OK, hi, everyone. Thanks for coming. I'm very sorry about the technical difficulties. We clearly should have had a bit more time to set up and prepare. And I really don't please try nothing to look ahead too far in the slides. I know it's going to be difficult, but there you go. OK, so I'm going to talk about web scraping best practices. I originally called this advanced web scraping because we're going to touch on a lot of advanced topics. But it's not advanced in the sense that you need to be past the beginner level or anything to understand it. So I changed it to best practices. And I hope that everybody can follow this talk and understand what's going on. If you can't, please just shout or let me know. So a bit about me. Let's see. Eight years ago about that, I started scraping kind of an anger. And that was around the time when we did the scraping web scraping framework. And since that time, we've been involved in a couple of other projects, including Portia and Frontera. If you don't know what they are, don't worry. I'll get to them later. So why would you want to scrape? Well, lots of good sources of data on the internet. And actually, we come across a lot of companies and universities and research labs of all different sizes who are using web scraping. But getting data from the web is difficult. You can't rely on APIs. You can't rely on semantic markup. So that's where web scraping come in. These are some stats. You probably can't read them very well because it's small. But basically, web scraping has been on the increase recently. We've seen that ourselves, but this has been also something we've seen from other companies reporting. These stats are from a company called Incapsula that provide anti-bot scraping technology. And it's a sample of their customers. So it's probably not completely representative of the internet as a whole. But still, it's very interesting to see. And another thing that I can see from this as well is that smaller websites have a larger percentage of bot traffic, probably because they have less users, but it's something to keep in mind. Especially if you write bad bots, they cause more trouble for smaller websites. Smaller websites might have bandwidth limits, for example. And many HTTP libraries, they don't compress content. So you'll easily go over their bandwidth limits. Also, of course, doing a bad job means your web scrapers are very hard to maintain. This is a notorious problem, of course, because websites change. So when I think about web scraping, I like to think of it in two parts. The first is actually getting the content. So it's finding good sources of content and downloading it. And then the second is the extraction. Actually, extracting structured data from that downloaded content. And I've kind of structured this talk in two parts as well. That follows this. So as an example of web scraping, I just said that scraping help gets scraped all the time. And it's not just people testing out scrappy or something like that or our tools. But actually, a couple of weeks ago, we posted a job ad on our website. And the next day, it was up on a job listing board. And none of us posted it there. So we thought, well, how did that happen? And I think we were probably scraped. So a question for the audience would be to think about how would you write that scraper? I would break it down into, OK, how do I find good sources of content? And how do I extract that data? It turns out that we tweeted about the job. So hashtag remote working. So maybe somebody picked it up from Twitter, got retweeted. That would be an easy source of content. And we did use semantic markup. So perhaps they extracted it from that. And that's relatively, to write such a scraper that could do this is a relatively easy task. You could do it in a day, maybe. But then if you wanted to handle cases where people didn't use semantic markup, or you wanted to find people who didn't tweet about it or post it to some other website, then it becomes a much bigger and much more complex task. And I think that highlights the scope of web scraping. From the very easy pool of fun hacks that don't take very long to the very ambitious and very difficult projects that happen. So moving on to downloading. Yeah, I've got to mention the Python Request Library. Probably many people know it. It's a great library for HTTP. And doing simple things is simple, as it should be. But when you start scraping at a little bit more scale, you really want to worry a bit more about a few other things. Like, for example, retrying requests that fail. Certainly, when we started out, you'd run a web scrape, and it might take days to finish. And then about three quarters of the way through, you get a network error, or you get the website itself that you're scraping, but suddenly return 500 internal server error for 10 minutes.  So yeah, you want to think about that. In this example, you can see I'm using a session. Well, I don't know if you can see it or not, because it's small. But consider using sessions with Python requests, sessions handle cookies. They also use ConnectionKeepAlive. So you don't end up repeatedly opening and closing connections to the sites you scrape. But I would say, as soon as you start crawling, you really want to think about using Scrapy right away. This little example here is not much code. It uses Scrapy's CrawlSpider, which is a common pattern for scraping, for crawling. Just defining one rule, a start URL, and that's enough to go from the our your Python website for this conference to actually follow all the links to speakers, and you just need to fill in some code to parse the speaker details. So it's really not much code. And it solves all the problems, like highlighting or solves all the problems, like retrying, et cetera. You can cache the data locally. Which is good if you're going to live demo stuff. Yeah. So a single crawl like that often turns into crawling multiple websites. At PyCon US in 2014, we did a demo. And it's up on Scraping Hub's GitHub account. It's called PyCon Speakers, where we actually scraped data from a whole lot of tech conferences. This is a really good example to look at because it shows a way to manage and how a Scrappy project looks when you've got a lot of spiders. And Scrappy provides a lot of facilities for managing that. You can list all the spiders that are there. A spider is a bit of logic that we write for a given website. And it also shows best practices in terms of it's easy, but Scrappy, to put common logic in common places and share it across multiple websites. When they're crawling the same type of thing, there's a lot of scope for code reuse. So definitely for Scraping multiple websites. Yeah, Scrappy's no-brainer. So some tips for crawling. Find good sources of things. Some people maybe might not think about using sitemaps. Scrappy actually has a sitemap spider that makes this very easy and transparent. But often it can be a much more efficient way to get to content. And that also means, of course, don't follow unnecessary links. You can waste an awful lot of resources for everybody following stuff that doesn't need to be followed. Consider crawl order. So if you're discovering links on a website, it might make sense to crawl breadth first and limit the depth you go to. This can help you avoid crawler traps where maybe you're, I don't know, repeatedly scraping a calendar, for example, and just going through the dates is a common example. I used to work in a company before that had a search engine, and crawlers every now and then would follow some link into it and would follow all the search facets and turn every permutation and combination of search. And this generated huge load, of course. So as you decide to scale up, so I was talking here about maybe single-website scrapes, which is, I guess, the most common use case, at least, especially for Scrappy. And single-website scrapes can be big, right? I mean, we frequently do maybe hundreds of millions of pages. But at scale, say, for example, you're writing a vertical search or a focused crawler, then we're talking maybe tens of billions or even hundreds of billions of discovered URLs. So you might crawl a certain set of pages, but the amount of URLs you discover on those pages, so your entire state that you need to keep in your URL frontiers can be much, much larger. So maintaining all of that is a bit of a headache. It's a lot of data. And one common way to do it is people just write all that data somewhere, and then perform the big batch computation to maybe to figure out the next set of unique URLs to crawl, typically using Hadoop or MapReduce. It's a very common thing. Maybe not just a good example of that. And then incremental crawling would be where you are. Continuous crawling, actually, would be where you're continuously feeding your URLs to your crawlers. This has the advantage that you can respond much more quickly to changes. You don't need to stop the crawl and resume it. But also, nowadays, maybe you want to repeatedly hit some websites. Maybe you're following social media or something like that or good sources of links. So it's much more useful, but it's much more complex at the same time, and it's a harder problem to solve.  But it's something really you want to consider when you're doing it on any scale. I think almost anybody can fire up a lot of instances nowadays on EC2, or your favorite cloud platform, and just download loads of links, download loads of pages really quickly without putting much thought into what those pages are, particularly the impact it's going to have on the websites are crawling. In a larger crawl, where you're crawling from multiple servers, you would typically only crawl a single website from a single server. And that server could then maintain politeness. So you can ensure whatever your crawling policies are, you don't break it. So, Frontera, I thought I'd briefly mention it. Alexander Sibirikov gave a talk on it yesterday. This is a Python project that we worked on, or we're working on, that implements this crawl frontier, so it maintains all the state of it. It maintains all the state about visited URLs and tells you what, you should crawl next. There's a few different configurable backends to it. So, you can use it embedded in your scrappy crawl, or you can just use it via an API with your own thing.  So, if you, say, want to go back to some pages more often than others, and maybe, you know, keep content fresh, it can do that. And I think Alexander particularly talked about doing it at scale. And he's going to be talking about that in the poster session as well. So, please come visit. So, just to summarize quickly, what we talked about downloading. Request is an awesome library, for simple cases. But once you start crawling, it's better to move to scrappy quickly. Maybe you wouldn't even want to start there. And if you need to do anything really complicated, or sophisticated, or at scale, consider Frontera. So, moving on to extraction. Extraction is the second part that I wanted to talk about. Of course, Python is a great language for extracting content, or for messing with strings, or messing with data. There's probably a lot of talks at this conference about managing data with Python. But even just the simple, you know, built-in features to the language and the standard library make it very easy to play with text content. Regular expressions, of course, is one thing that's built into the library, and probably, yeah, I should mention something about it. Regular expressions are brilliant for textual content. Yeah, it works great with things like telephone numbers, or postcodes. But if you find yourself ever matching against HTML tags, or HTML content, you've probably made a mistake, and there's probably going to be a better way to do it. I see this code all the time of regular expressions, and yeah, it works fine, but it's hard to understand and to modify. And often, it actually doesn't work fine. So other techniques, well, use HTML parsers. So we have some great options. Yeah, so if you want, this is when you want to extract based on the content, based on the structure of HTML pages. So often, you will say, okay, this area here, underneath that table, HTML parser is absolutely the way to go. Yeah, so, just a brief example. Oh, yeah, on the right-hand side, I just had some examples of HTML parsers. LXML, HTML 5.0, 5.0, beautiful soup, gumbo, and of course, Python has its own built-in HTML parser. I'll talk about them in a bit more in a minute, so don't worry if you can't see that. So, just as a brief example of what they do is take some raw HTML here that looks like text and create a parse tree. My favorite way of dealing, and then use some technique. Usually, these parsers provide some method to navigate this parse tree and extract the bits you're interested in. I don't know if you can see that, so I'll skip this quickly, but I quite like XPath as a way to do this. In this case, just select all bold tags or a bold tag under a div or, you know, the text from the second div tag. It lets you specify rules. It's really worth learning if you're going to be doing a lot of this. Here's an example from Scrapy. You don't really need to read that.  So this is probably definitely the most common way to scrape content from a small set of known websites. I definitely want to mention BeautifulSoup as well. This is a very popular Python library. Maybe in the early days, it was a bit slow, but the more recent version, you can use different parser backends. So you can even use BeautifulSoup on top of LXML. The main difference with the example I showed previously is that BeautifulSoup is a pure Python API. So you can navigate content using Python constructs and Python objects versus XPath expressions. The other thing is, of course, you might not need to do this at all. Maybe somebody has already written something to extract what you're looking for. So, yeah, definitely, maybe there's stuff you wouldn't even think of. So in the early days, we wrote a log-in form module for Scrapy that automatically fills in forms and logs them into websites. We have a date parser module that takes textual strings and can build a data object from it. And webpagers, another project that we wrote which looks at a HTML page and will pull out links that perform pagination, as well as webpages. I was going to live-demo this, but I think we're probably short on time and, yeah, maybe it's not worth tempting face. We had enough technical problems already. But Portia is a visual way to build web scrapers. It's applicable in many of the cases where I had previously mentioned where we would use XPath or BeautifulSoup. But it's advantages. It's not as applicable. It's usually say, oh, I want to select this element. This is the title. This is the image. This is the text. I was going to demo this about scraping the EuroPython website. Maybe if somebody wants to drop by our booth later, I can do it. I can show you. But it's really good. It can save you a lot of time. However, it's not very good. If you want to use extraction logic, it might not always work with this. Of course, if you want to use any of the previously mentioned stuff, like automatically extracting dates and things that might not be built into Portia yet. So scaling up extraction, Portia is great. It's much quicker to write extraction for websites. But at some point it becomes pointless again. You might be scraping 20 websites. But what about tens of thousands or maybe even hundreds of thousands? At this point, you want to look for different techniques. There are some libraries that can extract articles from any page. They're easy to use. I want to focus quickly on a library called WebStruct that we worked on that helps with automatically extracting data from HTML pages. In the example, I'm going to use this named entity recognition. In this case, we want to find elements in the text and assign them into categories. So we start with annotating web pages. So of the type of stuff, we label web pages basically with what we want to extract as examples. We're going to use a tool called Web Annotator, but there are others. Here's an example of labeling. In this case, we want to find organization names. So the old tea café is an organization and we would label it within a sentence, within a page. That format is not so useful for machine learning and for the kind of tools we want to use. Of course, that text is split into tokens. Each token in this case is a word and we label every single token in the whole page as being either outside of what we're looking for as being the beginning of an organization or inside an organization. Given that encoding, we can apply more standard machine learning algorithms. In our case, we found conditional random fields as a good way to go about it. But an important point is that it needs to take into account the sequencing of tokens. The sequencing of information. Some features. We feed it basically not just the tokens itself, but the actual features. The features can be things like about the token itself, but they can also take into account the surrounding context. This is a very important point. We can take into account the surrounding text or even HTML elements that it's embedded in. It can be quite powerful. One way to do it, and this is what we've been doing recently, is to use our WebStruct project. This helps load the annotations that were done previously in WebAnnotator. Call back to your Python modules that you write yourself to do the feature extraction. And then it interfaces with something like Python CRF Suite to actually perform the extraction. This is just briefly to summarize. We use slightly different technologies depending on the scale of extraction. We have HTML parsing and Porsche are very good for a single page or a single website. Or for multiple websites if we don't have too many. The machine learning approaches are very good if we have a lot of data. We compromise a bit on maybe the accuracy. But that's the nature. I just wanted to briefly mention a sample of a project we've done recently. Actually, we're still working on it. You might know the Saatchi art gallery. We did a project with them to create content for their global gallery guide. This is an ambitious project to showcase artworks and artists and exhibitions from around the world. It's a fun project and it's nice to look at artworks all day. Of course, we use Scrapy for the crawling. We deployed it to Scrapy Cloud which is a scraping hub service for running Scrapy crawls. We used WebPager one of the tools I mentioned earlier to actually paginate. The crawl, we prioritize the links to follow. Using machine learning so we don't waste too many resources on each website we scrape. Once we hit the target WebPages we then use WebPager to paginate. That's the crawling side. On the extraction side we use WebStruct very much like I previously described. One interesting thing that came up I thought when we were extracting images for artists we often got them wrong and we had to use a classification to... We actually classified them based on the image content using face recognition to see which one were artists versus artworks. It's working pretty well. This is in Scraping 11,000 websites hopefully to continue and increase. And so one important thing of course is to measure accuracy to test everything, improve incrementally and it's also good to not treat these things too much like a black box to try and understand what's going on. Don't make random changes. It tends to not work so well.  It seems like we have everything to go and scrape at large scale but there's still plenty of problems and we're just going to touch on a few in the last five minutes. Of course web pages have an irregular structure. This can break your crawl pretty badly.  Other times I don't know, maybe the developers have too much time in their hand and they write a million different kinds of templates. You can discover that they're halfway through that the website's doing multivariate testing and it looks different the next time you run your crawl. I wish there was a silver bullet or some solution I could offer you for these but there's not. Another problem that will come up is sites requiring JavaScript are browser rendering. We tend to have... We have a service called Splash which is a scriptable browser that presents an HTTP API. So this is very useful to integrate with Scrapy and some other services. You can write your scrapers in Python and just have the browser... you know, have Splash take care of the browser rendering and we can script extensions based in Lua. Selenium is another project. If you start thinking like, okay, follow this link, type this here. Selenium is a great way to go. Oh, yeah. Finally, of course, you can look at Web Inspector or something, see what's happening. This is maybe the most common thing for Scrapy programmers because it's quite efficient. You can just... Often there's an API behind the scenes that you can actually use instead. Proxy management is another thing that you might want to consider because some websites will give you different content depending on where you are. We called one website that actually did currency conversion so I thought I was being very clever by selecting the currency at the start but it turns out the website did a double conversion and some products were like a center two different so didn't discover any of the changes. So they ban hosting centers often where they've had one or two abusive bots. It could be somebody else. This is just part of the nature of Scraping in the cloud. For reliability, sometimes for speed, you might want to consider proxies. Please don't use open proxies. They sometimes modify content. It's just not a good idea. Tor, I generally don't like it for large content Scraping. It's not really what it's intended for. But we've done some things with maybe government agencies or security in the security area where we really don't want any blowback from the Scraping and it really needs to be anonymous. Otherwise, there are plenty of private providers but very in quality. Finally, last slide is just briefly want to mention about ethics of web scraping. I think the most important question to ask yourself is what harm is your web scraping doing? Either in a technical side or with the content that you scrape or are you misusing it? Are you hurting the sites you're getting it from? Yeah, so on the technical side crawl at a reasonable rate and it's best practice to identify yourself via user agent and to respect robots.txt especially on broad crawls. That's when you visit lots of websites. That's it. We have some questions. Thank you. Wonderful talk, one question. Imagine you have to login into some website and if you use a tool that will generate some fake credentials and stuff, for example, you have a profile of a programmer or a farmer or a rockstar and so on. Thanks. Okay, so about logging into websites the tool I mentioned just finds the login box and lets you configure your user ID that you want to use. So it doesn't handle managing multiple contacts. I have seen people do that but it's not something I've done myself. Yeah, so sorry, that's all I can say about it really. Any other questions? Hi. First of all, thanks for the scraping library. I mean, it's an awesome thing and we're using it on a daily basis. That's great to hear. Actually, these guys you should be thanking in the audience. I don't know why they're all rolling but stand up guys, stand up. But these are the contributors really here. There's more of them up there but I don't know why they're being shy. Sorry. I probably have a few questions but I'll only ask a couple, I guess. First is I'd like to mention PyQuery. That was an awesome development change for us from Xpath and this is one thing we use regularly and it proves... Yeah, I've heard of it but I haven't really paid it properly so we'll check it out. I think there might be scope for including other approaches to extraction. And one is did you maybe think about master spiders or spiders that can... You said that APIs are brittle but you could still think of web frameworks and some behave in similar ways and maybe you could get a way to extract certain information from certain kinds of websites. Yeah, absolutely. We have a collection of spiders for all the forum engines, for example. It's not individual websites but it's the underlying engine powering it and that works really well. We're building collections of those kind of things. One example about APIs, I didn't really meant to diss API in general they're often quite useful but in some cases they don't have the content you're after and in some cases the content is maybe lags behind or it's a bit less fragile than what's on the website. That's been my experience but definitely if there is a web API available you should check it out. It works fine, it's creepy too. Okay, and just last question a little bit more technical. Do you have plans for anything to, I don't know, to handle throttling or to handle robots.txt or to reschedule 500 errors or something like that. I know there's an autothrottle plugin but that does I mean it slows you down significantly on a good website though it does work for slow websites. Thanks. You're welcome. Yeah, throttling is an interesting one and often internally what we do is we deploy with autothrottle by default and then override it when we know the website can do better differently. So it is a case, especially when you're crawling a single website or a small set of websites, it's worth tuning yourself, it's hard to find good heuristics and definitely it's something we do all the time when we write individual scrapers. I'd be interested in your thoughts on how you could come up with some better heuristics by default. It's definitely a very interesting topic. Yeah, and retrying, again Scrapey does retry stuff by default but you can configure for example the HTTP error quotes that signify an error that you want to be retried because they're not always consistent across websites. Thank you. So a slight follow up to the retry thing. You mentioned this briefly under the talk. Do you actually like do things like backoffs and jitters and stuff because from my job we have very interesting situations with synchronized clients and other fun. It's good to avoid. Yeah, definitely. And actually I glossed over a lot of details. I mean I said we run in Scrapey Cloud but that takes care of a lot of the kind of infrastructure that we typically need. And Alexander gave a talk on the crawl frontier which is crawling at scale and there's a lot more that goes into that that it happens outside of Scrapey itself. The first thing of course that we noticed as soon as we started crawling from EC2 is DNS errors all over the place. But there's several technical hurdles that you need to overcome I think to do a larger crawl at any scale. Okay, thank you Shane. Thanks very much.


So in today's tutorial, we'll be sharing a little bit about how we do video editing. So in the last tutorial, we showed you how to capture the video of the presenter as well as their laptop screen. So what we will get is basically two videos, the video of the person talking and as well as the video of the laptop screen of the presenter. So right now, I'll be showing you a little bit how I do the video editing using iMovie. So if you're a Mac user, this will be very useful for you. So first of all, let's review what the videos that we have had so far. Alright, so we have two videos that we took from the last tutorial. So the first video is of the screen. This is how it sounds like. If you say, hello world, this is Michael Chang. So I'm showing you now the engineer's SG website. So this is basically how it looks like right now. And the other video is from the camera. So here I have turned on the recording on the Q4 camera. So it's looking at me as I make the presentation. Right, I'm showing the engineer's SG website. So at the same time as I do the recording, I will also be recording on the screen. And if you say, hello world, this is Michael Chang. So I'm showing you now the engineer's SG website. So this basically how it looks like right now. So these are two videos that are there. So what I do next is I start up iMovie. So iMovie is the software we use to edit the files and to put them together. So in iMovie, what we want to do next is actually import both videos into iMovie. So this is what I have right now in iMovie. So first I'll start by creating a new movie with only teams. Test one. So next thing we do is we look at introducing a couple of areas in the iMovie. So on the left we have the libraries, which are basically all the video files that you have. The video sources of files that you can get. And over here is the media that is being used in your project. At the bottom part is the timeline. So where we see all the videos as you edit them, you can put them in layers. And on the top right is the preview window where you can see the video as is being previewed. So first of all, we need to create a new event. The event is kind of like a list of all the events like a folder. Think of it as a folder where you keep all your files in. So first of all, this will be a sample video, a sample vid. Let's create that. So we have a new folder or event for keeping our files. You click on import mode media. You should then be able to drag in the two files that we created. So these are all on the desktop. I have a folder called Tutorial for Editing. And these are two videos there. You can see them and preview them again. And then you can just take these two and import them. Depending on how big your files are, it will take a while. And you can see that it's now been edited. Now it's been imported. So you can play them back. I'm showing the engineers the SG website. So the video you want to see is probably going to start first of all with an opening scene. So usually our opening scene is our... Let me just import the file. The opening scene is usually our... ...Engines or SG opening scene, which is our splash page like this. So we take that, drag it in to a new file. To the bottom part, which is the screen, which is the timeline. So this is what you see. This is about three seconds. Three seconds for footage. And next we're going to do... Well, first of all, you see that it's actually... It's getting bigger and smaller on the top right-hand corner. So it's actually the canburns effect. So we can turn it off or set it to fit all. So you flow through without anything happening. So you can zoom in and zoom out of this. You can just click on this slider and you can reduce the size of the timeline. So you can zoom down to three seconds. You can use the command plus, the command minus to do the same thing. Next we're going to bring the video in. So this is the video I want to bring in. First of all, we have the presenters window as background. So the command click to just like the entire footage. Drag it in. And you will see that it goes like this. This is the microchain. So I'm showing you now the engine SG website. So this is basically how it looks like right now. As you can see, the audio itself is kind of low. So what you want to do is basically make the... Make this thing go a little bit... Make this thing be a bit louder. So you click on that and we say I want to auto. Which will basically adjust the volume on this clip. As you say, hello world, this is microchain. So the waveform here shows you how loud the video is or the audio is. So yeah, so this is the point part of it. So next thing I'll do is we also want a nice transition between the opening scene and the video. So we can click on transition, which is over here. We usually use a cross blur. So select that and drag into the space between the two clips. Then you can preview it by pressing play. So you bring over this. Next I want to do is look at the video of my face, which is over here. And I can now bring that in as well. But we only need the certain part of it, right? Because you can see the video starts. We can try to find the audio area. So it starts with the word hello world. So you can find the spot over here. So here I have turned on the recording on the Q4 camera. So it's looking at me as a quick presentation. I'm showing you the engineers SG website. So at the same time as I'm recording, I will also be recording on the screen. You should say hello world. So it's roughly around there. We actually need to be precise. We just need to drag the area which we are interested in into the video. You will try to synchronize the two. You will try to line up the two at the beginning spot. You want to also adjust the audio. So again click on the audio tab. Click on auto which will then adjust the audio. So you can click on, usually I just click on the plus to zoom in to the areas which I'm interested in. And listen to the areas which are being put. So this is microchains. So I'm showing you. So I would like to align the audio such that it would fill up roughly around the same area as I started speaking on the screen. This is microchain. It's a bit off so I can just adjust it a bit more. This is microchain. This will echo there. So you can actually see where it is by zooming in a bit further and look at the waveform and roughly maybe it might need to be just a little bit more further to the right. So let's see how it sounds. And also maybe try and add a little fade in effect. So it actually fades in at the front as well as the back. You will try to fade in as well and fade out. So what I want to do is also make sure the clip over that, the overhand clip is actually going to be fitted over. So right here the first one you say it's cut away, you change it to picture in picture. Which then lets you adjust the size of this thing over here. So what I also want to do is sometimes the audio feed on one of these may not be necessary. So I can just swap it down. Hello world, this is microchain review now that you did an SG website. So this is basically how it looks like right now. Right and in this part probably we don't need to have everything. So what we can do is crop out the bits that we don't need. Just drag it in and then we also make it fade out. So it looks something like this. Microchain, so I'm showing you now that you did an SG website. So this basically how it looks like right now. The video can also be extended further because we know there's actually additional footage. This is microchain, so I'm showing you now that you did an SG website. So this basically how it looks like right now. Alright so this is roughly the rough cut of the whole thing. I can also do a fade in from the beginning. So once the video has been edited you can actually export the video. So what we want to do is we take a look at the top right corner. Export, say you want to export as a file. Then you can actually export this entire file as a video file. So you can switch to 720p or 1080p. So I'll just keep it at 720p so let's keep it small. Click on next to export the file or drop it into the dropbox into the desktop. And that should be it. So at the end of the rendering process you see this circle go away and you should have your file. So once the video has been exported you will see this little success message here. So you click on show and it will show you where the file is. And this is how it looks like. It's a microchain so I'm showing you now that it's an SG website. So this is basically how it looks like right now. Yup that's it. So thanks for watching. I hope you can try and do your own editing of the videos after watching my tutorial. So if you have anything just drop me an email. Admin at engineers.sg I will give you if you have any questions. You can also add mention us at engineers for the win. Engineers FTW on Twitter right. Thanks. Cheers.


What's going on, everyone? Sam here, late in sports cards. I'm a 22, 23, Bowman University Chrome Basketball Hobby, 12 box, full case break number two, random player style. Here is a look again at your random results. Start with Wang, go down to Capelli. Again, these are on the website under the results tab, as well as the link that's currently in chat. If you'd like to see your name again, if you do not catch it on this first run through here. Tiger you, good luck here, everybody. Let's do it. Kyle's getting a yellow card next time he says something. He's already got one today too. You've got one, Sam's got one, Kyle's got one. That's the account for yellow cards that they're in the morning so far. There'll be a lot of people getting thrown out. This match is gonna have to conclude. The breaks today are gonna have to conclude based on not enough people to be able to put together a full squad, unfortunately. So it's tough, it's rough, dude, it's rough. Here we go, box one. A lot of yellow cards gonna be given out today. Trying to upgrade to red, come on. That can happen, can make that happen. Oh, now he's arguing with the rest. Man, man, man, man. MJ Rice, Skyscraping, Marcus Sasser. Oh, you've done plenty. Just Ashlyn Watkins, Purple Shimmer first. Just say it's for something you did and I didn't see. That's how you gotta look at it. For something that you did but I didn't see. That's what your yellow card will be for. Bryce Sensible, nice one there. Ohio State potential top 15 pick, I'd say. Lottery guy for Ohio State. Nice Buckeyes hit. There's a Kyle Lofton teal to 2.99, or aqua for it. Florida, Gator Chomp, baby. Shake your head out. Amari Bailey, that might be yellow card for you. See, there you go. Even Kyle says that assumption's fair. Bacop, nope, Caleb Love, just kidding. Yeah, don't know, I'm gonna say I want that. Jordan Walsh, insert red here. That's a red card. No one's given, I'm the only one who can give cards out, Tyrese Proctor. I got a monopoly on the cards right now. Tyre Sambel, Yabushiku, Nuzelis. Jaden Zachary, there's a Caitlyn Clark as well. Tomorrow night, I'm just saying get ready to be yellow carded. Juju Walkins, everybody. There's nobody safe from being yellow carded tomorrow night. Donnie is probably gonna be thrown out. Donnie got yellow carded last night too for coming in and taking mags, or two nights ago. Yeah, I was like, come in, just steal. No, it wasn't magged, it was the mag stickers. Came in and took an entire sheet of them. I said, that's a yellow card. And they started arguing. I'm like, that got upgraded to red, you're out. It's red, you're out. Throne out. See you later, Jeremy Roach, nice one there on the gold to 50 on the auto Purdue. Hi, it's Jeremy Roach. The Jeremy Roach spot. That yellow card coming out of whatever came out of a Bowman or something is the best thing ever. I'm so happy about that, dude. It's a random yellow card. It's just literally a random yellow card. Tyre Campbell, 2.299, there you go, Sab. Literally just like, he was helping you, I can test the yellow. There's Chris Livingston. Unfortunately, that's not gonna be re-looked at. Drew Timmy, Anthony Black, seeing as that was also someone who received the yellow card, it doesn't really matter at that point. That's just conspiracy at that point. Ernest Uday for Kansas, Trey White. Brandon Miller, Skye Scraper, Kamari Lanz. Kamari Lanz as well, and Felix Akpara. Anthony Black, first refractor, and Ryan Neymar. John Morgan on the case. Morgan and Morgan. Dude, I'll yellow card him, I don't care. Let's see what other buddy people have. What'd you say? Kyle said he's for the people he is, but she was. Morgan and Morgan. Dan too, was that Dan Nuland, is that who it is? Ifry Anderson, first refractor auto, 2.499 for OSU. Judamence, nice one there. I don't want a yellow card, John. Bring it, tell John, bring it. Ray Wave, Race Thompson, 2.199 on the order. Nice one there for the Race Thompson spot. He loves enemies. Ray Bailey, Skye Scraping, Will Richardson. Lauren Betts for Stanford, Malik right now. Marcus Sasser and Victor, one Harris. Fractor, Brandon Murray first, Georgetown. Hoyas, programs and shambles recently. Auburn is Chance Westry. Nick Smith, Jr. and Victor, Seth Trimble. Chris Livingston, first refractor. Next person to come in here is definitely gonna yellow card. I don't care who it is, I don't care for what, they're yellow carded. MJ Wright, Skye Scraping. Yourself, what am I choosing and why? I don't know, that's a good question, Benz. That's a future mini diamonds to 150, Chris Livingston. I don't know, I mean like, Tiger Campbell to 2.99, there's more color. He had more parallels for sure in this, but you have a chance of like the really cool dual autos and the jersey autos and such and Victor, or an inception, that's MJ Rice. I don't know, that's close for sure, Benz. Pasha Alexander, Brandon Miller, Skye Scraping. I literally dare somebody to walk into this room. Fractor, Ray Thompson. I'm assuming they have a nat on in them, man. It's us. Frankie Collins first. Matt, please report to the Breaking Studio. Matt, and if Matt has his headphones in, please somebody tell him out there. Think about which one to rip for yourself. There's Ernest Uday, bass auto. Chrome's good, Chrome's a lot of fun. It's Nick Smith, Junior, Skye Scraping, Kallel Ware, try to get the first and scribe Victor Otto, Hansel Manuel, Katelyn Clark, insert. Frankie Collins. I swear, if I go out there and we're not on, you're getting red carded. There's a lot of Boston blue ray waves to 199. Nice one there for South Carolina. Better hope we weren't wrong. Chris Livingston and Victor. Katie Johnson, insert. Two more boxes, feel a bass Wemby. Let's hope, dude. No bass Wemby's yet. Caleb Love refractor, Grace Thompson. Mark Mitchell, Kejani Wright, Skye Scraping. More spots coming in, thanks again, everybody. Do appreciate that. Mike Miles first, I'm leaving right now. I knew you were gonna do it. Yeah, shocking. I knew it, baby. There's L.J. Crier, nice one there. Some solid autos. Basically it's like, there's a couple things that go into it. If there's like streaks on it, if the pen comes off the paper, like if it's a sticker and the pen comes off the sticker a little bit, it can knock down the auto grid. Fuchsia, Colin Chandler, mini diamonds, do 150. Bro, where is this kid? He's just gonna ignore me. I think I'll get Jake in there. I think he's ignoring him. There's a DJ Horn, nice one there. Two 4.99. Jake, please come to the breaking studio. Jake, please. I think I'll get somebody in here. Arkansas is Nick Smith, Jr. Derek Lively, and Victor for Duke. Zach Eadie, first refractor. Brian Nemhardt, first refractor. And Julian Phillips. Auto Grades typically go for more than just authenticated autos. I mean, yes, I would say so. Connor, like very rarely do you see like autos that aren't created tens. Red guard. You're very on your way to getting a red guard, I have to say. And it's only gonna take you like two breaks, a break and a half, and you're gonna be out of here already. Armando Baker, Skyscraping, Hunter Dickinson. There's Caitlyn Clark base. First, firm with the boys. You know it, Connor. You know it. Sheeblee. Armando Baker, purple. Not to know. No, that is the 3.99. That is not to be shimmy. Can you go look and see if we're on or not? Gold, Kajani Wright, nice one there, 34.50. Grats on that, Kajani Wright's spot. Judamance, Juju Watkins. Yeah, no problem, Connor, you got it, buddy. Mark Mitchell, insert. Brandon Miller first as well. Yellow card on you. That's what I'm saying. Dylan's about to find out. Skyscraping, Jaros Walker. So we're on up there, but they don't have a volume box. Oh, okay, that makes sense then. JJ Starling, first refractor. All right, you're good. You saved yourself. You bought yourself a little bit of time. A little bit of time. Matches got a yellow. Felix Okapara, Anthony Black. Purple Shimmer, PJ Hall for Clemson. Nice secondary color match. Ooh, an orange, one of that would be sweet. Color match with the Clemson jersey, that'd be fire. Chris Murray on top there. Felix Okapara auto for Ohio State, nice one there for the Felix Okapara spot. What is Bryston doing in the shop? Got that guy out of there. 31 to go now on our last break of the day, guys. Thanks again, 31 to go. Chris Livingston Skyscraper. And that guy can't be walking around on Super 5C. Absolutely not. Ray Wave auto, Julian Phillips to $1.99. Nice one there for Tennessee. And the Julian Phillips spot, Go Vols. That Grady Dick, Brandon Miller. Gun charger, Smeller. Kyle Filipowski. It's a, like, shockingly large number of players in this with gun charges, Brandon Miller. All you need is Imani Bates, basically. Mikey's in here. Mikey's in here too, yeah. Jalen Bridges, first refractor, J.J. Starling. First, Trey White refractor and base. Maybe Imani Bates, I'm gonna gun charge, I might just be picking that up. He had something, I had something. And now, I think he just got money from someone trying to buy him to go to the, 28 to go, everybody. We're officially under 30 spots now. 28 to go, about halfway home. Here's your guys' link again. Getting random player style, 47.99 a spot. Gets you two random players. So like I said, for one spot, you have the potential to get Henderson and Wemby. You have the potential to get Wemby and Clark. Clark and Scoot, a bunch of different possibilities that you can have. Jordan Walsh, Guy Scraping, Trey White. Two, Seth Trimble, nice one there too, 199.  Cam Whitmore, Green Shimmer, Mike Miles, the 99. Poor TCU, Colin Chandler, Jaris Walker. That's what I'm saying, yeah. It's almost like, I feel like 48.99 is worth Daren Holmes, it's worth the shot to have Wemenyama in a full case. Know what I mean? Juniments, Guy Scraping, Chance Westry. Purple Mini Diamonds, Grady Dick, or no, Purple Shimmer, so that's not numbered, for Kansas. Jailor Wilson, First Refractor for Kansas. KU, Rockchoss J-Hawk. Green, Hansel Emanuel, nice one there. That's awesome dude. Grats to that spot, to 99, that's really cool dude. Really cool. Yeah, I get eight players in the next two cases to send, technically. So you get Wemenyama in full, is what you're saying, man. Jared McCain, Bass Auto. Nice one for the, Jared McCain spot. Arterio Morris, Guy Scraping, Seth Trimble. Big Kahuna, Jordan Walsh, nice one there on the short print. Julian Phillips, there's, if I just walk, I'm just gonna walk away.  Julian Phillips, Kulowar. Nick Smith, no, Anthony Black, just kidding. Oh, like three guys at Arkansas. Shibue Invicta, Colin Chandler, First Refractor, Frankie Collins. Will Richardson, First Refractor. And Jalen Washington, bless you. Okay guys, still 28 to go. Last group break of the morning. 47.99 gets you two random players. And all of their cards, numbers, seats, autos, inserts. Mari Bailey, Invicta, Brandon Murray. Arterio Morris, Refractor First, Tiger Campbell. Tamar Linkard. Zach Edie, Refractor First Auto for Purdue to 4.99. Be very busy this weekend, not even. Oh man. Mari Bailey on the purple shimmer. Everything must go, minus DC. There you go. Minus the, all the K-Von tibidos, of course. Yello, Jordan Hawkins. Nice one there for Yukon to 75.  That's sick. Where's he? I think he's mocked like top six right now. That's 12, so lottery pick, not bad. We'll take that all day long. Congrats to that spot. Frankie Collins. Child's gonna inherit the, whether they want to or not. Derek Lively. There's Mikey Williams, gun charge Williams. They're gonna like, the Vargas family is one day gonna run this country based on the wealth, like accumulated from K-Von tibidos rainbows. There's Katelyn Clark and Victor. If it's a boy, K-Von, if it's a girl, K-Vonny. Oh man, oh that's funny. There's Sky Clark first. I'm sure the wife is on board with that one, manny, right? Marcus Sasser and Whitmore Skye Scraping, Colin Shannon. Purple Race Thompson to 3.99. Purple Many Diamonds, Mark Mitchell to 3.99. That is Derek Lively, Katelyn Phillips. Sky Scraping, Sky Clark. Katelyn Clark, refractor first. There's a nice one there for that spot. Kishon Barthellamy on the refractor first. Oscar de Chiba refractor. Cam Whitmore I'm assuming, yes it is for Villanova and the Cam Whitmore spot insert. Blue Will Richardson, nice one there too, 1.99 for Oregon. And the Will Richardson spot. Jaris Walker, Timmy Allen. Refractor first, Ianna Patterson. There's Judah Mint, Skye Scraping and Cam Whitmore. Purple Shimmer is Amari Bailey for UCLA. Bruce Thornton on your refractor first. Colin Chandler, first base on the autograph. Nice one, Colin Chandler spots. John H, just because I could see it right there. Zartary Amore, Skye Scraping, Marcus Sasser. Tiger Campbell, Ray Wave Auto, nice one there too, 1.99. Gratsab. And Katelyn Clark, Julian Phillips. Anthony Black, G.J. Watkins. Anthony Black and Victor. And Brandon Miller first, about to A.J.J. Starling for Notre Dame. What's your favorite college team? Tirey Sunder, first refractor. Mark Armstrong, first refractor for Villanova. Yep, yes sir. Yukon for basketball, the Gators for football. Because what is this guy doing out there? I really want to know. Yeah, I don't know. I really don't know why they're letting them run around unsupervised. I really don't know. That's a little scary. I see none of the shots today. Julian Phillips, first base auto, nice one there for Tennessee. He's not pretty high, I think. I'm thinking of somebody else. No, I'm thinking of somebody else. Still nice. Chris Livingston. Orange and Victor, Chris Livingston to 25. There you go, Chris Livingston spot. Grats on that. Here's Grady Dick, Seth Trimble, the big kahuna, Gigi Jackson for South Carolina. Skyscraping, too bad Syracuse, Truman's. Grady Dick didn't go to the University of South Carolina. There's a logo. Brandon Murray first. Buy a good choice, man. Yeah, probably. Probably, it's right. Katelyn Clark and Victor, nice one there. Skyscraping, Cam Whitmore. DeMar Langford, first refractor. Purple Shimmer, Rudy Gayle Jr. Roddy Gayle Jr. Purple Shimmer. Purple Shimmers are not numbered in this again. They are like one-a-box, similar to the pinks in Prism. There's a Oscar to Sheeboy, first refractor. Nice one there for Kentucky and the Oscar to Sheeboy spot to 499. Very cool. Congrats on that to the Oscar to Sheeboy spot. Oh, what I said earlier. Lauren Betz to 100 on the Raywave, nice. Lively Skyscraper. Mark Mitchell on the insert. Zayn Amari Bailey in Victor Darnold. Chris Livingston, first refractor. Zach Edie. Race Thompson, first refractor. And Colin Chandler. That might be a yellow card right there. I might have to card myself. Good Lord, that was brutal. 26 to go now. Everybody hears your link again. 26 spots to go. Box number nine. MJ Ray Skyscraping. Sound just a hair. There we go, now we're back. Now we're so back. Eric Lively. Mountain Dew with me. Blew that one, 12 words. I had an energy drink earlier, but I don't have more caffeine. Gold shimmer, Tyrese Hunter for Texas to 50. Nice one there on the first. Grats to the... Tyrese Hunter spot. There's a green Caitlyn Clark. There we go, 70 of 99. Big time Caitlyn Clark. Heck yeah dude, we'll get this one magged. Grats to that Caitlyn Clark spot. That will work right there. Very nice. Caitlyn Clark first. Of course, wrong on that of course. Why would I be right? Avery Anderson. Chris Livingston for Kentucky and Chris Livingston again. Fractor RJ Davis, Terrio Morris. Brandon Miller, Skyscraping, Ray Thompson. Katie Johnson, Purple Shimmer. Rice Sense of All first. Brandon Slater, first refractor auto for Villanova. Brandon Miller, base first auto. Nice, two for two on Brandon Miller autos in both cases. Brandon Miller spot doing nice there. There's Amari Bailey. Tyrese Proctor, Hosh Alexander. Drew Timmy, Hunter Dickinson. Whoa, whoa, whoa, whoa, chill. There's Nick Smith, Jr. That one I know. Nick Smith, Jr., again on the Invicta. Shiba first. Another Invicta, that's not gonna be Marcus Sasser. Look right now. I have a first refractor DJ Horn for Arizona State. And the last pack of box nine is a Jackson Culler. First refractor, the one Harris as well. All right, box 10. Let's go to sold to Sam Donald. Sam Donald. No, Adam, we haven't pulled in yet. No, no, no Wemby's yet. No Wemby's yet. No Scoots either. Purple Shimmer, Razir Bolton. Hand full of Brandon Miller. There's a couple of nice Caitlyn Clarks now. Full of the green Caitlyn Clarks, pretty solid. Not auto, but still, still pretty solid. Ariel Morris, just starling. Juju Watkins, first auto. Nice one there for the Juju Watkins spot. Jordan Walsh, Skyscraver. There's a Jarris Walker. Purple, Jarris Walker to 3.99 for Houston. Invicta, Julian Phillips. Come on, Urkele. Yeah, it's like extended base for Wemby. It's very, they're super short-printed. Tennessee is Julian Phillips, which is nice. Yeah, I was gonna say Scoots the only guy with no base. Caitlyn Clark refractor first now. Think the second one of the case. Nice, Caitlyn Clark spot doing well. Caitlyn Clark spot, I would argue, is the best spot in the entire break. The argument could definitely be made there. Kowski, yeah, yeah, very, very tough to pull Wemby. Base, Tiger Campbell, first refractor. Ray Wave, Jeremy Roach. Nice one there to 1.99 for Duke. Jeremy Roach spot. It's a second color of Jeremy Roach auto we've pulled, so not too bad. Ernest Uday. Still at 26 to go, everybody. Let's get this filled on up last group break of the day. I know, I appreciate that, Adam. I'm hoping, dude. I am hoping. Leak right now. Kyle Filippowski to 1.Harris Jr. Luke, Colin Chandler. Nice one there too, 1.99. Only the base. Basse, Anthony Black refractor. Oscar de Sheeboy on the Invicta. Avery Anderson. A Judiment Skyscrapers, DeMar Langford. Juju Watkins first. Artario Morris. Sky Clark first. And Chance Westerie. All right, that'll do it for box 10. Just two left on the break. Thanks again, everybody. Again, just 26 left on our last one. That is number five. So thank you all for getting that very close to full. We do appreciate it, 26 to go. I think it's officially almost over halfway sold out. So that's awesome. The other, still have two more to go. These after, before that one. So those are both sold out. Thank you guys again. Three was sold out very early on today. Four was sold out during the last break. So also nice. And five still got some spots in five. And then we have one four box straight down on our baseball at the end of the ship. That is still, that has been sold out for a while. Armando at backup. So thank you all. Making this Friday nice and easy. Show up and have some fun. Purple shimmer, Kiki Rice for Ukla. Tyrese Proctor, first base auto. Nice one there. Yeah, I agree, Steven. These are nice, man. These are clean. These are really clean. Gold, Anthony Black. Nice one there for that spot. Potential top 10 pick, 48 to 50. Plus they have the little firsts on there too. It's awesome. Chris Livingston, sky scraping. Jalen Bridges, Mikey Williams, Mikey Gunn Charges. What are we doing here? What's up? 18 years old, you should not be here. Right. Thank you. What are we doing here? Cam Whitmore. Jalen Wilson, refractor first. Colin Shannon. I think, yeah, I think Wemby's the only one. Wemby's are redemption though. Sky Clark to 199. Ray Wave Auto for Illinois, the fighting of line nine. Yeah, Wemby's are redemption but I think he is on card. Yeah, everybody else is a sticker. Drew Timmy. And I hope so, Steven. I really hope so. There's Drew Timmy on the Invicta. Especially if fanatics starts getting guys exclusively, I really have to pipe Panini out before the license is up. Kyle Lofton to 299. Sky scraping, Jeris Walker. No Wemby's, no. What's up, Ramble? No Wemby's yet. No Wemby's yet. Unfortunately, Julian Phillips first and Filipowski, Will Richardson first and Frankie Collins. I thought it was good. I mean, I predicted Denver to take game one at home. I wasn't super surprised by the outcome, Steven. I gotta be honest with you. Down to 25 to go now, everybody. Wasn't super, super surprised. I think it'll be really interesting. Game two, I think game two's arguably more important than game one. Cause it's either gonna be the heat win game two and have momentum going back to Miami or the Nuggets take a two-oh series lead.  What's up? Nuggets win, yeah. They look good. They look really good. I know. That's the only issue with the heat. It's like, if you shut down Jimmy, unless one of the role players randomly goes off, like they did in the Celtic series, yeah.  Gabe Vincent, yeah. Bruce and Duncan Robinson will have his one game a series where he shows up. Jalen Bridges, nice one there. First base on it. They do. MJ writes, Teal, wave to 299. But this will be like the first team since like the Mabs where there's not like multiple all-stars on finals teams. It's crazy, dude. Let's just go show how good Yochitch is, if that's the case. So they win. Yochitch is like, Lyah Boston starting to enter like top 20 of all-time territory. Like two MVPs should be three. Should have been the third, yeah. Mark Mitchell, Anthony Black. And the finals, and they'll probably win finals MVP, I'm sure. Mark Mitchell. Triple-double first game, like. Yeah, oh yeah. Unreal, dude. This is so good. Invicta Arterio Morris. Hansel Emanuel, first refractor. Caitlin Clark, base first. Drew Timmy, first refractor as well. Ryan Neymar. Johnny White, no. Right on the skyscrapers. Yeah, Dirk was a beast that 2011 finals run. Jalen Hood-Chefina. I think everybody in the world is rooting for the Mabs at finals, too. I know Iowa, that was heavily rooting for the Mabs. There's Zach Eadie, refractor, first auto for Purdue to 499. That was a fun team, too. Paja, Kidd, Chandler. Marion, Matrix was there. Yeah, that was a fun squad, fun, old squad. Nick Smith Jr., skyscraper. Derek Lively. Purple Mini Diamond, Jalen Washington to 399. Caitlin Clark, insert, refractor. Paris Proctor. Ernest Uday, first refractor, Hunter Dickinson. Katie Johnson on the insert. And Brandon Miller first, nice one there. Alabama in the Brandon Miller spot. Look, I have gum charges. Cheris Walker for Houston. Jeez, dude. The hell. Great play, man. Now I know, honestly. First, Cheris Walker, base for Houston and MJ Rice. All right, guys, do a quick recap here. Gold of Kejani Wright, Anthony Black, Tyrese Hunter, Orange Chris Livingston, base autos. Now we have Jalen Bridges, Tyrese Proctor, Juju Walkins, Brandon Miller, Julian Phillips, Colin Chandler, Jared McCain, Felix Okpara, Ernest Uday, Rice Sensible. We had refractors to 499, Zach Edie, DJ Horne, Oscar de Sheeboy, Brandon Slater, Zach Edie again, Avery Anderson, Ray Waves to 199, Tiger Campbell, Sky Clark, Jeremy Roach, Julian Phillips, Race Thompson, Green to 99, Hansel Emanuel, that's awesome. Yellow to 75, Jordan Hawkins, Gold to 50, Jeremy Roach, and a Green, Caitlin Clark. 70 of 99 on the first base. That'll do it for the break, guys. Thanks again for the fill. Up next, number three.


So once you get your beret, if you are a combat controller, special reconnaissance or a so-com assigned para-rescumen, most of the time you will end up going to another course, which is called advanced skills training back at Holbert Field.  Now that is not necessarily a selection. That is not, I mean, it's tough, but it is where we take the basic level skills that you have learned, and we just increase them by doing full mission profiles and live shooting and all that kind of stuff.


The Makers of Wrigley's Spearman Chewing Gum invite you to enjoy life, life with Luigi, a comedy show created by Si Howard, directed by Max Benhoff, and starring that celebrated actor, Mr. J. Carol Nash, with Alan Reed as Fasquale.  And you know, Wrigley's Spearman Chewing Gum offers you relaxation and enjoyment, too. It's pleasant to chew on a smooth piece of Wrigley's Spearman for the ill-working, shopping, listening to your radio, or doing just about anything. Wrigley's Spearman Gum tastes good. It's refreshing, and the good, easy chewing gives you comfort and satisfaction. Now, Wrigley's Spearman Chewing Gum brings you Luigi as he writes another letter describing his adventures in America to his mama-basco in Italy. I don't know me. Isn't that too wishy since the Pasquale put his daughter Rusty into my night school class, so I should have gotten used to her in America? Perhaps the worst thing that's ever happened to me, Mama Mia. When I'm a join the schooler to learn the trials, I'm never taught she's going to be raised in a right and a rooster. But a funny part is the Pasquale was a right. The more I'm a see rooster, the more I'm going to get used to her. Just like Uncle Pietro was the one who got used to his daughter. Only I'm going to get used to an elephant. I don't like to say anything about the rooster because when she's got a good heart, a good character, then she's got a good appetite, too. That's the girl he's every meal like is the last one before the electric chair. When she makes herself a hammer sandwich, she's going to put a hammer inside to bring her back to the whole thing. Mama Mia, I'm a worried, I don't know what to do. I'm never going to leave her my wonderful night school and I've got to get the rooster out there. But Pasquale, he's very stubborn. He says the rooster stays in my class because I'm a learner, he's the kind of victim of things. One and one is the sweet wins and a two and two is a four quadruple and a stone and a butter. But even now, he's telling her how she should catch me for her husband. Rosa! Where is that girl Rosa? She's trying to catch me. Yes, my little ride, Chris. Who's been changing the spanner on these manuals? Hey Papa, you sell cascature with five K's. Well, you did it once, you spelled it without any K's. Papa, cascature hasn't got any K's. It's spelled C-A-C-C. You'll stop, you're making me see thick. It's not for you in that night school. You're getting it so smart. By the way, daughter, how's it going over to Luigi? Oh, good. He has to leave any carry his books to school. That's wonderful. I can hardly wait till he lets you carry him. Oh, yeah, Papa. Now, the right way to spell cascature... Oh, stop! I didn't put you in school to tell me how to spell a cascature story. I put you in Luigi's class so you could touch a hammer for a husband. Well, I think he's getting along with me more and more, Papa. Good, good. Did he ask you for a place to kiss the handsome daughter? Oh, I should ask. Forget everything I ever told you. This is a leap year, so leap. Now, look, Rosa. I want you to do everything possible to keep on seeing Luigi. Walk with him to school. Talk with him in school. Walk home with him to his antique shop. Go inside and help him with his homework. Papa! What? Don't I get time off for lunch? Stop worrying about eating. You think, uh, Lily Poppick's starting to get used to, yeah? Yes, Papa! I think I better start ordering up those wedding invitations. There, Mr. and Mrs., who would make her excited? Pascuali is happy to invite you to the wedding of his daughter, Rosa and Luigi Pascuali.  Oh, Mr. my little baby. Soon you're gonna be married and Luigi's gonna be Mr. Pascuali.  I can adjust to see you. 200 cubic feet. Well, little baby, you watch the store. I'm gonna go into him right now and find out how crazy he is about you. All right, Papa. Hey, come to the bride. Oh, the best in the wine. Come to me, little Luigi, my friend. Hello, Luigi. Hello, hello. Hello, Pascuali. Hey, you're looking different today, little banana nose. No, different of how, Pascuali.  I face is flush. It keeps all the blushing. Wouldn't it be love, huh, Luigi? No, Pascuali. I'm just a commander to have to shower. Tell the truth, little cop. Well, since I put a rose in your class, do you start to get used to it, huh? Well, yes, Pascuali. You may be a little more used to this week than you did last week, huh? You like a better little man than her? Well, it could be. Maybe another week you like her so much, you would let the priest ship me to you one, huh? But the wife, Pascuali, I'm the one right now. Now, for Joe for a while, Luigi, you know what I mean. But, Pascuali, I don't think I'm ready enough for marriage. Who's asking you to be ready? Just be there. That's all. Pascuali, please, please. Is it no rush you were to marry me? No rush, Dave says.  It's been the tragedy of my life. Always a pop, but never a grandpa. Dear very Pascuali, I promise you, when the time comes, I'm going to tell you. Not gonna rush me. You're gonna know right. Oh, yes, I am a god.  Now, look for Luigi. I went to a lot of trouble.  I expect a quick result.  No, I don't understand. And if you keep on bothering me, then I'm never gonna marry you. Look, Mr. Spencer, I'm giving you one more week to fall in love with my daughter at first sight. And if you don't, then I'm gonna tell you you don't know what's going on. Then I'm gonna figure out how you gotta feel every minute of the day from when you get up in the morning till you go to sleep every night.  But, Pascuali, I couldn't have a such a shadow if I wasn't the Queen of Mary. Well, it's a sin to you and the King of England. I don't want to stop.  Well, I... I just... I'm worried. Something inside of me is afraid this is gonna come through and it's making me out to side between the greens. Lovigio got a real problem. A man going into the fixer. That's why I'm gonna wait at the quick auto. You gotta help him figure out how to get a rose out of our class. That's gonna be hard, Lovigio. You gotta get that girl fast. Fast for no fast. She is proving that she has a real good brain. Yeah. Yeah, from the holdsteins she's turning into an Einstein. Ach, ja, von der Holstein, she is turning into an Einstein. So, there was not a kind thing to say.  Oh, I hate what you said, but I love the way you said it. Ach, now smile, everybody. We're gonna find a way out.  Saying she's been dismissed. Then she stays home forever. Yeah, and then we all go to Zing Zing for ten years. There must be something we could do. There must be something we could do. Hey, maybe we can make a lunch to get the silly. She's acting too nice in a classroom. Ach, Luigi, Luigi, you got it. Oh, why didn't I think of it before? Oh, why didn't I think of it before? Rosa loves to laugh, right? To laugh is putting it mildly she giggles. Cattle is more lion. All right, now, today Mr. Ors, the principal, is coming in to watch the class. Do you begin to catch on? Yes, you mean we make her a lesson and then she acts the silly? Silly, I told him to begin it. I'm gonna make him a lot of jokes. Rosa gets to stare at you with laugh. Maybe you can reach over and give her a tickle. And when the principal hears the hyena calling to it make, he's gonna sing she's a lunatic. She's a lunatic. And so Rosa all the time. Well, that's wonderful. Quiet, Emily, and she is coming here. So that's not a classmate. Hello, Rosa. Hello, Rosa. Well, I wouldn't even need the show. Oh, here comes the teacher. Good evening, Laffy. Before I begin the lesson, let me warn you, our principal is coming in today to observe it, so let's be especially smart. All right, I'll call the row now. And Mr. Basko? I'm here. Mr. Howard? Yes. Mr. Rosen? Rosa? Yes. Mr. Schultz, is your name Rosa? I don't know. Call out Schultz if Rosa answers that in me. Mr. Schultz, that is not funny. There's been entirely too much laughter in this class, and if Mr. Orts decides to throw anyone out, he'll have my cooperation. Oh, he's good for the business. Good evening, George. Good evening, Maura. Good evening, Miss Faulding. Good evening, class. Go right ahead with the lesson, please. I'll just take a seat right here. Class, I ask you to memorize certain important dates in American history. Mr. Basko, you may tell us why 1775 was important. Well, it was the start of American Revolution. Yes. Mr. Howard, why were 1776 famous? It was one year after the start of the American Revolution. Why? Oh, the declaration of independence. Yes, of course. Mr. Ortson, 1787. The United States Constitution was adopted. Mr. Schultz, 1796. That's what my wife said for her new dress. Why? 1796 reduced from 18,000. Why, Rose, that's a funny thing. Rose, why ain't you laughing? Mr. Schultz, how ridiculous can you get? Huh? Schultz, Schultz, make a lesson. I warned you, no hooping. Rose, tell Mr. Schultz what happened in 1796. Washington gave his farewell address. Not address, say address. That's what I said, 1796 before address. Smile, Rose, that's hilarious. Mr. Schultz, you're very corny today.  Certainly, Miss Schultz, I got to go now. Thank you. My reason for stopping by is to relay a message from the main office. There's been too much absenteeism in the night school class. Now, we feel that absenteeism is an abuse of a valuable privilege. Hereafter, one or two absences, unless entirely justifiable, may lead to dismissal from the school. Thank you. And as for myself, I might place in the same category family tactics and destruction of the class. Good night. I'm sorry, Miss Schultz. This is a fine time to be sorry. I asked you to cooperate and then I'm going to Miss Schultz. Good for you. Schultz, do you think we know how he does if you don't? You didn't even bother to apologize for your own behavior. And I heard you prodding him on. I don't like it at all. I can tell you that, Mr. Bass, so I'm ashamed of you. I don't like it one bit. Don't worry, Louise C.  Thank you, that's all.  Kim will hang up the black tape. It looks like we're going to have a marriage after all. Before we return to life with Louise C., we want to tell you how chewing Wrigley's spearmint gum can help make your daily work go more smoothly and successfully. You just see to keep going at your best, you've got to feel fresh, alert and on your toes. And chewing a stick of Wrigley's spearmint gum really helps you feel that way.  The smooth easy chewing goes right along with the job itself. Makes the time pass faster and helps you keep feeling and doing your best. You don't have to take time out for it either.  It will make your work more pleasant and it will help you do the job more smoothly and successfully. Now, let's turn to page two of Louise C. Basko's letter to his mother-in-law. Hello, ma'am and ma'am here. I'm a thief. I never went so bad off in my class before. The spotting is you get a mad enemy and it's only make the rusts look better now. The more I see her, the less the fact that she looks at me.  He's a rote. In these days of inflation, you can still get good buys and the rusts are the giant economy size. And now I'm not the only one who's worried about me because all of my friends in the class are there getting worried too. So we decide to have a meeting in a my antique shop and it shows you what's inside. I now call to order this United Nations meeting special SPTL division. SPTL? It shows you what's inside. The Society for the Prevention of Cruelty to Luigi. We start off by calling the role of the member nation. The delegate from Italy, the delegate from Sweden, the delegate from Israel. Here is the delegate. Thanks to you. Oh, thank goodness. I was about to declare war on my time. The Swedish delegate, please review the problem now before the General Assembly. According to section 4 Amendment 8 of our UN Charter, a no entangling alliance shall be imposed upon one nation by another fellow nation without the full consent and agreement of fellow nation. That's right. In other words, we don't want Luigi to get hooked. All right. The floor is now open for General Discussion. The delegate from Italy has his hand raised. Thanks to Mr. President. He ordered a white first party to put the Russian out of classes. So I should have gotten used to her and then marry her. Personally, I don't like when a girl gets fed up in the class and she's always busy with father, the rouge, the lipstick, and the mascara. Yeah, that's chemical warfare. So do I hear any more complaints about the offending party? Well, Mr. President, you think it was a fact to suddenly put the Russian in a class with a man like this? Absolutely not. The robbing of the atom bomb is strictly outlawed. Mr. President, if I may say so, we shouldn't take this matter too lightly. It's the struggle of a man who doesn't want to get married. If it's old, it's the age.  In fact, the oldest story known is how a girl gets her man.  You mean you don't want me of the voyage? Who does women? All the time, you are getting drafted and they make you feel like you're enlisted.  With a Russian in a class, I'm getting so used to how anything is in life but to happen to which I'm a woman wouldn't want to happen even if I'm a woman it wouldn't happen but if it got to happen and then I'm... You are getting the United Nations all for shimmer. You, I mean, I have an idea. You have a... that's so wonderful. What is it? It's a good one. You know, then Sweden gets a chance to keep the Nobel Prize in its own country. The principal said anyone who is unduly absent will be dismissed. What we should use with Rosa is psychological warfare. Well, what's the official thing? Did it out? What is her greatest weakness? That it's... Food. What kind of food? Anything that grows, works, swims, or flies. What's food got to do with the whole delicacy full of stuff? Right? Right. I've done it. I've done it all than you have achieved. Luigi, when Rosa walks you to school tonight, you stop off first in my delicacy. And while she's inside, we begin teasing her appetite. Brilliant. Then she starts to eat. She's so happy. Sure. She don't wanna come to school. She doesn't show up once or twice, and next thing, you know, she is out because of abscess. I mean, that's the sense of wonderful, that's the wonderful... One thing Rosa cannot change herself, that's about the food. United Nations delegates, all those in favor of the Swedish proposal, say aye. Aye. Motion pass. Then I think you realize that tonight we're gonna make history. History? Yeah. For the first time since education started, a girl is gonna leave school and I can't believe I've heard. Working at school with you. Yeah, that's it. Yeah, that's it. Let's stop in the delicacy and I see for sure that you're ready for school, huh? All right. Luigi. And Rosa. What a respected surprise. Come on in, sit down. Oh, that's delicious. We just dropped in just to see if you're ready for school. Oh, what's the hurry? We got time. Here, Rosa. A nibble on this little Frankfurt. No, thank you, Mr. Scho. Rosa, this is on the house. Free for nothing. Stop yourself. Yes. Live. No, thank you. I never indulge actors.  Yeah, but a Schütze Schütze. No, that's a very nice deal for you to say that to Schütze. Oh, yeah, yeah. I'm sorry, Rosa. Maybe she don't like Frankfurt. Rosa, it's a green post. No, I'm determined to improve myself. Luigi, come. It's time we should go to... We have created a literary Frankenstein. No, Rosa, I'm going to honor you with the most expensive delicacy in my delicatessen. Romanoff caviar, 30 dollars a pound.  Yeah, go ahead and eat it. No. Rosa. Romanoff, that's named after a king. That's right. There must be king eat it. Him will she make jokes? Yeah. Schütze. Schütze's a nice guy. Well, I guess... I guess she ain't that hungry. Look, look, look. Pradegolas. No. She looks like a typical Janinic. Rosa, darling. Darling, do me a favor, huh? My wife, Rita, wants to see a movie tonight. So, how's it about you watching my delicatessen store tonight? I don't know. But what about school? Oh, me and Luigi will watch the school. Well... I'm sorry, Mr. Schütze. I have to stay in school with Luigi. Well, Luigi, we came, we saw, and we got conquered. Let's go to school. That's the right thing. I like this. Come on, Rosa. What's the matter, Luigi? Your books too heavy to carry? No, my books are they're lighter. This time, my heart is a heavy. So, she wouldn't fall for the eating business, huh, Luigi? No, no, no. Hey, Hudson, what do you think I should do now? Luigi, you got to act like a man. After all, every man has to get married. Yeah, but in Luigi's case, why shouldn't it be to a woman? No, no, no, no. Schütze, Schütze, you shouldn't have said that because it... Rosa, well, where is she? She lives to follow these books. No, you lost fair and square, Luigi. You admit you're getting used to her.  She wouldn't make you a bad wife, Luigi. And we all got to go sometime. She's crazy about you. And she will always be. She will be. And besides, you can never get her out of school. That's right. While I write some reminders and make up, I'm going to tell her as long as she's going to go to the school with me, I'm going to propose to her. That's the boy. Good luck, Luigi. Hey, Schütze, why do you look at me like that? Nothing. Good luck, little Englishman. I told you to pull around with these menus again. Papa, your spelling is just terrible. Instead of one. So what? It tastes the same, no matter how many Gs you've got in it. And you left out the H, Papa. An H in a spaghetti? Sure, only the H is silent.  Rosa, since you took up a spelling in a school, I got a nothing but a trouble with you. Papa, change that sign you had in the window. What for? Your arithmetic is all wrong. You put down special, two dollars. That's bad adding. But it's a good business. Around this neighborhood of Rosa, nobody can add. You know, since you started to go to school... I might just as well tell you the rest, Papa. In school, they teach us that a good citizen always pays a bill. Rosa, you didn't pay all those bills, I haven't the cash register. You sent the cash out today, Papa. I wasn't a more than six months behind in those bills. Rosa, you think I sent you to school to drive me crazy?  You're not yourself. You don't even a giggle like you used to. I don't pay square. Rosa? Who sent it for you, you old maid? Rosa, I got something important to say to you. The first I got is something important to say to Rosa. I'm taking you out of school to start tonight. Well, I was... what the...? Yes, I'm taking her out of school. That's right. You want to say some more about it? Because I can't smile for my own good and it would make my life miserable. Well, Mr. Marrager Dodger, what are you standing around saying little things about? You mouth's agonizing. Well, because of the study. You really taking Rosa out of school tonight? Yes, and now what was you going to tell her that's so important? Rosa? Yes, Luigi? You think it's going to rain tomorrow? I'm just ahead of most of one of the three weeks of my whole life. But now with Rosa in the morning, my class, I'm going to feel like a free man again. Like Uncle Pietro is always used to say, marriage is like some accident.  But you don't have to go out and look for it. And I'm not going to go out and look for it for a long, long time. You'll have a son, Luigi Baster, a little immigrant. Friends, the makers of Wrigley's Spear Mint Chewing Gum hope you enjoyed tonight's episode of Life with Luigi.  You see, Wrigley's Spear Mint is made for good chewing. It's smooth and satisfying to chew on. And the lively, long-lasting Spear Mint flavor is really delicious.   So carry Wrigley's Spear Mint Chewing Gum with you at all times, as millions do. Be sure to get Wrigley's Spear Mint Gum. Healthful, refreshing, delicious. The makers of Wrigley's Spear Mint Chewing Gum invite you to be sure to listen next week at this time when Luigi Baster writes another letter to his mama Baster in Italy. Life with Luigi is a Psy Howard production. Pat Burton is associate producer. The script is written by Mac Benhoff and Lou Derman, and directed by Mr. Benhoff. Jay Cowan acts as starred as Luigi Baster with Alan Reed as Pasquale, House Conreader, Jody Gilbert as Rosa Mary, Ship of Miss Balding, Joe Forte as Horowitz, and Ken Peters as Olson. The music is under the direction of Lud Guston. This is Charles Lyons. This is the CBS Radio Network.


Congratulations, you are now on 103 points, you are 9 points clear. You must be feeling pretty good as we headed to Cardiff. Yes, but I don't look for the table because I'm all the time focused on myself. Yes, this is an unbelievable night for me and everything is very good working. Yes, I'm prepared for the next round. Okay, Mati, there you go. It's good to have you back on the podium. Back-to-back podiums and now that puts you into our top eight as well. Yes, step by step. I'm pretty pleased with my progress. Of course, I was looking for these results a bit earlier in the season, but it's not too late. I'm happy where I am at the moment and let's keep it going. Yes indeed, you should be happy too, podiums. I'm going to get you to hand down the microphone to Freddie. Now, this is your third podium of the season, Freddie, and that moves you up to fourth position, so you have overtaken Martin in that table as well. Definitely a fantastic night for you. Yes, it was a good result for myself tonight. I was consistent all the way through the meeting. I felt comfortable on my bike tonight and that always helps and I'm very happy when you're back on the box. It's a nice feeling. Yes indeed. Okay, Bartos, in your own language, congratulations. You must be feeling very good right now in Polish. Thank you very much everyone for the hot doping, because without you, we wouldn't be able to get such points, because you didn't get me from the first run to the last one. Such support is very important. Thank you very much. We'll give you two more rounds, keep your fingers crossed and let's go. Well, congratulations, guys. That brings to a close your Danish FIM Speedway Grand Prix. One, two, three, stand in front of me. Bartos Malzek, Bati Zegar and Freddie Lindgren. Congratulations, guys.


So, gingeral fibres are basically collagen fibres, collagen bundles of fibres seen in the connective tissue of ginger, so which are known as gingeral fibres. So it is basically a type 1 collagen. So these connective tissue of marginal ginger, which is densely collagenous, which contains a prominent system of collagen fibre bundles, which are known as gingeral fibres, consists of type 1 collagen. So, functions are to raise the marginal ginger firmly against the tooth and to provide the rigidity necessary to withstand the mascricatory force without being deflected away from the tooth surface. So, bearing the mascricatory force to unite the free marginal ginger with the symptom of the root and adjacent ginger. So uniting the free marginal ginger with the symptom of root and adjacent ginger. So these are the functions of gingeral fibres. Now let's see what are the fibres. So hope you can see this picture. So let me tell you this is the enamel. So this part is enamel and this is enamel, this part and this is alveolar bone, enamel alveolar bone and this is our gingiva, okay. So we have types of fibres, circular dendro gingiva, dendoperiosteal and transeptor. So circular fibres are fibre bundles which run their course in the free gingiva and circle the tooth in a cuff or ring like fashion. So circular gingiva will not be shown here. This is a cross section. So you can see the circular gingiva here, okay, which circles from the top view. So this is the top view of gingiva. This is the side view. So circular fibres you can see this circle, orange colour circle which is circular gingiva which are the fibre bundles which run their course and the free gingiva. It encircles the tooth. So it encircles the tooth. It is not easy to show here. So it encircles the tooth. So that is circular gingiva. Now we have dendro gingiva. That is dendro gingiva fibres which are embedded in cementum of the supra alveolar portion of the root and it projects from cementum in a fan like configuration out to the free gingiva tissue of facial, lingual and interproximal surface. So you can easily understand this. This is dendro. So it starts from cementum and it is fanning out to the free gingiva tissue of facial, lingual and interproximal surface. So it starts from here. It goes like this. That is dendro gingiva fibres. Now next one is dentoperiosteal. Okay. So this is a dentoperiosteal. It starts from cementum. It ends in bone. So this is a periosteum. This is a bone. So dentoperiosteal fibres. So it starts from cementum and it ends in periosteum. So these are the embedded in the same portion of the cementum as dendro gingiva fibres. But they run their course apically over the vestibular and lingual bone crest and terminate the tissue of the attached gingiva. Okay. So this is going apical direction, dento gingiva going coronal direction. So this blue color, this violet color is dento gingiva and this pink color is dentoperiosteal. Okay. This is the bone. So gingiva. So from cementum. So this is a cementum. Okay. So cementum. It is going. So this is enamel. So cementum, cementum. So from cementum, dendro gingiva and dentoperiosteal. Now we have the transceptile fibres. Two transceptile fibres you can see here. Okay. This one which is connecting between two tooth. They extend between the supra alveolar cementum of adjacent teeth. So this is between the teeth. This is cannot be seen from a side view. This should be from top view. So this is a transceptile fibres. It is running between the teeth. That is a, it is runs straight across the interdental septum and are embedded in the cementum of adjacent teeth. Okay. So it was between the teeth. Okay. So it is run straight across the interdental septum. So interdental septum is here. It is going like this, this blue line. Hope you can see this blue line between the teeth. It is known as transceptile fibres. And we have additional fibres which is given by page and co-workers. They are semicircular, transgenjival, intergenjival, interpapillary, intercircular and periosteogenjival. Okay. So periosteogenjival is here. So it starts from periosteum. It goes to the genjiva. And this is circular we have already seen. This is intergenjival. It is between the genjiva, this pink one and transgenjival. It is going between the tissues, genjival tissues, transgenjival.  So interpapillary is this horizontal lines, horizontal violet lines, interpapillary and intercircular and periosteogenjival I have already shown. So when question asked about genjival fibres, we need to draw both the pictures. So this is the principal fibres and this is the additional fibres. Circular, intergenjival, tender periosteal, transceptile. And fibres are semicircular, transgenjival, intergenjival, interpapillary, intercircular and periosteogenjival.