large_image_wheels

manylinux wheel files for girder/large_image dependencies.

Use

You can install from the wheels in this repository using a command like:

pip install pylibtiff openslide_python pyvips gdal mapnik glymur javabridge -f https://girder.github.io/large_image_wheels

Building

The wheels are all generated with the accompanying Dockerfile.

Building the wheels:

docker build --force-rm -t girder/large_image_wheels .

To extract the wheel files from the docker image:

mkdir -p wheels
docker run -v wheels:/opt/mount --rm --entrypoint bash girder/large_image_wheels -c 'cp /io/wheelhouse/*many* /opt/mount/.'

This will use the last recorded versions (stored in the versions.txt file). To update the versions that are used, you can do (before the docker build):

python3 -u check_versions.py > versions.txt

Results

This makes wheels for the main libraries:

GDAL
Glymur
mapnik
openslide_python
pylibmc
pylibtiff
python_javabridge
pyvips

Currently, wheels are built for Python 3.7, 3.8, 3.9, 3.10, 3.11, 3.12. Some libraries have older versions for older versions of Python that were built before support for those versions is ended.

Extras

Various related executables are bundled with the Python packages. These are added as package data in a bin directory within the main package. There is a python wrapper script exposing these in the Python binary path. For instance, gdalinfo is available from the GDAL package. It is located in the Python site-packages osgeo/bin directory. To access it directly (rather than through the wrapper script), the appropriate directory can be gleaned from Python as part of a bash command, e.g., `python -c 'import os,sys,osgeo;sys.stdout.write(os.path.dirname(osgeo.__file__))'`/bin/gdalinfo --version.

Issues

In order to find the built libraries, this modifies how pylibtiff, openslide_python, and pyvips load those libraries. The other libraries are patched in place. There is probably a better way to do this.

Example Use

This makes is more convenient to use large_image. For instance, you can create a Jupyter Notebook with large_image.

docker run --rm -p 8888:8888 jupyter/minimal-notebook bash -c 'pip install git+git://github.com/girder/large_image.git#egg=large_image[openslide,mapnik] -f https://girder.github.io/large_image_wheels matplotlib && start.sh jupyter notebook --NotebookApp.token="" --ip=0.0.0.0'

In the Jupyter interface, create a new notebook. In the first cell run:

import large_image
import requests
import matplotlib.pyplot as plt
wsi_url = 'https://data.kitware.com/api/v1/file/5899dd6d8d777f07219fcb23/download'
wsi_path = 'TCGA-02-0010-01Z-00-DX4.07de2e55-a8fe-40ee-9e98-bcb78050b9f7.svs'
open(wsi_path, 'wb').write(requests.get(wsi_url, allow_redirects=True).content)
ts = large_image.getTileSource(wsi_path)
tile_info = ts.getSingleTile(
    tile_size=dict(width=1000, height=1000),
    scale=dict(magnification=20),
    tile_position=1000
)

And in the second cell run:

plt.imshow(tile_info['tile'])

Rationale

It is an inconvenience to have to add --find-links https://girder.github.io/large_image_wheels to pip install commands to use these wheels. There are alternatives: (a) convince upstream repositories to publish wheels, or (b) publish these under unique names (e.g., large_image_dependency_gdal). None of these are perfect solutions.

Using --find-links requires modifying pip install commands. Further, if a newer non-wheel version of a package is published on pypi, it will be used in favor of the wheel unless the explicit version is used. Since this repository won't maintain old versions, this means that the wheels must be rebuilt as soon as new versions are released.

It isn't practical to produce wheels for some upstream packages. For instance, GDAL can be compiled with optional components that require licensing. A publicly published wheel can't contain such components, and, therefore, it makes sense for the package on pypi to expect that the library has been installed separately from the python module.

If these wheels were published under alternate names, they could be published to pypi. However, this would require a wheel for every supported OS or have conditionals in downstream packages' setup.py install_requires. Further, it would preclude using custom-built libraries (such as GDAL with licensed additions).

Using --find-links seems like the best choice of these options. Downstream packages can list the expected modules in install_requires. Installation doesn't become any harder for platforms without wheels, and custom-built libraries are supported.

Special use cases

GeoDjango

GeoDjango expects libgdal and libgeos_c to be in standard locations. These libraries can be installed by installing the GDAL wheel. Starting with GDAL 3.1.2, the osgeo module from these wheels exposes two values that can be used to tell Django where these libraries are located. Specifically, Django can be configured using these values::

import osgeo

django.conf.settings.configure() django.conf.settings.GDAL_LIBRARY_PATH = osgeo.GDAL_LIBRARY_PATH django.conf.settings.GEOS_LIBRARY_PATH = osgeo.GEOS_LIBRARY_PATH

Inside a Django application's settings.py file, this is somewhat simpler::

import osgeo

GDAL_LIBRARY_PATH = osgeo.GDAL_LIBRARY_PATH GEOS_LIBRARY_PATH = osgeo.GEOS_LIBRARY_PATH

Future Work

More optional libraries

Several packages (GDAL, ImageMagick, vips, and probably others) could have additional libraries added to the built wheels. As time permits, those libraries that are appropriately licensed may be gradually added. See the Dockerfile for comments on what else could be built. If there is a specific need for a library that hasn't yet been included, please create an issue for it.
More executables

A variety of executables are bundled with the wheels in appropriate bin directories. There are additional tools that could be added. If there is a specific need for an executable that hasn't been included, please create an issue for it.
Automate releases

The wheels should be published from a successful CI run rather than from a user commit.

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