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#460: Dropbase: Build Internal Tools with Python

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WEBVTT 00:00:00.001 --> 00:00:04.060 Do you find yourself for your team building internal apps frequently for your company? 00:00:04.060 --> 00:00:06.980 Are you familiar with the term forms over data? 00:00:06.980 --> 00:00:12.260 They can be super empowering for your organization, but they can also be pretty repetitive. 00:00:12.260 --> 00:00:18.920 And you might find yourself spending more time than you like working on them rather than core products and services. 00:00:18.920 --> 00:00:27.280 I've invited Jimmy Chan from Dropbase to tell us about their services, whose tagline is build internal web apps with just Python. 00:00:27.280 --> 00:00:29.900 It's a cool service and a fun conversation. 00:00:30.480 --> 00:00:35.940 This is Talk Python To Me, episode 460, recorded March 12, 2024. 00:00:35.940 --> 00:00:37.980 Are you ready for your host? 00:00:37.980 --> 00:00:38.600 Please. 00:00:38.600 --> 00:00:42.260 You're listening to Michael Kennedy on Talk Python To Me. 00:00:42.260 --> 00:00:45.940 Live from Portland, Oregon, and this segment was made with Python. 00:00:45.940 --> 00:00:53.320 Welcome to Talk Python To Me, a weekly podcast on Python. 00:00:53.320 --> 00:00:55.060 This is your host, Michael Kennedy. 00:00:55.060 --> 00:01:02.560 Follow me on Mastodon, where I'm @mkennedy, and follow the podcast using @talkpython, both on fosstodon.org. 00:01:02.560 --> 00:01:07.640 Keep up with the show and listen to over seven years of past episodes at talkpython.fm. 00:01:08.480 --> 00:01:11.980 We've started streaming most of our episodes live on YouTube. 00:01:11.980 --> 00:01:19.520 Subscribe to our YouTube channel over at talkpython.fm/youtube to get notified about upcoming shows and be part of that episode. 00:01:20.680 --> 00:01:25.620 This episode is sponsored by Mailtrap, an email delivery platform that developers love. 00:01:25.620 --> 00:01:28.860 Try for free at mailtrap.io. 00:01:28.860 --> 00:01:32.840 And it's brought to you by us over at Talk Python Training. 00:01:32.840 --> 00:01:36.320 Did you know that we have over 250 hours of Python courses? 00:01:36.320 --> 00:01:37.260 Yeah, that's right. 00:01:37.260 --> 00:01:40.680 Check them out at talkpython.fm/courses. 00:01:42.140 --> 00:01:42.860 Hey, Jimmy. 00:01:42.860 --> 00:01:43.400 Hey, Michael. 00:01:43.400 --> 00:01:43.820 How are you doing? 00:01:43.820 --> 00:01:44.800 I'm doing well. 00:01:44.800 --> 00:01:46.620 Welcome to Talk Python To Me. 00:01:46.620 --> 00:01:47.840 It's fantastic to have you here. 00:01:47.840 --> 00:01:48.240 Thank you. 00:01:48.240 --> 00:01:48.700 I'm really excited. 00:01:48.700 --> 00:01:49.660 Yeah, I am too. 00:01:49.660 --> 00:01:51.040 I saw DropBase. 00:01:51.040 --> 00:01:51.920 I saw what you all were building. 00:01:51.920 --> 00:01:54.440 I'm like, that is pretty darn interesting. 00:01:54.440 --> 00:01:56.540 I think people will want to check it out. 00:01:56.540 --> 00:02:03.040 So we'll dive into this app and this platform that you made for app building, basically. 00:02:03.040 --> 00:02:04.060 We'll have a lot of fun. 00:02:04.060 --> 00:02:08.280 Now, before we get into that, though, just give us a quick bit of background on yourself. 00:02:08.280 --> 00:02:09.440 How'd you get into programming? 00:02:09.600 --> 00:02:13.020 How'd you find yourself writing a Python building platform? 00:02:13.020 --> 00:02:13.440 Awesome. 00:02:13.440 --> 00:02:15.060 Yeah, I went to school for engineering. 00:02:15.060 --> 00:02:17.100 This was actually back in Canada. 00:02:17.100 --> 00:02:20.360 I studied in Montreal at a little school called McGill University. 00:02:20.360 --> 00:02:20.720 Nice. 00:02:20.720 --> 00:02:21.540 We started then. 00:02:21.540 --> 00:02:26.000 I used to intern, by the way, at this company called Research in Motion that used to make 00:02:26.000 --> 00:02:27.780 BlackBerrys way back in the time. 00:02:27.780 --> 00:02:28.680 Oh, yeah. 00:02:28.680 --> 00:02:29.420 Awesome. 00:02:29.420 --> 00:02:30.660 In the heyday? 00:02:30.660 --> 00:02:31.480 In the heyday. 00:02:31.480 --> 00:02:36.960 I remember when they said we had 50% of the US smartphone market share. 00:02:36.960 --> 00:02:38.900 But the platform was actually built on Java. 00:02:39.260 --> 00:02:39.720 No, Python. 00:02:39.720 --> 00:02:41.420 Python was something afterwards. 00:02:41.420 --> 00:02:44.940 Actually, my co-founder is the Python programmer. 00:02:44.940 --> 00:02:47.360 And I picked up Python after we started working together. 00:02:47.360 --> 00:02:47.640 Cool. 00:02:47.640 --> 00:02:50.100 You got any fun stories from your time at BlackBerry? 00:02:50.100 --> 00:02:50.920 Did you enjoy it? 00:02:50.920 --> 00:02:51.480 How long were you there? 00:02:51.640 --> 00:02:52.840 I was there as an intern only. 00:02:52.840 --> 00:02:56.780 Spent about 16 to 20 months of internships. 00:02:56.780 --> 00:02:57.220 Yeah. 00:02:57.220 --> 00:02:59.320 At the time, I was, I think, in my third year of school. 00:02:59.320 --> 00:03:05.360 And we were just working on these little Java apps for the smartphones and just making sure 00:03:05.360 --> 00:03:06.540 everything was working. 00:03:06.540 --> 00:03:12.720 The cool thing is when you work at a company that's making devices, devices have a very long 00:03:12.720 --> 00:03:14.000 development cycle. 00:03:14.000 --> 00:03:16.380 So imagine, for example, you worked at Apple today. 00:03:16.380 --> 00:03:20.060 Like the iPhone, what, 15, whichever one's coming next. 00:03:20.060 --> 00:03:23.020 Like they've been working on it for at least a year, probably longer. 00:03:23.020 --> 00:03:26.860 Do you get access to all these prototypes that you get to use? 00:03:26.860 --> 00:03:28.740 Because like you're building for it, you're testing it. 00:03:28.740 --> 00:03:30.840 That was a really nice, nice, nice thing. 00:03:30.840 --> 00:03:32.540 But you actually couldn't tell anybody about it. 00:03:32.540 --> 00:03:35.000 But it was really cool
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to know that you're on the last thing. 00:03:35.000 --> 00:03:38.140 And you couldn't lose it in a bar or anything like that, right? 00:03:38.140 --> 00:03:39.680 You remember those stories, right? 00:03:39.680 --> 00:03:40.800 Yes, exactly. 00:03:40.800 --> 00:03:41.640 A few times. 00:03:41.640 --> 00:03:46.280 Somebody got a hold of a lost phone and it was sold and there was all sorts of drama. 00:03:46.280 --> 00:03:46.980 It was a big deal. 00:03:46.980 --> 00:03:51.760 That was around an iPhone 4, 3, 4, 5 sort of time frame. 00:03:51.760 --> 00:03:53.520 Yeah, I remember that very clearly. 00:03:53.520 --> 00:03:53.860 Yeah. 00:03:53.860 --> 00:03:55.420 So you didn't want to be that. 00:03:55.500 --> 00:03:57.060 You wanted to make sure you hung on to it. 00:03:57.060 --> 00:03:57.440 Oh, yeah. 00:03:57.440 --> 00:03:57.680 No. 00:03:57.680 --> 00:04:02.360 Yeah, I think working for a company like that would have been awesome, at least in the heyday. 00:04:02.360 --> 00:04:09.380 It's cool to work for a tech company that's got a lot of wind that it's back and a lot of people using it. 00:04:09.380 --> 00:04:10.400 It's kind of neat. 00:04:10.400 --> 00:04:11.000 I was very happy. 00:04:11.000 --> 00:04:14.300 We had a lot of other interns that they hired at the time. 00:04:14.300 --> 00:04:17.020 So you just had a blast to work in there over the summer. 00:04:17.020 --> 00:04:19.200 Yeah, a lot of excited people to do stuff. 00:04:19.200 --> 00:04:19.880 Excellent. 00:04:19.880 --> 00:04:20.520 Cool. 00:04:20.520 --> 00:04:24.560 And so then you picked up Python, I guess, when you started this project. 00:04:24.560 --> 00:04:25.000 Is that right? 00:04:25.080 --> 00:04:26.020 Just a little bit before. 00:04:26.020 --> 00:04:30.100 So when we started our startup, this was back in 2020. 00:04:30.100 --> 00:04:32.980 My co-founder had been using Python. 00:04:32.980 --> 00:04:38.260 He did a master's degree, computer science, focused on machine learning, actually. 00:04:38.260 --> 00:04:42.320 In that field, Python is really the main language you use. 00:04:42.320 --> 00:04:42.800 Yeah, it is. 00:04:42.900 --> 00:04:44.460 And so he was very familiar with it. 00:04:44.460 --> 00:04:49.200 And so he set our stack, basically, to be a Python backend. 00:04:49.580 --> 00:04:56.540 And then just through that process, just looking at things and designing features, we just all got involved with Python. 00:04:56.540 --> 00:04:58.140 So it kind of just became the same. 00:04:58.480 --> 00:05:04.480 And this is actually the reason why we're working on a Python builder is we're kind of building a product for ourselves. 00:05:04.480 --> 00:05:08.720 It's something where it fits our own needs, that works with our mental models. 00:05:09.120 --> 00:05:10.660 So that's pretty much it. 00:05:10.660 --> 00:05:16.140 So today, I spent a lot of time building apps with DropBase, so internal tools. 00:05:16.140 --> 00:05:18.720 And that's most of the app building
I do now. 00:05:18.720 --> 00:05:22.880 So building demos, testing the product, making sure everything is working. 00:05:23.280 --> 00:05:27.300 And then just finding other ways to make the developer experience more convenient. 00:05:27.300 --> 00:05:32.980 It seems like something you could really take care of a bunch of internal automation type of apps. 00:05:32.980 --> 00:05:40.580 You don't have to create full-on web apps to secretize this data or get that dashboard or whatever, right? 00:05:40.580 --> 00:05:43.420 You just fire up your own platform and win at your data sources. 00:05:43.420 --> 00:05:44.380 That's right, yeah. 00:05:44.380 --> 00:05:51.380 So the big difference with other frameworks is that you're going to use these frameworks to build your customer-facing applications. 00:05:52.000 --> 00:05:56.440 And customers, they have expectations about what they need. 00:05:56.440 --> 00:05:59.740 Interactions sometimes make a big difference for them. 00:05:59.740 --> 00:06:03.180 UI components, the way models come up. 00:06:03.180 --> 00:06:04.740 It's all part of the experience. 00:06:04.740 --> 00:06:09.100 And so for that, you really need a lot of extra components complexity. 00:06:09.100 --> 00:06:14.140 For internal tools, it's not to say that internal users don't have high expectations. 00:06:14.140 --> 00:06:19.220 But the kinds of things that you do with those tools tend to be very, very similar. 00:06:19.220 --> 00:06:20.580 You search for data. 00:06:21.020 --> 00:06:23.960 You get context about that. 00:06:23.960 --> 00:06:26.500 So for example, you search for a transaction or for a user. 00:06:26.500 --> 00:06:30.980 You get some more context to make sure that that's the user or the transaction that you want to act on. 00:06:30.980 --> 00:06:32.340 And then you just act on it, right? 00:06:32.340 --> 00:06:37.200 Like you trigger an action on that item or that resource or that person. 00:06:37.200 --> 00:06:39.460 It helps you simplify the kind of things you need. 00:06:39.460 --> 00:06:44.560 And so for that, having a framework, a builder to make this happen is super convenient. 00:06:45.260 --> 00:06:50.880 This is a little bit of a tool. 00:06:50.880 --> 00:07:01.940 And when I think of internal web apps or even traditionally, if you look back a ways, there was VB6 and Windows Forms and those types of things that were kind of playing the same role. 00:07:02.340 --> 00:07:03.880 So same basic idea. 00:07:03.880 --> 00:07:08.520 There was a lot of people who referred to that as forms over data. 00:07:08.720 --> 00:07:16.280 It kind of the not quite a negative term, but kind of like we're sort of doing the same basic architecture over and over. 00:07:16.400 --> 00:07:18.120 But it's a different problem every time. 00:07:18.120 --> 00:07:22.420 And so we kind of got to write code, create these projects from scratch every time. 00:07:22.420 --> 00:07:25.020 But they're the kind of same kind of thing. 00:07:25.020 --> 00:07:36.700 And so, you know, I think that's probably why VB6 with its kind of visual drag and droppy experience became real popular because you could drag a table on there and drag a data source, bind it to that and make a button click when somebody touches this thing. 00:07:36.700 --> 00:07:45.580 And that didn't create something that would rival, say, Airbnb.com or, you know, these really dynamic design sites. 00:07:45.960 --> 00:07:47.200 But that's not what they need. 00:07:47.200 --> 00:07:50.820 The company says, look, we need this week. 00:07:50.820 --> 00:07:55.180 I need our salespeople to be able to answer this question and make this change. 00:07:55.180 --> 00:07:57.120 That's what we need you to build this week. 00:07:57.120 --> 00:08:00.780 And if it's from scratch every time, that's a ton of rework. 00:08:00.780 --> 00:08:01.920 It's a lot of work. 00:08:01.920 --> 00:08:04.300 It's funny you mentioned the forms over data. 00:08:04.300 --> 00:08:10.960 It is true that a lot of the, well, if you take it at a very high level, all apps are forms over data. 00:08:10.960 --> 00:08:12.400 In some sense, yeah. 00:08:12.520 --> 00:08:17.680 All SaaS apps are forms over a database in some sense. 00:08:17.680 --> 00:08:25.160 And then you start to hear also about the similar things with, you've heard about the GPT wrappers, right? 00:08:25.460 --> 00:08:30.140 It's the same concept where it's like an oversimplification of what's happening. 00:08:30.140 --> 00:08:32.720 But at the same time, it is kind of core to what's happening. 00:08:32.720 --> 00:08:36.460 And for internal tooling, at least, is exactly what you need. 00:08:36.460 --> 00:08:38.400 Forms over data, but very quickly. 00:08:38.620 --> 00:08:44.280 So that developers don't have to spend a lot of time basically doing the same things over and over again. 00:08:44.280 --> 00:08:48.460 You want to make their lives easier to support their internal users. 00:08:48.460 --> 00:08:51.060 So people in customer support, operations. 00:08:51.060 --> 00:08:54.540 And I think sometimes even supporting other engineers as well. 00:08:54.540 --> 00:08:54.720 Yeah. 00:08:54.720 --> 00:09:00.740 And it's not that people in companies don't have expectations of nice apps and nice interactions. 00:09:01.060 --> 00:09:02.880 It's just that it's more utilitarian. 00:09:02.880 --> 00:09:11.800 Like so many of these big enterprises, when you kind of think of them, maybe the right way to think of them is there's a massive Postgres or Microsoft SQL server at the center. 00:09:11.800 --> 00:09:20.980 And like it almost connects the business divisions, like the sales team and the marketing team and the product team and all that. 00:09:20.980 --> 00:09:33.500 And if you can get into the database and answer questions, expose data, expose relationships, put a UI to some aspect of that, you're really right at the heart of the company in some sense, you know? 00:09:33.500 --> 00:09:35.580 Yeah, it's definitely
about effectiveness. 00:09:36.140 --> 00:09:51.000 One way we think about what these kinds of tools should do, you have to enable developers to very quickly build apps that have maximal value, that lets you get the job done as effectively as possible. 00:09:51.000 --> 00:09:54.440 But also that's easy to use for the end users. 00:09:54.440 --> 00:10:01.480 So, you know, if it's like a business operator or someone in the operations team, they also need to be able to learn quickly how to use it and trigger actions. 00:10:01.960 --> 00:10:07.740 And so we call that sort of effectiveness of the apps, some sort of like effectiveness score. 00:10:07.740 --> 00:10:08.040 Yeah. 00:10:08.040 --> 00:10:09.400 It just combines these components. 00:10:09.400 --> 00:10:19.520 And that's really the, like, if you can get to the essence of it and create a framework or a tool builder that maximizes for that, I think you're in a really good place. 00:10:19.520 --> 00:10:22.080 And this is something we're trying to do with DropBase. 00:10:22.080 --> 00:10:23.780 The components are simple. 00:10:24.240 --> 00:10:29.140 The kinds of apps that you can build look roughly the same, but they look really nice. 00:10:29.140 --> 00:10:31.660 And they're also quite simple to understand. 00:10:31.660 --> 00:10:39.680 They're modeled after, but it's in a way where you have data, a greater table in the middle, and then there's a sidebar from where you can trigger actions. 00:10:40.180 --> 00:10:55.600 And this ties back to this concept of when you ask people in operations what they do, like sales, marketing, business operations, essentially it ties back to the previous comments, which was you search for something, you get context about it, and you trigger action. 00:10:55.600 --> 00:11:03.640 And so the way we translated that insight about what people just end up doing over and over again, we said, well, then you really just need some sort of search bar. 00:11:03.640 --> 00:11:11.020 You need a grid and you need a sidebar with some buttons or some other drop downs and other components. 00:11:11.020 --> 00:11:15.160 And then you realize, okay, this is kind of what spreadsheets I've been trying to do for a long time. 00:11:15.160 --> 00:11:15.760 Yeah, that's true. 00:11:15.760 --> 00:11:17.560 Except we like to trigger actions. 00:11:17.560 --> 00:11:17.940 Yeah. 00:11:17.940 --> 00:11:22.900 People do oddly connect Excel to, like, external data sources and all sorts of weird things as well. 00:11:22.900 --> 00:11:23.300 Yeah. 00:11:23.300 --> 00:11:25.660 Or write VBA that makes some change. 00:11:25.660 --> 00:11:27.300 They probably should just not be doing that. 00:11:27.300 --> 00:11:27.540 Yeah. 00:11:27.540 --> 00:11:29.520 There's a lot of, it's actually a big use case. 00:11:29.520 --> 00:11:32.480 One of our previous product, we actually did exactly that. 00:11:32.480 --> 00:11:32.740 Okay. 00:11:32.740 --> 00:11:39.440 We let you connect any database source to your Google Sheets and just kind of run that on a schedule. 00:11:39.440 --> 00:11:48.380 So you'd imagine in a business setting, you have sort of these, like, weekly, daily reports that analysts end up working on, right? 00:11:48.380 --> 00:11:52.640 And what you want is for the data to be fresh, up to date. 00:11:52.640 --> 00:12:02.320 And so people just wanted a way to, on, at 7 a.m., 8 a.m. on Monday morning, basically automatically pull data from a database, load it up to your spreadsheet. 00:12:02.320 --> 00:12:11.120 And then all your tables and calculations, which is sort of updated because they're referencing a tab, a sheet, basically, that has fresh data. 00:12:11.120 --> 00:12:13.620 It's very interesting, the evolution of all these tools. 00:12:13.620 --> 00:12:14.380 It is really interesting. 00:12:14.380 --> 00:12:21.480 Maybe one of the big differences is the interactivity here versus what you might do in that story, right? 00:12:21.560 --> 00:12:22.920 That's read-only, really. 00:12:22.920 --> 00:12:29.420 And then here, what we're doing is letting you trigger actions, perform actions, basically outside the app. 00:12:29.420 --> 00:12:35.540 So you might call an API or you might trigger an internal endpoint or just trigger some action in the UI. 00:12:37.240 --> 00:12:44.140 This portion of Talk Python To Me is brought to you by Mailtrap, an email delivery platform that developers love. 00:12:44.140 --> 00:12:55.580 An email sending solution with industry-best analytics, SMTP, and email API SDKs for major programming languages and 24-7 human support. 00:12:55.580 --> 00:12:58.540 Try for free at mailtrap.io. 00:12:59.920 --> 00:13:04.360 I think we'll get to this more later, but I want to maybe touch on it since there's a good question. 00:13:04.360 --> 00:13:06.620 Also, it might be a question a lot of people have. 00:13:06.620 --> 00:13:08.860 So what's the pricing model for this? 00:13:08.860 --> 00:13:13.020 And basically, more broadly, what is the business model around here? 00:13:13.020 --> 00:13:18.080 Luis says, already amazed by it, would like to compare it. 00:13:18.080 --> 00:13:20.980 First thought, there's nothing like this available in open source. 00:13:20.980 --> 00:13:22.180 So very neat. 00:13:22.180 --> 00:13:29.120 The business model is we're going to sell the product on a per-user, per-month basis. 00:13:29.220 --> 00:13:31.000 So it's a B2B SaaS app product. 00:13:31.000 --> 00:13:38.320 Now, developers need to be able to play around with products before they can decide whether that's something they want. 00:13:38.320 --> 00:13:48.520 And so we have a free version of the products that you can set up locally, like in your own machine, or you can just put it up on EC2. 00:13:48.520 --> 00:13:50.620 And you can just build apps for yourself. 00:13:50.620 --> 00:13:54.700 If you want to automate personal tasks, you can totally use this for it. 00:13:55.000 --> 00:14:10.460 And then the way that we, in a way, layer
the pricing is like, if you need very complex permission systems, so like you build an app and you want it accessible by this person, by person A, but not person B, then you'll need very granular permission systems. 00:14:10.460 --> 00:14:15.040 And so that's an indicator that you're probably like a corporate user, you're a business user. 00:14:15.040 --> 00:14:17.560 And so we do the pricing based on that. 00:14:17.560 --> 00:14:19.680 The source is open, at least. 00:14:19.680 --> 00:14:21.260 People can go and check it out, right? 00:14:21.260 --> 00:14:21.980 Is that true? 00:14:21.980 --> 00:14:22.900 Let me clarify that. 00:14:22.900 --> 00:14:24.300 So you can self-host it. 00:14:24.300 --> 00:14:24.600 Yes. 00:14:24.760 --> 00:14:26.540 You know, you can look at the repo. 00:14:26.540 --> 00:14:30.620 Behind the scenes, it's a Docker image that you set. 00:14:30.620 --> 00:14:41.160 So the code for draw base is not immediately, you know, you can't just browse it through the file system, but the code is basically sitting in your machine when you set this up locally. 00:14:41.160 --> 00:14:45.920 Now, the difference here is if you look at the directory where you have the workspace. 00:14:45.920 --> 00:14:52.580 So the workspace directory is where all your apps files would be generated as you build the apps. 00:14:53.240 --> 00:14:58.220 That's really nice because you can essentially version control this from day one. 00:14:58.220 --> 00:14:59.260 You can build apps. 00:14:59.260 --> 00:15:01.000 You can check it in GitHub. 00:15:01.000 --> 00:15:02.320 You can just keep your code. 00:15:02.320 --> 00:15:03.040 You can version it. 00:15:03.040 --> 00:15:05.520 And so it's really, it's not open source. 00:15:05.520 --> 00:15:08.020 It's clarified that, but you can self-host it. 00:15:08.020 --> 00:15:16.160 It's on GitHub, but the licensing is really not like just straight up GPL open source type of thing, right? 00:15:16.160 --> 00:15:16.720 That's correct. 00:15:16.720 --> 00:15:17.120 Yes. 00:15:17.120 --> 00:15:17.460 Okay. 00:15:17.460 --> 00:15:22.820 And it's on GitHub because you need to, you do need to clone the repo and then you need to send it out and install it. 00:15:22.920 --> 00:15:29.540 The free tier doesn't allow self-hosting, but if you pay for one of the versions, then it does have a self-hosting option. 00:15:29.540 --> 00:15:40.000 So when you, just to wrap this up on the price, when you say it's $10 per user per month, is that per person that makes the project, that builds the apps? 00:15:40.000 --> 00:15:43.220 Or is that per person that interacts with the web app? 00:15:43.440 --> 00:15:46.140 This is currently per member of your workspace. 00:15:46.140 --> 00:15:51.340 So we're not yet differentiating between someone who is building the app or using the app. 00:15:51.340 --> 00:15:54.540 Although that might be something that we'll have to add later on. 00:15:54.540 --> 00:15:54.760 Sure. 00:15:54.860 --> 00:16:03.240
So if you had say four salespeople and one developer in quotes, maybe developer, that would be five users under this story. 00:16:03.240 --> 00:16:03.560 Correct. 00:16:03.560 --> 00:16:04.940 Under the current pricing, yes. 00:16:04.940 --> 00:16:05.220 Okay. 00:16:05.440 --> 00:16:08.520 You know, even if it's not just pure open source, take it and run with it. 00:16:08.520 --> 00:16:22.720 I do like the self-hosting aspect of it because if you've got private data or maybe even more important than any of that is I want to connect it to data sources that are, I don't want to give your cloud access to my company database, for example. 00:16:22.720 --> 00:16:23.860 I can expand on that, actually. 00:16:23.860 --> 00:16:29.520 So we built this specifically with that comment in mind. 00:16:29.520 --> 00:16:41.180 So when you're using internal tools, it's very, well, let's say it's almost all the cases you are interacting with production, at least one production database, right? 00:16:41.180 --> 00:16:48.040 Like if you're supporting customers and you're issuing them a refund, you don't do that in tests and then take it to staging and then deploy it, right? 00:16:48.040 --> 00:16:51.680 You basically, you act on it on your production data. 00:16:51.680 --> 00:17:06.180 And so we thought, okay, people are probably going to be very hesitant to basically say, let me load up all my creds, all my API keys into some new player, new cloud, and then like hope for the best, right? 00:17:06.180 --> 00:17:11.600 So when we designed DropBase, we call it the worker or the worker's server. 00:17:11.600 --> 00:17:19.620 The way you connect to data sources is you basically go to your .env file and you just add your database creds. 00:17:20.020 --> 00:17:27.520 And that .env file sits in the same directory that that workspace directory sits, the one that we saw on GitHub. 00:17:27.520 --> 00:17:30.220 And that's completely on your side. 00:17:30.220 --> 00:17:32.720 And that's in your VPC or in your local machine. 00:17:32.720 --> 00:17:39.240 And the same server is the one that triggers the task to query your database. 00:17:39.240 --> 00:17:43.140 So, and that's also sitting on your side in your machine. 00:17:43.140 --> 00:17:54.680 And so the entire part of the product that processes, queries, touches your data, your data sources, your credentials, that's completely on the user side. 00:17:54.680 --> 00:17:59.520 And the only part that we manage is really just the permission system. 00:17:59.520 --> 00:18:04.180 So that controlling the workspace and controlling the like the app permissions. 00:18:04.180 --> 00:18:06.680 That's the layer that we control. 00:18:06.680 --> 00:18:10.720 And that's really like the part where we can do the pricing on to begin with. 00:18:10.720 --> 00:18:15.180 Like that's the, that's the feature set thing that helps us say, okay, this is going to be paid customers. 00:18:15.180 --> 00:18:18.940 And these are going to be developers who
are just going to learn how to code in Python. 00:18:18.940 --> 00:18:22.480 They just want to build little apps for their own personal use. 00:18:22.480 --> 00:18:22.780 All right. 00:18:22.780 --> 00:18:23.240 That makes sense. 00:18:23.240 --> 00:18:27.040 You know, let's maybe talk through an example. 00:18:27.040 --> 00:18:35.020 If you go to dropbase.io, there's a, right at the top, there's a sort of tutorial or a demo video of you using it. 00:18:35.020 --> 00:18:42.380 Obviously, I don't want to just play the video, but maybe just talk us through the steps of what this app is and what are the steps to build it. 00:18:42.380 --> 00:18:49.420 And just for people who are listening, haven't watched that video, maybe I think it's 12 minutes long and you're like, let's create a new project. 00:18:49.760 --> 00:18:52.160 And here it is published at the end, right? 00:18:52.160 --> 00:18:52.920 Which is really nice. 00:18:52.920 --> 00:18:53.720 So yeah, talk us through. 00:18:53.720 --> 00:18:58.100 I'm going to try to recreate the exact same one that's, that you have on the, on the screen, right? 00:18:58.100 --> 00:19:04.880 So it looks like an app that has two tables and you can somehow perform an action with up on the sidebar. 00:19:04.880 --> 00:19:11.060 Basically, it just notifies, either notifies a user or it performs some sort of permissions. 00:19:11.060 --> 00:19:18.460 I think what this one does is it has a workspaces and then users are in a workspace and you can make them admins or not admins of that workspace. 00:19:18.620 --> 00:19:19.400 Gotcha. 00:19:19.400 --> 00:19:19.840 Perfect. 00:19:19.840 --> 00:19:20.340 Okay. 00:19:20.340 --> 00:19:21.260 Okay. 00:19:21.260 --> 00:19:22.980 So I'll describe how you build this app. 00:19:22.980 --> 00:19:26.280 So you go to our app studio and it's going to be a blank canvas. 00:19:26.280 --> 00:19:29.120 In that canvas, you can add tables. 00:19:29.120 --> 00:19:36.560 So the first thing you do is you add table one, you add the first table, and then you add table two, which is the second table. 00:19:36.960 --> 00:19:39.460 And then you add a widget on the sidebar. 00:19:39.460 --> 00:19:44.340 You just click on add button and then it just places a button on the screen for you. 00:19:44.340 --> 00:19:46.460 That will be sort of a shell of the application. 00:19:46.460 --> 00:19:48.700 It'll be just the UI part. 00:19:48.700 --> 00:19:50.980 At this point, it's just a few mouse clicks. 00:19:50.980 --> 00:19:54.080 There's no JavaScript code or Python code that you're writing. 00:19:54.340 --> 00:19:57.960 The next step is to add the sort of the logic behind the scenes. 00:19:57.960 --> 00:20:03.580 The first thing we need to do is to populate the first table with data about your workspaces. 00:20:03.580 --> 00:20:08.920 And essentially what we do is you click on create new, you create a new function. 00:20:09.340 --> 00:20:12.740 And in that function, it could be a SQL function or a Python function. 00:20:12.740 --> 00:20:16.780 Because that's just a table, you can just create a new SQL function. 00:20:16.780 --> 00:20:21.920 So you do create a new function, select everything from workspaces, let's say that's the table. 00:20:21.920 --> 00:20:26.600 And then you can see a little preview of what that select statement will result in. 00:20:26.600 --> 00:20:29.120 So you can verify that that's the data that you want to show. 00:20:29.120 --> 00:20:34.760 Once you've done that, you just save that file, that query, and you do something we call binding. 00:20:34.760 --> 00:20:40.120 So in the UI, you can select table one, and it'll present you with the table's properties. 00:20:40.120 --> 00:20:46.080 And one of the properties is which SQL file, which SQL script it's bound to. 00:20:46.080 --> 00:20:51.040 So you just click bind to the SQL file that you just wrote, and then it just automatically 00:20:51.040 --> 00:20:53.720 populates it with data for your workspace. 00:20:53.720 --> 00:20:59.680 Now, the second table is a little bit more interesting because the second table will update 00:20:59.680 --> 00:21:02.620 depending on what row you've selected in the first table. 00:21:02.620 --> 00:21:07.200 When you click on a workspace in the first table, it should load all of the users that 00:21:07.200 --> 00:21:08.940 are part of a particular workspace. 00:21:08.940 --> 00:21:14.660 And so we do this, we have a feature called dependent tables, and that's exactly what it 00:21:14.660 --> 00:21:14.820 does. 00:21:14.820 --> 00:21:19.160 So for the second table, you would still write a SQL query, and the query would just say, 00:21:19.160 --> 00:21:27.620 select everything from users where the workspace ID is the selected row workspace ID from the 00:21:27.620 --> 00:21:28.140 first table. 00:21:28.140 --> 00:21:32.380 And we used to sort of a Jinja, I'm not sure, maybe the audience will be familiar with Jinja, 00:21:32.380 --> 00:21:37.640 it's sort of like Jinja templating style where you say, select everything from users where 00:21:37.640 --> 00:21:41.520 workspace ID is double curly brace. 00:21:41.520 --> 00:21:43.720 And then we have something called state. 00:21:43.720 --> 00:21:48.520 State basically gives you the state of the UI at any point in time when you've clicked something. 00:21:48.520 --> 00:21:50.880 And it's really, we made it into a class. 00:21:50.880 --> 00:21:56.020 So you can say state.tables.table1.workspaceID. 00:21:56.240 --> 00:22:01.720 We resolve that into the value that's the workspace ID from the first table. 00:22:01.720 --> 00:22:03.620 And so that's, and then you do the same thing. 00:22:03.620 --> 00:22:07.060 You save that SQL query, you bind it to the second table. 00:22:07.060 --> 00:22:12.340 And then we automatically infer that whenever you need, whenever you select a different row 00:22:12.340 --> 00:22:17.960 in the first table, the second table will update the workspace ID value, rerun the
query, 00:22:17.960 --> 00:22:19.420 and then show you the data for it. 00:22:19.500 --> 00:22:19.740 That's cool. 00:22:19.740 --> 00:22:21.100 I was wondering how that happened. 00:22:21.100 --> 00:22:26.080 I thought you must have to wire some on change event, clicks over here, then it triggers that. 00:22:26.080 --> 00:22:27.720 But you just have that all automatic, right? 00:22:27.720 --> 00:22:31.360 The UI actually knows that which tables are related. 00:22:31.360 --> 00:22:37.780 The UI sends a payload to the backend saying, this table was clicked and this other table is related 00:22:37.780 --> 00:22:38.180 to it. 00:22:38.180 --> 00:22:41.700 And so we kind of know that we need to process those again. 00:22:42.040 --> 00:22:49.060 And so that's how we do this dependent table for the getting the value of the workspace ID in the 00:22:49.060 --> 00:22:49.700 first table. 00:22:49.700 --> 00:22:56.560 We basically, we resolve the sort of the variables in the backend and then pass the value so that 00:22:56.560 --> 00:22:57.680 we can update the query. 00:22:57.680 --> 00:23:00.160 So let's say that you stop at that point, right? 00:23:00.160 --> 00:23:01.960 And then you say preview the app. 00:23:01.960 --> 00:23:07.860 The app would look like two tables where it's really just lets you see all the users for each 00:23:07.860 --> 00:23:10.860 workspace that you have in your database. 00:23:10.860 --> 00:23:16.440 And then a few more things to make that very useful is you might want to search for a workspace 00:23:16.440 --> 00:23:18.740 before you know who to support. 00:23:18.740 --> 00:23:22.260 So let's say each workspace is associated with one of your customers. 00:23:22.260 --> 00:23:27.180 So let's say company A is your customer and company A gives you a call, a support call and 00:23:27.180 --> 00:23:31.160 says, hey, can you make John in our company an admin? 00:23:31.160 --> 00:23:35.180 So the first thing you want to do is you want to find, you search for company A and 00:23:35.180 --> 00:23:35.920 then find John. 00:23:35.920 --> 00:23:40.520 So we have this nice feature that basically automatically creates searches for you. 00:23:40.520 --> 00:23:46.080 So let's say in the first table, you can click on a button to convert it to a smart table. 00:23:46.080 --> 00:23:50.700 And when you do that, we basically generate filters for you. 00:23:50.700 --> 00:23:56.360 So you can then just say, I'd like to search by company name and you can select the filter 00:23:56.360 --> 00:23:58.760 and you can pin the filter into the table. 00:23:58.760 --> 00:24:01.600 And that automatically performs the search for you. 00:24:01.600 --> 00:24:03.280 So it's just pretty neat that way. 00:24:03.440 --> 00:24:05.780 It reminds me a little bit of Notion, Notion tables. 00:24:05.780 --> 00:24:07.180 I don't know if you play with Notion any. 00:24:07.180 --> 00:24:07.620 Yes. 00:24:07.620 --> 00:24:11.560 You know, you have got those pinned swords and
those pinned filters and different things 00:24:11.560 --> 00:24:14.840 you can kind of put at the top of the, I guess their databases are called in Notion. 00:24:14.840 --> 00:24:16.080 A little like that. 00:24:16.160 --> 00:24:21.640 It's very similar to that in the sense that you're not writing any code to be able to search 00:24:21.640 --> 00:24:26.760 through tables, but you can still modify what you let people search by pinning certain filters. 00:24:26.760 --> 00:24:34.120 The really interesting thing that we've done here is that we let you do joins and still provide 00:24:34.120 --> 00:24:34.820 you that feature. 00:24:34.940 --> 00:24:39.300 So in Notion, for example, you would just have one database and you can filter and sort 00:24:39.300 --> 00:24:40.180 that database. 00:24:40.180 --> 00:24:45.560 With DropBase, what we have is, let's say you have a table called users and a table called 00:24:45.560 --> 00:24:46.180 roles. 00:24:46.180 --> 00:24:53.960 And then they're related by an ID where, let's say, ID 1 is users, ID 2 is developers, ID 3 is 00:24:53.960 --> 00:24:54.400 admins. 00:24:54.400 --> 00:24:54.700 Yeah. 00:24:54.740 --> 00:24:56.600 You might have to join those two tables first. 00:24:56.600 --> 00:25:02.260 And so that same smart table feature, you can just write that SQL statement, that join 00:25:02.260 --> 00:25:06.440 statements, and we can still generate sort of the right filters for you. 00:25:06.440 --> 00:25:08.920 And we'll actually let you edit those tables as well. 00:25:08.920 --> 00:25:15.760 What we do is we take your SQL statement and then we infer all the SQL required to search 00:25:15.760 --> 00:25:18.840 or edit any column within the SQL statement. 00:25:18.840 --> 00:25:19.500 That sounds awesome. 00:25:19.500 --> 00:25:25.260 That's a really neat feature, especially for the people who are used to using something 00:25:25.260 --> 00:25:31.580 like Django admin in the sense that it helps you very quickly build an admin panel with very 00:25:31.580 --> 00:25:33.380 little developer work. 00:25:33.380 --> 00:25:33.660 Yeah. 00:25:33.660 --> 00:25:36.640 You can just write a SQL statement and then we give you an admin panel. 00:25:36.640 --> 00:25:36.940 Yeah. 00:25:36.940 --> 00:25:37.860 So that's really neat. 00:25:37.860 --> 00:25:42.260 The final thing with the app here in the demo is the little button on the right side. 00:25:42.260 --> 00:25:42.500 Yeah. 00:25:42.500 --> 00:25:44.020 That is a Python function. 00:25:44.020 --> 00:25:52.220 So you create a new Python function and you essentially write a database update to update 00:25:52.220 --> 00:25:56.580 the role from whatever it was, let's say from developer to an admin. 00:25:56.580 --> 00:26:03.300 So it's just really a select statement, update, table, set, column, something on this particular 00:26:03.300 --> 00:26:03.620 ID. 00:26:03.620 --> 00:26:05.300 And so that's just a Python function. 00:26:05.300 --> 00:26:10.040 And the final thing is just to connect that button to run this Python function. 00:26:10.040 --> 00:26:14.880 You click on the button, we run the function, and then we perform a database update to update 00:26:14.880 --> 00:26:16.600 the role to whichever role you want. 00:26:16.600 --> 00:26:19.440 And that really is just the gist of the demo. 00:26:19.440 --> 00:26:22.820 So a couple of things about that Python function that's pretty interesting. 00:26:22.820 --> 00:26:25.880 When you create it, you can say, I want to create a function and it says, do you want SQL 00:26:25.880 --> 00:26:28.680 or do you want Python, which is pretty interesting. 00:26:28.680 --> 00:26:32.460 The Python function has access to the UI widgets. 00:26:32.460 --> 00:26:37.540 Like in the actual video, not the screenshot of the video, I think you've got a dropdown select 00:26:37.540 --> 00:26:38.220 box. 00:26:38.220 --> 00:26:41.680 And so the Python function go, well, what did the user select? 00:26:41.680 --> 00:26:45.720 And then we'll make the change to the person in the workspace along those lines. 00:26:45.720 --> 00:26:47.700 So that's pretty cool, right? 00:26:47.700 --> 00:26:51.600 That you interact with this UI in kind of an object-oriented way, I suppose. 00:26:51.600 --> 00:26:53.320 That's exactly how it works. 00:26:53.320 --> 00:26:56.360 So behind the scenes, we have two classes. 00:26:56.360 --> 00:26:59.300 One is called state and one is called context. 00:26:59.500 --> 00:27:06.000 So the state class just lets us access all of the UI state at any point in time. 00:27:06.000 --> 00:27:12.300 Anything you enter in an input component or any row you select in the tables, you can see 00:27:12.300 --> 00:27:14.860 the currently selected values of it. 00:27:14.860 --> 00:27:22.400 And so whenever you click on a button or you perform an action, that state is passed to the 00:27:22.400 --> 00:27:24.800 backend just as a payload, just like a dictionary. 00:27:25.180 --> 00:27:31.300 And the backend, we generate all the classes, all the objects related to state and context. 00:27:31.300 --> 00:27:36.560 So we just have to pass the values in and then execute the function with those values as the 00:27:36.560 --> 00:27:36.860 input. 00:27:36.860 --> 00:27:40.760 And so that's how we're able to do the state thing with Python. 00:27:41.080 --> 00:27:45.560 If you've seen how you would do it in Python, it is very much a dot notation, right? 00:27:45.560 --> 00:27:52.040 So you would say to get the value of column one in table one, you basically just say state dot 00:27:52.040 --> 00:27:57.380 tables, which gives you all the tables, dot table one, dot column one. 00:27:57.380 --> 00:28:04.860 And that basically resolves into the value of the table, of the row in that table for that column. 00:28:05.000 --> 00:28:05.500 Yeah, that's cool. 00:28:05.500 --> 00:28:08.240 I can imagine the implementation of that thing. 00:28:08.240 --> 00:28:11.120 It's like dot, dot, dot, dot, git
adder. 00:28:11.120 --> 00:28:15.140 And if you ask for the thing, you look in the dictionary and you traverse the thing. 00:28:15.140 --> 00:28:23.200 But with that in mind, what I thought was really nice about this is you had pretty decent autocomplete in your little embedded Python editor. 00:28:23.200 --> 00:28:24.000 How did you pull that off? 00:28:24.000 --> 00:28:24.700 I did that you noticed. 00:28:24.700 --> 00:28:25.080 Yeah. 00:28:25.080 --> 00:28:26.720 We spent a lot of time on it. 00:28:26.720 --> 00:28:28.040 I bet you did. 00:28:28.040 --> 00:28:28.400 Yeah. 00:28:28.480 --> 00:28:28.900 How's that work? 00:28:28.900 --> 00:28:32.560 When we were designing this, we were thinking, damn, VS Code is really nice. 00:28:32.560 --> 00:28:36.120 You have all the plugins, all the autocomplete and everything. 00:28:36.120 --> 00:28:38.200 But we had two choices, right? 00:28:38.200 --> 00:28:47.760 Either we build this whole UI builder into VS Code, or we kind of take some of the things that make VS Code great and then bring it into the DropAce Studio. 00:28:47.760 --> 00:28:50.960 We don't know sort of the final eventually where this will be. 00:28:51.300 --> 00:29:05.840 But the current version of this is we thought, you know what, I think we need to give users an editor, like a built-in editor, so they can just quickly, they can have the best experience building the app and the access to UI and context and state really quickly. 00:29:05.840 --> 00:29:12.260 We just did it that way where we added in LSP, so like a language server. 00:29:12.260 --> 00:29:23.040 So anytime you type code in your Python function, it's basically over a WebSocket connection, basically streaming the code changes and saving them in your file system. 00:29:23.040 --> 00:29:28.960 That's the only way we can do this, this like object-oriented Python dot notation access. 00:29:28.960 --> 00:29:32.260 And so we need to have access to all the files. 00:29:32.260 --> 00:29:41.000 And so we set this up so that not only you can do autocomplete, but also that we can actually do the state and context approach to the web framework. 00:29:41.000 --> 00:29:45.980 It was a bit complicated because we hadn't been really exposed to LSPs before. 00:29:45.980 --> 00:29:53.100 And so we had to learn how to use LSPs, and we had to sort of hijack sort of the WebSocket connection in a way. 00:29:53.100 --> 00:29:56.460 So like we intercept the code, and then we save it in your file system. 00:29:56.460 --> 00:29:59.220 So we had to customize it a little bit to do this. 00:29:59.220 --> 00:30:03.000 And it's really nice because now you can do autocomplete for your files. 00:30:03.000 --> 00:30:04.100 It's just a need. 00:30:04.100 --> 00:30:05.880 It's so hard to develop now. 00:30:05.880 --> 00:30:07.360 We're so used to these tools. 00:30:07.360 --> 00:30:12.780 And now with things like Copilot, like we're used to even more than just autocomplete, right? 00:30:12.780 --> 00:30:16.380
It's like autocomplete the function, not just the variable, right? 00:30:16.380 --> 00:30:21.640 I feel like autocomplete is just table stakes, you know, especially in this kind of thing. 00:30:21.700 --> 00:30:28.020 There's somebody who's just done Python forever, and they'd rather get it out of the way, and it's fine. 00:30:28.020 --> 00:30:31.300 It's not my way of working, but it's fine for people who want to do that. 00:30:31.300 --> 00:30:40.800 But if you're working with somebody who might not be a full-time developer, but they want to use your framework, your service to build some app, it seems like this could really empower them. 00:30:41.060 --> 00:30:46.040 But if you give them something with zero autocomplete, zero highlighting, you're going to be having a rough time, you know? 00:30:46.040 --> 00:30:50.580 Yeah, even for a more experienced developer, I think it's still a hard time. 00:30:50.580 --> 00:30:53.620 Even if you can do it, it's just less productive to go like, oh, yeah. 00:30:53.620 --> 00:30:54.580 Way less productive. 00:30:54.780 --> 00:30:55.880 Yeah, way less productive. 00:30:55.880 --> 00:31:03.660 I think AI gets added to apps a lot just to kind of check a box, but the result of it is not that great. 00:31:03.660 --> 00:31:11.340 To get on my email client that has AI integrated, but it almost always seems like, well, that's not something I'd, yeah, something I want to read. 00:31:11.340 --> 00:31:14.460 Like, I don't really want to read that, and I don't need to summarize it. 00:31:14.460 --> 00:31:15.760 It's not emails, you know? 00:31:15.760 --> 00:31:19.420 It just seems like a lot of energy goes into it when it's not that big of a value. 00:31:19.420 --> 00:31:22.040 But maybe something like Copilot could be here. 00:31:22.040 --> 00:31:24.660 This is something we've talked about, me and my co-founder. 00:31:24.660 --> 00:31:37.300 So one of the things that we didn't get to cover, because we're not going to go through all the demos, but the way that we render data in these tables is we basically format it as a pandas data frame. 00:31:37.300 --> 00:31:37.540 Okay. 00:31:37.540 --> 00:31:43.500 So what that means is that, let's say that you query data from Stripe, right? 00:31:43.500 --> 00:31:46.060 Like you get all your customers from Stripe. 00:31:46.060 --> 00:31:48.020 Stripe is not going to return a data frame for you. 00:31:48.020 --> 00:31:50.380 It's going to return like an object, right? 00:31:50.380 --> 00:31:51.000 A dictionary. 00:31:51.480 --> 00:31:56.000 And then you basically have to take that dictionary and then basically convert it into a data frame. 00:31:56.000 --> 00:31:58.400 And then we automatically know how to render everything else from there. 00:31:58.400 --> 00:31:59.740 So we've thought about this. 00:31:59.740 --> 00:32:13.700 And like, wouldn't it be cool if as soon as you get the response from an endpoint, let's say as a JSON dictionary, that we suggest that we can just take it
at next step for you, which is just to like convert it into a data frame. 00:32:13.700 --> 00:32:15.560 And then you wouldn't have to hustle with it. 00:32:15.560 --> 00:32:15.720 Yeah. 00:32:15.720 --> 00:32:16.440 We've done that with it. 00:32:16.440 --> 00:32:18.780 But in theory, that sounds very, very helpful. 00:32:19.140 --> 00:32:22.920 If you're proficient in pandas and using data frames, 00:32:22.920 --> 00:32:24.360 it's actually not that hard. 00:32:24.360 --> 00:32:25.880 It's a very quick thing for you. 00:32:25.880 --> 00:32:28.720 But if you just know Python but not exposed 00:32:28.720 --> 00:32:32.240 to the whole data frame ecosystem, 00:32:32.240 --> 00:32:35.100 then maybe it would be really nice if you just said, OK, 00:32:35.100 --> 00:32:36.740 we just started to data frame for you, 00:32:36.740 --> 00:32:38.660 and then that's all you have to care about. 00:32:38.660 --> 00:32:39.580 So we've thought about this. 00:32:39.580 --> 00:32:40.560 We haven't added this yet. 00:32:40.560 --> 00:32:41.860 MARK MANDEL: I think it's fine without. 00:32:41.860 --> 00:32:43.320 But it's kind of one of those things, 00:32:43.320 --> 00:32:45.420 like you're in there, and you've got these data sources, 00:32:45.420 --> 00:32:47.080 and maybe you're not super familiar with them. 00:32:47.080 --> 00:32:48.700 Maybe you can pull them together somehow. 00:32:48.700 --> 00:32:50.940 One of the things that I find myself struggling with 00:32:50.940 --> 00:32:52.760 is, let's say I want to build a demo. 00:32:52.760 --> 00:32:56.200 Let's say I haven't been exposed to the SendGrid API 00:32:56.200 --> 00:32:57.780 or the HubSpot API. 00:32:57.780 --> 00:33:00.820 Then I have to go to their documentation 00:33:00.820 --> 00:33:05.340 to figure out what's the package name so I can install it. 00:33:05.340 --> 00:33:06.960 How do I authenticate in? 00:33:06.960 --> 00:33:09.740 How do I call a few endpoints to do what I need to do? 00:33:09.740 --> 00:33:11.380 And I think in that case where it's 00:33:11.380 --> 00:33:13.360 not about your knowledge of Python, 00:33:13.360 --> 00:33:16.220 it really is about your knowledge of this other thing 00:33:16.220 --> 00:33:17.260 that you're using. 00:33:17.260 --> 00:33:21.600 In those cases, it seems that it could be extremely helpful for someone to build apps very quickly 00:33:21.600 --> 00:33:27.640 if they somehow had access to either quick documentation or you just suggested what you might want to do. 00:33:27.640 --> 00:33:29.500 MARK MANDEL: Yeah, that's kind of what I was thinking as well. 00:33:29.500 --> 00:33:35.840 If you're a regular listener of the podcast, you surely heard about Talk Python's online courses. 00:33:35.840 --> 00:33:37.840 But have you had a chance to try them out? 00:33:37.840 --> 00:33:41.740 No matter the level you're looking for, we have a course for you. 00:33:41.740 --> 00:33:48.080 Our Python for Absolute Beginners is like an introduction to Python plus that first year computer science course that you never took. 00:33:48.080 --> 00:33:54.860 Our data-driven web app courses build a full PyPI.org clone along with you right on the screen. 00:33:54.860 --> 00:33:58.080 And we even have a few courses to dip your toe in with. 00:33:58.080 --> 00:34:03.120 See what we have to offer at training.talkpython.fm or just click the link in your podcast player. 00:34:03.120 --> 00:34:09.460 MARK MANDEL: So speaking of that sort of external resources, you've got this Python function. 00:34:09.460 --> 00:34:10.960 And what can I put in there? 00:34:10.960 --> 00:34:12.960 Can I use external packages? 00:34:12.960 --> 00:34:18.160 Can I call out on the network to talk to some API endpoints? 00:34:18.160 --> 00:34:19.460 Can I spin up threads? 00:34:19.460 --> 00:34:21.380 Like what can I do? 00:34:21.380 --> 00:34:23.000 How much Python can I do there? 00:34:23.000 --> 00:34:24.440 MARK MANDEL: Pretty much all of the above. 00:34:24.440 --> 00:34:26.400 MARK MANDEL: So I'll elaborate what I mean by that. 00:34:26.400 --> 00:34:34.780 So the standard way that you would connect to some of these services, these third party services, is you'll make like an HTTP request. 00:34:34.780 --> 00:34:36.660 Like get requests, post requests. 00:34:36.660 --> 00:34:39.720 So you can just like import requests, basically. 00:34:39.720 --> 00:34:44.900 PIP install requests and then just do it over the standard Python, basically Python package. 00:34:44.900 --> 00:34:50.300 Now, it is way more convenient when you use an SDK provided by one of these third parties. 00:34:50.300 --> 00:34:54.300 So if you want to use Stripe, if you're able to just import Stripe, it'll make your life 00:34:54.300 --> 00:34:58.340 a lot easier, very nicely, Pythonic, everything set up. 00:34:58.340 --> 00:35:03.480 So in DropBase, you can install anything that you can install via PyPI. 00:35:03.480 --> 00:35:06.880 We have a file called custom requirements. 00:35:06.880 --> 00:35:12.620 And if you just list them out, when you set up DropBase, we'll basically install all those for you. 00:35:12.620 --> 00:35:17.620 And then when you write a function, you can just basically import Stripe directly in the function 00:35:17.620 --> 00:35:20.920 without pip installing it again, and then you just use it. 00:35:20.920 --> 00:35:22.120 So that's really nice. 00:35:22.120 --> 00:35:23.000 But basically anything. 00:35:23.000 --> 00:35:25.540 I think you were doing a previous uv. 00:35:25.540 --> 00:35:26.040 You were talking. 00:35:26.040 --> 00:35:27.040 Yeah, yeah. 00:35:27.040 --> 00:35:29.040 I was talking to Charlie Marsh about uv earlier today. 00:35:29.040 --> 00:35:29.040 Yeah. 00:35:29.040 --> 00:35:30.800 We haven't looked into it yet. 00:35:30.800 --> 00:35:36.920 But anything you can pip install from PyPI, you can install in DropBase, which makes it really, 00:35:36.920 --> 00:35:37.720 really powerful. 00:35:37.720 --> 00:35:38.280 Yeah, nice.
00:35:38.280 --> 00:35:39.560 There's a database connections. 00:35:39.560 --> 00:35:42.920 I mean, you could use SQLAlchemy or you can import whatever else you want. 00:35:42.920 --> 00:35:48.520 But we make those a bit more native because we know that you're going to connect to databases. 00:35:48.520 --> 00:35:50.760 So we want to make it a bit more convenient. 00:35:50.760 --> 00:35:51.560 So. 00:35:51.560 --> 00:35:55.420 And your tables need sort of direct access to it as well, right? 00:35:55.420 --> 00:36:01.220 Not just the output of some access to the database, but you've got to figure out the columns and all that kind of stuff, right? 00:36:01.220 --> 00:36:01.760 That's correct. 00:36:01.760 --> 00:36:11.140 So we created a little library, like a utility slash helper that lets you perform database operations very quickly. 00:36:11.140 --> 00:36:22.700 So if you've added your database credentials to the .env file, then you can quickly perform, you know, like a select statement or, you know, make an update to that database via functions. 00:36:22.700 --> 00:36:32.380 But without, you know, the standard thing where you do, if you use SQLAlchemy, for example, where you like start a session, start a connection, you know, like all those steps, we kind of abstract that for you. 00:36:32.380 --> 00:36:37.480 But you can totally use SQLAlchemy in its full glory if you, you know, if that's what you're used to. 00:36:37.600 --> 00:36:43.560 Nice. Can I write Python files, like separate Python scripts and stuff, and then just import and call them from there? 00:36:43.560 --> 00:36:45.080 Or does it have to be done through the UI? 00:36:45.080 --> 00:36:45.400 Totally. 00:36:45.400 --> 00:36:45.700 Yeah. 00:36:45.700 --> 00:36:57.960 There's actually one of the biggest advantages of DropBase is that if you have like a Python script lying around and you want to sort of use it in DropBase, you can add it to that file system somewhere in the workspace directory. 00:36:57.960 --> 00:37:01.080 And you can just import it in via your function. 00:37:01.080 --> 00:37:06.320 So you just like from your file, you can import a specific function in that file, for example. 00:37:06.580 --> 00:37:14.460 And so the implication of this is that you can set up DropBase in a way that it just lives in your existing Python code base. 00:37:14.460 --> 00:37:20.820 So imagine you're already, you know, you've set up your company, you've got product market fit, you know, things are running, right? 00:37:20.820 --> 00:37:22.140 And you have a Python backend. 00:37:22.140 --> 00:37:25.900 And now you're starting to scale and you need to build tools. 00:37:25.900 --> 00:37:29.460 So your first option would be to do all custom, obviously. 00:37:29.460 --> 00:37:33.260 The second option is to use some sort of tools builder. 00:37:33.340 --> 00:37:40.040 But every single action you take is done over an HTTP request with authentication, with everything. 00:37:40.040 --> 00:37:42.340 So just like a standard internet communication. 00:37:42.340 --> 00:37:54.400 But if you wanted to just interact with an existing functions or internal endpoints, then you'd have to either set up an RPC server or you might want to use some other way to get in there. 00:37:55.220 --> 00:38:00.340 DropBase, you basically just set up DropBase in the same directory as your app. 00:38:00.340 --> 00:38:03.540 And you can then import selectively what functions you need. 00:38:03.880 --> 00:38:14.060 It's sort of like a window into your code base that it's like a plug into that code base where you can now expand and build a lot of internal tools that leverages everything that you've already built. 00:38:14.060 --> 00:38:14.360 Yeah. 00:38:14.360 --> 00:38:15.320 That's it, by the way. 00:38:15.320 --> 00:38:15.720 Yeah. 00:38:15.720 --> 00:38:17.780 When you've got, yeah, there's the requirements at custom, right? 00:38:17.780 --> 00:38:20.360 So you've got your Docker compose file. 00:38:20.360 --> 00:38:28.140 I mean, could you set it up just so as you build, maybe even better, just set up a volume so that it can directly find. 00:38:28.140 --> 00:38:30.440 I mean, I guess that's what you're kind of showing right here, right? 00:38:30.440 --> 00:38:38.380 Is that you can sort of map, mount a volume just directly into, say, your Git repo for your big project code. 00:38:38.380 --> 00:38:40.800 And then you can just start importing that and doing stuff with it, right? 00:38:40.800 --> 00:38:44.740 We still need to do some tweaks because of the relative paths. 00:38:44.740 --> 00:38:48.400 But the idea is that you can do that with a little bit of customization. 00:38:48.400 --> 00:38:56.020 But yeah, our workspace server, basically, you mount files or directories, and then we can look into those to execute. 00:38:56.020 --> 00:38:58.260 Yeah, manage those files with Git or something like that. 00:38:58.260 --> 00:39:02.280 A good example of this is, are you familiar with Django and Django Admin? 00:39:02.280 --> 00:39:04.820 Not super, as I do every day, but I'm aware, sure. 00:39:04.820 --> 00:39:07.480 Django, it's a great web framework. 00:39:07.480 --> 00:39:08.580 It's used by a lot of companies. 00:39:08.580 --> 00:39:11.140 It's like, if you want to build web apps, you have Django. 00:39:11.140 --> 00:39:12.700 It comes with a lot of stuff, right? 00:39:12.700 --> 00:39:21.540 And there's this thing called Django Admin that basically automatically generates admin panels for you based on your Django models. 00:39:21.680 --> 00:39:25.740 And so if you have a model for a book, right? 00:39:25.740 --> 00:39:27.060 And the book has authors. 00:39:27.060 --> 00:39:29.940 It basically exposes that to the Django admin. 00:39:29.940 --> 00:39:33.800 And then now you can edit a book without really doing anything. 00:39:33.800 --> 00:39:35.360 It all kind of comes for free. 00:39:35.360 --> 00:39:36.220 It's pretty neat. 00:39:36.220 -->
00:39:38.640 I think that's half the appeal of Django right there. 00:39:38.640 --> 00:39:39.200 It is. 00:39:39.200 --> 00:39:41.220 Yeah, I think a lot of people use it for that. 00:39:41.220 --> 00:39:42.620 Yeah, they're like, I don't want to write that stuff. 00:39:42.620 --> 00:39:43.280 I'm using Django. 00:39:43.280 --> 00:39:44.180 Yeah, for real. 00:39:44.180 --> 00:39:44.860 And it's great. 00:39:44.860 --> 00:39:58.120 Now, at some point, when your company hits a certain milestone or a certain number of customers, you will need to customize those admin panels. 00:39:58.120 --> 00:40:03.860 You might need to create admin panels for things that maybe you don't have models for yet. 00:40:03.860 --> 00:40:10.980 Or for things that combine data from your database with data from like Stripe or some other source. 00:40:10.980 --> 00:40:20.940 And so what we see when we talk to these people is that they kind of struggle to like either do I like keep using this or do I like completely rebuild everything? 00:40:20.940 --> 00:40:29.860 For those users, when we talk to them about DropBase, they get very excited because with DropBase, you can install Django and it can sit in your file system. 00:40:29.860 --> 00:40:38.760 And so essentially all the models that you've already built in Django, you can basically call them via DropBase, with DropBase function because it's all Python, right? 00:40:38.920 --> 00:40:43.180 And so it gives you this like, okay, Django admins are great up to a certain point. 00:40:43.180 --> 00:40:45.100 And then after that, what happens, right? 00:40:45.100 --> 00:40:48.440 Like you might not want to rebuild everything just so you can have internal tooling. 00:40:48.440 --> 00:41:01.760 And so I think that's quite of a nice spot for us to say, look, DropBase can live in your code base, uses everything you already have, but it gives you some extra things if you want to build internal tools very quickly. 00:41:01.760 --> 00:41:04.720 So that's something we're obviously very, very excited about. 00:41:04.720 --> 00:41:05.380 That's really cool. 00:41:05.380 --> 00:41:06.620 I like that aspect of it. 00:41:06.880 --> 00:41:12.620 So when we talk about this code, I guess there's two scenarios, the cloud version or the self-hosted version. 00:41:12.620 --> 00:41:15.600 But where and how does this Python run? 00:41:15.600 --> 00:41:17.660 Is it, it must be full CPython? 00:41:17.660 --> 00:41:20.020 Is it running in isolated Docker containers? 00:41:20.020 --> 00:41:22.160 Or in your cloud, what happens? 00:41:22.160 --> 00:41:25.200 Is it functions like AWS functions, Lambda? 00:41:25.200 --> 00:41:30.180 It just runs either on your local machine, if you've set it up as a developer. 00:41:30.180 --> 00:41:31.240 It's all running there. 00:41:31.240 --> 00:41:34.340 Obviously, if you turn off your machine, you can use your apps. 00:41:34.340 --> 00:41:42.800 And then if you set it up in a production instance, let's say you deploy
this on an EC2, your Python functions are running on that EC2. 00:41:42.800 --> 00:41:46.440 But it's running via Docker container inside. 00:41:46.540 --> 00:41:49.700 So it gets a little isolation, a little bit of protection, that kind of stuff. 00:41:49.700 --> 00:41:54.360 And we're assuming that, I mean, you're building these apps to run on your own infrastructure. 00:41:54.360 --> 00:41:56.700 It's that you would, that you know what you're doing. 00:41:56.700 --> 00:42:15.900 So this is as opposed to us having a full cloud version where all customers run untrusted code in the same sort of backend system, which would be obviously very dangerous because I'm sure there's ways a customer can somehow, you know, go through the backend and access other customers' untrusted code. 00:42:15.900 --> 00:42:17.040 And that would be a nightmare. 00:42:17.040 --> 00:42:22.740 And so if, you know, we have isolation, first layer is, well, it's in your infrastructure you're going to do. 00:42:22.740 --> 00:42:24.480 It's just your company's code. 00:42:24.480 --> 00:42:29.780 But then further, you know, we run Python in containers in that instance. 00:42:29.780 --> 00:42:33.200 That sounds more like a durability thing than anything. 00:42:33.200 --> 00:42:35.440 I mean, it is also for isolation protection. 00:42:35.440 --> 00:42:40.580 But first and foremost, just don't let bad Python code take down the whole thing, you know? 00:42:40.580 --> 00:42:52.080 The way we recommend people using DropBase or setting up their dev sort of process with DropBase is that they would clone, basically fork the for DropBase. 00:42:52.080 --> 00:42:53.740 And then they will develop locally. 00:42:54.120 --> 00:42:55.320 They will test changes. 00:42:55.320 --> 00:43:00.120 And once they're happy with the new code, you know, they'll push it back. 00:43:00.120 --> 00:43:03.640 And then they will have CI/CD into the production instance. 00:43:03.640 --> 00:43:05.460 And then they can version control everything. 00:43:05.460 --> 00:43:11.340 So that also gives you that extra layer of, okay, let's make sure that whatever we're pushing is tested. 00:43:11.340 --> 00:43:19.360 You can always add test databases that you develop locally with before you push the production, where it's going to have to act on your production data. 00:43:19.460 --> 00:43:20.500 Yeah, that's pretty interesting. 00:43:20.500 --> 00:43:22.960 I like the version control aspect of it. 00:43:23.020 --> 00:43:31.900 That gives it a much nicer touch to connection to real software rather than just it's a text input area in an app that who knows what happens. 00:43:31.900 --> 00:43:34.740 As developers, it sometimes feels a bit scary, right? 00:43:34.740 --> 00:43:39.500 Like you're building something and it's in this other framework and this other cloud. 00:43:39.500 --> 00:43:45.400 And it just feels like you can't kind of get, like if the thing goes away, like you can't even see your previous code. 00:43:45.400
--> 00:43:57.740 That was another key concept that we wanted to have is in this tool that it feels friendly for developers, that it matches your mental models and your sort of like your development process, let's call it. 00:43:57.740 --> 00:44:04.140 Like how you're used to making apps or developing code, that we keep that feeling when you're building apps for a trial phase. 00:44:04.140 --> 00:44:09.700 I want to maybe have a PR to understand if we accept this change to it, right? 00:44:09.700 --> 00:44:10.240 That's right. 00:44:10.240 --> 00:44:10.480 Yeah. 00:44:10.560 --> 00:44:10.720 Yeah. 00:44:10.720 --> 00:44:14.000 You don't normally hear that kind of stuff around these kind of tools, you know? 00:44:14.000 --> 00:44:26.280 And if you do, I think it tends to be like, yeah, okay, it's like a huge enterprise contract, you know, pay us $50,000 a year and then you get version control, which to me, it sounds scary. 00:44:26.280 --> 00:44:28.600 I mean, it just, it will make me a little bit less comfortable. 00:44:28.600 --> 00:44:35.560 Now, obviously, if I'm a big company and I just really need the tool, sure, maybe I'll just pay for it and I get version control. 00:44:35.560 --> 00:44:42.260 But, you know, getting version control, it just feels so like, like table stakes for developers, especially today. 00:44:42.260 --> 00:44:44.900 But yeah, it just wouldn't make sense otherwise for us. 00:44:44.900 --> 00:44:46.420 I mean, it's the way we're approaching this product. 00:44:46.420 --> 00:44:46.700 Yeah. 00:44:46.700 --> 00:44:49.640 Well, the other aspect is, you know, what are you version controlling? 00:44:49.640 --> 00:44:56.920 You know, do you end up with, you know, something like effectively a Jupyter Notebook, like big blob of something. 00:44:56.920 --> 00:45:00.140 And then there's an older blob of something and then you diff it. 00:45:00.140 --> 00:45:01.000 You're like, what is this? 00:45:01.000 --> 00:45:05.320 But since you end up with just these, you know, your workspace files that just live there, right? 00:45:05.320 --> 00:45:08.060 It's a real optimized, like, show me the changes. 00:45:08.060 --> 00:45:09.060 Show me what's happened here. 00:45:09.060 --> 00:45:09.420 Yeah. 00:45:09.420 --> 00:45:13.500 It all lives there, including the component properties. 00:45:13.500 --> 00:45:18.420 Like we don't store this in like a separate database or anything like that. 00:45:18.420 --> 00:45:24.480 So like, you know, like for some of their tools, they will store all the components in their database. 00:45:24.480 --> 00:45:36.380 And so what they do is, you know, when you load up their tools, like their tools builder, it'll fetch all the components from the provider's database, combine it with maybe your custom code, and then it'll do it. 00:45:36.380 --> 00:45:40.940 And so even that feels like, okay, but where's like config for my components? 00:45:40.940 --> 00:45:41.300 Yeah. 00:45:41.300 --> 00:45:42.240 Where'd this button come from? 00:45:42.240 --> 00:45:43.080 Why is it gone? 00:45:43.080 --> 00:45:43.660 That's tough. 00:45:43.660 --> 00:45:44.040 Yeah. 00:45:44.040 --> 00:45:44.420 That's tough. 00:45:44.420 --> 00:45:50.060 And then like, imagine if you wanted to like share their apps or, you know, it's just like version control makes a bit less sense. 00:45:50.060 --> 00:46:00.020 I mean, you're just version controlling, just like the individual functions, maybe like the custom part of the code that you write, which is still useful, but it still feels like you don't have the full picture of what's happening. 00:46:00.020 --> 00:46:00.340 Yeah. 00:46:00.340 --> 00:46:01.800 You don't have a full record. 00:46:01.800 --> 00:46:03.240 It could easily get out of sync. 00:46:03.240 --> 00:46:03.540 Yeah. 00:46:03.540 --> 00:46:04.260 Quite interesting. 00:46:04.260 --> 00:46:15.040 I guess one thing we touched on a little bit before I press go here in the show, you said that at one point you were considering using Jupyter in this whole mechanism. 00:46:15.040 --> 00:46:15.780 Yeah. 00:46:15.780 --> 00:46:17.340 What's the story around that? 00:46:17.340 --> 00:46:18.320 We love Jupyter. 00:46:18.320 --> 00:46:19.680 We love notebooks. 00:46:19.680 --> 00:46:21.600 And we love the experience of them. 00:46:21.600 --> 00:46:30.120 The sense that you can write some code and you can quickly test and execute the code without, basically without, without needing to write anything else. 00:46:30.120 --> 00:46:33.660 So for prototyping, for getting quick feedback, it's great. 00:46:33.660 --> 00:46:41.160 And we wanted to give our developers something like that, because when you build these apps, you're kind of iterating, right? 00:46:41.160 --> 00:46:42.180 You're like, you're testing it. 00:46:42.180 --> 00:46:48.100 A lot of times you don't even know the documentation for Drive or HubSpot or, and so like there's a lot of experimentation. 00:46:48.680 --> 00:46:50.720 And so we wanted a quick way to do that. 00:46:50.720 --> 00:46:58.520 So we considered maybe having something like a Jupyter kernel within DropBase that allowed people to do it. 00:46:58.520 --> 00:47:05.180 There were some issues with it in the sense that the kernel actually stores results from like previous blocks. 00:47:05.760 --> 00:47:10.320 And sometimes that gets in the way of you triggering an action in a later block. 00:47:10.320 --> 00:47:14.480 And so we were like, okay, maybe that's a little bit more than we need. 00:47:14.480 --> 00:47:17.480 Now, we still kind of eventually want something like that. 00:47:17.480 --> 00:47:18.660 We hacked it in a way. 00:47:18.660 --> 00:47:22.360 Like, so the way that we do it is you can write a Python function. 00:47:22.360 --> 00:47:23.820 You basically get one block. 00:47:23.820 --> 00:47:30.200 You can write a Python function and you can click on a play button to basically run that function. 00:47:30.360 --> 00:47:32.000 But it's not like a
kernel. 00:47:32.000 --> 00:47:36.200 So what we do is behind the scenes, we have like a main function. 00:47:36.200 --> 00:47:41.120 And when you trigger that function, we take the state from the client. 00:47:41.120 --> 00:47:46.520 So whatever you've selected or input it, we take the underlying file for your Python function. 00:47:46.520 --> 00:47:48.200 And then we call it from me. 00:47:48.200 --> 00:47:54.180 And so we kind of simulate that experience of like instantly testing code that you just wrote. 00:47:54.180 --> 00:47:57.760 But there is no Jupyter kernel behind the scenes. 00:47:57.760 --> 00:47:59.960 And then you can only do one block at a time. 00:47:59.960 --> 00:48:04.700 And so we said, okay, for now, as we're getting started with it, it's good enough. 00:48:04.700 --> 00:48:05.740 You can write your functions. 00:48:05.740 --> 00:48:08.820 You can run and test them immediately, which is really nice. 00:48:08.820 --> 00:48:10.440 You can do this with VS Code, by the way. 00:48:10.440 --> 00:48:13.460 Like you would have to open up the terminal and then basically run your function. 00:48:13.840 --> 00:48:19.940 And so we still wanted this feature where you can click and just see your outputs and basically debug and troubleshoot. 00:48:19.940 --> 00:48:23.860 But it would be really nice if you could get out multiple blocks and you can just build functions that way. 00:48:23.860 --> 00:48:25.200 So maybe for the future. 00:48:25.200 --> 00:48:25.700 Interesting. 00:48:25.700 --> 00:48:29.120 Did you say that you were a core developer for Jupyter? 00:48:29.120 --> 00:48:29.920 No, no. 00:48:29.920 --> 00:48:31.180 I just spoke to them. 00:48:31.180 --> 00:48:32.620 It sounds fun. 00:48:32.700 --> 00:48:34.900 I interviewed a whole bunch of them recently. 00:48:34.900 --> 00:48:41.180 And what I thought was interesting is Jupyter is such an empowering thing for Python developers. 00:48:41.180 --> 00:48:53.000 But many of the core developers are so focused on writing JavaScript and TypeScript to sort of make these interactions possible so that the rest of us don't have to write JavaScript and that kind of stuff. 00:48:53.000 --> 00:48:55.420 So I think we're getting about to the end of our time here. 00:48:56.220 --> 00:48:58.960 I'm sure that actually this is somewhat similar. 00:48:58.960 --> 00:49:01.920 It's really a dynamic interactive web app. 00:49:01.920 --> 00:49:05.960 And in that case, it probably has to have some interesting front end JavaScript stuff going on. 00:49:05.960 --> 00:49:07.420 What's the JavaScript story? 00:49:07.420 --> 00:49:07.960 Yeah. 00:49:07.960 --> 00:49:09.440 What framework are you using and stuff like that? 00:49:09.440 --> 00:49:12.220 We just react to build our components. 00:49:12.220 --> 00:49:18.360 Obviously, we abstract that away so that you as a Python developer, you're just writing Python. 00:49:18.360 --> 00:49:19.820 Well, you're writing SQL as well. 00:49:19.820 --> 00:49:20.980 But
let's call that Python. 00:49:21.300 --> 00:49:24.900 And then we deal with the components for you. 00:49:24.900 --> 00:49:32.940 And so it's not the kind of framework where you're writing Python and we're generating HTMX or something like that. 00:49:32.940 --> 00:49:35.320 So obviously, we understand React. 00:49:35.320 --> 00:49:39.540 And we know we can build some beautiful components, customize them with it. 00:49:39.540 --> 00:49:45.980 We weren't about to create a completely new framework where we somehow just generate HTML from Python. 00:49:45.980 --> 00:49:49.180 I think there's a few people working on that, actually. 00:49:49.520 --> 00:50:02.580 We already know React, so let's just build those components or customize those components and then just let people declare them and then sort of access and modify them via the context objects in your Python functions. 00:50:02.580 --> 00:50:07.660 So our stack, we use FastAPI for our backend, which is great. 00:50:07.660 --> 00:50:08.700 It's excellent, yeah. 00:50:08.700 --> 00:50:11.680 I'm not sure if you've had the creator here. 00:50:11.820 --> 00:50:16.100 Yeah, I've had Sebastian on, I think, at least three times, Sebastian Ramirez. 00:50:16.100 --> 00:50:17.440 Yeah, he's great. 00:50:17.440 --> 00:50:18.560 Yeah, he is really great, yeah. 00:50:18.560 --> 00:50:20.700 FastAPI is a fantastic app. 00:50:20.700 --> 00:50:22.080 And so, yeah, we use them. 00:50:22.080 --> 00:50:24.640 We use React or our client side. 00:50:24.640 --> 00:50:27.900 And we are a lot of our infras on AWS. 00:50:27.900 --> 00:50:29.540 Yeah, sounds really interesting. 00:50:29.540 --> 00:50:31.060 Sounds like a fun app to work on. 00:50:31.060 --> 00:50:32.940 Yeah, you should play around with it. 00:50:32.940 --> 00:50:36.840 I can help you build some apps to manage your podcast library. 00:50:37.400 --> 00:50:40.980 All right, well, Jimmy, I think we are pretty much out of time. 00:50:40.980 --> 00:50:43.060 Final thought for people listening. 00:50:43.060 --> 00:50:44.500 Maybe they're excited to try this out. 00:50:44.500 --> 00:50:45.460 What are you telling them? 00:50:45.460 --> 00:50:49.600 Yeah, just go to droppace.io and sign up for a free account. 00:50:49.600 --> 00:50:50.760 It's free for developers. 00:50:50.760 --> 00:50:51.780 You can set it up locally. 00:50:51.780 --> 00:50:54.600 If you have any issues setting it up, just reach out. 00:50:54.600 --> 00:50:56.600 I'll personally help you get it up and running. 00:50:56.600 --> 00:50:59.500 Yeah, you can look at the documentation for everything else. 00:50:59.500 --> 00:50:59.840 Yeah. 00:50:59.840 --> 00:51:00.400 Let's find it. 00:51:00.400 --> 00:51:00.860 Try it. 00:51:00.860 --> 00:51:01.560 Give us some feedback. 00:51:01.560 --> 00:51:02.700 We'd love to hear from you. 00:51:02.760 --> 00:51:03.000 Awesome. 00:51:03.000 --> 00:51:06.460 Congrats on building a cool project for people. 00:51:06.460 --> 00:51:07.640 And yeah, good luck with it. 00:51:07.640 --> 00:51:08.040 Thanks, Michael. 00:51:08.040 --> 00:51:11.420 This has been another episode of Talk Python To Me. 00:51:11.420 --> 00:51:13.220 Thank you to our sponsors. 00:51:13.220 --> 00:51:14.840 Be sure to check out what they're offering. 00:51:14.840 --> 00:51:16.280 It really helps support the show. 00:51:16.280 --> 00:51:21.160 Mailtrap, an email delivery platform that developers love. 00:51:21.160 --> 00:51:24.420 Try for free at mailtrap.io. 00:51:24.420 --> 00:51:26.820 Want to level up your Python? 00:51:26.820 --> 00:51:30.860 We have one of the largest catalogs of Python video courses over at Talk Python. 00:51:31.320 --> 00:51:36.060 Our content ranges from true beginners to deeply advanced topics like memory and async. 00:51:36.060 --> 00:51:38.720 And best of all, there's not a subscription in sight. 00:51:38.720 --> 00:51:41.620 Check it out for yourself at training.talkpython.fm. 00:51:41.620 --> 00:51:43.700 Be sure to subscribe to the show. 00:51:43.700 --> 00:51:46.480 Open your favorite podcast app and search for Python. 00:51:46.480 --> 00:51:47.780 We should be right at the top. 00:51:47.780 --> 00:51:52.960 You can also find the iTunes feed at /itunes, the Google Play feed at /play, 00:51:52.960 --> 00:51:57.140 and the direct RSS feed at /rss on talkpython.fm. 00:51:57.140 --> 00:52:00.100 We're live streaming most of our recordings these days. 00:52:00.240 --> 00:52:03.520 If you want to be part of the show and have your comments featured on the air, 00:52:03.520 --> 00:52:07.900 be sure to subscribe to our YouTube channel at talkpython.fm/youtube. 00:52:07.900 --> 00:52:10.000 This is your host, Michael Kennedy. 00:52:10.000 --> 00:52:11.300 Thanks so much for listening. 00:52:11.300 --> 00:52:12.460 I really appreciate it. 00:52:12.460 --> 00:52:14.360 Now get out there and write some Python code. 00:52:14.360 --> 00:52:35.340 We'll see you next time.
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