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Terminal dashboard for ports, processes, and Docker containers

Project description

whosat

A terminal dashboard for ports, processes, and Docker containers.
Like htop but focused on network ports.

PyPI Python License


What is whosat?

whosat is a terminal-based system monitor that answers one question: "who's sitting on that port?"

It scans all listening ports on your machine, groups them by process, enriches them with CPU/memory stats, and displays everything in a rich interactive TUI. Think of it as htop meets netstat — you get a live, searchable, themeable dashboard showing every port, the process behind it, and what resources it's consuming.

Whether you're debugging a port conflict, hunting down a runaway process, or just want a quick overview of what's running on your system — whosat gives you the answer in one command.

whosat screenshot

Install

pip install whosat

With Docker support:

pip install 'whosat[docker]'

Usage

TUI Dashboard

whosat

Launch the full interactive TUI — live-updating, searchable, themeable.

CLI One-liners

# What's on port 3000?
whosat 3000

# Kill whatever is on port 8080 (finds parent process, kills the tree)
whosat kill 8080

# Force kill without confirmation
whosat kill 8080 --force

# List all ports in a table
whosat ls

# Sort by CPU usage, descending
whosat ls --sort cpu --desc

# JSON output — pipe to jq, use in scripts
whosat --json
whosat 3000 --json
whosat ls --json

Examples

$ whosat 8880
🐍 :8880 → uvicorn (pid 7218)  TCP/0.0.0.0  [ONLINE]  cpu 0.1%  mem 1.0 GB  up 5h 8m  user adwitiya

$ whosat ls
PORT    NAME             PID  PROTO  IP           STATUS     CPU     MEM     UPTIME
22      🔒 sshd            -  TCP    0.0.0.0      ● ONLINE     -       -     -
3000    📗 node        12847  TCP    0.0.0.0      ● ONLINE  0.2%  115 MB     2h 8m
5432    🐘 postgres     1234  TCP    127.0.0.1    ● ONLINE  0.0%   42 MB     3d 2h
8880    🐍 uvicorn      7218  TCP    0.0.0.0      ● ONLINE  0.1%  1.0 GB    5h 8m

$ whosat kill 8000
🐍 python3 (pid 96365) on port 8000
Worker pid 96365 is a child of uvicorn (pid 96363)
Kill uvicorn (pid 96363)? [y/N] y
Sent SIGTERM to uvicorn (pid 96363)

Features

  • CLI Powerwhosat 3000 for instant port lookup, whosat kill 3000 to free a port, whosat ls for a quick table, --json for scripting
  • Smart Kill — Detects parent processes (uvicorn master, node supervisor) and kills the whole tree
  • Port Conflict Detection — Warns about multiple PIDs on the same port or mixed bind addresses
  • Port & Process Monitoring — See all listening ports with owning processes, CPU/memory usage, and uptime
  • Memory View — System-wide process memory usage with GPU memory tracking (NVIDIA)
  • Docker Integration — Optional container monitoring alongside system processes
  • Group & Flat Views — Group processes by name or view as a flat list
  • Detail Panel — Expand any process to see full network info, open ports, resource usage, and CPU sparkline
  • Actions — Ping, curl, and kill processes directly from the TUI
  • Live Refresh — Configurable auto-refresh (15s / 30s / 1m / 2m / off)
  • Theming — 6 built-in themes (matrix, nord, dracula, tokyo-night, gruvbox, solarized)
  • Search & Filter — Search by process name, port, or IP; filter by scope (system / docker)
  • Keyboard Driven — Full keyboard navigation
  • Cross-platform — Linux, macOS, and WSL2

Keyboard Shortcuts

Key Action
1 / 2 Switch to Ports / Memory view
Up / Down Navigate rows
Enter Expand/collapse row + open detail panel
Esc Close detail panel / modal / clear search
/ Focus search
R Refresh data
G Toggle group/flat view
K Kill selected process
S Cycle scope (ALL / SYS / DOCKER)
T Cycle theme
Y Copy IP:PORT to clipboard
Q Quit

Configuration

On first run, whosat creates ~/.whosat/config.toml with default categories and settings.

theme = "matrix"
refresh_interval = 30

[[categories]]
name = "python"
icon = "snake"
section = "System"
match = ["python3", "python", "uvicorn", "gunicorn", "celery"]

# Add your own:
# [[port_names]]
# port = 8020
# name = "My App"
# icon = "robot"

Requirements

  • Python 3.10+
  • Linux, macOS, or WSL2
  • Optional: Docker SDK for container monitoring
  • Optional: NVIDIA GPU for GPU memory tracking in memory view

License

MIT

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