This is a bad example because it implies that the bikes aren't observing traffic laws.
A more analogous would be that some cars choose to go off roading, or spend most of their time in driveways or parking lots - or some only drive to car shows. A much more accurate analogy would be cars that only drive in one lane and never use the left lane for passing.
My visidata protip is using it as a pager for terminal database clients. I'm using it with mycli/MySQL right now but it should work with any client that lets you use a custom result pager. This setup has entirely replaced gui db clients which I've found to be consistently awful.
We desperately need the continued work of serious investigative journalism outfits. Even the existence of organizations able (willing?) to report fact-checked stories held to a high editorial standard seems tenuous. These businesses are not a public service but in my estimation all Americans benefit from an independent fourth estate.
If you read NYT articles with any regularity I strongly urge you to subscribe. For me the cost of a digital subscription is trivial relative to the value I get from it.
Micropayments have failed constantly since the .com bubble days.
The whole thing with micropayments is that the content creator is hoping that the cost to purchase the article is going to be low enough to where the user isn't going to notice the money.
But they will notice. You're forcing a person to read a headline (and maybe a half paragraph intro) and then deciding if it's actually worth buying the article. That's a decision that the average person is not going to put up with.
The best solution is to support publications that produce consistent and high quality content. The best model for this (that we know of) is recurring payment.
I think they are referring to "event-driven" DAGs which would be both shaped and triggered dynamically. You can accomplish this now but it feels a bit hacky and is pretty clear that it goes against the Airflow paradigm of static, slowly-changing workflows
[Airflow author here] in general, and when thinking in terms of best practices, we like to think of a DAG's shape as slowly changing, in a similar way that a database's tables definition is slowly changing. In general, you don't want to change your table's structure dynamically. This constraint brings a certain clarity and maintainability, and most use cases can be expressed this way.
Now. Airflow allows you to do what you're describing as well and will explain how to. If you were my coworker I'd dig deeper and try to understand whether the design you want is the design that is best, but let's assume it is. So first we support "externally triggered DAGs", which means those workflows don't run on a schedule, they run when they are triggered, either by some sensor, or externally in some way. A use case for that would be some company processing genomes files, and everytime a new genome file shows up, we want to run a static DAG for it.
https://airflow.incubator.apache.org/scheduler.html#external...
Now if your DAG's shape changes dramatically at every run [a shapeshifting DAG!], I would argue that conceptually they are different DAGs, and would instruct to build "singleton" DAGs dynamically. Meaning you have python code that creates a dag object [with its own dag_id] for each "instance", with the schedule_interval='@once', meaning each DAG will run only once. You can shape each DAG individually, from that same script, and craft whatever dependency you might like for each one.
Though all of this is not only possible and easy-ish to do, it may not be the best approach. Try to think of your DAGs and tables as static [or slowly changing] if you can, and the data as the variable.
As an analogy, try to think of an oil pipeline that changes shape based on the quality of the oil it processes. Crazy?! It's easier to think of the pipeline as static and infrastructure, and to have components that can sort and direct the flow in [existing and static] pipes.
Starting from 1.8 you will be able to trigger dags through a rest API, that is fully supported.
Shaping DAGs dynamically poses a challenge to the scheduler on how to 'predict' what tasks need to run in the future. The scheduler needs to evaluate which tasks will need to run, without actually executing these tasks themselves. For Airflow in its current state that is a chicken and egg problem.
For the future, I can think of allowing dynamic dags being described through the Rest API, but that is definitely further out and has not really popped up yet on the horizon.
The same reason we might invest in traffic lights or stop signs even though cars regularly ignore them.