donjoe

It's great you do have a bank-bound system in Finland. I hope their implementation is not as bad as e.g. the Swedish BankID.

BankID is _in theory_ a nice technology. However, it is only handed out to people registered with the Swedish tax authorities holding a Swedish bank account.

All daily activities are nowadays bound to BankID: need a doctor's appointment? -> needs BankID; Want to buy something on Blocket? -> needs BankID.

As an European frequently spending some time in Sweden not in possession of a Swedish tax #, I feel very much excluded from online and partially offline activities in this country.

The video brought me back to my internship in the early 2010s. My job was testing the new US ovens (which for us Europeans are massive). The bus was amazing. Integrated into a LabView setup, you could basically collect any readings from the oven as well as remotely control it. Also, it was super easy to confirm "manual" actions (e.g. soleniods pushing buttons/motors turning knobs).

A few other interesting tasks I was involved back then were:

- smashing an oven's door until the hinges would give up - testing new heating elements in the open (basically, building a gigantic grill) - appliance transport packaging tests - cooking and baking on a daily basis to make sure food turns out as expected

Overall, home appliances are a great product as an engineer to work on. It is a product you usually use multiple times a day. And if you love cooking yourself, even better :-)

To me, the most important question is: how do I scale v7 in an environment of 20+ engineers?

When using v7, I need some sort of audit that checks in every API contract for the usage of v7 and potential information leakage.

Detecting V7 uuids in the API contract would probably require me to enforce a special key name (uuidv7 & uuid for v4) for easier audit.

Engineers will get this wrong more than once - especially in a mixed team of Jr/sr.

Also, the API contracts will look a bit inconsistent: some resources will get addressed by v7, others by v4. On top, by using v4 on certain resources, I'd leak the information that those resources addressed by v4 will contain sensitive information.

By sticking to v4, I'd have the same identifier for all resources across the API. When needed, I can expose the creation timestamp in the response separately. Audit is much simpler since the fields state explicitly what they will contain.

... If you live close by Theresienwiese, the city provides free cleaning for any accidents during Oktoberfest in your front/backyard also. I have to smile everytime I do find the note containing an emergency accident cleanup number in my mailbox :-)

Let's hope it's deepseek-compatible.

testcontainers is great. I struggled a bit with testcontainers due to the nature of one container per test which just felt too slow for writing gray/blackbox tests. The startup time for postgres was > 10 seconds. After a bit of experimenting, I am now quite happy with my configuration which allows me to have a snappy, almost instant testing experience.

My current setup:

- generate a new psql testcontainer _or_ reuse an existing one by using a fixed name for the container - connect to the psql container with no database selected - create a new database using a random database name - connect to the randomly generated database - initialize the project's tables - run a test - drop the database - keep the testcontainer up and running and reuse with next test

With this setup, most tests run sub-second;

Which is perfectly fine. However, you will be able to process only a single message per connection at once.

What you would do in go is:

- either a new goroutine per message

- or installing a worker pool with a predefined goroutine size accepting messages for processing

UseMemo should not be used for fetching/kicking off a fetch either. UseMemo fans should be pure. Using logic that belongs into useEffect (logic that happens _outside_ the reactive flow) could potentially lead to other side effects which are very hard to debug. Just a example: a lot of fetch implementations are using fetch with a cache triggered in useMemo returning immediately. You will probably have a setState somewhere in the flow which will terribly interrupt react and break your page.

In case you trigger a native fetch, you've got no way to cancel the call due to the missing cleanup fn.