Fixed missing deps error

Author: PauBadiaM

pyproject.toml

@@ -4,7 +4,7 @@ requires = [ "hatchling" ]
 
 [project]
 name = "decoupler"
-version = "2.0.4"
+version = "2.0.5"
 description = "Python package to perform enrichment analysis from omics data."
 readme = "README.md"
 license = { file = "LICENSE" }

src/decoupler/_odeps.py

@@ -16,13 +16,13 @@ def _try_import(
 
 
 def _check_import(
-    module: types.ModuleType
+    module: types.ModuleType,
+    name: str,
 ) -> None:
     if module is None:
-        name = module.__name__
         raise ImportError(
             f"{name} is not installed. Please install it using:\n"
-            f"  pip install {name}"
+            f"  pip install {name}\n"
             "or install decoupler with full dependencies:\n"
             "  pip install 'decoupler[full]'"
         )

src/decoupler/mt/_mdt.py

@@ -50,7 +50,7 @@ def _func_mdt(
         All other keyword arguments are passed to ``xgboost.XGBRegressor``.
     %(returns)s
     """
-    _check_import(xgboost)
+    _check_import(xgboost, 'xgboost')
     nobs = mat.shape[0]
     nvar, nsrc = adj.shape
     m = f'mdt - fitting {nsrc} multivariate decision tree models (XGBoost) of {nvar} targets across {nobs} observations'

src/decoupler/mt/_udt.py

@@ -54,7 +54,7 @@ def _func_udt(
         All other keyword arguments are passed to ``xgboost.XGBRegressor``.
     %(returns)s
     """
-    _check_import(xgboost)
+    _check_import(xgboost, 'xgboost')
     nobs = mat.shape[0]
     nvar, nsrc = adj.shape
     m = f'udt - fitting {nsrc} univariate decision tree models (XGBoost) of {nvar} targets across {nobs} observations' 

src/decoupler/pl/_network.py

@@ -232,7 +232,7 @@ def network(
     """
     assert isinstance(net, pd.DataFrame), "net must be pd.DataFrame"
     assert (data is None) == (score is None), "data and score must either both be None"
-    _check_import(ig)
+    _check_import(ig, 'igraph')
     if data is None:
         srcs = net["source"].unique().astype("U")
         score = pd.DataFrame(np.ones((1, srcs.size)), index=["0"], columns=srcs)

src/decoupler/tl/_rankby_order.py

@@ -62,7 +62,7 @@ def rankby_order(
     df['name'] = adata.var_names
     # Fit
     if stat == 'dcor':
-        _check_import(dcor)
+        _check_import(dcor, 'dcor')
         f = dcor.independence.distance_correlation_t_test
     elif stat == 'pearsonr':
         f = sts.pearsonr