投稿時間:2021-12-15 20:34:44 RSSフィード2021-12-15 20:00 分まとめ(34件)

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TECH	Engadget Japanese	次世代トランシーバー『BONX BOOST』でサイクリング、車通りが多くてもノイズがほとんど無い!	https://japanese.engadget.com/bonx-boost-103048363.html	bonxboost	2021-12-15 10:30:48
TECH	Engadget Japanese	Google フォトの思い出機能、ウェブ版でも幅広く展開開始	https://japanese.engadget.com/google-photos-desktop-100050119.html	google	2021-12-15 10:00:50
IT	ITmedia 総合記事一覧	[ITmedia ビジネスオンライン] Uber Eats初のリアル店舗、東京・日本橋にオープン　食品など1100点以上を取り扱い	https://www.itmedia.co.jp/business/articles/2112/15/news153.html	itmedia	2021-12-15 19:18:00
IT	ITmedia 総合記事一覧	[ITmedia News] 新海誠監督の最新作「すずめの戸締まり」22年秋公開　「楽しい映画になるはず」	https://www.itmedia.co.jp/news/articles/2112/15/news154.html	itmedia	2021-12-15 19:10:00
python	Pythonタグが付けられた新着投稿 - Qiita	Pythonライブラリ開発のための環境構築	https://qiita.com/kirin123kirin/items/b72a34257609fd2d7297	Pythonライブラリ開発のための環境構築開発環境の利用目的Windowsbit環境で開発する自分の現在の用途はPythonパッケージの作成が主である。	2021-12-15 19:56:01
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	latexの二つの\sumの添字領域を共有したい	https://teratail.com/questions/373974?rss=all	latex	2021-12-15 19:48:28
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	Pandasでqueryを使って条件抽出する方法	https://teratail.com/questions/373973?rss=all	Pandasでqueryを使って条件抽出する方法クラスタリングをして、その後、満足度がまたはのものだけを抽出してヒートマップで可視化したいです。	2021-12-15 19:48:10
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	numpy ブールインデックス参照+ファンシーインデックスによる代入ができない	https://teratail.com/questions/373972?rss=all	numpyブールインデックス参照ファンシーインデックスによる代入ができない問題ブールインデックス参照ファンシーインデックスによる代入ができないpythonnbspnumpynbspを使って代入操作で少しトリッキーなことブールインデックス参照ファンシーインデックスによる代入をしたいのですがうまくいきません。	2021-12-15 19:47:29
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	AtCoder Beginner Contest B問題で1例だけ誤答になる	https://teratail.com/questions/373971?rss=all	AtCoderBeginnerContestB問題で例だけ誤答になる前提・実現したいことプログラミング始めたての初心者です。	2021-12-15 19:35:54
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	ローカル環境の Django REST framework で作成したAPIに対してリクエストし、レスポンスを得たい	https://teratail.com/questions/373970?rss=all		2021-12-15 19:25:07
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	pandasで作成した散布図をエクセルに画像として保存したい	https://teratail.com/questions/373969?rss=all	pandasで作成した散布図をエクセルに画像として保存したい前提・実現したいことpandasで作成した散布図をエクセルに画像として保存したい該当のソースコードdfnbspnbsppdreadexcelaposcontentdriveMyDrivexlsxaposdfplotscatterxaposRecencyaposnbspyaposMonetaryaposdfplotscatterxaposRecencyaposnbspyaposFrequencyaposdfplotscatterxaposFrequencyaposnbspyaposMonetaryaposその後に、上記つの散布図をエクセル内に画像として保存する方法をご教示いただきたいです。	2021-12-15 19:21:47
AWS	AWSタグが付けられた新着投稿 - Qiita	はじめてEKS/ArgoCDを触る人に向けた手順書	https://qiita.com/kahirokunn/items/328a30a1ecf41f7807d1		2021-12-15 19:15:30
Docker	dockerタグが付けられた新着投稿 - Qiita	コンテナを介して攻撃者にボコボコにされないためのtips	https://qiita.com/YuasaJunki/items/8da1ef708a6f826f5915	コンテナ内でrootユーザーを使用しないDockerコンテナ内ではデフォルトでroot権限でプロセスが実行されます。	2021-12-15 19:33:20
技術ブログ	Developers.IO	SMSでテストメッセージを送ってみた	https://dev.classmethod.jp/articles/sms-send-testmessage/	送信	2021-12-15 10:40:56
海外TECH	DEV Community	What is PyTorch: a Summary Guide for Beginners	https://dev.to/imagescv/what-is-pytorch-a-summary-guide-for-beginners-3eeb	What is PyTorch a Summary Guide for BeginnersPyTorch is a deep learning framework that was created by Facebook It allows you to use Python as your main programming language which provides flexibility and speed for many programmers who work with machine learning tasks PyTorch is also GPU accelerated which makes it preferable for many users This blog post will provide an overview of what PyTorch is and how to get started using this powerful tool What Are Some Key Features of PyTorch PyTorch has several key features that make it stand out as a deep learning framework Some of these include It s Python basedPyTorch uses Python as its main programming language which is an extremely popular choice for programmers who work with machine learning tasks every day This gives you the flexibility and speed you need to get your tasks done quickly However if python isn t your preferred language then another great feature comes into play ️GPU acceleratedGPU acceleration makes PyTorch preferable for many users because this allows them to run their code much faster than they would be able to without using GPUs If this doesn t sound like something you ll use or care about right now then keep reading because there are still several other reasons why PyTorch is a great choice for you 🪢The use of TensorsTensors are at the heart of PyTorch and this allows you to easily create and manipulate your data in ways that other frameworks don t always allow This makes PyTorch an extremely powerful tool for many different tasks PyTorch ModulesPyTorch also has several modules that you can use to expand its functionality These include torchvision for image processing torchaudio for audio processing and more Having these modules available makes it possible to do a wide range of deep learning tasks with ease FlexibilityPyTorch is flexible in the sense that you can use it for many different deep learning applications Whether your data comes from python or an external source like Caffe PyTorch has a way to handle and work with this data in order to get results quickly and effectively This makes it possible to solve problems fast when they arise on the job site which keeps everyone happy ️SpeedPyTorch is known for its speed which makes it great for researchers and data scientists who need to get their work done quickly The python interface combined with GPU acceleration means you can do all this without having to worry about spending hours trying to figure out how something works or getting stuck on tasks that should be simple This lets your team focus on the important things instead of wasting time debugging code Who Can Benefit From Using PyTorch There are many different people who could benefit from using PyTorch including Data Scientists Researchers Software Engineers Developers and QA Testers because there isn t anyone particular industry where it wouldn t be useful If you re looking at machine learning as a possible solution to a problem you re facing then PyTorch is definitely worth taking a look at In conclusion PyTorch is a deep learning framework that was created by Facebook It allows you to use Python as your main programming language which provides flexibility and speed for many programmers who work with machine learning tasks PyTorch is also GPU accelerated which makes it preferable for many users It has several key features that make it stand out as a deep learning framework including python based GPU accelerated tensors modules flexibility and speed PyTorch can be used by many different people in a wide range of industries to solve machine learning problems quickly and effectively If you re looking for a deep learning framework that has all the features you need then PyTorch is definitely worth taking a look at images cv provide you with an easy way to build image datasets K categories to choose fromConsistent folders structure for easy parsingAdvanced tools for dataset pre processing image format data split image size and data augmentation Visit images cv to learn more	2021-12-15 10:11:47
海外TECH	DEV Community	Widget Driven Development	https://dev.to/aantipov/widget-driven-development-1n5m	Widget Driven Development PrefaceWhen developing UI applications we compose them from components Each UI component is essentially a combination of markup scoped styles and some UI logic Data Management is frequently left out of components control resulting in a complicated architecture with convoluted data flows In this article I ll demonstrate how we can transform components into autonomous isolated widgets with complete control over both Data Logic and UI The History of ComponentsWidgets in my opinion are the natural successors of Components To see this I suggest going back in time and look at how our approaches to building UI have evolved over time Many remember the times when all application styles were defined in a single global CSS file Styles definitions used complex combinations of different CSS selectors Style collisions were common in apps The size and complexity of those styles sometimes affected even the performance of websites In BEM was born BEM provided a set of guidelines for defining styles and naming classes These rules were intended to address the problem of style collisions and inefficient selectors BEM encouraged to think of UI in terms of blocks elements and modifiers marked the rise of Components approach React made it simple to divide UI into components that were a combination of markup HTML and UI logic JavaScript It was a game changer in application development Other frameworks soon followed suit adopting a components based approach as well With the rise of build tools CSS preprocessors and techniques like CSS in JS and CSS Modules it became feasible to make Styling a part of Components Components playgrounds such as Storybook emerged to help developers build components in an isolated environment and ensure proper styles scoping They encouraged developers to think of UI as a function of state components props values defined the look and behaviour of components Collections of reusable high quality components became a thing The unresolved hurdlesComponent driven approach helped break UI into isolated reusable pieces and enabled building large scale applications using collections of pre built components What was missing though is a way of supplying UI components with data Data management became one of the most difficult tasks in Frontend Engineering and the primary contributor to the complexity of UI apps We learned to split components into two types Presentational components which are responsible for UI representation and are usually stateless and side effect freeContainer components which deal with data related logic and pass data down to Presentational components All that remains is to define how Container components should work with data The Naive approachThe naive approach would be for each Container component to simply fetch data needed by underlying Presentational components Because the same data is usually needed by multiple different components implementing such an approach in practice would bring a bunch of problems duplicated requests and data over fetching Slow UI and overloaded server as a result possible data inconsistency between components when requests to the same endpoint result in different datacomplicated data invalidation think of a case when the data has changed on Backend and you need to make sure every dependent component refetches the data The Common parent approachWe learnt to overcome the problem by moving data fetching and mutation functionality up to common parent components which pass data down to all underlying components We solved the problem of requests duplication and data invalidation However we did face new challenges the whole application logic became more complex and more coupledwe were forced to pass data down through multiple components This issue became notorious and got a name “Prop Drilling The State Management approachTo bypass the Prop Drilling problem we learnt to use State Management libraries and techniques instead of propagating data down to underlying components we place data in some Store that is accessible to all the components down the tree letting them obtain the data directly from there Components subscribe to the changes in the Store to have the data always up to date The Prop Drilling issue was resolved but not for free we now have to deal with a completely new concept the Store and care about a bunch of new things such as designing and maintaining Store structure appropriately updating data in the Store data normalization mutable vs immutable a single store vs multiple stores and so on state management libraries require us to learn a new vocabulary Actions Action Creators Reducers Middlewares Thunks and so on the introduced complexity and lack of clarity forced developers to create styleguides on how to work with the Store what to do and what to avoid as a result our applications became very tangled and coupled Frustrated developers try to mitigate the issues by inventing new state management libraries with different syntax The Naive approach reimaginedCan we do better Is there an easier way to approach data management Can we have the data flows transparent and easy to understand Can we untangle our apps and boost orthogonality Can we bring Data Logic under control of Components in the same way that we have done with Markup Styles and UI Logic We must have gotten too far into the woods and can t see the forest for the trees Let s go back to the starting point to the Naive approach and see if we can solve its problems differently The main bummers there were requests duplication and data inconsistency What if we could have an intermediate player between our components and Backend say an API wrapper or interceptor solving all those problems under the hood deduplicate all the requestsensure data consistency all the components should always have the same data when using the same requestprovide data invalidation ability if a component changes data on the server other components that rely on that data should receive the new databe transparent to components and not affect their logic in any way make components think they communicate to Backend directly The good news is that we can have it and there are already libraries providing such solutions some GraphQL clients e g RelayReact Query SWR Redux Toolkit Query Vue Query for RESTful APIsAll we basically need to do is to wrap every API call with such an API Wrapper The rest is handled automatically for us The huge benefit of such an approach is that we can finally untangle our applications data logic put Data Logic under control of Components and achieve better orthogonality by combining all pieces together Widget driven developmentIn my team we started to use the described above Naive approach together with React Query and we love it It enabled us to approach building our application differently Let me call it Widget Driven Development The idea is that we split every page into so called widgets which behave autonomously and are self contained Every widget is responsible for fetching and providing all the required data to its UImutating the related data on server if neededdata representation in the UIUI for Loading state optional UI for Error stateSpeaking of code organization we co locate all the widgets related files Usually the same API endpoint is used across multiple widgets So we decided to keep all of them in a separate shared folder We use React Query library and each file in the queries folder exposes fetch and mutation methods wrapped into React Query All Container components have a similar code structure import useParams from react router dom import useBookQuery from queries useBookQuery import useAuthorQuery from queries useAuthorQuery import Presentation from Presentation import Loading from Loading import Error from Error export default BookDetailsContainer const bookId useParams const data book isError isBookError useBookQuery bookId const data author isError isAuthorError useAuthorQuery book author if book amp amp author return lt Presentation book book author author gt if isBookError isAuthorError return lt Error gt return lt Loading gt Notice how easy and declaratively dependant queries are handled Also the only dependency of our widget is the presence of bookId in the URL Most of our widgets container components have no props and rely on no external state except for URL data Such an approach makes it transparent what API queries our widget relies upon That transparency combined with near to zero external dependencies makes it easy to test widgets and gives us confidence in our code Usually changes to a widget are limited by modifications to files under that widget s folder It significantly limits the risk of breaking any other parts of the application Adding new widgets is also very straightforward create a new folder for the widget with all required files in it and if necessary create a new query in the queries folder Again the risk of breaking any other parts of the application is very limited Every widget can also be easily reused on different pages thanks to the limited dependency on the context We usually just need to make sure the URLs of those pages contain the data identifiers needed for the widget ConclusionThe Components approach made easy and straightforward creation of reusable independent pieces of UI It didn t solve all the problems though and Frontend applications often suffer from convoluted Data Management There are libraries that enable approaching Data Management differently and significantly reduce the complexity of our applications Leveraging those libraries we can put data logic under control of components and convert an application into a set of reusable self contained widgets It makes the data flows transparent architecture flexible the code resilient and easy to test	2021-12-15 10:02:48
海外TECH	DEV Community	Blazingly fast Preview Environments for NextJS, NodeJS, and MongoDB on AWS	https://dev.to/pjeziorowski/blazingly-fast-preview-environments-for-nextjs-nodejs-and-mongodb-on-aws-o1k	Blazingly fast Preview Environments for NextJS NodeJS and MongoDB on AWS IntroductionHave you ever dreamed of deploying your applications on the cloud without any hassle Imagine a platform where all you need to do is to sign in with your AWS credentials and automagically the platform does all the hard work of configuration of the cloud for you and on top of that provides some extra features that do not exist out of the box anywhere else Qovery is this platform not only does it allow you to deploy your infrastructure and applications on your own cloud account but also provides extra cool features one of which we will see in this article Don t take our words for granted developers from more than countries use Qovery to deploy their apps on AWS Preview EnvironmentsImagine working on a new feature You re dealing with a full stack application you have a frontend backend and a database You introduce a change to your backend app how do you test all of it It would be great if there was a service that could deploy everything for you so you can test your changes quickly and in separation with all the components Qovery Preview Environments are designed to help you with exactly this It not only deploys the app you changed but all other related applications and databases as well in the cloud so that you can test your new features and collaborate with reviewers of your code Preview environments feature is available on other platforms as well Vercel and Netlify allows you to test your changes before merging code into production It s perfect for single frontend applications but the concept of Preview Environments on Qovery goes far beyond this Qovery is able not only to create a preview environment for your frontend but also for the backend and databases the whole stack is supported Running a set of backend microservices No worries Qovery got you covered All services will be replicated in the new environment Preview environments benefitsTime saving You don t have to set up a fresh environment to test changes in isolation Qovery does it all for youProductivity Faster changes quicker review better feedback loop the productivity and quality of your application increases dramaticallyBetter tests It s best to test apps in isolation but it s almost impossible with a complicated stack if you have to prepare the testing environment manually Qovery does it all automagically for youIndependence Each environment is completely separate meaning more people can work flawlessly on the project testing the changes they introduce in parallel not blocking each otherDeliver quickly Faster feedback loop independent developers fewer bugs meaning the product is delivered more quicklyReduce friction Waiting for others to test your changes is frustrating with preview envs everyone has his own testing environment Demo AWS InfrastructureBefore we start with the deployments we need to have our AWS infrastructure ready and deployed It can be done as simply as by providing credentials to your cloud account you can see how to configure the credentials in this article The initial setup takes about min and your cluster is ready to host your applications Full Stack ApplicationIn this example we will use a Next js frontend Node js backend and MongoDB as a database The app will display an image gallery with images fetched from the backend Preview Environments feature will help us introduce a new change in the backend moving away from a hardcoded POC list of images to a list fetched from our database FrontendOur simple image gallery will look like this To generate the application we used npx create next app latest but the source code can be found here The main changes introduced to the generated application scaffolding are Adding a DockerfileFROM node alpineRUN mkdir p usr srcWORKDIR usr srcCOPY usr srcRUN npm installRUN npm run buildEXPOSE CMD npm run startAdding a query to our backend which we will be built soon in the next steps that fetches a list of images to display in our galleryfunction useImages return useQuery images async gt const data await axios get apiRoot api v images return data Plus we adjusted the HTML and styling for the demo purpose of showing a list of images BackendOur backend is the main star of the demo In its first version the backend is displaying a hardcoded list of images In the next step we will gradually expand its capabilities It will connect to a database and fetch the list from MongoDB instead To make sure the changes are correct we will use Preview Environment feature before merging the pull request to our production environmentThe backend was generated using Express npx express generator no view and the source code can be found here Changes that we introduced to the generated app scaffolding are the following Adding a DockerfileFROM node WORKDIR usr src appCOPY package json RUN npm installCOPY EXPOSE CMD node src index js Creating a api v images endpoint that returns a hardcoded array of imagesrouter get images req res gt res json title IMG HEIC size MB source ixlib rb amp auto format amp fit crop amp w amp q In the next step we will improve the function to use a Mongo database instead DeploymentAfter creating a new project let s now set up our production environment First let s deploy our frontend Click Add my first application select a correct repository Docker as build mode and expose port The application root path is frontend Next step add a MongoDB database it will be used by our backend later on You can do so by clicking on Add button in Qovery Console in Environment Now let s deploy our backend Click Add →Application pick up backend as application root path port and Docker build mode For the future connection to DB let s add an alias named DATABASE URL that points to our Mongo database internal URL in our backend Environment Variable settings Additionally let s create an alias called API ROOT in our frontend application that points to our backend external URL This is it Now we can deploy our production environment After a few minutes navigate to the frontend app click on Open you should be redirected to the image gallery Enable Preview EnvironmentsThe next step to see the preview environment feature in action is to enable it for our backend application To do so navigate to Environment →Settings →Preview Env and tick it for the backend app Great The feature is enabled To see it in action let s edit our code in the backend app so that the list of images is fetched from the database instead Testing Preview EnvironmentsLet s make a small update of our backend let s connect to MongoDB and fetch images from there Here are changes to the function we could introduce to make it happen const databaseUrl process env DATABASE URL mongodb localhost test const imageSchema new mongoose Schema title String size String source String mongoose connect databaseUrl router get req res gt imageSchema find then data gt res json data Let s now create a new branch in our repository and create a pull request to our production master branch environment Preview Environments feature will spin up a new environment for us so that we can safely test changes we just introduced Now when we display environments in our project we will see that a new environment for the pull request is being deployed with all the resources we need A database backend frontend we can now test our changes in complete separation from the production without any manual setting up work Preview Environment ExplainedThe Preview Environment feature can be enabled or disabled per app It creates a complete copy of your environment so that you can test new changes from pull requests in separation It deploys your databases backend and frontend applications to a completely new environment once a pull request is opened If you update your pull request all new changes are also reflected in the new environment so that you can test them or fix problems during the review What is great is that Qovery takes care of managing all environment variables for you as well creates new aliases just as you had in your prod environment so that everything is really tested separately and it all happens automagically After the pull request is merged Qovery automatically cleans up the preview environment to save your money Testing Preview Environments PT IIAfter a few minutes your preview environment should be up and running You can now navigate to the frontend app and click Open in the image gallery you will see an empty list because we don t yet have any images in the database You can add a few images manually by connecting to your mongo instance via CLI The credentials can be found in the database overview After connecting let s add images by executing the following db createCollection images db images insert title IMG HEIC size MB source ixlib rb amp auto format amp fit crop amp w amp q title IMG HEIC size MB source ixlib rb amp auto format amp fit crop amp w amp q title IMG HEIC size MB source ixlib rb amp auto format amp fit crop amp w amp q Now after opening the frontend app in our preview environment we will see all the images we put in the database It looks like the feature is working well so let s merge the PR What now happens is automatically after the PR merge the preview environment is automatically cleaned up Great job Thanks to Qovery Preview Environments we managed to develop a new feature in a complete separation from our production we tested it in a real environment deployed in the cloud and we didn t have to spend any time preparing our environment for tests at all ConclusionIn the article we quickly went through the process of creating a full stack application with frontend backend and database We enabled the Preview Environment feature to develop new features more quickly We learned what the benefits of Preview Environments are how to use them and how to integrate them to day to day development workflow	2021-12-15 10:00:59
海外TECH	Engadget	US puts drone maker DJI and seven other Chinese companies on investment blocklist	https://www.engadget.com/us-government-china-dji-investment-blocklist-103514525.html?src=rss	US puts drone maker DJI and seven other Chinese companies on investment blocklistThe US government will place eight Chinese companies including drone manufacturer DJI on an investment blocklist for alleged involvement in surveillance of Uyghur Muslims the Financial Times has reported The firms will reportedly be put on the Treasure department s quot Chinese military industrial complex companies quot list on Tuesday meaning US citizens will be barred from making any investments nbsp DJI is already on the Department of Commerce s Entity list meaning American companies can t sell it components unless they have a license At the time the government said it was among companies that quot enabled wide scale human rights abuses within China through abusive genetic collection and analysis or high technology surveillance quot However unlike products from Huawei and others DJI drones are have not been banned for sale in the US nbsp The latest moves are part of an effort by US President Joe Biden to sanction China for repression of Uyghurs and other ethnic minorities in the Xinjiang region Others that will be added to the list include cloud computing firms and facial recognition companies that operate in Xinjiang Yesterday the US House and Senate passed a bill that would ban imports from Xinjiang unless companies could prove they were not made using forced labor It s set for a vote in the upper chamber of Congress prior to a holiday recess Xiaomi was placed on the same investment blocklist early in However it fought the decision saying that none of its principals were connected with the Chinese military and that a lack of US investment would lead to quot immediate and irreparable harm quot In May the government agreed to lift the ban nbsp In DJI commanded a massive percent of the consumer drone market Over the last two months it has released a pair of key products the large sensor Mavic drone and full frame Ronin D cinema camera with a built in gimbal and LiDAR focus system A year ago DJI said it had quot done nothing to justify being placed on the Entity list quot and that quot customers in America can continue to buy and use DJI products normally quot	2021-12-15 10:35:14
海外TECH	Engadget	Oppo’s Find N foldable phone has a more practical landscape screen	https://www.engadget.com/oppo-find-n-foldable-phone-china-101211924.html?src=rss	Oppo s Find N foldable phone has a more practical landscape screenSamsung s three generations of foldable phones put it in a leading position in the field so much that Huawei and Xiaomi eventually followed the same double screen form factor Having already shown a foldable prototype a couple of years ago it was only a matter of time before Oppo the world s fourth largest smartphone brand would join the scene After a teaser from earlier today the Chinese company unveiled the Find N which features a inch external display and unfolds into a inch flexible quot Serene Display quot What s special about this design is that Oppo went for a landscape aspect ratio ー x to be exact ーfor the flexible AMOLED screen which offers a more practical split screen usage A bit like Microsoft s Surface Duo except this is across one single panel Similarly the Find N s external AMOLED screen comes in a more familiar aspect ratio x as opposed to something like the narrow on Samsung s Galaxy Z Fold The shorter body should also make the device more pocketable than its competitors OppoOppo added that thanks to its special water drop flexion hinge design it s able to widen the angle of the flexible panel s fold thus reducing the crease ー quot up to percent less noticeable compared with other devices quot which is apparently certified by TÜV Rheinland The same mechanism allows for a no gap design when folded As for the flexible screen itself its layer structure apparently lets it withstand over folds ーeven at temperatures as low as degrees Celsius or degrees Fahrenheit Alas there s no IP rating for the Find N but Oppo reassures us that the device has passed the company s own humidity and splash tests To our surprise the Find N is powered by Qualcomm s slightly older Snapdragon as opposed to the upcoming Snapdragon Gen or the existing Snapdragon Plus Oppo explained that this is due to the longer development cycle of this project To be fair this G chipset is still plentiful plus the phone also comes with up to GB of LPDDR RAM and up to GB of UFS storage along with ColorOS based on Android which should keep things running smoothly on that Hz flexible screen though the external screen is capped at Hz Sanji Feng Engadget ChineseOther goodies in this g device include a megapixel f main camera Sony IMX sensor same as the Find X Pro a megapixel IMX f ultra wide camera plus a megapixel Samsung SKM f x telephoto camera on the back and a megapixel IMX f punch hole selfie camera on both the external screen and the inner screen There s a mAh battery which supports W SuperVOOC rapid charging and W AirVOOC wireless charging you can also use the phone for W reverse charging Unlike many recent flagship Androids unlocking is done with a side mounted fingerprint scanning power button rather than an under display fingerprint reader which makes sense since it d be a bit ambitious to work that sensor into the large flexible screen Sanji Feng Engadget ChineseOn the software side this version of ColorOS comes with a quot FlexForm Mode quot which lets you use the Find N in the form of a mini laptop This applies to use cases like video calls taking notes taking K time lapse photos of the sky and more Likewise you can use the external screen as a selfie viewfinder though this is nothing new in the world of foldables Sanji Feng Engadget ChineseMy favorite feature here is perhaps the split screen gesture simply use two fingers to swipe down the middle of the flexible screen and you ll instantly split the screen into two You can also tap the three dots in the middle of this virtual divider to create a shortcut for the current app combo If needed you can also use four fingers to pinch the large screen to turn the current app into a floating window nbsp Last but not least there s a quot seamless relay quot feature which lets you easily go from the large screen to the smaller external screen As soon as you fold the Find N the external screen will offer a five second window to let you swipe up and activate it Sanji Feng Engadget ChineseThe Find N comes in black white and purple with the purple offering being exclusive to its higher end model In China this new phone is immediately available for pre ordering ahead of its December rd launch with the base model GB RAM and GB storage asking for yuan about and the higher end model GB RAM and GB storage going for yuan around That s surprisingly affordable ーeven more so than Xiaomi s Mix Fold nbsp Sadly Oppo doesn t plan on bringing its first ever foldable to outside of China just yet but our review unit did just land on my doorstep a few hours ago I ll be spending the next few days figuring out whether this device lives up to its hype and whether I can even run Google services on it so stay tuned for our further impressions	2021-12-15 10:12:11
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