投稿時間:2023-07-14 12:29:59 RSSフィード2023-07-14 12:00 分まとめ(33件)

カテゴリー等	サイト名等	記事タイトル・トレンドワード等	リンクURL	頻出ワード・要約等/検索ボリューム	登録日
IT	気になる、記になる…	Anker、MagSafe対応iPhone専用モバイルバッテリー｢Anker 334 MagGo Battery (PowerCore 10000)｣を発売 ｰ 初回限定セールも開催中	https://taisy0.com/2023/07/14/174124.html	anker	2023-07-14 02:25:04
IT	気になる、記になる…	人気Apple Watch用バンド｢NOMAD Sports Band｣に限定カラー｢Atlantic Blue｣が登場	https://taisy0.com/2023/07/14/174120.html	applewatch	2023-07-14 02:13:46
IT	ITmedia 総合記事一覧	[ITmedia News] “政府認定クラウドサービス”登録の“つまずきポイント”　実務から見る注意点	https://www.itmedia.co.jp/news/articles/2307/13/news023.html	itmedia	2023-07-14 11:45:00
IT	ITmedia 総合記事一覧	[ITmedia Mobile] PayPayフリマが「Yahoo!フリマ」に名称変更　ヤフオク!は「Yahoo!オークション」に回帰	https://www.itmedia.co.jp/mobile/articles/2307/14/news120.html	itmediamobilepaypay	2023-07-14 11:40:00
IT	ITmedia 総合記事一覧	[ITmedia News] PS5の「Access コントローラー」は1万2980円、12月発売へ　障害者などの利用想定	https://www.itmedia.co.jp/news/articles/2307/14/news117.html	access	2023-07-14 11:16:00
IT	ITmedia 総合記事一覧	[ITmedia News] OpenAIとAP通信がライセンス契約　LLMトレーニングに過去記事取り込み	https://www.itmedia.co.jp/news/articles/2307/14/news116.html	itmedianewsopenai	2023-07-14 11:14:00
IT	ITmedia 総合記事一覧	[ITmedia News] 映画「君たちはどう生きるか」公開でハッシュタグ「米津玄師」話題に　ジブリ公式は「カヘッカヘッ」	https://www.itmedia.co.jp/news/articles/2307/14/news113.html	itmedia	2023-07-14 11:01:00
python	Pythonタグが付けられた新着投稿 - Qiita	PythonとAIの密接な関係性！これから必須のプログラミングスキルを徹底解説	https://qiita.com/maricablog/items/13ee30b5eb9c9e25a157	人工知能	2023-07-14 11:08:26
js	JavaScriptタグが付けられた新着投稿 - Qiita	Typescript	https://qiita.com/yukihara1126/items/87d9c8c6b0754b25f711	numberstringbooleansymbol	2023-07-14 11:47:19
js	JavaScriptタグが付けられた新着投稿 - Qiita	Javescriptを独学で極める方法！	https://qiita.com/maricablog/items/73d1929b9dd46715d934	javescript	2023-07-14 11:03:13
Docker	dockerタグが付けられた新着投稿 - Qiita	Dockerってなんで必要なんだっけ？	https://qiita.com/TakanoriVega/items/7875426708bf9abe2175	docker	2023-07-14 11:52:43
技術ブログ	Developers.IO	[マルチアカウント]SESのVPCエンドポイントを集約させて、メール送信してみた	https://dev.classmethod.jp/articles/ses-smtpendpoint-aggregation-in-multiaccount/	集約	2023-07-14 02:38:39
技術ブログ	Developers.IO	「.NET + Lambda のパフォーマンスを最適化する方法」というテーマのビデオセッションで話しました #devio2023	https://dev.classmethod.jp/articles/devio2023-video-57-dotnet/	developersio	2023-07-14 02:05:42
技術ブログ	Developers.IO	【8/9（水）東京】クラスメソッドの会社説明会を開催します（リモート参加OK）	https://dev.classmethod.jp/news/jobfair-230809/	会社説明会	2023-07-14 02:04:25
海外TECH	DEV Community	Ingesting Data into OpenSearch using Apache Kafka and Go	https://dev.to/abhirockzz/ingesting-data-into-opensearch-using-apache-kafka-and-go-4j7f	Ingesting Data into OpenSearch using Apache Kafka and GoThere are times you might need to write a custom integration layer to fulfill specific requirements in your data pipeline Learn how to do this with Kafka and OpenSearch using GoScalable data ingestion is a key aspect for a large scale distributed search and analytics engine like OpenSearch One of the ways to build a real time data ingestion pipeline is to use Apache Kafka It s an open source event streaming platform used to handle high data volume and velocity and integrates with a variety of sources including relational and NoSQL databases For example one of the canonical use cases is real time synchronization of data between heterogeneous systems source components to ensure that OpenSearch indexes are fresh and can be used for analytics or consumed downstream applications via dashboards and visualizations This blog post will cover how to create a data pipeline wherein data written into Apache Kafka is ingested into OpenSearch We will be using Amazon OpenSearch Serverless Amazon Managed Streaming for Apache Kafka Amazon MSK Serverless Kafka Connect is a great fit for such requirements It provides sink connectors for OpenSearch as well as ElasticSearch which can be used if you opt for the ElasticSearch OSS engine with Amazon OpenSearch Sometimes though there are specific requirements or reasons which may warrant the use of a custom solution For example you might be using a data source which is not supported by Kafka Connect rare but could happen and don t want to write one from scratch Or this could be a one off integration and you re wondering if it s worth the effort to set up and configure Kafka Connect Perhaps there are other concerns like licensing etc Thankfully Kafka and OpenSearch provide client libraries for a variety of programming languages which make it possible to write your own integration layer This is exactly what s covered in this blog We will make use of a custom Go application to ingest data using Go clients for Kafka and OpenSearch You will learn Overview of how to set up the required AWS services OpenSearch Serverless MSK Serverless AWS Cloud along with IAM policies and security configurations High level walk through of the application Get the data ingestion pipeline up and running How to query data in OpenSearch Before we get into the nitty gritty here is a quick overview of OpenSearch Serverless and Amazon MSK Serverless Introduction to Amazon OpenSearch Serverless and Amazon MSK ServerlessOpenSearch is an open source search and analytics engine used for log analytics real time monitoring and clickstream analysis Amazon OpenSearch Service is a managed service that simplifies the deployment and scaling of OpenSearch clusters in AWS Amazon OpenSearch Service supports OpenSearch and legacy Elasticsearch OSS up to the final open source version of the software When you create a cluster you have the option of which search engine to use You can create an OpenSearch Service domain synonymous with an OpenSearch cluster to represent a cluster with each Amazon EC instance acting as a node However OpenSearch Serverless eliminates operational complexities by providing on demand serverless configuration for OpenSearch service It uses collections of indexes to support specific workloads and unlike traditional clusters it separates indexing and search components with Amazon S as the primary storage for indexes This architecture enables independent scaling of search and indexing functions You can refer to the details in Comparing OpenSearch Service and OpenSearch Serverless Amazon MSK Managed Streaming for Apache Kafka is a fully managed service for processing streaming data with Apache Kafka It handles cluster management operations like creation updates and deletions You can use standard Apache Kafka data operations for producing and consuming data without modifying your applications It supports open source Kafka versions ensuring compatibility with existing tools plugins and applications MSK Serverless is a cluster type within Amazon MSK that eliminates the need for manual management and scaling of cluster capacity It automatically provisions and scales resources based on demand taking care of topic partition management With a pay as you go pricing model you only pay for the actual usage MSK Serverless is ideal for applications requiring flexible and automated scaling of streaming capacity Let s start by discussing the high level application architecture before moving on to the architectural considerations Application overview and key architectural considerationsHere is a simplified version of the application architecture that outlines the components and how they interact with each other The application consists of producer and consumer components which are Go applications deployed to an EC instance As the name suggests the producer sends data to the MSK Serverless cluster The consumer application receives data movie information from the MSK Serverless topic and uses the OpenSearch Go client to index data in the movies collection Focus on simplicityIt s worth noting that the blog post has been optimized for simplicity and ease of understanding hence the solution is not tuned for running production workloads The following are some of the simplifications that have been made The producer and consumer applications run on the same compute platform an EC instance There is a single consumer application instance processing data from the MSK topic However you can try to run multiple instances of the consumer application and see how the data is distributed across the instances Instead of using the Kafka CLI to produce data a custom producer application was written in Go along with a REST endpoint to send data This demonstrates how to write a Kafka producer application in Go and mimics the Kafka CLI The volume of data used is small OpenSearch Serverless collection has a Public access type For a production workload here are some of the things you should consider Choose an appropriate compute platform for your consumer application based on data volume and scalability requirements more on this below Choose VPC access type for your OpenSearch Serverless collectionConsider using Amazon OpenSearch Ingestion to create your data pipelines If you still need to deploy your custom application to build a data pipeline from MSK to OpenSearch here are the range of compute options you can choose from Containers You can package your consumer application as a Docker container Dockerfile is available in the GitHub repository and deploy it to Amazon EKS or Amazon ECS If you deploy the application to Amazon EKS you can also consider using KEDA to auto scale your consumer application based on the number of messages in the MSK topic Serverless It s also possible to use MSK as an event source for AWS Lambda functions You can write your consumer application as a Lambda function and configure it to be triggered by MSK events or alternatively run it on AWS Fargate Since the producer application is a REST API you can deploy it to AWS App Runner Finally you can leverage Amazon EC Auto Scaling groups to auto scale the EC fleet for you consumer application There is enough material out there that talks about how to use Java based Kafka applications to connect with MSK Serverless using IAM Let s take a short detour into understanding how this works with Go How do Go client applications authenticate with MSK Serverless using IAM MSK Serverless requires IAM access control to handle both authentication and authorization for your MSK cluster This means that your MSK clients applications producer and consumer in this case have to use IAM to authenticate to MSK based on which they will be allowed or denied specific Apache Kafka actions The good thing is that the franz go Kafka client library supports IAM authentication Here are snippets from the consumer application that show how it works in practice func init cfg err config LoadDefaultConfig context Background config WithRegion us east config WithCredentialsProvider ecrolecreds New creds err cfg Credentials Retrieve context Background func initializeKafkaClient opts kgo Opt kgo SeedBrokers strings Split mskBroker kgo SASL sasl aws ManagedStreamingIAM func ctx context Context sasl aws Auth error return sasl aws Auth AccessKey creds AccessKeyID SecretKey creds SecretAccessKey SessionToken creds SessionToken UserAgent msk ec consumer app nil First the application uses the ecrolecreds New credentials provider to retrieve the temporary IAM credentials from the EC instance metadata service The EC Instance role should have appropriate IAM role with permissions to execute required operations on MSK cluster components more on this in the subsequent sections These credentials are then used to initialize the Kafka client with the AWS MSK IAM SASL authentication implementation in the sasl aws package Note Since there are multiple Go clients for Kafka including Sarama please make sure to consult their client documentation to confirm whether they support IAM authentication Ok with that background let s set up the services required to run our ingestion pipeline Infrastructure setupThis section will help you set up the following components Required IAM rolesMSK Serverless ClusterOpenSearch Serverless collectionAWS Cloud EC environment to run your application MSK Serverless ClusterYou can follow this documentation to setup a MSK Serverless cluster using the AWS Console Once you do that note down the following cluster information VPC Subnet Security group Properties tab and the cluster Endpoint click View client information Application IAM roleThere are different IAM roles you will need for this tutorial Start by creating an IAM role to execute the subsequent steps and use OpenSearch Serverless in general with permissions as per Step Configure permissions in the Amazon OpenSearch documentation Create another IAM role for the clients applications which will interact with MSK Serverless cluster and use OpenSearch Go client to index data in the OpenSearch Serverless collection Create an inline IAM policy as below make sure to substitute the required values Version Statement Effect Allow Action kafka cluster Resource lt ARN of the MSK Serverless cluster gt arn aws kafka us east lt AWS ACCOUNT ID gt topic lt MSK CLUSTER NAME gt arn aws kafka us east AWS ACCOUNT ID group lt MSK CLUSTER NAME gt Effect Allow Action aoss APIAccessAll Resource Use the following Trust policy Version Statement Effect Allow Principal Service ec amazonaws com Action sts AssumeRole Finally another IAM role to which you will attach OpenSearch Serverless Data access policies more on this in the next step OpenSearch Serverless collectionCreate an OpenSearch Serverless collection using the documentation While following point in Step Create a collection make sure to configure two Data policies i e one each of the IAM roles created in step and in the previous section Note the for the purposes of this tutorial we chose Public access type It s recommended to select VPC for production workloads AWS Cloud EC environmentUse this documentation to create an AWS Cloud EC development environment make sure to use the same VPC as the MSK Serverless cluster Once complete you need to do the following Open the Cloud environment under EC Instance click Manage EC instance In the EC instance navigate to Security and make a note of the attached security group Open the Security Group associated with the MSK Serverless cluster and add an inbound rule to allow the Cloud EC instance to connect to it Choose the security group of the Cloud EC instance as the source as the Port and TCP protocol You are now ready to run the application Select the Cloud environment and choose Open in Cloud to launch the IDE Open a terminal window clone the GitHub repository and change directory to the folder git clone cd opensearch using kafka golangStart the producer application cd msk producerexport MSK BROKER lt enter MSK Serverless cluster endpoint gt export MSK TOPIC moviesgo run main goYou should see the following logs in the terminal MSK BROKER lt MSK Serverless cluster endpoint gt MSK TOPIC moviesstarting producer apphttp server readyTo send data to the MSK Serverless cluster use a bash script that will invoke the HTTP endpoint exposed by the application you just started and submit movie data from movies txt file in JSON format using curl send data shIn the producer application terminal logs you should see output similar to this producing data to topicpayload directors Joseph Gordon Levitt release date T Z rating genres Comedy Drama image url V SX jpg plot A New Jersey guy dedicated to his family friends and church develops unrealistic expectations from watching porn and works to find happiness and intimacy with his potential true love title Don Jon rank running time secs actors Joseph Gordon Levitt Scarlett Johansson Julianne Moore year record produced successfully to offset in partition of topic moviesproducing data to topicpayload directors Ron Howard release date T Z rating genres Action Biography Drama Sport image url V SX jpg plot A re creation of the merciless s rivalry between Formula One rivals James Hunt and Niki Lauda title Rush rank running time secs actors Daniel Br uc ubchl Chris Hemsworth Olivia Wilde year record produced successfully to offset in partition of topic movies For the purposes of this tutorial and to keep it simple and easy to follow the amount of data has been purposely restricted to records and the script intentionally sleeps for second after sending each record to the producer You should be able to follow along comfortably While the producer application is busy sending data to the movies topic you can start the consumer application start processing data from the MSK Serverless cluster and index it in the OpenSearch Serverless collection cd msk consumerexport MSK BROKER lt enter MSK Serverless cluster endpoint gt export MSK TOPIC moviesexport OPENSEARCH INDEX NAME movies indexexport OPENSEARCH ENDPOINT URL lt enter OpenSearch Serverless endpoint gt go run main goYou should see the following output in the terminal which will indicate that it has indeed started receiving data from the MSK Serverless cluster and indexing it in the OpenSearch Serverless collection using default value for AWS REGION us east MSK BROKER lt MSK Serverless cluster endpoint gt MSK TOPIC moviesOPENSEARCH INDEX NAME movies indexOPENSEARCH ENDPOINT URL lt OpenSearch Serverless endpoint gt using credentials from ECRoleProviderkafka consumer goroutine started waiting for recordsparitions ASSIGNED for topic movies got record from partition key val directors Joseph Gordon Levitt release date T Z rating genres Comedy Drama image url V SX jpg plot A New Jersey guy dedicated to his family friends and church develops unrealistic expectations from watching porn and works to find happiness and intimacy with his potential true love title Don Jon rank running time secs actors Joseph Gordon Levitt Scarlett Johansson Julianne Moore year movie data indexedcommitting offsetsgot record from partition key val directors Ron Howard release date T Z rating genres Action Biography Drama Sport image url V SX jpg plot A re creation of the merciless s rivalry between Formula One rivals James Hunt and Niki Lauda title Rush rank running time secs actors Daniel Br uc ubchl Chris Hemsworth Olivia Wilde year movie data indexedcommitting offsets After the process is complete you should have movies indexed in the OpenSearch Serverless collection You don t have to wait for it to finish though Once there are a few hundred records you can go ahead and navigate to Dev Tools in the OpenSearch dashboard to execute the below queries Query movies data in OpenSearch Run a simple queryLet s start with a simple query to list all the documents in the index without any parameters or filters GET movies index search Fetch data only for specific fieldsBy default a search request retrieves the entire JSON object that was provided when indexing the document Use the source option to retrieve the source from selected fields For example to retrieve only the title plot and genres fields run the following query GET movies index search source includes title plot genres Fetch data to match the exact search term a Term QueryYou can use a Term query to achieve this For example to search for movies with the term christmas in the title field run the following query GET movies index search query term title value christmas Combine selective field selection with term queryYou can use this query to only retrieve certain fields but are interested in a particular term GET movies index search source includes title actors query query string default field title query harry AggregationUse aggregations to compute summary values based on groupings of the values in a particular field For example you can summarize fields like ratings genre and year to search results based on the values of those fields With aggregations we can answer questions like How many movies are in each genre “GET movies index search size aggs genres terms field genres keyword Clean upAfter you are done with the demo make sure to delete all the services to avoid incurring any additional charges You can follow the steps in the respective documentation to delete the services Delete OpenSearch Serverless collectionDelete MSK Serverless clusterDelete Cloud environmentAlso delete IAM roles and policies ConclusionTo recap you deployed a pipeline to ingest data into OpenSearch Serverless using Kafka and then queried it in different ways Along the way you also learned about the architectural considerations and compute options to keep in mind for production workloads as well as using Go based Kafka applications with MSK IAM authentication I would also suggest reading the article Building a CRUD Application in Go for Amazon OpenSearch particularly if you re looking for a tutorial centered on carrying out OpenSearch operations via the Go SDK This was pretty lengthy I think Thank you reading it till the end If you enjoyed this tutorial found any issues or have feedback for us please send it our way	2023-07-14 02:10:58
海外TECH	DEV Community	A Comprehensive Beginner's Guide to NPM: Simplifying Package Management	https://dev.to/abhixsh/a-comprehensive-beginners-guide-to-npm-simplifying-package-management-57l5	A Comprehensive Beginner x s Guide to NPM Simplifying Package ManagementIn the vast landscape of web development efficiently managing project dependencies is crucial for seamless development workflows Enter NPM Node Package Manager a robust package manager designed for JavaScript projects primarily used in conjunction with Node js This fully beginner friendly guide will take you through the fundamentals of NPM providing you with a solid foundation for simplifying package management and streamlining your development process NPM is a command line tool that facilitates the installation management and sharing of reusable JavaScript code modules known as packages within your projects As the default package manager for Node js NPM comes bundled with the Node js installation making it readily available Installing NPM Before diving into NPM you ll need to have Node js installed on your system Simply head over to the official Node js website nodejs org and download the appropriate version for your operating system Once Node js is successfully installed NPM will be at your fingertips through your command prompt or terminal And also npm includes a CLI Command Line Client that can be used to download and install the software Windows ExampleC gt npm install lt package gt Mac OS Example gt npm install lt package gt Here are some beginner level NPM commands npm initThis command initializes a new NPM package within your project directory It creates a package json file where you can define project metadata dependencies and other configurations npm install lt package name gt This command installs a specific NPM package and its dependencies into your project Replace lt package name gt with the name of the package you want to install The package and its dependencies will be downloaded and saved in the node modules folder npm installRunning npm install without specifying a package name will install all the dependencies listed in the package json file It ensures that all required packages for your project are installed and up to date npm uninstall lt package name gt This command removes a specific NPM package from your project Replace lt package name gt with the name of the package you want to uninstall The package and its associated files will be removed from the node modules folder npm updateRunning npm update updates all the packages listed in the package json file to their latest versions It checks for new versions of packages and updates them accordingly It s important to test your code after running this command to ensure compatibility with the updated packages npm outdatedThe npm outdated command displays a list of installed packages that have newer versions available It helps you identify which packages are outdated and need to be updated to their latest versions npm run lt script name gt NPM allows you to define custom scripts in the scripts section of your package json file The npm run lt script name gt command executes a specific script defined in the package json file Replace lt script name gt with the name of the script you want to run npm publishIf you have developed a package and want to make it available to others the npm publish command helps you publish your package to the NPM registry It allows other developers to install and use your package in their projects You can See a simple NPM Basics Cheat Sheet through this linkFree Courses NPM Full Course For Beginners Learn NPM fundamentals and basicsNode js Essential Training Web Servers Tests and Deployment There are some additional points Managing Dependencies NPM simplifies dependency management by allowing you to specify desired package versions and ranges directly within the package json file With this approach NPM ensures that all required packages are installed correctly thereby avoiding version conflicts and ensuring the stability of your project To update or remove packages NPM provides dedicated commands like npm update or npm uninstall further streamlining the management process Unleashing the Power of NPM Scripts NPM Scripts are a powerful feature that empowers developers to define custom scripts within the package json file These scripts can be easily executed via the command line using the npm run syntax By harnessing NPM Scripts you can automate a wide range of tasks such as running tests building your project or deploying to a server greatly enhancing your development workflow Publishing Your Packages NPM goes beyond consuming packages and enables developers to publish their packages to the NPM registry thereby contributing to the vibrant JavaScript ecosystem By creating an account on the NPM website and following a few straightforward steps you can share your code with the community receive feedback and make your mark within the development community Introducing the Package json File At the core of every NPM project lies the essential package json file This file acts as the project s manifesto housing crucial metadata such as the project name version dependencies and other essential configurations You can manually create a package json file or generate one effortlessly by executing the npm init command within your project directory NPM serves as a robust and indispensable tool for simplifying package management within JavaScript projects By familiarizing yourself with NPM s fundamentals you gain the ability to effortlessly install manage and share packages ultimately improving your development workflow Armed with this knowledge you can harness the benefits of NPM to create efficient and maintainable projects all while enhancing your web development skill set Additional resourcesNPM website NPM documentation Node js website JavaScript tutorial Okay that s it for this article Also if you have any questions about this or anything else please feel free to let me know in a comment below or on Instagram Facebook or Twitter Thank you for reading this article and see you soon in the next one ️	2023-07-14 02:00:46
金融	ニッセイ基礎研究所	数字の「15」に関わる各種の話題－「15」という数字は、「完全・完璧」なものを意味する考え方があるってこと知っていますか－	https://www.nli-research.co.jp/topics_detail1/id=75453?site=nli	これに対して、ラグビー・リーグの人数については、人や人とする提案があり、人を希望するクラブもあったりしたが、最終的には年に人とすることが決定されている。	2023-07-14 11:33:02
海外ニュース	Japan Times latest articles	Ons Jabeur and Marketa Vondrousova set up clash for Wimbledon title	https://www.japantimes.co.jp/sports/2023/07/14/tennis/jabeur-vondrousova-wimbledon-semifinal/	aryna	2023-07-14 11:28:15
海外ニュース	Japan Times latest articles	Saki Kumagai eager to chart own path as Nadeshiko Japan captain at Women’s World Cup	https://www.japantimes.co.jp/sports/2023/07/14/soccer/womens-world-cup/kumagai-follow-example-past-captain/	Saki Kumagai eager to chart own path as Nadeshiko Japan captain at Women s World CupThe year old will be the only remaining member of the Japan s World Cup winning squad at this year s tournament	2023-07-14 11:01:09
ニュース	BBC News - Home	SAG strike: Hollywood actors announce historic walkout	https://www.bbc.co.uk/news/entertainment-arts-66196357?at_medium=RSS&at_campaign=KARANGA	productions	2023-07-14 02:05:40
ニュース	BBC News - Home	Watch: Man catches Florida’s longest-ever Burmese python	https://www.bbc.co.uk/news/world-us-canada-66197675?at_medium=RSS&at_campaign=KARANGA	burmese	2023-07-14 02:43:08
ニュース	BBC News - Home	RBA: Australia names first woman to lead its central bank	https://www.bbc.co.uk/news/business-66197443?at_medium=RSS&at_campaign=KARANGA	australia	2023-07-14 02:22:18
ビジネス	ダイヤモンド・オンライン - 新着記事	【マンガ】「おしっこを出さないとどうなるの？」子どもに聞かれたらどう答える？ - ニュース3面鏡	https://diamond.jp/articles/-/325482	身近	2023-07-14 12:00:00
ビジネス	ダイヤモンド・オンライン - 新着記事	「オタクは“結婚”に向いている」と、婚活コンサルタントが断言する理由 - ニュースな本	https://diamond.jp/articles/-/321127	「オタクは“結婚に向いている」と、婚活コンサルタントが断言する理由ニュースな本今や日本国民の人に人が、何かしらの「オタク」といわれる時代。	2023-07-14 11:30:00
ビジネス	ダイヤモンド・オンライン - 新着記事	法政がMARCHで一番入りやすいって本当？ナメられがちな風潮に塾長が「合格点とってからディスって」 - ネット発！教育ニュース最前線	https://diamond.jp/articles/-/326135	法政がMARCHで一番入りやすいって本当ナメられがちな風潮に塾長が「合格点とってからディスって」ネット発教育ニュース最前線MARCHの中で一番入りやすいのは法政大ー中央大と法政大を比較することで見えてきた、法政大が「入りやすい」と思われる理由とは。	2023-07-14 11:20:00
ビジネス	ダイヤモンド・オンライン - 新着記事	米インフレ鈍化、軟着陸の可能性高まる - WSJ発	https://diamond.jp/articles/-/326176	鈍化	2023-07-14 11:12:00
ビジネス	ダイヤモンド・オンライン - 新着記事	早稲田と慶応、就職の注目企業1位は同じ会社！塾長が「人気ランキングには気をつけて」と語る理由 - ネット発！教育ニュース最前線	https://diamond.jp/articles/-/326136	castdice	2023-07-14 11:10:00
ビジネス	東洋経済オンライン	ビッグモーターと損保ジャパン､不正請求の蜜月 水増し請求の温床｢営業ノルマ｣を黙認した罪 | 金融業界 | 東洋経済オンライン	https://toyokeizai.net/articles/-/686623?utm_source=rss&utm_medium=http&utm_campaign=link_back	損保ジャパン	2023-07-14 11:30:00
ビジネス	東洋経済オンライン	世界的人気｢BTS｣と｢ユング心理学｣の意外な接点 自分たちは｢何者であるか｣を問い続けてきた | リーダーシップ・教養・資格・スキル | 東洋経済オンライン	https://toyokeizai.net/articles/-/685887?utm_source=rss&utm_medium=http&utm_campaign=link_back	防弾少年団	2023-07-14 11:30:00
ニュース	Newsweek	台湾有事のタイミングを計る「一島三峡」とは？...中国侵攻に日本はどう備えるか	https://www.newsweekjapan.jp/stories/world/2023/07/post-102176.php	中国軍の目が台湾東部に注がれているということは、それだけ中国の台湾侵攻作戦の準備が成熟してきたことを示している。	2023-07-14 11:30:00
IT	週刊アスキー	A6文庫本サイズの水筒「memobottle」を衝動買い	https://weekly.ascii.jp/elem/000/004/145/4145095/	衝動買い	2023-07-14 11:30:00
IT	週刊アスキー	【本日公開】『君たちはどう生きるか』を君たちはどのフォーマットで観るか	https://weekly.ascii.jp/elem/000/004/145/4145265/	君たちはどう生きるか	2023-07-14 11:30:00
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