alt Hacker NewsI 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.
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My company network wont let me see newly registered domains, so I couldn't check out your build (I'll wait until I get home!), but our local state government set up a tool called Fuel Watch that does a pretty good job of showing the today/tomorrow pricing based on post code.
Probably not doing exactly what your tool does, but you might be interested: https://www.fuelwatch.wa.gov.au/
>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.
Comparing the absolute size of price rises vs drops doesn't make sense, because it could very well be an issue with the underlying price (eg. crude oil or whatever). It seems hardly fair to blame gas stations for being slow to lower prices, when refineries are still also slow to lower prices. Same for blaming refineries when the global market is slow to lower prices.
For the "supermarket saving", did you include Asda in the supermarket pool, or as a general pool? They seem to be rather less price competitive than other supermarkets, I'd presumably because of the recentish private equity takeover involving petrol station operator Euro Garages meaning they've kinda opted out of the petrol price war (they're hardly likely to want to undercut their existing forecourts).
Although the other recent private equity takeover of Morrisons led to some sort of deal with Motor Fuels Group to operate their petrol stations (but no ownership stuff in this case?), but they're seemingly still being competitive with Sainsbury's and Tesco's.
Are you aware the some of the Fuel Finder data is total garbage?
https://successfulsoftware.net/2026/03/29/stop-publishing-ga...
Why did you make 'Esso' and 'Shell' the same colour in your brand chart?
> 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.
Only 1 change per station per week on average? Fewer than I expected. Not sure I'd call it a scraper, myself.
157p/L national average is about 8 USD/G.
What did you use for the UI widgets, graphs, etc? Looks like tailwind is being used but is the design bespoke or a CSS/dashboard lib?
Since you are happy to talk on this topic, can I mention your privacy policy page?
If a new user clicks on Accept, he has no (normie) mechanism to revoke that as the choice is stored in local storage and it doesn't expire.
Any appetite in adding data for electricity rates for EVs?
Is at least part of this comment LLM-generated?
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Just curious, not intending this as an attack on your project.
Another insightful way to look at this is to include gasoline spot market data as a comparison.
I kept hearing about the vast profits of gas stations, so one day I started a spreadsheet of my gas purchases and kept it going over 10 years. When I tried lining up the graph of what I have actually paid per litre with a spot market graph, after converting for currency, units, taxes etc, they were almost identical, indicating extremely slim margins, if any. Yes there were differences, places in the graph where stations had likely made money on my purchase, but there were just as many where they likely lost money, unless I also stepped inside to but a snack.