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これまで、型駆動設計を実践することが何を意味するのか、簡潔でシンプルな説明を見つけるのに苦労してきました。誰かに「どうやってこのアプローチを思いついたのですか?」と尋ねられることが多いのですが、満足のいく答えを出せないことがよくあります。そのアイデアが突然のひらめきで浮かんだわけではなく、正しいアプローチを空から引っ張り出す必要がない、反復的な設計プロセスがあると分かってはいるのですが、そのプロセスを他の人にうまく伝えることができていませんでした。 しかし、およそ1ヶ月前、JSON を静的型付け言語で、そして動的型付け言語にパースしたときに経験した違いについてTwitter上で振り返っていた時、ついに私が探していたものを見つけました。そして、そのスローガンはたった3つの英単語で表せます。 Parse, don’t validate (バリデーションせずパースせよ) 型駆動設計のエッセンス
TUI Interface: A full-featured terminal user interface for managing and monitoring workflow executions Validate Workflow Files: Check for syntax errors and common mistakes in GitHub Actions workflow files Execute Workflows Locally: Run workflows directly on your machine using Docker containers Emulation Mode: Optional execution without Docker by emulating the container environment locally Job Depe
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Networking & Content Delivery Use CloudFront continuous deployment to safely validate CDN changes Content delivery networks (CDN) like Amazon CloudFront are often the front door for users and devices to connect to websites or applications. A change to your CDN configuration could result in a complete outage with limited visibility into the cause of the issue. Today’s existing industry solutions fo
Vue.jsに限らずアプリケーションに入力フォームを追加した場合には必バリデーション機能を実装する必要があります。バリデーションはユーザが入力フォームから入力した値がアプリケーションの要件を満たしているかチェックを行う仕組みです。例えばネット上のサービスを利用する場合にはメールアドレスの入力を求められます。入力後にメールアドレスの形式になっているかどうかチェックを行うのがバリデーションです。 フォームバリデーションには入力値をチェックするだけではなくエラーメッセージの管理、入力したデータの管理、submit処理(サーバに)など含まれ、すべて自分で実装しようとすると非常に大変な作業になります。vee-validateなどのライブラリの力を借りることでフォーム作成の負担を下がることができフォーム以外の処理に時間をかけることができます。ライブラリを利用することで自分で実装することに比べて楽にはな
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"Parse, don’t validate" has been one of my favourite programming articles for some time. The main gist of the article is that, when writing in a type-driven fashion, your snappy slogan should be: Parse, don’t validate. The core difference between parsing and validating can be explained by looking at two very similar functions: parseInt :: String -> Maybe Int parseInt str = Text.Read.readMaybe str
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Monitoring our monitoring: how we validate our Prometheus alert rules2022-05-19 We use Prometheus as our core monitoring system. We’ve been heavy Prometheus users since 2017 when we migrated off our previous monitoring system which used a customized Nagios setup. Despite growing our infrastructure a lot, adding tons of new products and learning some hard lessons about operating Prometheus at scale
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はじめに Pythonベースで作成されたAWS Lambdaのハンドラリファクタリングをしていました。個人的にとにかく面倒に感じたのはeventとcontextのバリデーションでした。値のチェックによる行数の肥大化、及び一時変数の増加がつきものになります。 チェック用コードの関数化、及び関数のdecorator化とまで進めてみましたが、中々頭を捻ったのがdecoretorのテストです。実際のコード及びテストを元にした実装例を交えて、考慮した部分をまとめてみました。 decoretorのコード テスト対象のdecoratorコードは以下の通り。実際のコードから最低限のロジックを抜粋しています。decorator化にはpartialを使う手もありましたが、wrapsはラップされた関数のみを引数に指定すれば良い点がメリットです。 import json from argparse import
AWS DevOps & Developer Productivity Blog Proactively validate your AWS CloudFormation templates with AWS Lambda AWS CloudFormation is a service that allows you to define, manage, and provision your AWS cloud infrastructure using code. To enhance this process and ensure your infrastructure meets your organization’s standards, AWS offers CloudFormation Hooks. These Hooks are extension points that al
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App Based Security Build Pack: Docs Heroku applications are deployed on dynos, these dynos can utilize build packs to support their underlying infrastructure. There are many official build packs that can be used and this is taken into consideration when looking at the security of your app. Using official buildpacks and trusted images is an important factor in keeping your code running free from po
Ensuring you have data that makes sense is why Rails provides validations through the Active Model library, which underpins Active Record. Making sure you can email your users is one of the most important things to get right in your application, so you probably already have validation checks around your User#email attribute. Instead of... ...inventing your own regular expression, or using this one fro
Our customers have immense faith in our ability to deliver packages timely and as expected. A well planned network seamlessly scales to handle millions of package movements a day. It has monitoring mechanisms that detect failures before they even happen (such as predicting network congestion, operations breakdown), and perform proactive corrective actions. When failures do happen, it has inbuilt r
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