Instruct the user how to install qunfold in the case of an unsuccessful import

quapy/method/composable.py

@@ -1,9 +1,19 @@
 """This module allows the composition of quantification methods from loss functions and feature transformations. This functionality is realized through an integration of the qunfold package: https://github.com/mirkobunse/qunfold."""
 
-import qunfold
-from qunfold.quapy import QuaPyWrapper
-from qunfold.sklearn import CVClassifier
-from qunfold import (
+_import_error_message = """qunfold, the back-end of quapy.method.composable, is not properly installed.
+
+To fix this error, call:
+
+    pip install --upgrade pip setuptools wheel
+    pip install "jax[cpu]"
+    pip install "qunfold @ git+https://github.com/mirkobunse/qunfold@v0.1.4"
+"""
+
+try:
+    import qunfold
+    from qunfold.quapy import QuaPyWrapper
+    from qunfold.sklearn import CVClassifier
+    from qunfold import (
         LeastSquaresLoss, # losses
         BlobelLoss,
         EnergyLoss,
@@ -19,9 +29,9 @@ from qunfold import (
         LaplacianKernelTransformer,
         GaussianKernelTransformer,
         GaussianRFFKernelTransformer,
-)
+    )
 
-__all__ = [ # control public members, e.g., for auto-documentation in sphinx; omit QuaPyWrapper
+    __all__ = [ # control public members, e.g., for auto-documentation in sphinx; omit QuaPyWrapper
         "ComposableQuantifier",
         "CVClassifier",
         "LeastSquaresLoss",
@@ -39,7 +49,9 @@ __all__ = [ # control public members, e.g., for auto-documentation in sphinx; om
         "LaplacianKernelTransformer",
         "GaussianKernelTransformer",
         "GaussianRFFKernelTransformer",
-]
+    ]
+except ImportError as e:
+    raise ImportError(_import_error_message) from e
 
 def ComposableQuantifier(loss, transformer, **kwargs):
     """A generic quantification / unfolding method that solves a linear system of equations.