WEBVTT 00:00:00.001 --> 00:00:05.480 Hello and welcome to Python Bytes, where we deliver Python news and headlines directly to your earbuds. 00:00:05.480 --> 00:00:09.680 This is episode 112, according to January 9th, 2019. 00:00:09.680 --> 00:00:10.620 I'm Michael Kennedy. 00:00:10.620 --> 00:00:11.480 And I'm Brian Okken. 00:00:11.480 --> 00:00:12.400 Hey, Brian. How are you doing? 00:00:12.400 --> 00:00:15.020 I am great. It's a wonderful January. 00:00:15.020 --> 00:00:19.120 We're starting to get back into the swing of things. The news is starting to flow again. 00:00:19.120 --> 00:00:19.640 Yes. 00:00:19.640 --> 00:00:26.000 Yeah, absolutely. Now, before we get into it, I just want to say thank you to Datadog for sponsoring the show, 00:00:26.000 --> 00:00:29.260 as they are many of our shows. So, tell you more about them later. 00:00:29.760 --> 00:00:37.560 Right now, I want to just think back to what it was like to have my programming and computer science assignments graded. 00:00:37.560 --> 00:00:45.040 They were like, here is an algorithm. Write the output with a pencil on a piece of paper. 00:00:45.040 --> 00:00:46.740 We've come a long way from there, right? 00:00:46.740 --> 00:00:53.560 Yeah. I mean, I even remember, I guess, turning in floppy disks and code printouts and stuff like that. 00:00:53.560 --> 00:00:54.760 Because what are you going to do? Go for them? 00:00:54.760 --> 00:00:59.000 First thing I want to talk about is a thing called NB Grader. 00:00:59.520 --> 00:01:01.120 That's short for Notebook Grader. 00:01:01.120 --> 00:01:05.400 And this, I just ran across this. This is just so totally cool. 00:01:05.400 --> 00:01:07.840 I'm just going to read there, the little thing. 00:01:07.840 --> 00:01:11.940 There was an article about it in Journal of Open Source Education. 00:01:11.940 --> 00:01:13.600 Beginning of the summary is, 00:01:13.600 --> 00:01:18.340 NB Grader is a flexible tool for creating and grading assignments in the Jupyter Notebook. 00:01:18.340 --> 00:01:23.280 NB Grader allows instructors to create a single master copy of an assignment, 00:01:23.400 --> 00:01:25.740 including tests and canonical solutions. 00:01:25.740 --> 00:01:31.320 From the master copy, a student version is generated without the solutions, thus obviating. 00:01:31.320 --> 00:01:33.720 That's totally a smarty word. 00:01:33.720 --> 00:01:37.100 Anyway, thus obviating the need to maintain two separate versions. 00:01:37.500 --> 00:01:44.860 NB Grader also automatically grades submitted assignments by executing the notebooks and storing the results of the test in a database. 00:01:44.860 --> 00:01:53.480 After auto grading, instructors can manually grade free responses and provide partial credit using the Form Grader Jupyter Notebook extension. 00:01:54.480 --> 00:01:59.300 Finally, instructors can use NB Grader to leave personalized feedback for each student submission, 00:01:59.300 --> 00:02:02.620 including comments as well as detailed error information. 00:02:02.620 --> 00:02:03.620 That sounds super useful. 00:02:03.620 --> 00:02:05.820 I totally want to play with that, even though I'm not a teacher. 00:02:06.320 --> 00:02:12.040 We're also linking to the NB Grader documentation that has a little intro video on how it all works. 00:02:12.040 --> 00:02:14.600 And wow, it just looks totally cool. 00:02:14.600 --> 00:02:18.220 That seems like an awesome way to grade computer science stuff. 00:02:18.220 --> 00:02:24.400 And you could grade pretty much anything that is reasonable to compute within a Jupyter Notebook, right? 00:02:24.740 --> 00:02:30.940 So I guess the people would have to have some Python or some sort of skill where they interact with it. 00:02:30.940 --> 00:02:39.160 But maybe that could be really simple, like just put an answer or a number or something into a cell that then gets stored and checked. 00:02:39.160 --> 00:02:48.620 But the thing that was kind of a concern for me as you're describing it was, well, what if there's like a super simple mistake you make? 00:02:48.620 --> 00:02:52.140 And then the answer is way off, so you just get it wrong, right? 00:02:52.140 --> 00:02:57.100 But the fact that you can go back and give partial credit and like evaluate it, that sounds pretty cool. 00:02:57.100 --> 00:03:03.180 Like a lot of the stuff, if you've got tests in place where it just checks their code and all the people that got it right, 00:03:03.180 --> 00:03:05.920 you don't have to really go back and double check that stuff. 00:03:05.920 --> 00:03:10.180 Maybe spot check to make sure they're not all right in the same answer or something. 00:03:10.180 --> 00:03:11.940 But it looks like a lot of fun. 00:03:11.940 --> 00:03:12.500 Yeah, that's cool. 00:03:12.500 --> 00:03:15.860 I was a TA in college and had to grade a lot of like calculus tests and stuff. 00:03:15.860 --> 00:03:20.780 This seems really lovely compared to the alternative, honestly. 00:03:20.780 --> 00:03:21.340 It's great. 00:03:21.340 --> 00:03:21.580 Yeah. 00:03:21.720 --> 00:03:24.900 Sometimes when people are doing their assignments, they can get pretty upset. 00:03:24.900 --> 00:03:26.120 Things aren't working out. 00:03:26.120 --> 00:03:27.120 It's really frustrating. 00:03:27.120 --> 00:03:27.640 Yeah. 00:03:27.640 --> 00:03:28.540 They might even swear. 00:03:28.540 --> 00:03:29.220 They might. 00:03:29.220 --> 00:03:37.680 And they might do it in like a public forum or maybe they do it in like a GitHub commit that is going to be public and you don't want it there. 00:03:37.680 --> 00:03:39.760 So you might want to check that. 00:03:39.760 --> 00:03:47.040 And there's a couple of ways to check for profanity check. 00:03:47.040 --> 00:03:48.080 Profanity check. 00:03:48.080 --> 00:03:49.280 Profanity dash check. 00:03:49.920 --> 00:03:50.920 So what's cool about this. 00:03:50.920 --> 00:03:51.740 So what's cool about this. 00:03:51.740 --> 00:04:00.340 I mean, obviously you could say, does it have these seven words or whatever, but this one takes AI and applies it to this problem. 00:04:00.340 --> 00:04:01.000 Basically. 00:04:01.000 --> 00:04:01.800 Wow. 00:04:01.880 --> 00:04:10.840 It takes a linear SVM model trained on 200,000 human labeled samples of clean and profane text. 00:04:10.840 --> 00:04:13.360 So this string is bad. 00:04:13.360 --> 00:04:15.300 This sentence is good. 00:04:15.300 --> 00:04:16.400 This phrase is bad. 00:04:16.400 --> 00:04:17.200 This phrase is good. 00:04:17.340 --> 00:04:26.180 And then it uses that to understand how similar whatever you're looking at is to something like one of these bad phrases. 00:04:26.180 --> 00:04:27.040 Isn't that cool? 00:04:27.040 --> 00:04:27.420 Yeah. 00:04:27.420 --> 00:04:27.920 Very. 00:04:27.920 --> 00:04:33.940 So one of the problems with a lot of the systems out there that are more simple is they just have like explicitly bad words. 00:04:33.940 --> 00:04:44.200 But as you can imagine, there are many, many bad words that you might forget or there's some slightly different way of saying some other thing and they fall through. 00:04:44.200 --> 00:04:46.660 So this one turns out to catch a lot of them. 00:04:46.660 --> 00:04:48.900 And it's also super, super fast. 00:04:48.900 --> 00:04:56.420 So there's another one out there called profanity dash filter, which is more sophisticated than a lot of these, you know, like just are these words in here? 00:04:56.420 --> 00:04:56.800 Checks. 00:04:56.800 --> 00:05:06.200 This one is similar, but because it creates this model and just uses the result, it's actually like 300 to 400 times faster than the other one. 00:05:06.200 --> 00:05:06.620 That's cool. 00:05:06.620 --> 00:05:10.720 If you have 300 to 400 times faster, not percent times, right? 00:05:10.720 --> 00:05:14.880 Like 13 seconds versus 24 milliseconds type of difference. 00:05:14.880 --> 00:05:15.880 That's pretty awesome. 00:05:15.980 --> 00:05:21.200 And the speed really matters if you're, especially if the amount of text you're filtering is huge. 00:05:21.200 --> 00:05:21.500 Right. 00:05:21.500 --> 00:05:23.980 Or a whole bunch of stuff real time or something like that. 00:05:23.980 --> 00:05:25.740 And so it's super simple to use. 00:05:25.740 --> 00:05:27.020 It has basically two functions. 00:05:27.020 --> 00:05:31.600 It's predict whether or not something is bad or give the probability. 00:05:31.840 --> 00:05:35.520 So you can call predict and give it some text and it'll give you like zero one. 00:05:35.520 --> 00:05:37.400 Or you can say, give me the probability. 00:05:37.400 --> 00:05:42.400 And it'll say, we think this is 76.3% bad. 00:05:42.400 --> 00:05:44.480 Do with that what you will. 00:05:44.480 --> 00:05:49.920 So you can take it as black and white or gray and then just decide how gray you'll let it get. 00:05:49.920 --> 00:05:50.160 Okay. 00:05:50.240 --> 00:05:53.000 So I'm like, I'm redoing one of my websites. 00:05:53.000 --> 00:05:57.840 Maybe I'll do this on my own blog posts and make sure that I haven't. 00:05:58.580 --> 00:06:02.420 Just curious to see what my confidence level is that they're clean. 00:06:02.420 --> 00:06:03.300 Yeah, exactly. 00:06:03.300 --> 00:06:05.760 I think a lot of people don't have this problem. 00:06:05.760 --> 00:06:11.280 But if your problem is to take user input and evaluate it for this characteristic, like that would be a complete pain. 00:06:11.280 --> 00:06:11.500 Right. 00:06:11.560 --> 00:06:17.340 And so here's a pip install one-liner sort of thing you can do that will help a lot, I think. 00:06:17.340 --> 00:06:17.580 Yeah. 00:06:17.580 --> 00:06:18.180 Neat. 00:06:18.180 --> 00:06:18.440 Yeah. 00:06:18.440 --> 00:06:19.480 Yes, indeed. 00:06:19.480 --> 00:06:20.060 All right. 00:06:20.060 --> 00:06:20.800 What's the next one? 00:06:20.800 --> 00:06:23.060 Something we've never talked about on this show, right? 00:06:23.060 --> 00:06:27.160 We've actually talked, of course, talked about packaging quite a bit. 00:06:27.160 --> 00:06:38.700 So dealing with packages, if you're dealing with Python a lot, like the difference between a module and a package in the file system and then an installable package that you can distribute, 00:06:38.700 --> 00:06:40.840 that all just becomes second nature. 00:06:40.840 --> 00:06:42.740 And we don't even really think about it anymore. 00:06:42.740 --> 00:06:48.020 But as I'm working with different people and different people are starting to work in Python around you, 00:06:48.020 --> 00:06:51.800 sometimes you have somebody that you need to explain this to. 00:06:51.800 --> 00:06:58.940 And it's hard for me to remember what it was like to not know all this stuff. 00:06:58.940 --> 00:07:04.660 So I bookmarked this article called An Introduction to Python Packages for Absolute Beginners. 00:07:04.940 --> 00:07:18.040 And it's just a nice, gentle discussion about somebody trying to share some code and then describes modules and packages and using packages and installing and what import means and a bunch of stuff like that. 00:07:18.040 --> 00:07:18.560 Yeah. 00:07:18.660 --> 00:07:23.440 So I think this would be good either to hand around or just review before you go explain it to somebody. 00:07:23.440 --> 00:07:23.720 Right. 00:07:23.720 --> 00:07:28.700 We get so excited about jumping in and talking about poetry or pip enf or all these other things. 00:07:28.700 --> 00:07:31.320 And it's just like, wait, what are these? 00:07:31.320 --> 00:07:33.100 You know, when you're new, it's like, what are these things? 00:07:33.100 --> 00:07:34.980 Like, how do I make a package? 00:07:34.980 --> 00:07:36.860 You know, how do I share it? 00:07:36.860 --> 00:07:41.420 You know, people probably start out with just like one giant Python file. 00:07:41.420 --> 00:07:45.260 And like, that's the whole, the whole app is just crammed into the one file even. 00:07:45.260 --> 00:07:45.480 Right. 00:07:45.600 --> 00:07:51.620 And people share the code by just emailing it around or copying it into different repos and stuff. 00:07:51.620 --> 00:07:54.000 And there's, yeah, there are better ways. 00:07:54.000 --> 00:08:03.720 To me, it's a little annoying that the word package has multiple meanings because it's Python calls just a directory with an init in it. 00:08:03.720 --> 00:08:04.840 That's a package. 00:08:04.840 --> 00:08:08.780 But that's not what PyPI is full of. 00:08:08.780 --> 00:08:09.060 Right. 00:08:09.060 --> 00:08:10.240 Distributions. 00:08:10.240 --> 00:08:12.060 Like wheels and all that stuff, right? 00:08:12.060 --> 00:08:13.660 Like, yeah, a whole nother level. 00:08:13.760 --> 00:08:16.460 I do agree that those are like oddly the same and different. 00:08:16.460 --> 00:08:17.020 Yeah. 00:08:17.020 --> 00:08:17.340 Yeah. 00:08:17.340 --> 00:08:18.100 Definitely confusing. 00:08:18.100 --> 00:08:18.700 So this is good. 00:08:18.700 --> 00:08:24.280 So if you're confused about how your app is working, we know a company that can help, right, Brian? 00:08:24.280 --> 00:08:24.940 Yes, we do. 00:08:24.940 --> 00:08:25.400 DataDog. 00:08:25.400 --> 00:08:27.840 So DataDog sponsoring the show, as I said at the opening. 00:08:27.840 --> 00:08:34.820 They're a cloud scale monitoring platform that brings together all your metrics, logs, distributed traces all into one place. 00:08:35.300 --> 00:08:48.640 And it will auto instrument things like Django or Flask or Postgres and let you track requests across those different pieces of infrastructure and put them all back together to know why it was slow, where it was working, things like that. 00:08:48.640 --> 00:08:49.280 So that's pretty awesome. 00:08:49.280 --> 00:08:53.040 Check them out at pythonbytes.fm/DataDog. 00:08:53.200 --> 00:08:56.940 Go do a free trial and they will send you a cool DataDog t-shirt. 00:08:56.940 --> 00:08:59.060 So definitely check them out. 00:08:59.060 --> 00:08:59.880 It helps support the show. 00:08:59.880 --> 00:09:00.960 Plus the t-shirts are cool. 00:09:00.960 --> 00:09:02.060 And the t-shirts are very cool. 00:09:02.060 --> 00:09:03.120 They have a cute little dog on them. 00:09:03.120 --> 00:09:09.300 Now, I'm going to bring up something on here that we don't spend a whole lot of time on. 00:09:09.300 --> 00:09:11.300 And maybe it's even a little bit controversial. 00:09:11.300 --> 00:09:11.880 What do you think? 00:09:11.880 --> 00:09:13.520 I'm looking forward to talking about this. 00:09:13.520 --> 00:09:14.600 Yeah, I figured you are. 00:09:14.600 --> 00:09:16.280 I figured you have an opinion one way or the other. 00:09:16.360 --> 00:09:25.260 So the idea is in Python, we can usually get away with replacing our dependencies. 00:09:25.260 --> 00:09:36.980 Like if we're talking to a database or a web service, we can kind of cancel that out so we can test our code by doing like some sort of patch operation or something to that effect. 00:09:36.980 --> 00:09:37.180 Right. 00:09:37.180 --> 00:09:38.680 We can get it out of the way. 00:09:38.680 --> 00:09:53.640 But this guy named Yasha Gutzur, hopefully I got that closely right, sent us a message that said, hey, I've been reviewing all of the Python dependency injection and IOC inversion control containers around Python. 00:09:53.640 --> 00:10:01.240 And I know that some folks say it's not even necessary, but on large apps, I think there's a lot of value in making your dependencies more explicit. 00:10:01.240 --> 00:10:01.720 Interesting. 00:10:01.720 --> 00:10:02.080 Yeah. 00:10:02.080 --> 00:10:04.700 So he sent us a big long list of all the options, basically. 00:10:04.700 --> 00:10:07.260 And he did a bunch of good research for us. 00:10:07.260 --> 00:10:07.520 Awesome. 00:10:07.520 --> 00:10:07.780 Yeah. 00:10:07.780 --> 00:10:10.920 So I'll just read off a couple of them here. 00:10:10.920 --> 00:10:12.040 We got five or six. 00:10:12.040 --> 00:10:19.920 So we have one called dependency injector, which apparently requires some tricks to get installed on Windows, but he couldn't get it quite working. 00:10:19.920 --> 00:10:21.820 But it looks pretty good. 00:10:21.820 --> 00:10:23.520 I'm kind of mediocre on that one. 00:10:23.520 --> 00:10:26.660 There's injector, which is fairly Java-esque. 00:10:26.660 --> 00:10:33.660 There's pinject, probably pinject, P-I-N-J-E-C-T, something like that. 00:10:34.360 --> 00:10:39.820 And this one had kind of gone unmaintained for about five years, a long time. 00:10:39.820 --> 00:10:44.280 But now there's new folks working on it, so that's kind of cool, and it seems like it's doing a lot. 00:10:44.280 --> 00:10:50.060 There's Python inject, which has got some really nice testing features. 00:10:50.060 --> 00:10:53.200 It's got like built-in mocking stuff and things like that. 00:10:53.460 --> 00:10:55.400 Are you starting to notice a similarity in the name? 00:10:55.400 --> 00:10:56.260 In the naming? 00:10:56.260 --> 00:10:57.400 Yeah. 00:10:58.300 --> 00:11:05.720 There's another one that's just here more for a complete mistake, DIPy, but it only works on Python 3.4, apparently. 00:11:05.720 --> 00:11:08.360 So I appreciate the comment here. 00:11:08.360 --> 00:11:12.160 It's like, you know, this is a legacy, so I can't really be touching on this. 00:11:12.160 --> 00:11:12.880 Like, this is no good. 00:11:12.880 --> 00:11:15.580 And then the next two, I think, are really quite good. 00:11:15.580 --> 00:11:15.820 Okay. 00:11:15.820 --> 00:11:26.340 There's Serum, which I think actually is a pretty interesting thing to look at, because what it does is it primarily is driven through class decorators. 00:11:26.340 --> 00:11:27.480 Okay? 00:11:27.560 --> 00:11:35.280 So what you do is you go to, like, some class here, and you say, this class is a dependency. 00:11:35.280 --> 00:11:39.120 So you put an add dependency on to the class definition. 00:11:39.120 --> 00:11:46.500 And then later on, you can put an add inject on top of either a function call or a class. 00:11:46.500 --> 00:11:58.040 And if the class has, like, say, like a log field, a class-level log field, it will automatically be set to an instance of that dependency based on the type annotation. 00:11:58.040 --> 00:12:03.960 There's an interesting way that it kind of uses type annotations and class decorators to link that back together. 00:12:03.960 --> 00:12:04.380 Yeah. 00:12:04.380 --> 00:12:04.960 Okay. 00:12:04.960 --> 00:12:05.320 Okay. 00:12:05.320 --> 00:12:08.240 And then the final one is this thing called HAPS. 00:12:08.240 --> 00:12:15.520 And HAPS is pretty cool, and it's really lightweight and quite simple, also based on type annotations. 00:12:15.520 --> 00:12:19.640 So a lot of them are taking advantage of the, I think it's probably 3.6, either 3.5 or 3.6. 00:12:19.640 --> 00:12:22.700 But I think it's 3.6 because of some of the ways it's using type annotations. 00:12:22.700 --> 00:12:31.520 But the point is using the modern features of Python 3 to help figure out a lot of the configuration and how stuff wires together. 00:12:31.520 --> 00:12:31.900 Okay. 00:12:31.900 --> 00:12:37.280 That's the survey that Yosha gave us, and thank you for that. 00:12:37.280 --> 00:12:37.740 That was cool. 00:12:37.740 --> 00:12:42.380 Now, you want to have a quick chat about whether Python needs dependency injection? 00:12:42.380 --> 00:12:43.500 What do you think? 00:12:43.500 --> 00:12:48.500 I'm still confused as to what the problem is that it's trying to solve, is my thing. 00:12:48.500 --> 00:12:48.980 I hear you. 00:12:48.980 --> 00:12:53.580 And I think, let me try to talk about the other side, although I find myself not doing this very often. 00:12:53.580 --> 00:12:57.300 So for what it's worth, I don't do dependency injection a lot. 00:12:57.300 --> 00:13:00.900 So I think the fundamental, let's do it a couple steps. 00:13:00.960 --> 00:13:10.560 I think the fundamental starting point is it's trying to write object-oriented Python or even functions following the open-closed principle, which is one of the solid principles. 00:13:10.560 --> 00:13:13.080 And it's pretty interesting, this principle. 00:13:13.080 --> 00:13:20.720 It says that software entities like classes and functions should be open for extension but closed for modification, which is like, what the heck does that mean? 00:13:21.080 --> 00:13:29.920 Basically, I should be able to change the behavior of this class or this function without touching the source code to modify it, which kind of sounds like, wait, how do you do that? 00:13:29.920 --> 00:13:30.720 How is that possible? 00:13:31.160 --> 00:13:34.540 But imagine it has a logging feature. 00:13:34.540 --> 00:13:41.860 Instead of just internally creating one, if you could pass in the logger, you could pass in different loggers changing the behavior of how it logs. 00:13:41.860 --> 00:13:44.100 So open-closed principle, that's how it works. 00:13:44.100 --> 00:13:49.120 I think the general motivation for all of these frameworks is they're like, that's cool. 00:13:49.120 --> 00:13:50.020 I want to do that. 00:13:50.020 --> 00:13:54.860 It's good for testing because I could pass in a fake logger or a mock database. 00:13:54.860 --> 00:13:57.780 I could pass that in and not touch the database. 00:13:58.780 --> 00:14:02.000 And I think that's generally a good feature, a good way to do things. 00:14:02.000 --> 00:14:10.580 The problem is if you do that at low-level stuff and at all the different layers of your app, at the top, you've got to pass 20 things to the top-level things. 00:14:10.580 --> 00:14:14.520 So it can distribute them down as it creates all the objects further down the graph, right? 00:14:14.520 --> 00:14:20.940 So then people have come up with IOC containers, which get registered for when I need one of these. 00:14:20.940 --> 00:14:22.120 I really give it one of those. 00:14:22.120 --> 00:14:25.380 And then I create this object by giving it three of these things at once. 00:14:25.520 --> 00:14:32.240 And that starts to get really hard in my mind to know, like, okay, what is being done here? 00:14:32.240 --> 00:14:35.080 Like, I see a bunch of abstract types and I can't even tell. 00:14:35.080 --> 00:14:39.040 An example of, like, you don't know what database you're going to use. 00:14:39.040 --> 00:14:45.660 Another, you can use the injection thing, but it kind of ripples through a whole bunch of layers of code. 00:14:45.660 --> 00:14:46.280 It does. 00:14:46.420 --> 00:14:47.680 The part that I don't like. 00:14:47.680 --> 00:15:00.020 Whereas another way to do this is to kind of bypass all of the middle stuff and at a top level have, and like Flask, I think Flask does this sort of a thing. 00:15:00.260 --> 00:15:11.300 And a lot, this is a common design is to, you define, instantiate the real objects at a, like an application level and just set those where they need to be set. 00:15:11.300 --> 00:15:13.820 So there's like a, whatever the real database is. 00:15:13.820 --> 00:15:14.180 Right. 00:15:14.180 --> 00:15:18.680 Go look up the service for the database and everybody can ask that thing to give it the database, right? 00:15:18.680 --> 00:15:25.200 And then everybody just uses the same interface and we don't need to pass it through all the levels of constructors and stuff. 00:15:25.260 --> 00:15:27.160 It can just kind of bypass all of that. 00:15:27.160 --> 00:15:31.260 I guess then, because that's how I generally do things. 00:15:31.260 --> 00:15:36.600 And then for testing, yeah, I'm okay with patching and monkey patching and stuff like that. 00:15:36.600 --> 00:15:37.340 I hear you. 00:15:37.340 --> 00:15:45.940 I think in Python, it is certainly something that's open more for debate because we do have these alternative ways to accomplish the same thing like monkey patching. 00:15:45.940 --> 00:15:48.120 Now, I don't know. 00:15:48.120 --> 00:15:51.220 I'm kind of a fan of the open close principle in general, 00:15:51.220 --> 00:15:55.720 but I do think it can just become like too much when you put it all together. 00:15:55.720 --> 00:16:00.560 And certainly I've worked on some applications that did this all over the place. 00:16:00.560 --> 00:16:05.400 And it was some of the most frustrating code I've ever had to like work through because it was just like every step. 00:16:05.400 --> 00:16:13.560 You're like, I have, there's four things working together and I don't know what any of them are right now because of some configuration setting somewhere other than that. 00:16:13.560 --> 00:16:14.220 So I don't know. 00:16:14.220 --> 00:16:16.200 I'm kind of, I'm on the fence. 00:16:16.360 --> 00:16:23.380 Like some parts of this I think are cool and some I think can go too far, but I guess, you know, check out HAPS if this kind of stuff is interesting to you. 00:16:23.380 --> 00:16:24.720 It is, it is pretty well done. 00:16:24.720 --> 00:16:31.340 I think that one of the places for it is if people are really used to using this kind of a model and then coming to Python. 00:16:31.340 --> 00:16:32.760 Yeah, you can do it here too. 00:16:32.760 --> 00:16:33.020 Yeah. 00:16:33.020 --> 00:16:35.280 It's just, I'm not, I'm not sure I'm there. 00:16:35.280 --> 00:16:35.580 Yeah. 00:16:35.580 --> 00:16:43.680 I think there's simpler things in IOC containers, but this podcast is probably a little short if we're going into them, but it's certainly an interesting thing to think about. 00:16:43.680 --> 00:16:45.180 And here's a bunch of options. 00:16:45.460 --> 00:16:45.600 Yep. 00:16:45.600 --> 00:16:46.020 Cool. 00:16:46.020 --> 00:16:52.760 You know, after all that, Brian, I feel like I just need something gentle, like a gentle conversation about like a soft, fuzzy animal. 00:16:52.760 --> 00:16:53.800 Yeah. 00:16:53.800 --> 00:16:56.080 Like a gentle introduction to pandas. 00:16:56.080 --> 00:16:56.600 Yes. 00:16:56.600 --> 00:16:58.440 Well, maybe not an animal, but yeah, something gentle. 00:16:58.440 --> 00:16:59.340 Tell us about pandas. 00:16:59.420 --> 00:17:05.580 So this is another kind of a newbie thing, but I, we're starting to use pandas data frames at work. 00:17:05.580 --> 00:17:14.680 And I kind of, I really kind of needed a pretend I'm just starting out, which I am and kind of tell me how these things work. 00:17:14.680 --> 00:17:23.340 And so this is a, it's called a gentle introduction to pandas, but it's really a gentle introduction to the data structures, series and data frame. 00:17:23.660 --> 00:17:25.360 The series are interesting. 00:17:25.360 --> 00:17:29.020 I think it's just a precursor to try to jump you into data frames. 00:17:29.340 --> 00:17:32.000 That's where the real fun gets, starts to happen. 00:17:32.000 --> 00:17:36.540 Goes through about a half an article talking about arrays, series. 00:17:36.540 --> 00:17:39.140 How do you create series from arrays and dictionaries? 00:17:39.400 --> 00:17:47.680 And I didn't know you could create a, a series from, from just a scaler and give it a bunch, a different index and it'll like fill it in. 00:17:47.680 --> 00:17:48.380 That's pretty cool. 00:17:48.380 --> 00:17:49.080 Oh, that is cool. 00:17:49.080 --> 00:17:49.620 Yeah. 00:17:49.620 --> 00:17:56.940 But then it jumps into data frames and then talks about sorting and slicing and how do you select things by label or position. 00:17:56.940 --> 00:18:05.820 And then what, one of the things and how easy it is to get the statistics on columns and then how to get things in and out of data frames. 00:18:05.820 --> 00:18:07.480 So importing and exporting. 00:18:07.760 --> 00:18:17.500 And then, you know, where you take it from there is, depends on your problem space, but this is kind of a really good, why do we call these things data frames and why do we care about them? 00:18:17.500 --> 00:18:20.500 If you need to understand them, this is a decent article. 00:18:20.500 --> 00:18:20.740 Yeah. 00:18:20.740 --> 00:18:25.940 If you need to understand them in 15 minutes, this is kind of a no fluff, keep it simple one. 00:18:25.940 --> 00:18:26.240 Yeah. 00:18:26.240 --> 00:18:28.000 Nice little article by Wilson Boussaka. 00:18:28.000 --> 00:18:28.720 Well done. 00:18:28.720 --> 00:18:30.040 Let's see. 00:18:30.040 --> 00:18:34.980 Medium tells me it's a five minute read, but I bet Medium's not taking into account the code. 00:18:34.980 --> 00:18:36.300 So 15 minutes. 00:18:36.300 --> 00:18:36.720 How about that? 00:18:36.720 --> 00:18:37.920 Yeah, I think so. 00:18:37.920 --> 00:18:38.140 Right. 00:18:38.140 --> 00:18:44.000 So this last one I have for you, Brian, I think, I think it's going to be a little bit of a shock. 00:18:44.000 --> 00:18:50.340 It'll come across a little bit weird at first, but the more you look at it, the more it starts to sound appealing, let's say. 00:18:50.340 --> 00:18:50.660 Yeah. 00:18:50.660 --> 00:18:50.960 All right. 00:18:50.960 --> 00:18:52.040 So I'm going to give you some advice. 00:18:52.040 --> 00:18:53.100 I'm going to tell you about it. 00:18:53.100 --> 00:18:58.500 So the advice, you know, you also get all sorts of advice, like don't format your code like this. 00:18:58.500 --> 00:19:02.120 Don't have a bunch of multiple. 00:19:02.120 --> 00:19:07.200 If this is equal to this value and that value and that value, maybe do an end test. 00:19:07.260 --> 00:19:10.400 So there's like sort of Pythonic ways to do conditionals and whatnot. 00:19:10.400 --> 00:19:18.120 The advice here is to never, not almost never, says don't use the greater than sign in programming. 00:19:18.120 --> 00:19:18.780 Yeah. 00:19:18.780 --> 00:19:19.460 It's crazy, right? 00:19:19.520 --> 00:19:21.180 It seems like kind of a bold statement. 00:19:21.180 --> 00:19:22.800 I'm like, well, we have it. 00:19:22.800 --> 00:19:24.200 It must be useful somewhere. 00:19:24.200 --> 00:19:25.420 It must be useful. 00:19:25.420 --> 00:19:26.980 And why would we not want to use it? 00:19:26.980 --> 00:19:32.320 So this is an article by a good friend of mine, Llewellyn Falco, who I've known for a long time. 00:19:32.320 --> 00:19:36.500 But someone else sent me this article, which I thought was a pretty interesting coincidence. 00:19:36.500 --> 00:19:45.100 And Llewellyn has a really interesting way of like looking at straightforward stuff and then just getting it down to its essence. 00:19:45.100 --> 00:19:48.220 So he says, like, let's look at this problem. 00:19:48.300 --> 00:19:54.780 Let's suppose I want to check whether a number, let's call it x, it's a variable, is between 5 and 10. 00:19:54.780 --> 00:19:58.160 There are a lot of ways that we can do this. 00:19:58.160 --> 00:20:02.140 We could say x greater than 5 and 10 greater than x. 00:20:02.140 --> 00:20:06.260 Or we could say x greater than 5 and x less than 10, right? 00:20:06.260 --> 00:20:07.480 Those are equivalent. 00:20:07.480 --> 00:20:11.040 But why should you choose one over the other? 00:20:11.040 --> 00:20:15.200 Well, he lists off these six different ways of doing this. 00:20:15.200 --> 00:20:16.400 He says, actually, here's all the ways. 00:20:16.400 --> 00:20:17.120 Oh, no, wait. 00:20:17.200 --> 00:20:18.260 Look, one of them is wrong. 00:20:18.260 --> 00:20:20.420 Go back and figure out which one is wrong. 00:20:20.420 --> 00:20:21.860 And it's like not very obvious. 00:20:21.860 --> 00:20:25.580 You know, you kind of got to go through and think through every little bit. 00:20:25.580 --> 00:20:26.520 All right. 00:20:26.520 --> 00:20:31.560 So he says, look, if you remove the greater than sign, there's actually only two ways to say this. 00:20:32.120 --> 00:20:36.120 x less than 10 and 5 less than x, which is kind of weird. 00:20:36.120 --> 00:20:39.600 Or 5 less than x and x less than 10. 00:20:39.600 --> 00:20:48.040 So in that last one, it's cool because the variable you're trying to test between 5 and 10 is literally between the 5 and the 10 in that statement. 00:20:48.040 --> 00:20:50.840 Like it's in text, it's between, and it's actually between. 00:20:50.840 --> 00:20:51.240 Yeah. 00:20:51.380 --> 00:20:57.320 So here you can test like this containment interval bit completely with no greater than. 00:20:57.320 --> 00:20:58.540 That's how I code. 00:20:58.540 --> 00:21:06.840 I think of, especially, well, especially with numbers, I think of the, that all of the comparisons need to kind of be on the number line. 00:21:06.840 --> 00:21:07.300 Yes. 00:21:07.400 --> 00:21:08.800 You can think about them easier. 00:21:08.800 --> 00:21:15.480 I've never really seen it as it put in place as a rule, kind of a rule of thumb of just don't use the greater than sign. 00:21:15.480 --> 00:21:15.700 Yeah. 00:21:15.700 --> 00:21:16.380 It's really interesting. 00:21:16.380 --> 00:21:22.820 And this analogy back to the number line is perfect because it's like, well, where do you want the variable to be relative to those? 00:21:22.820 --> 00:21:27.120 So if you want it to be between, then as you say, like 5 less than x, x less than 10. 00:21:27.120 --> 00:21:27.440 Right? 00:21:27.440 --> 00:21:28.460 So it's between. 00:21:28.460 --> 00:21:32.280 If you want to test that it's outside there, you could do the same thing. 00:21:32.280 --> 00:21:34.820 x less than 5 or 10 less than x. 00:21:34.820 --> 00:21:36.820 And you put the variable outside the numbers. 00:21:36.820 --> 00:21:37.520 Right? 00:21:37.520 --> 00:21:45.540 So you can do this number line sort of relative bit with both, you know, and and or and containment and not contained in and things like that. 00:21:45.540 --> 00:21:50.820 We'd kind of be remiss if we didn't mention that this article is referencing all programming languages. 00:21:50.820 --> 00:21:56.120 If you're doing Python, of course, you would just say 5 is less than x is less than 10. 00:21:56.120 --> 00:21:57.480 You can, you don't need the and. 00:21:57.480 --> 00:21:57.820 Nice. 00:21:57.820 --> 00:22:02.460 And also somebody said, okay, I'm all for, I follow you on this. 00:22:02.460 --> 00:22:03.120 This is great. 00:22:03.120 --> 00:22:05.940 And I'm with you. 00:22:05.940 --> 00:22:10.960 But how do you say I would like all the numbers greater than one without the greater than sign? 00:22:10.960 --> 00:22:15.860 And so the answer is, of course, one less than x. 00:22:15.860 --> 00:22:16.720 Yeah. 00:22:16.720 --> 00:22:21.480 There's times where it's a little, that's why it's not like it's more of a rule of thumb. 00:22:21.480 --> 00:22:22.100 Yeah. 00:22:22.140 --> 00:22:25.000 I think because there's times where it just doesn't look right. 00:22:25.000 --> 00:22:27.020 And you kind of, you have to go for maintenance. 00:22:27.020 --> 00:22:30.380 If it, if it just looks weird, then change it. 00:22:30.380 --> 00:22:32.820 I brought this in because I thought it was interesting. 00:22:32.820 --> 00:22:35.500 And like when I first read it, I'm like, well, that's dumb advice. 00:22:35.500 --> 00:22:36.120 What is this? 00:22:36.120 --> 00:22:37.360 You know what I mean? 00:22:37.360 --> 00:22:38.100 And I read it. 00:22:38.100 --> 00:22:41.260 I'm like, actually, you know, this makes a lot of sense a lot of the time. 00:22:41.260 --> 00:22:42.640 But it's, I agree. 00:22:42.640 --> 00:22:45.300 If you have one thing, you want to say x is greater than one. 00:22:45.300 --> 00:22:48.760 You know, don't twist around so you don't have to have the greater than sign. 00:22:48.760 --> 00:22:50.840 Just like say the most straightforward thing. 00:22:50.840 --> 00:22:54.740 But if you're doing more complicated comparisons, then I think it's worthwhile. 00:22:55.060 --> 00:22:55.220 Yeah. 00:22:55.220 --> 00:23:01.480 Like I would say, like, for instance, a series of if clauses, if you have, and you're not 00:23:01.480 --> 00:23:07.040 really testing both ends, if you're doing like, if x is greater than the max, then do something. 00:23:07.040 --> 00:23:11.580 And if all the comparisons have x on the left, I wouldn't change it just because of this. 00:23:11.580 --> 00:23:12.560 But, you know, anyway. 00:23:12.560 --> 00:23:13.000 All right, Brian. 00:23:13.000 --> 00:23:14.960 Well, that's it for all of our main topics. 00:23:14.960 --> 00:23:18.000 I got a few extras to share with everyone while we're here. 00:23:18.000 --> 00:23:19.140 Just really quick and short things. 00:23:19.140 --> 00:23:21.500 And of course, not be forgotten as our joke. 00:23:21.500 --> 00:23:23.140 But you got any extras to share with everyone? 00:23:23.260 --> 00:23:28.020 I did mention last time that I was having some issues with pythontesting.net. 00:23:28.020 --> 00:23:29.340 I think I mentioned that. 00:23:29.340 --> 00:23:31.260 But with SSL and stuff. 00:23:31.260 --> 00:23:33.720 But that's all resolved and fixed. 00:23:33.720 --> 00:23:34.420 Wait, wait, wait. 00:23:34.420 --> 00:23:40.080 So if I go over here and I pull this up in Chrome, is it going to tell me that it's secure? 00:23:40.080 --> 00:23:40.700 It should. 00:23:40.700 --> 00:23:41.260 Nice. 00:23:41.260 --> 00:23:43.760 Yeah, testing code over SSL. 00:23:43.760 --> 00:23:44.060 Beautiful. 00:23:44.060 --> 00:23:47.260 It's now, it's still kind of a WordPress thing is what I use. 00:23:47.260 --> 00:23:48.640 And I'm not thrilled with that. 00:23:48.640 --> 00:23:52.280 So I have a side project going on to convert that to something else. 00:23:52.760 --> 00:23:54.140 But it's not urgent anymore. 00:23:54.140 --> 00:23:54.920 Yeah, that's good. 00:23:54.920 --> 00:23:59.060 Well, you'll have to give us the full report once you get it all fixed up. 00:23:59.060 --> 00:23:59.340 Okay. 00:23:59.340 --> 00:24:01.160 So you said you got a bunch of stuff for us. 00:24:01.160 --> 00:24:01.540 I do. 00:24:01.540 --> 00:24:02.340 I'll go through them quick. 00:24:02.340 --> 00:24:05.600 First of all, there's a new Python podcast, which is pretty exciting. 00:24:05.600 --> 00:24:08.600 And this one is focused on teaching Python. 00:24:08.600 --> 00:24:10.580 And do you know what the name of it is? 00:24:10.580 --> 00:24:12.320 I think it's probably teaching Python. 00:24:12.560 --> 00:24:13.280 Yeah, it is. 00:24:13.280 --> 00:24:18.460 So Teaching Python is by Kelly Perdez and Sean Tibor. 00:24:18.460 --> 00:24:20.140 Sorry about messing up the names. 00:24:20.140 --> 00:24:21.200 But they're doing a podcast. 00:24:21.200 --> 00:24:25.680 These are two middle school teachers who are learning and teaching Python to their students 00:24:25.680 --> 00:24:28.200 and go, you know, basically documenting that journey. 00:24:28.200 --> 00:24:32.440 So if you're interested in that, especially if you're a teacher or you work with kids, 00:24:32.440 --> 00:24:34.740 I think this will be really, really helpful for you. 00:24:34.740 --> 00:24:35.360 So you can check that out. 00:24:35.440 --> 00:24:40.620 I'm about halfway through their backlog so far, and I really like it so far. 00:24:40.620 --> 00:24:41.560 Yeah, they're doing a nice job. 00:24:41.560 --> 00:24:49.000 One of the things that had kept people from using GitHub for their private work was that 00:24:49.000 --> 00:24:52.600 you had to pay for private repositories on GitHub, no matter what. 00:24:52.600 --> 00:24:52.940 Yes. 00:24:52.940 --> 00:24:53.360 Right. 00:24:53.360 --> 00:24:57.660 So people would use Bitbucket because Bitbucket had free private repositories. 00:24:57.660 --> 00:25:02.060 Well, GitHub decided we're also going to have free private repositories. 00:25:02.060 --> 00:25:05.140 So if you're working on projects that they have to stay private, 00:25:05.240 --> 00:25:08.880 you just want them private, you can now use GitHub without paying anything. 00:25:08.880 --> 00:25:10.920 There's been some weird reactions to it, 00:25:10.920 --> 00:25:15.860 but they're just sort of following the model of Bitbucket and GitLab now. 00:25:15.860 --> 00:25:18.560 So I don't think there's anything weird going on. 00:25:18.560 --> 00:25:18.980 Exactly. 00:25:18.980 --> 00:25:21.640 Competition is a good thing, and here we have it. 00:25:21.640 --> 00:25:23.300 So it's not like entirely free. 00:25:23.300 --> 00:25:25.780 It's not like GitHub decided they're not going to make money anymore. 00:25:25.780 --> 00:25:29.300 You can only have three contributors to the private repository, 00:25:29.300 --> 00:25:31.320 and so there's limits and things like that. 00:25:31.320 --> 00:25:34.220 But still pretty cool for most things. 00:25:34.220 --> 00:25:34.560 Yep. 00:25:34.560 --> 00:25:34.760 All right. 00:25:35.040 --> 00:25:39.700 Also, very quickly, some early details about Europython are available, 00:25:39.700 --> 00:25:41.400 and it's looking pretty sweet. 00:25:41.400 --> 00:25:42.220 I'd love to go. 00:25:42.220 --> 00:25:43.320 I don't know if I'll be able to. 00:25:43.320 --> 00:25:43.900 Yeah, me too. 00:25:43.900 --> 00:25:45.660 Yeah, so they just announced Europython. 00:25:45.660 --> 00:25:51.560 It's going to be in Basel, Switzerland, July 8th to 14th, and it looks great. 00:25:51.560 --> 00:25:55.020 So I put a link to the conference site there. 00:25:55.020 --> 00:25:58.040 I don't think they have a call for papers or anything like that out yet, 00:25:58.040 --> 00:25:59.260 but it should be out pretty soon. 00:25:59.360 --> 00:26:06.040 Another thing that has been lacking in the world is good data center support in Africa. 00:26:06.780 --> 00:26:13.380 So I know this because I use AWS to deliver the video course content, 00:26:13.380 --> 00:26:14.700 like actual the videos. 00:26:15.060 --> 00:26:20.660 And I have streaming servers all over the place, like in Brazil or Mumbai or whatever, 00:26:20.660 --> 00:26:23.440 but there's just no way to do that in Africa. 00:26:23.440 --> 00:26:32.340 So the big news is there's an AWS data center coming to South Africa, which is pretty cool for anyone that wants to be closer to that part of the world. 00:26:32.780 --> 00:26:36.960 And finally, Pandas is dropping legacy support. 00:26:36.960 --> 00:26:39.400 No more Python 2 in Pandas. 00:26:39.400 --> 00:26:40.080 Oh, cool. 00:26:40.080 --> 00:26:42.500 Yeah, and that's coming out like this month. 00:26:42.500 --> 00:26:43.900 So it should be good. 00:26:43.900 --> 00:26:47.760 Yeah, this is the year that a ton of projects are dropping Python 2. 00:26:47.760 --> 00:26:48.540 Yeah, for sure. 00:26:48.540 --> 00:26:51.720 So one more major thing. 00:26:51.720 --> 00:26:53.160 We already covered how cool Pandas is. 00:26:53.160 --> 00:26:55.980 It's not going to support legacy Python anymore. 00:26:55.980 --> 00:26:56.880 All right. 00:26:56.880 --> 00:26:58.700 You ready for the joke? 00:26:58.700 --> 00:26:59.000 Yeah. 00:26:59.000 --> 00:26:59.900 Can I click on it now? 00:26:59.900 --> 00:27:00.620 You can click on it. 00:27:00.660 --> 00:27:02.940 This is a visual one, but I can describe it to you folks. 00:27:02.940 --> 00:27:09.720 Now, I just got to do a quick little bit of history here for people who maybe have not seen Harry Potter. 00:27:09.720 --> 00:27:11.240 So this is the Harry Potter joke. 00:27:11.240 --> 00:27:15.480 And there's a point in the Harry Potter movie, I think this might be the first one, 00:27:15.480 --> 00:27:21.680 where Harry Potter has to get on this like long table and is battling, I don't know, someone, something. 00:27:21.680 --> 00:27:23.840 And all the other students are standing around. 00:27:23.840 --> 00:27:26.880 And somebody like conjures a snake, a serpent. 00:27:27.860 --> 00:27:35.160 And in the real show, Harry starts speaking to the thing in its native tongue, which apparently is a freaky thing to do. 00:27:35.160 --> 00:27:36.860 And people were all freaked out. 00:27:36.860 --> 00:27:40.120 And it was called a parcel tongue, something like that, right? 00:27:40.120 --> 00:27:41.060 That he could speak snake. 00:27:41.060 --> 00:27:43.080 So with that, here's the joke. 00:27:43.460 --> 00:27:46.780 So there's a picture, Harry's fighting the snake in that environment. 00:27:46.780 --> 00:27:50.980 And he says, import OS, current path equals OS, get current working to her. 00:27:50.980 --> 00:27:54.260 And just start speaking out Python commands at the snake. 00:27:54.260 --> 00:27:58.080 And Hermione says, I didn't know Harry spoke Python. 00:27:58.080 --> 00:28:02.400 And Ron Weasley says, yeah, he's a parser tongue. 00:28:02.400 --> 00:28:05.400 That's terrible. 00:28:05.400 --> 00:28:06.540 It's really bad. 00:28:06.540 --> 00:28:07.400 It's really bad. 00:28:07.400 --> 00:28:08.600 But there it is. 00:28:08.720 --> 00:28:10.220 And Nick Spirit sent that to us. 00:28:10.220 --> 00:28:13.380 So thank you, Nick, for finding that joke and letting us share it here. 00:28:13.380 --> 00:28:14.420 Yeah, very nerdy. 00:28:14.420 --> 00:28:14.800 Yep. 00:28:14.800 --> 00:28:15.800 He's a parser tongue. 00:28:15.800 --> 00:28:18.840 Well, I think we're going to leave it at that, Brian. 00:28:18.840 --> 00:28:19.800 Thanks for being here. 00:28:19.800 --> 00:28:20.740 Yeah, thank you. 00:28:20.740 --> 00:28:21.200 Yeah, bye. 00:28:21.200 --> 00:28:21.420 Bye. 00:28:21.720 --> 00:28:23.320 Thank you for listening to Python Bytes. 00:28:23.320 --> 00:28:25.860 Follow the show on Twitter via at Python Bytes. 00:28:25.860 --> 00:28:28.740 That's Python Bytes as in B-Y-T-E-S. 00:28:28.740 --> 00:28:32.160 And get the full show notes at pythonbytes.fm. 00:28:32.160 --> 00:28:36.500 If you have a news item you want featured, just visit pythonbytes.fm and send it our way. 00:28:36.500 --> 00:28:39.200 We're always on the lookout for sharing something cool. 00:28:39.200 --> 00:28:42.600 On behalf of myself and Brian Okken, this is Michael Kennedy. 00:28:42.600 --> 00:28:46.120 Thank you for listening and sharing this podcast with your friends and colleagues.