ClickHouse HTTP API: A Complete Beginner's Guide Introduction When most people think about interacting with a database, they usually imagine connecting through a database client or application. However, ClickHouse also provides a simple and powerful HTTP API that allows you to query and manage your database using standard HTTP requests. The ClickHouse HTTP API provides a universal interface for communicating with your ClickHouse server. Since almost every programming language and automation tool supports HTTP, it becomes an excellent choice for integrations, monitoring, scripting, and lightweight applications. In this guide, you'll learn what the ClickHouse HTTP API is, why it's useful, and how to perform common database operations using simple HTTP requests. What Is the ClickHouse HTTP API? The ClickHouse HTTP API is a built-in interface that enables clients to communicate with a ClickHouse server using the HTTP protocol. Instead of connecting through the native TCP protocol, you simply send HTTP requests and receive responses in formats such as JSON, CSV, TSV, XML, or plain text. The HTTP interface is: Language agnostic Easy to integrate with web applications Firewall friendly Simple to test using tools like cURL, Postman, or a web browser Because of its simplicity, the HTTP API is widely used for automation, dashboards, data pipelines, and monitoring systems. Why Use the HTTP API? The ClickHouse HTTP API offers several advantages: No dedicated database driver is required. Works with virtually every programming language. Easy integration with REST-based applications. Supports multiple output formats. Ideal for automation and scripting. Perfect for cloud-native applications and microservices. Common Operations Using the HTTP API, you can: Execute SQL queries Insert data Create and modify tables Retrieve query results Export data in different formats Automate database operations Authentication Options ClickHouse supports multiple authentication methods when using th

Think out loud and get a polished version of your thoughts Discussion | Link

E-2 visa business plans, drafted by an AI Discussion | Link

Save on bulk groceries, household essentials, and electronics with a verified Sam's Club promo code or membership discount.

Find the best L.L.Bean promo codes and coupons for 10% off your first order, major sale discounts, free shipping on $75+, and extra savings for select groups.

Students can get a Hulu plan for $1.99 per month. Get more details on this and other great deals below.

Use these verified Chirp coupon codes and shopping tips to score up to 67% off wheels, up to 50% off refurbished products, and more.

Five months after returning to OpenAI, Barret Zoph - the company's head of enterprise AI sales - has departed, The Verge has learned. Zoph returned to OpenAI in mid-January after a stint as co-founder and CTO of Thinking Machines Lab, the competing AI company founded by former OpenAI CTO Mira Murati. Shortly after Zoph returned […]

API integration testing that remembers what breaks Discussion | Link

Hi everyone 👋 I'm a Full Stack Developer with experience in JavaScript, React.js, Next.js, Node.js, Express.js, MongoDB, and WordPress development. Over the last few years, I have worked on multiple projects ranging from company websites to full-stack web applications. In this article, I want to share my experience transitioning from the traditional MERN stack to Next.js and why it has become my preferred framework for modern web development. Why I Started with MERN Stack The MERN stack was my first choice because it allowed me to build complete applications using JavaScript. Technologies MongoDB Express.js React.js Node.js Benefits ✅ Single language across frontend and backend ✅ Huge ecosystem ✅ Fast development ✅ Easy API integration Challenges I Faced As projects became larger, I started facing issues like: SEO limitations Performance optimization Routing complexity Code organization Server-side rendering requirements This is where Next.js entered the picture. Why I Switched to Next.js Next.js provides several powerful features out of the box. Server-Side Rendering (SSR) Pages can be rendered on the server which improves SEO and initial page load performance. 2.** Static Site Generation (SSG)** Perfect for blogs, landing pages, and marketing websites. 3.** App Router** The new App Router makes routing cleaner and more scalable. Server Components Less JavaScript is sent to the browser, improving performance. Better Developer Experience Features like: File-based routing Built-in image optimization Middleware API routes make development faster and cleaner. My Current Tech Stack Frontend Next.js React.js TypeScript Tailwind CSS Backend Node.js Express.js MongoDB Tools Git & GitHub Postman Vercel Contentful CMS What I Learned The biggest lesson I learned is: Focus on solving real business problems instead of chasing every new technology. Frameworks will change, but understanding JavaScript fundamentals, APIs, databases, authentication, and system design will always be

You added .env to .gitignore . You felt responsible. But three weeks later it's still in the repo, still pushed to GitHub, still in every clone — because adding a path to .gitignore does nothing to a file git already tracks. That's not a bug. It's documented behavior: .gitignore only stops untracked files from being added. Anything already committed keeps getting tracked, ignore rule or not. So the secrets, build artifacts, and 40 MB log files that were committed before someone wrote the rule just... stay. The fix is one command — git rm --cached — but only once someone notices . And nobody notices, because git status is clean and the file looks ignored. So I built gitslip : a zero-dependency CLI that finds every tracked file your own ignore rules say should be gone, and hands you the exact fix. $ npx gitslip 2 tracked files are ignored by your rules but still committed: config/secrets.env ↳ .gitignore:7 *.env logs/app.log ↳ .gitignore:2 *.log Fix — stop tracking them (keeps your local copy): git rm --cached -- config/secrets.env git rm --cached -- logs/app.log or let gitslip do it: gitslip --apply It tells you which rule caught each file ( .gitignore:7 *.env ), so there's no guessing. And --apply runs the git rm --cached for you — it only un-tracks, it never deletes your working copy. Why not just grep? You can grep your .gitignore patterns against git ls-files . But: A raw grep '\.env' can't tell a still-tracked leftover from a file that's correctly excluded, and it has no idea about !negation rules, build/ directory rules, nested .gitignore files, .git/info/exclude , or your global core.excludesFile . Reimplementing gitignore's matching semantics to get this right is exactly the kind of subtly-wrong code you don't want guarding your secrets. gitslip doesn't reimplement anything. It asks git. How it works (the fun part) Detection is a single git incantation: git ls-files -i -c --exclude-standard -c = tracked (cached), -i = ignored, --exclude-standard = use all the

You wire up OCR for your KYC flow, point it at a national ID card, and get back a clean { name, idNumber, dateOfBirth } . Ship it. Then you onboard your second country — and it falls apart. Fields you mapped don't exist. The name comes back as garbled Latin. The date of birth says the year 2567. Here's the thing nobody tells you when you start: the hard part of national ID OCR isn't the OCR. It's that every country's ID is a different document. A model that reads text off a card is table stakes. Turning 30 countries' cards into data your system can actually use is where the work is. Let me show you the three axes of variation that will bite you, then how to architect so they don't. Axis 1: the fields are different There is no universal "national ID" schema, because the cards themselves don't agree on what to print. A Thai ID card prints the holder's religion . A German ID card prints height and eye color . A Chinese ID card prints ethnicity and the issuing authority. None of these are edge cases — they're core fields on those documents. So the instinct to define one IdCard type with a fixed set of columns is wrong from day one. Either you drop information that some countries consider essential, or you end up with a sparse table full of null s and country-specific special-casing. And it's not just which fields exist — it's what they're called and how they're split. The same "name" concept might come back as a single full-name string on one card and as separate given/family fields on another, sometimes in two scripts at once. Your data model has to treat "the field set depends on the country" as a first-class fact, not an afterthought. Axis 2: the script is different If your users are global, a lot of their names are not in the Latin alphabet — Chinese, Thai, Arabic, and more. The naive move is to transliterate everything to Latin "so it's consistent." Don't. Transliteration is lossy and ambiguous: multiple native spellings collapse to the same Latin form, diacritics