Welcome to paquo
👋, a library for interacting with QuPath
from Python.
paquo
's goal is to provide a pythonic interface to important features of
QuPath, and to make creating and working with QuPath projects intuitive for
Python programmers.
We strive to make your lives as easy as possible: If paquo
is not pythonic,
unintuitive, slow or if its documentation is confusing, it's a bug in
paquo
. Feel free to report any issues or feature requests in the issue
tracker!
Development
happens on GitHub
You can find paquo
's documentation at
paquo.readthedocs.io ❤️
paquo's stable releases can be installed via pip
:
pip install paquo
or via conda
:
conda install -c conda-forge paquo
After installing, paquo requires a QuPath installation to run. To get QuPath follow the installation instructions. If you choose the default installation paths paquo should autodetect your QuPath.
Or you can run the following command to download a specific version of QuPath
to a location on your machine. Follow the printed instructions to configure
paquo to use that version. Currently, paquo supports every version of QuPath from
0.2.0
to the most recent. (We even support older 0.2.0-mX
versions but no guarantees).
> paquo get_qupath --install-path "/some/path/on/your/machine" 0.5.0
# downloading: https://github.com/qupath/qupath/releases/download/v0.5.0/QuPath-0.4.3-Linux.tar.xz
# progress ................... OK
# extracting: [...]/QuPath-0.5.0-Linux.tar.xz
# available at: /some/path/on/your/machine/QuPath-0.5.0
#
# use via environment variable:
# $ export PAQUO_QUPATH_DIR=/some/path/on/your/machine/QuPath-0.5.0
#
# use via .paquo.toml config file:
# qupath_dir="/some/path/on/your/machine/QuPath-0.5.0"
/some/path/on/your/machine/QuPath-0.5.0
- Install conda and git
- Clone paquo
git clone https://github.com/bayer-science-for-a-better-life/paquo.git
- Run
conda env create -f environment.devenv.yaml
- Activate the environment
conda activate paquo
Note that in this environment paquo
is already installed in development mode,
so go ahead and hack.
- Please follow pep-8 conventions but:
- We allow 120 character long lines (try anyway to keep them short)
- Please use numpy docstrings.
- When contributing code, please try to use Pull Requests.
- tests go hand in hand with modules on
tests
packages at the same level. We usepytest
.
You can set up your IDE to help you to adhere to these guidelines.
(Santi is happy to help you to set up pycharm in 5 minutes)
Build with love by Andreas Poehlmann and Santi Villalba from the Machine Learning Research group at Bayer. In collaboration with the Pathology Lab 2 and the Mechanistic and Toxicologic Pathology group.
paquo
: copyright 2020 Bayer AG, licensed under GPL-3.0