Heisse Preise

A terrible grocery price search "app". Fetches data from big Austrian grocery chains daily and lets you search them. See https://heisse-preise.io.

The project consists of a trivial NodeJS Express server responsible for fetching the product data, massaging it, and serving it to the front end (see server.js). The front end is a least-effort vanilla HTML/JS app (see sources in site/).

Requirements

• Node.js

Running

Development

Install NodeJS, then run this in a shell of your choice.

git clone https://github.com/badlogic/heissepreise
cd heissepreise
mkdir -p data
npm install
npm run dev

The first time you run this, the data needs to be fetched from the stores. You should see log out put like this.

Fetching data for date: 2023-05-23
Fetched LIDL data, took 0.77065160000324 seconds
Fetched MPREIS data, took 13.822936070203781 seconds
Fetched SPAR data, took 17.865891209602356 seconds
Fetched BILLA data, took 52.95784649944306 seconds
Fetched HOFER data, took 64.83968291568756 seconds
Fetched DM data, took 438.77065160000324 seconds
Merged price history
App listening on port 3000

Once the app is listening per default on port 3000, open http://localhost:3000 in your browser.

Subsequent starts will fetch the data asynchronously, so you can start working immediately.

Production

Install the dependencies as per above, then simply run:

git clone https://github.com/badlogic/heissepreise
cd heissepreise
npm install
npm run dev

Once the app is listening per default on port 3000, open http://localhost:3000 in your browser.

Using data from heisse-preise.io

You can also get the raw data. The raw data is returned as a JSON array of items. An item has the following fields:

• store: (billa, spar, hofer, dm, lidl, mpreis, ...)
• name: the product name.
• price: the current price in €.
• priceHistory: an array of { date: "yyyy-mm-dd", price: number } objects, sorted in descending order of date.
• unit: unit the product is sold at. May be undefined.
• quantity: quantity the product is sold at for the given price
• bio: whether this product is classified as organic/"Bio"

If you run the project locally, you can use the data from the live site including the historical data as follows:

cd heisse-preise
rm data/latest-canonical.*
curl -o data/latest-canonical.json https://heisse-preise.io/data/latest-canonical.json

Restart the server with either npm run dev or npm run start.

Historical Data Credits

The live site at heisse-preise.io feature historical data from:

• Dossier
• @h43z, who runs preisinflation.online, another grocery price tracker.