rawpy is an easy-to-use Python wrapper for the LibRaw library. It also contains some extra functionality for finding and repairing hot/dead pixels.

API Documentation

Jupyter notebook tutorials

Sample code

Load a RAW file and save the postprocessed image using default parameters:

import rawpy
import imageio.v3 as iio

path = 'image.nef'
with rawpy.imread(path) as raw:
    rgb = raw.postprocess()
iio.imwrite('default.tiff', rgb)

Save as 16-bit linear image:

with rawpy.imread(path) as raw:
    rgb = raw.postprocess(gamma=(1,1), no_auto_bright=True, output_bps=16)
iio.imwrite('linear.tiff', rgb)

Extract embedded thumbnail/preview image and save as JPEG:

with rawpy.imread(path) as raw:
    # raises rawpy.LibRawNoThumbnailError if thumbnail missing
    # raises rawpy.LibRawUnsupportedThumbnailError if unsupported format
    thumb = raw.extract_thumb()
if thumb.format == rawpy.ThumbFormat.JPEG:
    # thumb.data is already in JPEG format, save as-is
    with open('thumb.jpeg', 'wb') as f:
        f.write(thumb.data)
elif thumb.format == rawpy.ThumbFormat.BITMAP:
    # thumb.data is an RGB numpy array, convert with imageio
    iio.imwrite('thumb.jpeg', thumb.data)

Find bad pixels using multiple RAW files and repair them:

import rawpy.enhance

paths = ['image1.nef', 'image2.nef', 'image3.nef']
bad_pixels = rawpy.enhance.find_bad_pixels(paths)

for path in paths:
    with rawpy.imread(path) as raw:
        rawpy.enhance.repair_bad_pixels(raw, bad_pixels, method='median')
        rgb = raw.postprocess()
    iio.imwrite(path + '.tiff', rgb)

Installation

Install rawpy by running:

pip install rawpy

64-bit binary wheels are provided for Linux, macOS, and Windows.

Stable vs. pre-release

All stable rawpy releases are always built against a stable LibRaw library release. You can output the dynamically loaded LibRaw version with print(rawpy.libraw_version). The version of the LibRaw headers used to compile rawpy is available as rawpy.libraw_version_compiled.

rawpy pre-releases have version numbers like 0.15.0a1 and are built against a recent LibRaw snapshot. To install a pre-release, run:

pip install --pre rawpy

Optional features

The underlying LibRaw library supports several optional features. The following table shows which PyPI binary wheels support which features.

Feature Windows macOS Linux
LCMS color engine yes yes yes
RedCine codec yes yes yes
DNG deflate codec yes yes yes
DNG lossy codec yes yes yes
Demosaic Pack GPL2 no no no
Demosaic Pack GPL3 no no no
OpenMP yes no yes

Tip: You can dynamically query supported features by inspecting the rawpy.flags dictionary.

Note on GPL demosaic packs: The GPL2 and GPL3 demosaic packs are not included as rawpy is licensed under the MIT license which is incompatible with GPL.

Installation from source on Linux/macOS

For macOS, LibRaw is built as part of the rawpy build (see external/). For Linux, you need to install the LibRaw library on your system.

On Ubuntu, you can get (an outdated) version with:

sudo apt-get install libraw-dev

Or install the latest release version from the source repository:

git clone https://github.com/LibRaw/LibRaw.git libraw
git clone https://github.com/LibRaw/LibRaw-cmake.git libraw-cmake
cd libraw
git checkout 0.20.0
cp -R ../libraw-cmake/* .
cmake .
sudo make install

After that, install rawpy using:

git clone https://github.com/letmaik/rawpy
cd rawpy
pip install numpy cython
pip install .

On Linux, if you get the error "ImportError: libraw.so: cannot open shared object file: No such file or directory" when trying to use rawpy, then do the following:

echo "/usr/local/lib" | sudo tee /etc/ld.so.conf.d/99local.conf
sudo ldconfig

The LibRaw library is installed in /usr/local/lib (if installed manually) and apparently this folder is not searched for libraries by default in some Linux distributions.

Installation from source on Windows

These instructions are experimental and support is not provided for them. Typically, there should be no need to build manually since wheels are hosted on PyPI.

You need to have Visual Studio and Python installed to build rawpy.

In a PowerShell window:

$env:PYTHON_VERSION = '3.12'
$env:PYTHON_ARCH = 'x86_64'
git clone https://github.com/letmaik/rawpy
cd rawpy
git submodule update --init
.github/scripts/build-windows.ps1

FAQ

I'm getting deadlocks when using multiprocessing on Linux

If you're experiencing deadlocks when using rawpy with Python's multiprocessing module on Linux, this is caused by an interaction between OpenMP (which is enabled in the Linux wheels) and the default fork start method used by multiprocessing.

The Problem: When a process using OpenMP is forked, OpenMP's internal thread pool state becomes inconsistent in the child process, which can cause deadlocks on subsequent calls to rawpy functions.

The Solution: Use the spawn or forkserver start method instead of fork:

import multiprocessing as mp
import rawpy

def process_raw(filename):
    with rawpy.imread(filename) as raw:
        rgb = raw.postprocess()
    return rgb

if __name__ == '__main__':
    # Set the start method to 'spawn' before creating any processes
    mp.set_start_method('spawn')
    
    with mp.Pool(processes=4) as pool:
        results = pool.map(process_raw, ['image1.nef', 'image2.nef'])

Note: The start method can only be set once per program, and must be called within an if __name__ == '__main__': guard. The spawn method creates a fresh Python interpreter process, avoiding the OpenMP thread state issue entirely.

For more information, see:

I'm getting "LibRawFileUnsupportedError: Unsupported file format or not RAW file"

This error occurs when rawpy/LibRaw cannot recognize the file as a supported RAW image format. Common causes include:

  1. The file is not actually a RAW file - Make sure you're trying to open a RAW image file (e.g., .NEF, .CR2, .ARW, .DNG, etc.) and not a regular image format like JPEG or PNG.

  2. The file is corrupted or incomplete - If the file was not fully downloaded or is damaged, LibRaw cannot read it properly.

  3. The file lacks proper headers - Some proprietary or headerless RAW formats are not supported by LibRaw. RAW files need to contain proper metadata headers that identify the camera model, sensor configuration, and other essential information for LibRaw to decode them.

  4. Unsupported camera or RAW format - While LibRaw supports a wide range of cameras, some very new or obscure camera models may not be supported yet. Check the LibRaw website for the list of supported cameras.

What you can do:

  • Verify the file is a genuine RAW file from a supported camera
  • Try opening the file with the camera manufacturer's software to confirm it's valid
  • Check if you're using the latest version of rawpy, as newer versions may support additional cameras
  • If you have a headerless or proprietary RAW format, you may need to convert it to a standard format like DNG using the camera manufacturer's tools first

Project links

Data verified by PyPI on Aug 30, 2026
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Key dates

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  • Released:
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Avatar for letmaik from gravatar.com letmaik

Credits

Author: Maik Riechert

GitHub Statistics

Data verified by PyPI on Aug 30, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

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MIT
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Requires

Python >=3.9

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Release history Release notifications | RSS feed

This release

0.27.1 This release

29 files

0.27.0

25 files

0.26.1

24 files

0.26.0

24 files

0.25.1

25 files

0.25.0

25 files

0.24.0

25 files

0.23.2

20 files

0.23.1

20 files

0.22.0

20 files

0.21.0

23 files

0.20.0

23 files

0.19.1

23 files

0.19.0

20 files

0.18.1

20 files

0.18.0

20 files

Pre-release

0.18.0a1

16 files

0.17.3

20 files

0.17.2

16 files

0.17.1

16 files

0.17.0

14 files

0.16.0

12 files

0.15.0

12 files

Pre-release

0.15.0a1

12 files

0.14.0

12 files

Pre-release

0.14.0a1

12 files

0.13.1

20 files

0.13.0

20 files

0.12.0

16 files

Pre-release

0.12.0a1

16 files

0.11.0

16 files

Pre-release

0.11.0a1

16 files

0.10.1

16 files

0.10.0

16 files

Pre-release

0.10.0a1

16 files

0.9.0

12 files

0.8.1

9 files

0.8.0

9 files

0.7.0

12 files

0.6.0

12 files

0.5.1

12 files

0.5.0

12 files

0.4.0

9 files

0.3.5

9 files

0.3.4

9 files

0.3.3

9 files

0.3.2

6 files

0.3.1

9 files

0.3.0

9 files

0.2.0

7 files

0.1.0

6 files

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