Discover how to quickly turn your Python scripts into interactive web apps using Streamlit. This session will cover key features like visualisations, widgets, and deployment, empowering you to create user-friendly interfaces with minimal effort.
Transcript
1 00:00:02.390 --> 00:00:05.820 Gabor Szabo: So hello and welcome to the Code Maven Channel.
2 00:00:05.960 --> 00:00:14.180 Gabor Szabo: My name is Gabor. I organize these events because I think it's very important for people to be able to share their knowledge.
3 00:00:14.410 --> 00:00:38.479 Gabor Szabo: and it's very useful for everyone else to learn from other people all around the world. I myself usually teach python and rust and help companies introduce testing in these 2 languages or introduce these languages. And that's it. Basically, this channel is mostly with. Now these videos from these meetings.
4 00:00:38.860 --> 00:01:07.330 Gabor Szabo: and I am really happy that you agreed to give this presentation in our meeting, and thank you everyone for joining us here. If you are in the Zoom Meeting. Then feel free to ask questions. Just remember that it's going to be in Youtube. If you're watching it in Youtube, then. And if you enjoy this video, then please, like the video and follow the channel, and later on we'll have below the the video links
5 00:01:07.380 --> 00:01:14.970 Gabor Szabo: and where you can contact layer as well if you are interested later on. So now it's your turn. Go ahead.
6 00:01:15.950 --> 00:01:16.850 Gabor Szabo: Welcome now.
7 00:01:21.690 --> 00:01:30.810 Leah Levy: so hopefully, you can see my screen. So my name is Leah. I'm currently living in the Uk, I'm a data scientist in the Uk.
8 00:01:30.810 --> 00:01:41.190 Gabor Szabo: Maybe I it's only just me, but I can see all the list of the people who are joined. Is it on your screen, or it's just mine. No, it's it's I think you're sharing that one.
9 00:01:43.930 --> 00:01:44.700 Leah Levy: Yeah.
10 00:01:49.860 --> 00:01:53.950 Gabor Szabo: Wait a second. Maybe it's my, it's mine. No view.
11 00:01:54.720 --> 00:01:56.819 Gabor Szabo: Yeah, no, it was mine. Sorry.
12 00:01:58.430 --> 00:02:00.800 Gabor Szabo: Sorry, confusing you. Okay.
13 00:02:02.020 --> 00:02:02.550 Leah Levy: It's okay.
14 00:02:02.550 --> 00:02:06.490 Gabor Szabo: Go ahead. No, no, it's okay. It was on my screen in the.
15 00:02:11.030 --> 00:02:22.899 Leah Levy: yeah. So I'm a data scientist in the for the Uk government. I'm currently get living in in England. I'm hoping to move to Israel soon. So be nice to meet everybody.
16 00:02:23.611 --> 00:02:42.418 Leah Levy: I'm gonna talk today about streamlit, which is a python library and how I use it to like deploy machine learning models and just build web apps. I'll put my contact details in the chat. If you wanna connect with me on Linkedin or follow me on Github.
17 00:02:43.200 --> 00:02:45.630 Leah Levy: be great to be great, to connect
18 00:02:46.694 --> 00:02:55.610 Leah Levy: and please feel free to ask questions as we go along. I've I can see the chat. So if you want to put messages in the chat or come off mute, whatever you prefer.
19 00:02:56.760 --> 00:03:02.790 Leah Levy: So streamlet is a python library. It's open source.
20 00:03:02.790 --> 00:03:10.029 Gabor Szabo: Sorry. Sorry. Just one note, I mean, right now we can see both you and and this and the slides.
21 00:03:10.300 --> 00:03:11.630 Gabor Szabo: and.
22 00:03:11.900 --> 00:03:12.880 Leah Levy: Oh, okay.
23 00:03:12.880 --> 00:03:22.350 Gabor Szabo: So maybe you want to turn off your your camera, or or just show the slides, because in the recording you you will be seen, anyway, probably at the top right corner
24 00:03:23.000 --> 00:03:25.769 Gabor Szabo: that now you can. I can see myself.
25 00:03:26.950 --> 00:03:28.720 Leah Levy: I'll share again. Hold on.
26 00:03:29.060 --> 00:03:29.850 Gabor Szabo: Okay.
27 00:03:36.170 --> 00:03:40.759 Leah Levy: Oh, yeah, it was on a strange I think I was messing around with the settings before.
28 00:03:40.960 --> 00:03:41.710 Leah Levy: Okay.
29 00:03:46.550 --> 00:03:47.979 Gabor Szabo: Oh, now it's good!
30 00:03:48.590 --> 00:03:49.296 Leah Levy: Yeah, okay.
31 00:03:50.100 --> 00:03:50.510 Gabor Szabo: Okay.
32 00:03:51.450 --> 00:03:56.100 Leah Levy: Thanks for letting me know. So you can see just like there's the slideshow.
33 00:03:57.130 --> 00:03:57.710 Gabor Szabo: Yeah.
34 00:03:58.130 --> 00:03:58.790 Leah Levy: Yeah,
35 00:04:02.210 --> 00:04:22.959 Leah Levy: so how many of you ever perhaps worked on a data science project? You've built a machine learning model. And you've wished you could deploy it quickly for others to use. Or perhaps you've built a web application. But front end development isn't really your expertise. It's too complicated. So this is where stream it really comes into its own.
36 00:04:23.270 --> 00:04:41.560 Leah Levy: It makes it easy for python developers to and data scientists to create beautiful interactive web apps without needing any front end development expertise. So it's lightweight. It's really easy to use doesn't require, you know, hundreds of lines of code.
37 00:04:41.620 --> 00:04:56.920 Leah Levy: And there's a really strong community online. So there's people building like add ons constantly. And there's also a strong community of people happy to answer questions and help if you have any issues.
38 00:05:01.950 --> 00:05:10.450 Leah Levy: So Streamline allows you to turn your python scripts into interactive web applications and just a few lines of code. So you don't need to be. Know any like
39 00:05:10.620 --> 00:05:19.650 Leah Levy: break traditional web frameworks like Flask or Django. You don't need any HTML Css. Or javascript. It's all python.
40 00:05:20.640 --> 00:05:32.522 Leah Levy: You can easily customize your web application using like sliders, buttons, check boxes making it interactive. And you're able to capture user, input too.
41 00:05:34.180 --> 00:05:53.920 Leah Levy: The app automatically updates when you're coding in in whatever id prefer, like visual studio code, as soon as you update the code and save it then updates in the in the actual application. I'll show I'll do a demo of it a bit later, so you could see exactly what I mean.
42 00:05:55.020 --> 00:06:00.160 Leah Levy: And but that just like makes development much faster. So you can see your changes as you go along.
43 00:06:00.400 --> 00:06:05.189 Leah Levy: And it works really well with other python libraries, popular ones like
44 00:06:05.370 --> 00:06:11.689 Leah Levy: numpy pandas plotly, even data science ones like tensorflow and scikit-learn.
45 00:06:11.900 --> 00:06:18.939 Leah Levy: So it enables you to visualize data. You can build dashboards, graphs, charts and also
46 00:06:19.470 --> 00:06:23.439 Leah Levy: integrate machine learning models directly into your application.
47 00:06:26.840 --> 00:06:51.719 Leah Levy: So a bit about deploying machine learning models so often. In data science, you go. You put a lot of work into creating it in a model. You've got your data, you've cleaned it. You've built a model. You've tested it, optimized it. You've evaluated the performance. But the real key is to kind of surface that to your end users or your clients
48 00:06:52.170 --> 00:07:01.079 Leah Levy: and using stream that makes it easy. It's quite user friendly interface. And it can handle resource, intensive tasks.
49 00:07:01.690 --> 00:07:03.910 Leah Levy: And it's easy to deploy as well.
50 00:07:04.050 --> 00:07:14.830 Leah Levy: You a basic workflow could be something like loading a pre-trained model from pickle file or on something from hugging face or tensorflow.
51 00:07:16.480 --> 00:07:32.710 Leah Levy: collect input from users. So as soon as they could enter some text. If it's like a chat bot, they could use some sliders and then it uses the machine learning model to make predictions and display the results to users.
52 00:07:33.150 --> 00:07:39.510 Leah Levy: So I've created a couple of examples of
53 00:07:39.610 --> 00:07:46.359 Leah Levy: what it can do. Just like kind of basic one's a dashboard and one's uses a pre-trained machine learning model.
54 00:07:50.010 --> 00:07:59.530 Leah Levy: I'm gonna I've taken some screenshots, but I think it'd be better to just show it live. So I'm just gonna have a go showing like, can you see this.
55 00:08:00.660 --> 00:08:01.400 Gabor Szabo: Then like.
56 00:08:03.980 --> 00:08:06.170 Leah Levy: Because, yeah, the code.
57 00:08:06.620 --> 00:08:07.280 Gabor Szabo: Yes.
58 00:08:09.100 --> 00:08:14.939 Leah Levy: So I've just pre pre-built like this very basic dashboard.
59 00:08:15.070 --> 00:08:17.750 Leah Levy: What it does is
60 00:08:18.230 --> 00:08:24.410 Leah Levy: I've got some dummy data about British culture. I thought I'd make it relative to me.
61 00:08:25.030 --> 00:08:27.209 Leah Levy: and I've just put it into a.
62 00:08:27.210 --> 00:08:29.650 Gabor Szabo: Saying, maybe you can enlarge the fonts a little bit.
63 00:08:32.220 --> 00:08:32.970 Leah Levy: Yeah, let me.
64 00:08:33.276 --> 00:08:33.889 Gabor Szabo: Yeah. Thanks.
65 00:08:35.520 --> 00:08:36.020 Gabor Szabo: Think so.
66 00:08:38.250 --> 00:08:38.909 Gabor Szabo: Noon.
67 00:08:42.010 --> 00:08:43.020 Gabor Szabo: Okay, well.
68 00:08:43.020 --> 00:08:43.420 Leah Levy: Oh, 2.
69 00:08:43.429 --> 00:08:47.150 Gabor Szabo: Yeah, yeah, no, it's good. I see.
70 00:08:48.430 --> 00:08:49.330 Leah Levy: Pardon.
71 00:08:50.920 --> 00:08:51.859 Gabor Szabo: I think it's fine now.
72 00:08:52.500 --> 00:08:53.440 Leah Levy: Okay?
73 00:08:54.357 --> 00:09:02.049 Leah Levy: So in the terminal I just use the command stream. Let run. So I do. Stream lit.
74 00:09:02.210 --> 00:09:06.640 Leah Levy: run, and then the name of your file.
75 00:09:06.830 --> 00:09:13.420 Leah Levy: In this case it's in the app folder, and it's called English chat, Hi.
76 00:09:16.530 --> 00:09:21.744 Leah Levy: and it takes a couple of seconds and it should pop up in like your browser.
77 00:09:23.780 --> 00:09:28.030 Leah Levy: so here you can have you stream it up in your browser. It's popped up here.
78 00:09:29.430 --> 00:09:37.429 Leah Levy: and here's the very basic app that I built in the top right hand corner. You see it running
79 00:09:38.360 --> 00:09:42.490 Leah Levy: and then there's a option here to deploy. If you want. If you're ready to deploy it.
80 00:09:43.405 --> 00:09:45.339 Leah Levy: Oh, what's this?
81 00:09:48.310 --> 00:09:49.360 Leah Levy: Okay?
82 00:09:56.720 --> 00:10:03.289 Leah Levy: If this doesn't work, I will just show you the screenshot instead.
83 00:10:03.890 --> 00:10:05.980 Leah Levy: Okay, so I've saved it here.
84 00:10:06.750 --> 00:10:10.696 Leah Levy: And you'll see an example now, actually, of
85 00:10:12.450 --> 00:10:23.590 Leah Levy: of how it updates in real time. So I've updated the file, the source file. And you see in the top right hand corner. Now there's an option I'll just zoom in and make it a bit bigger.
86 00:10:25.070 --> 00:10:28.779 Leah Levy: but it says source file change, and it gives you the option. Rerun
87 00:10:29.161 --> 00:10:33.799 Leah Levy: and they can click, always rerun. So I don't have to click that every time. So if I try that.
88 00:10:34.150 --> 00:10:38.630 Leah Levy: and it's work now. So this is just like a
89 00:10:39.100 --> 00:10:46.520 Leah Levy: basic application. There's a dropdown menu here, so you can select the category if I wanted to. Just see landmarks. See that
90 00:10:46.830 --> 00:10:50.740 Leah Levy: some reason it's giving me error sports
91 00:10:54.010 --> 00:11:03.280 Leah Levy: and the size of each bubble is the size of visitors per year, and you can hover over, and it gives you a little bit more information. And then if
92 00:11:04.900 --> 00:11:12.589 Leah Levy: yeah, I think I think the map plot little bit is broken on bottom. So that's 1 example. The next
93 00:11:13.270 --> 00:11:22.030 Leah Levy: application. Let me just cancel this. I'll just do control. C, let's run another
94 00:11:23.102 --> 00:11:30.350 Leah Levy: another. This is more of like a machine learning one. So I just run, stream, let run and
95 00:11:31.820 --> 00:11:32.980 Leah Levy: spell check.
96 00:11:50.550 --> 00:11:54.489 Leah Levy: Oh, I know why it's giving me an error because I haven't installed the packages.
97 00:12:09.660 --> 00:12:13.009 Leah Levy: I'm actually just using poetry library, which
98 00:12:13.200 --> 00:12:34.820 Leah Levy: it's it's not sure how common, how widely it's used. But it's a 3rd party. It's like A, it's not an inbuilt typically, you might manage your libraries, use your dependencies using like requirements, dot text file and then have a virtual create a virtual environment. But I'm just.
99 00:12:35.420 --> 00:12:45.569 Leah Levy: I've got used to using poetry, which is another like dependency package. So and that's just
100 00:12:46.130 --> 00:12:48.370 Leah Levy: just to clarify exactly what it is.
101 00:12:51.940 --> 00:12:58.580 Leah Levy: Yeah, that's not working. So let me just show you on the on the slide show.
102 00:12:59.580 --> 00:13:00.750 Leah Levy: Sorry?
103 00:13:09.314 --> 00:13:18.655 Leah Levy: What this is. Is. It imports text blog, which is a light, very lightweight kind of natural language processing library
104 00:13:20.020 --> 00:13:26.119 Leah Levy: and what happens is you put in your spelling. So you put in some text. In this case
105 00:13:26.530 --> 00:13:35.059 Leah Levy: I'm so bad at spelling spell really wrong, and then it returns the correct spelling and then in the top right. You can see it's very kind of
106 00:13:35.320 --> 00:13:47.810 Leah Levy: simply. There's only like 16 lines of code. It's quite lightweight. And I've put a link here to more community projects. You can see on on the stream website.
107 00:13:48.440 --> 00:13:50.030 Leah Levy: they've actually got
108 00:13:51.100 --> 00:13:59.750 Leah Levy: community projects. You can kind of get an idea of flavor, of exactly what's possible. So this one's quite cool. This is like a map.
109 00:14:00.445 --> 00:14:06.500 Leah Levy: Application that somebody's built that's called pretty map, where you kind of visualize
110 00:14:07.361 --> 00:14:11.959 Leah Levy: maps in like different, cool, different, cool ways.
111 00:14:13.051 --> 00:14:22.290 Leah Levy: But just so you can get kind of get an idea of like, it's quite personalizable. It doesn't have to look like they did. All the applications don't necessarily have to look the same.
112 00:14:38.920 --> 00:14:40.470 Leah Levy: Sorry gone too far.
113 00:14:45.890 --> 00:14:53.241 Leah Levy: Okay. So I wanted to talk about deployment. So I mentioned. It's there's different options to deploy.
114 00:14:54.210 --> 00:14:59.230 Leah Levy: Just gonna wait for the slides to kind of sync.
115 00:15:07.560 --> 00:15:08.619 Leah Levy: Not sure.
116 00:15:09.560 --> 00:15:10.799 Leah Levy: Okay, there we go.
117 00:15:13.880 --> 00:15:27.930 Leah Levy: There's a there's a couple of different options you could deploy locally, which is kind of what we've done. Just before we do the stream that run. But in most cases you want to deploy it to a cloud or servers.
118 00:15:28.370 --> 00:15:31.159 Leah Levy: So there's stream that has its own kind of
119 00:15:31.370 --> 00:15:39.799 Leah Levy: built like customized deployment option called the stream community cloud where you can deploy from, get straight from Github.
120 00:15:40.551 --> 00:15:46.568 Leah Levy: But that also supports other deployment options like Docker, Aws
121 00:15:48.475 --> 00:15:53.880 Leah Levy: and all these other options. The another benefit of the community cloud is.
122 00:15:54.720 --> 00:16:12.700 Leah Levy: you can it provides you with analytics data. So how many people have clicked on on your onto your dashboard. Total viewers, most recent viewers, timestamps of people's last visit. So you can kind of get an idea of when people have have used your application.
123 00:16:14.520 --> 00:16:18.800 Leah Levy: So I want to talk about the testing framework in the app.
124 00:16:18.910 --> 00:16:21.500 Leah Levy: This is something.
125 00:16:22.090 --> 00:16:35.319 Leah Levy: Last time I gave this talk at Pi Web in Tel Aviv. Someone asked me about testing. And I thought, Oh, yeah, that's I've not really used the testing framework. So I thought, I put a section in here to to show you kind of how I've done it.
126 00:16:36.415 --> 00:16:58.584 Leah Levy: So stream that has its own. You can use pi test, and and those usual kind of testing frameworks and stream. It has its own framework, which enables developers to build and run headless tests, which I executes the app code directly. So it simulates that user input and inspects the output for correctness.
127 00:16:59.090 --> 00:17:07.560 Leah Levy: for those who don't know headless tests is like a way to run automated browser tests without having, like the user interface.
128 00:17:08.027 --> 00:17:13.299 Leah Levy: So it's a more efficient way of testing the application because it doesn't need to like render the HTML.
129 00:17:13.569 --> 00:17:27.959 Leah Levy: It just sends requests to the server the same way like you would do in a browser, and it's much faster because you don't need to wait for a page to load, and it integrates well into your like any crcd pipelines you might have as well.
130 00:17:29.670 --> 00:17:47.450 Leah Levy: So an example of testing. So on the left hand side. I've written what might be a more traditional way to write a test. So you would import streamlet and also import textblob, which is the library I mentioned before that we used for the spell checker.
131 00:17:47.660 --> 00:17:49.590 Leah Levy: You kind of set up a
132 00:17:50.100 --> 00:17:57.630 Leah Levy: set up the app just as it appears in that, just as what you've to kind of mirror what you've written
133 00:17:58.258 --> 00:18:07.070 Leah Levy: and have some simulated user input and then load the text blob and then run the
134 00:18:07.520 --> 00:18:15.440 Leah Levy: run. The text Blob Library to generate the correct spelling, and then have an assert to correct, to ensure that
135 00:18:15.740 --> 00:18:23.610 Leah Levy: that is, what the output is is what you've expected is that should be the corrected spelling of what you've inputted.
136 00:18:24.489 --> 00:18:32.130 Leah Levy: But on the right, all you need to do is run install the streamer testing framework
137 00:18:32.250 --> 00:18:45.980 Leah Levy: with app test. App test is is what simulates the running of the app, and it provides different methods to set up, manipulate and inspect the app via the Api instead of doing it in the browser
138 00:18:49.370 --> 00:18:57.074 Leah Levy: And then I've just written a function to test the spelling. So you you've got app test, which runs the
139 00:18:57.710 --> 00:19:03.239 Leah Levy: which runs the application as if I was running it in the terminal.
140 00:19:03.950 --> 00:19:09.750 Leah Levy: I is simulate an input of the incorrect spelling and run that.
141 00:19:10.520 --> 00:19:16.360 Leah Levy: and then the assert that the corrected text equals the correct spelling.
142 00:19:17.358 --> 00:19:25.871 Leah Levy: And then I've just written some a couple of other tests this next function just asserts that the
143 00:19:27.180 --> 00:19:33.809 Leah Levy: the application is running and not producing any exception errors. And then this one tests that the title is
144 00:19:33.990 --> 00:19:36.970 Leah Levy: displaying the correct title as we've expected.
145 00:19:39.550 --> 00:19:48.459 Leah Levy: so you'll see it's much quicker. It's fewer lines of code. And you could just run it using like in the terminal using. I test
146 00:19:48.680 --> 00:19:51.339 Leah Levy: as you would like any other testing.
147 00:19:54.660 --> 00:20:03.330 Leah Levy: you can add multiple pages to an app. So you kind of create a new pages folder in the same folder where your application is running
148 00:20:03.934 --> 00:20:15.910 Leah Levy: and then you can give it. You can, whatever you name the whatever you name. The file is what kind of appears on the sidebar and you can amend the
149 00:20:17.040 --> 00:20:23.254 Leah Levy: you can amend the content as you would like any other application. I've put a link in here.
150 00:20:24.030 --> 00:20:25.680 Leah Levy: just so you can kind of
151 00:20:27.610 --> 00:20:30.949 Leah Levy: I was gonna show how to
152 00:20:32.609 --> 00:20:36.229 Leah Levy: it. It gives a good example rather than me, like giving
153 00:20:36.680 --> 00:20:41.279 Leah Levy: setting up lots of different ones. But you can kind of see the from the. It's got a good
154 00:20:41.750 --> 00:20:44.358 Leah Levy: kind of demo page.
155 00:20:49.446 --> 00:20:53.703 Leah Levy: hey? It's got a hello page. It's got a plotting demo.
156 00:20:54.980 --> 00:20:58.089 Leah Levy: yeah, you can have a look in your own time if you like.
157 00:21:24.610 --> 00:21:27.299 Leah Levy: Sorry. My computer's running super slow.
158 00:21:30.410 --> 00:21:32.449 Gabor Szabo: So I just I was just saying.
159 00:21:33.350 --> 00:21:38.320 Leah Levy: It's also supports chat inputs. So oops.
160 00:21:38.920 --> 00:21:47.796 Leah Levy: So if you if you everybody wants to build their own chat bots nowadays, and it provides support for that
161 00:21:48.380 --> 00:21:55.700 Leah Levy: where it kind of mimics a user. And it's got like an assistant with these like different emojis
162 00:21:56.242 --> 00:22:02.159 Leah Levy: so as if you were speaking to a person. Similar to kind of.
163 00:22:02.720 --> 00:22:07.300 Leah Levy: you know, like chat. Gpt's got an assistant kind of answer.
164 00:22:07.560 --> 00:22:30.921 Leah Levy: You can also like stream, the reply, you know how chat gpt kind of streams it, or writes it word by word, instead of just giving you an answer right away. As if somebody just to like make it look like somebody's typing. You can add a delay as well of like a couple of seconds to make it seem like it's thinking about a reply.
165 00:22:32.280 --> 00:22:52.160 Leah Levy: And different things like that. So this is just a an echo bot which just echoes, echoes whatever you type into it. Obviously not using any large language models. But you can use kind of any large language models that you want, and kind of just plug it in to a streaming dashboard.
166 00:23:01.040 --> 00:23:04.700 Leah Levy: So finally, just some additional features
167 00:23:05.710 --> 00:23:16.739 Leah Levy: which I've oops added kind of some links to. So, as I mentioned before, it's got like a whole wide range of different input widgets. And
168 00:23:17.180 --> 00:23:32.760 Leah Levy: I didn't kind of include them all on the dashboard, because I think that this page actually does it in a nicer way. You can see it's got different buttons, check boxes, feedback options, radio buttons.
169 00:23:33.550 --> 00:23:35.240 Leah Levy: sliders.
170 00:23:35.966 --> 00:23:39.269 Leah Levy: Numeric inputs. Yeah, I could just go on, but
171 00:23:40.150 --> 00:23:49.400 Leah Levy: pretty much you know anything you would need to build a nice looking app. It's got another
172 00:23:49.840 --> 00:23:56.568 Leah Levy: another thing is status elements of like progress bars loading
173 00:23:58.890 --> 00:24:03.326 Leah Levy: call out messages, but error boxes I've used before.
174 00:24:04.080 --> 00:24:08.824 Leah Levy: I can't say I've used the balloon ones, but that looks fun
175 00:24:12.470 --> 00:24:20.803 Leah Levy: And it also has integration for like interactive maps, as we saw before, like that, the map application that I
176 00:24:21.340 --> 00:24:27.209 Leah Levy: And it's also you can build interactive charts with like plotly and other similar libraries.
177 00:24:27.640 --> 00:24:36.139 Leah Levy: You can cache large data sets. So particularly when you're working with machine learning models. You're often dealing with
178 00:24:36.250 --> 00:24:48.150 Leah Levy: lot really, really, large data sets which you can cache into memory. So rather than reloading the reloading like a data set each time it can just store it in memory.
179 00:24:50.161 --> 00:25:12.448 Leah Levy: From a safety point of view. I've just looked at the privacy policy and took this this 4th bullet point straight from the privacy policy which is stream that cannot see and does not store any information contained inside stream. The apps like text shots and images, but as general advice, I would say, not to expose sensitive data.
180 00:25:13.020 --> 00:25:17.580 Leah Levy: unless you yeah.
181 00:25:18.310 --> 00:25:40.254 Leah Levy: you can expect, unless you're kind of like it's locked down. It's in a safe, secure environment. And you've got like full access controls and ensure your app is also protected from malicious input, like sequel injections, because, you know any. Any application is susceptible to to being hacked. So I guess just
182 00:25:41.480 --> 00:25:48.060 Leah Levy: be wary of this is probably no different either to to malicious input like that.
183 00:25:52.590 --> 00:25:53.465 Leah Levy: But
184 00:25:54.630 --> 00:26:01.731 Leah Levy: yeah, that's all I prepared for now, but happy to answer questions and go into into more detail on different bits.
185 00:26:03.040 --> 00:26:07.319 Leah Levy: but thank you for your time, and happy to answer any questions.
186 00:26:12.910 --> 00:26:15.524 Gabor Szabo: So thank you for the presentation.
187 00:26:17.190 --> 00:26:25.759 Gabor Szabo: I heard it the second time. I really like the testing part. I always think about testing when I, whatever I try to show.
188 00:26:25.890 --> 00:26:26.970 Gabor Szabo: And
189 00:26:27.810 --> 00:26:38.989 Gabor Szabo: if anyone has questions, then please ask. Now we can also, after the recording, after we stop the recording, we can stay around and have a conversation without the recording.
190 00:26:39.240 --> 00:26:45.520 Gabor Szabo: But anyway, it seems that there are no questions now.
191 00:26:46.440 --> 00:26:50.600 Gabor Szabo: So, Leah, thank you very much for for this presentation.
192 00:26:50.780 --> 00:26:56.499 Gabor Szabo: If we'd like to add anything more, I mean, I'll I'll have the links below also the the video.
193 00:26:59.180 --> 00:27:05.545 Gabor Szabo: So thank you for for giving this presentation. And thank you. Thank you. Thanks. Everyone who was attending. And
194 00:27:06.420 --> 00:27:11.800 Gabor Szabo: and everyone who was watching. So please remember to like the video and follow the Channel and see you
195 00:27:11.980 --> 00:27:15.530 Gabor Szabo: at one of our next one of our upcoming events.
196 00:27:15.960 --> 00:27:16.850 Gabor Szabo: Bye, bye.
197 00:27:18.140 --> 00:27:19.260 Leah Levy: Thanks, bye.
