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kevinveenbirkenbachandClaude Opus 5
370c8d54c8
_ram_gb reimplemented the /proc/meminfo parse that utils/env/runtime.py owns: same pseudo-file, same MemTotal scan, same line.split()[1], same swallow-and-fall-back guard. It now calls mem_total_mb(). The error semantics map exactly. The helper returns 0 for an unreadable file, a malformed line and a missing field; all three previously produced 4.0, and 0 is falsy, so the conservative fallback still covers every one of them. One real delta: the helper floors kB to MB before the GB conversion, so _ram_gb loses up to 0.001 GB. That can only move the worker count where MemTotal/2 sits within half a megabyte of an exact 1.5 GiB multiple, and it moves it downwards, which is the direction this sizing already prefers. Touching the file pulled its ten pre-existing narration comments into the diff-scoped comment lint. They were deleted, not relabelled. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
80 lines
2.3 KiB
Python
80 lines
2.3 KiB
Python
from __future__ import annotations
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import os
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from typing import Any
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from ansible.plugins.lookup import LookupBase
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from utils.env.runtime import mem_total_mb
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_PER_WORKER_GB = 1.5
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_RAM_FRACTION = 0.5
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_CPU_DIVISOR = 4
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_HARD_CAP = 6
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_CI_CAP = 2
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_CI_ENV = ("CI", "GITHUB_ACTIONS", "GITLAB_CI", "BUILDKITE", "JENKINS_URL")
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def _cpu_count() -> int:
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try:
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return max(1, len(os.sched_getaffinity(0)))
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except (AttributeError, OSError):
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return max(1, os.cpu_count() or 1)
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def _ram_gb() -> float:
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total_mb = mem_total_mb()
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return total_mb / 1024 if total_mb else 4.0
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def _is_ci() -> bool:
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return any(os.environ.get(k) for k in _CI_ENV)
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def compute_workers(
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cpus: int,
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ram_gb: float,
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ci: bool,
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*,
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per_worker_gb: float = _PER_WORKER_GB,
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ram_fraction: float = _RAM_FRACTION,
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cpu_divisor: int = _CPU_DIVISOR,
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hard_cap: int = _HARD_CAP,
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ci_cap: int = _CI_CAP,
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) -> int:
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cpu_workers = max(1, cpus // max(1, cpu_divisor))
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ram_workers = max(1, int((ram_gb * ram_fraction) // per_worker_gb))
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workers = min(cpu_workers, ram_workers, hard_cap)
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if ci:
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workers = min(workers, ci_cap)
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return max(1, workers)
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class LookupModule(LookupBase):
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"""
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lookup('playwright_workers')
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Conservative, stable parallel-worker count for the Playwright e2e suite.
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Derived from the control host's effective CPU and RAM, divided down because
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browser workers are heavy and run against the co-resident application stack,
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reserved against RAM, hard-capped for the application-under-test's
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concurrency limits, and reduced further on CI. Always returns an int >= 1.
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Tunable via kwargs: cpu_divisor, hard_cap, ci_cap, per_worker_gb,
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ram_fraction.
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"""
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def run(self, terms, variables: dict[str, Any] | None = None, **kwargs):
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return [
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compute_workers(
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_cpu_count(),
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_ram_gb(),
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_is_ci(),
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per_worker_gb=float(kwargs.get("per_worker_gb", _PER_WORKER_GB)),
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ram_fraction=float(kwargs.get("ram_fraction", _RAM_FRACTION)),
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cpu_divisor=int(kwargs.get("cpu_divisor", _CPU_DIVISOR)),
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hard_cap=int(kwargs.get("hard_cap", _HARD_CAP)),
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ci_cap=int(kwargs.get("ci_cap", _CI_CAP)),
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)
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]
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