Move OpenCV to an optional dependency

.github/workflows/python-package.yml

@@ -27,7 +27,7 @@ jobs:
     - name: Install
       run: |
         python -m pip install --upgrade pip
-        python -m pip install .[test]
+        python -m pip install .[full,test]
     - name: Lint with flake8
       run: |
         # stop the build if there are any warnings or errors.

CHANGES.md

@@ -1,5 +1,11 @@
 # Change log
 
+## 2.0.0
+
+### Major changes
+
+- Make [OpenCV](https://pypi.org/project/opencv-python/) an optional dependency, simplifying installation requirements for forecasting from an existing model. This change requires users to specify the "full" package version at installation to get support for model fitting. [#4](https://github.com/blab/popcast/pull/4) (@huddlej)
+
 ## 1.1.0
 
 ### Features

README.md

@@ -4,8 +4,16 @@ See the methods of [Huddleston et al. 2020](https://doi.org/10.7554/eLife.60067)
 
 ## Install
 
+For a full installation with the OpenCV package that's required for model fitting, specify the "full" package dependencies.
+
+``` bash
+python -m pip install 'popcast[full]'
+```
+
+For a smaller installation that only supports forecasting with an existing model, omit the optional package dependency.
+
 ``` bash
-python3 -m pip install popcast
+python -m pip install popcast
 ```
 
 ## Usage
@@ -30,7 +38,7 @@ popcast fit \
 ### Install locally
 
 ``` bash
-python3 -m pip install ".[test]"
+python -m pip install '.[full,test]'
 ```
 
 ### Lint and run tests
@@ -52,17 +60,17 @@ cram --shell=/bin/bash tests/
 Install or upgrade publishing tools.
 
 ``` bash
-python3 -m pip install --upgrade build twine
+python -m pip install --upgrade build twine
 ```
 
 Build the distribution packages.
 
 ``` bash
-python3 -m build
+python -m build
 ```
 
 Upload the distribution packages.
 
 ``` bash
-python3 -m twine upload dist/*
+python -m twine upload dist/*
 ```

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "flit_core.buildapi"
 
 [project]
 name = "popcast"
-version = "1.1.0"
+version = "2.0.0"
 authors = [
   { name="John Huddleston", email="huddlej@gmail.com" },
 ]
@@ -20,13 +20,15 @@ classifiers = [
 
 dependencies = [
     "jellyfish >=0.8.2, ==0.*",
-    "opencv-python >=4.5, ==4.*",
     "numpy >=1.17.0, ==1.*",
     "pandas >=1.2.0, ==1.*",
     "scipy >=1.5.4, ==1.*",
 ]
 
 [project.optional-dependencies]
+full = [
+    "opencv-python >=4.5, ==4.*",
+]
 test = [
     "coverage[toml] >=5.2.1, ==5.*",
     "cram >=0.7, ==0.*",

src/popcast/__init__.py

@@ -2,4 +2,4 @@
 
 __author__ = """John Huddleston"""
 __email__ = 'huddlej@gmail.com'
-__version__ = '1.1.0'
+__version__ = '2.0.0'

src/popcast/fit.py

@@ -1,6 +1,5 @@
 """Fit a model for the given data using the requested predictors and evaluate the model by time series cross-validation.
 """
-import cv2
 import json
 import numpy as np
 import pandas as pd
@@ -418,6 +417,12 @@ def _fit(self, coefficients, X, y, use_l1_penalty=True, calculate_optimal_distan
             error between estimated values using the given coefficients and
             input data and the observed values
         """
+        try:
+            import cv2
+        except ImportError:
+            print("Failed to import cv2 package required for model fitting. Install popcast with OpenCV using \"python -m pip install 'popcast[full]'\".", file=sys.stderr)
+            sys.exit(1)
+
         # Estimate target values.
         y_hat = self.predict(X, coefficients)