:03:42.560 --> 00:03:45.220 Actually, there's a cool project to throw in the mix here. 00:03:45.220 --> 00:03:47.940 It's called FLIT, F-L-I-T. 00:03:47.940 --> 00:03:51.880 And it's, well, what's a good way to describe it? 00:03:51.880 --> 00:03:56.420 It's sort of a minimal, simple way to put Python packages on PyPI. 00:03:56.420 --> 00:03:59.700 So they kind of completely done away with the setup.py. 00:03:59.700 --> 00:04:03.860 Instead, you write an init file where you just put in, you know, your author name and your 00:04:03.860 --> 00:04:04.500 homepage or whatever. 00:04:04.500 --> 00:04:06.620 And it generates all of that other stuff. 00:04:06.620 --> 00:04:09.880 And it might not be really necessary anymore now. 00:04:09.880 --> 00:04:13.540 You know, if you have like a really sort of short and sweet tutorial, like the one that 00:04:13.540 --> 00:04:14.480 we were just talking about. 00:04:14.480 --> 00:04:18.940 But it is super, super beginner friendly, this FLIT thing. 00:04:18.940 --> 00:04:20.140 Oh, that's cool. 00:04:20.140 --> 00:04:20.480 Nice. 00:04:20.480 --> 00:04:21.400 It's F-L-I-T? 00:04:21.400 --> 00:04:22.380 It's F-L-I-T. 00:04:22.380 --> 00:04:22.720 Yeah. 00:04:22.720 --> 00:04:23.100 Awesome. 00:04:23.100 --> 00:04:23.720 All right. 00:04:23.720 --> 00:04:25.860 And so that's probably on GitHub, isn't it, Dan? 00:04:25.860 --> 00:04:26.760 Yes, it is. 00:04:26.760 --> 00:04:28.080 Nice transition. 00:04:28.080 --> 00:04:32.760 So the next thing you have for us is an async library for calling GitHub's API. 00:04:32.760 --> 00:04:33.400 Yeah. 00:04:33.400 --> 00:04:33.860 Yeah. 00:04:33.860 --> 00:04:39.520 So I was going to talk about this thing called GidgetHub, which is, yeah, a Python wrapper 00:04:39.520 --> 00:04:40.820 around the GitHub API. 00:04:40.820 --> 00:04:45.700 So basically allows you to talk to GitHub and you can interact with all the different 00:04:45.700 --> 00:04:49.100 content types that GitHub provides or exposes. 00:04:49.100 --> 00:04:51.340 So you can add and modify issues. 00:04:51.340 --> 00:04:53.480 You can, you know, create pull requests. 00:04:53.480 --> 00:04:55.520 You can add comments to pull requests. 00:04:55.520 --> 00:04:58.120 You can download all the comments to pull requests and all that stuff. 00:04:58.660 --> 00:05:03.960 So the other thing it does, it allows you to parse GitHub's webhooks. 00:05:03.960 --> 00:05:08.360 So you can configure GitHub so that every time a new pull request or something like that is 00:05:08.360 --> 00:05:14.540 created, it sends, essentially calls a, an API callback on the web, like on some URL that 00:05:14.540 --> 00:05:15.200 you give it. 00:05:15.200 --> 00:05:21.960 And so what you can use GidgetHub for is a really nice and clean way to write GitHub bots with 00:05:21.960 --> 00:05:22.860 Python, essentially. 00:05:23.700 --> 00:05:26.180 And it's just a really cool library. 00:05:26.180 --> 00:05:28.080 And I think it's API super well designed. 00:05:28.080 --> 00:05:34.840 So we were recently using it on a workshop that we did in Vancouver, like Marietta, who's a 00:05:34.840 --> 00:05:36.080 CPython core developer, did it. 00:05:36.080 --> 00:05:38.060 And I served T8 and was running around helping her. 00:05:38.060 --> 00:05:41.880 And so she wrote a really good, cool tutorial about how to use GidgetHub. 00:05:42.420 --> 00:05:48.080 I think it's just a really nice example from modern Python web API library. 00:05:48.080 --> 00:05:49.180 It looks really great. 00:05:49.180 --> 00:05:52.240 And so you just go over here and you say like, I'd like to open a PR. 00:05:52.240 --> 00:05:57.700 So you get some PR data, then you say await GitHub.post. 00:05:57.700 --> 00:06:01.680 And, you know, all your, all your methods are async. 00:06:01.680 --> 00:06:03.240 Yeah, definitely nice and scalable. 00:06:03.240 --> 00:06:10.020 Well, it looks like it's based on aiohttp, which is a really nice client side, async enabled 00:06:10.020 --> 00:06:12.440 REST library. 00:06:12.440 --> 00:06:16.700 What's really, really cool about this GidgetHub thing is that it's actually abstracting away 00:06:16.700 --> 00:06:22.220 from the actual backend, I want to say, you know, what the actual library you use to talk 00:06:22.220 --> 00:06:26.840 to or to handle those web requests, whether they're incoming or outbound. 00:06:26.840 --> 00:06:31.720 So I just learned that this is referred to as a sans IO library. 00:06:31.720 --> 00:06:37.380 So basically, it's just a protocol implementation that doesn't really specify how the IO is 00:06:37.380 --> 00:06:37.780 performed. 00:06:37.780 --> 00:06:45.320 So it allows you to plug in different backends, different concrete implementations that make 00:06:45.320 --> 00:06:47.300 this thing super reusable. 00:06:47.300 --> 00:06:51.120 Because, well, if there's a new async library, you know, flavor of the day kind of thing in 00:06:51.120 --> 00:06:53.940 a couple of months, then, well, you can probably just plug that in and work with that. 00:06:53.940 --> 00:06:55.460 So it's kind of nice. 00:06:55.460 --> 00:06:56.480 It's really well-designed. 00:06:56.480 --> 00:06:58.060 Yeah, so you can use aiohttp. 00:06:58.060 --> 00:06:59.540 You can use Tornado. 00:06:59.540 --> 00:06:59.980 Yep. 00:06:59.980 --> 00:07:05.620 Yeah, I was recently, we covered it on the show, this thing called unsync instead of async, 00:07:05.620 --> 00:07:06.360 U-N-sync. 00:07:07.300 --> 00:07:12.940 And it's a different implementation with a different event loop thing. 00:07:12.940 --> 00:07:14.880 Maybe you could use that here as well. 00:07:14.880 --> 00:07:16.100 That's pretty awesome. 00:07:16.100 --> 00:07:17.400 I like it. 00:07:17.400 --> 00:07:18.320 Nice pick. 00:07:18.320 --> 00:07:18.900 Nice, yeah. 00:07:18.900 --> 00:07:19.740 It's nice to use. 00:07:19.740 --> 00:07:20.640 Super friendly. 00:07:20.640 --> 00:07:21.100 Yeah. 00:07:21.100 --> 00:07:22.820 Brian, do you guys do any GitHub automation? 00:07:22.820 --> 00:07:25.840 You just started with Git at your organization, right? 00:07:25.920 --> 00:07:30.340 We're doing a, we've got a private server, so we don't go through GitHub for work stuff. 00:07:30.340 --> 00:07:32.040 But I use GitHub all the time. 00:07:32.040 --> 00:07:32.740 Yeah, of course. 00:07:32.740 --> 00:07:33.160 Locally. 00:07:33.160 --> 00:07:34.080 Yeah, nice. 00:07:34.080 --> 00:07:40.500 Yeah, I feel like this kind of automation is more relevant and useful when either you're 00:07:40.500 --> 00:07:46.120 building an app or you have like a big organization and you want to automate your company's interaction 00:07:46.120 --> 00:07:47.560 with GitHub, right? 00:07:47.560 --> 00:07:53.140 Like me as an individual, I just don't really see a massive use of this for me because I just 00:07:53.140 --> 00:07:55.880 don't do that much different other than what I personally do with GitHub. 00:07:55.880 --> 00:07:59.100 But I think it looks really cool and I love the way it works. 00:07:59.100 --> 00:08:02.700 Some uses where you could often use like Travis or something like that. 00:08:02.700 --> 00:08:07.160 Like if you were watching different, if your project depended on a bunch of dependencies 00:08:07.160 --> 00:08:12.240 and you wanted to, when, if they changed, pull them in and run your build, repackage everything 00:08:12.240 --> 00:08:16.100 and run some tests against it, you could do that locally with something like this. 00:08:16.240 --> 00:08:16.880 Yeah, that's pretty cool. 00:08:16.880 --> 00:08:20.060 Or you have that one person on your team that often breaks the build. 00:08:20.060 --> 00:08:22.740 So you run extra tests when you see them do a check-in. 00:08:22.740 --> 00:08:28.660 A harassment bot that just goes in and be careful. 00:08:28.660 --> 00:08:32.920 Yeah, I think they use it on CPython. 00:08:32.920 --> 00:08:35.520 You know, they've moved all of the source for that to GitHub. 00:08:35.520 --> 00:08:39.940 And I think now they, they have run a couple of bots that I think one of the things they 00:08:39.940 --> 00:08:44.800 do is, so when you contribute to CPython, they need you to sign an agreement that you're 00:08:44.800 --> 00:08:47.060 giving up the rights essentially for your contributions. 00:08:47.060 --> 00:08:49.600 And so they, I think Marietta actually runs that bot. 00:08:49.600 --> 00:08:54.120 I might be mistaken here, but it's a bot that checks if that committer or that contributor 00:08:54.120 --> 00:08:55.360 already has given their permission. 00:08:55.360 --> 00:08:58.400 And if they didn't yet, then it's just going to ask them to do it. 00:08:58.400 --> 00:08:59.600 And it sets a flag on the PR. 00:08:59.600 --> 00:09:04.300 So it's, it's super cool that way when you can sort of code up a workflow like that, that 00:09:04.300 --> 00:09:08.180 you never have to worry about again in your life because it's a hundred percent automated. 00:09:08.180 --> 00:09:10.920 So I think it's, it's great for that sort of use case. 00:09:11.120 --> 00:09:12.120 That is a great use case. 00:09:12.120 --> 00:09:13.380 Yeah, that's really, really awesome. 00:09:13.380 --> 00:09:13.900 Okay. 00:09:13.900 --> 00:09:19.860 So the next one that I wanted to talk about actually was recommended to me, recommended 00:09:19.860 --> 00:09:24.360 to me and Brian because of some stuff that I had recently been doing. 00:09:24.360 --> 00:09:25.800 I think, you know, we were all at PyCon. 00:09:25.800 --> 00:09:29.280 I think maybe we're all at the same, same meeting or get together. 00:09:29.800 --> 00:09:31.660 And I had just decided like, that's it. 00:09:31.660 --> 00:09:40.420 I'm writing a Python system D daemon that will synchronize all of my course data geo, basically 00:09:40.420 --> 00:09:43.020 across the various servers in the different locations. 00:09:43.020 --> 00:09:47.960 So there's like eight or nine places in the world that serve up course content based on 00:09:47.960 --> 00:09:48.500 where you are. 00:09:48.500 --> 00:09:55.600 And so I wrote a service in Python that is a system D service that will basically keep all 00:09:55.600 --> 00:09:56.780 those places in sync. 00:09:57.160 --> 00:09:58.700 Nothing too impressive, but it's kind of cool. 00:09:58.700 --> 00:09:59.440 You can do that in Python. 00:09:59.440 --> 00:10:05.980 So we got pointed at this thing called PySystemD and this was actually presented at PyCon 2018. 00:10:05.980 --> 00:10:10.020 So there's a whole talk and you can go learn about what is system D, why you care about it, 00:10:10.020 --> 00:10:10.780 how is it used. 00:10:10.780 --> 00:10:19.640 But the short version is this PySystemD is an API into the system D whole API part of Linux. 00:10:19.840 --> 00:10:23.380 So you can create things that are daemons. 00:10:23.380 --> 00:10:28.800 You can say like, I would like to have my Python web app start and I want it to start in this 00:10:28.800 --> 00:10:33.100 way, but I want it to not start before my MongoDB server starts. 00:10:33.100 --> 00:10:35.080 I don't want MongoDB to start in that way. 00:10:35.080 --> 00:10:39.740 You can configure these things to all just happen on boot or on demand, things like that. 00:10:39.740 --> 00:10:42.080 So I think this is really pretty awesome. 00:10:42.300 --> 00:10:46.760 So if anyone's doing any sort of automation with system D and they're already using Python, 00:10:46.760 --> 00:10:51.300 here's a really great way to just like, you know, import this library and just ask, hey, 00:10:51.300 --> 00:10:55.860 let's load up this unit, which is like one of these services and ask, is it running? 00:10:55.860 --> 00:10:57.140 Let's start it. 00:10:57.140 --> 00:10:58.180 Let's create a new one. 00:10:58.180 --> 00:10:59.060 All sorts of stuff. 00:10:59.060 --> 00:10:59.780 Really, really nice. 00:10:59.780 --> 00:11:00.400 That's cool. 00:11:00.400 --> 00:11:01.160 Yeah. 00:11:01.200 --> 00:11:03.480 And also kind of cool how this was built. 00:11:03.480 --> 00:11:05.280 So this is like based on Cython. 00:11:05.280 --> 00:11:09.780 So it's a wrapper and the C library that actually talks to system D, right? 00:11:09.780 --> 00:11:10.720 Yeah, I think so. 00:11:10.720 --> 00:11:17.240 And actually, I'm going to cover in the next episode, this sort of article on using Cython 00:11:17.240 --> 00:11:21.440 as a way for a simple way to wrap C APIs. 00:11:21.440 --> 00:11:22.760 That's what surprised me. 00:11:22.760 --> 00:11:23.200 Yeah. 00:11:23.200 --> 00:11:26.060 I think that's why, because it doesn't seem like a performance thing, right? 00:11:26.080 --> 00:11:31.940 I think it's like, let's use Cython to get a really simple API into the C layer as well 00:11:31.940 --> 00:11:33.900 as build the integration back into Python. 00:11:33.900 --> 00:11:34.640 So pretty cool. 00:11:34.640 --> 00:11:35.060 Yeah, nice. 00:11:35.060 --> 00:11:38.600 I'd love to see that because I'm surprised they're using Cython for that and not just, 00:11:38.600 --> 00:11:40.860 you know, C types or CFFI or something like that. 00:11:40.860 --> 00:11:43.340 But I'm sure there's a reason for that. 00:11:43.340 --> 00:11:47.800 The other thing I wanted to point out about this is this was created and presented by Alvaro 00:11:47.800 --> 00:11:48.820 Liva. 00:11:48.820 --> 00:11:50.640 Sorry if I'm mispronouncing your last name there. 00:11:50.640 --> 00:11:54.880 But he's a production engineer at Instagram and Facebook. 00:11:55.280 --> 00:11:57.880 And so, you know, they have a few servers to manage. 00:11:57.880 --> 00:12:03.620 And this is probably pretty polished and comes from a pretty well, well-informed space if 00:12:03.620 --> 00:12:04.800 it's being used there, right? 00:12:04.800 --> 00:12:05.540 Pretty sweet. 00:12:05.540 --> 00:12:06.720 All right. 00:12:06.720 --> 00:12:11.300 So before we get to the next one, let me tell you guys about DigitalOcean. 00:12:11.300 --> 00:12:19.220 So DigitalOcean is definitely one of the best hosting frameworks or places out there. 00:12:19.220 --> 00:12:23.700 You can go up, create a server, super easy, create a load balancer. 00:12:24.480 --> 00:12:30.260 You can create floating APIs that allow you to switch between various machines with perceived 00:12:30.260 --> 00:12:32.120 zero downtime, all sorts of stuff. 00:12:32.120 --> 00:12:37.340 All of our code and our sites, our delivery, all that stuff is running on top of it. 00:12:37.340 --> 00:12:40.180 It has been for a long time and it's been working great. 00:12:40.740 --> 00:12:45.480 So like I said, if you're thinking about running servers and you want to do it affordably, high 00:12:45.480 --> 00:12:50.480 performance with lots of control, then go to pythonbytes.fm/DigitalOcean. 00:12:50.480 --> 00:12:53.600 If you're a new user, you'll get $100 credit. 00:12:53.600 --> 00:12:56.020 And, you know, check out what they have. 00:12:56.020 --> 00:13:00.880 It takes about 60 seconds to set up a new server and you'll be SSH'd in and doing all sorts of 00:13:00.880 --> 00:13:01.240 good stuff. 00:13:01.660 --> 00:13:05.080 Maybe you could even use PySystemD to like automate some cool stuff on it afterwards. 00:13:05.080 --> 00:13:07.280 So check them out. 00:13:07.280 --> 00:13:08.100 It helps support the show. 00:13:08.100 --> 00:13:10.640 And it's definitely a good product worth checking out. 00:13:10.640 --> 00:13:13.320 Speaking of products, Brian, you're excited about one. 00:13:13.320 --> 00:13:14.240 Oh, an update one, right? 00:13:14.240 --> 00:13:15.640 Yeah, I am. 00:13:15.640 --> 00:13:23.880 I usually, for a while, I was running the latest or the last 2017 release of PyCharm. 00:13:24.440 --> 00:13:31.540 But I don't know how recent this was, but not too long ago, we had the early access program 00:13:31.540 --> 00:13:36.920 build one of 2018.2 is out for PyCharm. 00:13:36.920 --> 00:13:43.600 And the really exciting bit, and we got notified by this from the Bruno Oliveira, who goes by 00:13:43.600 --> 00:13:48.880 Nicodermis on Twitter, but it supports a whole bunch of new pytest features. 00:13:48.880 --> 00:13:52.620 And I'm kind of a pytest kind of nut. 00:13:53.080 --> 00:13:55.440 So the things that I'm really excited about... 00:13:55.440 --> 00:13:56.760 You could say you wrote the book on it. 00:13:56.760 --> 00:13:57.300 Yeah. 00:13:57.300 --> 00:14:00.020 Well, you could, because I did. 00:14:00.020 --> 00:14:06.220 Anyway, a couple of the features that I was really waiting for is PyCharm's really, being 00:14:06.220 --> 00:14:09.380 an IDE, has a lot of, like, what do you call that? 00:14:09.380 --> 00:14:10.540 IntelliSense or something? 00:14:10.540 --> 00:14:11.880 Yeah, Autocomplete IntelliSense. 00:14:11.880 --> 00:14:12.280 Yeah. 00:14:12.280 --> 00:14:12.980 Autocomplete. 00:14:12.980 --> 00:14:16.320 That didn't work for fixtures to a test. 00:14:16.320 --> 00:14:22.260 So if your test was using fixtures and you was returning an object or a function or something, 00:14:22.720 --> 00:14:27.200 and you were trying to call that, you didn't have all of those cool autocomplete features, 00:14:27.200 --> 00:14:30.460 those are now in for fixtures of tests. 00:14:30.460 --> 00:14:32.120 And that's really cool. 00:14:32.120 --> 00:14:39.340 But the thing that I'm really excited about is parameterization now works seamlessly within 00:14:39.340 --> 00:14:39.760 PyCharm. 00:14:39.900 --> 00:14:45.980 So if you've got a test that is parameterized so that you've got, like, several, or in my 00:14:45.980 --> 00:14:51.300 case, sometimes dozens of different parameter sets that are run through the same test, you 00:14:51.300 --> 00:14:55.360 could always run that through, run all of those parameterizations in PyCharm. 00:14:55.360 --> 00:14:56.220 And that was wonderful. 00:14:56.380 --> 00:15:01.780 If you wanted to rerun one or rerun the failing ones, it would just rerun all of them. 00:15:01.780 --> 00:15:02.080 I see. 00:15:02.080 --> 00:15:05.900 It treated like a whole method in the decorator bit that had, here's all the variations. 00:15:06.120 --> 00:15:08.720 That was just like a thing that it would just rerun, right? 00:15:08.720 --> 00:15:09.000 Yeah. 00:15:09.000 --> 00:15:10.520 So now you can run a test. 00:15:10.520 --> 00:15:16.280 And then in the left sidebar, you can right click on one of them and rerun just one of the 00:15:16.280 --> 00:15:17.020 parameterizations. 00:15:17.020 --> 00:15:23.560 Or you can, like, for instance, if like only two or three or some of them failed, when you 00:15:23.560 --> 00:15:26.740 rerun failures, it only runs the parameterizations that failed. 00:15:26.740 --> 00:15:29.760 And this is a huge time saver for me. 00:15:29.760 --> 00:15:30.980 So I'm really excited about it. 00:15:30.980 --> 00:15:31.540 Yeah, that's nice. 00:15:31.580 --> 00:15:33.980 I use that feature a lot where I just say rerun the failed tests. 00:15:33.980 --> 00:15:37.880 For people that are like really, and may not be too much of an issue for people that are 00:15:37.880 --> 00:15:42.620 running really quick tests, but a lot of my tests talk to hardware. 00:15:42.620 --> 00:15:44.080 So they're not really that fast. 00:15:44.080 --> 00:15:47.720 So this will save me like an hour a day, I'm sure. 00:15:47.720 --> 00:15:48.300 That's awesome. 00:15:48.300 --> 00:15:49.220 Very, very cool. 00:15:49.220 --> 00:15:50.900 Dan, do you use pytest? 00:15:50.900 --> 00:15:51.400 Yeah, I do. 00:15:51.400 --> 00:15:54.280 Yeah, I actually just, you know, used it. 00:15:54.280 --> 00:15:57.360 I rewrote the backend for realpython.com. 00:15:57.360 --> 00:16:00.800 So we've got pytest powered tests and integration tests for that. 00:16:00.800 --> 00:16:03.480 And yeah, it's just been a joy to use, like especially the parameterization stuff. 00:16:03.480 --> 00:16:06.660 It's just so nice when you can reuse a lot of test code. 00:16:06.660 --> 00:16:08.660 You don't have to like copy paste it around so much. 00:16:08.660 --> 00:16:13.160 So Dan, one thing I was going to cover, but you put it in here before, before I could get 00:16:13.160 --> 00:16:13.500 to it. 00:16:13.500 --> 00:16:21.540 So you're faster is basically why is installing Python 3.6 so hard and so sort of confusing, 00:16:21.540 --> 00:16:21.900 right? 00:16:21.900 --> 00:16:26.620 Like you talked about this workshop that you recently did and I've thrown this out on Twitter 00:16:26.620 --> 00:16:28.440 and people sometimes tell me, oh, it's not hard. 00:16:28.440 --> 00:16:28.940 It's super easy. 00:16:29.040 --> 00:16:33.240 You do this, but then you, if you actually go teach a workshop to beginners, you're like, 00:16:33.240 --> 00:16:36.000 why are those four people over there not ready yet? 00:16:36.000 --> 00:16:36.960 Like it's been 10 minutes. 00:16:36.960 --> 00:16:38.540 What could they have possibly been doing? 00:16:38.540 --> 00:16:41.260 And it's because it's like, there's all these edge cases, right? 00:16:41.260 --> 00:16:45.920 It's one of these things where in theory it's easy and it's not a problem that you really 00:16:45.920 --> 00:16:48.680 run into when you've, you know, have a little bit more experience under your belt. 00:16:48.960 --> 00:16:52.780 But for people getting into Python, it is definitely a barrier. 00:16:52.780 --> 00:16:56.080 And we were taught, teaching this, this workshop. 00:16:56.080 --> 00:16:59.380 So Mariada was teaching it and I was just running around kind of, you know, supporting people. 00:17:00.040 --> 00:17:05.200 And for some people we spend almost like two hours to get them to a working Python 3.6 install. 00:17:05.200 --> 00:17:05.600 That's insane. 00:17:06.420 --> 00:17:10.460 And, you know, there were some really, like you hit all of these interesting, but obviously 00:17:10.460 --> 00:17:12.260 kind of frustrating edge cases. 00:17:12.260 --> 00:17:17.020 Like some people were running, they were running a Windows host and then they were also running 00:17:17.020 --> 00:17:18.540 the Linux subsystem for Windows. 00:17:18.540 --> 00:17:23.560 So now you can, you know, can essentially boot up a VM that is integrated into Windows and it 00:17:23.560 --> 00:17:26.800 boots Ubuntu or Debian or some other Linux, the Linux distribution, I think. 00:17:26.800 --> 00:17:28.520 I think it defaults to Ubuntu. 00:17:28.520 --> 00:17:28.960 I'm not sure. 00:17:29.120 --> 00:17:29.940 I think it's Ubuntu as well. 00:17:29.940 --> 00:17:30.540 Yeah, that's nice. 00:17:30.540 --> 00:17:34.080 So basically you have this like really tightly integrated Linux environment that you can just 00:17:34.080 --> 00:17:37.140 work from, from your Windows host environment. 00:17:37.140 --> 00:17:44.260 The problem is that people maybe accidentally installed Python in the Linux environment and 00:17:44.260 --> 00:17:48.480 they try and access it from the Windows environment because it's a little bit unclear if you're a 00:17:48.480 --> 00:17:51.060 beginner, like what actually the difference is, you know, between these like two different 00:17:51.060 --> 00:17:52.140 terminal windows. 00:17:52.140 --> 00:17:52.900 Right. 00:17:52.900 --> 00:17:55.460 And you also might open PowerShell, which is like a third still. 00:17:55.460 --> 00:17:55.940 Exactly. 00:17:55.940 --> 00:17:56.720 You know, things like that. 00:17:56.720 --> 00:17:58.820 And then you have like your paths set in different ways. 00:17:59.000 --> 00:18:00.800 And other issues were that. 00:18:00.800 --> 00:18:05.460 So the previous long term release of Ubuntu, I think it was 1604. 00:18:05.460 --> 00:18:08.600 So it doesn't ship with Python 3.6. 00:18:08.600 --> 00:18:11.060 And so for this tutorial, we specifically needed 3.6. 00:18:11.060 --> 00:18:16.440 And so, you know, people started Googling and just copying a bunch of stuff from Stack Overflow 00:18:16.440 --> 00:18:18.300 to install Python 3.6 on Ubuntu. 00:18:18.300 --> 00:18:21.280 Well, it turns out there's like two different PPAs. 00:18:21.280 --> 00:18:24.560 So like third party packages that you can install this from. 00:18:24.560 --> 00:18:28.300 And one of them is broken or was broken during that time. 00:18:28.880 --> 00:18:33.280 So, you know, people would have Python 3, but it had broken SSL and no pip. 00:18:33.280 --> 00:18:37.320 So it was essentially useless for the purposes of this tutorial. 00:18:38.100 --> 00:18:42.760 And it's kind of crazy just into, you know, all of the edge cases you can encounter with this. 00:18:42.760 --> 00:18:45.220 And I think it's really something we need to keep in mind. 00:18:45.220 --> 00:18:50.300 You know, when we're teaching beginners or kind of telling people how awesome Python is, it can be a pretty jarring experience. 00:18:50.300 --> 00:18:52.780 If you try to set it up and you're just sitting there. 00:18:52.780 --> 00:18:53.680 Well, okay. 00:18:53.680 --> 00:18:54.580 I just wanted to try this. 00:18:54.580 --> 00:18:55.060 It doesn't work. 00:18:55.060 --> 00:18:55.420 For sure. 00:18:55.900 --> 00:19:01.680 Well, so you guys are writing this up at realpython.com slash installing dash Python as sort of an ongoing guide, right? 00:19:01.800 --> 00:19:01.960 Yeah. 00:19:01.960 --> 00:19:04.360 So we decided to do something about it. 00:19:04.360 --> 00:19:07.180 So shout out to John Sturtz and Jim Anderson. 00:19:07.680 --> 00:19:13.920 And we got together and put together this sort of the ultimate Python 3 install guide. 00:19:13.920 --> 00:19:15.900 And we're going to keep it maintained. 00:19:15.900 --> 00:19:21.360 And it tells you how to install Python in very specific steps in all kinds of different configurations. 00:19:21.360 --> 00:19:25.800 So Linux, macOS, different Linux distributions, how to compile it from source. 00:19:26.120 --> 00:19:29.100 And we're just going to add to it and, you know, improve it based on feedback. 00:19:29.100 --> 00:19:33.600 And hopefully that's something we can just use in the next workshop and then tell people what to do. 00:19:33.600 --> 00:19:39.040 I hope that when you refer to Python 2 in there to say, oh, don't do Python 2, do Python 3, that you call it legacy Python. 00:19:39.040 --> 00:19:41.340 So just throw that in there. 00:19:41.340 --> 00:19:43.540 I'm still trying to make that a thing. 00:19:43.540 --> 00:19:45.900 I don't think we even mentioned it in that particular piece. 00:19:45.900 --> 00:19:47.260 This is Python 3 only. 00:19:47.260 --> 00:19:51.960 And then my Mac is about ready for a format because, you know, it's time. 00:19:51.960 --> 00:19:54.060 It's been like, it's been bad. 00:19:54.060 --> 00:19:56.040 So anyway, it's about time for format. 00:19:56.700 --> 00:20:00.140 What would you, like, after going through this whole experience, we could do homebrew. 00:20:00.140 --> 00:20:01.320 You could do anaconda. 00:20:01.320 --> 00:20:05.760 You could do download the PKG file from python.org, et cetera, et cetera. 00:20:05.760 --> 00:20:08.480 What would you do if you were setting up a new computer? 00:20:08.480 --> 00:20:09.460 Like on Mac? 00:20:09.460 --> 00:20:10.380 Yeah, on Mac. 00:20:10.380 --> 00:20:10.720 Yeah. 00:20:10.720 --> 00:20:16.800 So I'm a big homebrew fan because it makes upgrading very easy. 00:20:16.800 --> 00:20:22.300 And it's just something that I personally use for other purposes as well. 00:20:22.380 --> 00:20:27.780 So one of the things I usually do, you know, when I set up a new macOS development environment, I upgrade bash. 00:20:28.160 --> 00:20:33.340 So I use bash as my preferred shell and macOS ships with a super old version of bash. 00:20:33.340 --> 00:20:37.740 And with homebrew, it's super easy just to get the latest version of bash. 00:20:37.740 --> 00:20:40.460 And then, you know, a bunch of other command line tools that I use. 00:20:40.460 --> 00:20:43.180 And so I just use that to install Python as well. 00:20:43.180 --> 00:20:44.720 So I kind of like that. 00:20:44.820 --> 00:20:47.580 I mean, Python.org version, it works as well. 00:20:47.580 --> 00:20:54.520 But if you're going to use homebrew anyway, which I think you want to use if you're on a Mac, then I would just keep everything in homebrew. 00:20:54.520 --> 00:20:55.680 Yeah, that's what I'm thinking as well. 00:20:55.680 --> 00:20:56.440 It makes a lot of sense. 00:20:56.440 --> 00:20:57.600 Awesome. 00:20:57.600 --> 00:20:59.140 Both on Mac and on Windows. 00:20:59.140 --> 00:21:02.600 I just always just use the python.org installer. 00:21:02.600 --> 00:21:04.220 Yeah, that's what I've been doing as well. 00:21:04.220 --> 00:21:09.060 But with homebrew, you just type upgrade, you know, and you can have different versions and stuff. 00:21:09.060 --> 00:21:09.540 I don't know. 00:21:09.540 --> 00:21:11.220 I'm thinking of playing with homebrew next time. 00:21:11.300 --> 00:21:12.360 But anyway, very cool. 00:21:12.360 --> 00:21:13.700 Yeah, there's also pyenv. 00:21:13.700 --> 00:21:15.020 So that's sort of the other. 00:21:15.020 --> 00:21:19.700 If you're going to go with homebrew, you could just go, you know, brew installed Python 3. 00:21:19.700 --> 00:21:22.400 And you get sort of one, the latest version of Python 3. 00:21:22.400 --> 00:21:26.040 Or you could install something called pyenv first. 00:21:26.040 --> 00:21:35.440 And then that's another layer of abstraction on top that allows you to switch between different versions of Python, including different versions of Python 3. 00:21:35.440 --> 00:21:38.980 So you can just go, you know, I want Python 3.5 for testing. 00:21:38.980 --> 00:21:41.260 And I'm going to run all of my latest stuff. 00:21:41.260 --> 00:21:44.160 On the Python 3.7 beta version or something like that. 00:21:44.160 --> 00:21:45.780 So that's super nice. 00:21:45.780 --> 00:21:46.920 It's maybe a little bit more advanced. 00:21:46.920 --> 00:21:48.500 So I feel like you're probably there, Mike. 00:21:48.500 --> 00:21:50.760 But for a complete beginner, I'm not sure if I would recommend it. 00:21:50.760 --> 00:21:51.360 Yeah, yeah, yeah. 00:21:51.360 --> 00:21:51.800 Sure, of course. 00:21:51.800 --> 00:21:52.820 I don't think I'm there. 00:21:52.820 --> 00:21:55.680 I've tried it several times and it hasn't worked for me. 00:21:55.680 --> 00:21:56.960 I don't want to go too much longer. 00:21:57.120 --> 00:22:10.540 But what I've started doing on my servers is when I SSH in, part of my shell profile automatically configures the main virtual environment for whatever that purpose of that server is. 00:22:10.540 --> 00:22:14.880 So when I SSH in, I'm actually running just a virtual environment just by default. 00:22:15.440 --> 00:22:20.560 And I was considering doing even that for my Mac and just changing the shell back so it doesn't do something weird. 00:22:20.560 --> 00:22:21.080 I don't know. 00:22:21.080 --> 00:22:23.740 I may get myself into trouble with that, but it's been working so far. 00:22:23.740 --> 00:22:24.720 All right. 00:22:24.720 --> 00:22:30.820 So I want to round this out with just a short little list of 30 amazing Python projects from 2018. 00:22:31.060 --> 00:22:41.140 So there's this thing called MyBridge and MyBridge is a little bit like a readability or a little bit like a flipboard where they kind of keep track of different articles. 00:22:41.140 --> 00:22:44.960 But it's more technology focused than just say Flipboard or Zite, those types of things. 00:22:44.960 --> 00:22:55.280 And the article starts with the MyBridge AI evaluates the quality by considering popularity, engagement, recency, and so on. 00:22:55.340 --> 00:23:02.660 So apparently they have this AI, which is kind of cool, that goes through and looks at human interaction with all these articles, these tech articles in the Python space, 00:23:02.660 --> 00:23:10.080 and then says, here's the articles that our community sort of interacted with that they really liked, or packages actually in this case. 00:23:10.080 --> 00:23:18.160 So let me just give you a quick rundown on these just to kind of give you all some exposure and like, oh, hey, I hadn't heard of that package. 00:23:18.160 --> 00:23:19.140 That's pretty cool. 00:23:19.140 --> 00:23:20.780 And then you guys can jump in and give me some thoughts. 00:23:21.200 --> 00:23:25.120 So I'll go from the least popular to the most popular. 00:23:25.120 --> 00:23:33.720 So number 30 is PDF tab extract, which is a set of tools for getting tables out of PDF documents, which is pretty cool. 00:23:33.720 --> 00:23:35.720 And data mining on scan documents, pretty sweet. 00:23:35.720 --> 00:23:46.140 There's number 28 is surprise, which is a scikit learn extension for building and analyzing a building a recommender system. 00:23:46.320 --> 00:23:49.360 So you can like say, you might also like this, which is kind of cool. 00:23:49.360 --> 00:23:51.460 Number 27, we won't do all of them. 00:23:51.460 --> 00:23:53.500 That's why I'm skipping number 29. 00:23:53.500 --> 00:24:03.100 Number 27 is eel, which is basically a simple equivalent of the Python's version of an Electron JS system. 00:24:03.100 --> 00:24:03.960 What do you guys think of that? 00:24:03.960 --> 00:24:06.420 How have we not covered that already? 00:24:06.420 --> 00:24:11.960 I think we might have mentioned it because we have been on a, I think we've covered it, but there's two variations. 00:24:11.960 --> 00:24:16.160 And the sort of story that seems to go along with this is like, it's a simple library. 00:24:16.160 --> 00:24:17.800 It's not really like fully. 00:24:17.800 --> 00:24:22.740 There's my understanding that you can build simple apps, but not like full on massive apps. 00:24:22.740 --> 00:24:25.940 But if you could build full on massive apps, I'd be all over this. 00:24:25.940 --> 00:24:26.400 That's awesome. 00:24:26.400 --> 00:24:36.920 Number 25, clairvoyant, a Python program that identifies and monitors historical cues for short, short term stock movement and stuff. 00:24:37.540 --> 00:24:40.480 So I don't do really any stock trading. 00:24:40.480 --> 00:24:43.660 I mean, I put money into mutual funds, so I don't really care that much about it. 00:24:43.660 --> 00:24:51.440 But the reason I bring this up is Python actually is pretty involved in the whole stock trading automation and real time stuff. 00:24:51.440 --> 00:24:58.080 There's actually a really good documentary called The Wall Street Code that goes into all these programmers that are building like AIs and stuff in Python. 00:24:58.080 --> 00:24:59.140 And it's pretty cool. 00:24:59.140 --> 00:25:00.380 So it's free on YouTube. 00:25:00.380 --> 00:25:00.880 Nice. 00:25:00.880 --> 00:25:01.200 Yeah. 00:25:01.200 --> 00:25:03.660 Brian, are you a fan of Mr. Robot or Dan? 00:25:03.660 --> 00:25:04.180 Either you guys? 00:25:04.180 --> 00:25:05.180 Yeah, I was just going to say. 00:25:05.180 --> 00:25:06.180 No? 00:25:06.180 --> 00:25:06.580 No. 00:25:06.580 --> 00:25:07.260 Oh, man. 00:25:07.260 --> 00:25:07.860 Dan? 00:25:07.860 --> 00:25:08.500 I like it. 00:25:08.500 --> 00:25:08.720 Yeah. 00:25:08.720 --> 00:25:09.540 Good show. 00:25:09.540 --> 00:25:11.420 I think it went a little weird in episode two. 00:25:11.420 --> 00:25:12.660 I was sorry, season two. 00:25:12.660 --> 00:25:14.980 But like the first year, I was just like blown away. 00:25:14.980 --> 00:25:24.040 So there's this thing called F Society, which is a hacking tools pack for penetration testing in Python, which of course, Python is very big in the cybersecurity space. 00:25:24.040 --> 00:25:30.560 You might, if you want to like check your own stuff, run some of these tools against your things before someone else does. 00:25:31.200 --> 00:25:32.880 We talked about Kenneth Wright's last time. 00:25:32.880 --> 00:25:36.020 And number 18 was Maya, date time for humans. 00:25:36.020 --> 00:25:37.280 Better exceptions. 00:25:37.280 --> 00:25:38.400 I think we covered that as well. 00:25:38.400 --> 00:25:47.100 16, API star, a really cool, expressive Python 3, 5 based API from Tom Christie. 00:25:47.100 --> 00:25:48.440 Same guy that does Django rest framework. 00:25:48.600 --> 00:25:52.220 But this is like the re-envisioned Python 3 version, which is cool. 00:25:52.220 --> 00:25:55.500 Micro Python, very awesome for little projects. 00:25:55.500 --> 00:25:57.060 spaCy, industrial strength. 00:25:57.060 --> 00:25:59.880 Natural language processor is number six. 00:25:59.880 --> 00:26:02.760 Number two was PyTorch for machine learning. 00:26:02.760 --> 00:26:06.220 That seems to be sort of becoming one of the main machine learning libraries. 00:26:06.400 --> 00:26:10.000 Number one, home assistant for open source home automation. 00:26:10.000 --> 00:26:10.580 Very cool. 00:26:10.580 --> 00:26:16.260 I keep dreaming of like creating some IoT thing with MicroPython and then plugging it into home assistant. 00:26:16.260 --> 00:26:19.560 But I just have to figure out what that thing is going to be. 00:26:19.560 --> 00:26:23.180 It's a solution looking for a problem, right? 00:26:23.180 --> 00:26:25.800 It's a good solution, I think. 00:26:25.800 --> 00:26:27.520 Yeah, yeah, I think so. 00:26:27.520 --> 00:26:31.600 It's a good solution if I could just find a problem to like apply it to. 00:26:31.600 --> 00:26:34.040 Those that I read off there, are those surprising? 00:26:34.040 --> 00:26:35.660 Any of those like super interesting to you guys? 00:26:35.660 --> 00:26:36.920 I'm a huge fan of MicroPython. 00:26:36.920 --> 00:26:39.660 So I just learned a little bit more about it. 00:26:39.660 --> 00:26:46.060 And so it's basically this like super small and lean re-implementation of Python 3, I guess, 00:26:46.060 --> 00:26:51.040 that runs on these like super low power, low computational power microcontrollers. 00:26:51.040 --> 00:26:58.080 And it's, I mean, it's just so cool to be running Python on tiny, tiny machines that have very little RAM. 00:26:58.080 --> 00:27:00.360 And, you know, we're talking kilobytes and stuff. 00:27:00.360 --> 00:27:03.140 And it's just insane that you can program this with Python. 00:27:03.140 --> 00:27:03.920 Yeah, yeah. 00:27:03.920 --> 00:27:04.620 So cool. 00:27:04.720 --> 00:27:08.040 Yeah, and you got one of those little in your goodie bag at PyCon, right? 00:27:08.040 --> 00:27:11.500 They did like a video review of that on YouTube. 00:27:11.500 --> 00:27:14.840 And I was just, you know, all giddy about it, just playing with this thing. 00:27:14.840 --> 00:27:18.300 It just plugs into your USB and you can, you know, start running Python on this thing. 00:27:18.300 --> 00:27:20.300 That's a really good implementation they did. 00:27:20.300 --> 00:27:21.180 Brian, how about you? 00:27:21.260 --> 00:27:23.340 Yeah, I guess I'd have to second that. 00:27:23.340 --> 00:27:24.860 MicroPython is awesome. 00:27:24.860 --> 00:27:28.920 And a bunch of the Adafruit products run, are able to run it. 00:27:28.920 --> 00:27:31.580 And yeah, it's all fun. 00:27:31.580 --> 00:27:35.140 API store is something I've been meaning to try still. 00:27:35.140 --> 00:27:37.420 I haven't done any projects with it. 00:27:37.420 --> 00:27:38.960 But it looks fun. 00:27:39.100 --> 00:27:39.920 Yeah, it definitely looks fun. 00:27:39.920 --> 00:27:40.840 Quite cool. 00:27:40.840 --> 00:27:41.040 All right. 00:27:41.040 --> 00:27:42.960 There's one final thing I want to cover. 00:27:42.960 --> 00:27:48.500 We had the GDPR stuff come out, basically come into effect at the end of last week. 00:27:48.880 --> 00:27:56.100 So just a quick point to an article from our friend Chris Medina at tryexceptpass.org slash article slash GDPR. 00:27:56.100 --> 00:27:58.020 Sort of a take for developers. 00:27:58.020 --> 00:28:04.200 And if you haven't got your stuff all in line yet, please consider doing so for your own good. 00:28:04.200 --> 00:28:06.960 Pythonbytes.fm is all up and ready. 00:28:06.960 --> 00:28:10.980 So yeah, Dan, you probably had to do the same for real Python, right? 00:28:10.980 --> 00:28:15.660 Yeah, some sleepless nights because it's, well, everything is up for interpretation, right? 00:28:15.660 --> 00:28:19.620 So it's kind of hard to, yeah, just to put it into concrete terms. 00:28:19.620 --> 00:28:25.880 But I mean, it's just been nuts, you know, that now that the deadline for that law to go into effect is passed. 00:28:25.880 --> 00:28:27.980 Like we've seen some services shut down. 00:28:27.980 --> 00:28:31.900 I think like Instapaper is a service that I really, I've been using it for a long time. 00:28:31.900 --> 00:28:34.280 And they just shut down in Europe. 00:28:34.280 --> 00:28:36.340 They say it's temporary, but, you know, who knows? 00:28:36.340 --> 00:28:37.020 Yeah, we'll see. 00:28:37.020 --> 00:28:38.400 It's temporary until it's not. 00:28:38.400 --> 00:28:40.220 But yeah, hopefully they get that figured out. 00:28:40.220 --> 00:28:41.080 But yeah, I saw that. 00:28:41.080 --> 00:28:42.960 That was quite the discussion on Hacker News. 00:28:43.520 --> 00:28:47.900 The other thing I wanted to bring up, which I don't know, this is pretty cool to me. 00:28:47.900 --> 00:28:51.080 I deal with an insane amount of large files. 00:28:51.080 --> 00:28:53.440 And I use Dropbox mostly for that. 00:28:53.440 --> 00:29:00.440 Like to give you a sense, like I have the terabyte plan and it's like sometimes gets too full and I have to clean up my Dropbox storage. 00:29:00.440 --> 00:29:03.740 But my hard drive doesn't really want to sync that much stuff. 00:29:03.740 --> 00:29:06.760 Did you guys know that Dropbox released this thing called Smart Sync? 00:29:06.900 --> 00:29:07.220 Yes. 00:29:07.220 --> 00:29:10.780 And I've been wanting to use it, but it installs a kernel module. 00:29:10.780 --> 00:29:14.260 And so I was like, ah. 00:29:14.260 --> 00:29:15.380 Right. 00:29:15.380 --> 00:29:17.780 Because it's got to get into the file driver. 00:29:17.780 --> 00:29:18.020 Yeah. 00:29:18.060 --> 00:29:30.680 So if people have this problem, Dropbox came out with this thing called Smart Sync that will basically give you and your Explorer and your Open Dialogues and Windows or Mac a view which pretends as if the files are there. 00:29:30.680 --> 00:29:36.300 And as soon as you try to interact with them, even from like the command line, they will automatically download if they're not. 00:29:36.300 --> 00:29:41.600 Which is basically lets you sync nothing but what you interact with, which is really amazing. 00:29:41.600 --> 00:29:42.620 It sounds super cool. 00:29:42.620 --> 00:29:49.600 Like I have a lot of trust in the Dropbox engineering team and like if it works that smoothly, I think it's an amazing feature. 00:29:49.600 --> 00:29:52.040 Sort of been hesitant about enabling it. 00:29:52.040 --> 00:29:52.220 All right. 00:29:52.220 --> 00:29:53.680 When you enable it, you tell us how it goes. 00:29:53.680 --> 00:29:57.400 I'll probably try it out. 00:29:57.400 --> 00:29:59.600 I'll give you guys a report eventually. 00:29:59.600 --> 00:30:00.100 Cool. 00:30:00.100 --> 00:30:00.520 All right. 00:30:00.520 --> 00:30:01.400 Well, I think that's it. 00:30:01.400 --> 00:30:03.820 Unless Brian or Dan, you have extra stuff to share with everyone? 00:30:03.820 --> 00:30:04.140 Yeah. 00:30:04.140 --> 00:30:04.700 Right on. 00:30:04.700 --> 00:30:04.980 Well. 00:30:04.980 --> 00:30:05.820 I think I'm all good. 00:30:05.820 --> 00:30:06.100 Yeah. 00:30:06.100 --> 00:30:06.660 Yeah. 00:30:06.660 --> 00:30:07.500 Great to be back. 00:30:07.500 --> 00:30:08.400 Yeah. 00:30:08.400 --> 00:30:09.240 Definitely. 00:30:09.880 --> 00:30:10.860 Brian, thank you so much. 00:30:10.860 --> 00:30:16.540 And Dan, thanks for dropping in and adding some spice to the mix for our whole podcast here. 00:30:16.540 --> 00:30:17.120 Awesome. 00:30:17.120 --> 00:30:17.660 Thanks, guys. 00:30:17.660 --> 00:30:17.980 Yep. 00:30:17.980 --> 00:30:18.480 Bye, everyone. 00:30:18.480 --> 00:30:18.740 Bye. 00:30:18.740 --> 00:30:19.100 Bye. 00:30:19.100 --> 00:30:22.200 Thank you for listening to Python Bytes. 00:30:22.200 --> 00:30:24.760 Follow the show on Twitter via at Python Bytes. 00:30:24.760 --> 00:30:27.640 That's Python Bytes as in B-Y-T-E-S. 00:30:27.640 --> 00:30:31.040 And get the full show notes at Pythonbytes.fm. 00:30:31.040 --> 00:30:35.400 If you have a news item you want featured, just visit Pythonbytes.fm and send it our way. 00:30:35.400 --> 00:30:38.140 We're always on the lookout for sharing something cool. 00:30:38.760 --> 00:30:41.500 On behalf of myself and Brian Okken, this is Michael Kennedy. 00:30:41.500 --> 00:30:45.120 Thank you for listening and sharing this podcast with your friends and colleagues.