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$ show nicolargo/glances

[account ↗] [repo ↗] APPLICATION ★ 33746 1821 ● active (last update 1 week ago)
reviewed by: deepseek/deepseek-v4-flash

Glances is a cross-platform, real-time system monitoring tool written in Python. It collects system metrics (CPU, memory, disk, network, processes, sensors, containers, GPU, NPU, etc.) via the `psutil` library and optional hardware-specific backends, and renders them through multiple interfaces: a curses-based terminal UI, a web UI (Vue.js + FastAPI REST API), a pure JSON/CSV stdout mode, a Model Context Protocol (MCP) server for AI assistant integration, and exports to 20+ time-series databases and message brokers (InfluxDB, Prometheus, Kafka, Elasticsearch, etc.). The architecture is modular and plugin-based: each metric domain is a self-contained plugin inheriting from a common base class, and each export target is a separate module. Glances can run standalone (local monitoring), in client/server mode (XML-RPC or REST), or as a central browser that discovers and displays multiple Glances instances via Zeroconf. The project is production-grade, with extensive test coverage, CI/CD across multiple OSes, Docker images, and active security maintenance. Its primary use case is real-time monitoring of single or distributed systems, with optional historical data export for long-term analysis.

RATING8.9/10
QUALITY7.8/10
MAINTENANCEactive
DRIFTlow
CONTRIBUTORS257
VELOCITY0.98
OPEN ISSUES112
CLOSED ISSUES2124
LAST COMMIT1 week ago
defusedxml (pip) ==0.7.1
jinja2 (pip) ==3.1.6
markupsafe (pip) ==3.0.3
packaging (pip) ==26.2
psutil (pip) ==7.2.2
shtab (pip) ==1.9.2
windows-curses (pip) ==2.4.2
Files by Type (count)
Python
398
Markdown
125
reStructuredText
70
Other (.png)
63
Other (no ext)
54
Vue
35
JavaScript
34
Other (.mjs)
19
YAML
18
Shell
15
Text
10
JSON
8
Files by Type (size)
Other (.png)
4MB
Python
3MB
HTML
3MB
Markdown
3MB
Other (.gif)
1MB
JavaScript
586KB
reStructuredText
508KB
JSON
330KB
Other (.svg)
314KB
Vue
216KB
Config
109KB
Other (.mjs)
78KB

The LLM identified 5 files worth highlighting for reuse:

Base class for all Glances plugins. Provides decorators for refresh timing, rate computation, min/max/mean tracking, result logging, and input validation. Implements a consistent interface for update(), update_views(), get_export(), and alert threshold handling. The pattern is reusable for any plugin-based monitoring system and demonstrates clean separation of concerns.

file: glances/plugins/plugin/model.py ↗ | tags: #plugin-system #decorator-pattern #validation

Base class for all export modules. Handles configuration loading, field filtering, InfluxDB line protocol normalization, and a common export() interface. The {build_export} and {normalize_for_influxdb} methods are particularly reusable for any system that needs to export structured data to multiple backends.

file: glances/exports/export.py ↗ | tags: #export-base #config-loading #normalization

Provides a secure implementation of subprocess execution (secure_popen) that mitigates shell injection by controlling operator usage. The allow_operators flag and argument validation pattern are directly reusable in any Python application that needs to execute user-influenced commands safely.

file: glances/secure.py ↗ | tags: #security #command-execution #input-sanitization

Implements a directed acyclic graph (DAG) for plugin dependency resolution. Used to ensure plugins are updated in the correct order based on their dependencies. The DAG class is standalone and can be extracted for any project needing dependency ordering.

file: glances/plugins/plugin/dag.py ↗ | tags: #dependency-graph #topological-sort

Simple Timer and Counter classes for measuring elapsed time and counting iterations. Used extensively for refresh interval management and performance measurement. Self-contained and reusable in any Python project needing precise timing utilities.

file: glances/timer.py ↗ | tags: #timer #counter #utility
Last analyzed: 2026-08-20 14:00:12.403921
Next check: 2026-10-08 04:21:57.802071
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