FastGrab

April 25, 2026 · View on GitHub

Fastgrab is an opensouce high frame rate screen capture package. A typical capture frame rate at a resolution of 1080p on a modern machine is ~60 fps. There are several other such packages in the wild that are opensource as well, but none of them is as fast or provides a simple way of obtaining the captures image as a numpy array out of the box. The default behavior of fastgrab is to provide the user with the image as a numpy array. Beyond that the user is free to manipulate the image since the pixel data is accessible via a fast and flexible array, i.e a numpy array.

Typical capture frame rate on a modern machine

resolutionfps
360p> 800
720p260
1080p200
4K20

Usage example

  from fastgrab import screenshot
  # take a full screen screenshot
  img = screenshot.Screenshot().capture()
  # >> img is a numpy ndarray, do whatever you want with it
  # (optional)
  # e.g it can be displayed with matplotlib (install matplotlib first)
  from matplotlib import pyplot as plt
  plt.imshow(img[:, :, 0:3], interpolation='none', cmap='Greys_r')
  plt.show()

Getting Started

Fastgrab was initially developed in 2016 as part of an aimbot (for quake live). It supports Linux (X11 via a libX11 C extension; Wayland via the wlr-screencopy-v1 protocol behind the [wayland] extra), Windows 10/11 (Win32 BitBlt via ctypes), and macOS (CoreGraphics CGDisplayCreateImage via ctypes). The plain pip install fastgrab works on all three platforms; only Wayland needs an opt-in extra.

Comparison with other packages

The following comparison has been done a Intel i7-6700HQ with 16 GB ram at a 1080p resolution. fastgrab is designed to be fast and does not provide any features beyond capturing the screen, unlike the other packages mentioned in the comparison below that do many great things.

packagefps
fastgrab200
python-mss180
autopy34
pyautogui8
pyscreenshot4

to benchmark fastgrab run the script examples/benchmark.py

Prerequisites

Common to all platforms:

  • python >= 3.8 (python 2 is not supported)
  • Numpy >= 1.15 (auto-installed by pip)

Per-platform extras:

  • Linux/X11: gcc >= 4.8.5, X11 >= 1.20 (system package: libx11-dev for build; libX11 and libgomp1 at runtime).
  • Linux/Wayland: a wlroots-based compositor (Sway, Hyprland, river, niri, cage) for the no-prompt path; the [wayland] extra (pip install fastgrab[wayland]) pulls in pywayland.
  • Windows 10/11: nothing beyond Python + numpy. Capture goes through GDI BitBlt via ctypes.
  • macOS: nothing beyond Python + numpy. macOS 10.15+ requires Screen Recording permission for the running app (System Settings → Privacy & Security).

note that fastgrab could work with lower versions but I have not tested it (and probaby will not).

Installing

Fastgrab can be installed in several ways:

pip install fastgrab

pip install git+https://github.com/mherkazandjian/fastgrab.git

git clone https://github.com/mherkazandjian/fastgrab.git
cd fastgrab
pip install .

Running the tests

The canonical way to run the test suite is through the project's docker compose setup, which bundles Xvfb, libX11 and the build toolchain so tests are reproducible regardless of the host:

make test docker=1

which is equivalent to

docker compose run --rm test

If you have pytest, numpy, python-xlib and an X server (or xvfb-run) available on the host, the suite also runs directly:

make test

The Makefile exposes build, install, dev (a virtual desktop on localhost:5901 over VNC), benchmark, lock and clean targets — run make with no arguments for the help listing.

Contributing

Submit a pull request or create an issue if you find any bugs.

Any help/pull requests are welcome. The default wheel must stay dependency-light; additional backends or features ship as opt-in pip extras (pip install fastgrab[<extra>]) when they have non-trivial runtime deps. Open follow-ups include:

  • xdg-desktop-portal + PipeWire fallback for GNOME/KDE Wayland (currently stubbed behind the [wayland-portal] extra)
  • macOS ScreenCaptureKit backend for Apple-Silicon-era systems
  • Multi-monitor capture across all backends

Authors

License

This project is licensed under GPLv3

Acknowledgments