System resource info, processor usage logging, RAM limit — standalone module from the SciTeX ecosystem
Project description
scitex-resource
System resource info, processor usage logging, RAM limiting + host-identity config.
Full Documentation · uv pip install scitex-resource[all]
Installation
pip install scitex-resource
Architecture
src/scitex_resource/
├── __init__.py # public API surface (lazy via __getattr__)
├── _host.py # canonical host name + host config resolution
├── _machine.py # deprecated aliases → _host (back-compat)
├── _runtime.py # SCITEX_DIR-aware runtime path resolver
├── _log_processor_usages.py # CPU / RAM / GPU / VRAM CSV logger
├── limit_ram.py # cap process RSS via resource.RLIMIT_AS
├── _compat.py # vendored str / gen helpers (decoupling)
├── _cli/ # Click-based CLI (hosts, specs, metrics, …)
├── _mcp/ # FastMCP server (Python-API mirror)
├── _utils/ # psutil wrappers (metrics / specs)
└── _specs/ # rich human-readable snapshot helpers
1 Interfaces
Python API
import scitex_resource as r
# Hub-friendly metrics (cross-platform via psutil)
metrics = r.get_metrics()
# Canonical host identity
name = r.get_host_name()
cfg = r.get_host_config() # {"canonical_name", "aliases", "role", "hpc": {...}}
# Rich snapshot
specs = r.get_specs()
# CPU/RAM/GPU/VRAM samples + continuous CSV logging
usage = r.get_processor_usages()
r.log_processor_usages(limit_min=30, interval_s=1)
# default: ~/.scitex/resource/runtime/processor_usages.csv
# Cap process RAM
r.limit_ram(0.5)
CLI
# Host identity
$ scitex-resource hosts show
$ scitex-resource hosts config show --json
# System specs and live metrics
$ scitex-resource specs
$ scitex-resource metrics show --json
# Processor usage snapshot + continuous CSV log
$ scitex-resource processor-usages show --json
$ scitex-resource processor-usages log --interval 5 --max-rows 12
# Cap process RAM
$ scitex-resource ram-limit 0.8
Demo
flowchart LR
env["$SCITEX_RESOURCE_HOST"] --> resolve["resolve canonical name"]
proj["./.scitex/resource/config.yaml"] --> resolve
home["~/.scitex/resource/config.yaml"] --> resolve
host["socket.gethostname()"] --> resolve
resolve --> name["get_host_name() → 'mba'"]
resolve --> cfg["get_host_config()"]
psutil["psutil"] --> metrics["get_metrics()"]
metrics --> snapshot[("cpu / mem / disk / gpu / load")]
psutil --> log["log_processor_usages(limit_min=30)"]
log --> csv[("~/.scitex/resource/runtime/processor_usages.csv")]
Quick Start
import scitex_resource as r
print(r.get_host_name()) # canonical host identity
metrics = r.get_metrics() # cpu / mem / disk / gpu / load
specs = r.get_specs() # rich human-readable snapshot
Host identity config — ~/.scitex/resource/config.yaml
host:
canonical_name: mba # what every scitex-* package uses to refer to this host
aliases: # optional; cross-package discovery / drift detection
- Yusukes-MacBook-Air
- Yusukes-MacBook-Air.local
role: head # generic role tag (head, worker, hpc-login, ...)
hpc: # optional; HPC-only
cluster: spartan
login_only: true
partitions: [physical, sapphire]
Resolution cascade (highest precedence first):
$SCITEX_RESOURCE_HOST<project>/.scitex/resource/config.yamlhost.canonical_name~/.scitex/resource/config.yamlhost.canonical_namesocket.gethostname().split(".", 1)[0]
(Deprecated $SCITEX_RESOURCE_MACHINE and machine: config block are
still honoured as fallbacks with a one-time DeprecationWarning.)
Status
Standalone fork of scitex.resource. Deps: pandas, psutil, PyYAML, click.
Decoupling notes:
scitex.str.readable_bytes/scitex.gen.fmt_size/scitex.str.printc→ vendored as small helpers in_compat.py.scitex.io._load.load/scitex.io._save.save→ usepandas.read_csv/to_csvdirectly for the CSV log files.scitex.sh.sh→ preferscitex_shif installed, fall back to plainsubprocess.run(list-only).
The umbrella package's scitex.resource import path is preserved via a
sys.modules-alias bridge.
Part of SciTeX
scitex-resource is part of SciTeX. Install via
the umbrella with pip install scitex[resource] to use as
scitex.resource (Python) or scitex resource ... (CLI).
Four Freedoms for Research
- The freedom to run your research anywhere — your machine, your terms.
- The freedom to study how every step works — from raw data to final manuscript.
- The freedom to redistribute your workflows, not just your papers.
- The freedom to modify any module and share improvements with the community.
AGPL-3.0 — because we believe research infrastructure deserves the same freedoms as the software it runs on.
License
AGPL-3.0-only (see LICENSE).
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