perf

TD Perf

Diagnose TouchDesigner performance bottlenecks by measuring per-operator cook time and correlating the worst offenders with known heavy patterns.

Workflow

1. Explain up front that real measurement requires running a script via execute_python_script — the permission prompt that may follow is expected, not a malfunction.

2. Call get_td_info to confirm TouchDesigner is reachable before doing anything else; if it fails, point the user at /touchdesigner:setup instead of proceeding.

3. Resolve root to the root-path argument if given, otherwise /project1 if it exists, else / (a project launched by opening the tox as a document has no /project1).

4. With the user's consent, run a measurement script through execute_python_script with detailLevel: "detailed" so the complete ranking is returned rather than the summary formatter's 500-character preview. Collect the resolved root and its descendants: findChildren() walks the whole subtree when called with no arguments (maxDepth limits it, while depth is an exact-match filter, not a limit), but it never returns the operator it was called on — that operator is depth 0, and findChildren(depth=0) is empty. Leave the root out and a root-path naming a single TOP measures nothing at all, while a COMP's own cook time goes missing from totalCookTime, and for each operator record its path, name, opType, and cookTime (skipping operators where cookTime isn't a meaningful attribute rather than erroring out). Sort the collected results by cookTime descending and keep roughly the top 20 — but return the number of operators measured and the sum of all their cook times alongside that slice. The slice is the only thing that survives the call, so a denominator left behind cannot be recovered afterwards. For example:

   root = "/project1"  # the path resolved in step 3
   root_op = op(root)
   results = []
   for child in [root_op, *root_op.findChildren()]:
   	ct = getattr(child, "cookTime", None)
   	if ct is not None:
   		results.append(
   			{
   				"path": child.path,
   				"name": child.name,
   				"opType": getattr(child, "OPType", ""),
   				"cookTime": ct,
   			}
   		)
   results.sort(key=lambda r: r["cookTime"], reverse=True)
   result = {
   	"measuredCount": len(results),
   	"totalCookTime": sum(r["cookTime"] for r in results),
   	"top": results[:20],
   }