thermalcanary 1.1.9

GPU and CPU thermal gauges for Linux — six circular arc gauges on a dedicated monitor

The Linux software for dedicated hardware monitoring screens — like AIDA64's sensor panel, but native to your desktop.

6 circular arc gauges (CPU temp, usage, RAM · GPU temp, fan, VRAM) built with PyQt6 and pynvml. Smooth 60fps animation, rolling average stabilisation, dynamic heat colors. Auto-starts on login.

Built for dedicated monitoring screens — works out of the box on stretched panels (1920×480), small IPS monitors, or any secondary display you use as a permanent hardware panel.

⚠ Important — this is NOT an overlay. Thermal Canary is a fullscreen app intended for a dedicated monitor. Don't try to use it as an in-game overlay (use MangoHud for that).

Fully responsive — gauges scale to any resolution and orientation: ultrawide, portrait, rotated, compact.

One-command install — pipx install thermalcanary and you're done.

Dedicated monitoring screen setup

Plug in a secondary screen (a stretched panel, a small IPS monitor, anything), select it in the Settings sidebar under Monitor, and click Set as default. Thermal Canary will always open on that screen at login — no configuration files to edit.

Gauges

Row	Gauge	Source
CPU	CPU Temperature	psutil.sensors_temperatures() — coretemp/k10temp (configurable)
CPU	CPU Usage %	psutil
CPU	RAM Usage %	psutil
GPU	GPU Temperature	NVIDIA: pynvml · AMD: sysfs hwmon · Intel: xe/i915 sysfs
GPU	GPU Fan Speed %	NVIDIA: pynvml · AMD: sysfs hwmon (0% = fans stopped or AMD integrated GPU with no fan)
GPU	GPU VRAM Usage %	NVIDIA: pynvml · AMD: sysfs hwmon · Intel: always 0 (not exposed by driver)

Requirements

Tested and supported on Ubuntu 24.04 LTS. Other distros (Fedora, Arch, openSUSE) are supported by the installer but have not been formally tested yet. Ubuntu versions below 24.04 may work but are not guaranteed.

The installer checks and installs everything automatically. Here is the full dependency list:

System packages (installed automatically via your distro's package manager):

Dependency	Purpose
Python 3.10+	Runtime
python3-venv	Isolated Python environment
lm-sensors	Populates /sys/class/hwmon for CPU temperature
XCB cursor libs (libxcb-cursor0 / xcb-util-cursor)	Required by PyQt6 on X11

NVIDIA driver — checked separately. The installer prints distro-specific install instructions if the driver is missing. GPU gauges (temperature, fan, VRAM) require the driver for NVIDIA; AMD and Intel GPUs are read via sysfs without any driver installation.

GPU backends: NVIDIA (pynvml, direct NVML — no nvidia-smi subprocess), AMD (amdgpu sysfs hwmon — kernel driver, no extra install), Intel (xe/i915 sysfs hwmon). The backend is auto-detected at startup or can be forced in the Settings sidebar. If no GPU is detected, all three GPU gauges show —.

Python libraries (installed automatically into a venv):

Library	Purpose
PyQt6	GUI framework
psutil	CPU temperature, CPU usage, RAM usage
nvidia-ml-py (pynvml)	GPU metrics via direct NVML calls — no nvidia-smi subprocess
PyYAML	Config file read/write

Supported package managers: apt (Debian/Ubuntu), dnf (Fedora/RHEL), pacman (Arch), zypper (openSUSE).

Install

Prerequisites

Install these system packages once before the first run (needed by PyQt6 on X11):

Distro	Command
Ubuntu / Debian	sudo apt install lm-sensors libxcb-cursor0 libxcb-xinerama0
Fedora / RHEL	sudo dnf install lm_sensors xcb-util-cursor
Arch	sudo pacman -S lm_sensors xcb-util-cursor
openSUSE	sudo zypper install lm-sensors xcb-util-cursor

NVIDIA users: GPU gauges require the proprietary NVIDIA driver. Without it the three GPU gauges show — but everything else works fine.

Install

pipx install thermalcanary
thermalcanary

Thermal Canary runs entirely as your user — no root needed at runtime.

On first launch, it automatically installs the app grid icon and sets up autostart on login (8-second delay to let the desktop session initialize). No extra commands needed.

Migrating from a previous bash install.sh install

# Remove old install.sh files
rm -rf ~/.local/share/thermalcanary
rm -f ~/.config/autostart/thermalcanary.desktop
rm -f ~/.local/share/applications/thermalcanary.desktop

# Install fresh
pipx install thermalcanary
thermalcanary

Installed file layout

Path	What
~/.local/share/pipx/venvs/thermalcanary/	pipx-managed venv
~/.local/bin/thermalcanary	Entry point
~/.local/share/icons/hicolor/256x256/apps/thermalcanary.png	App icon
~/.local/share/applications/thermalcanary.desktop	App grid entry
~/.config/thermalcanary/config.yaml	User configuration (auto-saved by the app)
~/.config/autostart/thermalcanary.desktop	Autostart on login (8s delay)

Launch manually

thermalcanary

Settings sidebar

Two buttons sit in the top-right corner: ⚙ opens the settings sidebar, ✕ closes the app (with confirmation). Press Ctrl+, to toggle the sidebar from the keyboard. All changes apply live without restarting.

Section	Setting	Description
Display	Monitor	Which monitor to display on — works with any number of monitors and any orientation
Display	Set as default	Save the current monitor as the startup monitor — the app always opens here on launch
Sampling	Poll rate	Sensor poll interval (100ms – 10s)
Sampling	Smoothing	Rolling average window size (1–60 samples)
Colors	Background	Window background color
Colors	Inner circle	Gauge center fill color
Colors	Arc track	Unfilled arc track color
Colors	Tick marks	Tick mark color

The Reset to defaults button restores all colors and sampling values to factory settings while keeping your saved default monitor.

Configuration file

~/.config/thermalcanary/config.yaml is written automatically by the settings sidebar. You can also edit it by hand; changes take effect on next launch.

poll_ms:  1000     # sensor poll interval in milliseconds
smooth_n: 5        # rolling average window (number of samples)

bg_color:    "#252040"   # window background
inner_color: "#1e1a35"   # gauge inner circle
track_color: "#332e55"   # arc track (unfilled)
tick_color:  "#3d3860"   # tick marks

# screen_index and default_screen_index are set via the Settings sidebar

Autostart caveat

The autostart entry inherits $DISPLAY from the login session, falling back to :0. If the app doesn't start on login, check your display number with echo $DISPLAY and edit ~/.config/autostart/thermalcanary.desktop accordingly.

Uninstall

thermalcanary-setup --uninstall   # removes icon, desktop entry, autostart
pipx uninstall thermalcanary

Architecture

• SensorWorker runs in a QThread — all sensor reads are off the main thread
• GPU metrics use pynvml (direct NVML calls, <1ms) — never subprocess nvidia-smi which causes observer-effect CPU temperature spikes of 10–15°C
• CPU temp and usage are stabilised with a deque-based rolling average
• Config is reactive: Config(QObject) emits a signal on every change, all settings apply live
• Window runs fullscreen (showFullScreen) — no title bar, fills the entire monitor. This bypasses Mutter's WM_NORMAL_HINTS enforcement which otherwise clamps window geometry to minimumSizeHint, making maximize unreliable on short or rotated monitors
• Monitor switching uses an event-driven state machine: showNormal() → wait for WindowStateChange (Mutter ack) → windowHandle().setScreen() + setGeometry() → 50ms → showFullScreen(). wmctrl is called once after first show to set _NET_WM_STATE_SKIP_TASKBAR/SKIP_PAGER (hides the window from GNOME Dash without using Qt.WindowType.Tool, which would break cross-monitor placement on Mutter)
• Monitor indices are validated against actual connected screens at startup — safe on any number of monitors
• Single-instance lock via fcntl.flock on $XDG_RUNTIME_DIR/thermalcanary.lock
• Runs entirely as the logged-in user — no root required at runtime

License

MIT — see LICENSE