WEBVTT 00:00:00.001 --> 00:00:05.240 Hello and welcome to Python Bytes, where we deliver Python news and headlines directly to your earbuds. 00:00:05.240 --> 00:00:10.520 This is episode 215, reported January 6th, one of my favorite dates, 21. 00:00:10.520 --> 00:00:11.640 I'm Brian Okken. 00:00:11.640 --> 00:00:12.660 I'm Michael Kennedy. 00:00:12.660 --> 00:00:13.720 And we have Jason. 00:00:13.720 --> 00:00:14.160 Hello. 00:00:14.160 --> 00:00:16.440 Yeah, hey, Jason, nice to have you here. Jason McDonald. 00:00:16.440 --> 00:00:18.340 Yeah, it's good to be here. Thank you for having me. 00:00:18.340 --> 00:00:19.660 Yeah, thanks for joining us. 00:00:19.660 --> 00:00:24.040 Oh, and Brian, I think he's going to cover something we haven't really covered much on the show, GUIs. 00:00:24.040 --> 00:00:24.880 Oh, good. 00:00:26.320 --> 00:00:32.860 Actually, to be honest, I know this is like a longstanding joke in the show for longtime listeners, but we actually haven't covered GUIs that much recently. 00:00:32.860 --> 00:00:34.960 But there was a long stretch where we did. 00:00:34.960 --> 00:00:37.480 Yeah, yeah. That was probably like a year ago. 00:00:37.480 --> 00:00:38.440 Yeah, yeah. 00:00:38.440 --> 00:00:41.040 I like my programming projects and my brownies to be GUI. 00:00:41.040 --> 00:00:44.380 And fudge. Come on, fudge too. 00:00:44.380 --> 00:00:47.780 And you like bad jokes, so you'll fit in nicely. 00:00:47.780 --> 00:00:52.200 Oh, absolutely. No, if anyone likes puns, follow my Twitter. I post an original every Monday. 00:00:53.580 --> 00:00:57.640 Nice. I heard that there's going to be a lot of exciting news for space in 2021. 00:00:57.640 --> 00:01:00.580 So I kind of want to bring a little space and Python together. 00:01:00.580 --> 00:01:01.740 That's good. Yeah. 00:01:01.740 --> 00:01:02.160 Yeah. 00:01:02.160 --> 00:01:11.120 So the first topic that I want to talk about is this video done by a woman in the UK who is a astrophysicist. 00:01:11.120 --> 00:01:14.860 She goes by the name Dr. Becky, which is cool. 00:01:14.860 --> 00:01:16.460 She has a fantastic YouTube channel. 00:01:16.460 --> 00:01:22.240 She's also a Python developer and she works in cosmology, which is pretty cool. 00:01:22.240 --> 00:01:39.020 And she did this video that I'd just like to highlight for people who maybe are coming into Python, not from the, hey, I'm going to create a microservice set of APIs talking to Docker, but more from the, hey, I do some kind of science or data science or something like that. 00:01:39.020 --> 00:01:44.080 And the video is called the five ways that I use code as an astrophysicist. 00:01:44.080 --> 00:01:44.440 Cool. 00:01:44.440 --> 00:01:44.680 Huh? 00:01:44.680 --> 00:01:45.060 Yeah. 00:01:45.060 --> 00:01:45.460 Yeah. 00:01:45.460 --> 00:01:54.680 So she basically lays out the idea of as a modern day scientist, you can barely do your job if you're not doing some sort of programming. 00:01:54.680 --> 00:02:02.160 And of course, one of the best languages, technologies for programming these days is Python in the data science space, right? 00:02:02.160 --> 00:02:02.560 Right. 00:02:02.560 --> 00:02:02.820 Surprise. 00:02:02.820 --> 00:02:03.580 Yeah. 00:02:03.580 --> 00:02:05.860 No big surprise there since 2012, I would say. 00:02:05.860 --> 00:02:09.820 And so the, she covers five different things with examples of each. 00:02:09.820 --> 00:02:21.320 So I thought that was just a nice way for people who are either getting into Python from a science side, or maybe they're teachers and they want people ask them, why should I not just use MATLAB or some other custom tool? 00:02:21.320 --> 00:02:22.400 Like, let me show you. 00:02:22.620 --> 00:02:32.220 So here's some really cool examples of real astronomy being done with Python, but it's also super accessible to even like middle schoolers, I would say. 00:02:32.220 --> 00:02:36.980 And number one is image processing of galaxies from telescopes. 00:02:36.980 --> 00:02:40.040 So you can do things like noise removal. 00:02:40.220 --> 00:02:55.400 So it turns out that when you're taking pictures of galaxies, even if there's no actual background light or disturbances, just the basic disturbance in the actual sensors themselves will put little marks and imperfections in the images. 00:02:55.580 --> 00:03:00.800 So using Python to go through and clean those up makes it much easier to get started. 00:03:00.800 --> 00:03:07.060 And the size of these pictures and the amount of data coming in from some of these new telescopes is stunningly large. 00:03:07.060 --> 00:03:07.560 It's cool. 00:03:07.560 --> 00:03:07.800 Yeah. 00:03:07.800 --> 00:03:08.300 For sure. 00:03:08.620 --> 00:03:10.660 Another one is data analysis. 00:03:11.180 --> 00:03:18.380 So if you're trying to find the brightness of some part of an image, say, maybe you're looking for a transit of an exoplanet, right? 00:03:18.380 --> 00:03:20.840 You want to constantly monitor the brightness of a star. 00:03:21.060 --> 00:03:23.740 Or in her case, what she's studying, it just blows my mind. 00:03:23.740 --> 00:03:24.700 She's studying galaxies. 00:03:24.700 --> 00:03:28.220 Like when you see pictures of stars and you're zooming in, you're like, oh, that's not a star. 00:03:28.220 --> 00:03:29.080 That's a galaxy. 00:03:29.080 --> 00:03:32.060 It's just like, you know, like I still can't really get my mind around that. 00:03:32.060 --> 00:03:38.200 But she talks about one of her data sets that has 600,000 rows of like brightness of galaxies. 00:03:38.200 --> 00:03:41.880 So 600,000 galaxies, they all have information about that they're comparing. 00:03:41.880 --> 00:03:43.500 So that's pretty awesome, right? 00:03:43.500 --> 00:03:43.900 Yep. 00:03:43.900 --> 00:03:44.960 Model fitting. 00:03:44.960 --> 00:03:50.800 There's an example about theory that most galaxies have a supermassive black hole in the middle. 00:03:51.080 --> 00:03:57.680 There's also this idea that possibly the size of the black hole and the size of the galaxy, these things kind of grow in mass together. 00:03:57.680 --> 00:03:58.780 So she has all this data. 00:03:58.780 --> 00:04:03.040 She's like, well, let's do some statistical fits of black hole size and galaxy size. 00:04:03.040 --> 00:04:09.120 Also, the color of galaxies can indicate the relative speed or rate of star formation. 00:04:09.120 --> 00:04:09.880 And the age. 00:04:09.880 --> 00:04:10.600 And the age. 00:04:10.600 --> 00:04:10.960 Exactly. 00:04:10.960 --> 00:04:11.220 Yeah. 00:04:11.220 --> 00:04:12.460 All tied together. 00:04:12.460 --> 00:04:14.340 And so she's using Python for that. 00:04:14.340 --> 00:04:18.980 Finally, data visualization, you know, pretty straightforward, but in drawing graphs and pictures. 00:04:19.140 --> 00:04:22.220 And the last part that was my favorite part is simulation. 00:04:22.220 --> 00:04:24.000 So there's two really cool examples. 00:04:24.000 --> 00:04:30.220 What happens if a star gets too close to a black hole and gets, she said, spaghetti-ified? 00:04:30.220 --> 00:04:30.900 That's cool. 00:04:31.820 --> 00:04:37.100 And the other one is examples of galaxies colliding, which is just, again, mind-blowing. 00:04:37.100 --> 00:04:40.260 But really cool computational examples of all that. 00:04:40.260 --> 00:04:47.780 So I wanted to highlight this video because it's super accessible, but it's also really neat to show concrete examples of real science being done with Python. 00:04:47.780 --> 00:04:53.900 Yeah, I thought it was cool when she was talking to her colleague about building the simulations of the universe. 00:04:53.900 --> 00:04:55.400 You know, you have a simulation of the universe. 00:04:55.400 --> 00:04:57.460 Where do you start on that? 00:04:57.460 --> 00:05:00.740 It's like, we think we have project blocking. 00:05:00.740 --> 00:05:02.280 You know, it's like you start on a project. 00:05:02.280 --> 00:05:03.720 It's like, yeah, I'm just going to build a tool. 00:05:03.720 --> 00:05:04.620 Where do I begin? 00:05:04.620 --> 00:05:06.900 It's like, I'm going to build a simulation of the entire universe. 00:05:06.900 --> 00:05:07.840 Where do I start? 00:05:08.160 --> 00:05:08.560 Exactly. 00:05:08.560 --> 00:05:12.660 I'm going to simulate gravity at a galactic scale. 00:05:12.660 --> 00:05:13.500 Let's just do that. 00:05:13.500 --> 00:05:14.660 Yeah. 00:05:14.660 --> 00:05:15.100 Awesome. 00:05:15.100 --> 00:05:19.120 So if people are out there and they're interested in this kind of stuff, yeah. 00:05:19.120 --> 00:05:20.540 This is all in one video? 00:05:20.540 --> 00:05:21.020 Yeah. 00:05:21.020 --> 00:05:22.000 This is all in one video. 00:05:22.000 --> 00:05:22.880 Yeah. 00:05:22.880 --> 00:05:24.840 Robert says star or galaxy. 00:05:24.840 --> 00:05:25.360 It's big. 00:05:25.360 --> 00:05:25.540 Yeah. 00:05:25.540 --> 00:05:27.320 They're both huge, but obviously, man. 00:05:27.320 --> 00:05:30.140 It's just like, I can't get my head around like galaxy-sized stuff. 00:05:30.140 --> 00:05:31.660 It's so insane. 00:05:31.660 --> 00:05:35.600 Star is a primitive type in the universe. 00:05:35.600 --> 00:05:37.580 And then a galaxy is a collection. 00:05:38.040 --> 00:05:41.200 That's what I just immediately go to right there. 00:05:41.200 --> 00:05:41.480 Yeah. 00:05:41.480 --> 00:05:41.920 Exactly. 00:05:41.920 --> 00:05:43.620 Yeah. 00:05:43.620 --> 00:05:47.900 So Brian, it's like a 15 minute video that half of it is the stuff that I talked about. 00:05:47.900 --> 00:05:49.360 Then half is what Jason touched on. 00:05:49.360 --> 00:05:54.680 She actually interviews one of her colleagues who basically does the more, the simulation side 00:05:54.680 --> 00:05:55.140 of programming. 00:05:55.140 --> 00:05:56.160 That's pretty cool. 00:05:56.160 --> 00:05:56.580 Yeah. 00:05:56.580 --> 00:05:56.980 Yeah. 00:05:56.980 --> 00:05:57.820 I'll have to check that out. 00:05:57.820 --> 00:05:58.220 Yeah. 00:05:58.220 --> 00:05:58.920 It's definitely worth it. 00:05:58.920 --> 00:05:59.280 Yeah. 00:05:59.280 --> 00:05:59.780 I enjoyed it. 00:05:59.780 --> 00:06:01.900 I don't do very much data science actually at all. 00:06:01.900 --> 00:06:06.400 And so it's like, you know, understanding, seeing data science stuff is always interesting because 00:06:06.400 --> 00:06:09.160 I, but most of my work is in like application development. 00:06:09.160 --> 00:06:10.760 I don't usually work with a lot of data. 00:06:10.760 --> 00:06:14.840 So it's the, that side of it explained in this really cool, relevant way. 00:06:14.840 --> 00:06:17.980 And said, I was like, well, the statistics is a number of people, you know, who, you know, 00:06:17.980 --> 00:06:21.720 buy, you know, cheese every weekend that the supermarket is not interested galaxies. 00:06:22.560 --> 00:06:22.960 Exactly. 00:06:22.960 --> 00:06:27.580 Getting better click through rates on your ads is not, not super compelling, but I think 00:06:27.580 --> 00:06:30.560 it's really valuable to see alternate perspectives, right? 00:06:30.560 --> 00:06:33.640 We all get into our own little world of like, this is what programming is. 00:06:33.640 --> 00:06:34.720 This is what Python is for. 00:06:34.720 --> 00:06:36.700 And then, you know, it's, it's bigger. 00:06:36.700 --> 00:06:39.140 I want to talk about NumPy a little bit. 00:06:39.140 --> 00:06:39.480 All right. 00:06:39.480 --> 00:06:40.240 Tell us about it. 00:06:40.300 --> 00:06:43.480 Well, I've, I've, I actually, I've used NumPy off and on a lot. 00:06:43.480 --> 00:06:48.580 And it's definitely a staple scientific use of machine learning and sorts of stuff, but, 00:06:48.580 --> 00:06:50.480 but I'm starting to use it more. 00:06:50.480 --> 00:06:54.820 And I've realized, I realized that I had the wrong mental model. 00:06:54.820 --> 00:06:58.740 So I like think of arrays kind of just like lists, but different. 00:06:58.740 --> 00:07:01.460 And so I came across this article. 00:07:01.460 --> 00:07:05.480 It's a couple of years old, but it's a visual intro to NumPy and data represent. 00:07:05.720 --> 00:07:10.520 And to me, it really helps a lot, like to, to help me understand what you can do with 00:07:10.520 --> 00:07:15.320 it and just have a good mental picture of what, what the arrays are in NumPy. 00:07:15.320 --> 00:07:20.760 So it talks about arrays, matrices, and, and, and, and D arrays, which are in dimensional, 00:07:20.760 --> 00:07:23.920 but like, for instance, I'm even just creating an array. 00:07:23.920 --> 00:07:25.300 I knew how to create an array. 00:07:25.300 --> 00:07:30.100 I mean, you just kind of initialize it with a list and you get an array, but I didn't know 00:07:30.100 --> 00:07:35.260 you could do like, just say I want a list of ones or a list of zeros. 00:07:35.640 --> 00:07:40.220 Or an array of ones or just a random array pre-filled with random numbers. 00:07:40.220 --> 00:07:40.640 That's pretty. 00:07:40.640 --> 00:07:45.640 And then he talks about, you know, arithmetic you can do with them and slicing and stuff. 00:07:45.640 --> 00:07:49.840 You know, Brian, like when we talk about Pythonic code all the time, like, oh, you could write 00:07:49.840 --> 00:07:54.340 code in this way where you kind of hack a numerical for loop, but you should do this other way. 00:07:54.340 --> 00:07:55.420 And that would be more Pythonic. 00:07:55.420 --> 00:07:57.300 I suspect there's also a. 00:07:57.300 --> 00:07:58.120 A NumPy way. 00:07:58.120 --> 00:08:00.020 A NumPy way, right? 00:08:00.020 --> 00:08:00.180 Yeah. 00:08:00.180 --> 00:08:01.260 Sort of like filling up stuff. 00:08:01.260 --> 00:08:03.080 You're like, oh, you should just do ones on this one. 00:08:03.140 --> 00:08:07.280 And then then, you know, you always like there's a lot of cool other ways of sort of 00:08:07.280 --> 00:08:08.300 conceptualizing things. 00:08:08.300 --> 00:08:08.540 Right. 00:08:08.540 --> 00:08:09.040 Yeah. 00:08:09.040 --> 00:08:11.180 Well, and it's worth remembering. 00:08:11.180 --> 00:08:13.720 You know, I've said this quite a few times. 00:08:13.720 --> 00:08:15.180 Not here, obviously. 00:08:15.180 --> 00:08:21.060 But I regularly like to remind people abstractions are there to save us typing, never to save us 00:08:21.060 --> 00:08:21.360 thinking. 00:08:21.360 --> 00:08:25.880 It's like it helps to have that mental model, as you put it, Brian, you know, straight. 00:08:26.000 --> 00:08:29.820 Because if your mental model is wrong, it can really wind up. 00:08:29.820 --> 00:08:32.280 Well, you're prone to both cargo cult programming. 00:08:32.280 --> 00:08:34.400 Well, I do it this way because it's the way I was taught. 00:08:34.400 --> 00:08:40.380 Or trying to, you know, ill fit a pattern that's familiar to, you know, the wrong sort of problem 00:08:40.380 --> 00:08:42.740 and you don't realize what it is you're really working with. 00:08:42.740 --> 00:08:46.720 So understanding what's happening under the hood, even if, you know, you don't know all 00:08:46.720 --> 00:08:48.200 the technical details of the implementation. 00:08:48.200 --> 00:08:52.840 So understanding how it's doing things is important to, you know, choosing the right job. 00:08:52.840 --> 00:08:54.340 Idiomatic patterns always. 00:08:54.580 --> 00:08:55.040 Yeah, yeah. 00:08:55.040 --> 00:08:56.860 And you'll hear stuff like, oh, well, Python is slow. 00:08:56.860 --> 00:08:58.340 It's like, well, because you're doing it wrong. 00:08:58.340 --> 00:08:59.580 Don't do it that way. 00:08:59.580 --> 00:09:01.420 For example, use something like NumPy, right? 00:09:01.420 --> 00:09:05.380 And like, for instance, one of the things I really loved about this article was the explanation 00:09:05.380 --> 00:09:08.680 of dot product because I've heard this before. 00:09:08.680 --> 00:09:12.980 I've never had to use a dot product, but it like somebody described it to me several times 00:09:12.980 --> 00:09:14.720 and I'm like, yeah, okay, weird. 00:09:14.720 --> 00:09:20.040 But then like the visual representation of it, I like just stared at it and read it for like, 00:09:20.040 --> 00:09:21.100 you know, 30 seconds. 00:09:21.100 --> 00:09:22.380 Oh, that's easy. 00:09:22.380 --> 00:09:23.280 Now I get it. 00:09:23.280 --> 00:09:26.940 And I'll have it forever now because of that sunk in there. 00:09:26.940 --> 00:09:27.500 Pretty good. 00:09:27.500 --> 00:09:28.360 Yeah, that's awesome. 00:09:28.360 --> 00:09:35.560 One of the reasons why I went to it, I have this problem is that I have like large arrays, 00:09:35.560 --> 00:09:36.740 but they're not like huge. 00:09:37.220 --> 00:09:39.880 They're like in the thousands, say, of numbers. 00:09:39.880 --> 00:09:44.100 And I need to make sure that one array is like comparing to another. 00:09:44.100 --> 00:09:50.960 I know equal works, but I wanted to compare item by item to make sure every element is less 00:09:50.960 --> 00:09:54.860 than the other element in the other array, less than or equal. 00:09:54.860 --> 00:09:55.880 I didn't know how to do that. 00:09:55.880 --> 00:09:58.060 And I'm like, I think NumPy would probably do that easy. 00:09:58.060 --> 00:10:00.440 Can you do one NumPy array less than the other? 00:10:00.840 --> 00:10:01.240 Yeah. 00:10:01.240 --> 00:10:01.280 Yeah. 00:10:01.280 --> 00:10:06.240 So if you say less than, it compares it element by element and it gives you a list of true 00:10:06.240 --> 00:10:06.740 or false. 00:10:06.740 --> 00:10:08.260 And then you can do all. 00:10:08.260 --> 00:10:08.600 Yeah. 00:10:08.600 --> 00:10:09.360 Do an all on it. 00:10:09.360 --> 00:10:09.500 Yeah. 00:10:09.500 --> 00:10:13.520 Just say all of these two arrays less than or equal to each other. 00:10:13.520 --> 00:10:14.920 And I get exactly what I want. 00:10:14.920 --> 00:10:17.500 They're very expressive, simple line of code. 00:10:17.800 --> 00:10:17.980 Yeah. 00:10:17.980 --> 00:10:22.700 It's that kind of stuff I was thinking of when I was talking about like the NumPy, NumPy 00:10:22.700 --> 00:10:23.520 way or whatever. 00:10:23.520 --> 00:10:24.520 Idiomatic NumPy. 00:10:24.520 --> 00:10:25.440 Thank you. 00:10:25.440 --> 00:10:28.960 It's like, that's like one or two lines and it's really fast. 00:10:28.960 --> 00:10:33.300 Whereas you could loop over each item individually and it not only is more code, but it's also 00:10:33.300 --> 00:10:33.620 slower. 00:10:33.620 --> 00:10:34.180 Yeah. 00:10:34.180 --> 00:10:38.340 Well, and also I like, I also have to, I like that there's the intermediate step of that. 00:10:38.340 --> 00:10:43.120 There's gives me a list of true and false too, because I also on the debugging side, 00:10:43.380 --> 00:10:48.380 I need to be able to like wrap this in something and pick like, say the first five elements 00:10:48.380 --> 00:10:49.620 that are not matching. 00:10:49.620 --> 00:10:54.020 I mean, I don't want, if I, if, if it, if it's false, the whole statement's false. 00:10:54.020 --> 00:10:59.080 I don't want to like just say, you know, list all the thousands that are wrong, but I want 00:10:59.080 --> 00:11:02.660 to be able to like list a few to say, at least these are not in the right. 00:11:02.660 --> 00:11:03.000 Yeah. 00:11:03.000 --> 00:11:03.500 Yeah. 00:11:03.500 --> 00:11:04.060 It's good. 00:11:04.060 --> 00:11:05.400 I'm going to try out NumPy now. 00:11:05.400 --> 00:11:08.760 Hey, I now have a reason to try it out. 00:11:08.760 --> 00:11:09.480 Exactly. 00:11:09.480 --> 00:11:11.680 Like, why am I not using this in certain situations? 00:11:12.260 --> 00:11:15.440 Magnus, the live stream says, two dimensions is okay. 00:11:15.440 --> 00:11:18.140 Three is hard, but in that, then my mind blows. 00:11:18.140 --> 00:11:18.300 Yeah. 00:11:18.300 --> 00:11:22.220 I actually did a bunch of math research and four dimensional stuff, two dimensional, but 00:11:22.220 --> 00:11:23.160 complex numbers. 00:11:23.160 --> 00:11:26.360 So four dimensional sort of, and yeah, it's just, it's just hard. 00:11:26.360 --> 00:11:30.020 Well, what one, one of my weird nacks as a programmer is I actually can think in six 00:11:30.020 --> 00:11:30.360 dimensions. 00:11:30.360 --> 00:11:33.960 It's it's, I mentioned before the podcast, I had a head injury a few years ago. 00:11:33.960 --> 00:11:35.220 So I'm a minor traumatic savant. 00:11:35.220 --> 00:11:36.540 I can think in six dimension. 00:11:36.540 --> 00:11:40.520 And the best way I can explain it, if you're trying to do it without having a really bizarre brain 00:11:40.520 --> 00:11:45.540 like mine is think of, think of the fourth dimension as a timeline. 00:11:45.540 --> 00:11:51.060 And for each timeline you have, you have space represented as a cube, but then you have this 00:11:51.060 --> 00:11:53.000 row of cubes, which represents the timeline. 00:11:53.000 --> 00:11:57.660 It becomes a lot easier to think of four dimensional race when you think of it in that fashion. 00:11:57.660 --> 00:11:58.040 Yeah. 00:11:58.040 --> 00:12:01.660 And the way that we did it, we actually had animations of that three dimension thing and 00:12:01.660 --> 00:12:03.860 the animations were moving through that, that bit. 00:12:03.860 --> 00:12:04.040 Yeah. 00:12:04.040 --> 00:12:07.200 But still it's, it's, it's no easy, no easy thing. 00:12:07.200 --> 00:12:07.420 Yeah. 00:12:07.420 --> 00:12:11.420 It's easier when you're an animator to wrap your head around 4d than if you're just a, you 00:12:11.420 --> 00:12:14.240 know, an ordinary run of the mill programmer like most of us. 00:12:14.240 --> 00:12:17.220 Brian, would you say that that's a gooey type of solution? 00:12:17.220 --> 00:12:18.600 no. 00:12:18.600 --> 00:12:21.620 Maybe you could do something with cute. 00:12:21.620 --> 00:12:22.380 Yeah. 00:12:22.380 --> 00:12:22.620 Yeah. 00:12:22.620 --> 00:12:22.980 Okay. 00:12:22.980 --> 00:12:23.940 Oh yeah. 00:12:23.940 --> 00:12:24.600 I don't know. 00:12:24.600 --> 00:12:24.840 Yeah. 00:12:24.840 --> 00:12:25.260 Jason. 00:12:25.260 --> 00:12:25.840 Yeah. 00:12:25.840 --> 00:12:26.360 Who knows? 00:12:26.360 --> 00:12:26.920 It's possible. 00:12:27.640 --> 00:12:29.760 So, that's our next topic. 00:12:29.760 --> 00:12:30.280 Take it. 00:12:30.280 --> 00:12:30.940 Grab it, Jason. 00:12:30.940 --> 00:12:31.520 Yeah. 00:12:31.520 --> 00:12:32.100 Well, okay. 00:12:32.100 --> 00:12:36.800 Well, I, I, so I was really excited to discover the cute six just released on December 00:12:36.800 --> 00:12:37.280 8th. 00:12:37.280 --> 00:12:38.380 So, cute. 00:12:38.380 --> 00:12:39.080 Yeah. 00:12:39.080 --> 00:12:40.540 It is officially pronounced cute. 00:12:40.540 --> 00:12:41.920 Although it's much, it's very debatable. 00:12:41.920 --> 00:12:42.940 People like, Oh, it's cutie. 00:12:42.940 --> 00:12:43.360 It's cute. 00:12:43.360 --> 00:12:44.540 Come on. 00:12:44.540 --> 00:12:45.800 Yeah, exactly. 00:12:45.800 --> 00:12:48.040 Anyway, whatever you're going to call it, it just released. 00:12:48.040 --> 00:12:50.480 and this includes the Python binding. 00:12:50.480 --> 00:12:56.880 So, pie side six, Shabokan six, which is the, so pie side two was cutie five, 00:12:56.880 --> 00:12:57.860 as if that made sense. 00:12:57.860 --> 00:12:59.500 Pie side six is, is cute. 00:12:59.500 --> 00:13:00.520 T six, cute sexy. 00:13:00.520 --> 00:13:01.500 Now I'm doing it. 00:13:01.500 --> 00:13:03.340 Anyway, so that just released. 00:13:03.340 --> 00:13:09.960 and you also have the pie cute T six, if you prefer, Riverbanks version, but in 00:13:09.960 --> 00:13:13.720 whatever case, you're going to wind up with, with all the, all the cute six features. 00:13:13.720 --> 00:13:18.340 I think the coolest thing here is if you're doing, if you're doing like, 00:13:18.340 --> 00:13:24.060 you know, really fancy sort of, graphics is that, previously, cute five and prior 00:13:24.060 --> 00:13:28.820 had this hard dependency on open GL and they've actually put in a, what they call the rendering 00:13:28.820 --> 00:13:29.780 hardware interface. 00:13:29.780 --> 00:13:32.060 So it's an abstraction layer into, into cute. 00:13:32.060 --> 00:13:37.440 So now, it can natively support whatever the 3d graphics driver is on that device, whether 00:13:37.440 --> 00:13:42.000 it's direct ax, bulk in metal, whatever, whatever you want it to work with, but uses the native 00:13:42.000 --> 00:13:42.640 by default. 00:13:42.640 --> 00:13:45.440 You could, you could tell it to use whatever, whatever you want. 00:13:45.440 --> 00:13:46.920 that is so cool. 00:13:46.920 --> 00:13:47.480 Yeah. 00:13:47.700 --> 00:13:51.400 and there's a bunch of other optimizations and fixes to have in here. 00:13:51.400 --> 00:13:57.760 I am really excited because I discovered, and this was actually introduced in five 15, 00:13:57.760 --> 00:14:03.060 but they now support snake case for those of us who are like PEP 8 addicts who really 00:14:03.060 --> 00:14:06.860 hate the fact that cute kind of seemed to force you to use the camel case. 00:14:06.860 --> 00:14:08.240 You can use snake case. 00:14:08.240 --> 00:14:11.420 There is a, there is a, a setting for it. 00:14:11.660 --> 00:14:15.240 you can also use properties instead of getters and setters as a cute X. 00:14:15.240 --> 00:14:21.820 So you can just rely on properties and that is, it makes it a lot easier to write, you know, 00:14:21.820 --> 00:14:24.920 idiomatic Python code that is cute, which is fun. 00:14:24.920 --> 00:14:29.540 Well, it just feels wrong to write, you know, get with, set with all those things. 00:14:29.540 --> 00:14:33.080 They also have this cool thing called property binding where you can actually link those together 00:14:33.080 --> 00:14:35.160 now too, is like you can link the width and the height. 00:14:35.160 --> 00:14:37.180 So when you change the width, height automatically changes. 00:14:37.180 --> 00:14:37.620 Nice. 00:14:37.620 --> 00:14:38.060 Yeah. 00:14:38.060 --> 00:14:39.980 I really want to build some stuff with cute. 00:14:40.260 --> 00:14:42.860 I've, I've got a few app ideas in mind. 00:14:42.860 --> 00:14:44.380 What I don't have is time. 00:14:44.380 --> 00:14:45.800 Sadly. 00:14:45.800 --> 00:14:46.560 Can you help me with that? 00:14:46.560 --> 00:14:48.820 Jason, can you tell me to have more time in my life? 00:14:48.820 --> 00:14:53.340 I, I know I have a reputation as a time Lord, but unfortunately I can't control the 00:14:53.340 --> 00:14:55.800 stream of flow of time there. 00:14:55.800 --> 00:15:00.140 If I find my TARDIS, I'll pick you up and, and, and drop you off, you know, 10 years ago 00:15:00.140 --> 00:15:02.660 and you can relive those 10 years and do additional things. 00:15:02.660 --> 00:15:03.120 Okay. 00:15:03.120 --> 00:15:03.480 Yeah. 00:15:03.480 --> 00:15:03.740 Nice. 00:15:03.740 --> 00:15:04.000 Nice. 00:15:04.000 --> 00:15:05.000 That would be, yeah. 00:15:05.000 --> 00:15:05.420 Yep. 00:15:05.420 --> 00:15:09.760 let's see, actually a couple of questions from the live stream. 00:15:09.860 --> 00:15:12.720 Magnus asks, any news about cute going mobile? 00:15:12.720 --> 00:15:15.400 I actually am ashamed to admit. 00:15:15.400 --> 00:15:16.020 I don't know. 00:15:16.020 --> 00:15:23.420 I don't know either, but the, I think the bigger, more interesting question would, could PyQt stuff 00:15:23.420 --> 00:15:27.140 like could, would, could, would you be able to write a Python cute application and make it 00:15:27.140 --> 00:15:27.440 mobile? 00:15:27.440 --> 00:15:27.900 Right. 00:15:27.900 --> 00:15:29.420 I think that's where it gets really interesting. 00:15:29.420 --> 00:15:34.380 cause there's other, if you pick another language like C++, there's other options 00:15:34.380 --> 00:15:35.900 you might be able to choose. 00:15:35.900 --> 00:15:39.840 And then, maybe, you know, this one you're going to ask, are there any well-known Python 00:15:39.840 --> 00:15:40.780 apps built with cute? 00:15:41.060 --> 00:15:41.360 Oh yeah. 00:15:41.360 --> 00:15:41.680 Yeah. 00:15:41.680 --> 00:15:41.720 Yeah. 00:15:41.720 --> 00:15:42.820 They're, I'm on the spot. 00:15:42.820 --> 00:15:43.940 I'm trying to think of what mine. 00:15:43.940 --> 00:15:47.720 It's not well known, but I built time card in cute. 00:15:47.720 --> 00:15:52.380 If you look up, if you look up time card, it's just a time tracking, app that 00:15:52.380 --> 00:15:56.400 I, that I built, but actually there's, there's, there's quite a lot built, built with cute. 00:15:56.640 --> 00:15:58.280 I didn't want to K in front of it. 00:15:58.280 --> 00:16:04.080 If you're, if you're into KDE, the entire, the entire KDE stack is built on top of cute. 00:16:04.080 --> 00:16:05.260 And there's actually quite a bit of it. 00:16:05.260 --> 00:16:10.960 So, names are escaping me off the top of my head here, but, yeah, there's any, 00:16:10.960 --> 00:16:14.440 anything in the KDE universe is, is cute. 00:16:14.440 --> 00:16:16.780 And so you're either going to get C++ or Python. 00:16:16.780 --> 00:16:19.000 Python is certainly a lot faster, right? 00:16:19.000 --> 00:16:21.940 So, oh, filezilla apparently is built. 00:16:21.940 --> 00:16:26.540 You know, one that I know that's written in it, for sure that I, it's like one of my 00:16:26.540 --> 00:16:30.840 favorite apps actually is, Robo Mongo or Robo three T it got renamed to. 00:16:30.840 --> 00:16:36.320 I believe it's just C++ it's not Python cute, but that one's a really nice one 00:16:36.320 --> 00:16:36.800 as well. 00:16:36.800 --> 00:16:38.840 Actually, there's a huge long list. 00:16:38.840 --> 00:16:43.060 I'll put it in the show notes over here, of a bunch of apps written as well. 00:16:43.060 --> 00:16:47.300 So it's definitely a lot easier to write, write, something in KDE. 00:16:47.300 --> 00:16:50.580 I've, I've used a lot of different UI toolkits and KDE's definitely one of the easiest. 00:16:50.580 --> 00:16:51.140 Yeah. 00:16:51.140 --> 00:16:55.740 The thing that I like about it is it looks like it belongs because so many apps you build with 00:16:55.740 --> 00:16:59.480 these sort of cross platform things and it's just like, well, okay, well that's not how 00:16:59.480 --> 00:17:00.820 the file dialogue is supposed to look. 00:17:00.820 --> 00:17:04.340 You just know it's alien, but you're like, no, no, this looks, this looks like it belongs 00:17:04.340 --> 00:17:04.580 here. 00:17:04.580 --> 00:17:07.900 Well, and packaging is the other half of it because like I tried to build something with 00:17:07.900 --> 00:17:11.100 Kivi and I love Kivi from a, from a development standpoint. 00:17:11.100 --> 00:17:11.740 It's really cool. 00:17:11.740 --> 00:17:14.720 From a packaging standpoint, it's like beating yourself to death of the wet trout. 00:17:15.260 --> 00:17:21.360 So, and, and actually if you're going to do cross platform, then, actually, 00:17:21.360 --> 00:17:25.240 GTK is horrible too, because it's really hard to get it to package on windows. 00:17:25.240 --> 00:17:27.060 A lot of times it just works. 00:17:27.060 --> 00:17:28.820 It just packages everywhere, which. 00:17:28.820 --> 00:17:29.520 Yeah, that's great. 00:17:29.520 --> 00:17:29.900 Nice. 00:17:29.900 --> 00:17:30.200 Nice. 00:17:30.200 --> 00:17:30.940 All right. 00:17:30.940 --> 00:17:34.400 Brian, I think this episode is brought to everyone by us. 00:17:34.400 --> 00:17:34.940 Wonderful. 00:17:34.940 --> 00:17:35.460 Yeah. 00:17:35.460 --> 00:17:40.240 So we are, we're doing a lot of work out there and as everyone probably knows, if you're 00:17:40.240 --> 00:17:42.880 into testing, check out Brian's pytest book. 00:17:42.880 --> 00:17:49.940 If you're looking to take a Python course, we are just about to pass 200 hours of Python courses 00:17:49.940 --> 00:17:51.300 over at Talk Python training. 00:17:51.300 --> 00:17:56.780 I'm working on a new course, how to build web apps, not web APIs, but web apps with FastAPI. 00:17:56.780 --> 00:17:57.940 Super neat stuff. 00:17:57.940 --> 00:17:59.620 So that's, that should be out in a week or two. 00:17:59.620 --> 00:18:00.240 So anyway. 00:18:00.240 --> 00:18:00.680 Yeah. 00:18:00.680 --> 00:18:05.380 I'm also, I wanted to bring up that, there was kind of a spike in, pytest books. 00:18:05.380 --> 00:18:11.280 Sales in last, last quarter of 2020 and hoping that like some screws in it, right? 00:18:11.280 --> 00:18:13.260 Testing other teaching. 00:18:13.260 --> 00:18:14.700 So yeah, that'd be super cool. 00:18:14.700 --> 00:18:15.040 Yeah. 00:18:15.040 --> 00:18:18.620 It's nice to see more, more, more, more stuff about stuff other than unit test. 00:18:18.620 --> 00:18:22.180 I mean, unit test has its place, but I, when I wrote the chat, I've got a book coming out 00:18:22.180 --> 00:18:25.640 in May and when I wrote the chapter on testing and one of my editors was like, thank you for 00:18:25.640 --> 00:18:29.360 not forcing me to edit yet one more unit test chapter. 00:18:29.360 --> 00:18:30.640 Nice. 00:18:30.640 --> 00:18:31.300 What's your book on? 00:18:31.300 --> 00:18:33.620 Oh, my book's called a dead simple Python. 00:18:33.820 --> 00:18:39.480 It just, it, it introduces the language of Python, the idiomatic practices of Python 00:18:39.480 --> 00:18:41.940 to people who are coming from another language. 00:18:41.940 --> 00:18:45.760 So if you don't want to have to sit through yet one more explanation of what a variable 00:18:45.760 --> 00:18:50.360 or a function is or a class is, you can pick this up and it dives straight into the, the, 00:18:50.360 --> 00:18:54.580 the fine details of why idiomatic patterns are what they are in Python. 00:18:54.580 --> 00:18:54.920 Nice. 00:18:54.920 --> 00:18:55.700 That's yeah. 00:18:55.700 --> 00:18:56.280 That's a good idea. 00:18:56.280 --> 00:19:00.840 I, I, the courses or books that say, we're going to pretend, you know, nothing about the 00:19:00.840 --> 00:19:04.240 world and we're going to force you to go through everything from scratch every time that drives 00:19:04.240 --> 00:19:04.640 me crazy. 00:19:04.640 --> 00:19:10.440 You know, what else drives me crazy, Brian is, when my Python GC is doing stuff when 00:19:10.440 --> 00:19:12.200 I know that it doesn't need to do stuff. 00:19:12.200 --> 00:19:12.700 Yeah. 00:19:12.700 --> 00:19:14.820 I like to not have to think about the garbage collect. 00:19:14.820 --> 00:19:16.060 And you generally don't, right? 00:19:16.060 --> 00:19:21.300 Like one of the things that genuinely surprises me is the fact that we don't really talk about 00:19:21.300 --> 00:19:22.940 memory very much in Python. 00:19:22.940 --> 00:19:23.520 It's like, Oh, okay. 00:19:23.520 --> 00:19:24.460 I think it cleans itself up. 00:19:24.460 --> 00:19:24.860 That's good. 00:19:24.860 --> 00:19:25.400 Now what? 00:19:25.400 --> 00:19:25.880 Let's go. 00:19:25.960 --> 00:19:26.580 Let's go about stuff. 00:19:26.580 --> 00:19:26.800 Right. 00:19:26.800 --> 00:19:29.540 But if you dig into it, it's pretty interesting. 00:19:29.540 --> 00:19:32.960 There's a lot of stuff around allocation we've covered before, but it's quite unique. 00:19:32.960 --> 00:19:36.980 but Python's also somewhat unique in the sense that it has like two modes. 00:19:36.980 --> 00:19:44.080 So it has reference counting, which I would say 98% of all like memory management cleanup 00:19:44.080 --> 00:19:45.920 stuff is in the reference counting side. 00:19:45.920 --> 00:19:50.520 This is totally made up these numbers, but there's a little, there's, I would say maybe 00:19:50.520 --> 00:19:55.440 even more like 99.5, unless you're building some kind of a certain kind of app, like with 00:19:55.440 --> 00:19:58.960 interesting algorithms, most apps don't create cycles. 00:19:58.960 --> 00:20:03.460 And the only reason we have garbage collection in addition to the reference counting is to 00:20:03.460 --> 00:20:04.940 catch those cycles, right? 00:20:04.940 --> 00:20:07.420 you know, I've got a customer object. 00:20:07.420 --> 00:20:09.300 I've got it out of a SQLAlchemy database. 00:20:09.300 --> 00:20:11.800 It has a relationship over to the orders. 00:20:11.800 --> 00:20:12.560 I go to the orders. 00:20:12.560 --> 00:20:14.340 The orders have a link back to the customer. 00:20:14.340 --> 00:20:19.420 Maybe like traversing that lazy loaded list has created a cycle and now I need the GC to save 00:20:19.420 --> 00:20:19.580 me. 00:20:19.580 --> 00:20:24.560 So the rule for when the garbage collector runs is you can ask it. 00:20:24.560 --> 00:20:28.880 You can say, import the GC module and say GC dot get threshold or thresholds. 00:20:28.880 --> 00:20:31.200 I can't remember a singular or plural on my screen. 00:20:31.200 --> 00:20:35.120 If I would switch to a singular get threshold, it returns three numbers. 00:20:35.120 --> 00:20:38.020 they're not the same units, which makes them really hard to understand. 00:20:38.020 --> 00:20:42.600 The first number is how many allocations of collection objects. 00:20:42.600 --> 00:20:47.300 So classes, dictionaries, lists, tuples, things that could contain other stuff. 00:20:47.300 --> 00:20:51.720 So things that could potentially be participants in a cycle, like numbers and strings are not 00:20:51.720 --> 00:20:52.960 even considered by the GC. 00:20:52.960 --> 00:20:58.780 But how many allocations of collection types are there that exceed the reference counting 00:20:58.780 --> 00:20:59.680 deallocation? 00:20:59.860 --> 00:21:05.120 So if I had a list and I put a thousand classes, class objects in it by allocating and filling 00:21:05.120 --> 00:21:08.600 it up, then I would hold on to a thousand and none of them would have been come become garbage. 00:21:08.600 --> 00:21:12.180 So the first number that comes back is, well, how big is that number before we just run a 00:21:12.180 --> 00:21:13.440 GC no matter what? 00:21:13.440 --> 00:21:14.440 And the default is 700. 00:21:14.440 --> 00:21:19.500 So my example there, if I create a list of a thousand objects, that's a GC that's going 00:21:19.500 --> 00:21:19.780 to run. 00:21:19.920 --> 00:21:22.420 It doesn't matter if there's cycles, there's no cycles. 00:21:22.420 --> 00:21:23.520 It just doesn't matter. 00:21:23.520 --> 00:21:24.680 Like I've made a thousand of them. 00:21:24.680 --> 00:21:25.640 That's over 700. 00:21:25.640 --> 00:21:26.640 So we're going to run a GC. 00:21:26.640 --> 00:21:28.600 And then the rest are like, how much do you run? 00:21:28.600 --> 00:21:32.200 Like a whole memory GC versus a local, a small, like recent object GC. 00:21:32.380 --> 00:21:36.860 And what occurred to me is, you know, my website, there's a lot of pages that pull back thousands 00:21:36.860 --> 00:21:42.560 of items and any website that uses the database and an ORM that pulls stuff back and hangs on 00:21:42.560 --> 00:21:46.740 to it and not just like streams over the items, but puts them maybe in a list or something 00:21:46.740 --> 00:21:47.260 temporarily. 00:21:47.260 --> 00:21:51.300 Anytime you do that more with a thousand, you're going to have the GC run, right? 00:21:51.300 --> 00:21:53.640 They're just looking for anything to throw away, basically. 00:21:53.640 --> 00:21:54.020 Yeah. 00:21:54.020 --> 00:21:57.280 But you know, you're still in the process of building the list of them. 00:21:57.280 --> 00:21:59.400 I got to get 10,000. 00:21:59.400 --> 00:22:00.260 Well, guess what? 00:22:00.500 --> 00:22:04.780 That means you're going to have 14 GCs and you're just in the process of building the 00:22:04.780 --> 00:22:04.960 list. 00:22:04.960 --> 00:22:05.960 I'm like, that's kind of weird. 00:22:05.960 --> 00:22:08.060 That, that, that seems excessive to me. 00:22:08.060 --> 00:22:11.720 And then I went and looked at the site map on Talk Python training where we're pulling 00:22:11.720 --> 00:22:15.260 back like thousands of transcripts and all sorts of stuff to generate all the pages on 00:22:15.260 --> 00:22:15.420 there. 00:22:15.420 --> 00:22:16.240 77. 00:22:16.240 --> 00:22:18.640 There's 77 GCs to render the site map. 00:22:18.640 --> 00:22:19.540 There's no cycles. 00:22:19.540 --> 00:22:20.340 There's not one. 00:22:20.340 --> 00:22:21.200 So I'm like, that's not good. 00:22:21.200 --> 00:22:22.340 Well, let me think about that for a second. 00:22:22.340 --> 00:22:26.460 So what I ended up doing was I said, well, what if I made the threshold 10,000? 00:22:26.460 --> 00:22:28.100 Actually, I ended up on 50,000. 00:22:28.240 --> 00:22:33.020 So only run the GC if you get more than 50,000 allocations without deallocation. 00:22:33.020 --> 00:22:37.960 What was really interesting is doing that made my unit tests, which were including many, 00:22:37.960 --> 00:22:42.420 many integration tests on Talk Python training run 10 to 12% faster. 00:22:42.420 --> 00:22:43.920 Just setting that one line. 00:22:43.920 --> 00:22:46.860 And it basically does not use more memory in my case. 00:22:46.860 --> 00:22:47.560 Is that crazy? 00:22:47.880 --> 00:22:48.940 Well, it makes sense. 00:22:48.940 --> 00:22:56.040 Most issues of performance just come down to memory and how memory allocation is deallocation. 00:22:56.040 --> 00:23:00.200 I spend almost all my time in C++, more time in C++ than I do in Python. 00:23:00.200 --> 00:23:02.180 And we don't have a garbage collector over there. 00:23:02.180 --> 00:23:03.600 So you have to do all this manually. 00:23:03.600 --> 00:23:05.160 And doing it right. 00:23:05.160 --> 00:23:06.100 You know how much work it is, right? 00:23:06.100 --> 00:23:06.360 Yeah. 00:23:06.360 --> 00:23:07.480 Yeah, exactly. 00:23:07.480 --> 00:23:09.860 It's like doing it wrong is why stuff's slow. 00:23:09.860 --> 00:23:11.660 People are like, well, Python's slower than C++. 00:23:11.900 --> 00:23:13.900 So it has the potential. 00:23:13.900 --> 00:23:16.240 People's has the potential to be faster than Python. 00:23:16.240 --> 00:23:18.580 But it really depends on how you write that code. 00:23:18.580 --> 00:23:22.840 Because well-written code is always going to run faster than poorly written code. 00:23:22.840 --> 00:23:24.340 It doesn't matter what the two languages. 00:23:24.340 --> 00:23:24.700 Yeah. 00:23:24.700 --> 00:23:25.260 Yeah. 00:23:25.280 --> 00:23:30.780 And I realized that in my world, in my type of application, I almost never create cycles. 00:23:30.780 --> 00:23:40.640 But I often get back more than 700 class objects, which also have dictionaries potentially in the mix as they're allocating the converting, serializing into classes. 00:23:40.640 --> 00:23:42.800 There's got to be a lot of places where that's happened. 00:23:42.800 --> 00:23:44.680 So I just set this number to say, you know what? 00:23:44.680 --> 00:23:46.120 Let's waste a little bit of memory. 00:23:46.120 --> 00:23:48.380 And if there are cycles, we'll come back and get them later. 00:23:48.380 --> 00:23:51.820 And because there's almost no cycles, there's almost no memory growth. 00:23:51.900 --> 00:23:55.740 For example, so the server is running like eight worker processes, one of them. 00:23:55.740 --> 00:23:57.660 And I made this change. 00:23:57.660 --> 00:24:05.740 And I think over after running for a week without restarting any of the processes, it went from 1.89 gigs of memory usage to 1.91. 00:24:05.740 --> 00:24:07.960 So like 220 megs. 00:24:07.960 --> 00:24:09.760 I think it was 20 megs more memory usage. 00:24:09.760 --> 00:24:14.180 And yet like 10% speed up by just changing like one call at startup. 00:24:14.180 --> 00:24:14.860 It was insane. 00:24:14.860 --> 00:24:17.580 Well, and think about what Dr. Becky's code is. 00:24:17.580 --> 00:24:29.480 You know, like, you know, go back to the astrophysicist, you know, thing here, you know, with the sizes of data structures that she's doing or any data scientist who's listening, you know, they're usually dealing with 10,000, 100,000 million items. 00:24:29.480 --> 00:24:34.060 You know, you combine this with all the stuff that we talked about with NumPy and with data processing. 00:24:34.060 --> 00:24:37.680 And, you know, we talk about how long it takes to do some of these data regressions. 00:24:37.680 --> 00:24:38.720 How much would this be? 00:24:38.860 --> 00:24:39.420 Yeah, exactly. 00:24:39.420 --> 00:24:49.680 So if that data is being done in Python and it's not just purely being pushed down into the C data science layer, then yeah, that's really interesting, I think. 00:24:49.680 --> 00:24:55.200 Although I would caution at the same time that there's no such thing as a magic bullet. 00:24:55.200 --> 00:24:58.080 So you have to understand why this is going to speed things up. 00:24:58.080 --> 00:25:04.220 Well, I have to just copy and paste that line that my colleague has that he got from Michael Kennedy because it'll make the code faster. 00:25:04.320 --> 00:25:07.180 No, you have to know why it's going to go faster. 00:25:07.180 --> 00:25:08.400 It's an easy test. 00:25:08.400 --> 00:25:09.560 Some cases it makes sense. 00:25:09.560 --> 00:25:10.320 People can check it out. 00:25:10.320 --> 00:25:12.900 I thought it was really, it just so surprised me. 00:25:12.900 --> 00:25:16.380 I just walk along and I'm like, wait a minute, that must mean something weird is going on. 00:25:16.380 --> 00:25:18.480 And then I put it on just on one of my pages. 00:25:18.480 --> 00:25:21.080 Like, why would I do 77 GCs on a single page load? 00:25:21.080 --> 00:25:21.820 That's crazy. 00:25:21.820 --> 00:25:24.480 And so I just started exploring this and here we are. 00:25:24.480 --> 00:25:30.280 So did you, whatever you're linking to, does it talk about how you can test how many garbage collections? 00:25:30.280 --> 00:25:31.700 Let me see. 00:25:32.240 --> 00:25:36.840 I'm linking to a Twitter thread and way deep down. 00:25:36.840 --> 00:25:40.200 No, but there is a way to do it. 00:25:40.200 --> 00:25:44.900 If you, if you go to the GC, you can say, I think it's set debug stats or something. 00:25:44.900 --> 00:25:48.340 I'll, I'll look it up real quick while we're talking. 00:25:48.340 --> 00:25:49.420 I'll throw it in at the end here. 00:25:49.420 --> 00:25:51.700 But yeah, it's, there is a way to do it. 00:25:51.700 --> 00:25:52.980 Actually, I got it right here. 00:25:52.980 --> 00:25:53.280 Hold on. 00:25:53.280 --> 00:25:53.820 Give me just a sec. 00:25:53.820 --> 00:25:59.320 The way you do it is you say GC dot set underscore debug, and then you pass in numeration and the 00:25:59.320 --> 00:26:01.260 value is GC debug stats. 00:26:01.260 --> 00:26:01.780 Okay. 00:26:01.780 --> 00:26:05.880 So that thing was just lighting up my, you know, when I turned that on, it would just light 00:26:05.880 --> 00:26:11.140 up and just completely fill this, the terminal with the debug or, you know, GC, GC, GC, GC, 00:26:11.140 --> 00:26:15.500 GC over and over and over when I hit the, that one page and then changing it, guess what? 00:26:15.500 --> 00:26:15.960 Made it better. 00:26:15.960 --> 00:26:16.400 Yeah. 00:26:16.400 --> 00:26:20.900 Now we should probably be PC about the GC and call the garbage collector, the, the, the, 00:26:20.900 --> 00:26:23.260 the, the programmatic sanitation engineer. 00:26:23.260 --> 00:26:25.060 Right. 00:26:25.060 --> 00:26:29.360 Well, it, it, it doesn't have, it doesn't, it doesn't take offense. 00:26:29.360 --> 00:26:31.380 It's just there to help us out. 00:26:31.380 --> 00:26:34.620 Brian is probably a pretty awesome library. 00:26:34.620 --> 00:26:35.720 Honestly, the GC library. 00:26:35.720 --> 00:26:37.900 Probably, but it's built in. 00:26:37.900 --> 00:26:38.520 Yeah. 00:26:38.600 --> 00:26:44.080 So I'm, you know, of course I'm susceptible to click on a listicle, but the. 00:26:44.080 --> 00:26:45.080 Who isn't? 00:26:45.080 --> 00:26:45.440 Come on. 00:26:45.440 --> 00:26:45.840 Right. 00:26:45.840 --> 00:26:48.060 But we don't cover them very much, but I really like this. 00:26:48.060 --> 00:26:54.600 So this, this article is a top 10 Python libraries of 2020, but their criteria was interesting. 00:26:54.600 --> 00:26:58.080 The criteria was, it has to be a library that was launched or popular. 00:26:58.080 --> 00:27:03.540 It has to be well maintained as have maintenance changes since their launch date. 00:27:03.700 --> 00:27:06.980 And it has to be just outright cool that you should check it out. 00:27:06.980 --> 00:27:09.340 So I'm going to go through a handful of these. 00:27:09.340 --> 00:27:10.440 They listed 10. 00:27:10.440 --> 00:27:16.180 I don't know if all of them, since I'm, there's like four of them that are machine learning focused that I. 00:27:16.180 --> 00:27:17.820 I think cool is relative. 00:27:17.820 --> 00:27:18.580 Yeah. 00:27:18.580 --> 00:27:25.360 But the first one, I, the first one was typer and I can't, I'm like, I'm, I'm really a fan of typer now. 00:27:25.360 --> 00:27:26.760 Is it really just 2020? 00:27:26.760 --> 00:27:27.780 And I went back and look. 00:27:27.780 --> 00:27:30.820 It was released like, yeah, in December of 2019. 00:27:30.820 --> 00:27:33.140 So Sebastian Ramirez is killing it for sure. 00:27:33.140 --> 00:27:34.260 And then I looked in it. 00:27:34.260 --> 00:27:36.380 I'm like, well, FastAPI, when did that come out? 00:27:36.380 --> 00:27:37.800 Well, that was the previous December. 00:27:37.800 --> 00:27:45.140 So, the end of 2018 released FastAPI and then typer a year later, he's just crushing it. 00:27:45.140 --> 00:27:45.420 Yeah. 00:27:45.420 --> 00:27:46.460 So yeah, nice. 00:27:46.460 --> 00:27:51.240 both a huge fan of both of those, a big fan of rich also. 00:27:51.240 --> 00:27:55.060 So rich, actually just showed up this in last year in 2020. 00:27:55.060 --> 00:27:59.440 and rich is a beautiful, beautiful formatting in the terminal. 00:27:59.440 --> 00:28:03.000 And yes, it's a beautiful, it's really great. 00:28:03.080 --> 00:28:03.700 Let me use that. 00:28:03.700 --> 00:28:04.640 That's glorious. 00:28:04.640 --> 00:28:09.640 I'm even using it even in applications where I just need these, the tables. 00:28:09.820 --> 00:28:19.640 So if you need to print out a table in the command line, the tables, tables are kind of hard and there were like weird other, there were other table, specialized table libraries. 00:28:19.640 --> 00:28:23.420 but this one is great that you can, it works. 00:28:23.420 --> 00:28:27.140 You don't have to specify the width that like comes up with the width on its own. 00:28:27.200 --> 00:28:34.560 And then you, if you, you shrink the terminal to really narrow or wide, it'll word wrap correctly and stuff. 00:28:34.560 --> 00:28:37.300 and that's kind of incredible. 00:28:37.540 --> 00:28:40.540 so even if, even just for tables, I would. 00:28:40.540 --> 00:28:40.800 Yeah. 00:28:40.800 --> 00:28:41.460 Which is awesome. 00:28:41.460 --> 00:28:43.800 The third one is dear pie gooey. 00:28:43.800 --> 00:28:44.960 I think we covered this. 00:28:44.960 --> 00:28:45.560 Maybe we could. 00:28:45.560 --> 00:28:46.780 I don't remember. 00:28:46.780 --> 00:28:49.300 I mean, we did go on our gooey rant, so it feels like it should be. 00:28:49.560 --> 00:28:49.960 Yeah. 00:28:49.960 --> 00:28:51.980 So it's a, a, a gooey project. 00:28:51.980 --> 00:28:55.820 the, nice pictures though, at least. 00:28:55.820 --> 00:28:56.240 Yeah. 00:28:56.240 --> 00:28:56.680 Yeah. 00:28:56.680 --> 00:29:00.180 I've been drooling over, I've been drooling over dear I'm gooey for a while. 00:29:00.180 --> 00:29:02.840 I haven't, I haven't had an opportunity to use it yet, but I've been looking at it. 00:29:02.840 --> 00:29:03.620 So. 00:29:03.620 --> 00:29:04.300 Yeah. 00:29:04.300 --> 00:29:08.520 So, the last few I want to highlight pretty errors looks neat. 00:29:08.520 --> 00:29:12.260 I haven't tried that yet, but it's, it's a way to, yeah. 00:29:12.260 --> 00:29:13.340 That is glorious as well. 00:29:13.340 --> 00:29:14.180 Better tracebacks. 00:29:14.180 --> 00:29:15.140 so. 00:29:15.140 --> 00:29:18.940 I mean, ideally you don't show errors to people, but if you're going to, let's make them at least 00:29:18.940 --> 00:29:19.300 readable. 00:29:19.460 --> 00:29:20.060 This is great. 00:29:20.060 --> 00:29:21.820 And let's treat ourselves too. 00:29:21.820 --> 00:29:25.520 You know, it's like, you know, we're going to have to read the, we're going to spend at 00:29:25.520 --> 00:29:26.940 least half our life reading error messages. 00:29:26.940 --> 00:29:27.520 Face it. 00:29:27.520 --> 00:29:28.900 So let's at least make it readable. 00:29:28.900 --> 00:29:29.600 Yeah. 00:29:29.600 --> 00:29:32.440 And another quarter crying about the, what we just couldn't figure out. 00:29:32.440 --> 00:29:37.360 And then the last two that I want to highlight is diagrams and scaling. 00:29:37.360 --> 00:29:40.300 diagrams is a library. 00:29:40.300 --> 00:29:41.740 Look at that, picture. 00:29:41.740 --> 00:29:46.500 it's a way to do, it's intended for like, cloud architecture drawings. 00:29:46.500 --> 00:29:49.440 but the, it's written in, in Python. 00:29:49.440 --> 00:29:51.620 You, you write these diagrams in Python. 00:29:51.620 --> 00:29:57.460 and so because they're text, you can check them in and with version control. 00:29:57.460 --> 00:29:58.020 That's cool. 00:29:58.020 --> 00:29:59.040 which is nice. 00:29:59.040 --> 00:30:04.520 I'd like to see these sorts of diagrams look more would be great for not just, you 00:30:04.520 --> 00:30:06.420 know, network diagrams, other diagrams. 00:30:06.420 --> 00:30:08.040 Flow charts would be great. 00:30:08.040 --> 00:30:09.460 I still flow chart. 00:30:10.460 --> 00:30:10.900 Yeah. 00:30:10.900 --> 00:30:10.900 Yeah. 00:30:10.900 --> 00:30:10.940 Yeah. 00:30:10.940 --> 00:30:16.340 So the last one is scaling, which, is a, memory CPU and memory profiler in Python 00:30:16.340 --> 00:30:22.080 that, handles multi-threading well and distinguishes between Python versus run for use. 00:30:22.080 --> 00:30:24.220 Oh, that's, pretty cool. 00:30:24.480 --> 00:30:26.060 Like definitely need to try this out. 00:30:26.060 --> 00:30:28.660 I also like that you don't have to modify your code. 00:30:28.660 --> 00:30:29.020 Yeah. 00:30:29.020 --> 00:30:31.620 That's really cool. 00:30:31.620 --> 00:30:32.700 Yeah, absolutely. 00:30:32.700 --> 00:30:33.400 Yeah. 00:30:33.400 --> 00:30:33.840 Those are cool. 00:30:33.840 --> 00:30:35.540 there's a bunch of great ideas there. 00:30:35.540 --> 00:30:39.040 And man, I really need to find a use for rich solution. 00:30:39.040 --> 00:30:42.660 I'm going to source of a problem again, but Hey, I mean, I write a lot of like a little 00:30:42.660 --> 00:30:43.780 terminal apps and stuff. 00:30:43.780 --> 00:30:46.560 And I'm just like, you know, maybe you'll put a little color in here or something. 00:30:46.560 --> 00:30:50.040 And just, you know, I just need to take the time and go, no, this is a UI that I should 00:30:50.040 --> 00:30:50.940 pay more attention to. 00:30:50.940 --> 00:30:53.280 Not just some random thing with text. 00:30:53.280 --> 00:30:53.760 Yeah. 00:30:53.760 --> 00:30:55.200 Well, we'll find this cool stuff. 00:30:55.200 --> 00:30:58.520 It's like, I want to, I want to use, I feel the need to use this somewhere. 00:30:58.520 --> 00:31:03.540 Well, I had a little, so I had a little application where it's just like I said, with the 00:31:03.540 --> 00:31:06.720 tables and, and I'm like, I don't think it needs colors. 00:31:06.720 --> 00:31:08.040 I'm just showing a table. 00:31:08.040 --> 00:31:11.340 but the default for rich is to show colors. 00:31:11.340 --> 00:31:12.640 So, and you don't have to pick them. 00:31:12.640 --> 00:31:18.240 It just, so the, like the heading and the lines between were like different colors 00:31:18.240 --> 00:31:19.440 if you're on a color terminal. 00:31:19.440 --> 00:31:21.720 And if you're not on a color terminal, it works anyway. 00:31:21.720 --> 00:31:24.020 It just figures that out for you and lovely. 00:31:24.020 --> 00:31:24.580 Love it. 00:31:24.580 --> 00:31:24.900 Yeah. 00:31:24.900 --> 00:31:25.440 That's awesome. 00:31:25.440 --> 00:31:26.020 It's awesome. 00:31:26.020 --> 00:31:27.340 It's very awesome. 00:31:27.340 --> 00:31:27.960 Awesome. 00:31:27.960 --> 00:31:28.860 Speaking of awesome. 00:31:28.860 --> 00:31:33.720 So, PEP 518 rolled out a while back. 00:31:33.720 --> 00:31:36.560 I was introducing this thing called a pie project. 00:31:36.760 --> 00:31:40.960 T-O-M-L, I guess it's called a pie project. 00:31:40.960 --> 00:31:41.280 Toml. 00:31:41.280 --> 00:31:46.740 so the idea behind this was that it was going to be this, configuration file, you 00:31:46.740 --> 00:31:48.600 know, one configuration file to rule them all. 00:31:48.600 --> 00:31:51.220 And of course, we're, by then we like things to be simple. 00:31:51.220 --> 00:31:54.980 Well, ironically, this turned into a really political thing, which I'm still trying to 00:31:54.980 --> 00:31:55.680 wrap my head around. 00:31:55.680 --> 00:32:01.060 So basically the nice thing about this repository is, is, is, is keeping track 00:32:01.060 --> 00:32:03.700 of all the projects that have adopted pie project. 00:32:03.700 --> 00:32:07.700 Toml, either optionally or mandatory, for configurations. 00:32:07.700 --> 00:32:11.960 So instead of having to have, you know, a dozen configuration files in your project for all 00:32:11.960 --> 00:32:14.440 these different tools, you can just use this one. 00:32:14.440 --> 00:32:15.640 And so it's got this big list. 00:32:15.640 --> 00:32:18.140 What I find interesting is this part down here at the bottom. 00:32:18.140 --> 00:32:23.040 if you go down to, yeah, just scroll just slightly here, just slightly, just 00:32:23.040 --> 00:32:23.640 a little bit up. 00:32:24.020 --> 00:32:25.680 that's going to sound weird on the podcast. 00:32:25.680 --> 00:32:31.160 Anyway, so if you're going to, so these are projects that are quote unquote, discussing 00:32:31.160 --> 00:32:32.440 the use of pie project Toml. 00:32:32.440 --> 00:32:35.660 But if you actually look at these, it's kind of odd. 00:32:35.660 --> 00:32:39.960 you know, the big sticking points, cause these are the projects that are like stopping 00:32:39.960 --> 00:32:42.780 people from really just going all in on, on pie project Toml. 00:32:42.780 --> 00:32:46.300 And there's even some, you know, talk about circular, you know, dependencies or somewhere 00:32:46.300 --> 00:32:47.740 like, well, I'll do it when they do it. 00:32:47.740 --> 00:32:49.500 And they're like, well, I will do it when they do it. 00:32:49.500 --> 00:32:51.920 which makes you wonder if it's a serious excuse. 00:32:51.920 --> 00:32:53.720 so my pie is the weirdest. 00:32:54.240 --> 00:32:57.040 We'd have an awesome himself said, well, it doesn't solve anything. 00:32:57.040 --> 00:32:59.880 You know, someone said, can we just add this, please just add it. 00:32:59.880 --> 00:33:00.560 It's easy here. 00:33:00.560 --> 00:33:01.420 Here's the PR. 00:33:01.420 --> 00:33:02.240 Somebody even did the PR. 00:33:02.240 --> 00:33:04.120 He's like, nah, it doesn't solve anything. 00:33:04.120 --> 00:33:05.200 And he closed, he closed it. 00:33:05.200 --> 00:33:07.720 It's like, it does solve something. 00:33:07.720 --> 00:33:10.400 It's one less file I have to deal with. 00:33:10.400 --> 00:33:11.220 That is a solution. 00:33:11.220 --> 00:33:15.820 Blake eight, they have a couple of concrete objections. 00:33:15.820 --> 00:33:20.660 One is the fact we don't have the standard Toml parser in the Python, standard library. 00:33:20.660 --> 00:33:23.380 So that could be, you know, that could be a problem. 00:33:23.600 --> 00:33:23.680 Interesting. 00:33:23.680 --> 00:33:28.460 you're adding another dependency to just support having this format. 00:33:28.720 --> 00:33:29.120 Exactly. 00:33:29.120 --> 00:33:29.460 Yeah. 00:33:29.460 --> 00:33:33.300 but then again, it's, if it's a common dependency with a bunch of other, you know, 00:33:33.300 --> 00:33:35.340 tools that are already in use and it almost doesn't matter. 00:33:35.340 --> 00:33:38.900 pip, someone said, I don't understand this. 00:33:38.900 --> 00:33:40.200 Pip to change its behavior. 00:33:40.200 --> 00:33:42.560 So mere presence of the file doesn't change functionality. 00:33:42.560 --> 00:33:45.300 I can't wrap my head around what he's referring to there. 00:33:45.300 --> 00:33:50.220 Maybe a, but the stupid thing is someone already did flake nine, which is a, which an exact fork 00:33:50.220 --> 00:33:52.600 of flake eight that just adds high project Toml. 00:33:52.940 --> 00:33:54.940 So it's like, it's done. 00:33:54.940 --> 00:33:56.960 They just have to merge it. 00:33:56.960 --> 00:34:00.720 But it's, and actually the same thing happened with a bandit. 00:34:00.720 --> 00:34:02.800 someone actually implemented in 2019. 00:34:02.800 --> 00:34:05.120 The PR has been sitting there untouched since 2019. 00:34:05.120 --> 00:34:09.320 So over a year's gone by it's there and bandit is not picking it up. 00:34:09.320 --> 00:34:10.900 They're just, they're silent. 00:34:10.900 --> 00:34:12.840 Read the docs is saying it's too much work. 00:34:12.840 --> 00:34:18.080 like it's a lot of work for us to have the multiple, pie oxidizer shockingly hasn't 00:34:18.080 --> 00:34:18.840 even said anything. 00:34:18.840 --> 00:34:19.740 It's 2019. 00:34:19.740 --> 00:34:25.560 They're, they're like the, they're like the new trendy, like the trend setting packaging 00:34:25.560 --> 00:34:26.420 thing. 00:34:26.420 --> 00:34:29.440 And they haven't been saying anything about this. 00:34:29.440 --> 00:34:29.780 This. 00:34:29.780 --> 00:34:35.100 So I, I'm trying to figure out why it is that this is so controversial because it seems 00:34:35.100 --> 00:34:35.700 so obvious. 00:34:35.700 --> 00:34:39.340 You have one file to store all of the settings for all the different tools. 00:34:39.340 --> 00:34:43.840 and yet everybody seems to want to do their own thing with this. 00:34:43.840 --> 00:34:50.980 Well, I know that, you know, pip and poetry and flit and some of these other tools that 00:34:50.980 --> 00:34:52.260 suggest a workflow. 00:34:52.260 --> 00:34:59.120 I feel like I hear this file format being used along with those and, you know, telling people 00:34:59.120 --> 00:35:02.680 we're going to have a different way for you to like work with your projects and manage 00:35:02.680 --> 00:35:03.700 dependencies and stuff. 00:35:03.700 --> 00:35:06.980 And you know that I think that's part of the source of, of this. 00:35:06.980 --> 00:35:09.780 And I don't know if it's just necessarily all mixed together. 00:35:09.780 --> 00:35:10.580 Brian, what do you think? 00:35:10.580 --> 00:35:11.900 You know more about this than I do. 00:35:11.900 --> 00:35:18.560 I think a lot of projects are on the side of like, for instance, coverage was, 00:35:18.560 --> 00:35:21.100 was it, I don't know where they are on the list. 00:35:21.320 --> 00:35:22.060 That they adopted. 00:35:22.060 --> 00:35:22.220 Did they adopt it? 00:35:22.220 --> 00:35:23.140 Did they adopt it? 00:35:23.140 --> 00:35:23.360 Okay. 00:35:23.360 --> 00:35:23.660 Yeah. 00:35:23.660 --> 00:35:28.860 Well, coverage had this thing in, in other tools we're talking about, you know, there's 00:35:28.860 --> 00:35:32.240 no Toml parser and they, they didn't have any other dependencies. 00:35:32.240 --> 00:35:36.400 So they didn't want to add a third party dependency, just for this. 00:35:36.480 --> 00:35:41.340 And, and if they're just using it for packaging, however, or, or settings or something. 00:35:41.340 --> 00:35:45.920 But, the, so I do, I do think we will see a lot. 00:35:45.920 --> 00:35:50.380 I don't think it's a reasonable argument because, there's, there's reasons why, you know, 00:35:50.400 --> 00:35:54.000 the same thing, reason why request is, because there's making changes. 00:35:54.000 --> 00:35:59.620 But I do think that the, like the format of Toml basic format enough to get a by project, 00:35:59.620 --> 00:36:01.580 um, isn't going to change much. 00:36:01.580 --> 00:36:07.360 so I think enough of a project, Toml parser to handle by project. 00:36:07.360 --> 00:36:13.020 that's, I think we need one of the, something like that in the, in, in, in built into Python. 00:36:13.020 --> 00:36:13.260 Yeah. 00:36:13.260 --> 00:36:15.840 Especially since we have, we have PEP 5.18. 00:36:15.840 --> 00:36:18.680 So like we have some, we have some standard already. 00:36:18.680 --> 00:36:19.180 Yeah. 00:36:19.260 --> 00:36:24.740 So I think we'll see a big, I would like to see at least, even if it isn't the mainstream 00:36:24.740 --> 00:36:28.940 one, if we have, if the, if most projects that are okay with the third party use something 00:36:28.940 --> 00:36:35.160 else, for a Toml parser, but there's some built in stripped down version in the standard 00:36:35.160 --> 00:36:35.640 library. 00:36:35.640 --> 00:36:37.760 I think that that's, I think that's great. 00:36:37.760 --> 00:36:38.160 Yeah. 00:36:38.160 --> 00:36:41.300 I, I see you could solve that problem by just bendering it. 00:36:41.300 --> 00:36:43.600 Just like, here's the two files that make up the parser. 00:36:43.600 --> 00:36:46.220 We're just going to make it part of this package. 00:36:46.220 --> 00:36:47.200 So now we're good to go. 00:36:47.200 --> 00:36:47.920 I don't know. 00:36:47.920 --> 00:36:48.500 Sounds good. 00:36:48.500 --> 00:36:50.800 Well, I think that's it for all of our items. 00:36:50.800 --> 00:36:53.180 Brian, you got anything I actually want to share with folks? 00:36:53.180 --> 00:36:53.780 Yeah. 00:36:53.780 --> 00:36:55.040 I'm, it's my birthday. 00:36:55.040 --> 00:36:55.640 Yay. 00:36:55.640 --> 00:36:56.820 Happy birthday. 00:36:56.820 --> 00:36:57.960 Happy birthday, man. 00:36:57.960 --> 00:37:01.320 So I'm looking good for, I was gonna say you're looking good for 28 brother. 00:37:01.720 --> 00:37:02.620 So I'm 51. 00:37:02.620 --> 00:37:05.460 And, I heard today that that's just one. 00:37:05.460 --> 00:37:08.120 I'm just shy of a full deck. 00:37:08.120 --> 00:37:12.280 Well, yeah, I've, I've never been accused of playing with a full deck myself. 00:37:12.280 --> 00:37:17.240 but don't, I will say, don't let anyone tell you that you're old because, it says 00:37:17.240 --> 00:37:21.440 in the first chapter, chapter of Genesis, thou, and then God said, man's year shall be limited 00:37:21.440 --> 00:37:22.240 to 120. 00:37:22.480 --> 00:37:24.600 Half of 120 is 60. 00:37:24.600 --> 00:37:26.740 So what is biblical that 60 is middle age. 00:37:26.740 --> 00:37:27.720 You're not even middle aged. 00:37:27.720 --> 00:37:29.860 You've got a way to go. 00:37:29.860 --> 00:37:31.800 I mean, it's the Bible. 00:37:33.380 --> 00:37:36.420 I keep telling everybody that I don't look at day over 73. 00:37:36.420 --> 00:37:38.840 Oh, you're a good man. 00:37:38.840 --> 00:37:40.480 a couple of happy birthdays. 00:37:40.480 --> 00:37:43.040 And also you're going to ask if you're still a fan of flit. 00:37:43.040 --> 00:37:43.540 Yeah. 00:37:43.540 --> 00:37:47.700 I love flit, especially since they adopted the, source source directory. 00:37:47.700 --> 00:37:48.560 Yeah, that's right. 00:37:48.560 --> 00:37:49.020 That's awesome. 00:37:49.020 --> 00:37:50.920 that's, that's saved my life. 00:37:50.920 --> 00:37:54.900 Jason, anything extra that you want to throw out there? 00:37:54.900 --> 00:37:58.480 I mean, maybe people have a place they could get notified about your upcoming book or 00:37:58.480 --> 00:37:58.900 something like that. 00:37:58.900 --> 00:37:59.280 Yeah. 00:37:59.280 --> 00:38:02.360 You know, following me on Twitter is probably the best way to do that. 00:38:02.460 --> 00:38:03.760 I'm code mouse nine to one Twitter. 00:38:03.760 --> 00:38:07.600 and then, actually I follow no starts press too. 00:38:07.600 --> 00:38:10.360 I mean, no starts press is awesome to begin with. 00:38:10.360 --> 00:38:11.440 That's where you're doing the book. 00:38:11.440 --> 00:38:12.160 Yeah, exactly. 00:38:12.160 --> 00:38:12.580 You're there. 00:38:12.580 --> 00:38:13.300 They're my publisher. 00:38:13.300 --> 00:38:13.860 No search. 00:38:13.860 --> 00:38:16.160 I don't think they ever put out a bad book. 00:38:16.160 --> 00:38:17.580 I love that publisher. 00:38:17.580 --> 00:38:22.960 So, I was, I can, you can actually, you can ask my mother when I got, when I got, 00:38:22.960 --> 00:38:27.320 when my book contract got accepted, I actually screamed, very high pitched. 00:38:27.320 --> 00:38:28.600 That's awesome. 00:38:28.600 --> 00:38:29.460 Yeah. 00:38:29.460 --> 00:38:29.500 Yeah. 00:38:29.500 --> 00:38:32.020 Follow, follow those starts press for updates on, on that. 00:38:32.080 --> 00:38:34.780 And all their other awesome, they got some other incredible books coming up too. 00:38:34.780 --> 00:38:37.100 So I'll go ahead and ask her. 00:38:37.100 --> 00:38:38.500 So what's your mom's Twitter handle? 00:38:38.500 --> 00:38:40.260 Oh, my mom's Twitter handle. 00:38:40.260 --> 00:38:42.840 Oh, she doesn't have a Twitter handle actually. 00:38:42.840 --> 00:38:44.860 So I'll have to put you in touch directly. 00:38:44.860 --> 00:38:45.260 I think. 00:38:45.260 --> 00:38:46.720 Awesome. 00:38:46.720 --> 00:38:49.160 Well, cool. 00:38:49.160 --> 00:38:50.080 Thanks for being here again. 00:38:50.320 --> 00:38:53.060 So I have a couple of items to throw out here. 00:38:53.240 --> 00:38:56.800 This almost, Brian, this almost could have been an extra, extra, extra, extra, extra, extra, 00:38:56.800 --> 00:38:58.400 extra here all about it, but they're real short. 00:38:58.400 --> 00:38:59.320 So I didn't do that. 00:38:59.320 --> 00:39:01.700 Django 315 is released. 00:39:01.700 --> 00:39:02.380 Django 3. 00:39:02.380 --> 00:39:04.440 Didn't we just, just go to Django 2 or something? 00:39:04.440 --> 00:39:06.080 That's, I mean, that's good. 00:39:06.080 --> 00:39:07.180 That's really good to hear. 00:39:07.180 --> 00:39:08.220 So awesome. 00:39:08.220 --> 00:39:11.880 That Python 310 alpha 4 is available for testing. 00:39:11.980 --> 00:39:15.380 Yeah, the new parser is going to be in that one, which is going to be. 00:39:15.380 --> 00:39:17.580 Oh, that's the peg parser that Gita's been working on? 00:39:17.580 --> 00:39:21.400 Yeah, that's going to be, that's going to, that's going to revolutionize the language eventually. 00:39:21.400 --> 00:39:21.780 Yeah. 00:39:21.780 --> 00:39:22.260 Yeah. 00:39:22.260 --> 00:39:24.500 It'll definitely make it possible to do more. 00:39:24.500 --> 00:39:28.120 And in releases, SciPy 1.6.0 was released. 00:39:28.120 --> 00:39:29.840 I learned about a cool project. 00:39:29.840 --> 00:39:35.040 So we talked about like avoiding Excel for the Python data science stack, right? 00:39:35.040 --> 00:39:36.400 Like just stop doing Excel. 00:39:36.400 --> 00:39:37.540 There's all these weird errors. 00:39:37.780 --> 00:39:44.320 Like the organization that defines or governs how you can name genes has come up 00:39:44.320 --> 00:39:46.580 with rules for names you can't use. 00:39:46.580 --> 00:39:51.240 And the reason they can't be used is they'll be parsed incorrectly into other data types 00:39:51.240 --> 00:39:52.260 by Excel, for example. 00:39:52.260 --> 00:39:57.240 So there's a lot of issues you might run into with Excel and, and that's all good. 00:39:57.240 --> 00:40:02.700 But there's this project called PyXLL and this is actually a paid product. 00:40:02.700 --> 00:40:03.980 They're not sponsoring the show. 00:40:03.980 --> 00:40:04.940 I just think it's kind of neat. 00:40:04.940 --> 00:40:06.220 So spreading the word. 00:40:06.540 --> 00:40:10.360 But anyway, if it's interesting for you, what you can do is it's a plugin for Excel that 00:40:10.360 --> 00:40:16.680 will embed Jupyter into Excel and allow you to write functions and macros in Excel in Python. 00:40:16.680 --> 00:40:21.480 So basically it almost adds the program, Python, the programming language to Excel, which is 00:40:21.480 --> 00:40:21.860 good. 00:40:21.860 --> 00:40:22.340 Yeah. 00:40:22.340 --> 00:40:23.580 It's better than VBA. 00:40:23.580 --> 00:40:24.820 Let's see. 00:40:24.820 --> 00:40:26.000 No, I started in VBA. 00:40:26.000 --> 00:40:26.760 Tell me about it. 00:40:26.760 --> 00:40:29.340 Anything's better than VBA. 00:40:30.080 --> 00:40:36.800 So someone on Twitter asked if PyCharm works okay on my Apple Mac Mini M1. 00:40:36.800 --> 00:40:41.600 And they, PyCharm and JetBrains in general, just released a whole bunch of their tooling 00:40:41.600 --> 00:40:45.980 with different installs for the Apple Silicon native versions. 00:40:46.540 --> 00:40:50.940 And so I've got a cool little video that I'm going to link to in the show notes. 00:40:50.940 --> 00:40:52.600 And it's just like a five second video of here. 00:40:52.600 --> 00:40:58.280 I open up PyCharm and you basically from the time you click on open project till the project's 00:40:58.280 --> 00:40:59.960 open, if you've opened a project before. 00:40:59.960 --> 00:41:01.280 So that caveat. 00:41:01.280 --> 00:41:04.960 But at that point, if you click on it, you cannot perceive click. 00:41:04.960 --> 00:41:08.940 Like by the time you're letting up the mouse, the whole the project is loaded and ready to 00:41:08.940 --> 00:41:09.300 work on. 00:41:09.300 --> 00:41:10.740 It's like it's insane. 00:41:11.160 --> 00:41:15.040 I will I will consider picking up PyCharm again when they add live share into it. 00:41:15.040 --> 00:41:16.420 They have they're they're working on it. 00:41:16.420 --> 00:41:18.040 It's something called code with me. 00:41:18.040 --> 00:41:18.320 Yeah. 00:41:18.320 --> 00:41:18.620 Yeah. 00:41:18.620 --> 00:41:19.660 So I have not tried it. 00:41:19.660 --> 00:41:20.780 I have no one to code with. 00:41:20.780 --> 00:41:23.220 I'm sorry, but email me later. 00:41:23.220 --> 00:41:23.720 We'll set something. 00:41:23.720 --> 00:41:24.420 Yeah, exactly. 00:41:24.420 --> 00:41:25.820 We'll go together. 00:41:25.820 --> 00:41:32.760 So also, since I got my M1 like three, four weeks ago, whatever, I've only used used this 00:41:32.760 --> 00:41:33.900 for all my Python work. 00:41:33.900 --> 00:41:36.040 And apparently it's it's still going strong. 00:41:36.040 --> 00:41:41.040 I even had to send in my MacBook Pro because it had starting started shut. 00:41:41.040 --> 00:41:42.160 The battery was so bad. 00:41:42.160 --> 00:41:43.860 It would shut down at 75 percent. 00:41:43.860 --> 00:41:46.080 Like, you know, when it gets too low, it'll shut down. 00:41:46.080 --> 00:41:48.980 And as the battery gets bad, maybe it shuts down at 10 percent instead of zero. 00:41:48.980 --> 00:41:52.120 If I'm doing video work, it'll actually shut down at 75 percent. 00:41:52.120 --> 00:41:53.080 So I plug it back in. 00:41:53.080 --> 00:41:55.520 So so it's all in one until that comes back. 00:41:55.520 --> 00:41:57.240 Well, I'm I'm still on my system. 00:41:57.240 --> 00:41:58.280 76 Linux. 00:41:58.280 --> 00:41:59.540 I can't speak to Apple. 00:41:59.540 --> 00:42:00.540 I do love my system. 00:42:00.540 --> 00:42:02.040 That's cool. 00:42:02.040 --> 00:42:08.120 I just I think this whole like new arm architecture stuff that they're doing, it's going to be 00:42:08.120 --> 00:42:08.400 interesting. 00:42:08.400 --> 00:42:12.760 You know, I think Microsoft's following suit or trying in parallel with them. 00:42:12.760 --> 00:42:15.040 It just felt to me like Intel and AMD. 00:42:15.040 --> 00:42:16.680 That's just the way it was going to be forever. 00:42:16.680 --> 00:42:18.560 And it's not necessarily the case. 00:42:18.560 --> 00:42:21.600 I don't I don't have a problem with I don't have a problem with competition. 00:42:21.600 --> 00:42:25.880 What I have a problem with is software companies making their own, you know, architecture and 00:42:25.880 --> 00:42:27.280 it only works on their architecture. 00:42:27.280 --> 00:42:28.400 That's what you move towards. 00:42:28.400 --> 00:42:30.860 And then you wind up with a totally fragmented industry. 00:42:31.080 --> 00:42:32.860 I think that's yeah, that's not going to be great. 00:42:32.860 --> 00:42:34.240 Don't do it, Microsoft. 00:42:34.240 --> 00:42:35.140 It's not worth it. 00:42:35.140 --> 00:42:38.180 Awesome. 00:42:38.180 --> 00:42:38.500 All right. 00:42:38.500 --> 00:42:40.960 Well, that that's my extra, extra, extra, extra, extra, extra, right? 00:42:40.960 --> 00:42:41.460 Nice. 00:42:41.460 --> 00:42:43.440 I want to get an M1. 00:42:43.440 --> 00:42:44.440 I'd like to get a mini. 00:42:44.440 --> 00:42:45.840 Yeah, the mini is fantastic. 00:42:45.840 --> 00:42:47.200 I really, really like it. 00:42:47.200 --> 00:42:48.220 It's not even funny. 00:42:48.220 --> 00:42:49.600 It's not even it's not even a joke. 00:42:49.600 --> 00:42:51.640 I'm being serious, but we do need a joke. 00:42:51.640 --> 00:42:52.040 Yes. 00:42:52.040 --> 00:42:53.100 Oh, I have a joke. 00:42:53.100 --> 00:42:53.860 All right. 00:42:53.860 --> 00:42:54.060 Yeah. 00:42:54.060 --> 00:42:55.520 You got the joke this week. 00:42:55.520 --> 00:42:57.080 I actually do have the joke this week. 00:42:57.080 --> 00:42:57.280 Yeah. 00:42:57.480 --> 00:43:01.700 And it was a why, why did the programmer always refuse to check his code into the repository? 00:43:01.700 --> 00:43:02.180 Why? 00:43:02.180 --> 00:43:03.400 He was afraid to commit. 00:43:03.400 --> 00:43:06.520 Yeah. 00:43:06.520 --> 00:43:07.240 Yeah. 00:43:07.240 --> 00:43:10.620 If you want to, if you want a regular dose of my, of my, that is one of my originals. 00:43:10.620 --> 00:43:13.980 If you want a regular dose of my absolutely horrific puns, you can follow me on Twitter, 00:43:13.980 --> 00:43:14.680 your own peril. 00:43:14.680 --> 00:43:16.420 I posted every, every Monday. 00:43:16.420 --> 00:43:17.060 I've got a new one. 00:43:17.060 --> 00:43:17.720 So awesome. 00:43:17.720 --> 00:43:18.260 Nice. 00:43:18.260 --> 00:43:18.680 Yeah. 00:43:18.680 --> 00:43:19.560 Thanks for being on the show. 00:43:19.560 --> 00:43:20.300 Yeah, it was fun. 00:43:20.300 --> 00:43:20.860 Yeah. 00:43:20.940 --> 00:43:24.380 Thanks. See y'all. Thanks everyone out there on the live stream and thanks everyone who listened.