WEBVTT 00:00:00.001 --> 00:00:04.920 Hello and welcome to Python Bytes, where we deliver Python news and headlines directly to 00:00:04.920 --> 00:00:11.760 your earbuds. This is episode 128, recorded April 30th, 2019. I'm Michael Kennedy. 00:00:11.760 --> 00:00:12.600 And I'm Brian Okken. 00:00:12.600 --> 00:00:16.280 And this episode is brought to you by DigitalOcean. They're great supporters of the show. 00:00:16.280 --> 00:00:20.460 Please check them out at pythonbytes.fm/digitalocean and get $100 free credit. 00:00:20.460 --> 00:00:22.560 Brian, I am super excited. 00:00:22.560 --> 00:00:23.600 Are you? What about? 00:00:23.600 --> 00:00:26.400 We are on PyCon Eve. 00:00:26.720 --> 00:00:30.440 Yeah, but when is this going to go out, though? I mean... 00:00:30.440 --> 00:00:35.920 I think this is going out before PyCon. At least it'll be out during PyCon, if nothing else. We're 00:00:35.920 --> 00:00:36.360 going to rush. 00:00:36.360 --> 00:00:40.660 Yeah, I'm excited that I don't have to pack my banner thing this time. 00:00:40.660 --> 00:00:44.960 I know. We're going to be at the JetBrains booth, and they're going to have all that stuff set up 00:00:44.960 --> 00:00:50.040 for us. So we can just roll in like a normal attendee with a relatively small amount of gear 00:00:50.040 --> 00:00:50.780 and tow. It'll be great. 00:00:50.780 --> 00:00:55.360 Yeah, and I want people to show up at the 630 at the Thursday night thing, because I'm going to be 00:00:55.360 --> 00:00:57.980 recording at 630 live. So stop by there. 00:00:57.980 --> 00:01:02.120 Yeah, I feel like with the JetBrains stuff and just independent of that, we're going to be doing 00:01:02.120 --> 00:01:07.400 a lot of live recording there for test and code, for Talk Python, and for Python Bytes. And we'll 00:01:07.400 --> 00:01:09.560 try to get the word out about that, but it's going to be a lot of fun. 00:01:09.560 --> 00:01:09.900 Yeah. 00:01:09.900 --> 00:01:14.980 For sure. So let's just jump right in the first one here. I see this one as well within your 00:01:14.980 --> 00:01:15.420 wheelhouse. 00:01:15.420 --> 00:01:21.720 Yeah. I forgot about the order. Yes. There's an article from Adam Johnson called Solving Algorithmic 00:01:21.720 --> 00:01:27.400 Problems in Python with pytest. And yes, pytest is definitely my wheelhouse. I like the highlighting 00:01:27.400 --> 00:01:32.600 of this. Here's the idea. You've got coding challenges, especially algorithmic ones like 00:01:32.600 --> 00:01:39.140 Project Euler or Advent of Code or other. There's lots of coding challenges projects. And doing 00:01:39.140 --> 00:01:45.200 those goes through one example and shows how to translate the project description, the problem 00:01:45.200 --> 00:01:51.380 description and the specification into some quick little tests. And they're like showing 00:01:51.380 --> 00:01:57.920 it how small tests can be. Just testing one aspect of the answer. So the example goes through 00:01:57.920 --> 00:02:02.540 basically, yeah, it's a little bit of a TDD practice thing of coming up with some tests to 00:02:02.540 --> 00:02:07.300 test the test case, going through an exercise, translating all the specification into tests, 00:02:07.300 --> 00:02:11.820 and then just working through it and looking at all the failures, failure cases, especially. 00:02:11.820 --> 00:02:17.200 So one of the, his example was to just create a stub answer, just the function you're trying to 00:02:17.200 --> 00:02:23.600 actually write, just have it return some constant and then build that up. And it's a little bit of a 00:02:23.600 --> 00:02:29.920 TDD practice, but also just practice writing tests to do these sort of projects. And it's a short article 00:02:29.920 --> 00:02:30.840 and I really liked it. 00:02:30.840 --> 00:02:34.980 Yeah. It's a cool way to explore solving some problems with the whole Project Euler thing. 00:02:35.200 --> 00:02:41.840 And it's also a cool way to get some experience working with pytest. And I feel like these types 00:02:41.840 --> 00:02:48.640 of problems are pretty good entry level pytest type problems. It's not, well, we have the website and we 00:02:48.640 --> 00:02:52.840 want to make sure the user can register and like, okay, well, how do I mock out the database call and 00:02:52.840 --> 00:02:57.540 then like stub out the email service? You know, like all that complicated stuff, right? Where here, 00:02:57.540 --> 00:03:03.720 it's like a pretty constrained problem, right? Like find the minimum path, you know, amongst these bridges 00:03:03.720 --> 00:03:07.240 or, you know, whatever the problems, like these sort of mathematical algorithmic ones. 00:03:07.240 --> 00:03:12.500 Yeah. And his example is like super easy. It's just returning the minimum value in a list as long 00:03:12.500 --> 00:03:17.280 as it's positive. Nice. And it's easy to get your head around. And actually I love doing little 00:03:17.280 --> 00:03:23.120 practice things like that. So cool. Yeah, I do too. And I'm a fan of Project Euler. So quite cool. 00:03:23.120 --> 00:03:28.800 Now this next one that I have, I feel like maybe we haven't really discussed it enough, 00:03:28.800 --> 00:03:33.480 but it has to do with Python packaging. Do you think? Oh yeah. We haven't covered packaging much. 00:03:33.480 --> 00:03:38.040 No. So it's good that it's finally coming up on the show. Yeah. This one is interesting because it's 00:03:38.040 --> 00:03:44.760 kind of like a, a meta packaging tool. So we've talked about the pyproject.toml. We've talked about 00:03:44.760 --> 00:03:51.260 the pipfile.lockfile, requirements.txt, poetry, all these things, right? Well, this one that I found 00:03:51.260 --> 00:03:58.460 or was actually sent to us by Dr. Igleby on Twitter, it's called DepHell as in dependency hell. 00:03:59.100 --> 00:04:03.360 So it just comes out and it says it, right? Like there's flames on the logo. Come on. 00:04:03.360 --> 00:04:09.800 So the idea is that it will let you work in these different modes and even automatically translate 00:04:09.800 --> 00:04:16.900 between them. So one of them is like, Hey, we have a setup.py for managing this particular project. 00:04:17.160 --> 00:04:24.120 I would rather have a pyproject.toml file that expresses the same thing. And you just run a 00:04:24.120 --> 00:04:32.340 command line against that project and it'll generate the pyproject.toml based on the current setup in your 00:04:32.340 --> 00:04:36.880 project. Oh, nice. Yeah. So if you want to say, switch it to poetry, you can run a command. It'll 00:04:36.880 --> 00:04:41.800 switch to poetry. If you want to switch it over to pipenv, fine. You run that and it'll do it. So 00:04:41.800 --> 00:04:46.660 that's one of the things it does. It's pretty cool in that it'll let you use all these different 00:04:46.660 --> 00:04:50.840 things. It doesn't really try to replace them, but it more tries to like tie them together, 00:04:50.840 --> 00:04:56.520 right? Like I've grabbed a project, but maybe it's not in my, the tooling that I like. It's pretty easy 00:04:56.520 --> 00:05:01.800 to extend. It's really quite nice. I like this ability to translate between them. It also has some 00:05:01.800 --> 00:05:07.820 of the features of like pipenv. So it'll create like a shell. It'll install your command line 00:05:07.820 --> 00:05:13.800 utilities into their own isolated virtual environment. Like pytest could be in its own 00:05:13.800 --> 00:05:18.260 environment that has nothing to do with your project, but is available to run against your 00:05:18.260 --> 00:05:24.500 project. Things like that. Yeah. Nice. Yeah. So yeah, not too much else to say, I guess it's based on 00:05:24.500 --> 00:05:31.080 ASyncIO. So that means it only supports modern Python. That's pretty awesome. So it's super fast. All of its 00:05:31.080 --> 00:05:36.660 network calls and stuff are made asynchronously and yeah, it's pretty good. I think something like this 00:05:36.660 --> 00:05:42.240 would be great for like a project that has, has a maintainer that doesn't care about the pen for 00:05:42.240 --> 00:05:47.800 something is fine with requirements or whatever they're using, but there's a couple maintainers that 00:05:47.800 --> 00:05:53.120 really like pipenv and want to want to have the pip file around and the lock file. And yeah, that's 00:05:53.120 --> 00:05:58.220 interesting. Like you could have one of them that's the source of truth and then use this tool to generate 00:05:58.220 --> 00:06:02.760 the others if you'd rather work that way. Right. Yeah. Yeah. You could even do this part of a 00:06:02.760 --> 00:06:08.080 automated build, right? Delete the pip file and then recreate it as part of the build and then 00:06:08.080 --> 00:06:12.660 check that back in. Who knows? Yeah. Okay. Cool. Yeah. Yeah. Pretty cool. This next one that you 00:06:12.660 --> 00:06:17.960 found is a bit of a rant, huh? Yes, definitely. Mike Croucher, which, I'm not sure what he does. 00:06:17.960 --> 00:06:22.660 I think he works. He writes a lot of great articles and come across his name every once in a while. So 00:06:22.660 --> 00:06:29.260 thanks Mike. This rant is a, he even says it in the name, Python rant from Foo import star is bad, 00:06:29.260 --> 00:06:36.280 but basically just import star is bad. And I thought this was just done that nobody did this anymore, 00:06:36.280 --> 00:06:43.640 but I actually see quite a bit of code that still has this in it. And I was actually in looking for 00:06:43.640 --> 00:06:49.800 a different blog posts. There's some blog posts that have great advice in Python, but the example code has 00:06:49.800 --> 00:06:56.720 import star. And I'm not going to point people to that because it's just a bad practice. And his 00:06:56.720 --> 00:07:03.620 example is, for instance, is, the square root function SQRT. If you just have like result 00:07:03.620 --> 00:07:09.860 equals square root of minus one, what does that mean? You don't know what it means because you don't know 00:07:09.860 --> 00:07:15.780 where that came from. And there's some really confusing examples that he's showing how it may have 00:07:15.780 --> 00:07:21.820 been from the math library. It may have been from numpy or cmath or scipy or simpy. All of them have 00:07:21.820 --> 00:07:28.840 the same function name and we like namespaces, but when you use import star, you throw away the namespace 00:07:28.840 --> 00:07:33.620 ability. You just import everything into your current namespace. So don't do that. 00:07:33.620 --> 00:07:39.260 Yeah. I like the hat tip to a full metal jacket. This is my rant on import star. There are many like 00:07:39.260 --> 00:07:45.060 it, but this one is mine. This one is my own. You know, I've, I totally, like this as well. 00:07:45.060 --> 00:07:51.180 I'm a big fan of having like super explicit namespaces to like really tell where something 00:07:51.180 --> 00:07:57.540 comes from. In fact, I typically try to shy away from, from thing, import something. 00:07:57.680 --> 00:08:03.840 Yeah. Not just import star, just even that it's more like import this module than module dot 00:08:03.840 --> 00:08:10.260 function, module dot class. You know, sometimes if it's like deeply nested, I might do import thing as 00:08:10.260 --> 00:08:14.940 like just the last part of that name or, but you know, something to give you a hint, like where the 00:08:14.940 --> 00:08:15.800 heck did this come from? 00:08:15.800 --> 00:08:21.460 Right. And like, for instance, the, numpy is the convention is to import numpy as np. 00:08:21.460 --> 00:08:23.080 Because numpy is really long to type. 00:08:24.980 --> 00:08:30.720 I know. However, you're using a ton of it. And so, yeah, there, there are conventions. And if you 00:08:30.720 --> 00:08:33.200 can notice the conventions, you follow those. 00:08:33.200 --> 00:08:33.820 Yeah, absolutely. 00:08:33.820 --> 00:08:38.400 I'm with it too. So sometimes when I'm refactoring some code or trying to understand it, 00:08:38.400 --> 00:08:44.400 it's frustrating when somebody has a bunch of from library import, like five different functions. 00:08:44.400 --> 00:08:49.000 Yeah. And you know, it's, it's not terrible if you've got something like visuals to do your code, 00:08:49.000 --> 00:08:53.520 or you've got PyCharm and you can like go to definition or you hover over it and it'll say more. 00:08:53.900 --> 00:08:58.360 But if you see it in a blog post or you see it printed or you see it in like a gist or 00:08:58.360 --> 00:09:02.580 somewhere that doesn't have like understanding of the environment, then you're like, okay, 00:09:02.580 --> 00:09:05.140 well, what is that? Right? Like, so just, you know, think about it. 00:09:05.140 --> 00:09:08.680 Yeah. I actually kind of wish they deprecated, but that's probably never going to happen. 00:09:08.680 --> 00:09:13.420 Yeah, probably not. I talked about digitalization at the top. Let me just tell you about something 00:09:13.420 --> 00:09:16.920 that's new and cool. Brian, are you familiar with GitHub actions? 00:09:16.920 --> 00:09:19.260 I just heard a little bit about them. 00:09:19.260 --> 00:09:23.720 Yeah. Same. I haven't really done anything with them, but it's basically GitHub actions are like a 00:09:23.720 --> 00:09:30.280 series of workflows that can be triggered when you do like a push to a repository, you create a release or 00:09:30.280 --> 00:09:36.180 you create an issue, right? And it runs a series of actions that then, you know, can kick off CI or do 00:09:36.180 --> 00:09:43.040 other sorts of tests. Well, digital ocean has come out with GitHub actions for digital ocean. So you can do 00:09:43.040 --> 00:09:50.500 really cool things like I would like to upgrade my Kubernetes cluster anytime I push to the release 00:09:50.500 --> 00:09:56.480 branch or the master branch and my GitHub repo and just bake that straight into GitHub, right? Just the 00:09:56.480 --> 00:10:01.300 fact of you doing a commit or like, you know, the integration test passing or whatever, you know, 00:10:01.300 --> 00:10:04.680 whatever you want to do with the GitHub actions, you can set that up. So there's special GitHub actions 00:10:04.680 --> 00:10:10.380 for digital ocean and yeah, check them out. Really cool stuff. They have on their blog posts, 00:10:10.380 --> 00:10:15.540 they have something about working with the Kubernetes service there and then using the 00:10:15.540 --> 00:10:19.640 GitHub actions to sort of keep it always up to date. So check them out at pythonbytes.fm slash 00:10:19.640 --> 00:10:24.360 digital ocean, get a hundred dollars free credit for new users. And I feel like GitHub actions are 00:10:24.360 --> 00:10:27.820 something I just want to learn in general. How about you? Definitely. Yeah. It seems like something 00:10:27.820 --> 00:10:32.920 that could help out with workflows. Yeah, absolutely. Cool. Well, this next one that I want to talk 00:10:32.920 --> 00:10:38.020 about is not super new, but I don't know how we've gone this long really without talking about it. 00:10:38.380 --> 00:10:45.240 So Dask. So Dask is a way to natively scale Python. And when I first thought about it, 00:10:45.240 --> 00:10:49.520 I first heard about it, I thought, okay, well, Dask is like this thing that takes data science 00:10:49.520 --> 00:10:54.820 workloads and runs among clusters. And the reason I didn't get super excited is like, well, I don't do 00:10:54.820 --> 00:10:59.560 that much data science and I don't have enough that require clusters to run. Now they're usually 00:10:59.560 --> 00:11:04.720 pretty small little graphy things or something if I'm doing any data science. However, I recently had 00:11:04.720 --> 00:11:10.200 Matthew Rocklin, who's behind Dask on Talk Python in episode 207. And we talked a lot about it and 00:11:10.200 --> 00:11:15.400 there's actually some really cool stuff. And I think more applicability to more people than I first 00:11:15.400 --> 00:11:23.400 realized. So basically the idea is like Dask will take the NumPy, SciPy sort of stack and scale it out. 00:11:23.520 --> 00:11:27.560 All right. So you have NumPy, you have Pandas, you have side kit, learn code, all that. 00:11:27.560 --> 00:11:34.960 So there's Dask versions of like NumPy arrays and Panda data frames. So there's like Dask data frames. 00:11:34.960 --> 00:11:39.740 And what you can do is just work with those basically the same API, but instead of working 00:11:39.740 --> 00:11:45.060 just locally, it will work with them on the cluster. So suppose you have like three terabytes of data you 00:11:45.060 --> 00:11:50.240 need to process and it can't fit into RAM. So you can't just load it up into a NumPy array or a Panda data 00:11:50.240 --> 00:11:55.560 frame, but you can tell Dask to process and it'll share it across the cluster and do all the work and 00:11:55.560 --> 00:11:59.340 the computation and the cross server communication that you need. Isn't that cool? 00:11:59.340 --> 00:11:59.900 That is neat. 00:11:59.900 --> 00:12:03.600 So it sounds really neat. And that workload, like to me, doesn't really help that much because I don't 00:12:03.600 --> 00:12:07.640 have to do a whole lot with that. I know some people that'll be super valuable for, but you can 00:12:07.640 --> 00:12:13.400 also just run Dask locally on your machine and it'll create like a little mini cluster that runs locally 00:12:13.400 --> 00:12:18.680 and it'll use like threads and processes and whatnot. And it'll even let you process more 00:12:18.680 --> 00:12:23.440 data locally than will fit into RAM and do like, you know, lazy loading and all sorts of interesting 00:12:23.440 --> 00:12:29.620 stuff there. So pretty cool. It even lets you escape the GIL. So you get better like parallels 00:12:29.620 --> 00:12:35.460 and even on your own computer and it runs arbitrary Python code, not just NumPy and Pandas, even though 00:12:35.460 --> 00:12:36.760 that is main, that's its main use. 00:12:36.760 --> 00:12:38.140 That's actually pretty darn cool. 00:12:38.140 --> 00:12:41.380 Yeah, that's what I thought. So I decided to make it at one of our topics for today. 00:12:41.380 --> 00:12:45.060 Yeah. The large file stuff, I definitely hit that occasionally. 00:12:45.060 --> 00:12:50.580 Yeah. And I don't really want to think about it just for special cases, but being able to use 00:12:50.580 --> 00:12:53.860 running it under Dask might just speed it up. So that's cool. 00:12:53.860 --> 00:12:57.880 Yeah. You basically just create like a Dask client or something and it'll like locally create a little 00:12:57.880 --> 00:13:00.080 server cluster that'll process it all. It's pretty cool. 00:13:00.080 --> 00:13:00.420 Nice. 00:13:00.420 --> 00:13:04.400 Or run on a thread pool or something like that. Last thing I thought that was kind of interesting, 00:13:04.400 --> 00:13:08.820 maybe do this for me. Click on the Dask thing to open it up and just go to the bottom. 00:13:08.820 --> 00:13:10.460 Notice the supported by there? 00:13:10.720 --> 00:13:11.000 Wow. 00:13:11.000 --> 00:13:17.680 Isn't that cool? Supported by the NSF, supported by NVIDIA, supported by DARPA, Anaconda Inc., 00:13:17.680 --> 00:13:22.780 things like that. So here's a really interesting example of not just a project that's cool, 00:13:22.780 --> 00:13:28.180 but a project, an open source project that's like really supported by, you know, some neat 00:13:28.180 --> 00:13:33.200 companies or organizations. So anyway, I just kind of thought that was a cool thing that jumped 00:13:33.200 --> 00:13:37.160 at me as well as like the kind of the proper support this project's getting. 00:13:37.340 --> 00:13:39.020 Oh, I definitely need to check this out. Yeah. 00:13:39.020 --> 00:13:39.260 Yeah. 00:13:39.260 --> 00:13:39.440 Neat. 00:13:39.440 --> 00:13:42.420 Yeah. Pretty cool. It might tie in with graphing. 00:13:42.420 --> 00:13:48.220 Yeah. Actually, there's some pretty graphs on the Dask website. Yeah. But if you don't want to, 00:13:48.220 --> 00:13:53.440 I don't know how they're using it, but it's possible to do animations even within Matplotlib. 00:13:53.440 --> 00:13:53.880 Nice. 00:13:54.120 --> 00:13:59.600 And I'm highlighting an article by Parul Pandey, sorry if I'm getting that name wrong, 00:13:59.600 --> 00:14:04.300 called Animations in Matplotlib. I thought we'd already covered this, but we haven't yet. 00:14:04.300 --> 00:14:09.260 Just the fact that you can do animations. And I guess I hadn't realized when I first started 00:14:09.260 --> 00:14:15.420 working with plots in Python that Matplotlib did it. And you can do some, lots of different ways you 00:14:15.420 --> 00:14:23.980 can simulate or do animations within Matplotlib. And the top picture is just, is this, of the article, 00:14:23.980 --> 00:14:29.780 is this raindrop simulation. And I could just sit and watch this for like an hour. 00:14:29.780 --> 00:14:34.880 I was thinking the same thing. It's like the equivalent of white noise, but visual. It's just 00:14:34.880 --> 00:14:39.280 like, yeah, it really does look like raindrops hitting, you know, a little pond or a puddle 00:14:39.280 --> 00:14:40.160 or something. It's quite cool. 00:14:40.160 --> 00:14:44.960 Right. So it has these random circles that appear dark. And then as they get bigger, 00:14:44.960 --> 00:14:49.320 they get lighter and then they eventually disappear. And that just happens all over the 00:14:49.320 --> 00:14:56.920 page. And it's pretty neat. But that's all using Matplotlib animations. And there is a link to the 00:14:56.920 --> 00:15:01.840 source code for that. But the tutorial goes through and talks about, there's a couple different ways to 00:15:01.840 --> 00:15:08.180 do animations. And the author prefers funk animation and has a tutorial for animating a sine wave. 00:15:08.760 --> 00:15:13.820 The confusing part of that, to me, was that the x-axis doesn't really mean anything at that point. 00:15:13.820 --> 00:15:15.960 Because the sine wave keeps moving. 00:15:15.960 --> 00:15:16.280 Right. 00:15:16.280 --> 00:15:20.240 But it's a pretty small, concise example of how animations work. 00:15:20.240 --> 00:15:24.580 Yeah, it's super easy. So basically, you create a figure, set it up in Matplotlib. 00:15:24.580 --> 00:15:29.100 You create an initialize function that sets the data however it's going to be. And then you have an 00:15:29.100 --> 00:15:34.480 animate function that's given a frame and it just computes the change and, you know, sets it again. 00:15:34.480 --> 00:15:35.500 Yeah, it's quite nice. 00:15:35.620 --> 00:15:41.120 Yeah, just a few lines of code. She goes on to, I think it's a she, goes on to talk about live 00:15:41.120 --> 00:15:47.700 updates. So if you've got a graph or a plot that is using data that is changing, you can live update 00:15:47.700 --> 00:15:51.980 those. Animating, turning a 3D plot. And that's really pretty. 00:15:51.980 --> 00:15:53.680 Yeah, yeah. There's a bunch of cool graphs here. 00:15:53.680 --> 00:15:54.000 Yeah. 00:15:54.100 --> 00:15:56.960 Yeah, I could see if I had stuff to graph, I would be all over this. 00:15:56.960 --> 00:16:01.220 I guess there's a third-party package called celluloid that makes some of the animations 00:16:01.220 --> 00:16:04.840 a little bit more concise. So she gives some examples of that too. 00:16:04.840 --> 00:16:05.980 Cool. Yeah, that's a good one. 00:16:05.980 --> 00:16:14.060 All right. The last one here for us is pep554, multiple interpreters or sub-interpreters in the 00:16:14.060 --> 00:16:14.560 standard lib. 00:16:14.560 --> 00:16:15.100 Oh, wow. 00:16:15.100 --> 00:16:20.740 So this is kind of meta and interesting and possible. So this, I don't believe is approved 00:16:20.740 --> 00:16:27.900 yet. This is potentially, possibly coming. So I don't think it's out. Yeah, proposed in Python 3.9. 00:16:27.900 --> 00:16:32.020 And we'll just see if it's, yeah, I don't see whether it's approved or not. But, you know, 00:16:32.020 --> 00:16:38.980 maybe, probably in 3.9 coming is this pep554, which allows for multiple sub-interpreters in the 00:16:38.980 --> 00:16:45.080 standard lib. So apparently CPython already had this capability to have multiple sub-interpreters 00:16:45.080 --> 00:16:50.760 run, but it was never exposed. Right? So deep, deep down, there's some module you could use. And 00:16:50.760 --> 00:16:52.980 here's like a public API on top of that. 00:16:52.980 --> 00:16:53.260 Okay. 00:16:53.260 --> 00:16:59.040 So why do you care about it? Well, it says the proposal introduces the standard lib interpreters 00:16:59.040 --> 00:17:06.160 module, like import interpreters. And currently it's provisional. And it basically exposes this 00:17:06.160 --> 00:17:11.240 core functionality as sub-interpreters already provided by the C API along with new functionality. 00:17:11.240 --> 00:17:16.220 And here's the most important part for sharing data between interpreters. So the idea is you're 00:17:16.220 --> 00:17:21.180 going to set up some kind of channel, which is like a queue or a name pipe or something like that to pass 00:17:21.180 --> 00:17:26.360 data back. Like I can't take an object I've created in one part of my program and share it with one of 00:17:26.360 --> 00:17:31.260 these sub-interpreters. I've got to like JSON serialize it or pickle it and then bring it back or like 00:17:31.260 --> 00:17:36.140 there's no data sharing, which is really interesting for isolation. So the main use case of this, 00:17:36.140 --> 00:17:41.740 are well, one running code in isolation. Like if you want to work within your process and you don't 00:17:41.740 --> 00:17:45.920 want to kick off another process, say with multi-processing or something, you can still 00:17:45.920 --> 00:17:51.920 run code that you don't necessarily trust with some restrictions here because it won't have access 00:17:51.920 --> 00:17:56.740 to your memory structures or anything like that. It'll just be like a little isolated Python, 00:17:56.740 --> 00:17:59.700 but you don't have to result to multi-processing. 00:17:59.700 --> 00:18:00.300 Oh, that's cool. 00:18:00.300 --> 00:18:04.420 So that's kind of cool. Maybe plugin systems or something like that, or maybe even incompatible 00:18:04.420 --> 00:18:10.020 versions of modules. Like maybe, you know, I run into this with doc opt all the time for 00:18:10.020 --> 00:18:14.200 some reason, like MailChimp will only use this version, but something else requires another 00:18:14.200 --> 00:18:19.140 version. Like one's less than something and some other has to be greater than that. You know what I 00:18:19.140 --> 00:18:24.900 mean? So maybe you could run like that part of the code in one of these sub-interpreters and have it run 00:18:24.900 --> 00:18:34.400 on a different version. I'm not sure that might take a little bit of juggling, but another one that the one that stood out to me, I think is pretty interesting here is the guild, the global interpreter law. 00:18:34.400 --> 00:18:41.680 is there because, you know, basically the way people perceive it is, is it blocks parallelism. 00:18:41.680 --> 00:18:47.180 But the reason it blocks parallelism is around memory management of shared objects, right? So any PI object 00:18:47.180 --> 00:18:53.340 you have, it has to have reference counting and whatnot to keep its memory managed. Well, these sub-interpreters 00:18:53.340 --> 00:18:59.060 don't share objects, so they don't share the gill, which means you could have like true computational 00:18:59.060 --> 00:19:14.340 parallelism in your code. So they all have like their own GIL. Effectively, yes. Yeah, exactly. So it's still the gill, but if you have a bunch of them, then it doesn't really matter. And you don't have the overhead of multiple processes or passing data from multiple processes or all that. 00:19:14.340 --> 00:19:20.180 The case that I'm thinking about is people that have tried to write their own little IDE or even a big IDE 00:19:20.180 --> 00:19:21.680 in Python 00:19:21.680 --> 00:19:25.260 to run Python. You've got this issue that you've 00:19:25.260 --> 00:19:27.700 still only have one gill, so you've got to do 00:19:27.700 --> 00:19:30.760 launch another thread, you have to have another task or something. 00:19:31.200 --> 00:19:34.040 And this would allow something like that to be easier. 00:19:34.040 --> 00:19:37.280 Yeah, so I don't actually, yeah, I agree. I don't know what actually would come out of this, 00:19:37.280 --> 00:19:39.940 but it looks like it has some interesting potential. 00:19:39.940 --> 00:19:44.040 And it's also interesting that it basically just formalizes what was already there. 00:19:44.040 --> 00:19:45.060 So that's pretty cool, too. 00:19:45.060 --> 00:19:45.480 Yeah. 00:19:45.480 --> 00:19:48.200 Awesome. All right. Well, that's it for our main topics. 00:19:48.200 --> 00:19:50.320 You got any extra stuff you want to throw out there? 00:19:50.320 --> 00:19:52.500 Other than I'm just super excited about PyCon. 00:19:52.500 --> 00:19:54.340 Yes, it's PyCon Eve. I'm so excited. 00:19:54.340 --> 00:19:58.520 It's going to be good. I'm looking forward to seeing you and everyone in Cleveland. 00:19:58.520 --> 00:20:00.920 When are we going to be around? Do you remember our times? 00:20:01.040 --> 00:20:03.280 Middle of the day. 00:20:03.280 --> 00:20:04.380 Yeah. 00:20:04.380 --> 00:20:07.500 After lunch. So come try to find us. 00:20:07.500 --> 00:20:11.380 Yeah, we won't be at the booth all the time. We're going to be doing other events like open 00:20:11.380 --> 00:20:15.500 spaces and live recordings and other places and maybe even attend to talk. Who knows? 00:20:15.500 --> 00:20:20.020 The times that we will be there, it should be posted on the booth. So there'll be at least 00:20:20.020 --> 00:20:24.000 three hours each day that we're doing something interesting there that you can come by and see us. 00:20:24.000 --> 00:20:25.100 Yep. I'm getting stickers. 00:20:25.100 --> 00:20:27.040 And stickers. Definitely find us at PyCon. 00:20:27.040 --> 00:20:29.060 How about you? You've got some big news. 00:20:29.060 --> 00:20:30.320 Yeah, I got some big news. 00:20:30.880 --> 00:20:38.400 Big news is my iOS app is finally out after negotiating, let's call it, with the App Store folks 00:20:38.400 --> 00:20:44.020 who were better than Google Play, but still it was quite the back and forth to get everything right. 00:20:44.020 --> 00:20:47.240 So finally, the Talk Python training iOS app is out. 00:20:47.340 --> 00:20:55.220 Check it out at training.talkpython.fm/apps. If you install it, log in, you can get two free courses in addition to the ones you might already have. 00:20:55.220 --> 00:20:55.960 So that's pretty cool. 00:20:55.960 --> 00:20:57.700 Yep. I installed it this morning. 00:20:57.700 --> 00:20:59.180 You did? You're already on top of it? 00:20:59.180 --> 00:21:00.740 Yeah. Yeah. It looks great. 00:21:00.740 --> 00:21:02.400 Right on. Thanks. That's very cool. 00:21:02.800 --> 00:21:09.600 And then lastly, you know, like I've said, our listeners are awesome. Anytime we say, here's something that's kind of unique, they're like, and the five other amazing ones. 00:21:10.320 --> 00:21:20.520 So here's one called Blessings. We talked about Bullet, and we talked about Cooked Input, and Blessings is kind of in that realm of making terminal input nicer. 00:21:20.840 --> 00:21:29.460 And this is also output. It's not exactly the same, but Blessings lets you do things like bold your terminal output and move the cursor around and do all sorts of cool stuff. 00:21:29.460 --> 00:21:35.400 So this is from Eric Rose, and Preycin Daniel sent this over and said, hey, you should check this out in addition to the ones you're talking about. 00:21:35.400 --> 00:21:36.840 So here it is. It looks pretty cool. 00:21:36.840 --> 00:21:39.980 Ooh, I have the exact use case for this in mind. So yay. 00:21:39.980 --> 00:21:41.000 Nice. What are you going to do with it? 00:21:41.000 --> 00:21:45.480 I want to do, like I just got finished with reading the TDD by example. 00:21:45.480 --> 00:21:48.900 Yeah, I know. You would have thought I would have learned that beforehand. 00:21:49.500 --> 00:21:57.240 But yeah, I finally read it. And one of the things is a to-do list that is bold for stuff you're working on and like not. 00:21:57.240 --> 00:21:58.320 Nice. Yeah. 00:21:58.320 --> 00:21:59.680 Anyway, he uses that. 00:21:59.680 --> 00:22:04.780 Super cool. Yeah, there it is. Awesome. All right. We have a joke coming in from Topher Chung. 00:22:04.780 --> 00:22:06.480 Do you want to do it or should I do it? 00:22:06.480 --> 00:22:07.220 Oh, you do it. 00:22:07.220 --> 00:22:09.560 All right. Knock, knock. Race condition. 00:22:09.560 --> 00:22:10.380 Who's there? 00:22:10.380 --> 00:22:16.020 Knock, knock. Race condition. Who's there? 00:22:16.020 --> 00:22:16.700 Oh, perfect. 00:22:16.700 --> 00:22:18.680 Man, these never get old. 00:22:18.860 --> 00:22:19.860 We can do... 00:22:19.860 --> 00:22:29.780 I am starting to notice that the pie joke well is starting to run a little dry. We've been emptying it a lot. So people have to start sending in their jokes. That was a good one. Thank you, Topher. 00:22:29.780 --> 00:22:30.620 Yeah, thanks. 00:22:30.620 --> 00:22:33.660 All right. Well, Brian, we shall reconvene in Cleveland. 00:22:33.660 --> 00:22:35.320 Yeah, talk to you there. 00:22:35.320 --> 00:22:36.700 All right. See you, everyone there. See you, Brian. 00:22:36.700 --> 00:22:36.960 Bye. 00:22:37.100 --> 00:22:38.820 Thank you for listening to Python Bytes. 00:22:38.820 --> 00:23:00.900 Follow the show on Twitter via at Python Bytes. That's Python Bytes as in B-Y-T-E-S. And get the full show notes at pythonbytes.fm. If you have a news item you want featured, just visit pythonbytes.fm and send it our way. We're always on the lookout for sharing something cool. On behalf of myself and Brian Okken, this is Michael Kennedy. Thank you for listening and sharing this podcast with your friends and colleagues.