Just is the best general command runner for most new projects in 2026. It has Make-like syntax without the tab headaches. It works across Linux, macOS, and Windows. It stays out of your way as a command runner, not a build system. Task wins if your team prefers YAML and you want built-in file watching. Make is still right when you have real file-based compile dependencies or a Makefile that works fine.
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Dynamic Electricity Pricing Automations in Home Assistant With Tibber and Nordpool
Home Assistant pulls hourly spot prices through the Tibber integration or the Nordpool HACS add-on. It then schedules EV chargers, water heaters, heat pumps, and dishwashers during the cheapest hours. On a 2026 Nordic tariff with 3-8x daily price swings, shifting 10-15 kWh of flexible load each day cuts the bill by 20-40% with no comfort cost.
Why Dynamic Pricing Pays Off in 2026
The Nordpool day-ahead auction closes around noon CET. By 13:00, prices for all 24 hours of the next day are out for every bidding zone. That window is exactly what Home Assistant needs: a once-a-day drop of 24 hourly prices that your automations can plan against overnight.
HTMX + Alpine.js: 35KB Interactive UIs, Zero Build Step
Combine HTMX
(version 2.0.4, about 14KB gzipped) with Alpine.js
(version 3.15.9, about 17KB gzipped). You get a full interactive web stack for 31KB total. No Webpack. No Vite. No Node.js. No build step. Drop two <script> tags in your HTML, sprinkle a few attributes on your markup, and let any backend serve HTML fragments. That’s the whole setup.
The split is clean. HTMX drives server-side partial updates. Alpine.js covers light client reactivity. The server returns HTML, not JSON. The browser swaps it into the page. Alpine.js attributes in the markup handle toggles, dropdowns, and modals. No compile step sits between you and your running app.
Open Source Vector Databases: Qdrant vs Milvus vs Weaviate
Five open source vector databases are worth a shortlist in 2026. Qdrant is Rust-based and wins on single-node latency and filtered ANN. Milvus 2.5 is the billion-scale pick with disk and GPU indexes. Weaviate bundles hybrid search and generative modules. Chroma is the simplest Python option for prototypes and agent memory. pgvector 0.8 is the smart bet when Postgres already runs your data. LanceDB earns a mention for multimodal, read-heavy work on S3. The right pick depends on where your data sits, how big the index gets, and whether you want strict p95 latency or built-in RAG glue.
Build a Thread Device With ESPHome and the ESP32-H2
Thread is a low-power, IPv6-based mesh protocol for smart home devices. Since ESPHome
2025.6.0, you can flash Thread-native firmware onto any ESP32-H2 or ESP32-C6 board. No Zigbee2MQTT, no WiFi congestion. Grab an ESP32-H2-DevKitM-1, write a short ESPHome config with the esp-idf framework and the openthread component, then join it to a Thread border router
like Home Assistant Yellow or a HomePod mini. Your sensors show up over IPv6 with sub-second latency and battery life measured in months.
Plant Monitor System ESP32: Under $10 Per Plant
Yes, you can monitor every houseplant in your home for under $10 per plant. A single ESP32 board running ESPHome (currently at version 2026.3.0) reads capacitive soil moisture sensors, a BH1750 light sensor, and an AHT20 temperature/humidity sensor, then feeds everything straight into Home Assistant . From there, automations send you a notification when a plant needs water, dashboards show moisture trends over weeks, and you stop guessing whether that fern in the corner is actually happy. This guide covers sensor selection, wiring a 4-plant monitoring hub, the complete ESPHome YAML configuration, Home Assistant dashboards, and tips for long-term reliability.






