投稿時間:2021-12-27 23:31:33 RSSフィード2021-12-27 23:00 分まとめ(34件)

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IT	気になる、記になる…	トリニティ、ウェアラブルデバイス『weara』の開発中止を発表	https://taisy0.com/2021/12/27/150184.html	新型コロナウイルス	2021-12-27 13:27:02
AWS	AWS Database Blog	How Twilio modernized its billing platform on Amazon Aurora MySQL	https://aws.amazon.com/blogs/database/how-twilio-modernized-its-billing-platform-on-amazon-aurora-mysql/	How Twilio modernized its billing platform on Amazon Aurora MySQLThis is a guest post co written by Mayank Lahiri Ph D Software Architect at Twilio Inc Twilio a trailblazer in customer engagement and communication services sustains exponential growth of its billing platform on Amazon Aurora Twilio enables software engineers to programmatically make and receive phone and video calls send and receive text messages and emails and …	2021-12-27 13:04:23
python	Pythonタグが付けられた新着投稿 - Qiita	Chainerチュートリアル問6.4(ベイズの定理)の解法3選と解説	https://qiita.com/tomo-kn/items/b908f006e55da76af673	一方で解法私の解法は、数学的アプローチが完了したため計算は全くいらないが、実装するまでかなりの時間を要した。	2021-12-27 22:32:23
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	Dockerにて、一般のユーザーからrootに su した際のパスワードに関して	https://teratail.com/questions/375799?rss=all	Dockerにて、一般のユーザーからrootにsuした際のパスワードに関してDockerを最近学び始めて、Dockerのセキリュティ対策も最近色々調べていたりするのですがその際に、RUNuseraddmcoderUSERcoderWORKDIRhomecoderとDockerfileに記述すれば、コンテナのユーザーはrootユーザーではなく最小権限のユーザーcoderで動くの思うですが、その際にsuコマンドを使用してrootユーザーに切り替えできるのではないかと思い試してみたところ、パスワード入力を求められました。	2021-12-27 22:55:55
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	VBAでドロップダウンの連動をしたい	https://teratail.com/questions/375798?rss=all	VBAでドロップダウンの連動をしたいエクセルで一つ目のドロップダウンを選択したときに、その答えをもとに二つ目のドロップダウンを連動させています。	2021-12-27 22:49:05
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	プログラムの分割化について 画像の一部の色を変える	https://teratail.com/questions/375797?rss=all	プログラムの分割化について画像の一部の色を変える画像で指定した座標の範囲内を黒く表示するプログラムを分割して書こうとしたのですが、コンパイル時にエラーが出てきてしまいます。	2021-12-27 22:40:09
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	Permission deniedでpyenvでpythonがインストールできない	https://teratail.com/questions/375796?rss=all	PermissiondeniedでpyenvでpythonがインストールできないVMWareWorkStationで立ち上げたばかりのCentoOSに以下のコマンドを順に実行してPythonをインストールしたところでエラーがでました。	2021-12-27 22:34:01
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	データベースの接続に失敗する	https://teratail.com/questions/375795?rss=all	データベースの接続に失敗する突然、EclipseのDBviewerでMySQLに接続しようとすると下記のエラーが出ます。	2021-12-27 22:24:41
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	Twitterカードが表示されない	https://teratail.com/questions/375794?rss=all	Twitterカードが表示されない前提・実現したいことここに質問の内容を詳しく書いてください。	2021-12-27 22:23:24
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	ラズパイをブリッジモードでＡＰ化する際の認証方式	https://teratail.com/questions/375793?rss=all	wpawpa	2021-12-27 22:21:27
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	GoogleAdmob 登録した広告ユニットIDを使用するとリワード動画が表示されない	https://teratail.com/questions/375792?rss=all	GoogleAdmob登録した広告ユニットIDを使用するとリワード動画が表示されない実現させたいことadmobに登録した広告ユニットリワードIDを使ってリワード動画を表示させたいです。	2021-12-27 22:07:12
Ruby	Rubyタグが付けられた新着投稿 - Qiita	Minitestで「forkしたRubyのサブプロセスのIO」をテストする	https://qiita.com/kojix2/items/b1a53a35f23953e07366	かといって、spawn使ってbundleexecrubyrminimapehogefugaみたいなのを書くというのも嫌な感じがする。	2021-12-27 22:51:46
Ruby	Rubyタグが付けられた新着投稿 - Qiita	paizaラーニングの論理演算メニューのrubyの解答例	https://qiita.com/kumagaijirou/items/a6815c143b708a698aa9	paizaラーニングの論理演算メニューのrubyの解答例Paizaラーニングの論理演算メニューのrubyでの模範解答です。	2021-12-27 22:11:31
Linux	Ubuntuタグが付けられた新着投稿 - Qiita	Raspi4でROS noeticを使う	https://qiita.com/Ninagawa_Izumi/items/09cfbc3aa6d05e97cb17	STEP日本語入力もいれておきましょうsudoaptgetinstallibusmozcsudorebootおわりにubuntu専用機を持っておらず、ラズパイでubuntuとROSnoeticをつかうならデスクトップ環境もつかえるこのMATEで作るのがなにかと便利な気がします。	2021-12-27 22:36:07
AWS	AWSタグが付けられた新着投稿 - Qiita	MIRACLE LINUX 8.4をAWSでセットアップする	https://qiita.com/rkamei-github/items/4c786edb0ba2f9af048a	ステップインスタンス作成の確認起動をクリックします。	2021-12-27 22:29:35
golang	Goタグが付けられた新着投稿 - Qiita	Goroutineとselectとchannelを使って共同作業	https://qiita.com/msh/items/9eb94eb8ac89a0c36fa8		2021-12-27 22:42:16
Linux	CentOSタグが付けられた新着投稿 - Qiita	MIRACLE LINUX 8.4をAWSでセットアップする	https://qiita.com/rkamei-github/items/4c786edb0ba2f9af048a	ステップインスタンス作成の確認起動をクリックします。	2021-12-27 22:29:35
技術ブログ	Developers.IO	SecuriryGroup ルールの一覧をどうしても表計算ソフトに貼り付けたいのでマネジメントコンソールから CSV でエクスポートする	https://dev.classmethod.jp/articles/security-group-rule-export-csv/	excel	2021-12-27 13:33:09
海外TECH	Ars Technica	This may finally be the year we see some new chunky rockets take flight	https://arstechnica.com/?p=1817412	chunky	2021-12-27 13:15:19
海外TECH	DEV Community	I asked Github Copilot to code Copilot!	https://dev.to/virejdasani/i-asked-github-copilot-to-code-copilot-24b7	please	2021-12-27 13:42:52
海外TECH	DEV Community	Changelog #0007 — 🔒 Auth at the collection level	https://dev.to/pie/changelog-0007-auth-at-the-collection-level-7ha	Changelog ーAuth at the collection levelIt s Christmastime and we ve got some gifts for you All aligned with our mission to provide the best experience to anyone working with APIs of course When we announced library and collections we promised they d have superpowers in the future The future starts now with the first of its superpowers released In HTTPie for Terminal we ve implemented the most requested feature which has been up voted nearly times Check out what s new HTTPie for Web amp Desktop Auth at the collection levelIf you use collections to group requests to the same API and that API has an authorization process now you only need to set the authentication credentials once and relax from then on Set auth at the collection level and it ll auto apply to every request that belongs to it If you go to a nested request you ll verify the inherited auth and you ll be able to override it if needed Other improvementsHave you noticed that an active request tab gets highlighted in the library sidebar It helps with locating it And now it happens the same to the active collection tabs Context menus could be open all on top of another How would you know which one was important for you at the time Now when you open a context menu other ones get closed We now also specify a default User Agent HTTPie header in every request 🪲FixesDuplicating a request was not adding it to the library Now it does Sending a body with GET requests is not very common yet you might need it Now nothing stops you from doing it HTTPie for TerminalHere s a summary of this week s improvements to the development version of HTTPie for Terminal which will be part of the upcoming v release ️Timed responses One of the most requested features of all time has been the ability to see the response time natively And now the new meta section includes the total time spent sending the request receiving the response You can see it through the new m argument to print included by default with vv and there s also a new shortcut meta to only print the meta information See it in action below http print bm pie dev getIf you are using the new Pie styles through pie dark pie light you ll see this output colored according to the response time ImprovementsFriendlier error messages If you type the URL wrong or have some connection issues you ll no longer see a clunky error message If you have other cases where some of the error messages are annoying please let us know Happy testing and see you next week ‍ ️If you re not on the private beta yet you can join the waitlist here You can also follow httpie and join our Discord community ‍We re looking for new colleagues in engineering and design roles Originally published on HTTPie blog	2021-12-27 13:36:11
海外TECH	DEV Community	Create a captcha solver using 2captcha and PHP	https://dev.to/posandu/create-a-captcha-solver-using-2captcha-and-php-16ca	Create a captcha solver using captcha and PHPHello devs Today we will be creating a captcha solver using captcha So before we start let s see what is captcha and how it works What is captcha captcha is software that allows you to solve captchas It is a service that is used by many websites to solve captchas You can see their website here How does it work First we send an API request to captcha with the captcha and their workers solve it and we get the captcha solution CostThe cost of using captcha is per captcha Pretty cheap Getting startedMake sure you have a captcha account You can create one here After that you can get your API key from here And now that you have your API key you can start using it Next we need to install the captcha library Make sure you have composer installed If you don t you can install it here After that you can install the library using the following command composer require captcha captchaOnce you have the library installed you can start using it CodingNow let s create an index php file in the root directory of your project lt DOCTYPE html gt lt html lang en gt lt head gt lt meta charset UTF gt lt meta http equiv X UA Compatible content IE edge gt lt meta name viewport content width device width initial scale gt lt title gt Captcha Solver with Captcha lt title gt lt style gt container max width px margin px auto font family sans serif b padding px px background fff display block border px solid ccc color eee border radius px h font size px input type text margin bottom px display block lt style gt lt head gt lt body gt lt div class container gt lt h gt Solve Captchas with Captcha lt h gt lt p gt Let s solve captchas with lt a href gt Captcha lt a gt lt p gt lt php if isset message echo lt b gt lt p gt message lt p gt lt b gt gt lt form method POST gt lt p gt Enter text lt p gt lt input type text name a value lt isset POST a POST a gt gt lt button type submit gt Submit lt button gt lt form gt lt div gt lt body gt lt html gt This is the template of the index php file It contains the form where you can enter the captcha and submit it You can also see the message variable This variable is used to display the result of the captcha If the captcha is solved the message will be displayed If not the message will be empty or the error message Our result will be like this Now let s code the PHP code Set a time limit set time limit Include the captcha library require autoloader php Check if the form is submitted if isset POST a Declare variables captcha POST a captcha preg replace a zA Z captcha Check the length of the captcha if strlen captcha lt message The captcha is too short else Create a new instance of the captcha class Don t forget to add your API key solver new TwoCaptcha TwoCaptcha YOUR API KEY Send the captcha to the captcha com API server and get the result try result solver gt text captcha message And the answer is result gt code catch Exception e message Oops Something went wrong e gt getMessage Okay now we have our code Let s run it Here s what we get Nice Now you can solve captchas with Captcha See you soon	2021-12-27 13:29:45
海外TECH	DEV Community	Monitoring your Nestjs application using OpenTelemetry	https://dev.to/signoz/monitoring-your-nestjs-application-using-opentelemetry-4ic0	Monitoring your Nestjs application using OpenTelemetryNestjs is a Nodejs framework for building scalable server side applications with typescript It makes use of frameworks like Express and Fastify to enable rapid development It has gained wide popularity in recent times and many applications are making use of the Nestjs framework Monitoring your Nestjs application is critical for performance management But setting up monitoring for Nestjs applications can get cumbersome requiring multiple libraries and patterns That s where Opentelemetry comes in OpenTelemetry is the leading open source standard for instrumenting your code to generate telemetry data that can be a one stop solution for monitoring Nestjs applications OpenTelemetry is a set of tools APIs and SDKs used to instrument applications to create and manage telemetry data Logs metrics and traces It aims to make telemetry data logs metrics and traces a built in feature of cloud native software applications One of the biggest advantages of using OpenTelemetry is that it is vendor agnostic It can export data in multiple formats which you can send to a backend of your choice In this article we will use SigNoz as a backend SigNoz is an open source APM tool that can be used for both metrics and distributed tracing Let s get started and see how to use OpenTelemetry for a Nestjs application Running a Nestjs application with OpenTelemetryFirst you need to install SigNoz Data collected by OpenTelemetry will be sent to SigNoz for storage and visualization Installing SigNozYou can get started with SigNoz using just three commands at your terminal git clone https github com SigNoz signoz gitcd signoz deploy install shFor detailed instructions you can visit our documentation If you have installed SigNoz on your local host you can access the UI at  http localhost The application list shown in the dashboard is from a sample app called HOT R O D that comes bundled with the SigNoz installation package SigNoz Dashboard Instrumenting a sample Nestjs application with OpenTelemetryFor instrumenting a Nestjs application with OpenTelemetry you need to install the required OpenTelemetry packages first Steps involved in instrumenting a Nestjs application with OpenTelemetry are as follows Install below dependenciesnpm install save opentelemetry apinpm install save opentelemetry sdk nodenpm install save opentelemetry auto instrumentations nodenpm install save opentelemetry exporter trace otlp proto Create a tracer ts fileThe IP of SIgNoz will be localhost if you are running SigNoz on local tracing ts use strict const opentelemetry require opentelemetry sdk node const getNodeAutoInstrumentations require opentelemetry auto instrumentations node const OTLPTraceExporter require opentelemetry exporter trace otlp proto const Resource require opentelemetry resources const SemanticResourceAttributes require opentelemetry semantic conventions configure the SDK to export telemetry data to the console enable all auto instrumentations from the meta packageconst exporterOptions url http lt IP of SigNoz gt v trace const traceExporter new OTLPTraceExporter exporterOptions const sdk new opentelemetry NodeSDK resource new Resource SemanticResourceAttributes SERVICE NAME sampleNestJsApp traceExporter instrumentations getNodeAutoInstrumentations initialize the SDK and register with the OpenTelemetry API this enables the API to record telemetrysdk start then gt console log Tracing initialized catch error gt console log Error initializing tracing error gracefully shut down the SDK on process exitprocess on SIGTERM gt sdk shutdown then gt console log Tracing terminated catch error gt console log Error terminating tracing error finally gt process exit module exports sdk Import the tracer module where your app startsOn main ts file or file where your app starts import tracer using below command const tracer require tracer Start the tracerawait tracer start You can now run your Nestjs application The data captured with OpenTelemetry from your application should start showing on the SigNoz dashboard You can check out a sample Nestjs application already instrumented with OpenTelemetry here Sample Nestjs ApplicationIf you run this app you can find a SampleNestJsApp in the list of applications monitored with SigNoz Sample Nestjs application in the list of applications monitored by SigNoz Open source tool to visualize telemetry dataSigNoz makes it easy to visualize metrics and traces captured through OpenTelemetry instrumentation SigNoz comes with out of box RED metrics charts and visualization RED metrics stands for Rate of requestsError rate of requestsDuration taken by requestsMeasure things like application latency requests per sec error percentage and see your top endpoints with SigNoz You can then choose a particular timestamp where latency is high to drill down to traces around that timestamp View of traces at a particular timestampYou can use flamegraphs to exactly identify the issue causing the latency View of traces at a particular timestampYou can also build custom metrics dashboard for your infrastructure You can also build a custom metrics dashboard for your infrastructure ConclusionOpenTelemetry makes it very convenient to instrument your Nestjs application You can then use an open source APM tool like SigNoz to analyze the performance of your app As SigNoz offers a full stack observability tool you don t have to use multiple tools for your monitoring needs You can try out SigNoz by visiting its GitHub repo If you have any questions or need any help in setting things up join our slack community and ping us in help channel If you want to read more about SigNoz Golang Aplication Monitoring with OpenTelemetry and SigNozOpenTelemetry collector complete guide	2021-12-27 13:20:31
海外TECH	DEV Community	PyDP: A Python Differential Privacy Library	https://dev.to/balapriya/pydp-a-python-differential-privacy-library-34ln	PyDP A Python Differential Privacy Library Outline️⃣What does Differential Privacy try to address ️⃣Why doesn t anonymization suffice ️⃣PyDP example walkthrough What does Differential Privacy try to address Differential privacy aims at addressing the paradox of learning nothing about an individual while learning useful information about a population In essence it describes the following promise made by a data holder or curator to a data subject “You will not be affected adversely or otherwise by allowing your data to be used in any study or analysis no matter what other studies data sets or information sources are available Cynthia Dwork in The Algorithmic Foundations of Differential Privacy Differential Privacy ensures that any sequence of outputs which are responses to queries is essentially equally likely to occur independent of the presence or absence of any individual s record Consider the illustration below where the two databases Database and Database differ by only one record say your data If the results obtained from querying the database under these two different settings are almost the same or similarly distributed then they essentially are indistinguishable to an adversary Illustration of Differentially Private Database Mechanism Image Source Mathematically PrM d ∈S≤exp ϵ PrM d′ ∈SPr M d ∈S ≤exp ϵ Pr M d′ ∈S PrM d ∈S≤exp ϵ PrM d′ ∈Swhere d and d are two subsets of data that differ by a single training example M d is the output of the training algorithm for the training subset d and M d is the output of the training algorithm for the training subset d The probabilities that these outputs belong to a specific set S under both these conditions should be arbitrarily close The above equation should hold for all subsets d and d Smaller the value of Ɛ stronger the privacy guarantees Membership Inference Attack MIA attempts at determining the presence of a record in a machine learning model s training data by querying the model From the discussion above as the inclusion or exclusion of an individual s data record cannot be inferred differential privacy ensures protection against such attacks Differentially private database mechanisms can therefore make confidential data widely available for accurate data analysis Why doesn t anonymization suffice The Netflix Prize was an open competition for the best collaborative filtering algorithm for movie recommendations The dataset released was anonymized without the users or the films being identified except by numbers assigned for the contest Such anonymized movie records were published by Netflix as training data for the competition However there were several users who could be identified by linkage with the Internet Movie Database IMDb which was non anonymized and publicly available Researchers Arvind Narayanan and Vitaly Shmatikov at the University of Texas at Austin present their studies in their work Robust De anonymization of Large Datasets How to Break Anonymity of the Netflix Prize Dataset Therefore such linkage attacks can be used to match “anonymized records with non anonymized records in a different dataset Differential privacy aims at neutralizing such linkage attacks As Differential Privacy is a property of the data access mechanism and is unrelated to the presence or absence of auxiliary information available to the adversary Therefore access to the IMDb would no longer permit a linkage attack to someone whose history is in the Netflix training set than to someone not in the training set De anonymization of users in the Netflix Prize contest Image Credit Arvind Narayanan PyDP Example WalkthroughPyDP is OpenMined s Python wrapper for Google s Differential Privacy project The library provides a set of ε differentially private algorithms which can be used to produce aggregate statistics over numeric datasets containing private or potentially sensitive information Installing PyDP pip install python dp installing PyDP Necessary Importsimport pydp as dp by convention our package is to be imported as dp dp for Differential Privacy from pydp algorithms laplacian import BoundedSum BoundedMean Count Maximport pandas as pdimport statistics import numpy as npimport matplotlib pyplot as plt Fetch all the required data The dataset used here contains records and is stored across files each file containing records More specifically the dataset contains details such as the first and last names email addresses of customers and the amount they spent on purchasing goods and the state in the US they re from Let s fetch all the records read them into pandas DataFrames and take a look at the head of each of the DataFrames url df pd read csv url sep engine python print df head url df pd read csv url sep engine python print df head url df pd read csv url sep engine python df head url df pd read csv url sep engine python print df head url df pd read csv url sep engine python print df head Now that we ve fetched records from all the files let us concatenate all the DataFrames into a single large DataFrame and this constitutes our original dataset Note that our dataset has rows records and columns combined df temp df df df df df original dataset pd concat combined df temp print original dataset shape Result Creating a Parallel DatabaseLet us now create a parallel database that differs by only one record say Osbourne s record and name it redact dataset We then inspect the heads of both DataFrames to verify that Osbourne s record has been removed redact dataset original dataset copy redact dataset redact dataset print original dataset head print redact dataset head At this point let us ask ourselves the following question Is the amount of money we spend at our neighborhood store private or sensitive information Well it may not seem all that sensitive But what if the same information can be used to identify us In the example that we have let us say we remove all personal information such as name and email address Given that there s some access to the store s sales record will the sales amount in itself not suffice to infer Osbourne s identity Yes And to do that we sum up all entries in the sales amount column in our original dataset and the redact dataset The difference between these two sums exactly gives us the amount that Osbourne spent and is verified as shown in the code snippet below This is a simple example where membership inference was successful even after removal of personally identifiable information sum original dataset round sum original dataset sales amount to list sum redact dataset round sum redact dataset sales amount to list sales amount Osbourne round sum original dataset sum redact dataset assert sales amount Osbourne original dataset iloc Differentially Private SumNow we illustrate how differentially private sum in place of simple sum can help in rendering membership inference attacks unsuccessful For the example above let s assume that the customers should spend a minimum of at the store and no more than for a particular purchase We then go ahead and compute differentially private sum on both original and the parallel dataset that differed by one record as shown in the code snippets below dp sum original dataset BoundedSum epsilon lower bound upper bound dtype float dp sum og dp sum original dataset quick result original dataset sales amount to list dp sum og round dp sum og print dp sum og Output dp sum og dp redact dataset BoundedSum epsilon lower bound upper bound dtype float dp redact dataset add entries redact dataset sales amount to list dp sum redact round dp redact dataset result print dp sum redact Output dp sum redact Let s proceed to summarize a few observations Now that we ve calculated the differentially private sum on the original and the second dataset it s straightforward to verify that that the differentially private sums are not equal to sums under the non differentially private setting Also the difference is no longer equal to the amount that Osbourne spent indicating that membership attacks would now be unsuccessful regardless of access to any other customer records Interestingly the differentially private sum values are still comparable and are not very different We ve therefore succeeded in ensuring differential privacy in our simple example print f Sum of sales value in the orignal dataset sum original dataset print f Sum of sales value in the orignal dataset with DP dp sum og assert dp sum og sum original dataset OutputSum of sales value in the orignal dataset Sum of sales value in the orignal dataset with DP print f Sum of sales value in the second dataset sum redact dataset print f Sum of sales value in the second dataset with DP dp sum redact assert dp sum redact sum redact dataset OutputSum of sales value in the second dataset Sum of sales value in the second dataset with DP print f Difference in Sum with DP round dp sum og dp sum redact print f Actual Difference in Sum sales amount Osbourne assert round dp sum og dp sum redact sales amount Osbourne OutputDifference in sum using DP Actual Value Hope this introductory post helped in understanding the intuition behind differential privacy and protection against membership inference attacks We shall look at a few more examples in subsequent blog posts References The Algorithmic Foundations of Differential Privacy by Cynthia Dwork PyDP Tutorial by Chinmay Shah at OpenMined Privacy Conference	2021-12-27 13:12:00
Apple	AppleInsider - Frontpage News	Back to the Mac: how the 14-inch MacBook Pro won over a longtime iPad Pro user	https://appleinsider.com/articles/21/12/23/back-to-the-mac-how-the-14-inch-macbook-pro-won-over-a-longtime-ipad-pro-user?utm_medium=rss	Back to the Mac how the inch MacBook Pro won over a longtime iPad Pro userFor years the iPad Pro has been a primary work machine for one AppleInsider employee but the inch MacBook Pro combined with macOS Monterey has reinvigorated his interest in the Mac The inch MacBook Pro and iPad Pro work setupApple s transition to custom Apple Silicon in its Mac lineup has led to some surprising changes Several aspects previously reserved for iOS and iPadOS are now front and center in macOS Read more	2021-12-27 13:58:33
海外科学	NYT > Science	Why These Mexican Fish Do the Wave	https://www.nytimes.com/2021/12/22/science/fish-wave-mexico.html	earth	2021-12-27 13:49:51
金融	RSS FILE - 日本証券業協会	証券業報　２０２１年 １２月	https://www.jsda.or.jp/about/gaiyou/gyouhou/21/2112gyouhou.html	証券	2021-12-27 13:51:00
ニュース	BBC News - Home	Covid: PM gets Covid briefing as UK nations tighten rules	https://www.bbc.co.uk/news/uk-59798814?at_medium=RSS&at_campaign=KARANGA	england	2021-12-27 13:53:46
ニュース	BBC News - Home	Glasgow v Edinburgh off because of Covid outbreak	https://www.bbc.co.uk/sport/rugby-union/59803706?at_medium=RSS&at_campaign=KARANGA	squad	2021-12-27 13:39:35
LifeHuck	ライフハッカー［日本版］	ミニマルに見えて容量8L！ サイズ拡張するスリングバッグ「SEKKEI」	https://www.lifehacker.jp/2021/12/248547-machi-yasekkei-start.html	sekkei	2021-12-27 23:00:00
LifeHuck	ライフハッカー［日本版］	世界最小サイズのミニマル財布「COM-ONO」は小銭・紙幣・カード全部入る！｜これ買ってよかった2021	https://www.lifehacker.jp/2021/12/248009best-buy-2021-com-ono-wallet.html	comono	2021-12-27 22:05:00
北海道	北海道新聞	道内厳寒大雪、ＪＲ１５２本運休　空路２４便欠航　２９日も各地で雪	https://www.hokkaido-np.co.jp/article/628158/	冷え込み	2021-12-27 22:19:11
北海道	北海道新聞	無料ＰＣＲ・抗原検査、道内薬局で始まる　未接種者対象　最大７００カ所	https://www.hokkaido-np.co.jp/article/628159/	新型コロナウイルス	2021-12-27 22:13:00
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