WEBVTT 00:00:00.001 --> 00:00:05.000 Hello and welcome to Python Bytes, where we deliver Python news and headlines directly to your earbuds. 00:00:05.000 --> 00:00:09.800 This is episode 83, recorded June 20th, 2018. I'm Michael Kennedy. 00:00:09.800 --> 00:00:10.540 And I'm Brian Okken. 00:00:10.540 --> 00:00:12.000 And Brian, we have a special guest, don't we? 00:00:12.000 --> 00:00:12.600 Yes, we do. 00:00:12.600 --> 00:00:17.940 Yeah, so Chris Medina is here to join in the fun and share his perspective on things. 00:00:17.940 --> 00:00:18.820 Hey, Chris, welcome to the show. 00:00:18.820 --> 00:00:20.380 Hey, guys, how's it going? Good to be here. 00:00:20.380 --> 00:00:21.440 Yeah, it's good to have you. 00:00:21.440 --> 00:00:23.540 And I also want to say thank you to DigitalOcean. 00:00:23.540 --> 00:00:27.780 They are a major, major sponsor of the show, and they're sponsoring this one as well. 00:00:27.780 --> 00:00:32.120 I'll tell you more about them, but the short version is pythonbytes.fm/DigitalOcean. 00:00:32.120 --> 00:00:34.100 Get $100 credit for new users. 00:00:34.100 --> 00:00:39.080 Brian, speaking of new users, people learning Python, they might want to set up a server at some point. 00:00:39.080 --> 00:00:40.260 Set up a server? 00:00:40.260 --> 00:00:45.060 Well, you know, eventually, they'll have a website or something, right, once they learn to code. 00:00:45.060 --> 00:00:47.900 But you've got a really nice way for them to get started. 00:00:47.900 --> 00:00:55.140 I've always been reluctant to try to look or play with some of these beginning code editors, 00:00:55.140 --> 00:00:59.100 because part of learning how to code is learning an editor. 00:00:59.100 --> 00:01:03.200 But I'm kind of warming to the idea of some of these specialized editors. 00:01:03.200 --> 00:01:07.560 And there's one that I wasn't familiar with, which is Mu. 00:01:07.560 --> 00:01:09.180 I think it's Mu or Mu. 00:01:09.180 --> 00:01:09.840 I don't know. 00:01:09.840 --> 00:01:10.380 Emu. 00:01:10.380 --> 00:01:11.560 Code with Mu. 00:01:11.560 --> 00:01:14.000 It's got a whole bunch of people on board. 00:01:14.000 --> 00:01:15.140 If I go to the... 00:01:15.140 --> 00:01:19.680 I can't remember where it is, but there's a bunch of people working on this. 00:01:19.680 --> 00:01:23.200 And it's kind of a neat little editor that has... 00:01:23.200 --> 00:01:24.340 I was playing with it this morning. 00:01:24.340 --> 00:01:27.140 And it has some... 00:01:27.140 --> 00:01:29.580 You just open it up, and it has built-in right off the bat. 00:01:29.580 --> 00:01:36.260 It asks you if you're going to do it for Python 3, or if you're targeting, like, an Adafruit chip or a micro bit. 00:01:36.580 --> 00:01:39.580 So it has built-in targeting of those things, like, right away. 00:01:39.580 --> 00:01:41.140 And there's, like... 00:01:41.140 --> 00:01:50.740 Along the top, there's some icons for loading and saving files, running it, debugging it, popping up the REPL, interacting with the plotter. 00:01:51.140 --> 00:01:52.020 And then there's a... 00:01:52.020 --> 00:01:57.000 Even there's a theme button, so you can jump back and forth between dark theme and light theme. 00:01:57.000 --> 00:02:00.820 And it even has, like, a linter built-in where you can check things. 00:02:00.820 --> 00:02:02.280 And it's all... 00:02:02.280 --> 00:02:07.220 Like, you don't have to memorize any key sequences, or there's not really any menus around. 00:02:07.220 --> 00:02:09.260 It just is all up there. 00:02:09.260 --> 00:02:13.420 And I think this would actually be great for teaching people how to code. 00:02:13.420 --> 00:02:17.360 So I'm going to start using it for, like, demos and stuff. 00:02:17.360 --> 00:02:18.240 It's pretty cool, yeah. 00:02:18.320 --> 00:02:25.900 So as you type, basically, it pulls up both the completion for the arguments that go to a method or something, 00:02:25.900 --> 00:02:28.780 but also the documentation, like, while you're typing. 00:02:28.780 --> 00:02:31.520 So, you know, you might get annoyed with that if you know what you're doing. 00:02:31.520 --> 00:02:35.760 But if you're new, it's really cool to show you, like, hey, you can call these various things. 00:02:35.760 --> 00:02:37.100 And here's the arguments. 00:02:37.100 --> 00:02:38.040 Here's what it means. 00:02:38.040 --> 00:02:39.520 And it even has a debug. 00:02:39.520 --> 00:02:40.060 It's pretty cool. 00:02:40.060 --> 00:02:41.380 So it's a separate app? 00:02:41.380 --> 00:02:43.340 Yeah, it's a separate app. 00:02:43.340 --> 00:02:44.640 But you can... 00:02:44.640 --> 00:02:46.020 There's an installer available. 00:02:46.320 --> 00:02:47.500 So you can just... 00:02:47.500 --> 00:02:53.220 You don't even have to tell people about pip right away, because you can just install it with an installer. 00:02:53.220 --> 00:02:56.740 But you can install it with pip, because it's just a Python thing. 00:02:56.740 --> 00:02:58.240 I think it's a Qt application. 00:02:58.240 --> 00:02:59.540 I've been corrected. 00:02:59.540 --> 00:03:00.940 It's a Qt application. 00:03:00.940 --> 00:03:02.640 Oh, that's really cool. 00:03:02.640 --> 00:03:03.320 It's cute. 00:03:03.320 --> 00:03:03.720 Okay. 00:03:03.720 --> 00:03:05.300 Yeah, I installed it with pip. 00:03:05.300 --> 00:03:12.400 And then one of the things that it has in the installation instructions is instructions on how to use... 00:03:12.400 --> 00:03:17.300 So when you install it with pip, you get, like, a command line invocation to invoke it. 00:03:17.300 --> 00:03:23.180 But it recommends using another package called shortcut, which you just... 00:03:23.180 --> 00:03:27.200 If you pip install shortcut, you get shortcut moo editor, for instance. 00:03:27.200 --> 00:03:28.200 And it'll create... 00:03:28.200 --> 00:03:28.200 And it'll create... 00:03:28.200 --> 00:03:31.200 On my Mac, it created a... 00:03:31.200 --> 00:03:36.360 It just went ahead and created a shortcut in my launchpad to launch it. 00:03:36.360 --> 00:03:38.020 So I didn't... 00:03:38.020 --> 00:03:39.160 Oh, that's pretty cool. 00:03:39.160 --> 00:03:41.760 So you can attach that to any Python script. 00:03:41.760 --> 00:03:43.340 You can just launch it from there. 00:03:43.340 --> 00:03:44.440 So... 00:03:44.440 --> 00:03:44.680 Nice. 00:03:44.680 --> 00:03:45.280 Oh, but... 00:03:45.280 --> 00:03:47.260 It looks like it has different modes, too. 00:03:47.260 --> 00:03:52.800 Like, you can set it up to work for writing code for Adafruit or for Pygame or stuff like that. 00:03:52.800 --> 00:03:54.160 That looks kind of neat. 00:03:54.260 --> 00:03:56.160 Yeah, and then when it has... 00:03:56.160 --> 00:03:59.940 The built-in REPL, if you pop open the REPL, it's not just your normal REPL. 00:03:59.940 --> 00:04:04.600 It's a Jupyter notebook or Jupyter REPL, which is pretty cool. 00:04:04.600 --> 00:04:05.560 Yeah, that's really cool. 00:04:05.560 --> 00:04:06.360 I love this. 00:04:06.360 --> 00:04:07.660 Yeah, it's very neat. 00:04:07.660 --> 00:04:08.980 And there's some... 00:04:08.980 --> 00:04:14.040 Like, on the tutorials link, there's a whole bunch of tutorials that aren't quite there yet. 00:04:14.040 --> 00:04:18.300 So I'm guessing they could use some people to help out with this project. 00:04:18.300 --> 00:04:19.020 Oh, right. 00:04:19.020 --> 00:04:20.980 Yeah, and that'd be a great, easy way to get... 00:04:20.980 --> 00:04:24.180 Sort of gets your feet wet and open source is to write some tutorials. 00:04:24.180 --> 00:04:24.580 Right? 00:04:24.580 --> 00:04:29.440 You don't have too much to depend upon or you probably won't break anybody's code by writing one. 00:04:29.440 --> 00:04:29.740 Yeah. 00:04:29.740 --> 00:04:30.360 Yeah, nice. 00:04:30.360 --> 00:04:37.460 So, Chris, one of the things I find that's pretty interesting is we love to talk about super advanced topics, 00:04:37.460 --> 00:04:43.880 but a lot of times it's really what people need or want, especially if you're helping or mentoring someone else, 00:04:43.880 --> 00:04:45.600 is like some more fundamental stuff, right? 00:04:45.600 --> 00:04:52.260 Yep, I found this kind of an intro topic into how the Python parentheses system works. 00:04:52.260 --> 00:04:56.580 It's pretty interesting also for folks that come from other languages, 00:04:56.580 --> 00:05:01.700 so you can get kind of like a quick translation from one place to another and how things operate. 00:05:01.700 --> 00:05:02.660 It sounds pretty simple. 00:05:02.660 --> 00:05:04.340 I mean, it's about Python parentheses, right? 00:05:04.340 --> 00:05:07.900 The Python parentheses primer from Reuben Lerner. 00:05:07.900 --> 00:05:09.580 Shout out to him on that. 00:05:09.980 --> 00:05:15.240 But there's some pretty advanced things going on and a pretty cool feature coming at the end. 00:05:15.240 --> 00:05:15.660 Great. 00:05:15.660 --> 00:05:17.300 So, tell us about it. 00:05:17.300 --> 00:05:22.160 So, the fun stuff is it goes into all the different ways that you actually use parentheses 00:05:22.160 --> 00:05:24.900 while you're doing your Python syntax and what you can use it for. 00:05:24.900 --> 00:05:31.440 So, you get a couple of the simple topics like, you know, usually a parentheses is used in a callable, 00:05:31.440 --> 00:05:36.480 like to call a function and pass in parameters or to call a class that implements callable. 00:05:36.480 --> 00:05:42.220 Things like prioritization of operations or conditionals. 00:05:42.220 --> 00:05:44.720 You also use parentheses for making tuples. 00:05:44.720 --> 00:05:49.960 But you'll also get a little bit into generator expressions and the advantages of that. 00:05:50.420 --> 00:05:57.900 And a couple of little quirks you can use it for securing some of the indentation rules that Python has that some people kind of hate. 00:05:57.900 --> 00:06:00.420 But other people like me love. 00:06:00.420 --> 00:06:01.620 So, I'm special. 00:06:01.620 --> 00:06:04.440 You also get into square brackets and curly braces. 00:06:04.440 --> 00:06:10.700 And square brackets, which are typically used for lists and for indexing. 00:06:10.700 --> 00:06:15.440 For somebody that's new to the topic, you'll want to look at the slices section. 00:06:15.440 --> 00:06:19.820 Because slices are a pretty powerful little tool that you get out of Python. 00:06:20.400 --> 00:06:27.580 If you haven't used it before, how to get specific sections of a list or iterable. 00:06:27.580 --> 00:06:39.220 And there's also, while not in the article itself, but some of the folks that commented on the article also mentioned that some of the new type hint stuff also uses square brackets for identifying, 00:06:40.220 --> 00:06:50.400 like the variables, like the variables, like the data type of floats, the data type that it's implementing. 00:06:50.400 --> 00:06:55.460 So, if you have a list of floats, you would say list curly bracket floats when you're specifying what type it is. 00:06:55.600 --> 00:06:56.520 Yeah, that's really interesting. 00:06:56.520 --> 00:07:06.100 It's almost like generics in like C# or templates in C++ where you would say this thing takes a list of strings. 00:07:06.100 --> 00:07:07.420 You can say it's just a list. 00:07:07.420 --> 00:07:10.860 But then, like, you don't get any help on what's contained within it. 00:07:10.860 --> 00:07:15.180 But you could say, you know, import the list thing and say list square bracket int square bracket. 00:07:15.320 --> 00:07:19.460 Then it has to be a homogeneous list of ends, not just any random list, which is pretty cool. 00:07:19.460 --> 00:07:19.920 Exactly. 00:07:19.920 --> 00:07:26.040 I was looking through here, and down at the bottom, they're talking about some of the ways to, like, future-proof your code. 00:07:26.320 --> 00:07:31.700 So, like, you can say from Dunder future import division. 00:07:31.700 --> 00:07:35.600 And there's a proposal for braces, huh? 00:07:35.600 --> 00:07:36.120 Uh-huh. 00:07:36.120 --> 00:07:47.520 If you have a Python REPL open right now and you kind of want to try that, you'll get a neat little message of what the future will look like if you ever actually import braces. 00:07:47.520 --> 00:07:47.880 Right. 00:07:47.960 --> 00:07:56.320 So, if you can see, like, the coming braces feature, you can say from Dunder future import braces and see what support Python's probably going to be adding for braces soon. 00:07:56.320 --> 00:07:59.480 Which, you know, not everyone's typing. 00:07:59.480 --> 00:08:00.400 They're probably driving this up. 00:08:00.400 --> 00:08:06.800 So, basically, it throws a syntax exception error and says not a chance. 00:08:06.800 --> 00:08:07.940 We're never adding braces. 00:08:07.940 --> 00:08:09.420 It's beautiful. 00:08:09.420 --> 00:08:11.040 I knew about anti-gravity. 00:08:11.040 --> 00:08:12.060 We were joking about that earlier. 00:08:12.060 --> 00:08:13.940 But I did know about the import braces. 00:08:13.940 --> 00:08:14.680 That's pretty sweet. 00:08:14.880 --> 00:08:21.100 One more interesting thing to mention, obviously, goes into curly braces and how you use that as well for set comprehensions and dictionaries. 00:08:21.100 --> 00:08:24.240 The other thing to remind folks is Python 3.6+. 00:08:24.240 --> 00:08:25.860 There is f-strings. 00:08:25.860 --> 00:08:33.000 And with f-strings, you can use braces inside a string that you prefix with f. 00:08:33.000 --> 00:08:41.820 And the interpreter replaces any code that you put inside those braces, actually executes it, and replaces the result into the string. 00:08:41.820 --> 00:08:42.180 Yeah. 00:08:42.180 --> 00:08:42.860 Very nice. 00:08:42.860 --> 00:08:43.740 f-strings are great. 00:08:43.740 --> 00:08:44.700 And it's way more efficient. 00:08:44.860 --> 00:08:46.060 Fastest and the shortest. 00:08:46.060 --> 00:08:46.840 Cleanest. 00:08:46.840 --> 00:08:47.160 Very nice. 00:08:47.160 --> 00:08:52.100 So, Brian, you mentioned that Mew Editor is a Qt application. 00:08:52.100 --> 00:08:55.680 And Qt is kind of making a bit of a resurgence these days. 00:08:55.680 --> 00:08:57.740 At least I've been paying more attention to it. 00:08:57.740 --> 00:08:57.980 Yeah. 00:08:57.980 --> 00:08:58.320 Yeah. 00:08:58.320 --> 00:09:00.960 Well, it had gone through some fairly dark times. 00:09:00.960 --> 00:09:03.660 I mean, obviously, we've been on our GUI kick for a while. 00:09:03.660 --> 00:09:04.900 We're going through all these different options. 00:09:04.900 --> 00:09:06.380 And there's still tons of great options. 00:09:06.940 --> 00:09:12.880 Like, wxPython had their Phoenix release, which was sort of a rebuilding of that whole thing, which is awesome. 00:09:12.880 --> 00:09:14.100 A little while ago, we talked about that. 00:09:14.180 --> 00:09:20.420 So, the Qt company, Qt company, is the company that is behind the Qt framework. 00:09:20.420 --> 00:09:36.500 And they just announced the official release for Python for Qt, which is taking these various version mismatch, PySide 2, PyQt, all those things, and, like, rebuilding it, like, on a two-year project into a fresh, new, shiny version. 00:09:36.660 --> 00:09:38.540 So, that's pretty awesome that that's more or less out. 00:09:38.540 --> 00:09:39.420 Oh, that's exciting. 00:09:39.420 --> 00:09:42.700 We heard recent, not too long ago, that it was coming. 00:09:42.700 --> 00:09:45.000 But having it be released, wonderful. 00:09:45.000 --> 00:09:45.300 Yeah. 00:09:45.300 --> 00:09:47.920 So, if you're messing with this, it's version 5.11. 00:09:47.920 --> 00:09:53.720 And I think it's still in a tech preview in terms of the execution bits. 00:09:53.720 --> 00:09:56.380 But I suspect that this means the APIs are frozen. 00:09:56.380 --> 00:09:57.700 So, you can go and check that out. 00:09:57.700 --> 00:09:58.380 Yeah. 00:09:58.380 --> 00:10:00.000 So, it started two years ago. 00:10:00.000 --> 00:10:01.120 They've been working on this. 00:10:01.120 --> 00:10:04.720 And one thing that's really nice is the way you get it is you just pip install. 00:10:05.480 --> 00:10:10.780 And right now, it's not coming out of PyPI.org itself. 00:10:10.780 --> 00:10:11.860 It's coming out of a different place. 00:10:11.860 --> 00:10:19.200 So, they show you the command, like, to pass their particular sort of dev, their dev index URL, which I put in the show notes. 00:10:19.200 --> 00:10:20.240 So, people can check that out. 00:10:20.240 --> 00:10:24.080 So, that looks like they have their own PyPI implementation there. 00:10:24.080 --> 00:10:24.360 Yeah. 00:10:24.360 --> 00:10:25.200 Something like that, right? 00:10:25.200 --> 00:10:29.400 Like, a little bit like what you guys are doing that we talked about over on Talk Python, right, Chris? 00:10:29.400 --> 00:10:29.660 Yep. 00:10:29.660 --> 00:10:30.120 Exactly. 00:10:30.120 --> 00:10:32.480 But this one goes outside the firewall, it looks like. 00:10:32.480 --> 00:10:33.600 Nice. 00:10:34.060 --> 00:10:35.880 So, you know, I just want to give a shout out. 00:10:35.880 --> 00:10:41.860 People who are looking, waiting for Qt to become more important to get revitalized. 00:10:41.860 --> 00:10:44.980 I feel like, you know, this is the announcement we've been waiting for. 00:10:44.980 --> 00:10:47.060 Hopefully, this means lots of good things. 00:10:47.060 --> 00:10:47.920 We'll see what happens. 00:10:47.920 --> 00:10:48.380 Yeah. 00:10:48.380 --> 00:10:49.000 Pretty cool. 00:10:49.000 --> 00:10:49.320 Yeah. 00:10:49.320 --> 00:10:49.660 For sure. 00:10:49.660 --> 00:10:52.680 So, speaking of good things, DigitalOcean, they're very good. 00:10:52.680 --> 00:10:54.400 They do all sorts of awesome stuff, right? 00:10:54.400 --> 00:10:57.540 They're giving you guys tons of credit if you want to get started there. 00:10:57.880 --> 00:11:02.220 And I always try to talk about different ways we are using them in our various bits of infrastructure. 00:11:02.220 --> 00:11:03.740 And that's still true. 00:11:03.740 --> 00:11:04.220 Still are. 00:11:04.220 --> 00:11:05.000 Still enjoying that. 00:11:05.000 --> 00:11:13.280 But one of the things that they have that's really cool is when you go create a virtual machine, you can say, I want a one-click app, which really means a virtual machine configured to run something. 00:11:14.080 --> 00:11:18.680 And they recently set up a machine learning virtual machine for you. 00:11:18.680 --> 00:11:19.780 So, you can go there, create a droplet. 00:11:19.780 --> 00:11:21.360 That's their VM terminology. 00:11:21.360 --> 00:11:22.860 Click on one-click apps. 00:11:22.860 --> 00:11:24.600 Pick machine learning in AI. 00:11:24.600 --> 00:11:31.140 And you automatically get a machine with Python 3, R, Jupyter, Notebooks, SensorFlow, PyTorch, all that stuff. 00:11:31.140 --> 00:11:36.240 And you can pick, like, a CPU-optimized CPU for your virtual machine. 00:11:36.240 --> 00:11:37.660 All sorts of good stuff. 00:11:37.660 --> 00:11:41.580 So, if you want to check that out, you can do it real quick and affordably. 00:11:41.580 --> 00:11:43.660 Just play around with those tools, which is pretty awesome. 00:11:43.760 --> 00:11:49.900 So, check them out over at pythonbytes.fm/digitalocean. 00:11:49.900 --> 00:11:55.080 And like I said, if you go there and you're a new user, you'll get $100 credit, which is also pretty sweet. 00:11:55.080 --> 00:11:59.960 So, Brian, iteration is a key element of Python, right? 00:11:59.960 --> 00:12:05.940 Yeah, we often deal with lots of iteration and generators and iterators and all sorts of things. 00:12:05.940 --> 00:12:06.340 Exactly. 00:12:06.340 --> 00:12:07.160 We've got generators. 00:12:07.160 --> 00:12:13.080 Like, the primary for loop is not for I equals zero, I plus plus, but it's for thing in collection. 00:12:13.300 --> 00:12:14.100 It's beautiful, right? 00:12:14.100 --> 00:12:15.600 But it goes even deeper. 00:12:15.600 --> 00:12:19.260 Developing your own iterators and generators is a fun thing to learn about. 00:12:19.260 --> 00:12:23.120 But I have to admit that I don't often do that very much. 00:12:23.120 --> 00:12:30.760 And one of the things that I've – it's always been on my to-do list is to learn more about the iter tools module. 00:12:30.760 --> 00:12:33.540 And I've not really ever explored it too much. 00:12:33.540 --> 00:12:41.180 And real Python has a blog post called iter tools in Python 3 by example. 00:12:41.500 --> 00:12:43.220 And I really enjoyed this. 00:12:43.220 --> 00:12:49.980 It's a nice introduction as to what is the problem that iterators and generators are dealing with. 00:12:49.980 --> 00:12:59.640 And then, like, for example, it starts off with just how does zip work to take two lists and create another list with, like, each element. 00:13:00.140 --> 00:13:04.620 And then what if you need, like, not quite the same zip? 00:13:04.620 --> 00:13:06.920 What if they're not the same length and things like that? 00:13:06.920 --> 00:13:11.440 And some of the problems that can happen and why lazy evaluation is a good thing. 00:13:11.440 --> 00:13:16.240 And actually, in the discussion, it used the time function, the time shell function. 00:13:16.240 --> 00:13:23.080 I guess this is, like, a Unix-y kind of thing with a dash f, which I've never used before. 00:13:23.080 --> 00:13:25.860 And that showed the memory used also. 00:13:25.860 --> 00:13:27.200 Didn't know that was a thing. 00:13:27.200 --> 00:13:27.800 Oh, that's cool. 00:13:27.800 --> 00:13:34.500 But this example of using, like, a big example in the memory usage blew up to, like, huge. 00:13:34.500 --> 00:13:41.300 And so just talk through, like, some of the different things that are in iter tools and why that helps you. 00:13:41.300 --> 00:13:42.680 I pulled out a couple. 00:13:42.680 --> 00:13:47.420 Like, a lot of these things, if you don't know they're there, you'll just come up with it on your own. 00:13:47.420 --> 00:13:51.180 Like, doing combinatorial sets. 00:13:51.180 --> 00:13:52.220 Those are already in there. 00:13:52.220 --> 00:13:57.260 Coming up with permutations, you don't have to do, like, a random index. 00:13:57.260 --> 00:14:01.540 You can just use their iterate, the ones that are built in. 00:14:01.540 --> 00:14:08.460 I think that's a good example of, like, being fluent in Python versus being able to make the code work but not really deeply knowing it, right? 00:14:08.460 --> 00:14:15.620 Like, if somebody said, hey, I want you to take this thing and generate, like, a set of permutations, all the permutations of, say, this word or whatever, right? 00:14:15.620 --> 00:14:18.600 You might attempt to implement the fairly complicated algorithm. 00:14:18.600 --> 00:14:23.200 Or you might just call iter tools, you know, permute sort of thing, right? 00:14:23.200 --> 00:14:24.420 And then, boom, it's just there. 00:14:24.420 --> 00:14:28.240 So there's so many things like that that are just, like, at your fingertips if you just import them. 00:14:28.240 --> 00:14:28.480 Yeah. 00:14:28.560 --> 00:14:36.280 I mean, a lot of people are smart enough to, like, if you come up with all the combinations, you can just have a nested for loop and figure out how to do that. 00:14:36.280 --> 00:14:37.660 But you don't have to. 00:14:37.660 --> 00:14:38.380 It's already there. 00:14:38.380 --> 00:14:44.900 And one of the things I didn't know, there's some fun things like some fun uses of count and cycle. 00:14:44.900 --> 00:14:46.540 I didn't know about cycle. 00:14:46.540 --> 00:14:47.180 That's pretty cool. 00:14:47.180 --> 00:14:52.320 It just kind of cycles through a set and then keeps giving you more of the same. 00:14:52.680 --> 00:15:00.840 And the tutorial also talks about, in the tutorial, it's using the next function, which is for iterators. 00:15:00.840 --> 00:15:03.160 You don't have to use them in a loop. 00:15:03.160 --> 00:15:07.480 You can even just call the next function, which is kind of fun. 00:15:07.480 --> 00:15:10.120 And then something that's iSliced. 00:15:10.120 --> 00:15:11.300 I didn't know this was a thing. 00:15:11.300 --> 00:15:19.440 So if you want to take a slice of a list or a slice of some other iterator, you can do that. 00:15:19.440 --> 00:15:24.700 But if you want that to be an iterable also, this does it for you. 00:15:24.700 --> 00:15:26.900 And so there's a whole bunch of goodies in here. 00:15:26.900 --> 00:15:30.980 Yeah, one of my favorites is iSliced because, like Chris already said, slicing is awesome. 00:15:30.980 --> 00:15:35.200 But if you try to do, say, slice on a generator, it'll just go fail. 00:15:35.200 --> 00:15:37.000 Like, nope, we don't slice generators. 00:15:37.000 --> 00:15:39.880 Well, you can iSliced them, and it works just fine. 00:15:39.880 --> 00:15:40.640 It's beautiful, right? 00:15:40.640 --> 00:15:44.480 So you sort of make things sliceable that otherwise would not be. 00:15:44.480 --> 00:15:45.060 It's really great. 00:15:45.060 --> 00:15:50.640 Yeah, so this is definitely a good read to beef up on the iter tools. 00:15:51.600 --> 00:15:57.640 Yeah, I recommend everybody that writes any Python code to just go look at iter tools and all the things you can do. 00:15:57.640 --> 00:16:00.680 There's lots of stuff online, and this is a good resource. 00:16:00.680 --> 00:16:07.600 Every once in a while, every time there's an article that's something about iter tools, I always go just at least skim it. 00:16:07.600 --> 00:16:10.380 Because there's always some little magic in there. 00:16:10.380 --> 00:16:12.640 You're like, oh, I implemented that myself the other day. 00:16:12.640 --> 00:16:17.140 Let me go delete that code and actually do something that's maintained by somebody that knows something more than that. 00:16:17.260 --> 00:16:18.680 Yeah, and maybe even in C. 00:16:18.680 --> 00:16:20.940 So it's a little faster, right? 00:16:20.940 --> 00:16:21.780 Down in the internals. 00:16:21.780 --> 00:16:22.600 Nice. 00:16:22.600 --> 00:16:30.600 So speaking of sort of working with collections and iterables and things like that, Chris, I feel like your item dovetails really well in with this. 00:16:30.600 --> 00:16:30.960 Right. 00:16:31.160 --> 00:16:34.740 So the next item is about Python sets and set theory. 00:16:34.740 --> 00:16:45.600 It's a nice, also kind of a primer on how sets work in Python, how you divide them, how you work with them, and just a tiny bit on set theory. 00:16:45.600 --> 00:16:48.820 So you can build sets different ways. 00:16:48.820 --> 00:16:52.080 The most common way is by calling the set function to build an empty set. 00:16:53.360 --> 00:16:58.720 But you can also use curly braces, which we were talking about earlier, to have set comprehensions. 00:16:58.720 --> 00:17:03.580 And it's a great way of, say, deduping items in a list. 00:17:03.580 --> 00:17:14.900 So if you have a list of a bunch of integers or something like that, you can use the comprehension to iterate through the list and just grab the items that you care about, and you only get the unique items out of it. 00:17:15.080 --> 00:17:20.040 The interesting part about sets as well is that they're all of one. 00:17:20.040 --> 00:17:24.380 So when you're making a membership test, it's fast. 00:17:24.380 --> 00:17:30.060 It's considerably faster than going through, say, a list where you have to iterate through the entire list to see if the item is in it. 00:17:30.060 --> 00:17:30.600 Yeah, that's cool. 00:17:30.600 --> 00:17:32.700 I definitely like the distinct aspect. 00:17:32.700 --> 00:17:35.140 That's what I use a lot of sets for. 00:17:35.140 --> 00:17:36.240 It's like, I have all these things. 00:17:36.240 --> 00:17:37.280 There might be duplication. 00:17:37.280 --> 00:17:39.780 I just want them one of each. 00:17:39.780 --> 00:17:42.420 You know, if there's duplicate, just don't add it. 00:17:42.420 --> 00:17:42.600 Right. 00:17:42.720 --> 00:17:50.740 So you can just, like, you could even say set of some list and then, you know, just get that back as here's the distinct stuff in the list, which is great. 00:17:50.740 --> 00:17:54.120 Also, for simplifying conditionals. 00:17:54.120 --> 00:18:05.600 So you have the example, well, Python had the example, and the stuff you covered about parentheses of if item equals x or item equals y or item equals z or whatever. 00:18:05.600 --> 00:18:05.920 Right. 00:18:05.920 --> 00:18:09.120 Like that becomes like kind of a nasty multiline looking thing. 00:18:09.480 --> 00:18:14.520 Maybe a more Pythonic way of you say if x is in, you know, curly set x, y, z. 00:18:14.520 --> 00:18:14.860 Right. 00:18:14.860 --> 00:18:16.260 You can do stuff like that. 00:18:16.260 --> 00:18:22.840 It's always another point to keep in mind is sets are of immutable values. 00:18:22.840 --> 00:18:28.580 So you can't put, like, say, a normal set inside of a set. 00:18:28.580 --> 00:18:32.020 There's other value types and stuff like that. 00:18:32.020 --> 00:18:33.340 You can't just, like, stick in a set. 00:18:33.340 --> 00:18:33.680 Right. 00:18:33.720 --> 00:18:36.120 So it has to be hashable, basically same as dictionary keys. 00:18:36.120 --> 00:18:37.080 Yeah. 00:18:37.080 --> 00:18:37.680 Yeah. 00:18:37.680 --> 00:18:38.400 Right. 00:18:38.400 --> 00:18:39.120 So it can't change. 00:18:39.120 --> 00:18:45.220 But it's always, always interesting to remember once you've made a set that you're looking for distinct values and things like that. 00:18:45.440 --> 00:18:56.960 I always try to look through my code if there's some sort of, if I'm checking if item is in list one and also in list two, because you can always have two sets and do an intersection between them. 00:18:56.960 --> 00:18:59.540 And then you don't have to do those for loops. 00:18:59.540 --> 00:19:06.600 And the code is kind of optimized to do that for you, which I'm sure will not be all of n squared when you're writing your code. 00:19:06.600 --> 00:19:06.820 Right. 00:19:06.820 --> 00:19:07.500 Yeah, exactly. 00:19:07.500 --> 00:19:17.560 And then just to quickly look back on immutability, if you want to make a set of sets, there's also such a thing as a frozen set where the set itself is immutable. 00:19:17.560 --> 00:19:20.120 And you can stick that into a set. 00:19:20.120 --> 00:19:21.520 So stuff like that. 00:19:21.520 --> 00:19:22.340 That's very meta. 00:19:22.340 --> 00:19:23.560 Brian, do you use sets very often? 00:19:23.560 --> 00:19:29.360 I always have, like, a tutorial like this or something to look up because I forget what the operators are. 00:19:29.360 --> 00:19:35.220 Because it does have union, intersection, difference, symmetric difference, things like that. 00:19:35.740 --> 00:19:43.240 And remembering all of that stuff from your college days is good to try to make some elegant code. 00:19:43.240 --> 00:19:49.340 But it has, like, for instance, the union operator is you can just use the bar function for that. 00:19:49.340 --> 00:19:52.540 And looking up all those is a good thing. 00:19:52.540 --> 00:20:02.520 Although, since I know I have to look it up, I usually put a comment in there to tell anybody else what I'm doing to say this is a set operation going on here. 00:20:02.520 --> 00:20:03.520 Yeah, it makes sense. 00:20:03.520 --> 00:20:11.280 I feel like sometimes knowing the right data structure cannot, like, really open people's eyes or really change the way they're doing something. 00:20:11.280 --> 00:20:16.160 And sets and dictionaries definitely seem to fall into that space where, like, you don't use them that much. 00:20:16.160 --> 00:20:18.820 But when you do, you're like, whoa, that really is better. 00:20:18.820 --> 00:20:20.440 So many ways. 00:20:20.440 --> 00:20:23.580 Yeah, and it's also one of those things of, like, it's a new hammer. 00:20:23.580 --> 00:20:28.900 Try to be sure that you don't see everything as a set problem. 00:20:28.900 --> 00:20:30.880 Because everything isn't a set problem. 00:20:31.300 --> 00:20:32.000 Yeah, for sure. 00:20:32.000 --> 00:20:32.580 All right. 00:20:32.580 --> 00:20:39.800 So last item that I wanted to cover on this episode is a little bit of a look ahead, maybe to next week. 00:20:39.800 --> 00:20:45.940 But to put this on people's radar so when it launches, you can, like, do maybe a backflip or something if you've been practicing. 00:20:46.940 --> 00:20:54.540 So coming up, we just had the release of Python 3.7 Release Candidate 1, which was on June 12th. 00:20:54.540 --> 00:21:02.440 And expected or planned for June 27th, which is seven days from now, is the final release of Python 3.7 official. 00:21:02.440 --> 00:21:03.200 How about that? 00:21:03.200 --> 00:21:04.000 I'm so excited. 00:21:04.000 --> 00:21:05.860 Do you know what makes me most excited about this? 00:21:05.860 --> 00:21:07.980 There's certain things in here like, oh, okay, cool. 00:21:07.980 --> 00:21:08.800 Breakpoint. 00:21:08.800 --> 00:21:09.560 That's kind of nice. 00:21:09.760 --> 00:21:11.020 Data classes, kind of nice. 00:21:11.020 --> 00:21:17.180 But what really makes me most excited is this is the categorically fastest Python period. 00:21:17.180 --> 00:21:25.120 So all the people that say, no, we're using legacy Python because under this particular use case, it's faster than Python 3.7. 00:21:25.260 --> 00:21:27.260 And there may still be some very narrow use case. 00:21:27.260 --> 00:21:30.920 But generally speaking, this is the fastest Python period. 00:21:30.920 --> 00:21:36.140 It's much faster than Python 3, certainly up to 3.3. 00:21:36.140 --> 00:21:38.660 But it's even quite a bit faster than 3.6. 00:21:38.660 --> 00:21:51.080 So, for example, from 3.6 to 3.7, when you're calling methods, especially methods that are part of classes, not standalone functions, but, like, bound methods to classes, it's, like, 20% faster. 00:21:51.080 --> 00:21:52.560 That's a reason right there to switch. 00:21:52.720 --> 00:21:55.820 Yeah, and what's cool, like, all you got to do is just run on the new version, right? 00:21:55.820 --> 00:21:58.460 There's no, like, oh, I switched to PyPy or something. 00:21:58.460 --> 00:22:01.260 It's just I now have 3.7, so life is better. 00:22:01.260 --> 00:22:02.980 Especially if you're using a framework. 00:22:02.980 --> 00:22:03.340 Yeah. 00:22:03.340 --> 00:22:07.180 Anybody that's using a framework, remember, there's a bunch of levels of abstraction around it. 00:22:07.180 --> 00:22:08.860 So there's a bunch of function calls. 00:22:08.860 --> 00:22:09.380 Exactly. 00:22:09.380 --> 00:22:11.300 Yeah, there's tons of function calls. 00:22:11.300 --> 00:22:13.960 And so this is really, really good news. 00:22:14.440 --> 00:22:24.580 So just to run through some of the features, there's improvements to coupling that type annotations or type hints added to the system. 00:22:24.700 --> 00:22:30.600 So previously, if I wanted to say, here's a function, and it returns this type of thing, right? 00:22:30.600 --> 00:22:33.280 It returns, like, this object or some type I've defined. 00:22:33.280 --> 00:22:36.500 I have to literally import that type at the top of that file. 00:22:36.500 --> 00:22:47.420 And what that means is at import time, I pay an extra import processing that file, which I might not have otherwise loaded, potentially, or at least not right then. 00:22:47.660 --> 00:22:52.740 The other one is circular dependencies are super annoying in that. 00:22:52.740 --> 00:22:59.360 Like, so, for example, I've got, like, a repository class, and it returns some kind of object, right? 00:22:59.360 --> 00:23:01.900 But that object, when it's defined, has to know about the repository. 00:23:01.900 --> 00:23:04.780 So it says it returned, like, it uses this somewhere else. 00:23:04.780 --> 00:23:10.000 Like, that basically will fail and break the import because it's circular, right? 00:23:10.000 --> 00:23:21.180 So with this new thing, this change is instead of actually evaluating these type hints and having to import them, it's just evaluated as if you had typed them as strings. 00:23:21.180 --> 00:23:25.800 So they're not actually evaluating the true types when you do type annotations. 00:23:25.800 --> 00:23:27.120 So that gives you more flexibility. 00:23:27.120 --> 00:23:29.120 The circular dependencies are a problem, and it's faster. 00:23:29.120 --> 00:23:29.500 Yeah. 00:23:29.500 --> 00:23:30.140 That's neat. 00:23:30.140 --> 00:23:37.720 Yeah, the type annotations thing that makes me the most crazy is I have a class, and it's got, like, some function that returns an instance of itself. 00:23:38.200 --> 00:23:45.840 You can't say that in the previous type hints as concrete types because you can't say the name of the class until it's fully defined. 00:23:45.840 --> 00:23:49.920 But you're halfway through the class trying to say, this method returns one of me, you know? 00:23:49.920 --> 00:23:56.180 You can get around it by putting quotes, but that's effectively, like, what this does without the syntax to put in the quotes. 00:23:56.180 --> 00:23:57.340 So it looks more natural. 00:23:57.340 --> 00:23:59.520 So you can do that now with the 3-side? 00:23:59.520 --> 00:24:03.840 Yeah, but you have to put quotes, and you have to, like, say the name out exactly as a string. 00:24:03.840 --> 00:24:04.420 Oh, okay. 00:24:04.420 --> 00:24:04.880 Yeah, yeah. 00:24:04.880 --> 00:24:06.020 Let's take a look at that. 00:24:06.020 --> 00:24:06.640 Yeah, it's pretty cool. 00:24:07.140 --> 00:24:09.900 All right, you also have data classes, which are really nice. 00:24:09.900 --> 00:24:11.200 They're kind of like tuples. 00:24:11.200 --> 00:24:17.260 They have a lot of interesting hashing and equality operators on them as well as representation ones. 00:24:17.260 --> 00:24:21.460 They can be frozen, so they can be mutable or immutable, all sorts of things. 00:24:21.460 --> 00:24:26.460 So kind of like enumeration, name tuple, tuple, it's stuff all brought together. 00:24:26.640 --> 00:24:35.780 It's sort of a derivative of the attrs project, but they decided not to move attrs into the framework because it's evolving quickly, and they don't want to, like, freeze it. 00:24:35.780 --> 00:24:37.720 So data classes, kind of the same thing. 00:24:37.720 --> 00:24:45.540 I just want to point out that data classes has a back port for 3.6, so you can go ahead and start using those in 3.6 as long as you pip install them first. 00:24:45.540 --> 00:24:46.540 Yeah, how do I get that? 00:24:46.540 --> 00:24:47.920 Pip install data classes? 00:24:47.920 --> 00:24:49.320 Pip install data classes. 00:24:49.560 --> 00:24:50.620 Oh, that's pretty killer. 00:24:50.620 --> 00:24:51.480 I didn't know about that. 00:24:51.480 --> 00:24:55.800 All right, so there's a new breakpoint function, which we talked about. 00:24:55.800 --> 00:24:58.760 We don't use that much because, like, if you just fire a PyCharm, who cares? 00:24:58.760 --> 00:25:02.560 But there's some pretty interesting – it's got to be clicking the gutters. 00:25:03.060 --> 00:25:09.540 But there's actually some pretty interesting ways to, like, say, hook a remote debugger to your code, things like that. 00:25:09.540 --> 00:25:11.040 There's really interesting stuff going on there. 00:25:11.040 --> 00:25:12.060 AsyncIO got better. 00:25:12.060 --> 00:25:13.560 Chris, you should be happy about that. 00:25:13.560 --> 00:25:14.540 Did you see these? 00:25:14.540 --> 00:25:15.980 Some of this is pretty cool. 00:25:15.980 --> 00:25:16.820 Tell me about it. 00:25:16.820 --> 00:25:28.160 This asyncIO run function is a way of running a coroutine from synchronous code, which, I mean, that existed before, but you had to do, like, 50 million things to set your stuff up correctly and make sure you didn't break other – 00:25:28.160 --> 00:25:31.900 You just call run, and it will internally, like, create the loop and do it for you? 00:25:31.900 --> 00:25:32.260 Yep. 00:25:32.260 --> 00:25:34.360 Just call run, starts coroutine. 00:25:34.360 --> 00:25:35.880 Oh, that is sweet. 00:25:35.880 --> 00:25:40.080 It starts an event loop, runs your coroutine, and closes the event loop at the end. 00:25:40.080 --> 00:25:42.100 So you're going to have to be careful when you use this. 00:25:42.100 --> 00:25:42.880 This is pretty cool. 00:25:42.880 --> 00:25:48.500 And there's some of the task management stuff that's also a little bit better. 00:25:48.500 --> 00:25:49.380 So this is pretty cool. 00:25:49.380 --> 00:25:52.140 I'll have to – maybe I'll write a post on this. 00:25:52.140 --> 00:25:52.900 Yeah, that's awesome. 00:25:52.900 --> 00:25:53.700 Yeah, definitely cool. 00:25:53.700 --> 00:25:56.860 Another one that's really nice is the time module. 00:25:57.380 --> 00:26:05.460 And a bunch of other functions, as well, have become more accurate, especially over long durations, and they've taken on nanosecond resolution. 00:26:05.460 --> 00:26:14.980 So you can import time and say time – you just call time, and it will give you a floating point value of the number of seconds since the epoch, like 1970. 00:26:16.120 --> 00:26:23.260 But this – you can also now in 3.7 say time underscore ns, and it will give you the nanoseconds as an integer. 00:26:23.260 --> 00:26:30.100 And because it's an integer, not a float, that means there's no drift or anything in sort of the floating point operations. 00:26:30.100 --> 00:26:32.720 It's like truly the nanoseconds, which is awesome. 00:26:32.720 --> 00:26:33.020 Yep. 00:26:33.020 --> 00:26:33.400 All right. 00:26:33.400 --> 00:26:34.440 And finally, I just want to close out. 00:26:34.440 --> 00:26:37.460 Give it like – what would Python Bytes show be without? 00:26:37.460 --> 00:26:38.840 A shout-out to Anthony Shaw. 00:26:38.840 --> 00:26:39.340 Right, Brian? 00:26:39.880 --> 00:26:41.520 Yeah, he's been a part of the show a lot. 00:26:41.520 --> 00:26:42.920 For sure. 00:26:42.920 --> 00:26:49.400 So he actually did a brand-new course on Pluralsight called What's New in Python 3.7. 00:26:49.400 --> 00:26:51.300 So I put a link to his course there as well. 00:26:51.360 --> 00:26:56.640 And actually, it's only about an hour long, but it goes really in-depth into like the advantages or all these various things. 00:26:56.640 --> 00:26:57.820 So quite cool. 00:26:57.820 --> 00:27:02.540 If that's easy for you to check out, go ahead and drop over there and check out Anthony's course. 00:27:02.540 --> 00:27:03.140 Very nice. 00:27:03.140 --> 00:27:05.960 Yeah, so I'm really excited for when this ships. 00:27:05.960 --> 00:27:07.380 I think it's going to be great. 00:27:07.380 --> 00:27:12.880 There always seems to be like some latency on the Linux distributions and stuff before I can really make use of it. 00:27:12.880 --> 00:27:15.960 But, you know, pretty soon I'll be happy to be running this. 00:27:15.960 --> 00:27:16.540 Yeah, definitely. 00:27:16.540 --> 00:27:16.900 Yeah. 00:27:16.900 --> 00:27:19.100 Do you guys have any extra news that you want to cover? 00:27:19.100 --> 00:27:20.700 That's it for our official items. 00:27:20.940 --> 00:27:29.820 I've been doing a lot of going back, went through all of the code that was in the pytest book to make sure it's 3.7 compatible, 00:27:29.820 --> 00:27:33.160 which I was happy to find out that it's fine. 00:27:33.160 --> 00:27:33.980 Nice. 00:27:33.980 --> 00:27:34.780 So that's good. 00:27:34.780 --> 00:27:35.480 Yeah, very cool. 00:27:35.480 --> 00:27:40.380 I saw this really cool tutorial series about Mongo. 00:27:40.380 --> 00:27:42.260 Do you know anything about this? 00:27:42.260 --> 00:27:45.660 I may have spent an incredible amount of time working on this project. 00:27:45.660 --> 00:27:50.520 Yeah, so I did a three-part, three-hour webcast series in partnership with Mongo. 00:27:50.520 --> 00:28:05.280 And basically from concept to actually deploying it on DigitalOcean, actually, I rebuilt the PyPI.org website in MongoDB and then published it to the internet, which I then deleted. 00:28:05.280 --> 00:28:07.860 So I don't have to pay to keep it running because there's a real one. 00:28:07.860 --> 00:28:09.640 But yeah, there's like it's recorded. 00:28:09.640 --> 00:28:10.560 People can go check it out. 00:28:10.560 --> 00:28:11.620 You got the link in the show notes. 00:28:11.620 --> 00:28:12.120 So that's awesome. 00:28:12.120 --> 00:28:12.520 Yeah. 00:28:12.740 --> 00:28:13.060 Nice. 00:28:13.060 --> 00:28:14.120 It looks pretty fun. 00:28:14.120 --> 00:28:14.360 Yeah. 00:28:14.360 --> 00:28:14.580 Yeah. 00:28:14.580 --> 00:28:15.180 Thanks for the shout-out. 00:28:15.180 --> 00:28:17.160 Chris, anything you want to let people know about while you're here? 00:28:17.160 --> 00:28:17.640 Nope. 00:28:17.640 --> 00:28:18.600 I don't really have anything new. 00:28:18.600 --> 00:28:25.620 Maybe just keep an eye out for a few new posts coming up and try to step past in my new blog. 00:28:25.620 --> 00:28:26.800 Awesome. 00:28:26.800 --> 00:28:27.060 Yeah. 00:28:27.060 --> 00:28:29.680 There might be one about this asyncio.run, huh? 00:28:29.680 --> 00:28:30.180 Yeah. 00:28:30.180 --> 00:28:31.280 Awesome. 00:28:31.280 --> 00:28:32.000 Yeah, you called it out. 00:28:32.000 --> 00:28:33.040 You got to write it now. 00:28:33.040 --> 00:28:34.000 So, yeah. 00:28:34.380 --> 00:28:36.100 Remember, the internet is written in ink. 00:28:36.100 --> 00:28:38.360 And so this is permanent now. 00:28:38.360 --> 00:28:44.320 My next post was going to be about one of my modules, which uses asyncio a bunch. 00:28:44.320 --> 00:28:50.680 So maybe I'm going to go back and experiment with 3.7 and what changes I would have to do there to write it up. 00:28:50.680 --> 00:28:52.200 So this is pretty cool. 00:28:52.200 --> 00:28:52.760 Yeah, awesome. 00:28:52.760 --> 00:28:54.440 Well, Chris, thanks for being on the show. 00:28:54.440 --> 00:28:55.780 And Brian, thank you as always. 00:28:55.780 --> 00:28:56.380 Yeah, thank you. 00:28:56.380 --> 00:28:56.940 Thanks for having me. 00:28:56.940 --> 00:28:59.660 Thank you for listening to Python Bytes. 00:28:59.660 --> 00:29:02.240 Follow the show on Twitter via at Python Bytes. 00:29:02.360 --> 00:29:05.120 That's Python Bytes as in B-Y-T-E-S. 00:29:05.120 --> 00:29:08.560 And get the full show notes at pythonbytes.fm. 00:29:08.560 --> 00:29:12.880 If you have a news item you want featured, just visit pythonbytes.fm and send it our way. 00:29:12.880 --> 00:29:15.580 We're always on the lookout for sharing something cool. 00:29:15.580 --> 00:29:18.980 On behalf of myself and Brian Okken, this is Michael Kennedy. 00:29:18.980 --> 00:29:22.600 Thank you for listening and sharing this podcast with your friends and colleagues.