Python-MSS 11.0.0#
This is version 11.0.0 of Python-MSS, the ultra-fast cross-platform multiple screenshots module.
Release date: 2026-xx-x
Highlights#
API changes#
The API changes discussed in the 10.2 release notes are now implemented. (They’re not all implemented as of this writing, but should be by the time we release 11.0!)
ScreenShot attributes#
The mss.ScreenShot.raw attribute has been deprecated, and will soon be removed. Use the
mss.ScreenShot.bgra property instead.
The mss.ScreenShot.bgra and mss.ScreenShot.rgb properties now will return bytes-like
memoryview objects, rather than bytes or bytearray objects. For practical use
cases, this should not be noticeable. This change allows faster access to screenshot data, with fewer memory copies.
Python 3.9 EOL#
Python 3.9 reached end-of-life on October 31, 2025 . It is no longer receiving any updates, even security updates.
The MSS project has chosen to end support for Python 3.9, in order to focus our resources on current versions of Python.
Windows Improvements#
Improved error handling when interacting with Win32 API, which will improve diagnostics of issues.
Device contexts are now acquired and released within each grab() call, allowing monitor enumeration to work even when GetWindowDC(0) fails (#509).
Zero-Copy Screenshot Buffers (GNU/Linux, Python 3.12+)#
MSS now supports zero-copy screenshot buffers on GNU/Linux when running under Python 3.12 or later. Screenshot data can be exposed directly from operating system buffers without first being copied into a Python-owned buffer.
This removes an additional memory copy from the screenshot path and is enabled automatically with no application changes required.
In a benchmark capturing 3840×2160 screenshots as quickly as possible while forcing all pixel data to be read, processing time decreased from 22.64 ms to 18.59 ms per frame (approximately 18% faster).
Support for additional operating systems is planned.
Export Methods#
There are now convenient, easy-to-use methods to export screenshots to several popular formats: the popular PIL image library, the NumPy array format for scientific computing, and the PyTorch and TensorFlow deep learning frameworks.
Exporting to these formats was always possible from MSS, but the best way to do it hasn’t always been obvious. By providing these methods, MSS gives you tested, high-speed ways to transfer the data to these popular formats.
See the documentation section Accessing Pixel Data for details.
General Improvements#
The MSS context object will now always surface inner exceptions, even if __exit__ may also generate an exception during tear-down.