[Peaker]

Lazy evaluation implies that you keep the result for re-use later if it is shared between multiple users. So if laziness causes performance problems, it is generally:

* A space leak: The deferred computation holds lots of data alive for when it will be needed, whereas computing it would reduce all that data into a small result.

* A latency problem (sometimes called a "time leak") where we may idle around for a while, and only when some value is desperately needed, start computing it. We could preemptively compute the result to hide its latency.

These were not the problem here. The problem here was that part of the computation of the result is redone each time.

Sharing parts of the computation between the invocations was not trivial, and to do this, they found it easier to move the computation to the template loading time ("compile time").