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theazureguy

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Yeah aware of some data quality issues in the feed, bad coordinates, missing brands, occasional obviously wrong prices. I filter out anything outside 100-300p and exclude stations flagged as closed but there's definitely still noise in there. check the methodology page for the full detail on how i clean it.

On the colours, esso and shell are both red brands so they ended up close on the chart. will fix that.

fair point on scraper, it's more of an ingest pipeline really. the 90k is total price records across 7,700 stations since january, stations update a few times a week on average. the 10 min polling catches every move when it happens. the value is in the per-station, history over time, not the raw volume.

Update for anyone who hit a slow site earlier: b1ms postgres wasn't having a great time with 140 concurrent users. scaled the db up, bumped the instance, and shipped in-memory output caching while the thread was live so repeated requests stop hammering the db. Site is fully up and fast now. appreciate the interest, genuinely didn't expect to front page today.

Good shout. DESNZ publishes weekly wholesale rack prices and they are OGL, so there is no barrier there. The interesting bit isn't just showing the gap; it's the propagation lag. Wholesale spikes and pump prices follow within days. Wholesale drops and pump prices take their time. That asymmetry is basically what I built this dataset to measure. Adding the wholesale series as a reference line is on the list.

Yeah Asda is in there. I match on brand name directly rather than the API's is_supermarket flag because that flag is all over the place (loads of Asda stations don't have it set). So it explicitly checks for Asda, Tesco, Morrisons, Sainsbury's, Co-op, Costco.

Your point about post-PE Asda is interesting, I've noticed it too. If you want to see how they compare individually you can check the brands page on the site, shows each supermarket chain as its own line. Pretty easy to split the supermarket aggregate out per brand too, would probably show Asda creeping back towards the independents since the takeover. Might add that.

I got frustrated that every fuel price app just shows you what's cheap nearby. I wanted to know how stations actually behave: do prices go up faster than they come down, do supermarkets really save you much, how bad are motorway prices really?

So I built a scraper that hits the UK government's mandatory Fuel Finder API every 10 minutes and stores every price change. 90k records across 7,700 stations since January.

Some things I found that surprised me:

The rocket and feather effect is real and measurable. When stations raise prices the average move is 2.35p/litre. When they cut, it's 1.85p. There are also more up moves than down moves. I queried the raw history to check this rather than eyeballing a chart.

Motorway fuel is 28.4p/litre more expensive than everywhere else right now. That's about £14 extra on a 50L fill. Everyone knows motorways are expensive but I didn't expect the gap to be that wide.

The supermarket discount is only about 1.7p. I assumed it would be bigger.

Stack is Azure Functions, TimescaleDB, PostGIS, Next.js. The interesting thing about this project is the history. No public site shows how an individual station has priced over time or how a local cluster of stations react to each other. That's what I'm building towards.

Site: https://fuelinsight.co.uk

Happy to talk through the architecture or the data if anyone's interested.