投稿時間:2023-05-08 17:35:25 RSSフィード2023-05-08 17:00 分まとめ(36件)

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IT	ITmedia 総合記事一覧	[ITmedia News] “PayPay改悪”って、TwitterのAPIみたいだなあ	https://www.itmedia.co.jp/news/articles/2305/08/news109.html	itmedia	2023-05-08 16:50:00
IT	ITmedia 総合記事一覧	[ITmedia Mobile] 楽天ペイ、セブン銀行ATMでのチャージで最大20％還元キャンペーン	https://www.itmedia.co.jp/mobile/articles/2305/08/news121.html	itmediamobile	2023-05-08 16:34:00
IT	ITmedia 総合記事一覧	[ITmedia エンタープライズ] 富士通とNECは2023年度の国内IT需要をどう見ているか	https://www.itmedia.co.jp/enterprise/articles/2305/08/news057.html	業績予想	2023-05-08 16:30:00
IT	ITmedia 総合記事一覧	[ITmedia News] 楽天証券900万口座に　“単体最多”強調　つみたてNISA口座は300万に	https://www.itmedia.co.jp/news/articles/2305/08/news116.html	itmedia	2023-05-08 16:22:00
IT	ITmedia 総合記事一覧	[ITmedia PC USER] 扇風機としても使える!?　大型ファン搭載アルミ製ノートPC冷却台	https://www.itmedia.co.jp/pcuser/articles/2305/08/news112.html	itmediapcuser	2023-05-08 16:04:00
AWS	lambdaタグが付けられた新着投稿 - Qiita	Hono on AWS Lambdaを体感する	https://qiita.com/watany/items/72dad3c4953238a16c9c	awslambda	2023-05-08 16:13:01
Ruby	Rubyタグが付けられた新着投稿 - Qiita	クラスメソッド	https://qiita.com/F_Yoko/items/93af0375aa3fa46b8da6	様々	2023-05-08 16:37:59
Ruby	Rubyタグが付けられた新着投稿 - Qiita	ローカル変数/インスタンス変数/定数/クラス変数	https://qiita.com/F_Yoko/items/72a6326f9d5e64e8d80d	範囲	2023-05-08 16:07:27
Ruby	Railsタグが付けられた新着投稿 - Qiita	65歳、初心者がrailsの色々な日付機能を勉強しました。	https://qiita.com/matsumo33333/items/60d9c20a31316477c6c8	rails	2023-05-08 16:54:55
Ruby	Railsタグが付けられた新着投稿 - Qiita	【個人開発】俺のターン！ドロー！アングリーカードを召喚！日常のモヤっとをカードゲーム風に消化させるアプリを作りました。	https://qiita.com/itomiki22/items/958ff2c1d95f2caffa3f	作りました	2023-05-08 16:22:23
技術ブログ	Developers.IO	EC2にKinesisエージェントをインストールして、Kinesis Data Firehose経由でS3にログファイルを送信してみた	https://dev.classmethod.jp/articles/ec2-kinesis-agent-s3/	kinesis	2023-05-08 07:53:57
技術ブログ	Developers.IO	API Gateway カスタムオーソライザーの挙動を確認してみた	https://dev.classmethod.jp/articles/api-gateway-lambda-custom-authorizer/	apigatewayrestapi	2023-05-08 07:17:32
海外TECH	DEV Community	Katenary ile docker-compose'u helm chart'a çevirmek	https://dev.to/aciklab/katenary-ile-docker-composeu-helm-charta-cevirmek-4ajm	Katenary ile docker compose x u helm chart x a çevirmekKatenary uygulaması elinizde bulunan bir docker compose dosyasınıHelm Chart a çevirip Helm Kubernetes paket yöneticisi ile kurulabilmesini sağlar Katenary uygulamasıaçık kaynak kodlu bir uygulama olup golang dili ile yazılmıştır Katenary kurulumuBasitçe Katenary kurmak için aşağıdaki komutu çalıştırmanız yeterlidir Uygulamayıkullanabilmek için Kubernetes ortamına gereksinim yoktur sh lt curl sSL docker compose u Helm e çevirmeElinizde bir docker compose yml dosyasıolduğunu varsayarsak tek bir komut ile ilgili docker compose dosyasıHelm yapısına dönüşmektedir katenary convert c docker compose yml o chartsYukarıdaki komut ile docker compose yml bulunan dizinde charts isminde bir klasör oluşturarak içeriğinde loglarda görülebileceği gibi servis ve deployment yapılandırmalarınıiçermektedir İlgili komutu çalıştırdığınızda aşağıdaki gibi olumlu bir çıktıolmasınıbeklemekteyiz Do you really want to continue y N yGenerating deployment for ornekuygulamaGenerating deployment for redisGenerate volume values core for container named ornekuygulama in deployment ornekuygulamaGenerate volume values certs for container named ornekuygulama in deployment ornekuygulamaGenerating deployment for dbGenerating service for ornekuygulamaGenerating deployment for ornekikiGenerate volume values db for container named db in deployment dbGenerating service for dbBu şekilde olumlu olmayan durumlarda çeşitli docker compose yapılandırma ayarının eksik olduğu gibi bilgiler dönerek sizi ilgili bilgileri doldurmanızıteşvik etmektedir Helm chart klasörüiçeriğiBu şekilde oluşan klasör içerisinde Chart yaml ve values yaml dosyasıve templates klasörübulunmaktadır templates klasörüiçerisinde servis pvc ve deployment yapılandırma ayarlarıbulunmaktadır Kubernetes üzerinde sistemin ayağa kalkmasıiçin önemli dosyalardır Chart yaml dosyasıiçerisinde Helm Chart paketi için temel bazıiçerikler otomatik oluşmaktadır ve yaklaşık olarak aşağıdaki gibidir Katenary command line katenary convert c docker compose yml o chartsapiVersion vappVersion description A helm chart for ornekuygulamaname ornekuygulamatype applicationversion values yaml dosyasıiçerisinde kubernetes ortamıayağa kalkarken gerekli olan değişkenleri tutmaktadır Bunlar servis ve deploymenlar için hem ortam değişkenleri hem repository ve imaj bilgileri hem dosya storage bilgileri olabilmektedir Helm Chart dosyasıoluşturmaHelm Chart klasöründen dosya oluşturabilmek için Chart yaml dosyasının olduğu yerde aşağıdaki komut ile bir kontrol yapılabilir Bunun için öncelikle Helm in de yüklüolmasıgerekmektedir Bu durum için Kubernetes ortamıkurulu olmasıgerekmemekte sadece Helm yüklüolmasıyeterlidir helm lintBu komutla temel düzeyde bir paket kontrolüsağlanmaktadır Örneğin bu komut ile ikon bilgisinin eksik olduğunu aşağıdaki şekilde dönerek sorun olmadığınıbelirtmektedir gt Linting INFO Chart yaml icon is recommended chart s linted chart s failedSonrasında bir üst dizine Chart yaml ın bulunduğu dizinin üst dizini yani klasörün olduğu dizine çıkarak helm package komutu uygulanabilir cd helm package ornekuygulamaBu adım sonrasında aşağıdaki gibi Helm Chart oluşmaktadır Successfully packaged chart and saved it to PATH charts ornekuygulama tgz Elle Helm Chart kurulumuOluşan dosya Kubernetes ortamına entegre helm yapısıüzerinde aşağıdaki gibi kurulabilmektedir helm install ornekuygulama tgz generate name Başkalarının yaptıklarına söylediklerine ve düşündüklerine aldırışetmeyen sadece iyi bir insan olmak için kendi yaptıklarıyla ilgilenen bir insan ne çok zaman kazanır Marcus Aurelius Kendime	2023-05-08 07:50:00
海外TECH	DEV Community	Have ChatGPT Scrape your Website	https://dev.to/polterguy/have-chatgpt-scrape-your-website-2lpo	Have ChatGPT Scrape your WebsiteOur ChatGPT website chatbot AI Expert System and AI Website Search is based upon scraping your website The technique is actually quite simple However how can we end up having so much higher quality than most others What we do is really simple We scrape your website then we store your website s text as context snippets in a database When users asks a question to our ChatGPT website chatbot we use OpenAI s embedding API to look for the most relevant context snippets and attach this as a context to the question before we send the question to ChatGPT This allows OpenAI to return an answer to your question using the supplied context as its foundation for its answer Fundamentally you could argue the following We send the question AND the answer to ChatGPT and ChatGPT compiles a functioning response answering the question with the answer we ve already sent to it as a part of the request The end result is that ChatGPT can provide answer to questions it had no idea how to answer in its original state You could argue that what we re doing is fancy prompt engineering based upon automation AI based semantic search and database lookups The above sounds simple right In fact it is so simple that over the last few months thousands of developers and companies have done it Since we originally invented this technique thousands of companies have copied us Still every time somebody contacts us for a quote we hear the same over and over again I ve tried dozens of your competitors and you guys are simply the best Quality Website ScrapingEverything relies upon having an amazing website scraper This is where we are different and quality website scraping is our unique selling point To understand why realise first that when you scrape your website you need to somehow create super high quality data The reason is because you want ChatGPT to be able to create associations such that the user can ask questions such as What s the difference between product x and y The quality of your website chatbot is never higher than the quality of your context dataIf you just retrieve the HTML and store it in your database associations becomes impossible because of OpenAI s maximum token count In addition you will add a lot of irrelevant HTML tags to your context which ends up becoming noise to ChatGPT preventing it from returning a high quality response If your context snippets are too large each question will only be able to use one or two training snippets as its context What you want is a lot of small context snippets that our AI Search algorithms can retrieve easily which describes one concept and one concept only This is counter intuitive for most developers since we ve heard mantras of big data for decades and we ve been taught how machine learning relies upon large data sets When the exact opposite is in fact true implying the smaller data sets and context snippets you ve got the higher the quality becomes Super high quality AI is about SMALL data sets The way we solve this is by chopping up a single web page into multiple training context snippets during scraping resulting in many small snippets instead of one large In addition we calculate the number of tokens each snippet consumes and if the number is larger than of the maximum context token count for the model s configuration we actually use ChatGPT to create a summary of the training snippet before we insert it into the database as context data Needless to say of course but we also obviously remove all HTML tags as we scrape your website How our Website Scraper chops up your WebsiteOur website scraper algorithm will chop up each page into multiple context snippets according to where its Hx tags are and then create one context snippet for each Hx tag combined with all paragraphs below the Hx tag In addition we will keep hyperlinks and images and create Markdown from these allowing our chatbot technology to also display images and hyperlinks due to some intelligent prompt engineering trickery This is why our chatbots can display images and hyperlinks where most others can not This is why a website with web pages ends up becoming training snippets In addition to the above technique we also prevent inserts of the same training snippets twice A typical website contains navigation elements and footer elements These are often repeated in every single page in your site If we inserted the same training snippet twice any question that triggers these repeated elements will repeat the same context snippet multiple times spending valuable OpenAI tokens preventing ChatGPT from returning high quality responses Notice our ChatGPT website scraping technology even allows for semantically traversing websites without a sitemap and intelligently parse URLs from your HTML if your site does not have a sitemap Obviously it prefers sitemaps and will prioritize using sitemaps if existing but it will work even if your site does not have a sitemap This is a similar process to what Google uses and even though Google obviously have years of experience doing this I would argue our website scraper is probably almost as good as Google s crawling technology For the record you can see our website crawler in your web server s logs since we correctly identify it as a crawler And yes we for the most parts also respect robots txt files Although some additional work needs to be done here and will be implemented in the future Periodic crawlingOur chatbot technology is built upon Hyperlambda Hyperlambda makes it very easy to create scheduled tasks that are executing periodically given some repetition pattern Once every day we will execute such a scheduled task that crawls your site and checks for new URLs Each new URL is then scraped and context data created for it using the process described above This implies that if you add a new page or article to your website within hours our chatbots will be able to answer questions related to your article automatically without any effort required from you The background task is executed on a background thread and is async in nature implying the server CPU costs of this process is almost zero For the record this isn t even possible in theory using PHP due to its lack of multi threading Website Scraping Advanced FeaturesIn addition to the above we also allow for spicing models with individual pages taken from for instance WikiPedia CNBC or whatever really We use the same technique as illustrated above except when spicing a model we only retrieve the exact URL specified and we don t crawl the URL You can also crawl multiple sites in the same model but you can only have periodic crawling of one base URL If you crawl multiple sites in the same model you have to scrape one of your URLs once and only have one URL being periodically re scraped as new pages are added In addition to the above you can also manually insert context data and do any amount of CRUD towards your training data including filtering searching ordering creating inserting updating and deleting context data Interestingly this part of our technology was automatically created using Magic s Low Code features in seconds wrapping the related database tables in CRUD endpoints automatically Magic is a Low Code platform allowing us to deliver features a bajillion times faster than everybody else and we are taking advantage of that fact for obvious reasons ConclusionI ve seen a bajillion copy cat companies popping out from apparently nowhere these last months trying to copy our technology since it seems so easy However creating a chatbot that performs is easy Any schmuck with a PHP editor can do that However the difference is in the quality Where any schmuck with an IDE can deliver our stuff delivers almost automatically out of the box For instance PHP doesn t even have support for background threads How are you going to implement periodic crawling without background threads Implementing the same quality as we ve got is not even possible in theory using traditional programming languages such as PHP or Python My suggestion to you is to instead of implementing this yourself which you cannot do even in theory is to instead rely upon the fact that we ve got APIs for everything allowing you to create your own ChatGPT chatbot frontend and rely upon our API in the background This would allow you to integrate a ChatGPT chatbot with for instance WhatsAppTelegramiPhone SDKAndroid SDK whatever really WITHOUT having to reinvent the wheel but instead rely upon our amazing ChatGPT website scraping technology We also have a very lucrative partner program for those wanting to incrementally build on top of our stuff and we d love to help you market whatever you build on top of our stuff since instead of becoming a competitor you d enter a symbiotic relationship with us if you chose to partner up with us Besides not even Jasper can compare to our tech foundation Even companies with dozens of employees having existed for years are pale in comparison to our tech and quality This might sound incredibly arrogant especially considering there are only people working at AINIRO But we ve literally got the best ChatGPT website scraping technology on the planet	2023-05-08 07:39:55
海外TECH	DEV Community	Realistic Switch button in CSS	https://dev.to/jon_snow789/realistic-switch-button-in-css-2a2h	Realistic Switch button in CSSRealistic Switch button in CSS HTML Code lt input name switch id switch type checkbox gt lt label class switch for switch gt lt label gt CSS Code switch visibility hidden clip rect position absolute left px switch display block width px height px margin px auto position relative background cedda background linear gradient left cedda dee ccdd ddcdf ffff eeec bbfc filter progid DXImageTransform Microsoft gradient startColorstr cedda endColorstr bbfc GradientType transition all s ease out cursor pointer border radius em box shadow px px rgba inset px rgba inset px px rgba px px rgba Visit for more free css animation switch before display block position absolute left px right px top px bottom px z index content border radius em background ddde background linear gradient ddfe bcccd box shadow inset px rgba inset px px px rgba px px rgba px px px rgba pointer events none transition all s ease out switch after content position absolute right px top width px height px border radius background b margin top px z index box shadow inset px px rgba inset px px rgba px white px rgba px px px px rgba switch checked switch background bbfc background linear gradient to right bbfc eeec ffff ddcdf ccdd dee cedda filter progid DXImageTransform Microsoft gradient startColorstr bbfc endColorstr cedda GradientType switch checked switch after background bffff box shadow inset px px rgba inset px px rgba px white px rgba px px px px rgba Thanks for Reading ️ Check my website Demo coding for updates about my latest CSS Animation CSS Tools and some cool web dev tips Let s be friends Don t forget to subscribe our channel Demo code	2023-05-08 07:15:00
海外TECH	DEV Community	Developing a Desktop Application via Rust and NextJS. The Tauri Way.	https://dev.to/valorsoftware/developing-a-desktop-application-via-rust-and-nextjs-the-tauri-way-2iin	Developing a Desktop Application via Rust and NextJS The Tauri Way IntroductionThis article introduces you to a specific but exciting topic and is the sequel to my previous article If you are keen on Rust integrations please read Node amp Rust Friendship Forever The NAPI rs Way I suppose all of you dear colleagues work or at least know about VSCode Did you think about the technologies used in VSCode creation You probably will be surprised if I tell you that VSCode is mainly written on Typescript But stop Typescript and Javascript are typical for web or backend based applications and VSCode is a standalone UI application Is it possible to create a Javascript based standalone UI application Yes it is If we had discussed this topic a couple of months ago I would have recommended ElectronJS if you were looking for a way to create a standalone Javascript application Also I would provide you the following list of popular Electron based applications Microsoft TeamsZoomSlack for DesktopWordPress for DesktopSkypeDiscordWhatsApp DesktopPostmanMongoDB CompassBut the modern IT World does not stand still and we ve already had a powerful ElectronJS competitor it could be its killer in the nearest future BTW Meet Tauri If you want to get a brief comparison Tauri with Electron please read this article Goodbye Electron Hello Tauri will also be helpful if you want to understand Tauri pros and some brief technical details There is a brief comparison for my impatient readers Framework Frontend Backend ElectronChromium browserNodeJSTauriNative WebviewRust compiled codeOne small note regarding Native Webview meant above You can find ultimate information on this topic here In a nutshell Tauri applications use as HTML renderer Webkit safari engine on MacOS Microsoft Edge WebView on Windows and WebKitGTK on Linux port of Webkit for Linux Pay attention to the fact that a Tauri application could behave differently on different platforms according to the information above What thoughts would we conclude regarding the table above Tauri is about performance and simplicity As a developer who spent several years on Electron related projects I m pretty sure NodeJS could be a bottleneck for the following reasons NodeJS is a heavyweight solution with complicated architecture I mean V LibUV with Event Loop etc NodeJS is not a good choice if we need to implement heavy processes like image data processing or complicated math calculations Inter Process Communication Electron IPC is a way of communication between the Frontend and Backend in Electron Its functionality is overcomplicated in coding Implementing a multithreading NodeJS based Backend in our Electron based application could be a nightmare Tauri demolishes all of the cons above for the following reasons Rust complied code contains only the needed minimum of functionality without redundant architectural stuff like V or LibUV Rust is multithreading friendly and allows us to get multi platform implementations Rust is full of useful memory safe mechanisms that prevent developers from making the mistakes and as a result we get high quality predictable code Rust complied code is also more performative than NodeJS based In my opinion the pros above are critical for the Backend That s why according to the reasons above I found Tauri approach as a perspective BTW if you are not a Rust expert and want to know something new about Rust multithreading please read Multi threading for Impatient Rust Learners The ObjectiveOf course Tauri is something new Despite this it has good documentation There are many interesting articles on this topic and I recommend the following resources reading or watching Tauri a Rust powered Electron alternative a video allows us to do the first stepsGoodbye Electron Hello Tauri provides an exciting example including events between Frontend and Backend Tauri Next js explains how to provide NextJS based Frontend My objective is to provide you with something new to run and test I created a Tauri application with NextJS amp Ant Design based Frontend with some Backend calculations that look heavyweight This application shows us Progress Bar on a screen and related progress data is prepared on the Backend Rust side First StepsLet s get started Create Frontend partnpx create next app latest use npm typescriptAnswer the following questions Install Tauri dependenciescd tauri nextjs demonpm i save dev tauri apps clinpm i tauri apps api save UpdatesUpdate next config js type import next NextConfig const nextConfig reactStrictMode true Note This feature is required to use NextJS Image in SSG mode See for different workarounds images unoptimized true module exports nextConfig Update scripts section in package json scripts dev next dev build next build export next export start next start tauri tauri lint next lint Initialize Backend Tauri partnpm run tauri initAnswer the following questions Answer the following questions src tauri folder contains our backend part Backend functionalityThe first bootstrapped version contains a minimal set of functionality Let s fix it Please open src tauri src main rs and put the following code cfg attr all not debug assertions target os windows windows subsystem windows use tauri Window use std thread time derive Clone serde Serialize struct Payload progress i tauri command async fn progress tracker window Window let mut progress loop window emit PROGRESS Payload progress unwrap let delay time Duration from millis thread sleep delay progress if progress gt break fn main tauri Builder default invoke handler tauri generate handler progress tracker run tauri generate context expect error while running tauri application Pay attention to the points below progress tracker function should be called from the Frontend Typescript part tauri command is an attribute that defines the function above as a Javascript friendlywindow Window parameter should be passed from the Frontend side The loop inside progress tracker returns a number every ms times Pay attention on invoke handler tauri generate handler progress tracker in main function You must register your Frontend friendly function Also you need to change tauri identifier value in src tauri tauri conf json Say to com buchslava dev in my case After that change build beforeBuildCommand value to npm run build amp amp npm run export in the file above It s important because in this example we work with NextJS SSG Frontend first scratches Let s move to our Frontend part Move to the project s root folder and put the following code into src pages index tsximport invoke from tauri apps api tauri import listen from tauri apps api event import useEffect useState from react interface ProgressEventPayload progress number interface ProgressEventProps payload ProgressEventPayload export default function Home const busy setBusy useState lt boolean gt false useEffect gt listen what can Rust part tell us about const unListen listen PROGRESS e ProgressEventProps gt console log e payload progress return gt unListen then f gt f return lt div gt busy amp amp lt button onClick gt setBusy true setTimeout async gt const appWindow await import tauri apps api window call Rust function pass the window await invoke progress tracker window appWindow setBusy false gt Start Progress lt button gt lt div gt It s time to run the example npm run tauri devLet s open Developer Console Right click on the screen gt Inspect gt Switch to Console tab and press Start Progress button Congrats We finished the basic Touri stuff and it s time to focus on Frontend upgrading You can find this solution here Add UI partWe need to add a Progress Bar widget to the screen and show the progress on it instead of Console First install Ant Design dependency npm i antd saveSecond remove all content from src styles Home module css Third put the following content into src styles globals css body position relative width vw height vh font family sans serif overflow y hidden display flex justify content center align items center Fourth put the following code into src pages index tsx instead the existing import invoke from tauri apps api tauri import listen from tauri apps api event import useEffect useState from react import Button Progress from antd interface ProgressEventPayload progress number interface ProgressEventProps payload ProgressEventPayload export default function Home const busy setBusy useState lt boolean gt false const progress setProgress useState lt number gt useEffect gt const unListen listen PROGRESS e ProgressEventProps gt setProgress e payload progress return gt unListen then f gt f return lt div gt lt div style width vw gt lt Progress percent progress gt lt div gt lt Button type primary disabled busy onClick gt setBusy true setTimeout async gt const appWindow await import tauri apps api window await invoke progress tracker window appWindow setBusy false gt Start Progress lt Button gt lt div gt Let s look at the result npm run tauri devLooks good But I m a suspicious guy and I must be sure that everything between Rust and NextJS parts stays together I want to add a timer to the Frontend screen As a result Progress and Timer should work simultaneously without stops Let s put the following code into src pages index tsx instead the existing import invoke from tauri apps api tauri import listen from tauri apps api event import useEffect useState from react import Button Progress from antd interface ProgressEventPayload progress number interface ProgressEventProps payload ProgressEventPayload export default function Home const busy setBusy useState lt boolean gt false const progress setProgress useState lt number gt const timeLabel setTimeLabel useState lt string gt useEffect gt const timeIntervalId setInterval gt setTimeLabel new Date toLocaleTimeString const unListen listen PROGRESS e ProgressEventProps gt setProgress e payload progress return gt clearInterval timeIntervalId unListen then f gt f return lt div gt lt div style position fixed top left gt timeLabel lt div gt lt div style width vw gt lt Progress percent progress gt lt div gt lt Button type primary disabled busy onClick gt setBusy true setTimeout async gt const appWindow await import tauri apps api window await invoke progress tracker window appWindow setBusy false gt Start Progress lt Button gt lt div gt It s time to make the last stitch Till we have progress functionality we need to stop it somehow The following modifications allow us to do it src tauri src main rs cfg attr all not debug assertions target os windows windows subsystem windows use tauri Window use std thread time use std sync Arc RwLock derive Clone serde Serialize struct Payload progress i tauri command async fn progress tracker window Window New code let stop Arc new RwLock new false let stop clone Arc clone amp stop let handler window once STOP move stop clone write unwrap true New code let mut progress loop New code if stop read unwrap break New code window emit PROGRESS Payload progress unwrap let delay time Duration from millis thread sleep delay progress if progress gt break window unlisten handler New code fn main tauri Builder default invoke handler tauri generate handler progress tracker run tauri generate context expect error while running tauri application src pages index tsximport invoke from tauri apps api tauri import listen from tauri apps api event import useEffect useState from react import Button Progress from antd interface ProgressEventPayload progress number interface ProgressEventProps payload ProgressEventPayload export default function Home const busy setBusy useState lt boolean gt false const progress setProgress useState lt number gt const timeLabel setTimeLabel useState lt string gt useEffect gt const timeIntervalId setInterval gt setTimeLabel new Date toLocaleTimeString const unListen listen PROGRESS e ProgressEventProps gt setProgress e payload progress return gt clearInterval timeIntervalId unListen then f gt f return lt div gt lt div style position fixed top left gt timeLabel lt div gt lt div style width vw gt lt Progress percent progress gt lt div gt lt Button type primary disabled busy onClick gt setBusy true setTimeout async gt const appWindow await import tauri apps api window await invoke progress tracker window appWindow setBusy false gt Start Progress lt Button gt New code lt Button type primary disabled busy onClick async gt const appWindow await import tauri apps api window await appWindow emit STOP setProgress setBusy false gt Stop Progress lt Button gt New code lt div gt Looks persuasive Frontend Backend Communication in Tauri Implementing Progress Bars and Interrupt Button will tell you more regarding the technique above You can find the related source here The FastsFinally I want to focus on build stuff Let s build the app BTW I m working under MacOS Please read this one if you want to get more about Tauri build Let s build npm run tauri buildThe next information will help you understand where and what you can find regarding the result of the build You can find your build in src tauri target release bundle In MacOS you will find the standalone application src tauri target release bundle macos with the installer based build src tauri target release bundle dmg The most exciting thing here is the Mb application and Mb installer Can you believe it Mb of Rust amp NextJS amp Ant Design Do you want to compare Tauri s result with Electron s one Honestly when I got this result my memories from my past returned I remember mb hard disks and IBM PC XT I also thought about the following Amazing I can put an application from to my PC from Sounds like a time machine PS Thanks to Eduardo Speroni for helpful notes that improve the article	2023-05-08 07:08:34
医療系	医療介護 CBnews	コロナ死亡者が2週連続増、新規入院も微増傾向-感染研サーベイランス週報	https://www.cbnews.jp/news/entry/20230508163938	国立感染症研究所	2023-05-08 17:00:00
医療系	医療介護 CBnews	都道府県の指定ないなら特例水準の協定締結できず-医師の時間外労働、厚労省が解釈示す	https://www.cbnews.jp/news/entry/20230508163215	都道府県	2023-05-08 16:47:00
医療系	医療介護 CBnews	医療材料・光熱水費が2年で約790億円増、大学病院-23年度見込み	https://www.cbnews.jp/news/entry/20230508161730	大学病院	2023-05-08 16:30:00
海外ニュース	Japan Times latest articles	American School in Japan unveils master plan for renewed campus	https://www.japantimes.co.jp/news/2023/05/08/national/american-school-in-japan-renovation/	American School in Japan unveils master plan for renewed campusRenderings of ASIJ s possible new look depict a winding river shaped building that allows its elementary middle and high schools to flow into and interact with	2023-05-08 16:11:00
海外ニュース	Japan Times latest articles	50 students ill as gas smell reported at Osaka elementary school	https://www.japantimes.co.jp/news/2023/05/08/national/osaka-school-gas-smell/	students ill as gas smell reported at Osaka elementary schoolPolice received a report from firefighters at around a m that a gaslike odor had been detected at Kamei Elementary School in the city of	2023-05-08 16:05:17
ニュース	BBC News - Home	Texas mall shooting: Officials probe gunman's possible far-right links	https://www.bbc.co.uk/news/world-us-canada-65521656?at_medium=RSS&at_campaign=KARANGA	links	2023-05-08 07:11:59
ニュース	BBC News - Home	India Kerala: At least 22 dead as boat capsizes	https://www.bbc.co.uk/news/world-asia-india-65522435?at_medium=RSS&at_campaign=KARANGA	muddy	2023-05-08 07:47:05
ビジネス	不景気.com	メガネの愛眼の23年3月期は8億円の最終赤字へ、客数減で - 不景気com	https://www.fukeiki.com/2023/05/aigan-2023-loss2.html	業績予想	2023-05-08 07:45:49
ビジネス	不景気.com	シードの23年3月期は3億円の最終赤字へ、海外不振で減損 - 不景気com	https://www.fukeiki.com/2023/05/seed-2023-loss.html	最終赤字	2023-05-08 07:34:40
ビジネス	東洋経済オンライン	米国の輸入に占める｢中国比率｣下がり続ける背景 電子機器などの生産がベトナムやインドに移転 | 「財新」中国Biz＆Tech | 東洋経済オンライン	https://toyokeizai.net/articles/-/669406?utm_source=rss&utm_medium=http&utm_campaign=link_back	biztech	2023-05-08 16:30:00
IT	週刊アスキー	ツイッター、気象警報や交通情報などの発信にはAPIを無料提供すると発表	https://weekly.ascii.jp/elem/000/004/135/4135675/	交通情報	2023-05-08 16:45:00
IT	週刊アスキー	横浜ベイホテル東急にて北海道の食材を使用したスイーツなどが並ぶ“平日限定”アフタヌーンティー「スーツァン・アフタヌーンティー」開催中　6月30日まで	https://weekly.ascii.jp/elem/000/004/135/4135643/	中国料理	2023-05-08 16:40:00
IT	週刊アスキー	『三國志 覇道』の公式生放送が5月15日に放送決定！	https://weekly.ascii.jp/elem/000/004/135/4135674/	pcsteam	2023-05-08 16:40:00
IT	週刊アスキー	【関東甲信越のローソン限定販売】長野の人気ラーメン店コラボ 「気むずかし家監修 信州味噌らーめん」発売中	https://weekly.ascii.jp/elem/000/004/135/4135619/	信州味噌	2023-05-08 16:30:00
IT	週刊アスキー	盲目の少年が「見ている世界」をVRで表現　新宿のXR施設「NEUU」にてVRアニメーション「Thank you for sharing your world」上映中	https://weekly.ascii.jp/elem/000/004/135/4135632/	nkyouforsharingyourworld	2023-05-08 16:30:00
IT	週刊アスキー	PS VR2版『Organ Quarter（オーガンクォーター）』本日配信！90年代のサバイバルホラー体験が楽しめる	https://weekly.ascii.jp/elem/000/004/135/4135672/	organquarter	2023-05-08 16:30:00
IT	週刊アスキー	Slack、ChatGPTなどを機能として組み込める「Slack GPT」発表	https://weekly.ascii.jp/elem/000/004/135/4135663/	chatgpt	2023-05-08 16:15:00
IT	週刊アスキー	Luup、青山の小原流会館に電動キックボード「LUUP」のポートを導入	https://weekly.ascii.jp/elem/000/004/135/4135662/	商業施設	2023-05-08 16:10:00
マーケティング	AdverTimes	来店動機の促進に寄与 コメダのファンコミュニティ「さんかく屋根の下」	https://www.advertimes.com/20230508/article418380/	伊藤綾子	2023-05-08 07:33:35
マーケティング	AdverTimes	木住野彰悟・村上雅士らが参加「グラフィックトライアル2023」開催	https://www.advertimes.com/20230508/article418282/	凸版印刷	2023-05-08 07:17:21