Developer Launches Free Moving Cost Calculator That Requires No Personal Data

·1 views

A developer has built MoveCostMatrix, a free online tool that estimates moving costs without requiring users to submit an email address or phone number. The calculator was created in response to frustration with moving platforms that gate estimates behind contact forms and then pass user data to aggressive third-party brokers. It uses postal code geocoding via the open-source zippopotam.us API and the Haversine formula to calculate distances across the US, Canada, UK, and Australia. The tool compares three moving methods side by side — including DIY truck rental — using quarterly-updated industry rates. The calculator is also embeddable, allowing other website owners to add it to their own platforms at no cost.

Read the full story at DEV Community

This is an AI-generated summary. ShortSingh links to the original source for the complete article.

Discussion (0)

How to Migrate i18n from Vite to Next.js Without Hydration Errors

Migrating a React app from Vite to Next.js requires a fundamental shift in how internationalization (i18n) is handled, moving from a client-side model to a server-first approach. In Vite SPAs, translations are managed client-side via hooks, while Next.js uses URL-based sub-path routing such as /en/about to help search engines index localized pages. Developers must use middleware to detect user locale and redirect accordingly, replacing reliance on localStorage or browser APIs during initial render. A common pitfall is the hydration mismatch error, which occurs when the server and client render different languages — this can be avoided by ensuring server-side locale detection is consistent throughout the render cycle. Libraries like next-intl are recommended for the App Router, enabling translations to be fetched inside Server Components and reducing the JavaScript bundle sent to the client.

0 comments Read more at DEV Community

ProgrammingDEV Community ·

How to Diagnose Cloudflare Blocks Before Tweaking Your Scraper

When automated scrapers fail against Cloudflare-protected sites, developers often swap proxies or User-Agents without identifying the actual cause, leading to repeated failures. Cloudflare evaluates multiple signals—IP reputation, TLS fingerprinting, JavaScript challenges, and rate limits—each requiring a different fix. Common failure types include Error 1020 access denials, 429 rate-limit responses, endless JS challenge loops, and CAPTCHA cycles, all of which can appear as generic 403 errors if the response body is not inspected. A simple response classifier can distinguish between these failure modes and prevent counterproductive retries, such as resending a bot-flagged request that only worsens the client's reputation. The article emphasizes that this guidance applies strictly to authorized automation on sites where the operator has permission to run such workflows.

0 comments Read more at DEV Community

ProgrammingDEV Community ·

How to Eliminate Code Style Debates with Prettier, ESLint, and Husky

Code style disagreements during reviews — such as tabs vs spaces or quote styles — waste team time and add no real value to a project. A practical solution is to configure three tools together from day one: Prettier for automatic formatting, ESLint for catching bad patterns, and Husky for running checks before every commit. Lint-staged is used alongside Husky to ensure only clean, properly formatted code can be committed. Once configured via their respective config files and package.json, the setup requires no ongoing maintenance and enforces consistency automatically. Teams that adopt this workflow report fewer nitpicky PR comments, faster onboarding, and code reviews that focus on logic rather than formatting.

0 comments Read more at DEV Community

ProgrammingDEV Community ·

Google ADK 2.4.0 Lets Agents Trigger Dynamic Workflows as Native Tools

Google's Agent Development Kit (ADK) version 2.4.0 introduces a streamlined way to trigger dynamic workflows directly from a coordinator agent by registering a Workflow in the agent's tools list. This update addresses a core limitation of static, graph-based workflows, which struggle to handle runtime-dependent tasks whose number, sequence, and details cannot be known at design time. The new pattern uses three components: a root agent that collects and approves tasks, a workflow that iterates over them, and a sub-agent that generates step-by-step execution plans for each task. Developers can implement this using Python with the ADK library and Gemini models hosted on Google Cloud's Vertex AI platform. The approach is designed to be adaptable beyond task-list coordination, supporting a broad range of dynamic multi-agent orchestration use cases.

0 comments Read more at DEV Community