WEBVTT 00:00:00.080 --> 00:00:05.240 Hello and welcome to Python Bytes, where we deliver Python news and headlines directly to your earbuds. 00:00:05.240 --> 00:00:09.940 This is episode 137, recorded June 26th, 2019. 00:00:09.940 --> 00:00:10.780 I'm Michael Kennedy. 00:00:10.780 --> 00:00:11.620 And I'm Brian Okken. 00:00:11.620 --> 00:00:13.940 And this episode is brought to you by Rollbar. 00:00:13.940 --> 00:00:15.620 I'll tell you all more about them later. 00:00:15.620 --> 00:00:18.860 For now, Brian, I always wonder about, you know, 00:00:18.860 --> 00:00:21.760 you hear that Python is an efficient and expressive language, 00:00:21.760 --> 00:00:24.160 and if you write code in C++, it'll be a lot longer. 00:00:24.160 --> 00:00:25.720 But, you know, how can you quantify that? 00:00:25.720 --> 00:00:29.240 Well, you can set up a whole bunch of people to write the same thing 00:00:29.240 --> 00:00:30.580 in a whole bunch of languages. 00:00:30.580 --> 00:00:33.720 Well, that's awesome that people did that. 00:00:33.720 --> 00:00:36.380 It seems like a lot of work, but yeah, I guess that's cool. 00:00:36.380 --> 00:00:37.300 Tell us about it. 00:00:37.300 --> 00:00:38.360 Like, this is your first item, right? 00:00:38.360 --> 00:00:46.000 So this is an article called Comparing the Same Project in Rust, Haskell, C++, Python, Scala, and 00:00:46.000 --> 00:00:47.420 how do you pronounce that? 00:00:47.420 --> 00:00:48.000 OCaml? 00:00:48.000 --> 00:00:49.200 O-C-A-M-L? 00:00:49.200 --> 00:00:50.080 OCaml, I think, yeah. 00:00:50.080 --> 00:00:53.160 So this was written up by Christian Hume, 00:00:53.160 --> 00:00:57.880 and this is about a university project, which is kind of a neat project. 00:00:58.480 --> 00:01:03.200 Basically, they had to implement a big chunk of Java. 00:01:03.200 --> 00:01:09.340 So it's a Java to x86 compiler as part of a compiler class. 00:01:09.340 --> 00:01:14.700 And they were basically had to set up, get up teams, teams of people to do it, 00:01:14.700 --> 00:01:16.620 and they could pick any language they wanted, 00:01:16.620 --> 00:01:20.680 which is kind of cool because, you know, people be better at different languages. 00:01:20.680 --> 00:01:21.440 Yeah. 00:01:21.440 --> 00:01:22.600 So let them use what they're good at. 00:01:22.660 --> 00:01:26.820 Yeah, let them use what they're good at because then they'll do it properly and not just try to cram it one. 00:01:26.820 --> 00:01:29.960 They'll have the most efficient use of that language for sure. 00:01:29.960 --> 00:01:33.620 Up to three people on a team, and it was a multi-month project. 00:01:33.620 --> 00:01:35.720 And then also tests were added. 00:01:35.920 --> 00:01:40.520 So this is kind of a neat part of the process, which I think is an awesome way to teach people, 00:01:40.520 --> 00:01:45.500 is have some published tests of, like, you're going to have to run these test cases and they have to pass, 00:01:45.500 --> 00:01:52.580 but then also have some secret ones where people don't, they don't know what tests are going to be tested against it, 00:01:52.960 --> 00:01:59.760 which is kind of nice because people will have to be able to make sure their implementation is robust without knowing, 00:01:59.760 --> 00:02:01.580 without the test cases. 00:02:01.580 --> 00:02:02.400 It's kind of neat. 00:02:02.400 --> 00:02:03.060 Yeah, that's cool. 00:02:03.060 --> 00:02:06.200 So I do love it that there's unknown tests. 00:02:06.200 --> 00:02:07.920 Like, these are the specifications. 00:02:07.920 --> 00:02:12.740 You can kind of get close with these tests, but to pass, you actually have to just work. 00:02:12.740 --> 00:02:14.680 That's totally like real life, you know. 00:02:14.680 --> 00:02:19.660 You'll write down some specifications, and there's some specifications that are not written down. 00:02:19.660 --> 00:02:21.340 They're just supposed to be known. 00:02:21.340 --> 00:02:24.820 And then there's other things that people, once they see the implementation, they go, 00:02:24.820 --> 00:02:26.720 oh, yeah, I wish it did this also. 00:02:26.720 --> 00:02:28.700 So I think that's a cool idea. 00:02:28.700 --> 00:02:33.280 And they weren't shooting for lines of code or anything complexity. 00:02:33.280 --> 00:02:35.540 They were just trying to finish the project. 00:02:35.540 --> 00:02:37.320 So this analysis was done after. 00:02:37.320 --> 00:02:43.180 They had a Rust, a baseline implementation written by two people that were familiar with Rust, 00:02:43.180 --> 00:02:45.580 and then they compared everything against that. 00:02:45.580 --> 00:02:50.020 So there was another Rust team that chose different design decisions, 00:02:50.020 --> 00:02:53.880 and it took, they had like three times the code. 00:02:53.880 --> 00:02:56.060 So these are all just comparing lines of code. 00:02:56.060 --> 00:03:01.740 The Haskell implementation was about equal, but depending on how you measure it, 00:03:01.740 --> 00:03:04.640 one to 1.6 times the code. 00:03:04.640 --> 00:03:06.280 Same for the OCaml. 00:03:06.280 --> 00:03:11.400 C++ was bigger, about 1.4 times the baseline. 00:03:11.400 --> 00:03:17.000 And Scala was a little bit less with about 70% of lines of code. 00:03:17.360 --> 00:03:22.600 The big outlier was Python, which had a lot of standouts. 00:03:22.600 --> 00:03:29.340 Python implementation was half the size, approximately, plus written by one person, 00:03:29.340 --> 00:03:35.160 and had extra features past all the secret tests, plus others. 00:03:35.220 --> 00:03:40.340 Somebody excellent at programming, of course, used some of the meta programming techniques. 00:03:40.340 --> 00:03:43.440 And anyway, kind of a fun article. 00:03:43.440 --> 00:03:49.320 One of the things I forgot to mention, one of the hindrances was they were only supposed to use standard libraries, 00:03:49.320 --> 00:03:54.720 no extra parsing, and then not any parsing libraries, even if they were part of the standard library. 00:03:55.080 --> 00:03:59.620 So even the parsing had to be kind of built up from scratch. 00:03:59.620 --> 00:04:00.360 Yeah, how interesting. 00:04:00.360 --> 00:04:04.280 I wonder if that would make things like Python even better possible. 00:04:04.280 --> 00:04:05.700 I don't know about Rust, maybe as well. 00:04:05.700 --> 00:04:08.680 But like C++ doesn't have parsing libraries built in that I know of. 00:04:08.680 --> 00:04:09.660 Things like that, right? 00:04:09.660 --> 00:04:13.320 There's a lot of mini-language parsing libraries around Python. 00:04:13.320 --> 00:04:18.720 So it'd be interesting to do that with, you know, go wild and use whatever's available. 00:04:18.720 --> 00:04:21.020 Right, like maybe take this project and then go, 00:04:21.020 --> 00:04:24.360 all right, well, what if we hit it with all the pip installable things? 00:04:24.360 --> 00:04:25.960 What happens then, right? 00:04:25.960 --> 00:04:26.660 Yeah, exactly. 00:04:26.660 --> 00:04:29.220 Yeah, it sounds like a super intense project, though, right? 00:04:29.220 --> 00:04:31.480 Like deep, deep into the language, right? 00:04:31.480 --> 00:04:33.340 I mean, on one, you're writing the compiler. 00:04:33.340 --> 00:04:35.400 You're understanding Java. 00:04:35.400 --> 00:04:36.960 You're compiling to x86. 00:04:36.960 --> 00:04:38.300 You're doing meta programming. 00:04:38.300 --> 00:04:39.800 Like there's a lot of stuff going on here. 00:04:39.800 --> 00:04:40.720 It's a pretty cool article. 00:04:40.720 --> 00:04:41.080 Cool. 00:04:41.080 --> 00:04:44.760 If that last one really connected with like your deep geek outlets, 00:04:44.760 --> 00:04:47.000 like go like really hard into the language, 00:04:47.000 --> 00:04:49.280 this next one is going to connect with your, 00:04:49.420 --> 00:04:51.020 I just want it to work really quick and easy. 00:04:51.020 --> 00:04:51.380 Yeah. 00:04:51.380 --> 00:04:52.380 So this one is really nice. 00:04:52.380 --> 00:04:53.780 So if I was a data scientist, 00:04:53.780 --> 00:04:57.960 I might use Matplotlib or just any kind of person who wanted some visualization of data. 00:04:57.960 --> 00:05:00.040 I might use Matplotlib for that. 00:05:00.040 --> 00:05:01.380 And that's great. 00:05:01.380 --> 00:05:05.960 Except for at least I personally can't make Matplotlib look super good, right? 00:05:05.960 --> 00:05:07.320 Like if I used Excel, 00:05:07.320 --> 00:05:09.800 like I put the data in there and I'd highlight the stuff and I would say, 00:05:09.800 --> 00:05:11.440 okay, insert chart. 00:05:11.440 --> 00:05:15.860 And I would pick the kind and then I would go and I would like right click and edit the chart. 00:05:15.940 --> 00:05:18.540 And I would like maybe drag it around to size it correctly, 00:05:18.540 --> 00:05:21.260 double click on the axes to change the axes. 00:05:21.260 --> 00:05:24.280 But in Matplotlib, you just write code and the picture comes out, right? 00:05:24.280 --> 00:05:24.560 Yeah. 00:05:24.560 --> 00:05:27.700 And I know you can do all this stuff, but it's not obvious. 00:05:27.700 --> 00:05:31.160 And you have to look at everything, every little thing up and tweak it. 00:05:31.160 --> 00:05:31.680 Yeah. 00:05:31.680 --> 00:05:36.640 So there's this project that we heard about from one of our listeners. 00:05:36.640 --> 00:05:37.720 And I can't remember. 00:05:37.720 --> 00:05:39.260 I'm trying to remember who it was. 00:05:39.260 --> 00:05:39.840 Oh, here it is. 00:05:40.260 --> 00:05:42.120 I've got this is from Lee Wagner. 00:05:42.120 --> 00:05:44.540 So thank you, Lee, for sending us in because this is killer. 00:05:44.540 --> 00:05:51.720 So there's this project called PyLustrator for styling your Matplotlib plot. 00:05:51.720 --> 00:05:58.360 So you just do your Matplotlib code, but you import PyLustrator and you say start at the beginning. 00:05:59.140 --> 00:06:04.640 And what it does is it pops up when you show your plot an interactive thing, much like Excel, 00:06:04.640 --> 00:06:08.400 where you can drag and drop and arrange your different plots. 00:06:08.400 --> 00:06:15.600 You can like go to the properties and edit like the axes and the colors and just all the kind of stuff that you might do. 00:06:15.740 --> 00:06:23.600 It even has like the cool design layout stuff where like it'll help you equally space stuff between each other. 00:06:23.600 --> 00:06:25.220 So put those little bars to say right there. 00:06:25.220 --> 00:06:28.860 If you drag and drop it, they'll be equally spaced or like align the tops and the sides. 00:06:28.860 --> 00:06:29.220 Yeah. 00:06:29.220 --> 00:06:34.700 And with that, the start thing, you can even fill it with some of your data to begin with. 00:06:34.700 --> 00:06:40.300 So if you, you kind of know the data you want to plot, because that's going to affect how you're going to design it. 00:06:40.300 --> 00:06:43.820 So you can pre-fill it and then drag it around and design it. 00:06:43.820 --> 00:06:45.100 It's just totally cool. 00:06:45.100 --> 00:06:45.840 It's totally cool. 00:06:45.840 --> 00:06:46.620 I'm glad they have. 00:06:46.620 --> 00:06:50.920 So the link we're going to show has a little embedded video. 00:06:50.920 --> 00:06:55.020 And that's where, I mean, talking about it, you're like, yeah, I think this might be useful. 00:06:55.020 --> 00:06:58.420 But you watch this video and you're like, oh, my God, I need to use this right away. 00:06:58.420 --> 00:06:59.060 Yes. 00:06:59.060 --> 00:07:00.800 I had the exact same experience. 00:07:00.800 --> 00:07:02.300 I'm like, kind of interesting. 00:07:02.300 --> 00:07:03.500 Oh, look at the video. 00:07:03.500 --> 00:07:04.060 Oh, my God. 00:07:04.060 --> 00:07:04.520 It's amazing. 00:07:04.520 --> 00:07:04.800 Yeah. 00:07:04.800 --> 00:07:06.060 So this is super cool. 00:07:06.060 --> 00:07:10.900 And obviously, you don't save your changes to like an Excel workbook. 00:07:10.900 --> 00:07:12.760 What you do is you save your changes. 00:07:13.140 --> 00:07:15.140 And you can actually call save in PyListrator. 00:07:15.140 --> 00:07:20.260 And what it'll do is it'll put the configuration in Python back into the file that ran it. 00:07:20.260 --> 00:07:22.240 So that's pretty wild, actually. 00:07:22.240 --> 00:07:22.600 Yeah. 00:07:22.600 --> 00:07:24.280 And then you uncomment the PyListrator. 00:07:24.280 --> 00:07:28.860 You don't have to import it later because it's not a dependency on your project afterwards. 00:07:28.860 --> 00:07:29.380 Right. 00:07:29.380 --> 00:07:30.640 It's just a little design tool. 00:07:30.700 --> 00:07:38.100 So it's super cool if anyone's doing Matplotlib and they want to have it styled, especially if you're doing more than one plot and you want to put them like side by side. 00:07:38.100 --> 00:07:39.100 Like, this is super cool. 00:07:39.100 --> 00:07:39.860 So check that out. 00:07:39.860 --> 00:07:40.880 I'm definitely a fan. 00:07:40.880 --> 00:07:43.100 Another thing I'm a fan of, Brian, MongoDB. 00:07:43.100 --> 00:07:44.180 Love it. 00:07:44.180 --> 00:07:49.140 Since you and I are paying attention to a lot of projects, there's a lot of different release cycles. 00:07:49.140 --> 00:07:55.900 And we kind of decided early on that we weren't going to try to track everybody's releases because that might get boring to people. 00:07:55.900 --> 00:08:00.860 However, we covered MongoDB 4 because it came out with... 00:08:00.860 --> 00:08:01.420 Transactions. 00:08:01.420 --> 00:08:02.320 Transactions. 00:08:02.320 --> 00:08:03.140 Among other things, yeah. 00:08:03.140 --> 00:08:04.080 Which was a big thing. 00:08:04.940 --> 00:08:10.120 But 4.2 is out and I'm kind of excited about a couple of features that it came out with. 00:08:10.120 --> 00:08:14.460 So the transactions are there, but now they're multi-doc. 00:08:14.460 --> 00:08:15.920 They're distributed transactions. 00:08:15.920 --> 00:08:21.200 So they're transactions that cross sharded clusters and replica sets. 00:08:21.200 --> 00:08:23.740 And that's just really cool. 00:08:23.740 --> 00:08:24.700 Yeah, that's super cool. 00:08:24.700 --> 00:08:28.860 I mean, you could use a cool transactional set before, but you're kind of limited, right? 00:08:28.940 --> 00:08:35.580 And now it's like, no matter what crazy cluster with scaling and sharding and replication you have set up, you just do a transaction and it's all good. 00:08:35.580 --> 00:08:36.100 Pretty cool. 00:08:36.100 --> 00:08:37.180 They're a good idea anyway. 00:08:37.180 --> 00:08:42.360 But with testing, you can set up a complex database full of stuff. 00:08:42.360 --> 00:08:46.140 And then at the beginning of your test, start a transaction. 00:08:46.140 --> 00:08:52.920 And then after your test, and you roll this into a fixture, you can just roll back and your next test has the same data. 00:08:52.920 --> 00:08:53.680 It saves time. 00:08:53.680 --> 00:08:54.760 So that's cool. 00:08:54.760 --> 00:08:58.420 Yeah, and it's probably got isolation if for some reason they ran in parallel or whatever. 00:08:58.580 --> 00:08:59.220 Yeah, it's really cool. 00:08:59.220 --> 00:08:59.520 Yeah. 00:08:59.520 --> 00:09:03.400 The other feature that's pretty amazing is the field level encryption. 00:09:03.400 --> 00:09:09.480 And this is encryption done on a per field basis on the client side. 00:09:09.480 --> 00:09:15.140 So the server doesn't even have, it doesn't do the, it's not doing it on the server. 00:09:15.140 --> 00:09:28.320 So there's like system administration can be done without having to make sure everybody signs NDAs and all that stuff that you can just, you can manage your database without even being exposed. 00:09:28.320 --> 00:09:29.320 Yeah, that's awesome. 00:09:29.320 --> 00:09:29.600 Yeah. 00:09:29.600 --> 00:09:30.040 Yeah, that's awesome. 00:09:30.040 --> 00:09:33.460 Like most databases, most of what's in them is not sensitive. 00:09:33.460 --> 00:09:39.100 But there's often like a little bit that is, that's really, you don't want, you don't want anyone to get access to. 00:09:39.100 --> 00:09:39.980 And yeah, this is really cool. 00:09:39.980 --> 00:09:44.800 Because like you said, it's done in the library that talks to MongoDB. 00:09:45.340 --> 00:09:48.200 So in PyMongo for the Python folks. 00:09:48.740 --> 00:09:55.400 And you just set the encryption key or decryption key over there and the server cannot decrypt it. 00:09:55.400 --> 00:10:01.780 So if somebody breaks into the server or you lose it, or it's like you set it up on the cloud for like testing, you forget that it's there. 00:10:01.860 --> 00:10:03.960 All the kind of random stuff that happens to databases. 00:10:03.960 --> 00:10:09.600 It doesn't matter in terms of this encrypted stuff because like literally the database doesn't know how to read it. 00:10:09.600 --> 00:10:13.080 It's the drivers that on the client side that have the keys. 00:10:13.420 --> 00:10:20.020 So with GDPR stuff, if the customer says, hey, delete my stuff, that's always been an issue with databases. 00:10:20.020 --> 00:10:22.300 It might be in a whole bunch of tables. 00:10:22.300 --> 00:10:28.840 But if you destroy the customer key, the data might still be there, but it's unreadable to anybody. 00:10:28.840 --> 00:10:30.940 So it may as well be garbage. 00:10:30.940 --> 00:10:31.440 Absolutely. 00:10:31.440 --> 00:10:42.500 And it gets to be really tricky because even if you set up the right code to delete all the customer data out of your database, what about the backup? 00:10:43.040 --> 00:10:50.360 That somebody made when an older admin was hired and they stored that in the S3 buckets so it was offsite, right? 00:10:50.360 --> 00:10:52.560 How do you delete the data out of there? 00:10:52.560 --> 00:10:53.940 You know what I mean? 00:10:53.940 --> 00:10:59.420 But if it's encrypted, then you can just throw away the encryption key and then it's just gobbledygook. 00:10:59.420 --> 00:10:59.740 Yeah. 00:10:59.740 --> 00:11:00.440 Cool. 00:11:00.440 --> 00:11:00.740 Pretty cool. 00:11:00.740 --> 00:11:01.540 I like it. 00:11:01.540 --> 00:11:05.860 Speaking of cool, Rollbar, happy to have them come along and sponsor the show. 00:11:05.860 --> 00:11:09.660 We use Rollbar on pythonbytes.fm, among other things. 00:11:09.780 --> 00:11:26.960 So if anything goes wrong and it's kind of fortuitous, I guess, I woke up this morning with a ton of Rollbar messages because there was a data center failure that caused some connectivity between MongoDB and pythonbytes.fm. 00:11:27.420 --> 00:11:29.160 How about that for a funny thing? 00:11:29.160 --> 00:11:31.240 So some network card broke, right? 00:11:31.240 --> 00:11:34.200 And like the site couldn't talk to the server. 00:11:34.200 --> 00:11:35.000 So the database server. 00:11:35.000 --> 00:11:35.960 So it was freaking out. 00:11:35.960 --> 00:11:37.100 How do I know? 00:11:37.100 --> 00:11:38.260 And nobody complained to me. 00:11:38.260 --> 00:11:39.140 They probably should. 00:11:39.140 --> 00:11:40.300 Like, Michael, your site's down. 00:11:40.300 --> 00:11:40.920 What's going on? 00:11:40.920 --> 00:11:41.880 It's really messed up. 00:11:42.680 --> 00:11:44.360 But I just opened up my email. 00:11:44.360 --> 00:11:46.260 I'm like, whoa, there's a lot of Rollbar stuff going on here. 00:11:46.260 --> 00:11:51.480 So if you want to be notified right away, even when users don't tell you, check them out. 00:11:51.480 --> 00:11:52.300 They have a free tier. 00:11:52.300 --> 00:11:53.420 They have some great paid tiers. 00:11:53.420 --> 00:11:55.740 Visit pythonbytes.fm/Rollbar. 00:11:55.740 --> 00:11:59.000 Super easy to integrate into Python, into the web frameworks. 00:11:59.000 --> 00:12:02.840 They've just got like one or two lines you enter or maybe a little configuration. 00:12:02.840 --> 00:12:04.000 A few settings. 00:12:04.000 --> 00:12:04.740 Off you go. 00:12:04.740 --> 00:12:05.720 It's really, really nice. 00:12:05.800 --> 00:12:08.100 So check them out, pythonbytes.fm/Rollbar. 00:12:08.100 --> 00:12:08.480 Nice. 00:12:08.480 --> 00:12:12.960 So kind of like PyListrator, that sounds kind of useful and interesting. 00:12:12.960 --> 00:12:15.800 This next one also sounds useful and interesting. 00:12:15.800 --> 00:12:20.100 But like PyListrator, it's like, as you look into it, you're like, whoa, this thing does a lot, man. 00:12:20.100 --> 00:12:20.840 Look at it go. 00:12:20.840 --> 00:12:25.300 So there's this project that was recommended by Francois LeBlanc. 00:12:25.300 --> 00:12:27.120 Thank you for that, Francois. 00:12:27.120 --> 00:12:29.640 And it's called Deep Difference. 00:12:29.640 --> 00:12:31.640 It's just called Deep Dif. 00:12:31.640 --> 00:12:36.100 And so it does deep differences in search of any Python object graph. 00:12:36.100 --> 00:12:39.420 So I've got an object which holds a list. 00:12:39.420 --> 00:12:41.040 That list points to a bunch of objects. 00:12:41.040 --> 00:12:42.420 Those have other pointers. 00:12:42.420 --> 00:12:46.400 Like I want to know, is this thing somehow referenced by that? 00:12:46.400 --> 00:12:47.700 Let me do a search on it. 00:12:47.700 --> 00:12:48.960 Where is it? 00:12:48.960 --> 00:12:54.960 Is this giant crazy data structure same or different than other giant crazy data structure? 00:12:54.960 --> 00:12:56.660 And you could compare them. 00:12:56.660 --> 00:12:57.520 So that's pretty cool. 00:12:57.520 --> 00:12:58.360 So it has Deep Dif. 00:12:58.360 --> 00:12:59.620 It has Deep Search. 00:12:59.620 --> 00:13:01.200 And it also has Deep Hash. 00:13:01.720 --> 00:13:10.300 So if I've got some giant crazy data structure, you would like to know that if the data is the same across two of those, that the hash result is identical. 00:13:10.300 --> 00:13:14.320 And if any part of the data changes, that the hash then changes. 00:13:14.320 --> 00:13:15.360 Oh, yeah. 00:13:15.360 --> 00:13:16.000 Possibly, right? 00:13:16.000 --> 00:13:20.680 So it will do that on object graphs that are not even hashable themselves. 00:13:20.680 --> 00:13:21.180 Really? 00:13:21.180 --> 00:13:21.920 Yeah. 00:13:21.920 --> 00:13:24.000 So that's pretty wild. 00:13:24.200 --> 00:13:29.660 I have just a lot of nice touches in here that kind of made me realize like, wow, this is wild. 00:13:29.660 --> 00:13:36.300 So, for example, it'll give me the differences in a list, ignoring order and duplicates. 00:13:36.300 --> 00:13:37.200 Right? 00:13:37.200 --> 00:13:39.440 Just what is the essence of this data? 00:13:40.140 --> 00:13:46.660 Or you can say, is any data repeated in this list or in this, you know, dictionary or something like that? 00:13:46.660 --> 00:13:48.780 You can exclude certain types. 00:13:48.780 --> 00:13:49.700 Right? 00:13:49.780 --> 00:13:53.360 Like, maybe I want to know the data is the same, but they're both using like a thread object. 00:13:53.360 --> 00:13:54.640 And the thread object is different. 00:13:54.640 --> 00:13:55.780 So, of course, they're going to be different. 00:13:55.780 --> 00:13:58.040 But say, don't check on the thread object. 00:13:58.040 --> 00:13:59.140 Just check the other stuff. 00:13:59.140 --> 00:13:59.600 Right? 00:13:59.600 --> 00:14:04.200 So you can explicitly opt in or out data types that you might use. 00:14:04.200 --> 00:14:09.620 You can say, I'd like to compare these things, but only to like four significant digits because I computed them slightly differently. 00:14:09.620 --> 00:14:16.540 And maybe they're, you know, I can't get them like to the decimal accuracy to be exactly the same, just the way they're done. 00:14:16.540 --> 00:14:16.780 Right? 00:14:16.780 --> 00:14:20.880 You can exclude parts of your object tree that you're going for compared. 00:14:20.880 --> 00:14:21.740 I mean, isn't this insane? 00:14:21.740 --> 00:14:26.520 Being able to do like significant digits in a deep data structure. 00:14:26.520 --> 00:14:27.900 That's amazing. 00:14:27.900 --> 00:14:30.760 That's really cool for a lot of the stuff I work with. 00:14:30.760 --> 00:14:32.420 Yeah, I can imagine exactly. 00:14:32.420 --> 00:14:33.420 And you know what? 00:14:33.420 --> 00:14:35.540 I bet this would be really good to mix in with testing. 00:14:35.540 --> 00:14:38.860 Like you create your test data and then you deep diff it against the result. 00:14:39.160 --> 00:14:39.740 Yeah, exactly. 00:14:39.740 --> 00:14:44.620 Because there may be noise in the system and you know some of the signals are noisy. 00:14:44.620 --> 00:14:46.420 So, yeah, this is awesome. 00:14:46.420 --> 00:14:46.760 Cool. 00:14:46.760 --> 00:14:47.600 It's super simple. 00:14:47.600 --> 00:14:49.380 But, yeah, it's pretty cool. 00:14:49.380 --> 00:14:52.740 So if that sounds like problems you're trying to solve, it sounds like you are, Brian. 00:14:52.740 --> 00:14:54.480 And I think it's definitely worth having a look at. 00:14:54.480 --> 00:14:55.300 Yeah, thanks. 00:14:55.300 --> 00:14:56.100 Yeah, you bet. 00:14:56.100 --> 00:14:58.600 See, we just do this podcast to help each other out. 00:14:58.600 --> 00:14:59.960 Like people can listen in. 00:14:59.960 --> 00:15:01.060 Yeah. 00:15:01.060 --> 00:15:01.900 Speaking of testing. 00:15:01.900 --> 00:15:08.980 Josh Peek is somebody that we, I'm sure we met him before at a previous PyCon, but he stopped by at PyCon. 00:15:08.980 --> 00:15:12.740 And this last year and met us and a really great guy. 00:15:12.740 --> 00:15:15.520 He wrote this great article called Advanced Python Testing. 00:15:16.280 --> 00:15:17.940 And it's kind of incredible. 00:15:17.940 --> 00:15:34.320 He goes through his, he got in a situation at work where he was asked to do complex tasks where he had to, he knew that testing and making sure that he was doing things properly would, and do good coding practices would, would help the entire process and make it go smoothly. 00:15:34.680 --> 00:15:39.340 So this is sort of a start to finish summary of it. 00:15:39.440 --> 00:15:46.080 But it's not that long of a read, but he talks about his learning journey, which he includes some great podcasts, including ours. 00:15:46.080 --> 00:15:48.520 Also an awesome book on testing. 00:15:48.520 --> 00:15:50.060 And I know the author for that one. 00:15:50.060 --> 00:15:52.360 Not just plugging our own stuff. 00:15:52.360 --> 00:15:53.900 He's got some great stuff in here. 00:15:53.980 --> 00:16:02.340 He talks about, he starts off with just a basic, for people new to testing, what a basic test function looks like and having good structure. 00:16:02.340 --> 00:16:09.820 But then he talks about, he wanted to ensure, you know, do static analysis and code style. 00:16:09.820 --> 00:16:12.400 So he uses black within his testing. 00:16:12.400 --> 00:16:17.880 And when he was talking about using PyLint, I don't use PyLint every day. 00:16:17.880 --> 00:16:25.200 So I didn't know that there was, it's a very comprehensive check, but it takes some time for large code bases. 00:16:25.200 --> 00:16:26.380 I didn't know that. 00:16:26.380 --> 00:16:34.880 But he has a cool hack that he puts in place to only, for like check-in tests, only lint modified files. 00:16:34.880 --> 00:16:35.660 Oh, that's cool. 00:16:35.660 --> 00:16:39.520 Yeah, because of course, if they're unmodified, then why would they have a different outcome? 00:16:39.520 --> 00:16:40.020 Yeah. 00:16:40.020 --> 00:16:40.320 Right. 00:16:40.320 --> 00:16:48.500 And then he uses incorporating flake 8 to do doc string testing to make sure that people are using consistent doc string styles. 00:16:48.500 --> 00:16:52.280 He covers all of his tox any configuration changes. 00:16:52.280 --> 00:16:55.980 He was trying to increase his code coverage. 00:16:55.980 --> 00:17:09.440 So he includes coverage.py, but then also has a cov fail under flag that he adds for testing to make sure that if code coverage drops below, 00:17:09.440 --> 00:17:11.640 a certain point, it fails the test. 00:17:11.640 --> 00:17:15.540 And then just generally gradually ratchet that up. 00:17:15.540 --> 00:17:18.240 So the increase, his target was 75%. 00:17:18.240 --> 00:17:22.840 So it even goes into fixtures and mocks and spies and stubs. 00:17:23.100 --> 00:17:32.680 And then even a cool tool called pytest VCR, which records your network interactions and then replays those for future test runs. 00:17:32.680 --> 00:17:35.020 And he saw a 10x speedup in that. 00:17:35.020 --> 00:17:35.700 That's really cool. 00:17:35.700 --> 00:17:37.120 There's so much cool stuff in here. 00:17:37.120 --> 00:17:37.900 pytest VCR. 00:17:37.900 --> 00:17:38.460 That's really cool. 00:17:38.540 --> 00:17:43.740 I think the only problem with it is like maybe a lot of folks using it have no idea what VCR means. 00:17:43.740 --> 00:17:44.620 Oh, yeah. 00:17:44.620 --> 00:17:46.300 That's true. 00:17:46.300 --> 00:17:47.720 I mean, even, yeah. 00:17:47.720 --> 00:17:48.100 So. 00:17:48.100 --> 00:17:48.400 Yeah. 00:17:48.400 --> 00:17:53.280 But no, it's awesome that you just record the network interactions and don't have to depend on anything at all. 00:17:53.280 --> 00:17:53.920 I love it. 00:17:53.920 --> 00:17:57.280 And the recordings are done based on a per test basis. 00:17:57.280 --> 00:18:04.240 So if you rerun an individual test, it only plays back the recording for that portion. 00:18:04.240 --> 00:18:07.880 It doesn't have order dependency built in, which is cool. 00:18:07.880 --> 00:18:08.120 Yeah. 00:18:08.120 --> 00:18:08.680 Super cool. 00:18:08.680 --> 00:18:09.500 I love it. 00:18:09.500 --> 00:18:10.200 Yeah. 00:18:10.200 --> 00:18:11.420 That's a really nice article, Josh. 00:18:11.420 --> 00:18:12.020 Well done. 00:18:12.020 --> 00:18:15.560 The last one I want to talk about was sent over by Kevin Books. 00:18:15.560 --> 00:18:21.600 Now, we've covered a few of the language, sort of language level learning things recently. 00:18:21.600 --> 00:18:27.140 We talked about the CPython byte compiler either last time or the time before that. 00:18:27.240 --> 00:18:28.880 How it doesn't really optimize stuff. 00:18:28.880 --> 00:18:33.300 And maybe there's some opportunities there, but more just to understand what's going on. 00:18:33.300 --> 00:18:38.300 So Kevin sent in a message, said, hey, I'm basically a C, C++ guy. 00:18:38.300 --> 00:18:41.580 And I saw the Dell keyword in Python. 00:18:41.580 --> 00:18:48.660 And it threw me for a loop because Dell seems like delete in C++, which means free memory. 00:18:48.660 --> 00:18:51.840 But it doesn't necessarily mean that in Python. 00:18:51.840 --> 00:18:56.020 So it even seems like some of the books out there are kind of being a little misleading, 00:18:56.320 --> 00:18:58.120 at least according to Kevin's reading of them. 00:18:58.120 --> 00:19:05.120 So I thought I'd just pull up an article that he sent over and then talk a little bit over some of the uses for Dell. 00:19:05.120 --> 00:19:05.560 Great. 00:19:05.560 --> 00:19:06.320 I don't use it. 00:19:06.320 --> 00:19:07.220 So this would be good. 00:19:07.220 --> 00:19:07.480 Yeah. 00:19:07.600 --> 00:19:15.680 So the context where I know Dell is I want to get something out of a list or I want to get something out of a dictionary. 00:19:15.680 --> 00:19:16.500 Right. 00:19:16.500 --> 00:19:16.860 Okay. 00:19:16.860 --> 00:19:18.080 And it's a little bit weird. 00:19:18.080 --> 00:19:19.480 It's like in keyword. 00:19:19.480 --> 00:19:19.800 Right. 00:19:19.800 --> 00:19:25.160 A lot of times I would expect some operator to be on the object I'm modifying. 00:19:25.160 --> 00:19:25.880 Right. 00:19:25.880 --> 00:19:31.280 Like list or, you know, string dot in or something and you give it the value. 00:19:31.280 --> 00:19:31.460 Right. 00:19:31.460 --> 00:19:35.120 But you say string space in space, the variable. 00:19:35.120 --> 00:19:35.460 Right. 00:19:35.540 --> 00:19:40.500 So it's a little bit funky that you apply it not on the object, but as a keyword in the language. 00:19:40.500 --> 00:19:41.280 And Dell is like that. 00:19:41.280 --> 00:19:41.400 Right. 00:19:41.400 --> 00:19:46.900 So if I have a dictionary and I want to remove a key, not set it to nothing, but make it not be in the keys collection, 00:19:46.900 --> 00:19:53.360 you can say Dell dictionary of bracket, like as if you're accessing that value, but putting the Dell there takes it out. 00:19:53.520 --> 00:19:53.960 Oh, okay. 00:19:53.960 --> 00:19:54.240 Yeah. 00:19:54.240 --> 00:19:55.380 And you can also do that for lists. 00:19:55.380 --> 00:19:59.520 So I can go in and remove it, remove something from a list if I want. 00:19:59.520 --> 00:20:05.640 There's a remove function on the list, but somewhat confusingly, potentially it's by value. 00:20:05.640 --> 00:20:06.000 Right. 00:20:06.000 --> 00:20:11.860 So I could say remove Jeff from the list and Jeff will no longer be in that list wherever he appeared. 00:20:11.860 --> 00:20:17.120 But if I want to say remove the third thing, there's no remove at or anything like that. 00:20:17.120 --> 00:20:17.260 Right. 00:20:17.260 --> 00:20:19.760 I can't pass to that's not a value. 00:20:19.760 --> 00:20:20.020 Right. 00:20:20.020 --> 00:20:21.960 So Dell will let me remove that. 00:20:22.460 --> 00:20:26.680 You can also use pop for that, I believe on the list, but Dell is a little more general purpose. 00:20:26.680 --> 00:20:28.580 And you can also delete slices. 00:20:28.580 --> 00:20:34.920 So I could say, go to this list and take out everything from two to five, you know, two colon five like that. 00:20:34.920 --> 00:20:35.460 All right. 00:20:35.460 --> 00:20:37.280 So these are all pretty interesting. 00:20:37.280 --> 00:20:41.000 Now I'm linking over to the official docs that talk about it. 00:20:41.000 --> 00:20:44.640 And this article that kind of talks through some of these examples and shows you how to use it. 00:20:44.640 --> 00:20:48.740 You can also delete a variable out of like a local or a global namespace. 00:20:48.740 --> 00:20:52.200 So if there's a variable that's been defined and you want it to not be defined, 00:20:52.200 --> 00:20:53.920 I can say Dell space variable name. 00:20:53.920 --> 00:20:57.780 And now it's as if I didn't do that line that defined it, right? 00:20:57.780 --> 00:20:58.400 That created it. 00:20:58.400 --> 00:20:59.940 Does it remove it from the namespace? 00:20:59.940 --> 00:21:00.580 It removed. 00:21:00.580 --> 00:21:00.840 Yeah. 00:21:00.840 --> 00:21:06.180 It doesn't free the memory necessarily, but it takes it out as a global variable. 00:21:06.180 --> 00:21:06.800 Okay. 00:21:06.800 --> 00:21:08.520 Or a local one. 00:21:08.520 --> 00:21:08.720 Right. 00:21:08.720 --> 00:21:09.000 Yeah. 00:21:09.040 --> 00:21:10.740 So does it actually free any memory? 00:21:10.740 --> 00:21:11.460 Right. 00:21:11.460 --> 00:21:12.700 It depends. 00:21:12.700 --> 00:21:12.960 Right. 00:21:12.960 --> 00:21:17.160 So if I have it in the global names, let's say it's a global, right? 00:21:17.160 --> 00:21:21.560 It has obviously the thing that has a value at that variable. 00:21:21.820 --> 00:21:22.960 It's taking up some memory. 00:21:22.960 --> 00:21:26.040 If nothing else is pointing at it, right? 00:21:26.040 --> 00:21:28.120 It's still going to be around because that global variable is pointing at it. 00:21:28.120 --> 00:21:33.460 But if you call Dell that variable, you'll dereference that one reference to it, putting the reference 00:21:33.460 --> 00:21:35.160 count to zero and freeing it up. 00:21:35.160 --> 00:21:38.180 So theoretically, you could free up memory using Dell. 00:21:38.600 --> 00:21:43.280 Similarly, if it's in a list and the only place that points to it has a reference to it is that list itself. 00:21:43.280 --> 00:21:46.360 And you delete it out of there, out of the dictionary, it goes away, right? 00:21:46.360 --> 00:21:47.060 Memory wise. 00:21:47.060 --> 00:21:49.940 But if something else is pointing at it, then obviously it's not going to go away. 00:21:49.940 --> 00:21:50.280 Yeah. 00:21:50.280 --> 00:21:53.720 We also talked about how the CPython bytecode compiler is dumb. 00:21:53.720 --> 00:21:57.040 Dumb as in not super optimizing, maybe on purpose. 00:21:57.040 --> 00:22:02.720 And I think you could also, you know, if you're like really dealing with memory issues and you're like, 00:22:02.720 --> 00:22:07.680 I really wish this thing would just go away sooner in this one little edge case, 00:22:07.780 --> 00:22:14.080 you could probably use Dell to put in some of the optimizations that you might hope that the compiler itself might do, 00:22:14.080 --> 00:22:21.320 but it doesn't like dereference a thing as soon as it's used within a function before you can get to the end or things like this. 00:22:21.320 --> 00:22:21.780 Yeah. 00:22:21.780 --> 00:22:22.380 Okay. 00:22:22.380 --> 00:22:23.680 So is it for memory? 00:22:23.680 --> 00:22:24.420 Sort of. 00:22:24.420 --> 00:22:25.020 Not really. 00:22:25.020 --> 00:22:27.280 But maybe as a side effect. 00:22:27.280 --> 00:22:28.060 Yeah. 00:22:28.060 --> 00:22:32.160 This has been a long time, but I do remember it tripping me up because I was like, 00:22:32.160 --> 00:22:37.100 it seems a lot like delete, which should have a matching new to it. 00:22:37.360 --> 00:22:37.840 Exactly. 00:22:37.840 --> 00:22:38.660 Exactly. 00:22:38.660 --> 00:22:40.480 We both done the C++ thing, right? 00:22:40.480 --> 00:22:41.920 Like where's the new that goes with Dell? 00:22:41.920 --> 00:22:43.280 I've never seen a new. 00:22:43.280 --> 00:22:44.740 Anyway, it's pretty cool. 00:22:44.740 --> 00:22:45.960 There's a couple of links here. 00:22:45.960 --> 00:22:47.040 There's a visual documentation. 00:22:47.040 --> 00:22:49.600 There's the article understanding Python's Dell. 00:22:49.600 --> 00:22:53.380 And then there's the reference to that bytecode compiler people can check out. 00:22:53.380 --> 00:22:53.700 Yeah. 00:22:53.700 --> 00:22:58.180 In C++, I don't think there's a way to remove a name from a namespace. 00:22:58.380 --> 00:22:58.540 Yeah. 00:22:58.540 --> 00:22:59.860 I don't think so either, right? 00:22:59.860 --> 00:23:00.160 Yeah. 00:23:00.160 --> 00:23:04.340 You can like make it point at null, but that's about it, right? 00:23:04.340 --> 00:23:04.740 Yeah. 00:23:04.740 --> 00:23:06.140 But I mean, you got to think about it, right? 00:23:06.140 --> 00:23:09.160 Like classes, you could delete a field out of a class, right? 00:23:09.160 --> 00:23:11.200 Because it's just a dictionary, right? 00:23:11.200 --> 00:23:13.760 So much of Python is built on like dictionaries, right? 00:23:13.760 --> 00:23:17.960 Like the variables are their variable names or the keys in the dictionary and their values 00:23:17.960 --> 00:23:18.660 are their value. 00:23:19.040 --> 00:23:21.780 So you just take it out of the global dictionary effectively, right? 00:23:21.780 --> 00:23:22.000 Yeah. 00:23:22.000 --> 00:23:22.440 Okay. 00:23:22.440 --> 00:23:22.880 Cool. 00:23:22.880 --> 00:23:23.360 Pretty sweet. 00:23:23.360 --> 00:23:25.880 So those are our main items for today. 00:23:25.880 --> 00:23:27.740 You got anything else you want to chat about, Brian? 00:23:27.740 --> 00:23:29.700 I'm just, I'm glad it's summer. 00:23:29.700 --> 00:23:30.940 It's starting to feel nice. 00:23:30.940 --> 00:23:31.700 It feels like summer. 00:23:31.700 --> 00:23:33.940 But other than that, not much. 00:23:33.940 --> 00:23:34.420 How about you? 00:23:34.420 --> 00:23:35.180 Summer is awesome. 00:23:35.180 --> 00:23:38.200 It makes programming hard because programming is indoors. 00:23:38.200 --> 00:23:42.760 Although some of my friends and I who work from home, we try to get out and program 00:23:42.760 --> 00:23:45.580 in like a coffee shop or a cafe by lake or something. 00:23:46.080 --> 00:23:50.320 And periodically we have the weird experience of getting a sunburn while writing code. 00:23:50.320 --> 00:23:54.420 And yeah, we've dubbed it a code burn and it's kind of a badge of honor. 00:23:54.420 --> 00:23:55.920 That's funny. 00:23:55.920 --> 00:23:56.320 Cool. 00:23:56.320 --> 00:23:56.620 Yeah. 00:23:56.620 --> 00:23:59.120 So there's actually a couple of things I want to throw out here. 00:23:59.120 --> 00:24:02.280 We recently had Max Sklar from the local Maximum podcast. 00:24:02.280 --> 00:24:05.620 And afterwards he had me onto his podcast. 00:24:05.620 --> 00:24:09.320 So I'll be on episode 73, which should be out. 00:24:09.320 --> 00:24:13.640 Not yet, but thanks to time shifting when this episode comes out, it should already be out. 00:24:13.640 --> 00:24:14.400 I'll put a link to that. 00:24:14.860 --> 00:24:23.020 Josh Thurston sent over a cool video of the popularity of languages on Stack Overflow over 00:24:23.020 --> 00:24:25.520 time as a bar chart race. 00:24:25.520 --> 00:24:29.820 I didn't know about bar chart races, but these are basically animated bar charts over time. 00:24:29.820 --> 00:24:32.000 And you just watch the bars grow and shrink. 00:24:32.000 --> 00:24:33.100 And it's really cool. 00:24:33.100 --> 00:24:36.100 Python is kind of like a little tiny consideration at the bottom. 00:24:36.100 --> 00:24:40.980 And obviously we know that Python is crushing it on popularity and Stack Overflow and all those 00:24:40.980 --> 00:24:41.160 things. 00:24:41.260 --> 00:24:43.000 So it's like a minute and a half video. 00:24:43.000 --> 00:24:45.940 I think everyone will appreciate watching it if they just got a minute to kill. 00:24:45.940 --> 00:24:47.020 No, it's a fun video. 00:24:47.020 --> 00:24:54.080 And one of the things I enjoy about it is early on, you see the Java bar going up and down based 00:24:54.080 --> 00:24:58.780 on the time of the year because it was used in education a lot. 00:24:58.780 --> 00:24:59.880 That totally made sense. 00:24:59.880 --> 00:25:00.380 Exactly. 00:25:00.380 --> 00:25:02.740 You're like, oh, there's a huge spike in September. 00:25:02.900 --> 00:25:03.740 I wonder why. 00:25:03.740 --> 00:25:06.120 Maybe a bunch of people got a job. 00:25:06.120 --> 00:25:06.680 No. 00:25:06.680 --> 00:25:09.500 Like CS 101 is now back in session. 00:25:09.500 --> 00:25:10.120 Yeah. 00:25:10.120 --> 00:25:10.860 Exactly. 00:25:10.860 --> 00:25:14.580 Then the last one I want to throw out is this thing called Pine Source. 00:25:14.580 --> 00:25:17.940 So what this does, this comes to us from Anders Klint. 00:25:18.860 --> 00:25:24.820 It's basically a UML diagram creation tool for Python code. 00:25:24.820 --> 00:25:29.520 So you give it some Python files, it will generate a UML diagram that shows the relationship of 00:25:29.520 --> 00:25:30.840 all the classes in there. 00:25:30.840 --> 00:25:31.860 Oh, that's cool. 00:25:31.860 --> 00:25:32.180 Yeah. 00:25:32.180 --> 00:25:32.680 It's pretty cool. 00:25:32.680 --> 00:25:35.740 There's a free, maybe even open source version. 00:25:35.740 --> 00:25:37.460 And then there's also a paid version. 00:25:37.700 --> 00:25:44.420 So you can buy it and, you know, I'm actually not a huge fan of UML, but if you have Python 00:25:44.420 --> 00:25:49.500 code and you think a UML diagram would help describing it, this thing's pretty cool actually. 00:25:49.500 --> 00:25:50.880 And it's a little GUI app. 00:25:50.880 --> 00:25:51.800 There's a bunch of screenshots. 00:25:51.800 --> 00:25:53.400 You can check it out and see if it'll help you. 00:25:53.400 --> 00:25:54.800 But it looks pretty neat. 00:25:54.800 --> 00:25:59.080 And it does, you know, proper UML, not just like sort of visualization of classes. 00:25:59.080 --> 00:26:00.540 So that's kind of nice. 00:26:00.540 --> 00:26:05.240 My favorite use of these kinds of diagrams is to print them out and pin them to your wall, 00:26:05.420 --> 00:26:09.600 your cubicle wall so that other programmers think that you're smarter than they are. 00:26:09.600 --> 00:26:11.140 Absolutely. 00:26:11.140 --> 00:26:16.080 Put some little cryptic notes on them, like as if, you know, you're marking them up. 00:26:16.080 --> 00:26:16.680 Yeah, absolutely. 00:26:16.680 --> 00:26:17.160 Love it. 00:26:17.160 --> 00:26:18.700 Yeah, so you can do this with your project. 00:26:18.700 --> 00:26:20.600 Yes, this huge thing is our project. 00:26:20.600 --> 00:26:22.080 Anyway, it's pretty cool. 00:26:22.080 --> 00:26:24.900 And there's a free version, like I said, so maybe I'll help some folks out there. 00:26:24.900 --> 00:26:25.580 All right. 00:26:25.580 --> 00:26:26.860 You ready for some jokes, Brian? 00:26:26.860 --> 00:26:27.740 Yes, definitely. 00:26:27.740 --> 00:26:28.280 All right. 00:26:28.280 --> 00:26:32.340 I have a, you've heard about the glass being half full and half empty and like, oh, I'm a 00:26:32.340 --> 00:26:33.440 half empty sort of person. 00:26:33.440 --> 00:26:35.260 I kind of see the world as slightly negative. 00:26:35.260 --> 00:26:35.620 Yes. 00:26:35.620 --> 00:26:37.500 So here's the developer version. 00:26:37.500 --> 00:26:40.160 So we have an optimist who says the glass is half full. 00:26:40.160 --> 00:26:43.280 We have the pessimist who says the glass is half empty. 00:26:43.280 --> 00:26:47.260 And we have the programmer who says the glass is twice as large as necessary. 00:26:47.260 --> 00:26:48.900 Yes, definitely. 00:26:48.900 --> 00:26:51.700 So I wanted to extend that. 00:26:51.700 --> 00:26:52.000 Okay. 00:26:52.000 --> 00:26:56.860 With the pragmatist that says that I'm just allowing enough room for requirements, oversight, 00:26:56.860 --> 00:26:58.740 scope creep, and schedule overrun. 00:26:58.740 --> 00:26:59.840 That's right. 00:26:59.840 --> 00:27:00.300 It's perfect. 00:27:00.300 --> 00:27:01.560 I love it. 00:27:01.560 --> 00:27:04.400 And then you have this other one about software startups. 00:27:04.400 --> 00:27:05.220 Yeah, man. 00:27:05.220 --> 00:27:11.260 It's not really any startup, but I watched the upside with Kevin Hart last night and it 00:27:11.260 --> 00:27:13.080 was a joke that I couldn't help but sharing. 00:27:13.080 --> 00:27:18.560 I can't remember the characters, but Kevin's character said, would you invest in my business 00:27:18.560 --> 00:27:18.980 idea? 00:27:19.640 --> 00:27:23.260 And the other guy says, that seems too niche. 00:27:23.260 --> 00:27:25.760 Kevin, what's niche mean? 00:27:25.760 --> 00:27:28.280 Oh, it's the girl version of nephew. 00:27:30.500 --> 00:27:31.320 I love it. 00:27:31.320 --> 00:27:31.340 I love it. 00:27:31.340 --> 00:27:31.880 That's bad. 00:27:31.880 --> 00:27:34.900 If you got to ask, that's a pretty good answer. 00:27:34.900 --> 00:27:35.260 Yeah. 00:27:35.260 --> 00:27:35.780 Yeah. 00:27:35.780 --> 00:27:36.000 Cool. 00:27:36.000 --> 00:27:36.180 Cool. 00:27:36.180 --> 00:27:36.640 All right. 00:27:36.640 --> 00:27:40.240 Well, thanks for putting all the cool topics together as always and being here. 00:27:40.240 --> 00:27:40.540 Yeah. 00:27:40.540 --> 00:27:40.960 Thank you. 00:27:40.960 --> 00:27:41.340 Bye. 00:27:41.580 --> 00:27:43.180 Thank you for listening to Python Bytes. 00:27:43.180 --> 00:27:45.720 Follow the show on Twitter via at Python Bytes. 00:27:45.720 --> 00:27:48.580 That's Python Bytes as in B-Y-T-E-S. 00:27:48.580 --> 00:27:51.820 And get the full show notes at pythonbytes.fm. 00:27:51.820 --> 00:27:56.020 If you have a news item you want featured, just visit pythonbytes.fm and send it our way. 00:27:56.020 --> 00:27:58.720 We're always on the lookout for sharing something cool. 00:27:58.720 --> 00:28:01.840 On behalf of myself and Brian Okken, this is Michael Kennedy. 00:28:01.840 --> 00:28:05.260 Thank you for listening and sharing this podcast with your friends and colleagues.