投稿時間:2021-05-09 18:44:35 RSSフィード2021-05-09 18:00 分まとめ(44件)

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python	Pythonタグが付けられた新着投稿 - Qiita	Pythonで英語or日本語を自動判定するには？	https://qiita.com/Splashing_Whale/items/7f66d29bca9dfa1b6098	ちなみに文字を指定wordのようにしてしまうと、その文字がスペースであった場合等に「SPACE」のような「どれでもないもの」が返却されてしまい、正しい判定ができなくなってしまいます。	2021-05-09 17:07:27
python	Pythonタグが付けられた新着投稿 - Qiita	【ESP32入門】ESP8266との比較と追跡カメラを制御する♪ ～flash read error 1000の解決～	https://qiita.com/MuAuan/items/ff7c7815ca393b9aabb8	※上記と合わせると、chipの指定とzxの指定が必要だったのかなと思います【参考】④ESPでesptoolpyの使い方・見かけの違いと利用できるPinについてこれは、アマゾンの販売サイトのespの画像やespサイトからpin配置から両者の比較をしてみます。	2021-05-09 17:06:24
js	JavaScriptタグが付けられた新着投稿 - Qiita	LeafletでGPSログ(GPX)地図：クライアントローカルGPXファイルを指定可能に。	https://qiita.com/ok2nd/items/e72bec63d9d7c83959a6	地図データを扱うJavaScriptライブラリ「Leaflet」を使って、GPSログGPXファイルの地図表示を試している。	2021-05-09 17:10:48
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	TGraphicのEqualsメソッドを使うには	https://teratail.com/questions/337384?rss=all	TGraphicのEqualsメソッドを使うには前提・実現したいことCBuildernbspnbspCommunitynbspEditionをインストールし、Webの情報を参考にプログラミングを学んでいるものです。	2021-05-09 17:48:34
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	Javaで変数の定義の仕方	https://teratail.com/questions/337383?rss=all	Javaで変数の定義の仕方前提・実現したいことJavaで簡単なゲームを作ろうとしています。	2021-05-09 17:35:02
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	Colab kerasのInstanceNormalizationでのエラー	https://teratail.com/questions/337382?rss=all	ColabkerasのInstanceNormalizationでのエラー前提GooglenbspColabで以下のコードを試していますが、Goodnbspoldnbspimportsという部分のInstanceNormalizationnbspの実行でエラーがでます。	2021-05-09 17:34:40
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	WP ページネーションが1ページと同じ内容になる	https://teratail.com/questions/337381?rss=all	WPページネーションがページと同じ内容になる再投稿Wordpressでサイトを作っています。	2021-05-09 17:33:12
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	LoadError: dlopen(/Users/user/.rbenv/versions/2.5.1/lib/ruby/gems/2.5.0/gems/mysql2-0.5.2/lib/	https://teratail.com/questions/337380?rss=all		2021-05-09 17:28:36
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	python 関数の記述場所と呼び出しについての疑問を解決したい	https://teratail.com/questions/337379?rss=all	下記のtestpyというファイルががあります。	2021-05-09 17:11:21
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	esp32を用いて作成した製品開発	https://teratail.com/questions/337378?rss=all	arduino	2021-05-09 17:11:06
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	ViewModelでContextを取得する際のgetApplication()について	https://teratail.com/questions/337377?rss=all	ViewModelでContextを取得する際のgetApplicationについて前提・実現したいことViewModel内でシステムサービスを利用したいと考えており、そのためにContextを取得する必要があります。	2021-05-09 17:06:07
Ruby	Rubyタグが付けられた新着投稿 - Qiita	バックスラッシュ記法早見表	https://qiita.com/ren0826jam/items/3a1593068d0dd2dfd359	unnnnunicode	2021-05-09 17:31:14
Ruby	Rubyタグが付けられた新着投稿 - Qiita	[Ruby]モジュールを使いこなしてみた。	https://qiita.com/ren0826jam/items/fa096b09a2afecc7d571	Rubyモジュールを使いこなしてみた。	2021-05-09 17:22:19
Ruby	Rubyタグが付けられた新着投稿 - Qiita	継承について理解したい！	https://qiita.com/ren0826jam/items/9314cffdd83cd55e9bed	継承について理解したいはじめに皆さんは、「継承」を使いこなせていますでしょうか開発において使わないことはないのですはないか、というくらいに頻繁に利用します。	2021-05-09 17:14:30
AWS	AWSタグが付けられた新着投稿 - Qiita	Amazon Web Services で IPv6 を使う	https://qiita.com/yh1224/items/21d889edc9bb1e9433c0	作成されたALBに直接設定すれば有効にすることはできますが、AAAAレコードをAlias設定する場合、Beanstalkのエンドポイントへ向けることはできないので、生成されたALBのエンドポイントに直接向ける必要があります。	2021-05-09 17:20:20
Docker	dockerタグが付けられた新着投稿 - Qiita	Docker 操作コマンド	https://qiita.com/takaikeee12/items/64ba2730a5a714addd05	以前起動していたコンテナを起動dockerrestartコンテナID起動したコンテナに入るdockerexecitコンテナ名コンテナIDでも可コマンド名例dockerexecitコンテナIDbinbashコマンド名コマンド名はPCのシェルに合わせます。	2021-05-09 17:09:01
GCP	gcpタグが付けられた新着投稿 - Qiita	AutoML Vision で物体検出モデルを作成する為の学習データセットをVoTTで作成してみた	https://qiita.com/yasuaki9973/items/b0808e28f3fc067a9181	※VoTTでエクスポート出来るフォーマットの中にAutoMLVisionでそのまま読み込めるものがない為、以降の手順でフォーマットを変換します。	2021-05-09 17:19:45
Azure	Azureタグが付けられた新着投稿 - Qiita	Azure API Management - SwaggerからのAPIインポート、Functionsとの連携	https://qiita.com/takmot/items/6605ab69fb49d930c4a0		2021-05-09 17:59:33
Git	Gitタグが付けられた新着投稿 - Qiita	Gitコマンドまとめてみた	https://qiita.com/elen-qiita/items/1ead08c740c093578aa2	Gitコマンドまとめてみたはじめにこれから就職するにあたって、いままで個人開発だけで済んでいたところチーム開発をする必要が出てきたので、使いたいコマンドをまとめてみた。	2021-05-09 17:36:03
Ruby	Railsタグが付けられた新着投稿 - Qiita	バックスラッシュ記法早見表	https://qiita.com/ren0826jam/items/3a1593068d0dd2dfd359	unnnnunicode	2021-05-09 17:31:14
Ruby	Railsタグが付けられた新着投稿 - Qiita	[Ruby]モジュールを使いこなしてみた。	https://qiita.com/ren0826jam/items/fa096b09a2afecc7d571	Rubyモジュールを使いこなしてみた。	2021-05-09 17:22:19
Ruby	Railsタグが付けられた新着投稿 - Qiita	継承について理解したい！	https://qiita.com/ren0826jam/items/9314cffdd83cd55e9bed	継承について理解したいはじめに皆さんは、「継承」を使いこなせていますでしょうか開発において使わないことはないのですはないか、というくらいに頻繁に利用します。	2021-05-09 17:14:30
技術ブログ	Developers.IO	[小ネタ]CloudFrontのSSLポリシー設定変更で状態を確認してみた	https://dev.classmethod.jp/articles/cloudfront-tool-sslscan/	cloudfront	2021-05-09 08:36:23
海外TECH	DEV Community	Best Udemy Courses To Level Up Your Web Development Skills	https://dev.to/thinkpader/best-udemy-courses-to-level-up-your-web-development-skills-37fe	Best Udemy Courses To Level Up Your Web Development SkillsAre you a beginner developer and want to level up your dev game and progress faster than your competition Read on and I ll give you honest reviews of some of the courses I ve taken on Udemy These are courses that I ve paid for using my hard earned money and this article is in no way sponsored by Udemy There are no affiliate links so you can be doubly sure that I m not putting any course here just to earn some extra bucks If you wish to purchase any of these courses then make sure you wait for a sale Udemy has them on a bi monthly basis For Absolute Beginners The Web Developer Bootcamp by Colt SteeleThis is the new version of Colt s The Web Developer Bootcamp Udemy s most popular web development course This course has been completely overhauled to prepare students for the job market and has over hours of brand new content Some of the highlights of the course are The instructor Colt Steele is extremely knowledgable and witty He makes the tricky stuff a lot less tricky his explanations are spot on and his cat and dog jokes make you chuckle The course everything a beginner web developer needs to know ーfrom HTML CSS Bootstrap JavaScript all the way to Node js Express and MongoDB It follows a logical structure so that the student you is not overwhelmed or confused There are a lot of mini exercises to re enforce what you are learning and make it stick You make a BIG project towards the end and learn Node js Express and MongoDB in the process Overall this a great intro to the world of web development for beginners and you can t go wrong with this one Get the course here Levelling Up Your CSS and JavaScriptAlthough Colt s course covers the basics of CSS and JavaScript I think spending some time to brush up what you ve just learnt and more importantly why is does what it does will go a long way in making you a better developer And the next two courses are perfect for that Advanced CSS and Sass Flexbox Grid Animations and More by Jonas SchmedtmannThis is the perfect course to level up your CSS skills and getting a better understanding of CSS and even SaaS Some highlights of the course are Understand how CSS works behind the scenes Learn about the cascade specificity inheritance value processing the visual formatting model the box model box types positioning schemes and stacking contexts etc Learn about CSS architecture Learn about Flexbox and Grid layout Introduction to Sass Lots of cool and real world projects Get the course here The Modern Javascript Bootcamp Course by Colt Steele and Stephen GriderOne of the best courses to get an in depth understanding of JavaScript by two of Udemy s best instructors ーColt Steele and Stephen Grider The first half of the course is mostly theory and mini exercises and is taught by Colt The second half will have you build a lot of cool and interesting projects that you can use in your portfolio Some of the cool things you ll build in the course Fetch and manage information from third party API s Build command line tools from scratch using Node JS Build a fully featured E Commerce application from scratch ーincluding production grade authentication Get the course here Learning React ーthe HOTTEST JavaScript FrameworkFrameworks make your life easier by doing a lot of the heavy lifting for you So once you ve learnt enough JavaScript it s time to learn React React was created by Facebook and is the most widely used JavaScript framework It s also in a lot of demand in the job market So learning React with increase your employability and increase your chances of getting a job React Tutorial and Projects Course by John SmilgaAlthough this course is by a lesser known Udemy instructor it does not disappoint The instructor makes React concepts easy to understand The course uses the latest method of declaring functional components Some of the highlights of the course are Start from the very basics of React Learn about functional components Learn the various hooks such as useState useEffect etc Make a lot of projects to practice what you ve learnt Lots of repetition to make sure what you learn sticks Get the course here Concluding ThoughtsThe courses given above are a great starting point for someone looking to dive into the world of web development As I ve already said in my first blog post the secret to becoming a successful web developer are Practice what you learn ーmake your own mini projects to solidify your knowledge Be consistent ーtake out time to practice coding everyday Focus ーpick a language or technology and stick with it Don t hop from one thing to another Avoid distractions ーswitch off your phone or keep it in airplane mode Take your time ーdon t compare your progress with others So that s it from me for today I hope you ll benefit from the courses that I ve outlined above See you guys soon	2021-05-09 08:39:04
海外TECH	DEV Community	Docker for the frontend and backend development -just for local testing not for the deployment.	https://dev.to/vishwasnarayan5/docker-for-the-frontend-and-backend-development-just-for-local-testing-not-for-the-deployment-1470	Docker for the frontend and backend development just for local testing not for the deployment We now have a frontend and backend that work flawlessly on our local computer Although you can get more out of this guide if you have finished the previous pieces it can also be useful in general The aim of this section is to ready our web applications for modern deployment We want to be able to easily run our frontend and backend on every computer and scale the framework if necessary There are several ways to do that just as there are numerous ways to do something else We ll use Docker for this series since it s been very successful in recent years This guide is broken down into four sections What is Docker Dockerizing the frontendDockerizing the backendRunning it all at once what is docker There are a great many clarifications on what docker is everywhere on the web I need to contact the main parts however I will not go into subtleties here My primary concerns were taken from this video Lets say we fabricated our backend as container document and tried it locally Presently we need to discover a spot in the cloud to run it The primary test that we experience presently is that we can not ensure that our backend runs in the cloud actually as it does locally Just if the cloud climate is equivalent to our neighborhood climate we could make such a guarantee To get the hole between our neighborhood and the cloud climate as little as conceivable we need to tell our cloud supplier what we need Nonetheless as a cloud supplier you can not have designers reveal to you how their individual cloud arrangement should resemble That is the reason cloud suppliers offer various bundles They fluctuate between giving a virtual machine and giving us a static climate to run our application in If there should arise an occurrence of an individual machine it is presently dependent upon us the designer to ensure the machine carries on as our nearby machine That is too expensive time and is additionally costly as we don t actually require a whole machine We simply need a spot to run our container record If there should arise an occurrence of furnishing us with a static climate we would now need to ensure that our neighborhood climate acts something very similar This isn t valuable all things considered Precisely here becomes docker helpful Docker gives a shared conviction and is in a real sense tantamount with genuine steel trailers A banana organization just stresses over how to get their bananas into the compartment Whenever it is shut it does t make any difference what is in there It is fundamentally dealt with like each and every other compartment and the delivery organizations realize how to function with it Docker gives a standard that is adequately adaptable yet additionally ensures the product runs in the cloud a similar way it does locally We use docker to make a docker picture of our application Simply picture we would copy it on a Compact disc That picture is assemble utilizing a dockerfile that characterizes how the docker picture ought to be constructed That picture would then be able to be utilized inside a docker compartment Docker is an amazing asset and gives more valuable highlights for example scaling Anyway this isn t as important here Docker for the frontendPlease ensure that you have docker configured before attempting to dockerize the frontend In addition in config nuxt js we must examine our base url Since if we deploy our app in the cloud as is it would still believe that our backend is accessible at localhost That is why we must remove every environment specific element Extracting environment specific variablesPlease ensure that you have docker configured before you attempt to dockerize the frontend Furthermore in our frontend we only have one environment variable which is the URL of our backend You will remember that in the nuxt config js package we used the proxy module All that remains is to include the environment variables If no value is available we set it to the default value http localhost and we must check our base url in config nuxt js Since if we deploy our app in the cloud as is it would still believe our backend is accessible at localhost As a result we must remove any environment specific variable proxy api process env PROXY API http localhost Next in our frontend folder we ll make a dockerfile called frontend dockerfile The code in our docker file is as follows FROM node alpine Create an application directoryRUN mkdir p app The app directory should act as the main application directoryWORKDIR app Copy the app package and package lock json fileCOPY frontend package json Install node packagesRUN npm install Copy or project directory locally in the current directory of our docker image app COPY frontend Build the appRUN npm run build Expose PORT on container We use a varibale here as the port is something that can differ on the environment EXPOSE PORT Set host to localhost the docker imageENV NUXT HOST Set app portENV NUXT PORT PORT Set the base urlENV PROXY API PROXY API Set the browser base urlENV PROXY LOGIN PROXY LOGIN Start the appCMD npm start The remarks and comments on each line should hopefully clarify what s going on To create the picture simply type this command into the terminal Be sure to run it from the root directory of your project docker build file frontend frontend dockerfile t playground web frontend Full stop is very importantーfile →The file to use for the build t →To identify our image we tag it →The location of the build context the app In our case the current directory referenced as Until we can dockerize or backend we must remove every environment specific attribute just as we did for our frontend In our backend we have two environment specific variables The address of our frontend and the address of our servers The programme configures all environment specific variables The assets file is located in the resources folder Each line includes a key and a value For the value we ll use an environment variable provided by docker or the default value Put in the following code spring data mongodb uri MONGODB URI mongodb localhost todo server port PORT You may be wondering why we haven t already set the URI for mogoDB That s because spring thought by default that the mongoDB will be found at that URI That will change once we put it in place That s why we re extracting it Heroku can use the server port in the following section of the tutorial FROM openjdk Create an application directoryRUN mkdir p app The app directory should act as the main application directoryWORKDIR app Copy or project directory locally in the current directory of our docker image app COPY backend build libs jar app jar Expose PORT on container We use a varibale here as the port is something that can differ on the environment EXPOSE PORT Start the appCMD java jar app jar The remarks comments on each line should hopefully clarify what s going on with the dockerfile There is a significant disparity between the frontend and backend dockerfiles The former holds the application s code If we make improvements to the backend we must first construct it with this command gradle buildTo create the picture simply type this command into the terminal Again make sure to run it from the root directory of your project docker build file backend backend dockerfile t playground web backend ーfile →The file to use for the build t →To identify our image we tag it →The location of the build context the app In our case the current directory referenced as We ll use docker compose to start it up now that we have everything we need The docker compose command instructs Docker to launch the services and which images to use as well as to set the environment variables In the root folder of your project create a new file called docker compose yml version services playground web db image mongo environment MONGO INITDB DATABASE playground web ports playground web frontend image playground web frontend latest environment PORT PROXY API http playground web backend ports playground web backend image playground web backend latest environment MONGODB URI mongodb playground web db playground web ports To run the app execute docker compose f docker compose yml upThus you will have your application up and running	2021-05-09 08:16:28
海外TECH	DEV Community	Data storage patterns, versioning and partitions	https://dev.to/javatarz/data-storage-patterns-versioning-and-partitions-2han	Data storage patterns versioning and partitionsWhen you have large volumes of data storing it logically helps users discover information and makes understanding the information easier In this post we talk about some of the techniques we use to do so in our application In this post we are going to use the terminology of AWS S buckets to store information The same techniques can be applied on other cloud non cloud providers and bare metal servers Most setups will include a high bandwidth low latency network attached storage with proximity to the processing cluster or disks on HDFS if the entire platform uses HDFS Your mileage may vary based on your team s setup and use case We are also going to talk about techniques which have allowed us to efficiently process this information using Apache Spark as our processing engine Similar techniques are available for other data processing engines Managing storage on diskWhen you have large volumes of data we have found it useful to separate data that comes in from the upstream providers if any from any insights we process and produce This allows us to segregate access different parts have different PII classifications and apply different retention policies We would separate each of these datasets so it s clear where each came from When setting up the location to store your data refer to local laws like GDPR for details on data residency requirements Provider bucketsProviders tend to make their own directories to send us data This allows them to have access over how long they want to retain data or if they need to modify information Data is rarely modified but when it is a heads up is given to re process information If this was an event driven system we would have different event types suggesting that the data from an earlier date was modified Since the volume of data is large and the batch nature of data transfer on our platform verbal written communication is preferred by our data providers which allows us to re trigger our data pipelines for the affected days Landing bucketMost data platforms either procure data or produce it internally The usual mechanism is for a provider to write data into its own bucket and give its consumers our platform access We copy the data into a landing bucket This data is a full replica of what the provider gives us without any processing Keeping data we received from the provider separate from data we process and insights we derive allows us toEnsure that we don t accidentally share raw data with others we are contractually obligated not to share source data Apply different access policies to raw data when it contains any PIIPreserve an untouched copy of the source if we ever have to re process the data providers delete data from their bucket within a month or so Core bucketThe data in the landing bucket might be in a format sub optimal for processing like CSV The data might also be dirty We take this opportunity to clean up the data and change the format to something more suitable for processing For our use case a downstream pipeline usually consumes a part of what the upstream pipeline produces Since only a subset of the data is read downstream by a single job using a file format that allows optimized columnar reads helped us boost performance and thus we use formats like ORC and parquet in our system The output after this cleanup and transformation is written to the core bucket since this data is clean input that s optimised for further processing and thus core to the functioning of the platform While landing has an exact replica of what the data provider gave us core s raw data just transforms it to a more appropriate format parquet ORC for our use case and processing applies some data cleanup strategies adds meta data and a few processed columns Derived bucketYour data platform probably has multiple models running on top of the core data that produce multiple insights We write the output for each of these into its own directory Advantages of data segregationSeparating the data makes it easier to find the data When you have terabytes or petabytes of information across your organisation with multiple teams working on this data platform it becomes easy to lose track of the information that is already available and it can be hard to find it if they are stored in different places Having some way to find information is helpful For us separating the data by whether we get it from an upstream system we produce it or we send it out to a downstream system helps teams find information easily Different rules apply to different datasets You might be obligated to delete data from raw information you have purchased under certain conditions like when they have PII Rules for retaining derived data are different if it does not contain any PII Most platforms allow archiving of data Separating the dataset makes it easier to archive different datasets we ll talk about other aspects of archiving during data partitioning Data partitioningPartitioning is a technique that allows your processing engine like Spark to read data more efficiently thus making the program more efficient The most optimal way to partition data is based on the way it is read written and or processed Since most data is written once and read multiple times optimising a dataset for reads makes sense We create a core bucket for each region we operate in based on data residency laws of the area For example since the EU data cannot leave the EU we create a derived bucket in one of the regions in the EU Under this bucket we separate the data based on the country the model that s producing the data a version of the data based on its schema and the date partition based on which the data was created Reading data from a path like derived bucket country uk model alpha version will give you a data set with columns year month and day This is useful when you are looking for data across different dates When filtering the data based on a certain month frameworks like spark allow the use of push down predicates making reads more efficient Data versioningWe change the version of the data every time there is a breaking change Our versioning strategy is similar to the one talked about in the book for Database Refactoring with a few changes for scale The book talks about many types of refactoring and the column rename is a common and interesting use case Since the data volume is comparatively low in databases megabytes to gigabytes migrating everything to the latest schema is comparatively inexpensive It is important to make sure the application is usable at all points and that there is no point at which the application is not usable Versioning on large data setsWhen the data volume is high think terabytes to petabytes running migrations like this is a very expensive process in terms of the time and resources taken Also the application downtime during the migration is large or there s copies of the dataset created which makes storage more expensive Non breaking schema changesLet s say you have a dataset that maps the real names to superhero names that you have written to model superhero identities year month day real name superhero name Tony Stark Iron Man Steve Rogers Captain America The next day if you would like to add their home location you can write the following data set to the directory day real name superhero name home location Bruce Banner Hulk Dayton Ohio Natasha Romanoff Black Widow Stalingrad Soviet Union Soon after you realize that storing the real name is too risky The data you have already published was public knowledge but moving forward you would like to stop publishing real names Thus on day you remove the real name column superhero name home location Spider Man Queens New York Ant Man San Francisco California When you read derived bucket country uk model superhero identities using spark the framework will read the first schema and use it to read the entire dataset As a result you do not see the new home location column scala gt spark read parquet model superhero identities show real name superhero name year month day Natasha Romanoff Black Widow Bruce Banner Hulk null Ant Man null Spider Man Steve Rogers Captain America Tony Stark Iron Man Asking Spark to merge the schema for you shows all columns with missing values shown as null scala gt spark read option mergeSchema true parquet model superhero identities show real name superhero name home location year month day Natasha Romanoff Black Widow Stalingrad Sovie Bruce Banner Hulk Dayton Ohio null Ant Man San Francisco Ca null Spider Man Queens New York Steve Rogers Captain America null Tony Stark Iron Man null As your model s schema evolves using features like merge schema allows you to read the available data across various partitions and then process it While we have showcased spark s abilities to merge schemas for parquet files such capabilities are also available with other file formats Breaking changes or parallel runsSometimes you evolve and improve your model It is useful to do parallel runs and compare the result to verify that it is indeed better before the business switches to use the newer version In such cases we bump up the version of the solution Let s assume job alpha v writes to the directory derived bucket country uk model alpha version When we have a newer version of the model that either has a very different schema or has to be run in parallel we bump the version of the job and the location it writes to to making the job alpha v and it s output directory derived bucket country uk model alpha version If this change was made and deployed on st of Feb and this job runs daily the latest date partition under model alpha version will be year month day From the st of Feb all data will be written to the model alpha version directory If the data in version is not sufficient for the business on st Feb we either run backfill jobs to get more data under this partition or we run both version and until version s data is ready to be used by the business The version on disk represents the version of the schema and can be matched up with the versioning of the artifact when using Semantic Versioning AdvantagesEach version partition on disk has the same schema making reads easier Downstream systems can choose when to migrate from one version to anotherA new version can be tested out without affecting the existing data pipeline chain SummaryApplications system architecture and your data always evolve Your decisions in how you store and access your data affect your system s ability to evolve Using techniques like versioning and partitioning helps your system continue to evolve with minimal overhead cost Thus we recommend integrating these techniques into your product at its inception so the team has a strong foundation to build upon Thanks to Sanjoy Anay Sathish Jayant and Priyank for their draft reviews and early feedback Thanks to Niki for using her artwork wizardry skills	2021-05-09 08:07:10
海外科学	BBC News - Science & Environment	Chinese rocket debris crashes into Indian Ocean - state media	https://www.bbc.co.uk/news/science-environment-57045058	rocket	2021-05-09 08:30:30
ニュース	@日本経済新聞 電子版	外国籍の小中生、「支援学級」頼み　貧弱な日本語教育 https://t.co/oufoD7cIRa	https://twitter.com/nikkei/statuses/1391302893806886916	日本語教育	2021-05-09 08:03:53
海外ニュース	Japan Times latest articles	Getting into wine is easier than you think	https://www.japantimes.co.jp/life/2021/05/09/food/getting-into-wine/	essentials	2021-05-09 19:00:12
ニュース	BBC News - Home	Elections 2021: Sir Keir Starmer set to reshuffle Labour's top team	https://www.bbc.co.uk/news/uk-politics-57047027	leader	2021-05-09 08:47:44
ニュース	BBC News - Home	Election results 2021: PM calls Covid recovery summit after SNP victory	https://www.bbc.co.uk/news/uk-57043758	nations	2021-05-09 08:52:25
ニュース	BBC News - Home	Chinese rocket debris crashes into Indian Ocean - state media	https://www.bbc.co.uk/news/science-environment-57045058	rocket	2021-05-09 08:30:30
ニュース	BBC News - Home	Election results 2021: Conservatives hurt Labour in its former heartlands	https://www.bbc.co.uk/news/uk-politics-57033273	labour	2021-05-09 08:27:24
ニュース	BBC News - Home	Kabul attack: Blasts near school leave more than 50 dead	https://www.bbc.co.uk/news/world-asia-57046527	kabul	2021-05-09 08:28:09
ニュース	BBC News - Home	Game-worn Jordan college jersey sells for record £1m	https://www.bbc.co.uk/sport/basketball/57046244	Game worn Jordan college jersey sells for record £mBasketball legend Michael Jordan s game worn jersey from his sophomore season at the University of North Carolina sold for a record m £m on Saturday	2021-05-09 08:04:09
ニュース	BBC News - Home	Sir John Curtice: What the 2021 election results mean for the parties	https://www.bbc.co.uk/news/uk-politics-57040175	bumper	2021-05-09 08:25:04
北海道	北海道新聞	ＮＹ観光名所で発砲　４歳女児ら３人巻き添え負傷	https://www.hokkaido-np.co.jp/article/541779/	巻き添え	2021-05-09 17:17:00
北海道	北海道新聞	中２―０広（９日）　柳が８回２安打無失点	https://www.hokkaido-np.co.jp/article/541777/	無失点	2021-05-09 17:16:00
北海道	北海道新聞	競馬、シュネルマイスターが優勝　ＮＨＫマイルカップ	https://www.hokkaido-np.co.jp/article/541776/	競馬	2021-05-09 17:16:00
北海道	北海道新聞	後志管内で１６人感染確認　新型コロナ	https://www.hokkaido-np.co.jp/article/541774/	新型コロナウイルス	2021-05-09 17:09:00
北海道	北海道新聞	７０歳までの働き方「未定」６割　主要１１０社調査	https://www.hokkaido-np.co.jp/article/541770/	共同通信社	2021-05-09 17:08:05
北海道	北海道新聞	スペイン、非常事態を解除　対コロナ、国内移動自由に	https://www.hokkaido-np.co.jp/article/541773/	新型コロナウイルス	2021-05-09 17:05:00
北海道	北海道新聞	２３歳の片岡尚之、逆転で初優勝　男子ゴルフ最終日	https://www.hokkaido-np.co.jp/article/541772/	男子ゴルフ	2021-05-09 17:05:00
北海道	北海道新聞	西村優菜が国内四大大会初制覇　サロンパスゴルフ最終日	https://www.hokkaido-np.co.jp/article/541771/	四大大会	2021-05-09 17:05:00