Add a mechanism to install pyqtgraph as an option

.github/workflows/ci.yml

@@ -49,11 +49,11 @@ jobs:
         pip install -r requirements.txt
         pip install -r dev-requirements.txt
 
+    # We run the tests on the installed package, with all optional dependencies
     # Note the use of the -Wa flag to show DeprecationWarnings
-    # We run the tests on the installed package
     - name: Unit tests
       run: |
-        python setup.py install
+        python -m pip install .[diffshow]
         cd ~
         python -Wa -m pytest --pyargs skued --import-mode=importlib
     

CHANGELOG.rst

@@ -5,6 +5,7 @@ Release 2.1.5
 -------------
 
 * Releases are now automatically performed using Github Actions
+* It is now possible to install all the dependencies required to use :func:`diffshow` using the following installation option: ``pip install scikit-ued[diffshow]``.
 
 Release 2.1.4
 -------------

README.md

@@ -19,8 +19,11 @@ scikit-ued is available on PyPI; it can be installed with [pip](https://pip.pypa
 
     python -m pip install scikit-ued
 
-scikit-ued is also available on the conda-forge channel for the [conda
-package manager](https://conda.io/docs/):
+To also install optional dependencies required to view diffraction images interactively:
+
+    python -m pip install scikit-ued[diffshow]
+
+scikit-ued is also available on the conda-forge channel for the [conda package manager](https://conda.io/docs/):
 
     conda config --add channels conda-forge
     conda install scikit-ued
@@ -49,8 +52,7 @@ If you want to contribute to `scikit-ued`, take a look at [`CONTRIBUTING.md`](ht
 Related projects
 ----------------
 
-Streaming operations on NumPy arrays are available in the [npstreams
-package](https://pypi.org/pypi/npstreams).
+Streaming operations on NumPy arrays are available in the [npstreams package](https://pypi.org/pypi/npstreams).
 
 Interactive exploration of ultrafast electron diffraction data with the [iris-ued package](https://pypi.org/project/iris-ued/).
 

docs/installation.rst

@@ -18,6 +18,10 @@ You can install the latest stable version from PyPI::
 
     pip install scikit-ued
 
+To also install optional dependencies required to view diffraction images interactively with :func:`diffshow`::
+
+    python -m pip install scikit-ued[diffshow]
+
 scikit-ued is also available on the conda-forge channel for the `conda package manager <https://conda.io/docs/>`_::
 
     conda config --add channels conda-forge
@@ -31,7 +35,14 @@ repository::
 ...then installing the package with::
 
     cd scikit-ued
-    python setup.py install
+    python -m pip install .
+
+Alternatively, if you want to use :func:`diffshow`::
+
+    git clone https://github.com/LaurentRDC/scikit-ued.git
+    cd scikit-ued
+    python -m pip install .[diffshow]
+
 
 Testing
 =======

setup.py

@@ -56,6 +56,7 @@
         maintainer=AUTHOR,
         maintainer_email=AUTHOR_EMAIL,
         install_requires=REQUIREMENTS,
+        extras_require={"diffshow": ["pyqtgraph", "PyQt5"]},
         keywords="ultrafast electron scattering",
         project_urls={
             "Documentation": "https://scikit-ued.readthedocs.io/",