A cross-platform curses-based monitoring tool
Project description
Glances 🌟
Glances is an open-source system cross-platform monitoring tool. It allows real-time monitoring of various aspects of your system such as CPU, memory, disk, network usage etc. It also allows monitoring of running processes, logged in users, temperatures, voltages, fan speeds etc. It also supports container monitoring, it supports different container management systems such as Docker, LXC. The information is presented in an easy to read dashboard and can also be used for remote monitoring of systems via a web interface or command line interface. It is easy to install and use and can be customized to show only the information that you are interested in.
In client/server mode, remote monitoring could be done via terminal, Web interface or API (XML-RPC and RESTful). Stats can also be exported to files or external time/value databases, CSV or direct output to STDOUT.
Glances is written in Python and uses libraries to grab information from your system. It is based on an open architecture where developers can add new plugins or exports modules.
Usage 👋
For the standalone mode, just run:
$ glances
For the Web server mode, run:
$ glances -w
and enter the URL http://<ip>:61208 in your favorite web browser.
In this mode, a HTTP/Restful API is exposed, see document RestfulApi for more details.
For the client/server mode (remote monitoring through XML-RPC), run the following command on the server:
$ glances -s
and this one on the client:
$ glances -c <ip>
You can also detect and display all Glances servers available on your network (or defined in the configuration file) in TUI:
$ glances --browser
or WebUI:
$ glances -w --browser
It possible to display raw stats on stdout:
$ glances --stdout cpu.user,mem.used,load
cpu.user: 30.7
mem.used: 3278204928
load: {'cpucore': 4, 'min1': 0.21, 'min5': 0.4, 'min15': 0.27}
cpu.user: 3.4
mem.used: 3275251712
load: {'cpucore': 4, 'min1': 0.19, 'min5': 0.39, 'min15': 0.27}
...
or in a CSV format thanks to the stdout-csv option:
$ glances --stdout-csv now,cpu.user,mem.used,load
now,cpu.user,mem.used,load.cpucore,load.min1,load.min5,load.min15
2018-12-08 22:04:20 CEST,7.3,5948149760,4,1.04,0.99,1.04
2018-12-08 22:04:23 CEST,5.4,5949136896,4,1.04,0.99,1.04
...
or in a JSON format thanks to the stdout-json option (attribute not supported in this mode in order to have a real JSON object in output):
$ glances --stdout-json cpu,mem
cpu: {"total": 29.0, "user": 24.7, "nice": 0.0, "system": 3.8, "idle": 71.4, "iowait": 0.0, "irq": 0.0, "softirq": 0.0, "steal": 0.0, "guest": 0.0, "guest_nice": 0.0, "time_since_update": 1, "cpucore": 4, "ctx_switches": 0, "interrupts": 0, "soft_interrupts": 0, "syscalls": 0}
mem: {"total": 7837949952, "available": 2919079936, "percent": 62.8, "used": 4918870016, "free": 2919079936, "active": 2841214976, "inactive": 3340550144, "buffers": 546799616, "cached": 3068141568, "shared": 788156416}
...
Last but not least, you can use the fetch mode to get a quick look of a machine:
$ glances --fetch
Results look like this:
Use Glances as a Python library 📚
You can access the Glances API by importing the glances.api module and creating an instance of the GlancesAPI class. This instance provides access to all Glances plugins and their fields. For example, to access the CPU plugin and its total field, you can use the following code:
>>> from glances import api
>>> gl = api.GlancesAPI()
>>> gl.cpu
{'cpucore': 16,
'ctx_switches': 1214157811,
'guest': 0.0,
'idle': 91.4,
'interrupts': 991768733,
'iowait': 0.3,
'irq': 0.0,
'nice': 0.0,
'soft_interrupts': 423297898,
'steal': 0.0,
'syscalls': 0,
'system': 5.4,
'total': 7.3,
'user': 3.0}
>>> gl.cpu["total"]
7.3
>>> gl.mem["used"]
12498582144
>>> gl.auto_unit(gl.mem["used"])
11.6G
If the stats return a list of items (like network interfaces or processes), you can access them by their name:
>>> gl.network.keys()
['wlp0s20f3', 'veth33b370c', 'veth19c7711']
>>> gl.network["wlp0s20f3"]
{'alias': None,
'bytes_all': 362,
'bytes_all_gauge': 9242285709,
'bytes_all_rate_per_sec': 1032.0,
'bytes_recv': 210,
'bytes_recv_gauge': 7420522678,
'bytes_recv_rate_per_sec': 599.0,
'bytes_sent': 152,
'bytes_sent_gauge': 1821763031,
'bytes_sent_rate_per_sec': 433.0,
'interface_name': 'wlp0s20f3',
'key': 'interface_name',
'speed': 0,
'time_since_update': 0.3504955768585205}
For a complete example of how to use Glances as a library, have a look to the PythonApi.
Documentation 📜
For complete documentation have a look at the readthedocs website.
If you have any question (after RTFM! and the FAQ), please post it on the official Reddit forum or in GitHub Discussions.
Gateway to other services 🌐
Glances can export stats to:
CSV file
JSON file
InfluxDB server
Cassandra server
CouchDB server
OpenTSDB server
Prometheus server
StatsD server
ElasticSearch server
PostgreSQL/TimeScale server
RabbitMQ/ActiveMQ broker
ZeroMQ broker
Kafka broker
Riemann server
Graphite server
RESTful endpoint
Installation 🚀
There are several methods to test/install Glances on your system. Choose your weapon!
PyPI: Pip, the standard way
Glances is on PyPI. By using PyPI, you will be using the latest stable version.
To install Glances, simply use the pip command line.
Warning: on modern Linux operating systems, you may have an externally-managed-environment error message when you try to use pip. In this case, go to the the PipX section below.
pip install --user glances
Note: Python headers are required to install psutil, a Glances dependency. For example, on Debian/Ubuntu the simplest is apt install python3-psutil or alternatively need to install first the python-dev package and gcc (python-devel on Fedora/CentOS/RHEL). For Windows, just install psutil from the binary installation file.
By default, Glances is installed without the Web interface dependencies. To install it, use the following command:
pip install --user 'glances[web]'
For a full installation (with all features, see features list bellow):
pip install --user 'glances[all]'
Features list:
all: install dependencies for all features
action: install dependencies for action feature
browser: install dependencies for Glances centram browser
cloud: install dependencies for cloud plugin
containers: install dependencies for container plugin
export: install dependencies for all exports modules
gpu: install dependencies for GPU plugin
graph: install dependencies for graph export
ip: install dependencies for IP public option
raid: install dependencies for RAID plugin
sensors: install dependencies for sensors plugin
smart: install dependencies for smart plugin
snmp: install dependencies for SNMP
sparklines: install dependencies for sparklines option
web: install dependencies for Webserver (WebUI) and Web API
wifi: install dependencies for Wifi plugin
To upgrade Glances to the latest version:
pip install --user --upgrade glances
The current develop branch is published to the test.pypi.org package index. If you want to test the develop version (could be instable), enter:
pip install --user -i https://test.pypi.org/simple/ Glances
PyPI: PipX, the alternative way
Install PipX on your system (apt install pipx on Ubuntu).
Install Glances (with all features):
pipx install 'glances[all]'
The glances script will be installed in the ~/.local/bin folder.
Shell tab completion 🔍
Glances 4.3.2 and higher includes shell tab autocompletion thanks to the –print-completion option.
For example, on a Linux operating system with bash shell:
$ mkdir -p ${XDG_DATA_HOME:="$HOME/.local/share"}/bash-completion
$ glances --print-completion bash > ${XDG_DATA_HOME:="$HOME/.local/share"}/bash-completion/glances
$ source ${XDG_DATA_HOME:="$HOME/.local/share"}/bash-completion/glances
Following shells are supported: bash, zsh and tcsh.
Requirements 🧩
Glances is developed in Python. A minimal Python version 3.10 or higher should be installed on your system.
Note for Python 2 users
Glances version 4 or higher do not support Python 2 (and Python 3 < 3.10). Please uses Glances version 3.4.x if you need Python 2 support.
Dependencies:
psutil (better with latest version)
defusedxml (in order to monkey patch xmlrpc)
packaging (for the version comparison)
windows-curses (Windows Curses implementation) [Windows-only]
shtab (Shell autocompletion) [All but Windows]
jinja2 (for fetch mode and templating)
Extra dependencies:
batinfo (for battery monitoring)
bernhard (for the Riemann export module)
cassandra-driver (for the Cassandra export module)
chevron (for the action script feature)
docker (for the Containers Docker monitoring support)
elasticsearch (for the Elastic Search export module)
FastAPI and Uvicorn (for Web server mode)
graphitesender (For the Graphite export module)
hddtemp (for HDD temperature monitoring support) [Linux-only]
influxdb (for the InfluxDB version 1 export module)
influxdb-client (for the InfluxDB version 2 export module)
kafka-python (for the Kafka export module)
nvidia-ml-py (for the GPU plugin)
pycouchdb (for the CouchDB export module)
pika (for the RabbitMQ/ActiveMQ export module)
podman (for the Containers Podman monitoring support)
potsdb (for the OpenTSDB export module)
prometheus_client (for the Prometheus export module)
psycopg[binary] (for the PostgreSQL/TimeScale export module)
pygal (for the graph export module)
pymdstat (for RAID support) [Linux-only]
pymongo (for the MongoDB export module)
pysnmp-lextudio (for SNMP support)
pySMART.smartx (for HDD Smart support) [Linux-only]
pyzmq (for the ZeroMQ export module)
requests (for the Ports, Cloud plugins and RESTful export module)
sparklines (for the Quick Plugin sparklines option)
statsd (for the StatsD export module)
wifi (for the wifi plugin) [Linux-only]
zeroconf (for the autodiscover mode)
Project sponsorship 🙌
You can help me to achieve my goals of improving this open-source project or just say “thank you” by:
sponsor me using one-time or monthly tier Github sponsors page
send me some pieces of bitcoin: 185KN9FCix3svJYp7JQM7hRMfSKyeaJR4X
buy me a gift on my wishlist page
Any and all contributions are greatly appreciated.
License 📜
Glances is distributed under the LGPL version 3 license. See COPYING for more details.
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