{"repo":"lptva/gb-power-dashboard","free":true,"listed":false,"github":"https://github.com/lptva/gb-power-dashboard","clone":"git clone https://github.com/lptva/gb-power-dashboard.git","description":"A real-data market intelligence web app for the Great Britain power market, in the style of a commodity-analytics terminal. Single-page, static, no build step, driven entirely by public data fetched through a re-runnable ETL.","language":"Python","stars":16,"topics":["data-visualisation","data-visualization","echarts","energy-markets","power-systems","python"],"license":"MIT","category":"dashboards-admin","readme_excerpt":"GB Power Market Intelligence Dashboard A real-data market intelligence web app for the Great Britain power market, in the style of a commodity-analytics terminal. Single-page, static, no build step, driven entirely by public data fetched through a re-runnable ETL. See it live: – updated daily, nothing to install. This is not a stylised model. Every observed series comes from a public market data source; every estimated or assumption-based metric is labelled as such in the UI, panel by panel. The Overview tab on real data (July 2026). More screenshots below. Run your own copy Just want to look? Use the live link above – everything below is for running the dashboard yourself, with your own data pipeline. Never used a terminal or installed Python? Follow docs/SETUP.md instead – a step-by-step guide for Mac and Windows that assumes no experience at all. Or, with Python already installed, python3 install.py (Mac) / double-clicking install.bat (Windows) does everything below with prompts. The three commands that follow are the short version for people comfortable with a terminal. Every command in this README is written to be run from the repository root, whatever you named it and wherever you cloned it – nothing assumes a particular folder layout or username. Prefer a one-off full rebuild instead of relying on the automatic fallback (for example, to re-fetch every chunk after clearing data raw/cache/ )? Run python3 etl/build dataset.py --days 365 directly, then python3 ops/refresh.","default_branch":null,"files":null,"tree":[],"storefront":"/r/lptva","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/lptva/gb-power-dashboard/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}