mirror of
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211 lines
8.0 KiB
Python
Executable File
211 lines
8.0 KiB
Python
Executable File
#!/usr/bin/env python
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#
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# Glances - An eye on your system
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#
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# SPDX-FileCopyrightText: 2026 Nicolas Hennion <nicolas@nicolargo.com>
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#
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# SPDX-License-Identifier: LGPL-3.0-only
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#
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"""Glances v5 — unit tests for the `load` plugin.
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V4-aligned alert semantics:
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- `min1` is **not watched** (too volatile).
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- `min5` is watched, `prominent: False` (early-warning, font-only render).
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- `min15` is watched, `prominent: True` (sustained-load, background highlight).
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"""
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from __future__ import annotations
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from unittest.mock import patch
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import pytest
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from glances.config_v5 import GlancesConfigV5
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from glances.plugins.load.model_v5 import PluginModel
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from glances.stats_store_v5 import StatsStoreV5
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# ---------------------------------------------------------- fixtures
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@pytest.fixture
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def store() -> StatsStoreV5:
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return StatsStoreV5()
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@pytest.fixture
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def config(tmp_path, monkeypatch) -> GlancesConfigV5:
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monkeypatch.setattr(GlancesConfigV5, "SYSTEM_CONFIG_PATH", tmp_path / "etc" / "glances.conf")
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monkeypatch.setenv("XDG_CONFIG_HOME", str(tmp_path / "xdg"))
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return GlancesConfigV5()
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def _config_with(tmp_path, monkeypatch, body: str) -> GlancesConfigV5:
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monkeypatch.setattr(GlancesConfigV5, "SYSTEM_CONFIG_PATH", tmp_path / "etc" / "glances.conf")
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xdg = tmp_path / "xdg"
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cfg_dir = xdg / "glances"
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cfg_dir.mkdir(parents=True)
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(cfg_dir / "glances.conf").write_text(body)
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monkeypatch.setenv("XDG_CONFIG_HOME", str(xdg))
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return GlancesConfigV5()
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# ---------------------------------------------------------- contract
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def test_plugin_identity(store, config):
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plugin = PluginModel(store, config)
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assert plugin.plugin_name == "load"
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assert plugin.IS_COLLECTION is False
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def test_min1_is_not_watched(store, config):
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plugin = PluginModel(store, config)
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assert plugin._fields["min1"].get("watched", False) is False
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def test_min5_is_watched_non_prominent(store, config):
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schema = PluginModel(store, config)._fields["min5"]
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assert schema["watched"] is True
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assert schema["watch_direction"] == "high"
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assert schema["prominent"] is False
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assert "default_thresholds" in schema
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def test_min15_is_watched_prominent(store, config):
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schema = PluginModel(store, config)._fields["min15"]
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assert schema["watched"] is True
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assert schema["watch_direction"] == "high"
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assert schema["prominent"] is True
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assert "default_thresholds" in schema
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# ---------------------------------------------------------- update pipeline
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async def test_update_writes_loadavg_to_store(store, config):
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plugin = PluginModel(store, config)
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with (
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patch("glances.plugins.load.model_v5.psutil.getloadavg", return_value=(0.5, 0.7, 1.2)),
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patch("glances.plugins.load.model_v5.psutil.cpu_count", return_value=4),
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):
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await plugin.update()
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payload = store.get("load")
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assert payload is not None
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assert payload["min1"] == 0.5
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assert payload["min5"] == 0.7
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assert payload["min15"] == 1.2
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assert payload["cpucore"] == 4
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async def test_update_swallows_loadavg_oserror(store, config):
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"""OSError on getloadavg() must not crash the update loop."""
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plugin = PluginModel(store, config)
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with patch("glances.plugins.load.model_v5.psutil.getloadavg", side_effect=OSError):
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await plugin.update()
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# Empty stats accepted; payload reflects the metadata layer only.
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payload = store.get("load")
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assert payload is not None
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assert "min1" not in payload
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# ---------------------------------------------------------- _levels (per-core normalization)
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async def test_min1_never_in_levels(store, config):
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"""min1 is too volatile — must never produce a level entry."""
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plugin = PluginModel(store, config)
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with (
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patch("glances.plugins.load.model_v5.psutil.getloadavg", return_value=(99.0, 0.0, 0.0)),
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patch("glances.plugins.load.model_v5.psutil.cpu_count", return_value=4),
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):
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await plugin.update()
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assert "min1" not in store.get("load")["_levels"]
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async def test_min5_level_normalized_by_cpucore_non_prominent(store, config):
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"""Default warning=1.0 per core. With 4 cores and min5=4.0 → warning, prominent False."""
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plugin = PluginModel(store, config)
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with (
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patch("glances.plugins.load.model_v5.psutil.getloadavg", return_value=(0.0, 4.0, 0.0)),
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patch("glances.plugins.load.model_v5.psutil.cpu_count", return_value=4),
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):
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await plugin.update()
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assert store.get("load")["_levels"]["min5"] == {"level": "warning", "prominent": False}
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async def test_min15_level_normalized_by_cpucore_prominent(store, config):
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"""Default critical=5.0 per core. With 2 cores and min15=11.0 → critical, prominent True."""
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plugin = PluginModel(store, config)
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with (
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patch("glances.plugins.load.model_v5.psutil.getloadavg", return_value=(0.0, 0.0, 11.0)),
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patch("glances.plugins.load.model_v5.psutil.cpu_count", return_value=2),
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):
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await plugin.update()
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assert store.get("load")["_levels"]["min15"] == {"level": "critical", "prominent": True}
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async def test_levels_ok_when_below_careful_per_core(store, config):
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"""Default careful=0.7 per core. With 4 cores and min5=2.0 → 0.5/core → ok."""
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plugin = PluginModel(store, config)
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with (
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patch("glances.plugins.load.model_v5.psutil.getloadavg", return_value=(0.0, 2.0, 2.0)),
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patch("glances.plugins.load.model_v5.psutil.cpu_count", return_value=4),
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):
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await plugin.update()
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levels = store.get("load")["_levels"]
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assert levels["min5"]["level"] == "ok"
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assert levels["min15"]["level"] == "ok"
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async def test_levels_fall_back_to_one_core_when_cpucount_unknown(store, config):
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"""psutil.cpu_count returning None → divide by 1 (defensive)."""
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plugin = PluginModel(store, config)
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with (
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patch("glances.plugins.load.model_v5.psutil.getloadavg", return_value=(0.0, 0.8, 0.8)),
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patch("glances.plugins.load.model_v5.psutil.cpu_count", return_value=None),
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):
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await plugin.update()
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# 0.8 / 1 = 0.8 → between 0.7 (careful) and 1.0 (warning) → careful
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assert store.get("load")["_levels"]["min5"]["level"] == "careful"
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assert store.get("load")["_levels"]["min15"]["level"] == "careful"
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async def test_user_config_overrides_default_threshold(tmp_path, monkeypatch, store):
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config = _config_with(tmp_path, monkeypatch, "[load]\nwarning=2.0\n")
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plugin = PluginModel(store, config)
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with (
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patch("glances.plugins.load.model_v5.psutil.getloadavg", return_value=(0.0, 4.0, 4.0)),
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patch("glances.plugins.load.model_v5.psutil.cpu_count", return_value=4),
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):
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await plugin.update()
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# 4.0 / 4 = 1.0 — was `warning` at default 1.0; with warning=2.0 the value
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# is below warning → careful (default careful=0.7). Override applies to
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# both watched fields since the bare key is shared.
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assert store.get("load")["_levels"]["min5"]["level"] == "careful"
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assert store.get("load")["_levels"]["min15"]["level"] == "careful"
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async def test_field_prefixed_config_targets_one_field_only(tmp_path, monkeypatch, store):
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"""`min15_warning=2.0` overrides only min15, leaving min5 at default warning=1.0."""
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config = _config_with(tmp_path, monkeypatch, "[load]\nmin15_warning=2.0\n")
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plugin = PluginModel(store, config)
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with (
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patch("glances.plugins.load.model_v5.psutil.getloadavg", return_value=(0.0, 4.0, 4.0)),
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patch("glances.plugins.load.model_v5.psutil.cpu_count", return_value=4),
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):
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await plugin.update()
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# min5 (warning=1.0/core × 4 = 4.0) → value 4.0 → warning
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# min15 (warning=2.0/core × 4 = 8.0) → value 4.0 → careful
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assert store.get("load")["_levels"]["min5"]["level"] == "warning"
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assert store.get("load")["_levels"]["min15"]["level"] == "careful"
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async def test_no_loadavg_keeps_levels_empty(store, config):
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"""If getloadavg fails and _grab_stats returns {}, _levels stays empty."""
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plugin = PluginModel(store, config)
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with patch("glances.plugins.load.model_v5.psutil.getloadavg", side_effect=AttributeError):
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await plugin.update()
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assert store.get("load")["_levels"] == {}
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