WEBVTT 00:00:00.001 --> 00:00:03.360 Python is said to be a language that comes with batteries included. 00:00:03.360 --> 00:00:06.500 It has many meanings depending on the level you're focusing on. 00:00:06.500 --> 00:00:09.640 The lowest, it's a very rich and expressive language. 00:00:09.640 --> 00:00:16.140 Most commonly, this phrase means Python has a very powerful and comprehensive standard library. 00:00:16.140 --> 00:00:18.200 Itertools or elementary, anyone? 00:00:18.200 --> 00:00:23.620 But more holistically, most of the batteries are external, interchangeable ones from PyPI. 00:00:23.840 --> 00:00:30.120 Right now on PyPI.io, there are over 97,000 packages listed there. 00:00:30.120 --> 00:00:31.300 That's fantastic. 00:00:31.300 --> 00:00:34.740 However, it does lead to a discoverability problem. 00:00:34.740 --> 00:00:37.700 What options do you have for admin backends on web apps? 00:00:37.700 --> 00:00:40.920 How about cryptography or raw socket programming and so on? 00:00:40.920 --> 00:00:43.000 This week, Matt Makai is back with me. 00:00:43.000 --> 00:00:46.420 Remember him talking about deployments on episode 26 last year? 00:00:46.420 --> 00:00:48.900 This time, we're talking about Awesome Python, 00:00:48.900 --> 00:00:54.220 a website and open source project attempting to categorize and sort of rank these options. 00:00:54.220 --> 00:01:00.240 This is Talk Python To Me, episode 96, recorded January 16th, 2016. 00:01:00.240 --> 00:01:03.720 Developers, developers, developers, developers, developers. 00:01:03.720 --> 00:01:06.880 I'm a developer in many senses of the word 00:01:06.880 --> 00:01:11.240 because I make these applications, but I also use these verbs to make this music. 00:01:11.240 --> 00:01:15.780 I construct it line by line, just like when I'm coding another software design. 00:01:15.780 --> 00:01:19.020 In both cases, it's about design patterns. 00:01:19.020 --> 00:01:20.480 Anyone can get the job done. 00:01:20.480 --> 00:01:22.000 It's the execution that matters. 00:01:22.000 --> 00:01:23.460 I have many interests. 00:01:23.460 --> 00:01:24.200 Sometimes you can fly to Python. 00:01:24.200 --> 00:01:27.800 Welcome to Talk Python To Me, a weekly podcast on Python, 00:01:27.800 --> 00:01:30.860 the language, the libraries, the ecosystem, and the personalities. 00:01:30.860 --> 00:01:32.980 This is your host, Michael Kennedy. 00:01:32.980 --> 00:01:34.980 Follow me on Twitter where I'm @mkennedy. 00:01:34.980 --> 00:01:38.860 Keep up with the show and listen to past episodes at talkpython.fm 00:01:38.860 --> 00:01:41.440 and follow the show on Twitter via at Talk Python. 00:01:42.020 --> 00:01:47.900 This episode has been sponsored by AnacondaCon from Continuum Analytics and by Hired. 00:01:47.900 --> 00:01:50.000 Thank you both for supporting the podcast. 00:01:50.000 --> 00:01:51.340 Hey, Matt. 00:01:51.340 --> 00:01:53.080 Welcome back to Talk Python. 00:01:53.080 --> 00:01:53.860 Thanks, Michael. 00:01:53.860 --> 00:01:54.760 It's good to be back. 00:01:54.760 --> 00:01:55.940 It's great to have you back. 00:01:55.940 --> 00:01:59.840 You just pointed out a little bit ago that it's been 70 episodes 00:01:59.840 --> 00:02:04.760 since you were on episode 26 to talk about deployments with Python. 00:02:04.760 --> 00:02:06.020 I can't believe it's been so long. 00:02:06.020 --> 00:02:07.360 It's hard to believe. 00:02:07.360 --> 00:02:09.440 It's been like a year and a half, almost two years. 00:02:09.860 --> 00:02:10.320 Yeah, yeah. 00:02:10.320 --> 00:02:11.260 Well, that was a great episode. 00:02:11.260 --> 00:02:12.160 It was really popular. 00:02:12.160 --> 00:02:16.040 And, you know, the world has changed a lot since then. 00:02:16.040 --> 00:02:19.880 So that's a lot of cool things we're going to be talking about today. 00:02:19.880 --> 00:02:23.660 We're going to focus on stuff that we found, mostly you have found, 00:02:23.660 --> 00:02:25.720 that's awesome in the Python community. 00:02:25.720 --> 00:02:29.440 But before we get into those, let's, you know, 70 episodes ago. 00:02:29.440 --> 00:02:32.080 I'm not sure everybody can remember back 70 episodes. 00:02:32.080 --> 00:02:33.240 What do you do day to day? 00:02:33.580 --> 00:02:33.740 Sure. 00:02:33.740 --> 00:02:36.340 So I'm a developer evangelist at Twilio. 00:02:36.340 --> 00:02:40.060 And Twilio makes it easy for developers to add communications. 00:02:40.060 --> 00:02:44.240 So if you want to send a text message or you want to make a phone call with Python 00:02:44.240 --> 00:02:48.360 or any programming language or add video chat to an application, 00:02:48.360 --> 00:02:49.540 you can do that with Twilio. 00:02:49.540 --> 00:02:54.000 What I do as a developer evangelist, I am, first off, a software developer. 00:02:54.000 --> 00:02:55.040 I write a lot of code. 00:02:55.040 --> 00:02:56.800 Most of my code is open source. 00:02:56.800 --> 00:03:03.920 So it'll be examples for how to use Twilio or even just how to create something as a developer. 00:03:03.920 --> 00:03:05.240 It doesn't have to use Twilio. 00:03:05.240 --> 00:03:11.380 And then I travel and speak at tech conferences all on software development. 00:03:11.380 --> 00:03:12.980 No marketing fluff. 00:03:12.980 --> 00:03:18.800 Just really just being a software developer, I get to write code, explain code, and teach other people, 00:03:18.800 --> 00:03:20.480 which is just absolutely awesome. 00:03:20.480 --> 00:03:21.160 Yeah, that's great. 00:03:21.160 --> 00:03:25.640 I always, I've always thought that these developer evangelist jobs were just fantastic, right? 00:03:25.640 --> 00:03:28.200 Like it's part research and play. 00:03:28.200 --> 00:03:30.820 It's part telling people about stuff that's cool. 00:03:30.820 --> 00:03:34.440 And you have a lot of freedom to kind of learn and explore, right? 00:03:34.440 --> 00:03:34.960 Yeah. 00:03:34.960 --> 00:03:38.620 I mean, the big thing for me is just getting the time to create projects. 00:03:38.620 --> 00:03:41.820 Like when I have an idea, I can just go sit down, write some code, implement it, 00:03:41.820 --> 00:03:42.820 and then show it to other people. 00:03:42.820 --> 00:03:45.140 It's really, it's one of my favorite parts about it. 00:03:45.140 --> 00:03:50.540 How much does that feedback like tweak or inform the APIs that Twilio uses? 00:03:50.540 --> 00:03:51.480 Oh, a lot. 00:03:51.480 --> 00:03:52.480 Coming back from the evangelist. 00:03:52.480 --> 00:03:52.740 Yeah. 00:03:52.800 --> 00:03:56.760 I mean, one of the best parts about the gig is I get to use all of our APIs before they come out. 00:03:56.760 --> 00:04:02.540 So before anybody gets their hands on them, myself and some of my colleagues are like testing out the APIs, 00:04:02.540 --> 00:04:04.920 giving feedback to the API teams. 00:04:04.920 --> 00:04:10.060 And that helps to improve the results that ultimately get into the hands of developers. 00:04:10.060 --> 00:04:10.860 Oh, that's great. 00:04:10.860 --> 00:04:22.240 Now, if I go out and search for something on Python, there's a very good chance that something that you are responsible for that's not directly part of Twilio will be like the number one Google result for my answer. 00:04:22.240 --> 00:04:23.360 You do full stack Python, right? 00:04:23.480 --> 00:04:23.720 Yeah. 00:04:23.720 --> 00:04:27.900 So I'm the author of full stack Python, which is a open source project. 00:04:27.900 --> 00:04:29.560 I started over four years ago. 00:04:29.940 --> 00:04:33.400 And the whole idea behind full stack Python was I'm a Python developer. 00:04:33.400 --> 00:04:35.600 And I had this before I joined Twilio. 00:04:35.600 --> 00:04:39.840 I had a bunch of junior developers that were joining my team and they kept sending me emails. 00:04:39.840 --> 00:04:41.680 Hey, what's a what's a whiskey server? 00:04:41.680 --> 00:04:42.380 Like, what is that? 00:04:42.380 --> 00:04:48.580 And I kept sending all these emails and I was like, this would probably be relevant to much more than just our team. 00:04:48.580 --> 00:04:54.500 So I started putting together a project with pages that had explanations on every single Python topic. 00:04:54.500 --> 00:04:56.440 And it's just expanded out from there. 00:04:56.440 --> 00:04:57.820 I pretty much work on it every day. 00:04:57.820 --> 00:05:02.020 And it's it's read by over 80,000 developers a month at this point. 00:05:02.020 --> 00:05:02.980 That's fantastic. 00:05:02.980 --> 00:05:04.700 And you have a book that goes with it as well, right? 00:05:04.700 --> 00:05:09.200 Yeah, that's what I was on for in episode 26 back 70 episodes ago. 00:05:09.200 --> 00:05:13.700 It's about it's a step by step guide to deploying Python applications. 00:05:13.700 --> 00:05:16.420 So if you've never done it before, you've built your first web application. 00:05:16.880 --> 00:05:31.660 This is every single step to get a virtual private server and to stand everything up that you need DNS, the whiskey server, reverse proxy, all those things that trip developers up and certainly trip me up several years ago when I was trying to deploy my own applications. 00:05:31.660 --> 00:05:42.900 Yeah, it feels to me like that kind of that kind of information, those kinds of things are the things that you kind of it's a lot of work and a lot of research to get it all put all the pieces combined just right. 00:05:42.900 --> 00:05:46.420 So your web apps work great, but then you write it down, you put it in a script and you forget about it. 00:05:46.420 --> 00:05:50.460 So having like a book as a reference to learn it the first time and then keep it around is really cool. 00:05:50.460 --> 00:05:51.220 Yeah, exactly. 00:05:51.220 --> 00:05:56.920 So and as we talked about on that episode, first, I teach how to do it manually and then we automate it with Ansible. 00:05:56.920 --> 00:06:00.780 So it's a pretty good way to kind of understand the nitty gritty and then automate it. 00:06:00.780 --> 00:06:05.260 And you know what, if you want to forget about it at that point and just use the scripts, you can, but at least you learned it the first time. 00:06:05.260 --> 00:06:06.040 Yeah, absolutely. 00:06:06.040 --> 00:06:07.740 You'll understand that when you come back, right? 00:06:07.740 --> 00:06:11.080 You'll know what you're doing if you need to need to come back and tweak the automation. 00:06:11.080 --> 00:06:11.580 That's cool. 00:06:11.580 --> 00:06:15.440 Now we're going to talk about Awesome Python, the project, the GitHub project. 00:06:15.440 --> 00:06:20.700 But before we get into that, how about we do a quick update on our Python for Entrepreneurs course that you and I are writing together? 00:06:20.700 --> 00:06:21.600 Yeah, let's do it. 00:06:21.600 --> 00:06:22.360 Yeah, let's do it. 00:06:22.360 --> 00:06:24.220 So that course is almost done. 00:06:24.320 --> 00:06:28.200 I have to say, this one is, how shall I put it, longer than I expected. 00:06:28.200 --> 00:06:31.860 A little longer to write than I expected. 00:06:31.860 --> 00:06:37.240 But I haven't even told you, I've finished almost all the chapters I have to record. 00:06:37.240 --> 00:06:38.840 They're off to editors. 00:06:38.840 --> 00:06:43.000 I have basically one and a half chapters left to record and I'll be done. 00:06:43.000 --> 00:06:45.920 And then that just leaves a few more to go and that class will be all wrapped up. 00:06:45.920 --> 00:06:57.740 Yeah, and for me, I'm just finishing up some of the second Git chapter and then we're going to get into deployments and SEO and everything that goes along with actually running the application that you build. 00:06:57.740 --> 00:06:59.480 So I'm really excited. 00:06:59.480 --> 00:07:02.060 I am so excited to get this thing out to people. 00:07:02.060 --> 00:07:07.900 I know people have been watching it in early access mode, which you get from just buying, pre-ordering the course. 00:07:07.900 --> 00:07:11.160 But I'm excited for it to be like really wrapped up and done. 00:07:11.160 --> 00:07:20.440 Yeah, I really hope this turns out to be a great resource for the Python community around sort of this whole lifecycle of idea to web app to deployment to business. 00:07:20.440 --> 00:07:21.220 It'll be fun. 00:07:21.220 --> 00:07:26.160 Okay, so we'll come back and let people know when that's actually finished, but it'll be soon. 00:07:26.160 --> 00:07:28.000 I promise those of you who are out there waiting. 00:07:28.000 --> 00:07:30.300 So let's talk about some stuff that's awesome. 00:07:30.300 --> 00:07:30.940 Sure. 00:07:30.940 --> 00:07:37.400 So the awesome Python repository has the great slogan, life is short, you need Python. 00:07:37.740 --> 00:07:41.120 And it is one of many awesome lists. 00:07:41.120 --> 00:07:48.680 So the awesome list popped up on GitHub where people just started throwing together lists of tools and resources that they were using. 00:07:48.680 --> 00:07:53.080 And so this repository came up in the Python community. 00:07:53.080 --> 00:07:57.420 And so this is a GitHub Vinta slash awesome Python. 00:07:57.660 --> 00:08:00.740 It was created by Vinta Chen about a little over two years ago. 00:08:00.740 --> 00:08:15.580 And this is kind of the main one for the Python ecosystem that goes over all of the different open source projects and categorizes them, whether they're a task queue or web framework has some sort of basic categorization for each of the projects. 00:08:15.580 --> 00:08:22.100 Yeah, I think this is really handy when you don't know what it is you need for something. 00:08:22.100 --> 00:08:24.460 And so I don't know how many projects are listed here. 00:08:24.460 --> 00:08:29.220 I probably could have gone through GitHub source code and like written some script or something to figure it out. 00:08:29.240 --> 00:08:35.340 But it seems to me like it's close to like 500, 400 projects. 00:08:35.340 --> 00:08:36.700 And they're all categorized. 00:08:36.700 --> 00:08:38.420 Like you said, here's admin backends. 00:08:38.420 --> 00:08:40.180 Here's authentication. 00:08:40.180 --> 00:08:41.280 Here's caching. 00:08:41.280 --> 00:08:46.520 And maybe under caching, there's like 10 choices on how you can do caching and plug that into your apps. 00:08:47.300 --> 00:08:58.560 So if you don't know what you need or what even a good choice for caching is in Python, you're just like, hey, I know I need caching, but that's as much as I know, you know, drop into awesome-python.com. 00:08:58.560 --> 00:09:03.240 And then you can go to the caching section and, you know, pick. 00:09:03.240 --> 00:09:14.100 Yeah, so I think for me as a fairly senior developer, what I think these lists are most useful for is if you've already been programming in one language, say you're a Java developer. 00:09:14.280 --> 00:09:17.700 Like I actually came from Java and then started in Python several years ago. 00:09:17.700 --> 00:09:22.160 And I didn't know what the equivalent to a web application server was. 00:09:22.160 --> 00:09:23.260 Well, that's a WSGI server. 00:09:23.260 --> 00:09:28.960 And with the awesome lists, I can see at a glance, like what should I be using for caching in Python? 00:09:28.960 --> 00:09:39.700 So if you were already familiar with all the conceptual ideas, like a task queue, like a web framework, then you can see the implementations in a different programming language. 00:09:39.700 --> 00:09:52.220 So you could go to the awesome Ruby repository and see the equivalents to the Python projects that are out there in case you just happen to want to learn Ruby or you're, you know, on the job and you have to suddenly write some Ruby code. 00:09:52.220 --> 00:09:53.580 Yeah, I think exactly. 00:09:53.580 --> 00:10:02.580 If you know I need caching and you want to say these are the five things I should probably research and you can compare them pretty quickly because, you know, you'll open up the GitHub page. 00:10:02.580 --> 00:10:05.780 You can tell, does this have five stars or 5,000 stars, right? 00:10:05.780 --> 00:10:06.660 How active is it? 00:10:06.660 --> 00:10:08.000 What are the deployments? 00:10:08.000 --> 00:10:08.580 Things like that. 00:10:08.580 --> 00:10:10.420 It's really good for that. 00:10:10.420 --> 00:10:17.100 If you totally don't even know what you need to look for, you know, maybe something like full stack Python makes more sense, right? 00:10:17.100 --> 00:10:18.920 You want to talk about how you see those differently? 00:10:18.920 --> 00:10:33.200 Yeah, so there is a there's a bit of difference between an awesome list and what I'm trying to create with full stack Python, which is the awesome list is really a laundry list of all of the open source code that is out there that might be applicable to your your project. 00:10:33.340 --> 00:10:45.060 But again, going back to task use, for instance, if you're a junior developer or you're in a boot camp or you're just starting to program and you don't know what a task queue is, well, seeing a list of implementations really is not going to help you. 00:10:45.060 --> 00:10:50.640 It's not going to sell re RQ and these different implementations. 00:10:50.640 --> 00:10:52.860 You don't know what they're going to do for you. 00:10:52.860 --> 00:10:59.760 So that's why I have like a task queue page that explains the conceptual idea and then explains the differences between the implementations. 00:10:59.940 --> 00:11:03.100 So I think what's missing from an awesome list is the context. 00:11:03.100 --> 00:11:15.100 But if you're a more senior developer, you've already been working in one ecosystem and you're trying to switch over to another one or you're just trying to see what other implementations are out there compared to the implementations you've been using that. 00:11:15.100 --> 00:11:16.100 I mean, it's great for that. 00:11:16.100 --> 00:11:21.220 Doesn't it just kind of gets past the verbiage and gives you all the implementations that you need? 00:11:21.220 --> 00:11:23.820 Yeah, I find having been a programmer for a long time. 00:11:23.960 --> 00:11:32.680 I find these lists really, really helpful for discovering things that, you know, maybe they're not at the top of Google, but actually turn out to be just the thing that I need. 00:11:32.680 --> 00:11:37.520 So but yeah, it's when you're totally new, maybe maybe it's not the best place to start. 00:11:37.520 --> 00:11:39.720 But still, even if you're new, go check out the project. 00:11:39.720 --> 00:11:41.800 It's you'll find it interesting, I think. 00:11:42.180 --> 00:11:50.220 So you and I chose some things out of this awesome Python list that we thought would be fun to highlight as part of the show. 00:11:50.220 --> 00:11:52.260 Yeah, my criteria for this. 00:11:52.260 --> 00:11:55.960 So we picked 10 libraries at random that are listed in the awesome Python. 00:11:55.960 --> 00:12:02.840 And by the way, Talk Python To Me is not one of the 10 we chose, but it is listed on an awesome Python as it should be. 00:12:02.840 --> 00:12:03.460 Thank you. 00:12:03.460 --> 00:12:04.540 And so is Full Stack Python. 00:12:05.320 --> 00:12:19.320 And so the criteria that we used were projects that were not completely obvious to the community, but that are almost everywhere, or that have like a ton of potential to really impact the Python ecosystem. 00:12:19.320 --> 00:12:26.400 So for example, we didn't choose Django because Django is talked about widely and used widely in the Python ecosystem. 00:12:26.700 --> 00:12:31.460 But we did pick a CMS that is powered by Django under the cover. 00:12:31.460 --> 00:12:35.940 So the CMS runs on top of Django, and we'll get to that in a few minutes. 00:12:35.940 --> 00:12:45.660 So that's sort of the criteria we used to pick 10 projects at random that we wanted to highlight because they're important to the Python ecosystem, or they have potential to become really important in the future. 00:12:45.660 --> 00:12:55.980 I think that's really interesting and really great because it's while we could do a show where we just go and say, let's just go find the 10 most downloaded packages on PyPI. 00:12:55.980 --> 00:12:57.600 That would actually be pretty interesting. 00:12:57.600 --> 00:13:02.880 But I think here we're going to hopefully expose people to things that are like, oh, I didn't even know that existed. 00:13:02.880 --> 00:13:03.720 That's going to be awesome. 00:13:03.720 --> 00:13:04.720 I'm going to go check it out. 00:13:04.720 --> 00:13:06.800 So let's see if we can deliver on that, huh? 00:13:06.800 --> 00:13:07.640 Exactly. 00:13:07.640 --> 00:13:08.380 All right. 00:13:08.380 --> 00:13:09.020 You want to dive in? 00:13:09.020 --> 00:13:09.880 Yeah, let's get started. 00:13:09.880 --> 00:13:19.840 So the first thing that I'm really happy to see that's on our list is something that helps us move from legacy Python to Python, or as some people say, from Python 2 to Python 3. 00:13:19.840 --> 00:13:20.580 Sure. 00:13:20.580 --> 00:13:21.300 Yeah. 00:13:21.300 --> 00:13:24.100 So this is the library 6. 00:13:24.100 --> 00:13:28.100 So 6 is a Python 2 to 3 compatibility library. 00:13:28.100 --> 00:13:39.400 And this is one that you're not necessarily going to build an entire application around, but it is incredibly useful for developers who have built a Python 2 library. 00:13:39.620 --> 00:13:42.620 And now they want to support both Python 2 and 3. 00:13:42.620 --> 00:13:44.740 So you can think about it as a bridge. 00:13:44.740 --> 00:13:51.380 6 is a bridge from Python 2 to Python 3 and allows you to support both ecosystems at once. 00:13:51.380 --> 00:13:57.740 So it's really providing utility functions to smooth over some of the differences between the Python versions. 00:13:57.740 --> 00:14:07.120 And the goal is really to have that Python code that you're writing for your own library be compatible with both Python 2 and Python 3. 00:14:07.120 --> 00:14:07.480 Right. 00:14:07.480 --> 00:14:15.960 So where there's some kind of difference versus, you know, like raw input versus input or bytes versus stir, things like that. 00:14:15.960 --> 00:14:22.600 You can use this library and it will know which version of Python it's running on and it will, you know, switch between them. 00:14:22.600 --> 00:14:22.860 Right. 00:14:22.860 --> 00:14:23.160 Yep. 00:14:23.280 --> 00:14:23.720 Exactly. 00:14:23.720 --> 00:14:32.740 So if you're using Python 2.6 or above Python 2.6, 2.7, and then you want to support Python 3, for example, the syntax compatibility. 00:14:33.100 --> 00:14:35.160 So we've got print functions that have changed. 00:14:35.160 --> 00:14:40.100 We have other tech, the way that Unicode is handled. 00:14:40.100 --> 00:14:46.940 All those things need to be either smoothed over in your own code or you can just use 6 as a dependency. 00:14:46.940 --> 00:14:49.540 And it's only one Python file, which is awesome. 00:14:49.680 --> 00:14:51.420 So you can just copy this into your project. 00:14:51.420 --> 00:15:00.540 And then this helps you to smooth over those differences in that would otherwise come up because you're trying to support both 2 and 3. 00:15:00.540 --> 00:15:00.900 Right. 00:15:00.900 --> 00:15:07.240 And hopefully you can do this without having if Python 3, this code, if Python 2, that code. 00:15:07.240 --> 00:15:13.560 But right, just leveraging this library and presumably somewhere deep inside of it, it's doing those types of things for you. 00:15:13.720 --> 00:15:16.940 So you mentioned some of the areas that you can help with. 00:15:16.940 --> 00:15:18.060 What else does it cover? 00:15:18.060 --> 00:15:19.120 Where am I to use this? 00:15:19.120 --> 00:15:25.320 For example, if you have unit test assertions in your code or you're renaming modules and attributes. 00:15:25.320 --> 00:15:40.080 So there's actually a huge laundry list of areas that you may not be that intuitive if you're a Python developer, that if you're building a library for others to use, sort of it just crops up as you're looking to port from 2 to 3. 00:15:40.080 --> 00:15:42.320 And that's really where this would come in. 00:15:42.320 --> 00:15:42.640 Yeah. 00:15:42.640 --> 00:15:43.180 Okay, cool. 00:15:43.180 --> 00:15:51.600 Yeah, I remember there's like a module, something like copy underscore reg in Python 2 and it's copy reg without the underscore in Python 3 or vice versa. 00:15:51.600 --> 00:15:52.740 You know, things like that, right? 00:15:52.740 --> 00:15:55.160 Like, why are these so just barely different? 00:15:55.160 --> 00:15:55.880 This is crazy. 00:15:55.880 --> 00:15:57.120 Anyway. 00:15:57.120 --> 00:15:57.520 Okay. 00:15:57.520 --> 00:15:58.440 So, yeah. 00:15:58.440 --> 00:16:09.960 So if you've got some Python 2 code that you want to bring forward or maybe you can even use it to help somewhat bring a Python 3 libraries to support Python 2 if you're writing some kind of package, right? 00:16:09.960 --> 00:16:10.240 Yeah. 00:16:10.240 --> 00:16:10.680 Yeah. 00:16:10.680 --> 00:16:11.120 Yeah. 00:16:11.120 --> 00:16:14.500 And the reason why I picked this one to highlight was it's really everywhere. 00:16:14.500 --> 00:16:25.980 Many of the really popular, most commonly used Python libraries rely on 6 library in order to smooth over the differences in Python 2 and 3. 00:16:26.320 --> 00:16:33.000 And so it's sort of the guy behind the scenes who's helping everybody out, but no one really talks about as like the main person. 00:16:33.000 --> 00:16:34.000 It's the guy behind the curtain. 00:16:34.000 --> 00:16:34.440 Yeah. 00:16:34.440 --> 00:16:34.680 Okay. 00:16:34.680 --> 00:16:35.020 Awesome. 00:16:35.020 --> 00:16:35.280 Yeah. 00:16:35.320 --> 00:16:36.180 So check it out, 6. 00:16:36.180 --> 00:16:38.520 And it's named 6 because 2 times 3. 00:16:38.520 --> 00:16:39.320 Yeah. 00:16:39.320 --> 00:16:39.960 There you go. 00:16:39.960 --> 00:16:40.340 Nice. 00:16:40.340 --> 00:16:45.980 Let me take just a moment and tell you about an offer from one of our sponsors, Continuum Analytics. 00:16:45.980 --> 00:16:48.560 They're hosting AnacondaCon 2017. 00:16:48.560 --> 00:16:52.500 It's the first conference for open data science leaders around the world. 00:16:52.920 --> 00:16:55.800 This is the definitive gathering place for the Anaconda crew. 00:16:55.800 --> 00:17:05.060 Whether you're a new or a long-standing member of the data science community focused on business or technology, AnacondaCon will help you conquer your biggest data science challenges. 00:17:05.480 --> 00:17:12.500 Over 20 industry experts will discuss the open data science movement and share their best practices for leveraging Anaconda. 00:17:12.500 --> 00:17:20.760 You'll hear how they're discovering cures for rare genetic diseases, performing city planning, and refining tax policy analysis with Python. 00:17:20.760 --> 00:17:31.780 Team Anaconda wants to help empower your whole team, so they're offering a two-for-one ticket price to AnacondaCon 17 from now through January 31, 2017. 00:17:32.280 --> 00:17:38.740 Register today at talkpython.fm/acon to take advantage of this excellent offer. 00:17:38.740 --> 00:17:41.420 That's talkpython.fm/acon. 00:17:41.420 --> 00:17:44.340 Thank Continuum for supporting Talk Python. 00:17:44.340 --> 00:17:45.680 They help make the show possible. 00:17:45.680 --> 00:17:47.220 Now back to the interview with Matt. 00:17:47.220 --> 00:17:58.440 There are a lot of data scientists and actual straight scientists that listen to this show, and they might be happy to hear about your number two item here. 00:17:58.440 --> 00:17:59.080 Yeah. 00:17:59.080 --> 00:18:02.460 So I picked Boca, or you can also pronounce it Bo-kay. 00:18:02.460 --> 00:18:06.360 In the official FAQ for the project, it says you can pronounce it either way. 00:18:06.360 --> 00:18:11.300 I'm not sure if there's a more right version, but we'll call it Boca for now. 00:18:11.300 --> 00:18:16.360 And so what this allows you to do is write Python code and create data visualizations. 00:18:16.720 --> 00:18:23.640 And so I have tried to create data visualizations in many different JavaScript libraries before. 00:18:23.640 --> 00:18:27.000 The most popular right now, it seems like, is D3JS. 00:18:27.000 --> 00:18:28.600 And I love those libraries. 00:18:28.600 --> 00:18:36.180 But when I'm in Python land, sometimes I just, I can't think about switching over into the JavaScript world. 00:18:36.180 --> 00:18:42.460 And so a Boca allows you to just write the Python code, and then it will build the visualizations for you. 00:18:42.460 --> 00:18:48.580 Now, it's not relying on D3JS, but it draws visualizations that are very similar to that. 00:18:48.580 --> 00:18:52.360 And so you're not just getting like a cut rate data visualization. 00:18:52.360 --> 00:18:59.120 This is actually building something that is like, you can include it in your web application, and it is nice and professional. 00:18:59.120 --> 00:19:01.240 Yeah, this is really, really a cool library. 00:19:01.240 --> 00:19:09.080 And if you're already doing some kind of scientific computation or numerical computation in Python, 00:19:09.080 --> 00:19:16.160 you don't want to like drop out and just, you know, drop a bunch of data into a JavaScript file or to an HTML file 00:19:16.160 --> 00:19:20.260 and then write a bunch of JavaScript D3 to actually turn that back into something visual. 00:19:20.680 --> 00:19:24.640 You can basically do all the visualizations in Python and then just plug it in. 00:19:24.640 --> 00:19:29.740 And what's really cool is it's not just like generating like a picture, say, with Matplotlib. 00:19:29.740 --> 00:19:33.580 Like, so with Matplotlib, you can say, here, I'd like to have this picture, boom, save it to an image, 00:19:33.580 --> 00:19:34.820 then put the image on a page. 00:19:34.820 --> 00:19:41.740 But these things, these bokeh graphs and visualizations that go up there, they're totally interactive, right? 00:19:41.740 --> 00:19:42.640 Yeah, exactly. 00:19:42.640 --> 00:19:46.040 So it's not just, as you said, it's not just an image that is generated. 00:19:46.040 --> 00:19:50.360 It is the actual visualization that can be, that is fully interactive as well. 00:19:50.360 --> 00:19:57.580 And so you can control how much interactivity and what data and what axes you want to, you want the user to be able to explore. 00:19:57.580 --> 00:19:59.880 But you can do that all in, in Python itself. 00:19:59.880 --> 00:20:04.420 And I actually, I found out about this project a couple of years ago at PyCon 2015. 00:20:04.420 --> 00:20:12.020 Sarah Bird gave an awesome talk where, and you can actually go, go find it on YouTube for, if you search Sarah Bird PyCon 2015. 00:20:12.020 --> 00:20:15.520 And she drew an entire map with just bokeh. 00:20:15.520 --> 00:20:20.560 And I was like, whoa, you just, you just wrote, she live coded some Python code. 00:20:20.560 --> 00:20:22.580 And I was like, whoa, you've got a map on there with all your data. 00:20:22.900 --> 00:20:25.800 That would have taken me a week in D3JS. 00:20:25.800 --> 00:20:27.280 I was just so impressed with it. 00:20:27.280 --> 00:20:28.540 Yeah, it's really, really cool. 00:20:28.540 --> 00:20:29.640 Okay. 00:20:29.640 --> 00:20:38.060 So, you know, another thing that's really popular in Python these days, it seems, is static site generators, right? 00:20:38.060 --> 00:20:38.640 Yep. 00:20:38.640 --> 00:20:46.820 That well, and, and, and Pelican, which is a static site generator, which is not the project we pick, but Pelican, I use every single day to create full stack Python. 00:20:46.820 --> 00:20:53.540 So I picked a separate one, and this one is either pronounced make docs or mk docs. 00:20:53.540 --> 00:21:05.940 I actually just gave a talk on static site generators at San Francisco Python, and I tweeted at Tom Christie, who's the creator of not only Django rest framework, but this project as well, make docs. 00:21:05.940 --> 00:21:09.060 And I said, hey, how do I, I'm going to check myself before I wreck myself. 00:21:09.060 --> 00:21:10.760 How do I pronounce this project? 00:21:10.760 --> 00:21:15.220 And he said, well, you know, I say mk docs with a Scottish accent. 00:21:15.600 --> 00:21:17.220 And I was like, mk docs. 00:21:17.220 --> 00:21:18.640 Okay. 00:21:18.640 --> 00:21:22.780 I don't, you know, I'm not, I don't really have a Scottish accent. 00:21:22.780 --> 00:21:24.200 So, okay, sure. 00:21:24.200 --> 00:21:25.940 And then he said, but, you know, I don't really know. 00:21:25.940 --> 00:21:27.840 Let me, let me talk to one of their core committers. 00:21:27.840 --> 00:21:32.740 And he said, mk docs, that's how he pronounced it, but they don't really have a particular opinion about it. 00:21:32.740 --> 00:21:35.380 So, you know, whatever's easiest for you. 00:21:35.380 --> 00:21:40.440 If you've got a great Scottish accent, I say go for that route, but, but I certainly do not. 00:21:40.440 --> 00:21:46.620 So what make docs is, is a static site generator for really for project documentation. 00:21:46.620 --> 00:21:52.000 Let me ask you a quick question or clarification just for everyone listening, because many people would know, but not everyone. 00:21:52.000 --> 00:21:53.220 What's a static site? 00:21:53.220 --> 00:21:53.680 Yeah. 00:21:53.760 --> 00:21:57.880 So a static site is kind of taking you back to the origins of the web. 00:21:57.880 --> 00:22:05.700 It's just HTML flat files, HTML, and it has CSS and usually JavaScript, but there's no database backend. 00:22:05.700 --> 00:22:08.280 There's no dynamic content on the backend. 00:22:08.280 --> 00:22:11.680 So it's really just files that can be served up by a web server. 00:22:11.680 --> 00:22:13.820 And the reason why it's called a generator. 00:22:13.820 --> 00:22:15.320 So that, that would be the static site. 00:22:15.320 --> 00:22:23.300 The generator part of it is you write your content either in markdown or restructured text or some sort of markup format. 00:22:23.300 --> 00:22:25.280 And then you have templates. 00:22:25.280 --> 00:22:30.660 So for Pelican, for example, Pelican has Jinja templates that you can use. 00:22:30.660 --> 00:22:37.000 So Jinja is a template engine and make docs has its own, actually make docs makes it even easier. 00:22:37.000 --> 00:22:38.420 You don't even have to write the templates. 00:22:38.420 --> 00:22:40.540 If you don't want to, you just write the content. 00:22:40.540 --> 00:22:48.260 And what that does is it combines the content that you've written with some sort of template engine and then produces HTML files or some sort of output. 00:22:48.260 --> 00:22:53.340 It could be XML, whatever you want, but most commonly you're producing a static site, which would be an HTML. 00:22:53.340 --> 00:22:53.880 Okay. 00:22:53.880 --> 00:22:54.840 Yeah, that's really cool. 00:22:54.840 --> 00:22:56.340 And there's a lot of benefits to that. 00:22:56.340 --> 00:23:00.720 It's super easy to scale a site like that, right? 00:23:00.720 --> 00:23:04.440 You don't have to worry about the databases and concurrence execution. 00:23:04.440 --> 00:23:05.800 You're just serving static files. 00:23:05.800 --> 00:23:10.880 And it's also easy to put that on to like a CDN sort of thing, like Fastly or something, right? 00:23:10.880 --> 00:23:11.480 Yeah. 00:23:11.480 --> 00:23:18.960 So the way that I deploy a full stack Python is it's just, you know, it's just a bunch of HTML files that get generated with some CSS and JavaScript. 00:23:18.960 --> 00:23:22.000 And then I just have a content delivery network. 00:23:22.000 --> 00:23:24.380 So I have the files hosted. 00:23:24.380 --> 00:23:26.120 Sometimes I use GitHub pages. 00:23:26.120 --> 00:23:28.740 I've also switched it over to Amazon S3. 00:23:28.740 --> 00:23:32.740 In front of that is a CDN, and I use Cloudflare. 00:23:32.740 --> 00:23:35.700 And what that does is it just serves up all those files. 00:23:35.700 --> 00:23:37.700 There's no database calls or anything like that. 00:23:37.700 --> 00:23:43.360 It's just really fast, immediately serving up those files to whatever web browser is requesting them. 00:23:43.360 --> 00:23:43.900 Nice. 00:23:43.900 --> 00:23:44.680 And it serves them up. 00:23:44.680 --> 00:23:49.280 It moves them around the globe and serves them up from somewhere by place, which is pretty awesome. 00:23:49.280 --> 00:23:55.320 So people on the other side of the earth don't suffer because you decided to put your server in New York or whatever. 00:23:55.320 --> 00:23:56.680 Globally distributed, exactly. 00:23:56.680 --> 00:23:57.200 Yeah, yeah. 00:23:57.200 --> 00:23:57.640 That's awesome. 00:23:57.640 --> 00:23:58.340 Okay. 00:23:58.340 --> 00:24:00.080 So what's cool about MakeDocs? 00:24:00.080 --> 00:24:02.460 Why is it a great one? 00:24:02.460 --> 00:24:03.120 How does it work? 00:24:03.440 --> 00:24:08.800 I think the thing about static sites is they've traditionally been made around blogs. 00:24:08.800 --> 00:24:16.180 But project documentation is one of the best examples that I think, if you want to use the word, use cases that I've seen. 00:24:16.420 --> 00:24:24.720 So the idea behind MakeDocs is it's already being used to power a really popular project, a Python project, which is Django REST framework. 00:24:24.720 --> 00:24:30.140 And that allows MakeDocs to have a real project using it. 00:24:30.140 --> 00:24:32.920 And then they open sourced it so that anybody can use it. 00:24:32.920 --> 00:24:36.380 And the idea is generate beautiful project documentation. 00:24:36.620 --> 00:24:40.540 Now, for many developers, documentation is sort of not the first thing on their mind. 00:24:40.540 --> 00:24:45.420 But in the Python community, I think we have really great documentation for most of our projects. 00:24:45.420 --> 00:24:47.600 It's kind of something that is a badge of pride. 00:24:47.600 --> 00:24:55.440 And so that's where I think using MakeDocs and just writing your content, you don't have to worry about the styling if you don't want to. 00:24:55.780 --> 00:24:59.280 It's just going to create a beautiful set of project documentation for you. 00:24:59.280 --> 00:25:00.160 Yeah, that's excellent. 00:25:00.160 --> 00:25:04.000 And I think, you know, you could even check in the docs into, like, your GitHub repository. 00:25:04.000 --> 00:25:09.520 And if somebody clones your repo, they can just go, like, right there and just have offline docs as static files. 00:25:09.520 --> 00:25:10.180 That's really cool. 00:25:10.180 --> 00:25:11.280 Very nice. 00:25:11.280 --> 00:25:12.220 Okay, MakeDocs. 00:25:12.220 --> 00:25:20.360 You know, speaking of Markdown, I think having Markdown wherever you accept user input is really nice in your web apps. 00:25:20.360 --> 00:25:22.960 You know, Stack Overflow definitely popularized this. 00:25:23.180 --> 00:25:28.420 Markdown comes from John Grubner a long ago, I don't know, like 2008 or something like this. 00:25:28.420 --> 00:25:29.520 It's not a brand new idea. 00:25:29.520 --> 00:25:39.540 But certainly using Markdown to accept input from users is much safer than accepting pure, you know, rich formatted HTML, right? 00:25:39.540 --> 00:25:39.900 Yeah. 00:25:39.900 --> 00:25:43.740 So the thing about Markdown is it's a certain format. 00:25:43.740 --> 00:25:49.840 And there's, well, for better or worse, without getting too into the weeds, there are different variations on that format. 00:25:49.840 --> 00:25:51.780 But there is sort of a standard Markdown format. 00:25:52.060 --> 00:25:54.900 And there's a Python project that parses that out. 00:25:54.900 --> 00:25:57.560 So then you can work with it in your Python code. 00:25:57.560 --> 00:26:01.100 And so the Python Markdown project is kind of everywhere. 00:26:01.100 --> 00:26:07.360 Whenever you're talking about a content management system or a static site generator like MakeDocs or Pelican, which I use. 00:26:07.520 --> 00:26:20.840 Really, when you do pip install Markdown, what happens is that a Markdown parser is installed and allows the whatever libraries you're depending on to then parse out that Markdown and work with it in their own code. 00:26:20.840 --> 00:26:21.840 Yeah, that's really cool. 00:26:21.840 --> 00:26:31.320 So, for example, on like Python Bytes, the new podcast that I started, so Python Bytes.fm, on there, there's a back-end CMS type thing that I created for it. 00:26:31.320 --> 00:26:32.820 And there's a place we put the show notes. 00:26:33.160 --> 00:26:36.460 And on Talk Python, that was just an HTML fragment. 00:26:36.460 --> 00:26:38.840 But every now and then I would mess up that HTML fragment. 00:26:39.320 --> 00:26:41.640 And it would screw up the site. 00:26:41.640 --> 00:26:46.600 Or, you know, I just have to like format HTML in the browser and write it by hand. 00:26:46.600 --> 00:26:47.600 And it's not so fun. 00:26:47.600 --> 00:26:49.960 So when I did Python Bytes, I'm like, that's it. 00:26:49.960 --> 00:26:54.760 This part is going to be input as Markdown, output as, you know, HTML. 00:26:54.760 --> 00:26:59.480 And so I use something similar to Python Markdown for that, which is really cool. 00:26:59.480 --> 00:27:02.620 I actually use this thing called Python-Markdown2. 00:27:02.940 --> 00:27:04.620 I don't think they're related to these two things. 00:27:04.620 --> 00:27:07.160 It's nice because it has extensions. 00:27:07.160 --> 00:27:09.900 You can add on like variations. 00:27:09.900 --> 00:27:13.760 Like I want to add like GitHub table support type things and stuff like that. 00:27:13.760 --> 00:27:14.020 Yeah. 00:27:14.020 --> 00:27:16.860 Again, this is just another one of those libraries that's everywhere. 00:27:16.860 --> 00:27:21.760 And whether they're using Python Markdown, Python Markdown2, or there's many other parses that are out there, 00:27:21.760 --> 00:27:26.060 they're kind of the guy, the gal behind the scenes that is doing a lot of the heavy lifting 00:27:26.060 --> 00:27:29.580 and allows other projects to take advantage of that work that's done. 00:27:29.580 --> 00:27:30.100 Nice. 00:27:30.760 --> 00:27:37.200 So while we're on the topic of, hey, I want to put some stuff into some kind of back end on my site and have it show up, 00:27:37.200 --> 00:27:43.320 one thing you do is write a site from scratch and fill in a few pieces like show notes and episode names, 00:27:43.320 --> 00:27:45.640 or you could grab a whole CMS, right? 00:27:45.640 --> 00:27:46.120 Yeah. 00:27:46.120 --> 00:27:51.420 So Django can often be used as a CMS, which is a content management system. 00:27:51.420 --> 00:27:55.460 I would say like WordPress is probably the most popular of these, right? 00:27:55.460 --> 00:28:00.260 If you look at like overall deployments or maybe Squarespace, but plug it into Django is really sweet. 00:28:00.260 --> 00:28:02.100 So you found a really nice one. 00:28:02.100 --> 00:28:08.420 What happens is if you start building a site on Django, and particularly if people that are not developers are using it, 00:28:08.420 --> 00:28:11.060 you often find that you run into limitations. 00:28:11.060 --> 00:28:15.480 And that's not, I wouldn't say that this is necessarily something that Django has to fix. 00:28:15.480 --> 00:28:17.760 This is where a content management system comes in. 00:28:17.760 --> 00:28:19.820 So let me give you a specific example. 00:28:20.300 --> 00:28:29.640 If you have people that are not developers that are punching their content into this content management system, like Django and the Django admin panel, for example, 00:28:29.640 --> 00:28:34.820 and then you want to roll back, you say, oh, shoot, I deleted, I deleted a page. 00:28:34.820 --> 00:28:36.460 You know, let's roll back. 00:28:36.460 --> 00:28:40.180 Well, Django doesn't have that type of capability. 00:28:40.180 --> 00:28:44.540 And that's where content management systems are on top of that. 00:28:44.680 --> 00:28:47.380 So the one that we picked here is Wagtail. 00:28:47.380 --> 00:28:54.400 And Wagtail is actually a newer content management system than some of the other ones like Mezzanine or Django CMS. 00:28:54.400 --> 00:28:58.120 But Wagtail is, I've been really impressed with Wagtail. 00:28:58.120 --> 00:29:04.560 I've used it a bit, both as a non-developer user to punch content in and a little bit on the back end as well. 00:29:04.560 --> 00:29:06.000 And it's been really powerful so far. 00:29:06.000 --> 00:29:07.160 Yeah, that's really great. 00:29:07.300 --> 00:29:09.220 And they've got a great example. 00:29:09.220 --> 00:29:12.560 They have like a demo video for it as well for Wagtail. 00:29:12.560 --> 00:29:14.840 And it was used at the Royal College of Art. 00:29:14.840 --> 00:29:16.560 It's in the UK somewhere. 00:29:16.560 --> 00:29:25.680 And it basically powers that website with thousands of web pages and many, many users and all sorts of really cool workflows. 00:29:25.680 --> 00:29:27.880 It's actually quite visual and pretty. 00:29:27.880 --> 00:29:36.500 One of the things that comes to mind when I think of CMSs is they seem synonymous with slow and clunky to me. 00:29:36.800 --> 00:29:42.920 There's a tradeoff with CMSs, which is that they're building all this extra functionality on top of an existing web framework. 00:29:42.920 --> 00:29:45.440 And they need to be used by people that are not developers. 00:29:45.440 --> 00:29:53.160 So you don't want to get into a situation where the CMS is preventing you from doing things with your content that you want. 00:29:53.160 --> 00:29:54.420 So there's a tradeoff. 00:29:54.420 --> 00:29:56.120 Sometimes CMSs are too heavy-handed. 00:29:56.120 --> 00:29:59.300 Sometimes they're just really confusing to use. 00:29:59.300 --> 00:30:05.380 But I found that Wagtail, which we're actually using at Twilio, is actually one of our favorite CMSs. 00:30:05.380 --> 00:30:08.140 And we did a large evaluation with a lot of different programming languages. 00:30:08.140 --> 00:30:10.700 And this is the one that came on top for us. 00:30:10.700 --> 00:30:14.920 It's not necessarily the best for everybody, but it's the one that works really well for us. 00:30:14.920 --> 00:30:22.360 I can say the Royal College of Art website is quite zippy, even though I'm like nine hours time zone away from it. 00:30:22.360 --> 00:30:24.920 So mostly any sort of slowness would be ping time. 00:30:25.120 --> 00:30:29.540 So I feel like this is a CMS that doesn't have that feeling, right? 00:30:29.540 --> 00:30:30.400 It's really nice. 00:30:30.400 --> 00:30:32.040 And it's awesome because you're using it at Twilio, too. 00:30:32.040 --> 00:30:36.440 Well, the thing about Wagtail is that they've done a great job with making it really polished. 00:30:36.440 --> 00:30:39.560 And I think that's one of the reasons why we were so impressed with it. 00:30:39.560 --> 00:30:42.860 And so this is what's powering the Twilio docs. 00:30:43.120 --> 00:30:52.460 We actually look at our documentation, the documentation for the Twilio APIs as a platform itself, because many different teams around Twilio are using the docs. 00:30:52.460 --> 00:30:53.260 They're writing docs. 00:30:53.260 --> 00:30:55.980 They're updating the docs when things need to be fixed. 00:30:56.180 --> 00:31:01.260 And so we needed some sort of powerful platform that allowed many different teams to interact with it. 00:31:01.260 --> 00:31:05.900 So after our evaluation, we've used Wagtail as our CMS for the Twilio docs. 00:31:05.900 --> 00:31:06.840 Yeah, it's really cool. 00:31:06.840 --> 00:31:10.120 I'm looking forward to finding a place to use it because it looks like it's fun to use. 00:31:10.120 --> 00:31:14.300 The back end looks real friendly and modern, not like some crummy sort of app. 00:31:14.300 --> 00:31:14.880 It's nice. 00:31:14.880 --> 00:31:16.760 It's a really nice and polished project, really. 00:31:16.760 --> 00:31:19.760 I think a little bit newer and up and coming as a CMS. 00:31:19.760 --> 00:31:20.360 Awesome. 00:31:20.360 --> 00:31:22.320 And it's cool that it was on the awesome list. 00:31:22.660 --> 00:31:26.120 Okay, so another thing that I think is really interesting is design patterns. 00:31:26.120 --> 00:31:27.520 I've always loved design patterns. 00:31:27.520 --> 00:31:35.920 You know, I've read, I remember reading the Gang of Four book about C++ and small talk design patterns like way long ago. 00:31:35.920 --> 00:31:40.200 And then reading it again so I could actually understand it like a few years later. 00:31:40.200 --> 00:31:49.340 But one of the things that I think is interesting is if you take those patterns and you apply them to Python, sometimes they look very different and sometimes they look very similar. 00:31:49.340 --> 00:31:51.840 Like, for example, the decorator pattern. 00:31:52.520 --> 00:31:57.980 You know, that has one form of C++, but it's almost a language feature in Python. 00:31:57.980 --> 00:31:58.380 Yeah. 00:31:58.380 --> 00:32:03.980 That's where the, on the awesome list is the Python patterns repository. 00:32:03.980 --> 00:32:05.560 So there's a link to Python patterns. 00:32:05.560 --> 00:32:14.520 And this is the implementations of various patterns, whether it's like behavioral patterns or structural patterns, different conceptual ideas. 00:32:14.520 --> 00:32:15.980 And they're implemented in Python code. 00:32:15.980 --> 00:32:27.480 And they're implemented in Python code, which allows someone, for example, when I was going from Java and I had constantly use the singleton pattern or the factory pattern to then see what that looks like in Python. 00:32:27.560 --> 00:32:31.060 I think it's really great for people who are coming from another language. 00:32:31.060 --> 00:32:33.660 They already have these ideas in their mind, right? 00:32:33.660 --> 00:32:39.220 They can drop in really quick and you just pull up like, you know, 20 lines of code and you're like, oh, this is how you do it in Python. 00:32:39.220 --> 00:32:40.740 I never would have thought to do it this way. 00:32:40.780 --> 00:32:43.580 This is so much better than what I was trying to do a minute ago. 00:32:43.580 --> 00:32:46.040 And they have some interesting ones in here. 00:32:46.040 --> 00:32:50.880 They have the standard gang of four ones like state, strategy, iterator, visitor, and so on. 00:32:50.880 --> 00:32:57.180 But then they also have some things like the Borg design pattern and the Blackboard design pattern. 00:32:57.180 --> 00:32:59.740 So I actually learned a few things. 00:32:59.740 --> 00:33:04.140 And I don't really know yet where I'd use the Borg, but I'm pretty sure I like the name of it. 00:33:04.140 --> 00:33:06.720 This repository is great for learning. 00:33:06.720 --> 00:33:19.340 I would caution anyone that is coming from another programming language to suddenly drop different patterns into their code when those patterns may not be idiomatic to the way that you would write Python code. 00:33:19.340 --> 00:33:30.320 Because Python code has its own way of a different way that you would write Python code, for example, making everything explicit rather than implicit like you would in the Ruby ecosystem. 00:33:30.320 --> 00:33:35.200 So I think these are awesome for just learning about how different patterns could be implemented. 00:33:35.200 --> 00:33:44.040 But I would caution people to make sure that this is actually how you would write Python code as opposed to just dropping them into your code without thinking about them. 00:33:44.040 --> 00:33:50.180 Yeah, I kind of have like an Einstein type of philosophy about design patterns. 00:33:50.180 --> 00:33:51.700 Like design patterns are awesome. 00:33:51.700 --> 00:33:53.840 And you should use them in your code. 00:33:53.840 --> 00:33:56.520 But just enough, right? 00:33:56.520 --> 00:33:58.980 Things should be as simple as they can, but not simpler, right? 00:33:58.980 --> 00:34:01.060 Like you should have patterns that solve problems. 00:34:01.060 --> 00:34:05.320 But I feel like people, when they learn design patterns at first, they're like, oh, I'm going to put patterns everywhere. 00:34:05.320 --> 00:34:07.800 I can't wait to like turn everything into a state pattern. 00:34:07.800 --> 00:34:09.540 And then the visitors go in here like, oh, no. 00:34:09.540 --> 00:34:11.840 Oh, no, that's going to be unmaintainable, right? 00:34:11.900 --> 00:34:15.000 And so patterns, I don't know, to me, they're like salt, right? 00:34:15.000 --> 00:34:15.940 A little bit here and there. 00:34:15.940 --> 00:34:16.760 Yep. 00:34:16.760 --> 00:34:25.100 And if you find yourself with a specific problem in your code, knowing what those patterns are and how they can be implemented in your programming language can be really powerful. 00:34:25.100 --> 00:34:25.860 Yeah, absolutely. 00:34:25.860 --> 00:34:34.060 You know, another thing that I'd like to lean on to some kind of framework for is authentication, especially things like OAuth. 00:34:34.060 --> 00:34:37.580 Those are super, super complicated to figure out yourself. 00:34:37.580 --> 00:34:40.440 But luckily on our list here, we have some OAuth stuff, right? 00:34:40.720 --> 00:34:40.860 Yeah. 00:34:40.860 --> 00:34:43.420 So the project we picked here is Authomatic. 00:34:43.420 --> 00:34:48.740 And the tagline here is simple but powerful framework authentication and authorization client. 00:34:48.740 --> 00:34:52.720 I think there's a spectrum with authentication libraries. 00:34:52.720 --> 00:34:56.180 On one hand, you've got sort of these maybe heavy handed. 00:34:56.180 --> 00:34:59.860 They tell you exactly how to implement authentication models. 00:35:00.020 --> 00:35:01.100 So for example, OAuth. 00:35:01.100 --> 00:35:05.760 Let's say you want to have a Twitter-based login or a GitHub-based login. 00:35:05.760 --> 00:35:16.180 Some of the authentication authorization frameworks will tell you, hey, in these three steps, add this to your code, and then you'll have OAuth login. 00:35:16.580 --> 00:35:23.060 But on the other hand, these libraries have to work with various frameworks. 00:35:23.060 --> 00:35:29.720 So the way that you would implement something in Django versus Flask versus Pyramid versus Turbogears can be different. 00:35:29.720 --> 00:35:35.080 And that's where I think taking a look at all the different libraries can be helpful. 00:35:35.280 --> 00:35:41.800 So Authomatic seemed like a really great one because it had examples with different frameworks, which I really liked. 00:35:41.800 --> 00:35:42.280 Yeah. 00:35:42.280 --> 00:35:45.600 You can definitely go in there and it's like these are the few things you drop in for Django. 00:35:45.600 --> 00:35:47.360 Here's the few things you do for Flask. 00:35:47.360 --> 00:35:48.320 Here's what you do for Pyramid. 00:35:48.320 --> 00:35:49.640 Even one for Google App Engine. 00:35:49.980 --> 00:35:55.020 And I really found that some of the other ones that seemed comprehensive had almost no examples. 00:35:55.020 --> 00:35:57.700 And you're like, but there's all these moving parts. 00:35:57.700 --> 00:36:01.040 How do I put this together in this particular web framework? 00:36:01.040 --> 00:36:02.600 Like, why is there no example here? 00:36:02.600 --> 00:36:04.580 Yeah, I looked at a number of them. 00:36:04.580 --> 00:36:08.620 And maybe we should put a little word of caution in that this hasn't been updated for a little while. 00:36:08.620 --> 00:36:11.720 But that's kind of true with some of the other options out there as well. 00:36:11.720 --> 00:36:16.080 So they kind of seem more steady state or they're in some sort of flux or something. 00:36:16.080 --> 00:36:17.920 So look through the whole list. 00:36:18.020 --> 00:36:19.680 Here's just one example to sort of point out. 00:36:19.680 --> 00:36:23.540 Like, there's a bunch of great things about OAuth and social auth and things like that. 00:36:23.540 --> 00:36:23.820 Yep. 00:36:23.820 --> 00:36:29.220 And this makes it much easier for you to implement them rather than having to rewrite everything in your own code. 00:36:29.220 --> 00:36:30.020 Yeah, for sure. 00:36:30.020 --> 00:36:44.080 This portion of Talk Python is brought to you by Hired. 00:36:44.080 --> 00:36:47.100 Hired is the platform for top Python developer jobs. 00:36:47.420 --> 00:36:51.900 Create your profile and instantly get access to 3,500 companies who will work to compete with you. 00:36:51.900 --> 00:36:54.780 Take it from one of Hired's users who recently got a job and said, 00:36:54.780 --> 00:37:00.060 I had my first offer on Thursday after going live on Monday and I ended up getting eight offers in total. 00:37:00.060 --> 00:37:03.520 I've worked with recruiters in the past, but they've always been pretty hit and miss. 00:37:03.520 --> 00:37:06.360 I tried LinkedIn, but I found Hired to be the best. 00:37:06.360 --> 00:37:08.460 I really like knowing the salary up front. 00:37:08.460 --> 00:37:10.820 Privacy was also a huge seller for me. 00:37:10.820 --> 00:37:12.500 Sounds awesome, doesn't it? 00:37:12.500 --> 00:37:14.520 Well, wait until you hear about the sign-in bonus. 00:37:14.740 --> 00:37:17.940 Everyone who accepts a job from Hired gets $1,000 signing bonus. 00:37:17.940 --> 00:37:20.600 And as Talk Python listeners, it gets way sweeter. 00:37:20.600 --> 00:37:25.840 Use the link Hired.com slash Talk Python To Me and Hired will double the signing bonus to $2,000. 00:37:25.840 --> 00:37:27.620 Opportunity's knocking. 00:37:27.620 --> 00:37:31.400 Visit Hired.com slash Talk Python To Me and answer the door. 00:37:38.780 --> 00:37:40.700 You talked about static sites earlier. 00:37:40.700 --> 00:37:44.860 We mentioned the deployment and the performance story and all that, and that's great. 00:37:44.860 --> 00:37:49.080 But sometimes you just need a data-driven web app, right? 00:37:49.080 --> 00:37:56.040 Like, for example, it's super hard to go to, like, a static site and add voting or comments or things like this, right? 00:37:56.040 --> 00:38:01.540 So maybe the thing that you're building, you really do need to have some kind of data-driven thing here. 00:38:02.340 --> 00:38:05.240 But if it's not fast enough, what are you going to do? 00:38:05.240 --> 00:38:06.800 Well, you've got to have caching. 00:38:06.800 --> 00:38:10.620 So, you know, caching is one of these really hard problems in computer science. 00:38:10.620 --> 00:38:15.800 So taking advantage of a library that allows you to implement caching can be really helpful. 00:38:15.800 --> 00:38:18.560 And I know this one you picked, Beaker. 00:38:18.560 --> 00:38:20.400 Why don't you tell us a little bit about Beaker? 00:38:20.620 --> 00:38:21.100 Yeah, yeah. 00:38:21.100 --> 00:38:22.360 Beaker looks really awesome. 00:38:22.360 --> 00:38:31.820 So Beaker is a way in which you can cache binary representations, pickled versions of Python object graphs. 00:38:31.820 --> 00:38:35.500 So you just take the thing you want to save and you just stash it in Beaker. 00:38:35.500 --> 00:38:38.520 And it can go into all different places, right? 00:38:38.520 --> 00:38:41.020 It can go into databases. 00:38:41.020 --> 00:38:42.220 It can go into memcached. 00:38:42.220 --> 00:38:46.380 It can go into just be stuck in memory, you know, until your process reboots. 00:38:46.380 --> 00:38:47.360 You can go straight to the file. 00:38:47.480 --> 00:38:49.940 And it also has a SQLAlchemy plug-in. 00:38:49.940 --> 00:38:54.260 So you point SQLAlchemy at the database that you care about, right? 00:38:54.260 --> 00:38:56.460 SQLAlchemy supports all sorts of different databases. 00:38:56.460 --> 00:38:58.760 And then it just talks to SQLAlchemy. 00:38:58.760 --> 00:39:06.240 So pretty much any type of database you want to use as a back-end for your cache, if you don't want to put it in memory, you can do it here. 00:39:06.240 --> 00:39:08.460 So there's all sorts of cool stuff. 00:39:08.460 --> 00:39:13.140 Like you can take it and plug it in as middleware in WSGI servers. 00:39:13.580 --> 00:39:18.780 So it automatically has little plug-ins for pylons, pyramid, turbo gears, things like this. 00:39:18.780 --> 00:39:20.000 Yeah. 00:39:20.000 --> 00:39:26.640 I think this could be really helpful for people who need that one or two slow pages to go much faster. 00:39:26.640 --> 00:39:27.100 Yeah. 00:39:27.100 --> 00:39:33.940 And if you can't build your site as a static site, certainly you're probably going to investigate caching at some point in order to improve the performance. 00:39:33.940 --> 00:39:37.200 So Beaker seems like a really capable one to use. 00:39:37.200 --> 00:39:37.600 Yeah. 00:39:37.600 --> 00:39:37.800 Yeah. 00:39:37.800 --> 00:39:38.360 It definitely does. 00:39:38.500 --> 00:39:42.320 So some of the features they list are like it's fast, obviously. 00:39:42.320 --> 00:39:44.180 That's a requirement for a cache, right? 00:39:44.180 --> 00:39:48.260 But it has multiple reader, reader, writer, block performance. 00:39:48.260 --> 00:39:53.120 So it avoids duplicate creation but allows for high parallelism for reading. 00:39:53.120 --> 00:40:00.060 All the back-ends, like I said, you can extend it and write your own back-end if you want to plug into TinyDB or, you know, whatever. 00:40:00.060 --> 00:40:02.140 All that kind of stuff is really cool. 00:40:02.580 --> 00:40:02.700 Yeah. 00:40:02.700 --> 00:40:04.640 Sounds like a good one to check out. 00:40:04.640 --> 00:40:11.680 So another one that you picked, which I think is really smart because people always say, hey, don't roll your own crypto. 00:40:11.680 --> 00:40:18.760 And you don't want to write your own password storage hashing library unless you're just trying to learn how it's done. 00:40:18.760 --> 00:40:20.800 But you don't necessarily want to write something for production. 00:40:20.800 --> 00:40:23.680 But you picked Passlib, which you've used in the past. 00:40:23.680 --> 00:40:24.800 Why don't you tell us about Passlib? 00:40:25.040 --> 00:40:26.940 Yeah, I use Passlib all over the place. 00:40:26.940 --> 00:40:29.700 I use it on the training website, for example, for accounts there. 00:40:29.700 --> 00:40:34.780 And I don't want people to end up on, you know, some sort of news story. 00:40:34.780 --> 00:40:39.860 Oh, a development server with production data was compromised. 00:40:39.860 --> 00:40:42.880 And here's, you know, a quarter million accounts. 00:40:42.880 --> 00:40:48.360 And too bad they used poor, like an old outdated hashing algorithm or something like that. 00:40:48.360 --> 00:40:52.980 And it turns out that everybody's going to have to reset all their passwords on the internet everywhere. 00:40:52.980 --> 00:40:58.060 So Passlib, I hope, will help people avoid that fate. 00:40:58.060 --> 00:41:10.760 The idea with Passlib is it takes all the best practices around password storage and verification and validation and puts them into two functions, encrypt and verify. 00:41:11.720 --> 00:41:18.660 So if you can't remember to call encrypt and verify, you know, you probably have no business writing authentication code, right? 00:41:18.660 --> 00:41:25.340 But the idea is they provide a whole bunch of different caching algorithms or, sorry, hashing algorithms. 00:41:25.340 --> 00:41:40.420 And they only support ones that have no known vulnerabilities, are public, have public reference implementations, can be made to be computationally expensive, you know, have a lot of scrutiny and things like that. 00:41:40.420 --> 00:41:45.140 So Argon2, Bcrypt, SHA-512crypt, things like that. 00:41:45.140 --> 00:41:50.820 So you're already starting from, thank goodness they didn't use MD5 for the hashing, right? 00:41:50.820 --> 00:41:53.480 Which is one of the problems. 00:41:53.480 --> 00:42:04.140 The other problem is with the advent of graphics, the GPU processing, people can use the GPUs to do advent of computational GPU processing, not for graphics. 00:42:04.140 --> 00:42:11.700 They can use the power of those graphics cards to just try so many variations on these hashes because the graphics cards can do them really quickly. 00:42:11.700 --> 00:42:17.760 And so you want to make the stored passwords computationally difficult to guess at. 00:42:17.760 --> 00:42:24.480 So instead of just hashing with a strong algorithm, Passlib will take it and it'll hash it like 200,000 times. 00:42:24.580 --> 00:42:30.580 So it'll take the input, stuff it back around, hash that thing, and then just, you know, fold it over 200,000 times. 00:42:30.580 --> 00:42:34.040 And it also adds random salt to each thing it stores. 00:42:34.040 --> 00:42:36.340 And, of course, folds that all through. 00:42:36.340 --> 00:42:40.000 So it's just super hard to guess what the possibility is. 00:42:40.000 --> 00:42:42.000 But it's easy for you. 00:42:42.000 --> 00:42:43.780 You get back some kind of password hash. 00:42:43.860 --> 00:42:46.900 You call verify with the plain text password and either it matches or it doesn't. 00:42:46.900 --> 00:42:47.140 Yeah. 00:42:47.140 --> 00:42:54.360 Well, it seems like it provides a really good tradeoff between, you know, developers want to spend a least amount of time working on security. 00:42:54.360 --> 00:42:56.820 And so they have more time to work on features. 00:42:56.820 --> 00:43:01.540 And it seems like this is making a good tradeoff where it's, hey, this is really simple. 00:43:01.540 --> 00:43:02.320 Here's what you do. 00:43:02.320 --> 00:43:05.320 Call these two functions and we'll take care of this bit for you. 00:43:05.320 --> 00:43:09.340 So that seems like, as far as a library, that's probably some of the best you can ask for. 00:43:09.340 --> 00:43:10.360 Yeah, it's really cool. 00:43:10.360 --> 00:43:12.840 And you can actually evolve over time. 00:43:12.840 --> 00:43:21.740 So, for example, part of the thing that gets stored in the database has the number of rounds or the number of folding iterations you've done. 00:43:21.740 --> 00:43:28.160 And so as computers get faster, you can actually crank that number up over time without breaking the old passwords. 00:43:28.160 --> 00:43:33.680 And then when the user comes back, you just regenerate with a newer, more computationally expensive variant. 00:43:33.680 --> 00:43:34.100 Nice. 00:43:34.100 --> 00:43:34.400 Yep. 00:43:34.400 --> 00:43:38.140 Also supports two-factor authentication, but I know nothing about this. 00:43:39.640 --> 00:43:43.680 You could use Authy for that or implement with SMS via Twilio. 00:43:43.680 --> 00:43:46.800 That's my little Twilio commercial for this one episode. 00:43:46.800 --> 00:43:47.580 Oh, awesome. 00:43:47.580 --> 00:43:48.560 Very cool. 00:43:48.560 --> 00:43:49.300 Okay. 00:43:49.300 --> 00:43:58.000 So another thing that's cool, well, something that's just awesome about Python, the whole ecosystem, is really pip and the deployment and packaging story, right? 00:43:58.000 --> 00:44:03.520 That I can just go grab all these awesome packages and, you know, 95,000 others. 00:44:03.920 --> 00:44:04.240 Yeah. 00:44:04.240 --> 00:44:14.180 So the fact that we have PyPI as the central repository for all of our dependencies and it's really easy to upload your own libraries to the central repository. 00:44:14.920 --> 00:44:17.560 As a Python developer, it makes things so much easier for me. 00:44:17.560 --> 00:44:23.940 When I was a Java developer and I used to use Maven, Maven was incredibly complicated. 00:44:23.940 --> 00:44:27.640 You have this huge, you have these massive XML files. 00:44:27.640 --> 00:44:31.320 It worked, but it was just, it was really complicated. 00:44:31.400 --> 00:44:35.340 And then I came over to Python and you've got a requirements.txt file. 00:44:35.340 --> 00:44:40.060 And requirements.txt, when I read it, I thought, this is so beautiful. 00:44:40.060 --> 00:44:42.140 I literally thought it was beautiful. 00:44:42.680 --> 00:44:45.700 There, you have the name of the library that you depend upon. 00:44:45.700 --> 00:44:51.320 You have, and then you optionally have the version number that you want to use for that library. 00:44:51.320 --> 00:44:54.860 Now I say optionally, but really it should be required. 00:44:54.860 --> 00:45:04.740 Before I joined Twilio, I did a lot of Python consulting and it was my nightmare when I would get a project and either would not have a requirements.txt file. 00:45:04.940 --> 00:45:09.580 You know, this is something that had been running in production for a few years and they said, yeah, we threw all this stuff together. 00:45:09.580 --> 00:45:10.920 You know, we use Django. 00:45:10.920 --> 00:45:12.900 And I thought, okay, Django, that's great. 00:45:12.900 --> 00:45:13.680 Which version? 00:45:13.680 --> 00:45:15.440 And they're like, well, we don't, we don't know. 00:45:15.440 --> 00:45:24.200 And so, so we've got, we luckily have now some tools that help out with figuring out what those dependencies are. 00:45:24.200 --> 00:45:35.720 So pip-tools is a set of tools, not only to keep your, your pinned dependencies fresh, but also to kind of infer what some of the requirements are that you may, you may have. 00:45:35.720 --> 00:45:47.040 What's great about this is if you don't necessarily know what the exact version numbers are of all of the, of all of your dependencies, you can use the, some of the pip-tools in order to infer some of those things. 00:45:47.040 --> 00:45:51.620 So if you, for example, like Django, which version of Django is at 1.4 is a 1.10. 00:45:51.620 --> 00:45:53.140 This will help you to figure that out. 00:45:53.140 --> 00:45:53.920 Yeah, absolutely. 00:45:54.680 --> 00:45:54.800 Yeah. 00:45:54.800 --> 00:46:00.080 And pip-tools will actually generate the full dependency graph for you. 00:46:00.080 --> 00:46:10.040 So one thing you might say in your requirements file is like, I require flask and maybe even say I require flask 0.10.1 or whatever it happens to be. 00:46:10.040 --> 00:46:10.280 Right. 00:46:10.280 --> 00:46:16.420 But flask itself requires it's dangerous and Jinja to and markup safe and these types of things. 00:46:16.420 --> 00:46:22.180 So you can go to pip-tools and you say, run pip compile, and it will actually generate a requirements.txt. 00:46:22.860 --> 00:46:28.280 That has the sort of closure of all of your dependencies, the dependencies and their dependencies and so on. 00:46:28.280 --> 00:46:31.520 So you can see and pin every single dependence you have. 00:46:31.740 --> 00:46:36.360 And it also adds a little comment like these dependencies were added because of flask. 00:46:36.360 --> 00:46:41.200 This one was added because of Jinja, which was added because of flask, things like that. 00:46:41.200 --> 00:46:42.080 I think that was really cool. 00:46:42.080 --> 00:46:42.380 Yeah. 00:46:42.380 --> 00:46:43.060 Yeah, definitely. 00:46:43.060 --> 00:46:44.460 And just incredibly handy. 00:46:44.460 --> 00:46:53.120 If you get dropped into a project and you have no idea what the exact version numbers and requirements and dependencies of dependencies are. 00:46:53.120 --> 00:46:53.780 Yeah, absolutely. 00:46:53.780 --> 00:47:00.120 And the thing that I use actually in production for this kind of stuff, it's not the same, but I use pyup.io. 00:47:00.540 --> 00:47:04.020 I met those guys through the show a while ago and I'm like, wow, this is such a cool project. 00:47:04.020 --> 00:47:05.280 Pyup.io. 00:47:05.280 --> 00:47:08.720 And you basically, it's like an online system. 00:47:08.720 --> 00:47:12.880 You point it at your GitHub repo, public or private, and it will watch this file. 00:47:12.880 --> 00:47:22.480 And if there's changes or releases or especially security releases, it will like send you a pull request saying there's a security vulnerability and it's dangerous or something. 00:47:22.640 --> 00:47:25.820 Here's the updated requirements.txt to fix it in your app. 00:47:25.820 --> 00:47:26.180 Wow. 00:47:26.180 --> 00:47:27.000 That is incredible. 00:47:27.000 --> 00:47:27.940 That's super useful. 00:47:27.940 --> 00:47:28.760 Yeah. 00:47:28.760 --> 00:47:29.660 It's the notification. 00:47:29.660 --> 00:47:38.300 I mean, these things are changing all the time, but it's like the push notification to you that your app now has like an important update to its dependency, which I thought was really cool. 00:47:38.300 --> 00:47:39.480 Awesome. 00:47:39.480 --> 00:47:39.880 Okay. 00:47:39.880 --> 00:47:42.340 Well, those were a great bunch of libraries. 00:47:42.340 --> 00:47:44.400 Hopefully you guys learned a lot about them. 00:47:44.400 --> 00:47:47.920 Matt, it was fun to explore these with you. 00:47:47.920 --> 00:47:50.020 I didn't know about all of them before we started talking. 00:47:50.020 --> 00:47:55.040 Well, I don't think anybody knows all of the Python projects that are out there. 00:47:55.040 --> 00:47:58.740 You wouldn't get any coding done if you knew what all the projects were. 00:47:58.740 --> 00:48:06.960 So that's what I think is great about the awesome lists is you get to see at a glance just different libraries that you may never have known about. 00:48:06.960 --> 00:48:07.240 Yeah. 00:48:07.240 --> 00:48:08.140 I totally agree. 00:48:08.140 --> 00:48:17.240 And that's why I think it's so interesting to bring it up for people is because you can drop in there and really quickly learn about all these tools that you didn't know about a few minutes ago. 00:48:17.240 --> 00:48:17.600 Very cool. 00:48:17.600 --> 00:48:18.160 All right. 00:48:18.260 --> 00:48:22.200 So as always, before I let you get out of here, let me ask you the two questions. 00:48:22.200 --> 00:48:23.320 Okay. 00:48:23.320 --> 00:48:27.080 So I don't even actually remember your answer from a year and a half ago. 00:48:27.080 --> 00:48:30.740 So when you write some Python code or any code, really, what editor do you use? 00:48:30.740 --> 00:48:31.780 So I use Vim. 00:48:31.780 --> 00:48:33.180 That hasn't changed. 00:48:33.180 --> 00:48:36.800 It's been Vim for a fairly long amount of time. 00:48:36.800 --> 00:48:40.240 Now, to be fair, I use Vim for Python code. 00:48:40.240 --> 00:48:41.620 Most things I do. 00:48:41.620 --> 00:48:48.460 I use Xcode for my Swift code and I use IntelliJ, the ultimate IntelliJ edition for Java code. 00:48:48.460 --> 00:48:50.640 So I've been doing some more Java coding lately. 00:48:51.180 --> 00:48:52.900 So I kind of bounce back and forth. 00:48:52.900 --> 00:48:57.100 But I almost always use the Vim mode in whatever editor that I'm in. 00:48:57.100 --> 00:48:57.540 Yeah. 00:48:57.540 --> 00:48:59.080 That's probably a requirement for you, right? 00:48:59.080 --> 00:49:00.100 That it has a Vim mode. 00:49:00.100 --> 00:49:01.020 Yes. 00:49:01.020 --> 00:49:02.240 Nice. 00:49:02.240 --> 00:49:03.160 All right. 00:49:03.200 --> 00:49:07.320 And we kind of touched on a bunch here, but you want to pull out a favorite PyPI package? 00:49:07.320 --> 00:49:08.020 Oh, man. 00:49:08.020 --> 00:49:13.000 I'm going to, I got to, you know, I got to give a shout out to Pelican. 00:49:13.000 --> 00:49:18.580 I just, as a static site generator, I think when you use a tool, and I may have said this 00:49:18.580 --> 00:49:23.900 on episode 26, but when you use a tool for six, seven years and you still love it, I think 00:49:23.900 --> 00:49:25.980 that's a really good, really good sign. 00:49:25.980 --> 00:49:27.900 So Pelican is that tool for me. 00:49:27.900 --> 00:49:32.220 And it's a great static site generator that powers full stack Python. 00:49:32.220 --> 00:49:33.040 Yeah, that's awesome. 00:49:33.140 --> 00:49:34.640 I think that is a really good sign. 00:49:34.640 --> 00:49:39.440 If you love it after you've lived with it for a while, then it must be something special. 00:49:39.440 --> 00:49:40.620 Very cool. 00:49:40.620 --> 00:49:46.260 So I feel kind of like as a final call to action, I noticed there were some projects not listed 00:49:46.260 --> 00:49:48.260 there that I thought were awesome. 00:49:48.260 --> 00:49:53.120 You look in various, some of the categories, you're like, oh, why is this not listed here? 00:49:53.120 --> 00:49:57.940 So maybe if you're out there and you own a package or you're really passionate about it 00:49:57.940 --> 00:50:01.320 and you don't see it there, you think it's awesome, maybe go send those guys a message 00:50:01.320 --> 00:50:03.400 and let them know they should add your package. 00:50:03.400 --> 00:50:04.560 All right. 00:50:04.560 --> 00:50:07.060 Well, Matt, it's been fun to talk to you. 00:50:07.060 --> 00:50:09.080 Thanks for sharing these packages with everyone. 00:50:09.080 --> 00:50:09.620 Yeah. 00:50:09.620 --> 00:50:10.260 Thanks, Michael. 00:50:10.260 --> 00:50:11.340 It's been a great time. 00:50:11.340 --> 00:50:11.640 Yeah. 00:50:11.640 --> 00:50:12.420 Great to catch up with you. 00:50:12.420 --> 00:50:12.860 See you later. 00:50:14.660 --> 00:50:17.500 This has been another episode of Talk Python To Me. 00:50:17.500 --> 00:50:19.980 Today's guest has been Matthew Mackay. 00:50:19.980 --> 00:50:26.060 And this episode has been sponsored by AnacondaCon from Continuum Analytics and by Hired. 00:50:26.060 --> 00:50:28.160 Thank you both for supporting the podcast. 00:50:28.160 --> 00:50:32.800 Whether you want to hear the keynote by Ryan Curran from Forrester Research, meet the guys 00:50:32.800 --> 00:50:36.960 behind Anaconda, or just mingle with high-end data scientists, you need to find your way to 00:50:36.960 --> 00:50:39.400 Austin, Texas for AnacondaCon this February. 00:50:39.800 --> 00:50:42.340 Start at talkpython.fm/acon. 00:50:42.340 --> 00:50:45.360 Hired wants to help you find your next big thing. 00:50:45.360 --> 00:50:50.100 Visit Hired.com slash Talk Python To Me to get five or more offers with salary and equity 00:50:50.100 --> 00:50:53.840 presented right up front and a special listener signing bonus of $2,000. 00:50:53.840 --> 00:50:56.760 Are you or a colleague trying to learn Python? 00:50:56.760 --> 00:51:01.440 Have you tried books and videos that just left you bored by covering topics point by point? 00:51:01.840 --> 00:51:07.440 Well, check out my online course, Python Jumpstart by Building 10 Apps at talkpython.fm/course 00:51:07.440 --> 00:51:10.020 to experience a more engaging way to learn Python. 00:51:10.020 --> 00:51:14.840 And if you're looking for something a little more advanced, try my Write Pythonic Code course 00:51:14.840 --> 00:51:17.400 at talkpython.fm/Pythonic. 00:51:17.400 --> 00:51:19.860 Be sure to subscribe to the show. 00:51:19.860 --> 00:51:22.060 Open your favorite podcatcher and search for Python. 00:51:22.060 --> 00:51:23.300 We should be right at the top. 00:51:23.300 --> 00:51:29.100 You can also find the iTunes feed at /itunes, Google Play feed at /play, and 00:51:29.100 --> 00:51:32.620 direct RSS feed at /rss on talkpython.fm. 00:51:32.620 --> 00:51:37.720 Our theme music is Developers, Developers, Developers by Corey Smith, who goes by Smix. 00:51:37.720 --> 00:51:42.400 Corey just recently started selling his tracks on iTunes, so I recommend you check it out at 00:51:42.400 --> 00:51:44.400 Talk Python.fm slash music. 00:51:44.400 --> 00:51:48.840 You can browse his tracks he has for sale on iTunes and listen to the full-length version 00:51:48.840 --> 00:51:49.760 of the theme song. 00:51:50.580 --> 00:51:51.840 This is your host, Michael Kennedy. 00:51:51.840 --> 00:51:53.120 Thanks so much for listening. 00:51:53.120 --> 00:51:54.300 I really appreciate it. 00:51:54.300 --> 00:51:56.440 Smix, let's get out of here. 00:51:56.440 --> 00:51:56.440 Smix, let's get out of here. 00:51:56.440 --> 00:52:18.740 Outro Music. 00:52:18.740 --> 00:52:48.720 Thank you.