Make scikitlearn optional (#73)

* make scikilearn optional

* fix ci

.github/workflows/test.yml

@@ -32,7 +32,7 @@ jobs:
         run: |
           conda install pip
           pip install -r requirements-dev.txt
-          pip install .
+          pip install ".[lasso]"
           python --version
           conda list
           pip freeze

README.md

@@ -22,6 +22,10 @@ Assuming a standard Python environment is installed on your machine (including p
 
     pip install kulprit
 
+By default Kulprit performs a forward search, if you want to use Lasso (L1 search) you need to install `scikit-learn` package. You can install it using pip:
+
+    pip install kulprit[lasso]
+
 Alternatively, if you want the bleeding edge version of the package you can install it from GitHub:
 
     pip install git+https://github.com/bambinos/kulprit.git

docs/index.rst

@@ -30,6 +30,13 @@ Assuming a standard Python environment is installed on your machine (including p
 
     pip install kulprit
 
+
+By default Kulprit performs a forward search, if you want to use Lasso (L1 search) you need to install `scikit-learn` package. You can install it using pip:
+
+.. code-block:: bash
+    
+    pip install kulprit[lasso]
+
 Alternatively, if you want the bleeding edge version of the package you can install it from GitHub:
 
 .. code-block:: bash

kulprit/projection/search_strategies.py

@@ -1,7 +1,11 @@
 """This module contains the search strategies"""
 
 import numpy as np
-from sklearn.linear_model import lasso_path
+
+try:
+    from sklearn.linear_model import lasso_path
+except ImportError:
+    pass
 from kulprit.projection.arviz_io import compute_loo
 
 

pyproject.toml

@@ -26,8 +26,11 @@ description = "Kullback-Leibler projections for Bayesian model selection."
 dependencies = [
     "arviz>=0.17.1",
     "bambi>=0.12.0",
-    "scikit-learn>=1.0.2",
-    "numba>=0.56.0",]
+    "numba>=0.56.0",
+    ]
+
+[project.optional-dependencies]
+lasso = ["scikit-learn>=1.0.2"]
 
 [tool.flit.module]
 name = "kulprit"