Skip to main content

PyVisionAuto: Cross-platform desktop automation toolkit with visual image matching, mouse/keyboard control, and screen recording

Project description

PyVisionAuto

PyPI version Python Platform

PyVisionAuto is an end-to-end desktop automation toolkit. It is centered on visual image matching and also includes screen recording, mouse automation, and keyboard automation capabilities.

Runtime screenshot

Highlighted match region during runtime:

PyVisionAuto runtime screenshot with highlighted region

Scope

  • Linux (X11 session) and Windows
  • Real physical display required

Install

pip install pyvisionauto

Main APIs

  • Screen.find(image, confidence=None, region=None)
  • Screen.wait(image, timeout=10, confidence=None, region=None)
  • Screen.click(image, timeout=10, confidence=None, button="left", region=None)
  • Screen.wait_vanish(image, timeout=10, confidence=None, region=None)
  • Screen.click_and_wait_vanish(image, timeout=10, confidence=None, region=None)
  • Screen.activate_window(title_substring)
  • Screen.region(x, y, w, h) for region-scoped operations
  • MatchHandle.highlight().click() for fluent chaining
  • Input.type_text(text), Input.press(key), Input.hotkey(*keys)
  • Recorder.start(output_file, fps=15), Recorder.stop()

System dependencies

Linux

  • python3-tk — Required for border overlay highlight
  • xdotool — Preferred for window activation
  • wmctrl — Fallback for window activation
  • ffmpeg — Required for screen recording; install via sudo apt install ffmpeg

Windows

  • tkinter — Bundled with most Python installations
  • ffmpeg — Required for screen recording; download from ffmpeg.org, extract archive, and add the bin folder to system PATH

Verify ffmpeg installation

# Check if ffmpeg is installed and accessible
ffmpeg -version

Note: Screen recording (via Recorder API) requires ffmpeg. On Linux, it uses x11grab codec; on Windows, it uses gdigrab codec. Both are built into ffmpeg by default.

Quick start

Basic usage: Find and click

from pyvisionauto import Screen

screen = Screen()
# Wait for image to appear on screen, highlight it, then click
screen.wait("login_button.png", timeout=10).highlight().click()

Advanced example: Record automation with screen capture

This example demonstrates screen recording combined with visual automation:

from pyvisionauto import Screen, Recorder
from pathlib import Path

screen = Screen()
recorder = Recorder()

recorder.start(output_file=Path("automation_demo.mp4"))
try:
    screen.activate_window("Calculator")
    screen.wait("button_1.png", timeout=10).highlight().click()
    screen.click("button_plus.png", timeout=5)
    screen.type_text("5")
    screen.wait("button_equals.png", timeout=5).highlight().click()
    screen.wait("result_7.png", timeout=3).highlight()
finally:
    recorder.stop()

Activate a window before matching

screen.activate_window("Calculator")
screen.click("button.png")

Platform differences

Feature Linux Windows
Screen capture & template matching Supported Supported
Mouse / keyboard automation Supported Supported
Highlight overlay Supported Supported
Window activation xdotool / wmctrl pyautogui (pygetwindow)
Screen recording ffmpeg + x11grab ffmpeg + gdigrab

Screen recording requires ffmpeg installed and added to system PATH. Linux uses x11grab, Windows uses gdigrab.

Window focus on Linux (X11)

On X11 systems, mouse clicks alone do not automatically change keyboard focus. The window manager only reassigns focus in response to real hardware events or explicit window activation requests. This means:

  • click() moves the cursor to the correct coordinates and clicks, but the keyboard focus stays wherever it was before.
  • Any subsequent keyboard action (press(), type_text(), hotkeys) is delivered to whichever window currently has focus — which may not be the window you just clicked.

Rule of thumb: always call activate_window() before any keyboard action, targeting the exact window that should receive it.

Use xdotool to find the precise window name while the application is running:

xdotool search --name "" 2>/dev/null | while read id; do
    printf "ID=%-12s %s\n" "$id" "$(xdotool getwindowname "$id" 2>/dev/null)"
done

Pick the shortest substring that uniquely identifies the target window and use it in activate_window().

Main window vs. dialogs

When a modal dialog is open, activate the dialog directly — do not activate the main window and rely on the WM to forward focus:

from pyvisionauto import Screen

screen = Screen()

# --- Interacting with a dialog ---
# 1. Wait for the dialog image to appear and click it
screen.wait("open_project_dialog.png", timeout=30).click()
# 2. Activate the dialog window so keyboard input goes to it
screen.activate_window("Open Project")   # activate the dialog, not the main window
# 3. Now keyboard actions are reliably delivered to the dialog
screen.input.press("esc")

# --- Interacting with the main window ---
screen.activate_window("My App 2026")
screen.wait("toolbar_button.png", timeout=10).click()

Why not just activate the main window? On GNOME/Mutter, activating the main window does propagate focus to a modal child dialog — but this is WM-specific behaviour. Activating the dialog directly is explicit, portable, and not dependent on WM modal-focus rules.

highlight() and focus

highlight() launches a temporary tkinter overlay window. On some window managers this overlay can briefly steal keyboard focus. To avoid side effects:

  • Prefer .click() before .highlight(), not after — the API supports chaining in both directions.
  • Do not rely on focus being intact after .highlight() returns; call activate_window() again if keyboard actions follow.
# Safer pattern: click first, highlight after (for visual feedback only)
screen.wait("button.png", timeout=10).click().highlight()

# Risky pattern: highlight steals focus, click lands on wrong window
# screen.wait("button.png", timeout=10).highlight().click()  # avoid

Notes

  • Wayland-only and headless environments are not currently supported.
  • On Windows with high-DPI scaling, coordinate accuracy may be affected.

Acknowledgments

This project is inspired by Sikulix and built with:

  • OpenCV — Computer vision library for template matching
  • mss — Fast, efficient screen capture
  • PyAutoGUI — Cross-platform mouse and keyboard automation
  • ffmpeg — Multimedia framework for screen recording

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pyvisionauto-0.1.6.tar.gz (29.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

pyvisionauto-0.1.6-py3-none-any.whl (28.2 kB view details)

Uploaded Python 3

File details

Details for the file pyvisionauto-0.1.6.tar.gz.

File metadata

  • Download URL: pyvisionauto-0.1.6.tar.gz
  • Upload date:
  • Size: 29.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.4

File hashes

Hashes for pyvisionauto-0.1.6.tar.gz
Algorithm Hash digest
SHA256 74ff1be6f4a2043337a28cb176202388cf2fc51fa669a6a38855742378a2f450
MD5 eb1ae748c9bddf1d00a1854051e1cb37
BLAKE2b-256 5a812d6076c5da06458c68860a322ce98093fd96b03e14e9596f9006455c84e7

See more details on using hashes here.

File details

Details for the file pyvisionauto-0.1.6-py3-none-any.whl.

File metadata

  • Download URL: pyvisionauto-0.1.6-py3-none-any.whl
  • Upload date:
  • Size: 28.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.4

File hashes

Hashes for pyvisionauto-0.1.6-py3-none-any.whl
Algorithm Hash digest
SHA256 727c74a7e3d17a90a6178b35d4ca05b573495b36f48517e09fc14d5cef06c3b7
MD5 4b972c7aa53b20bd7102b525fd1550f8
BLAKE2b-256 255e1907986985b615dcfd6c1b9df63eb845a747a9977966a62d5c128899e852

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page