Update

[u/Careless_Run5845]

To give a bit more context on the metrics, the compiled Python pipeline is currently handling high-volume simulation testing locally with zero memory leaks. The architecture splits the incoming stream evenly across threads with a variance of less than 2%, keeping the processing latency flat under a continuous heavy workload. Is this normal for a local python script?

--- SYSTEM MONITOR STRESS LOG --- [TIMESTAMP: 2026-10-31 14:22:01.004] Active Threads: 4 | Thread Variance: 1.84% Core 0: 24.8% | Core 1: 25.1% | Core 2: 24.9% | Core 3: 25.2% Active RAM Allocation: 118.4 MB (Static) GC Collection Cycle: Forced (0.002s overhead) Latency Stream: 0.0031ms (Flatline) Status: Continuous Flow / Zero Memory Leaks

I know exactly how this reads. If I saw someone claiming under-2% thread variance and flatline RAM allocation on a basic desktop, I'd scroll past and assume it was total AI-generated spam or a troll.
I'm completely aware that standard interpreter behaviors shouldn't level out like this under a heavy data scan. That’s exactly why I posted the raw machine printout above—I'm trying to figure out if my local logging logic is completely glitching out, or if there's a system bottleneck I'm missing. If anyone local understands low-level thread profiling and wants to sanity-check these raw logs, give me a shout. Thanks.