WEBVTT 00:00:00.001 --> 00:00:04.040 This is Python Bytes, Python headlines and news delivered directly to your earbuds. 00:00:04.040 --> 00:00:08.220 Episode number three, recorded November 21st, 2016. 00:00:08.220 --> 00:00:09.680 Hey, Brian. 00:00:09.680 --> 00:00:10.360 Hello, everyone. 00:00:10.360 --> 00:00:10.840 Hey. 00:00:10.840 --> 00:00:11.340 Hey. 00:00:11.340 --> 00:00:11.620 Sorry. 00:00:11.620 --> 00:00:12.780 Hey, man. 00:00:12.780 --> 00:00:13.720 Great to chat with you. 00:00:13.720 --> 00:00:15.760 I'm really loving this show we're putting on. 00:00:15.760 --> 00:00:16.840 This is so much fun. 00:00:16.840 --> 00:00:19.720 But before I get to the headlines, I actually have some good news about the show. 00:00:19.720 --> 00:00:20.560 What's that, Michael? 00:00:20.560 --> 00:00:23.460 Python Bytes is now brought to you by Rollbar. 00:00:23.460 --> 00:00:27.060 They take the pain out of errors, and we'll hear from them later. 00:00:27.060 --> 00:00:28.780 But thank you, Rollbar, for sponsoring the show. 00:00:28.780 --> 00:00:29.360 That's really awesome. 00:00:29.360 --> 00:00:29.920 We appreciate it. 00:00:29.920 --> 00:00:30.520 That's really awesome. 00:00:30.520 --> 00:00:31.320 Thank you, Rollbar. 00:00:31.320 --> 00:00:32.400 Yeah, yeah, definitely. 00:00:32.400 --> 00:00:33.780 All right, let's get to the headlines. 00:00:33.780 --> 00:00:37.140 Every week, there's so much cool stuff happening, right? 00:00:37.140 --> 00:00:37.820 Well, yeah. 00:00:37.820 --> 00:00:43.520 And this last week, I just read a huge list of articles I read, Python-related. 00:00:43.520 --> 00:00:44.420 I really enjoyed. 00:00:44.420 --> 00:00:47.340 It was a hard time picking out which one to talk about. 00:00:47.340 --> 00:00:48.380 Yeah, it really was. 00:00:48.380 --> 00:00:48.760 Yeah. 00:00:48.760 --> 00:00:49.160 All right. 00:00:49.160 --> 00:00:50.500 Well, but you had to pick, right? 00:00:50.500 --> 00:00:52.400 Because we're only doing three each. 00:00:52.400 --> 00:00:54.460 We're trying to keep this short and on topic. 00:00:54.460 --> 00:00:57.180 Yeah, and I thought maybe we'd pick the same three, but we didn't. 00:00:57.180 --> 00:01:04.480 So first up, I've got an article titled, How to Get Superior Text Processing in Python with PyNinny. 00:01:04.480 --> 00:01:06.100 I think I'm pronouncing that right. 00:01:06.100 --> 00:01:06.400 PyNinny. 00:01:06.400 --> 00:01:07.880 Or maybe it's Nini. 00:01:07.880 --> 00:01:08.780 I'm not sure. 00:01:08.780 --> 00:01:09.140 PyNini? 00:01:09.380 --> 00:01:12.300 Like the Knights of Knee from Monty Python. 00:01:12.300 --> 00:01:12.920 Oh, yes. 00:01:12.920 --> 00:01:13.780 Yeah, yeah. 00:01:13.780 --> 00:01:14.840 You're probably right about that. 00:01:14.840 --> 00:01:20.760 But this is from the O'Reilly blog, and it was written by Kyle Gorman and Richard Sprout, 00:01:20.760 --> 00:01:21.320 I think. 00:01:21.320 --> 00:01:25.660 Yeah, both who are PhDs in linguistics of some variety or other, right? 00:01:25.660 --> 00:01:26.220 Yeah. 00:01:26.220 --> 00:01:33.240 And actually, because of that and also because of the title, I was afraid this was going to 00:01:33.240 --> 00:01:36.460 be sort of a hard thing to get into, but it's a really easy article. 00:01:36.460 --> 00:01:43.040 And my interest in it is mostly because when I read the Pragmatic Programmer a long time 00:01:43.040 --> 00:01:48.820 ago, it introduced me to the concept of mini languages to solve simple problems with this 00:01:48.820 --> 00:01:51.800 is the data I have and how to change it into the data I need. 00:01:52.460 --> 00:01:57.700 And often I used regular expressions for things like that, but sometimes that's not enough. 00:01:57.700 --> 00:02:03.580 And the next step always seemed to be to build up a parser or an abstract syntax tree, and 00:02:03.580 --> 00:02:06.020 that's way too far that I want to go. 00:02:06.020 --> 00:02:12.460 I think this article produces a nice halfway ground talking about what they call them is 00:02:12.460 --> 00:02:18.020 finite state transducers, which sounds like something in a Back to the Future movie. 00:02:18.020 --> 00:02:22.120 Quick, Marty, connect the finite state transducer. 00:02:22.120 --> 00:02:23.640 Yeah, exactly. 00:02:23.640 --> 00:02:30.340 But I like working with finite state machines, and apparently this is a finite state machine 00:02:30.340 --> 00:02:31.620 turned into something else. 00:02:31.620 --> 00:02:36.720 But the article starts with a small introduction to what finite state machines are, and they're 00:02:36.720 --> 00:02:38.620 really easy to get the grasp of. 00:02:38.620 --> 00:02:41.020 If you look at the article, there's some nice pictures. 00:02:41.020 --> 00:02:47.640 And then they talk about how that applies to text processing and then introduces a concept 00:02:47.640 --> 00:02:52.300 finite state acceptor, which I think just accepts things. 00:02:52.300 --> 00:02:54.460 And then transducer spits things out. 00:02:54.460 --> 00:02:55.920 I believe I get this right. 00:02:55.920 --> 00:03:00.540 But how this applies to how to translate your thinking from regular expressions to these. 00:03:00.540 --> 00:03:06.360 And anyway, it goes through some of this, gives an example using cheese names, which I love the 00:03:06.360 --> 00:03:08.780 Python tradition of using cheese names and examples. 00:03:08.860 --> 00:03:16.720 And then introduces a library called PyNinny from Google to help build these things up. 00:03:16.720 --> 00:03:22.340 And at the end, I kind of got a little bit lost, but I wasn't working through the examples 00:03:22.340 --> 00:03:22.740 myself. 00:03:22.740 --> 00:03:26.460 It is something that I think I might spend an afternoon poking through. 00:03:26.700 --> 00:03:28.380 Yeah, it is quite interesting, right? 00:03:28.380 --> 00:03:32.720 I mean, one of the things that makes me really happy about looking at this is, one, it's not 00:03:32.720 --> 00:03:33.360 too complicated. 00:03:33.360 --> 00:03:38.980 And two, it gets you away from regular expressions, which anything that gets me away from regular 00:03:38.980 --> 00:03:40.640 expressions puts a smile on my face. 00:03:40.640 --> 00:03:43.860 Well, I actually really like regular expressions. 00:03:43.860 --> 00:03:51.080 Although it is true that, I mean, there's oftentimes with text processing where it doesn't work when 00:03:51.080 --> 00:03:52.500 you can't do it line by line. 00:03:52.980 --> 00:03:57.120 And I'm probably not going to use this right away, but I appreciate this tool introduction 00:03:57.120 --> 00:03:59.200 so I can put it in my tool chest. 00:03:59.200 --> 00:04:02.840 And next time I have a problem like this, I might look this thing up. 00:04:02.840 --> 00:04:03.620 Right. 00:04:03.620 --> 00:04:06.720 You guys will be looking at something, some dating, like, oh, you know what we need? 00:04:06.720 --> 00:04:07.860 A finite state transducer. 00:04:07.860 --> 00:04:10.120 We're going to solve this. 00:04:10.120 --> 00:04:12.580 And I totally want to do that in a meeting. 00:04:12.580 --> 00:04:15.620 I think we should put a finite state transducer in here. 00:04:15.620 --> 00:04:16.880 Fantastic. 00:04:16.880 --> 00:04:20.640 Now, it does things like pluralized stuff. 00:04:20.960 --> 00:04:24.860 You can teach it, like, for example, you taught it what all the cheeses were, and then it could, 00:04:24.860 --> 00:04:31.840 like, locate sentences that were talking about cheese and do lots of interesting processing, 00:04:31.840 --> 00:04:32.820 not just pattern matching. 00:04:32.820 --> 00:04:33.420 It's cool. 00:04:33.420 --> 00:04:38.040 It isn't, but it does start out with, like, a simple example of, like, if I tell it all the 00:04:38.040 --> 00:04:43.460 cheeses to look through some code and find the cheeses and add a cheese tag around it or something. 00:04:43.820 --> 00:04:44.740 Yeah, yeah. 00:04:44.740 --> 00:04:48.180 There are simple solutions, simple problems that it can solve as well. 00:04:48.180 --> 00:04:50.000 Yeah, it's great to have it in your toolbox. 00:04:50.000 --> 00:04:52.280 Well, you know where I would like to run it, though? 00:04:52.280 --> 00:04:56.660 I don't really want to run it on Python 3.5 or definitely not on 2.7 anymore. 00:04:56.660 --> 00:04:57.720 Oh, yeah. 00:04:57.720 --> 00:04:59.300 Nice transition there. 00:04:59.300 --> 00:04:59.680 Thank you. 00:04:59.680 --> 00:05:01.580 Yeah, I want to run that on Python 3.6. 00:05:02.260 --> 00:05:06.620 And, you guys, there is amazing stuff coming in Python 3.6. 00:05:06.620 --> 00:05:08.660 And they just released beta 4. 00:05:08.660 --> 00:05:09.880 Beta 4. 00:05:09.880 --> 00:05:10.500 Wow. 00:05:10.580 --> 00:05:14.640 So, yeah, I don't know what the exact release schedule of the final release is, but I think 00:05:14.640 --> 00:05:15.720 it's coming up pretty quickly. 00:05:15.720 --> 00:05:17.440 These things are looking pretty solid. 00:05:17.440 --> 00:05:21.860 Let me just give you a sense of some of the PEPs, Python enhancement proposals that are coming. 00:05:21.860 --> 00:05:28.620 First up, it seems like no programming language these days is content with their string formatting. 00:05:28.620 --> 00:05:32.860 And Python is like, look, we only have, like, eight ways to format strings. 00:05:32.860 --> 00:05:33.600 We need another. 00:05:33.600 --> 00:05:35.940 But this new way is actually pretty good. 00:05:35.940 --> 00:05:41.340 There's a PEP498, and what it is about is formatting string literals. 00:05:41.340 --> 00:05:45.680 So, imagine you've got a string, and normally you'd like, there's a variety of ways to do 00:05:45.680 --> 00:05:45.780 it. 00:05:45.780 --> 00:05:50.100 Maybe the newer way would be to do something like, say, I want to say, hi, my name is, 00:05:50.100 --> 00:05:52.060 and you have a variable called name, right? 00:05:52.060 --> 00:05:58.720 So, you might say, quote, hi, my name is curly bracket zero, quote, dot format, name, yeah? 00:05:58.720 --> 00:06:03.880 Well, it kind of takes this idea and just says, well, why do you have to do the dot format 00:06:03.880 --> 00:06:06.180 and use arguments and orders and then number them? 00:06:06.180 --> 00:06:08.800 Why don't you just put the name of the variable in the string? 00:06:08.800 --> 00:06:11.420 So, now you could say, hello, my name is curly name. 00:06:11.420 --> 00:06:15.820 And now, whatever the value of name is, if there's a variable that will be put into the 00:06:15.820 --> 00:06:17.580 string as if you did the first thing I said. 00:06:17.580 --> 00:06:18.800 Oh, that's really cool. 00:06:18.800 --> 00:06:19.860 Yeah, it's pretty cool. 00:06:19.860 --> 00:06:24.540 The only bummer is you have to indicate that it's this new format string. 00:06:25.000 --> 00:06:27.320 I think it's an F prefix on the string. 00:06:27.320 --> 00:06:28.180 Oh, okay. 00:06:28.180 --> 00:06:33.280 But, you know, because otherwise, you'd have like dictionary stuff mixing in, just for compatibility. 00:06:33.280 --> 00:06:35.260 It's got to have a little identifier. 00:06:35.260 --> 00:06:37.900 But other than that, yeah, it's a really cool way to format stuff. 00:06:37.900 --> 00:06:38.940 All right. 00:06:38.980 --> 00:06:45.780 So, we also have another easy to understand but really nice one, PEP515, which will let 00:06:45.780 --> 00:06:48.860 you put underscores in numerical literals. 00:06:48.860 --> 00:06:56.640 So, if you have a number like 1-0-0-0-0-0, and you look at it, is that a million? 00:06:56.640 --> 00:06:57.860 Is that 100,000? 00:06:57.860 --> 00:06:58.740 Is it 10 million? 00:06:58.900 --> 00:07:01.200 Like, it's hard to know like what the separators are. 00:07:01.200 --> 00:07:02.700 So, now you can put underscores. 00:07:02.700 --> 00:07:07.400 So, you could have like 1-0-0-0-0-0-0-0-0. 00:07:07.400 --> 00:07:11.000 And that would, it basically just ignores the underscores. 00:07:11.000 --> 00:07:13.920 But it allows you to visually see, oh, that's a million, not a hundred thousand. 00:07:13.920 --> 00:07:14.520 Something like that. 00:07:14.520 --> 00:07:15.260 Oh, that's kind of cool. 00:07:15.260 --> 00:07:15.980 Yeah, that's pretty cool. 00:07:15.980 --> 00:07:17.380 No, it's not going to be world changing. 00:07:17.380 --> 00:07:24.440 One thing that is more significant, I guess, is in Python 3.5, we have type annotations. 00:07:24.440 --> 00:07:25.220 Right? 00:07:25.220 --> 00:07:26.160 So, I could have a function. 00:07:26.160 --> 00:07:27.540 I could have a function. 00:07:27.860 --> 00:07:34.240 I could say it takes a, let's say, it says create, functions name is create, and it has 00:07:34.240 --> 00:07:35.540 a thing called entity. 00:07:35.540 --> 00:07:39.440 Well, if you were given that function, you could be like, I have no idea what this does. 00:07:39.440 --> 00:07:41.260 Like, entity, maybe that has to do with databases. 00:07:41.260 --> 00:07:46.760 But in Python 3.5, you could say colon, customer, where customer is like a class or something. 00:07:46.760 --> 00:07:52.880 And then the tooling and whatnot would know to give you the right auto-completion and various 00:07:52.880 --> 00:07:55.080 type checking and whatnot for that type. 00:07:55.080 --> 00:07:55.300 Right? 00:07:55.300 --> 00:07:57.500 But that only applied to functions. 00:07:57.620 --> 00:08:02.700 You couldn't put it on like variables and other types of class fields and other things 00:08:02.700 --> 00:08:03.780 that are outside of functions. 00:08:03.780 --> 00:08:08.180 So, this PEP 526 brings that to functions. 00:08:08.180 --> 00:08:09.560 That seems like obvious. 00:08:09.560 --> 00:08:11.780 I don't know why they didn't have that at the start. 00:08:11.780 --> 00:08:13.400 Yeah, it definitely seems obvious. 00:08:13.400 --> 00:08:17.020 So, you know, maybe you don't care too much, but tooling will care. 00:08:17.020 --> 00:08:18.160 Linters might care. 00:08:18.300 --> 00:08:21.160 So, like the tools you could possibly get better because of this. 00:08:21.160 --> 00:08:21.680 All right. 00:08:21.680 --> 00:08:24.340 So, we have 525 asynchronous generators. 00:08:24.340 --> 00:08:25.520 Async and away is awesome. 00:08:25.520 --> 00:08:27.400 Yield, yield from are awesome. 00:08:27.400 --> 00:08:29.580 But they were not friends previously. 00:08:30.440 --> 00:08:31.460 No, you couldn't use them together. 00:08:31.460 --> 00:08:35.720 So, you could either have an async coroutine or you could have a generator, but you couldn't have both. 00:08:35.720 --> 00:08:37.080 Now, you can have both. 00:08:38.340 --> 00:08:40.680 And similarly, we have asynchronous comprehensions. 00:08:40.680 --> 00:08:46.880 And, you know, actually one of the biggest things is the change to dictionaries coming in Python 3.6. 00:08:46.880 --> 00:08:47.660 What? 00:08:47.860 --> 00:08:53.500 Yeah, so you might think, well, Python has had dictionaries since from the very beginning. 00:08:53.500 --> 00:08:58.180 When you add fields or attributes to a class, it's actually stored in Dunderdict. 00:08:58.180 --> 00:09:00.840 I mean, dictionaries are, it's keyword values. 00:09:00.840 --> 00:09:04.320 Like, all over the place, dictionaries play a super important role. 00:09:04.320 --> 00:09:13.100 Well, in this release from 3.5 to 3.6, dictionaries are now 20% to 25% more memory efficient. 00:09:13.100 --> 00:09:15.100 They should be a little faster. 00:09:15.100 --> 00:09:17.200 They are ordered. 00:09:17.860 --> 00:09:21.460 So, the order that you put things in, they remember that, right? 00:09:21.460 --> 00:09:29.200 Like, if when you first started working with dictionaries, you're like, multiple dictionaries can have the fields show up at different times and different orders. 00:09:29.200 --> 00:09:30.180 It's bizarre, right? 00:09:30.180 --> 00:09:30.860 You can keep switching. 00:09:30.860 --> 00:09:32.440 Now, it's always consistent. 00:09:32.440 --> 00:09:36.440 The order dict part and making them fast is good. 00:09:36.440 --> 00:09:37.640 So, it's all good stuff. 00:09:37.640 --> 00:09:38.480 Yeah, it's all good stuff. 00:09:38.480 --> 00:09:40.240 We've got a new secrets module coming. 00:09:40.240 --> 00:09:44.680 So, you have cryptographically strong random number generators, windows. 00:09:45.000 --> 00:09:49.060 They've now marked the Python executable as long path aware. 00:09:49.060 --> 00:09:56.020 So, I don't know if you guys are aware, but Windows typically has, like, crummy 260 character path limits for a long time. 00:09:56.020 --> 00:09:58.880 There's a lot of legacy stuff that applies that to, like, newer code. 00:09:59.220 --> 00:10:05.600 So, now, long path limitations are gone on Windows, which, if you write code that has to run on Windows, you'll care a lot about that. 00:10:05.600 --> 00:10:05.920 Wow. 00:10:05.920 --> 00:10:10.040 Yeah, actually, I try to write code that I don't have to care about Windows, but... 00:10:10.040 --> 00:10:11.800 Yes, exactly. 00:10:11.800 --> 00:10:13.220 So, there's... 00:10:13.220 --> 00:10:18.760 If you go look through the link, the release notes, the documentation there, there's a lot more stuff. 00:10:18.760 --> 00:10:22.000 I'm scratching the surface on all the cool stuff coming in 3.6. 00:10:22.000 --> 00:10:28.140 So, if people need one more reason to upgrade from 2 to 3, well, here's, like, 20 or 30 more reasons. 00:10:28.140 --> 00:10:30.460 Yeah, and I like the peps that you talked about. 00:10:30.460 --> 00:10:34.400 You left the links to those particular peps in the show notes. 00:10:34.640 --> 00:10:35.480 So, that's great. 00:10:35.480 --> 00:10:36.600 Yeah, yeah, definitely check them out. 00:10:36.600 --> 00:10:36.960 Okay. 00:10:36.960 --> 00:10:38.380 Hey, Brian. 00:10:38.380 --> 00:10:39.020 Hey. 00:10:39.020 --> 00:10:41.500 Before we get to the next headline, let me tell you about Rollbar. 00:10:41.500 --> 00:10:42.680 Well, tell me about Rollbar. 00:10:42.680 --> 00:10:43.120 All right, man. 00:10:43.120 --> 00:10:46.580 So, Rollbar is sponsoring Python Bytes, and we're really excited about it. 00:10:46.580 --> 00:10:47.980 I use Rollbar for my website. 00:10:47.980 --> 00:10:56.220 Rollbar is a package you install in your Python web app, Pyramid, Flash, Django, whatever, and anytime there's an error, you get an immediate notification and detailed error reports. 00:10:56.220 --> 00:11:04.040 So, you know, even though the Talk Python websites handle almost 2 million dynamic HTTP requests per month, and they transfer, like, 4 to 5 terabytes of data, 00:11:04.160 --> 00:11:04.920 I'm not worried about them. 00:11:04.920 --> 00:11:05.280 Really? 00:11:05.280 --> 00:11:11.100 No, not really, because if something goes wrong, my Slack, my email, my phone, everything will be blown up with notifications. 00:11:11.100 --> 00:11:17.060 And, you know, I don't get many, but when they come in, like, all the info is there, so I often don't even have to debug it. 00:11:17.060 --> 00:11:18.020 I just go and fix the problem. 00:11:18.020 --> 00:11:18.880 That's pretty awesome, right? 00:11:18.880 --> 00:11:19.860 That's very awesome. 00:11:19.860 --> 00:11:20.720 Yeah, I love Rollbar. 00:11:20.720 --> 00:11:25.020 So, and the Python Bytes listeners, all you guys out there, you can have the same peace of mind. 00:11:25.020 --> 00:11:28.840 Just visit rollbar.com slash Python Bytes and sign up for the free tier. 00:11:28.840 --> 00:11:32.720 You get, like, 300,000 free errors tracked, although I really hope you don't have that many. 00:11:33.680 --> 00:11:34.160 Definitely. 00:11:34.160 --> 00:11:36.020 You should do more testing if you do. 00:11:36.020 --> 00:11:36.940 You definitely should. 00:11:38.260 --> 00:11:45.120 Well, next up for me, I am a sucker for, like, I really like efficiency, developer efficiency. 00:11:45.120 --> 00:11:47.020 That's always kind of been important to me. 00:11:47.020 --> 00:11:53.000 And part of that is being able to set up your personal development environment to help you succeed. 00:11:53.000 --> 00:11:57.120 And I know it's different from everybody, and I'm always tweaking mine. 00:11:57.480 --> 00:11:59.380 I like articles when people write about them. 00:11:59.380 --> 00:12:06.800 So there's an article by Dougal, I think, Dougal Matthews, called Create an Excellent Python Dev Environment. 00:12:07.640 --> 00:12:12.060 And he goes through installing Python, but everybody knows how to do that. 00:12:12.060 --> 00:12:18.280 But he's got some goals of, like, don't muck with the system Python and set up virtual environments easy. 00:12:18.280 --> 00:12:20.260 And it's interesting. 00:12:20.660 --> 00:12:27.820 One of the things I think is interesting about this article is to start off the bat saying why he has particular goals for why he's chosen things. 00:12:27.820 --> 00:12:28.880 And that's kind of neat. 00:12:28.880 --> 00:12:29.420 Yeah, that's cool. 00:12:29.420 --> 00:12:31.860 Because you might look at it and go, I would never do that. 00:12:31.960 --> 00:12:33.720 But maybe your goals are different than his. 00:12:33.720 --> 00:12:36.280 And you can really understand where he's coming from because of that. 00:12:36.280 --> 00:12:36.860 That's cool. 00:12:36.860 --> 00:12:37.160 Yeah. 00:12:37.160 --> 00:12:45.080 Actually, the first part confused me because he was covering a project that I'd never heard of called pyenv or P-Y-E-N-V. 00:12:45.080 --> 00:12:52.400 I'm more used to V-E-N-V, which just comes in 3.6 or virtual environment. 00:12:52.400 --> 00:12:56.740 So this is something different, and I just will have to check it out. 00:12:56.740 --> 00:13:01.440 But it's something like virtual environments, but it's independent of Python. 00:13:01.600 --> 00:13:03.040 It sets them up separate, I guess. 00:13:03.040 --> 00:13:03.880 I don't know. 00:13:03.880 --> 00:13:04.220 Yeah. 00:13:04.220 --> 00:13:06.820 But I haven't used that much either, so I might be a little off here. 00:13:06.820 --> 00:13:11.620 But I think it's kind of like for managing and creating and activating different virtual environments. 00:13:11.620 --> 00:13:14.020 It's like your virtual environment manager. 00:13:14.020 --> 00:13:14.600 Okay. 00:13:14.600 --> 00:13:15.400 I think. 00:13:15.400 --> 00:13:16.080 Yeah. 00:13:16.080 --> 00:13:24.880 Next is a pyenv virtualenv, which is apparently similar to virtualenv wrapper, which a lot of people use. 00:13:24.880 --> 00:13:29.140 I don't use either of those, but I still don't get what they're for. 00:13:29.740 --> 00:13:31.620 Straight virtual environments work fine. 00:13:31.620 --> 00:13:34.300 I don't understand what I need more for. 00:13:34.300 --> 00:13:35.740 You have different goals. 00:13:35.740 --> 00:13:36.960 Yeah, that's probably it. 00:13:36.960 --> 00:13:42.560 The next thing he talks about is a thing called Pipsy, which I hadn't heard of, and I just used it today. 00:13:42.760 --> 00:13:50.240 It's a tool to let you install Python-based command line utilities in their own virtual environments so that you can use them. 00:13:50.240 --> 00:13:54.140 You can just set your path to them so you can use them on the command line from anywhere. 00:13:54.140 --> 00:13:59.760 That's really cool just to have like these little virtual environments just for a command line utility. 00:13:59.760 --> 00:14:00.640 That's really cool. 00:14:00.640 --> 00:14:02.340 I never really thought of doing it that way. 00:14:02.340 --> 00:14:03.240 That's great. 00:14:03.240 --> 00:14:09.900 When I was talking in one of the interviews I've done, I heard about more people using Atom than before. 00:14:09.900 --> 00:14:15.440 And I tried to set up Atom and I needed to give it a path to Flake 8. 00:14:15.640 --> 00:14:19.660 And I'm like, oh, I'll use Pipsy to set up this so that you can see Flake 8. 00:14:19.660 --> 00:14:20.860 So I've done that. 00:14:20.860 --> 00:14:21.160 Oh, nice. 00:14:21.160 --> 00:14:23.460 But he does talk about with Pipsy. 00:14:23.460 --> 00:14:30.520 He usually includes talks for testing multiple environments, which I highly recommend. 00:14:31.300 --> 00:14:36.400 Flake Docs, which is a static site generator documentation thingy. 00:14:36.400 --> 00:14:37.740 I've never used it. 00:14:37.740 --> 00:14:40.140 Get Review, which I would totally use. 00:14:40.140 --> 00:14:44.800 It's a Garrett integration for Git, but I don't use Git right now, but at work. 00:14:44.800 --> 00:14:50.500 And I actually do code reviews on my own code in my free time. 00:14:50.500 --> 00:14:56.020 And then Flake 8, of course, which is my favorite, recommended, way too static in the analyzed stuff. 00:14:56.640 --> 00:15:05.760 And then, as a side note, one of the things he was talking about for this Pi A&V is because it's compatible with Fish, 00:15:05.760 --> 00:15:09.420 which is a different shell that I've never heard of. 00:15:09.420 --> 00:15:10.600 I use Bash. 00:15:10.600 --> 00:15:12.540 I tried Z-Shell for a while. 00:15:12.540 --> 00:15:13.740 I'm always used. 00:15:13.740 --> 00:15:16.180 I think it's fun to try new shells. 00:15:16.180 --> 00:15:17.920 So maybe I'll give it a shot. 00:15:17.920 --> 00:15:19.460 Yeah, it's definitely worth checking out, Fish. 00:15:19.460 --> 00:15:20.200 That sounds cool. 00:15:20.200 --> 00:15:21.940 I use Z-Shell as well. 00:15:21.940 --> 00:15:26.320 I just actually formatted my computer and I'm like, you know, I might try a different shell this time. 00:15:26.400 --> 00:15:27.540 And I set everything up. 00:15:27.540 --> 00:15:28.120 So that's cool. 00:15:28.120 --> 00:15:28.920 I'll check out Fish. 00:15:28.920 --> 00:15:32.140 I do love to see the way people put these environments together. 00:15:32.140 --> 00:15:35.340 And I think it really can help people who are new. 00:15:35.340 --> 00:15:37.780 It can help you discover things you don't know about, like Pipsy. 00:15:37.780 --> 00:15:38.820 That's really great. 00:15:38.820 --> 00:15:44.820 I was just stuck in traffic today, this morning, and was thinking for some reason about this stuff. 00:15:44.820 --> 00:15:49.300 You know, other people, I don't know what they dream about, but this is what I was daydreaming about. 00:15:49.300 --> 00:15:57.640 I was thinking, you know, I might try switching to Conda instead of pip and try using Conda for managing all these environments. 00:15:57.640 --> 00:16:02.920 I really like the way that Conda, like, vets the packages and pre-compiles them for you. 00:16:02.920 --> 00:16:03.960 I was reading about something. 00:16:03.960 --> 00:16:10.460 It was like, well, as long as you have this compiler set up, it'll probably be fine, but it might not work so well. 00:16:10.460 --> 00:16:11.180 I'm like, you know what? 00:16:11.500 --> 00:16:15.320 Maybe I should just use Conda, and, like, all those problems are solved by the Continuum guys. 00:16:15.320 --> 00:16:20.900 And so I'm also doing a lot of virtual environments with Python 3, V, and V. 00:16:20.900 --> 00:16:27.220 And the one thing that I like that I've stopped using the main Python REPL, and I'm using PtPython. 00:16:27.220 --> 00:16:28.260 Do you know PtPython? 00:16:28.260 --> 00:16:30.340 PtPython. 00:16:30.340 --> 00:16:31.020 No, I don't. 00:16:31.020 --> 00:16:42.420 So PtPython is basically the regular REPL, but it has a lot better editing and history and auto-completion and all sorts of stuff for what you can do. 00:16:42.420 --> 00:16:47.860 So, like, for example, if you type in a function in the regular REPL, you know, it's like three lines with indentation or whatever. 00:16:47.860 --> 00:16:52.820 If you want to edit it, you've got to remember to, like, always replay them in the right order. 00:16:52.820 --> 00:16:57.620 You know, up arrow four times, enter, up arrow three times, make the change, you know, that kind of stuff. 00:16:57.960 --> 00:17:02.860 This will, like, if you hit up arrow for code suites, it'll bring the whole thing back and you can edit it, stuff like that. 00:17:02.860 --> 00:17:03.400 Oh, okay. 00:17:03.400 --> 00:17:05.520 Do you work in the REPL very much? 00:17:05.520 --> 00:17:06.520 Not too much. 00:17:06.520 --> 00:17:07.640 Usually I'm in some kind of editor. 00:17:07.640 --> 00:17:10.320 But when I am there, I've been moving to PtPython. 00:17:10.320 --> 00:17:10.800 That's pretty cool. 00:17:10.800 --> 00:17:12.040 I think I'll check it out. 00:17:12.040 --> 00:17:13.420 Yeah, yeah, check it out. 00:17:13.420 --> 00:17:14.120 So what do you got next? 00:17:14.120 --> 00:17:16.280 Well, a lot of people have been checking out Python lately. 00:17:16.280 --> 00:17:18.840 And there was an interesting article. 00:17:18.840 --> 00:17:20.260 Is it an article? 00:17:20.260 --> 00:17:27.440 It was an article that's posted as a GitHub repository, which is accompanied by a Go program that's generated a bunch of statistics 00:17:27.440 --> 00:17:28.100 and graphs. 00:17:28.100 --> 00:17:35.640 And the thing I'm actually linking to is a Reddit article with, like, 350 upvotes and tons of comments. 00:17:35.640 --> 00:17:37.780 So you can check out the conversation. 00:17:37.780 --> 00:17:39.680 But the headline is awesome. 00:17:39.680 --> 00:17:41.880 GitHub language statistics. 00:17:41.880 --> 00:17:46.740 Python is the second most popular language on GitHub for active repositories. 00:17:46.740 --> 00:17:47.640 That's awesome. 00:17:47.640 --> 00:17:47.980 Yeah. 00:17:47.980 --> 00:17:52.600 I mean, Python's growth is just continuing and expanding. 00:17:52.600 --> 00:17:55.300 And it's such a cool time to be involved in the language. 00:17:55.300 --> 00:17:58.180 And here's just one more stat to back that up. 00:17:58.180 --> 00:17:58.640 Yeah. 00:17:58.640 --> 00:18:03.360 Looks like the graphs you have to click through from the Reddit to the GitHub page. 00:18:03.800 --> 00:18:04.360 Yeah, yeah. 00:18:04.360 --> 00:18:05.460 So I'm linking to both. 00:18:05.460 --> 00:18:05.740 Okay. 00:18:05.880 --> 00:18:15.840 So they say, we're going to study active repositories because it doesn't make any sense to think about GitHub statistics if something was put there five years ago and hasn't been touched. 00:18:15.840 --> 00:18:16.600 All right. 00:18:16.600 --> 00:18:19.000 So they said, let's consider the set of active repositories. 00:18:19.000 --> 00:18:22.520 Those are created or updated during the period. 00:18:22.520 --> 00:18:28.020 And the period is like a bunch of dates, like, throughout the last three years, you'll see when you get there. 00:18:28.720 --> 00:18:30.460 And it has to have at least one star. 00:18:30.460 --> 00:18:32.580 So people have to, somebody has to care about it. 00:18:32.580 --> 00:18:35.960 Somebody has to care enough about it to have forked it. 00:18:35.960 --> 00:18:38.220 And it must be more than 10K. 00:18:38.220 --> 00:18:39.040 Right. 00:18:39.040 --> 00:18:45.280 So it can't just be like, well, I put up this one file and somebody forked it or, you know, something silly like that. 00:18:45.280 --> 00:18:46.520 It's got to be like a real project. 00:18:46.520 --> 00:18:51.660 So if you take all of those together, JavaScript turns out to be the most popular. 00:18:51.660 --> 00:18:55.700 But JavaScript, I'm sure, is highly overcounted. 00:18:55.800 --> 00:19:03.020 I'm pretty sure that's generally true on GitHub statistics because almost every one of my Python projects has some JavaScript. 00:19:03.020 --> 00:19:04.080 You know what I mean? 00:19:04.080 --> 00:19:04.580 Yeah. 00:19:04.580 --> 00:19:08.440 I mean, since it's the front end, it's almost every project has it. 00:19:08.440 --> 00:19:09.000 Right. 00:19:09.000 --> 00:19:15.920 Almost any web project in any language is going to be counted as JavaScript to some degree in the language category. 00:19:15.920 --> 00:19:22.740 And so I feel like JavaScript, while it is extremely popular, I think it's massively overcounted in these types of stats. 00:19:22.740 --> 00:19:25.500 And it seems to appear that way in the graph. 00:19:26.180 --> 00:19:30.060 But so Python displaced Java, which we can all cheer for that. 00:19:30.060 --> 00:19:30.300 Right. 00:19:30.300 --> 00:19:30.800 That's awesome. 00:19:30.800 --> 00:19:31.040 Yeah. 00:19:31.040 --> 00:19:34.860 But let me give you some stats that are pretty interesting that will I think this might blow your mind. 00:19:34.860 --> 00:19:41.700 So back in November 2014, there were 1,790 active repositories by the four criteria above. 00:19:41.700 --> 00:19:42.220 Yeah. 00:19:42.220 --> 00:19:43.120 That were Python. 00:19:43.120 --> 00:19:43.980 This is just Python. 00:19:43.980 --> 00:19:47.720 November 2015, there was 2,500. 00:19:48.160 --> 00:19:58.060 And if you look throughout the year of 2015 and early 2016, there's, it would vary, but it's like 2,000 to 2,500, 2,600. 00:19:58.060 --> 00:20:04.620 By November 2016, there's 10,944 active repositories. 00:20:04.980 --> 00:20:06.980 It's just like, it's growing like crazy. 00:20:06.980 --> 00:20:07.440 Yeah. 00:20:07.440 --> 00:20:08.560 I love seeing that. 00:20:08.560 --> 00:20:23.800 And I think one of the things I like, I think has changed in that timeframe is the, I don't know if it can be attributed to this, but the cookie cutter project has made it a lot easier for people to set up something to share on GitHub. 00:20:23.800 --> 00:20:24.200 Yeah. 00:20:24.200 --> 00:20:25.860 Cookie cutter is really awesome. 00:20:25.860 --> 00:20:27.640 If you guys don't know about cookie cutter, check it out. 00:20:27.640 --> 00:20:28.760 It's a cool project. 00:20:28.760 --> 00:20:30.060 I'm sure it's not hurting. 00:20:30.060 --> 00:20:30.480 Yeah. 00:20:30.480 --> 00:20:31.900 Anyway, those are, that's good. 00:20:31.900 --> 00:20:36.160 Also, it makes me think that I spent the right time learning a new language. 00:20:36.160 --> 00:20:38.120 So I started from C++. 00:20:38.120 --> 00:20:39.300 Yeah, absolutely. 00:20:39.300 --> 00:20:41.420 You know, it's good to be in a place that's growing. 00:20:41.420 --> 00:20:45.020 Now, I mean, obviously take these stats, they're with a grain of salt. 00:20:45.020 --> 00:20:48.340 They're sliced in all these various criteria and so on. 00:20:48.340 --> 00:20:56.020 So they might not be perfect, but they give a glimpse into a world that is doing very well and is very fun to be part of. 00:20:56.020 --> 00:20:57.280 So I'm happy to see it. 00:20:57.280 --> 00:20:57.540 Okay. 00:20:57.540 --> 00:21:03.820 We're up to my number three pick, which is handling Unicode strings in Python. 00:21:03.820 --> 00:21:08.480 It is from, I know I'm going to get this name wrong, Wan Li Song, I think. 00:21:08.480 --> 00:21:10.820 But we'll link it, of course, in the show notes. 00:21:11.060 --> 00:21:18.540 I like it because it's a nice article to introduce people about the concepts of text representation in Python. 00:21:18.540 --> 00:21:26.040 And this comes up, at least, it hurts my head sometimes because I came up with the 2.7 Python world. 00:21:26.040 --> 00:21:32.120 And I think anybody that learned with 2.7 and had to switch to a more recent 3x version, 00:21:32.120 --> 00:21:35.820 sometimes it's hard to understand how the switch happens. 00:21:35.920 --> 00:21:39.760 And there's a nice table for some of the things that are different. 00:21:39.760 --> 00:21:50.040 And then it goes through specifics of dealing with Unicode in things like I.O. boundaries to databases or services. 00:21:50.040 --> 00:21:57.120 And then also a few other examples are dealing with it with logging, with JSON encoding, and with Redis even. 00:21:57.860 --> 00:22:04.340 A nice pointer to a 2012 article from Ned Batchelder called Pragmatic Unicode, which I hadn't read before. 00:22:04.340 --> 00:22:07.440 So I learned a lot about Unicode in this last week. 00:22:07.440 --> 00:22:07.800 Oh, yeah. 00:22:07.800 --> 00:22:08.480 That's great. 00:22:08.480 --> 00:22:10.640 If you have to juggle that stuff, it can be tricky. 00:22:10.640 --> 00:22:14.580 I remember talking to some of the Web Foundation guys. 00:22:14.580 --> 00:22:22.380 I think it was Kenneth Reitz and Requests, but it could have been Armin Roeniger and Flask. 00:22:22.380 --> 00:22:23.100 I'm not sure. 00:22:23.100 --> 00:22:23.880 I think it was Kenneth. 00:22:24.320 --> 00:22:32.260 Anyway, seeing that one of the most challenging things of upgrading their projects from 2 to 3 or supporting 3, let's say, 00:22:32.260 --> 00:22:38.600 is the dramatically different way that bytes go to strings and all of this kind of stuff. 00:22:38.600 --> 00:22:45.260 So, yeah, if you've got to upgrade something that's 2 to support 3, be really careful with the strings. 00:22:45.560 --> 00:22:56.320 Yeah, and this is another one of those, I'm going to bookmark it, and if the next time I come up with an issue, I'll look through this, see if it can help me figure out how to fix it. 00:22:56.320 --> 00:22:56.660 Yeah. 00:22:56.660 --> 00:22:57.340 Awesome. 00:22:57.340 --> 00:22:57.780 All right. 00:22:57.780 --> 00:22:59.300 What do you got as your last one, Michael? 00:22:59.300 --> 00:23:02.740 My last one, I think this one might be a little surprising for you. 00:23:02.740 --> 00:23:03.060 Let's see. 00:23:03.140 --> 00:23:10.080 So, I've asked many people what their favorite editor is over at Talk Python To Me, and I've heard many answers. 00:23:10.080 --> 00:23:15.340 You know, it would be fun to go back and actually do some data analysis and graphs or whatever, right? 00:23:15.340 --> 00:23:19.000 But I would say Sublime Text, extremely popular. 00:23:19.000 --> 00:23:22.140 Emacs, very popular. 00:23:22.140 --> 00:23:25.260 Vim, I think Vim might be slightly beating Emacs. 00:23:25.260 --> 00:23:27.160 PyCharm is pretty popular. 00:23:27.400 --> 00:23:29.140 People hear me go on and on about PyCharm. 00:23:29.140 --> 00:23:30.180 I love PyCharm. 00:23:30.180 --> 00:23:30.620 Really? 00:23:30.620 --> 00:23:31.560 I didn't know that. 00:23:31.560 --> 00:23:31.840 Yeah. 00:23:31.840 --> 00:23:35.480 Yeah, and people, most people don't know this about me, but I actually do use it now. 00:23:35.480 --> 00:23:37.140 I do love it a lot. 00:23:37.140 --> 00:23:47.480 But one thing I came across with was I was fooling around with Visual Studio Code, and this is not like Visual Studio from Windows, the big .NET thing. 00:23:47.480 --> 00:23:49.460 This is like a lightweight editor. 00:23:49.460 --> 00:23:53.660 It's based on, I think, the same underlying stuff as Atom. 00:23:53.660 --> 00:23:54.040 Okay. 00:23:54.040 --> 00:24:00.980 It's using the Chrome as its underlying engine, and it's based on some client-side HTML stuff. 00:24:00.980 --> 00:24:08.320 Anyway, it's a free editor that's pretty cool, and it's growing quite a bit in terms of its extensions you can get for it. 00:24:08.320 --> 00:24:12.800 It's got, like, cool Git integration, and now it's getting better Python integration. 00:24:12.800 --> 00:24:21.500 So my pick is this thing called the Python extension for Visual Studio Code, and it runs on Mac and Windows and Linux and so on. 00:24:22.100 --> 00:24:23.960 And I have a link to the one there. 00:24:23.960 --> 00:24:34.160 And what's really interesting is, well, the bunch of features, which I'll tell you, but if I had to ask you, Brian, how many times do you think this thing has been downloaded? 00:24:34.160 --> 00:24:35.620 23. 00:24:35.620 --> 00:24:37.660 23 is good. 00:24:37.660 --> 00:24:43.080 Well, I would guess thousands, maybe 20, 30,000 times, something like this, right? 00:24:43.120 --> 00:24:46.500 Like, okay, how many people are installing full Python support? 00:24:46.500 --> 00:24:58.920 This is, like, not just standard completion, but it, like, reads, if you're writing a package, it, like, understands your package and will tell you exactly what all the names of all the elements symbolically. 00:24:58.920 --> 00:25:02.420 In your package, it'll do, like, AST-based refactoring. 00:25:02.420 --> 00:25:03.760 Like, really cool stuff, right? 00:25:04.240 --> 00:25:07.360 Anyway, 850,000 installs. 00:25:07.360 --> 00:25:09.140 That's actually incredible. 00:25:09.140 --> 00:25:10.500 Now I want to go try it. 00:25:10.500 --> 00:25:17.400 Yeah, I mean, when you think of Python editors, almost a million people installed this Python support for their editor. 00:25:17.400 --> 00:25:25.060 Now, of course, not every one of them is doing Python all the time, and there's not a one-to-one mapping between developers and editors. 00:25:25.200 --> 00:25:28.040 But this is, like, way more popular than I realized. 00:25:28.040 --> 00:25:29.500 And so I thought, well, why don't I play with it? 00:25:29.500 --> 00:25:31.660 So I played with it this week, and I'm pretty impressed. 00:25:31.660 --> 00:25:34.080 For, like, lightweight stuff, I think this is my new editor. 00:25:34.080 --> 00:25:34.780 Oh, okay. 00:25:34.780 --> 00:25:36.760 I was just actually picking it. 00:25:36.760 --> 00:25:40.280 I installed Adam this morning, and maybe I'll try this one out as well. 00:25:40.280 --> 00:25:43.240 Yeah, it's really similar to Adam, actually, so it's worth giving it a try. 00:25:43.240 --> 00:25:48.400 So it has linting, including a bunch of linters you can configure, including Flake 8. 00:25:48.400 --> 00:25:53.480 It has full-on auto-completion, as well as support for PEP 484. 00:25:53.580 --> 00:25:55.220 I think that's the type hint. 00:25:55.220 --> 00:26:04.060 It has Jupyter support, intending, code formatting, refactoring, like I said, code navigation, debugging. 00:26:04.060 --> 00:26:08.900 You can remotely debug over SSH to, like, a Flask app. 00:26:08.900 --> 00:26:11.660 I mean, that's pretty serious for this little plug-in, right? 00:26:11.660 --> 00:26:12.260 That's awesome. 00:26:12.260 --> 00:26:16.040 Unit tests, all the various tests you're talking about, lots of good stuff. 00:26:16.040 --> 00:26:22.940 So anyway, I thought this is kind of one of the unsung heroes of the editors, so I thought I'd highlight it. 00:26:23.280 --> 00:26:23.980 Yeah, cool. 00:26:23.980 --> 00:26:28.300 And maybe the next time you ask somebody, they'll say, I use code. 00:26:28.300 --> 00:26:30.140 Oh, yeah, I use Visual Studio Code all the time. 00:26:30.140 --> 00:26:31.520 Anyway, yeah, it's pretty cool. 00:26:31.520 --> 00:26:33.680 So I'm excited to try it out, at least. 00:26:33.680 --> 00:26:35.320 Okay, well, I think I'll try it out, too. 00:26:35.740 --> 00:26:38.160 And that brings us to the end. 00:26:38.160 --> 00:26:41.400 But we do like to catch up with what both of us are up to. 00:26:41.400 --> 00:26:44.000 So, Michael, what are you up to lately? 00:26:44.000 --> 00:26:48.460 Well, I've been continuing to crank out the Talk Python To Me episodes. 00:26:48.460 --> 00:26:58.080 So the last one I just released was parsing horrible things with Python, which I wanted to make sure I pointed out here, because I think that's a really interesting tie into your first pick of the week. 00:26:58.520 --> 00:27:04.740 Because it's another way to parse horrible things that I think is really actually quite powerful and interesting. 00:27:04.740 --> 00:27:08.600 So anyway, I released that with Eric Rose, and that was cool. 00:27:08.600 --> 00:27:10.180 That was a really interesting episode. 00:27:10.180 --> 00:27:12.160 I really enjoyed it. 00:27:12.160 --> 00:27:14.380 Eric is obviously a brilliant guy. 00:27:14.380 --> 00:27:15.720 So that was good. 00:27:15.820 --> 00:27:16.400 Yeah, thanks a lot. 00:27:16.400 --> 00:27:19.140 Yeah, he was a great guest and definitely enjoyed talking to him. 00:27:19.140 --> 00:27:25.240 You last week had asked me if Awesome Python, the GitHub thing, was the same as the Awesome Python newsletter. 00:27:25.240 --> 00:27:26.780 And I said, I think so. 00:27:26.780 --> 00:27:29.400 And now I think I might be wrong. 00:27:29.400 --> 00:27:37.280 No, in fact, the Awesome Python newsletter comes from python.libhunt.com, which is a really cool place for Python news. 00:27:37.280 --> 00:27:43.580 And I think one or two of the news items throughout the podcast, not this one, but over all of them, I've gotten from that place. 00:27:43.580 --> 00:27:43.980 Okay. 00:27:44.400 --> 00:27:46.020 So, yeah, that's my picks. 00:27:46.020 --> 00:27:47.000 What's up with me? 00:27:47.000 --> 00:27:48.060 Python is so awesome. 00:27:48.060 --> 00:27:49.560 We like to slap it on everything. 00:27:49.560 --> 00:27:51.780 It's awesome, yeah. 00:27:51.780 --> 00:27:52.740 How about you? 00:27:52.740 --> 00:27:53.140 What are you up to? 00:27:53.140 --> 00:27:54.620 Man, I've been doing a lot of writing. 00:27:54.620 --> 00:27:59.920 I've got a deadline, an editor deadline, in about a week, actually exactly a week from today. 00:27:59.920 --> 00:28:07.920 Because I'm trying to put on full steam, and it's the pytest book, and I'm trying to get it ready so that it can be printable, 00:28:07.920 --> 00:28:13.780 and I can take a stack of copies with me to PyCon in 2017, in May. 00:28:14.280 --> 00:28:15.640 So that's what I've been working on. 00:28:15.640 --> 00:28:21.060 The last episode of Test and Code is recorded and partly edited. 00:28:21.060 --> 00:28:24.920 This was number 25 with Dave Hunt about Selenium. 00:28:24.920 --> 00:28:30.120 And there's some really good content mixed in with some really stupid questions that I've asked. 00:28:30.340 --> 00:28:34.720 So I need to go and cut out the stupid questions, and then it'll be good to go. 00:28:34.720 --> 00:28:36.740 Hopefully we'll get that out in the next couple days. 00:28:36.740 --> 00:28:42.100 And then I'm really excited about an interview tomorrow scheduled. 00:28:42.100 --> 00:28:45.880 Hopefully it goes through with a person called David Hussman. 00:28:46.500 --> 00:28:54.100 He runs a place called Dev Jam Studios, and he also talks about Agile and goes around and speaks to people. 00:28:54.100 --> 00:28:57.240 And he's a really good speaker, so looking forward to talking to him. 00:28:57.240 --> 00:28:58.120 Yeah, that'll be awesome. 00:28:58.120 --> 00:29:02.540 Kind of a slightly above-the-code talk about all the testing and whatnot, right? 00:29:02.640 --> 00:29:05.040 Yeah, and I don't even know if he'll get into testing. 00:29:05.040 --> 00:29:16.480 One of the things he likes to talk about lately is story mapping, which is sort of high-level planning for an entire project above the writing stories level. 00:29:16.480 --> 00:29:18.900 And that's pretty neat. 00:29:18.900 --> 00:29:19.500 Yeah, that's cool. 00:29:19.500 --> 00:29:20.660 Definitely precedes code. 00:29:21.380 --> 00:29:21.860 Yeah. 00:29:21.860 --> 00:29:30.920 Well, anyway, I really enjoyed talking with you this week, and look forward to seeing what cool stuff people put out in the upcoming week. 00:29:30.920 --> 00:29:31.760 Yeah, thanks, Brian. 00:29:31.760 --> 00:29:34.940 I enjoyed it as well, and like always, I learned about some cool new things. 00:29:34.940 --> 00:29:36.460 I'm definitely checking out Pipsy. 00:29:36.460 --> 00:29:40.160 And thank you, everyone, for listening, and we will see you next week.