It happens in Python too. For example in ML, in 2015 everybody was using torch, then Keras, then TensorFlow, then PyTorch.
Pandas now being replaced by Polars.
If you look at MLOps, every 3 months there is a new hot library.
In other words, it happens in the active parts of the ecosystem (data-science), not in the old stable ones (standard library, reading files, ...)