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The lithography/EUV optics comes from Zeiss. The laser for generating the plasma from Trumpf. Both key elements that ASML would not be able to build in-house or get from a different supplier.

If you start scaling and running more than one instance, each instance would run the same periodic jobs. Shouldn't periodic jobs be off loaded to a queue and worker(s) to process to the messages?

How does this work? From the documentation it's clear that AWS credentials are required. Which permissions are necessary? This leads me to the assumption that the SpotML cli creates with boto3 the necessary resource (EBS Volume, spot instances, S3 bucket) on my AWS account. If this is the case, how does billing work if this is "just" a cli?

This! I am not a fan of SPA everything. This looks like a great framework for web only. But as you said, what about mobile development? Sure they are still going publish Strada. But will it also work, for example, with Flutter without additional friction? How about services that need to consume output from each other? I believe parsing HTML is more expensive than JSON.

That's great, really cool!

I wonder why it's deployed to Heroku. Isn't it just static html/css/js?

I have wondered for a long time about the hype around dark themes for this reason. No eye is perfect in terms of optical quality. Specifically, the lens can be misshaped and the vitreous can have impurities that lead to refraction of light. If we look at bright light sources the pupil is almost closed, which means all light entering propagates close to the optical axis of the eye, where lens defects are not playing a huge role. The less intense the light source gets, the more the pupil opens and more aperture is used. That means lens defects start to become more apparent and the probability the light crosses a part with inhomogeneities in the vitreous part becomes larger. With dark themes our pupils open more, using a bigger aperture of our eyes, which allows small aberrations like astigmatism to get pronounced. These optical aberrations can lead to double vision (cover up one eye and look at the white letters on a dark background from far), for which our brain compensates when both eyes are used. Of course, too much light isn't the answer either.

I have also thought about adding Turbolinks and Stimulus to a Django project. Can tell more about the changes to the middleware and webpack?

Exactly. That’s what we are doing in production.

Also Italy was gone at some point and re-appeared. I guess it’s just a glitch.

You can use CapRover and additionally save the steps of nginx and Let’s encrypt. On DigitalOcean exists even a 1-Click App of it, so it’s trivial to get CapRover running on a droplet.

Lisbon is my 'home' since ~8 years. Since I know the place well I started there. But as suggested I would like to collect similar data for several (European) cities and compare the results. For example Lisbon has a very high tourists/locals ratio which can be a reason for the huge number of trips shorter than 1km.

When I was trying to retrieve the same data from Lime API as I did for Circ, I retrieved only unique scooter ids. Even after recording 24h. First I was puzzled, but then I realized that many different scooter ids are at exactly the same GPS coordinates (also same battery level, etc). That's how I reached my conclusion.

But I might be wrong about this. I'll give it a second try for confirmation.