Stuttgart Gelbe Karten Scraping Update

I started scraping the data for Stuttgarts "Gelbe Karten", which is issues reported by residents, in the beginning of 2021 and wrote about it. Then I opted to add everything to one CSV file. This CSV file had nearly 70k lines after over 3 years and was no fun to use. So I decided to split the one CSV into daily CSV files in yearly folders. After migrating everything and updating the scripts I force-pushed to Github to get rid of the thousands of Git commits the Github Action made while scraping. As a result of the force-push the timeseries of changes is only in the CSV files and not in the commits anymore -- which seems like a good tradeoff versus the local clone time for the repo.

The code is on Github:

The whole scriping experiment showed me a few things:

  • Github Actions for scraping are quite reliable; thanks again Simon Willison for starting this trend.

  • The city of Stuttgart didn't change anything about their infrastructure (positive for scraping; but on the other hand no improvement happened)

  • Scraping every hour generates way to many commits

Use Tigris as S3 alternative

I use AWS for work and wanted to have an alternative S3 for a private project. Tigris seems to be ready to use from a App so lets try this to receive a webhook and save the data in a bucket.

The setup is on purpose very similar to the version using supabase I blogged about at the beginning of last year. The full code is on Github in

First create a bucket for an already existing/launched Fly App:

fly storage create -n ax-s3-demo

The secrets for this bucket are automatically added to the app.

The code to write into the bucket uses boto3 the same way we would for AWS S3. So writing the json we received into the bucket could look like this:

import boto3
import io

service = boto3.client("s3", endpoint_url="")

buf = io.BytesIO()

service.upload_fileobj(buf, "ax-s3-demo", f'{dataset["uid"]}.json')

The dataset is writen into a BytesIO file object which is then uploaded to the Tigris S3 storage. The code assumes that in the dataset a field named "uid" exists which can be used for the filename.

To verify the code (the one deployed to worked, we take a look into the Tigris dashboard:


Yay, we have a file in there, but how do we get the data loaded from a different place. For me this is not within so I need new credentials which can be obtained from the Tigris dashboard unter "Access Keys". We create a new access key that can read only the one bucket we need. The actual variable parts here are "Access Key ID" and "Secret Access Key".

Code to download all files from the bucket onto the local filesystem:

import boto3

BUCKET_NAME = "ax-s3-demo"  # probably a different bucket here too

service = boto3.client("s3", endpoint_url="",
for obj in service.list_objects_v2(Bucket=BUCKET_NAME)["Contents"]:
    service.download_file(BUCKET_NAME, obj["Key"], obj["Key"])

After running this I have one json file locally, as expected. Overall this could be a very cost effective method to pass on data or files between services.