fix: migrate from pkg_resources.resource_filename to ``importlib_…

…resources``

Resolves: #377.

sdcflows/utils/misc.py

@@ -24,6 +24,11 @@
 import logging
 
 
+def resource_fname(module: str, path: str):
+    from importlib.resources import files
+    return str((files(module) / path).absolute())
+
+
 def front(inlist):
     """
     Pop from a list or tuple, otherwise return untouched.

sdcflows/workflows/apply/registration.py

@@ -29,10 +29,10 @@
 The target EPI is the distorted dataset (or a reference thereof).
 
 """
-from pkg_resources import resource_filename as pkgrf
 from nipype.pipeline import engine as pe
 from nipype.interfaces import utility as niu
 from niworkflows.engine.workflows import LiterateWorkflow as Workflow
+from sdcflows.utils.misc import resource_fname as pkgrf
 
 
 def init_coeff2epi_wf(

sdcflows/workflows/fit/pepolar.py

@@ -21,11 +21,11 @@
 #     https://www.nipreps.org/community/licensing/
 #
 """Datasets with multiple phase encoded directions."""
-from pkg_resources import resource_filename as _pkg_fname
 from nipype.pipeline import engine as pe
 from nipype.interfaces import utility as niu
 
 from niworkflows.engine.workflows import LiterateWorkflow as Workflow
+from sdcflows.utils.misc import resource_fname as pkgrf
 
 INPUT_FIELDS = ("metadata", "in_data")
 _PEPOLAR_DESC = """\
@@ -146,9 +146,10 @@ def init_topup_wf(
     # The core of the implementation
     # Feed the input images in LAS orientation, so FSL does not run funky reorientations
     to_las = pe.Node(ReorientImageAndMetadata(target_orientation="LAS"), name="to_las")
+
     topup = pe.Node(
         TOPUP(
-            config=_pkg_fname("sdcflows", f"data/flirtsch/b02b0{'_quick' * sloppy}.cnf")
+            config=pkgrf("sdcflows", f"data/flirtsch/b02b0{'_quick' * sloppy}.cnf")
         ),
         name="topup",
     )
@@ -332,7 +333,7 @@ def init_3dQwarp_wf(omp_nthreads=1, debug=False, name="pepolar_estimate_wf"):
 
     align_pes = pe.Node(
         Registration(
-            from_file=_pkg_fname("sdcflows", "data/translation_rigid.json"),
+            from_file=pkgrf("sdcflows", "data/translation_rigid.json"),
             output_warped_image=True,
         ),
         name="align_pes",

sdcflows/workflows/fit/syn.py

@@ -34,10 +34,11 @@
 
 
 """
-from pkg_resources import resource_filename
 from nipype.pipeline import engine as pe
 from nipype.interfaces import utility as niu
 from niworkflows.engine.workflows import LiterateWorkflow as Workflow
+from sdcflows.utils.misc import resource_fname as pkgrf
+
 
 DEFAULT_MEMORY_MIN_GB = 0.01
 INPUT_FIELDS = (
@@ -120,7 +121,6 @@ def init_syn_sdc_wf(
         Short description of the estimation method that was run.
 
     """
-    from pkg_resources import resource_filename as pkgrf
     from packaging.version import parse as parseversion, Version
     from nipype.interfaces.ants import ImageMath
     from niworkflows.interfaces.fixes import (
@@ -401,7 +401,6 @@ def init_syn_preprocessing_wf(
         the cost function of SyN.
 
     """
-    from pkg_resources import resource_filename as pkgrf
     from niworkflows.interfaces.nibabel import (
         IntensityClip,
         ApplyMask,
@@ -496,7 +495,7 @@ def init_syn_preprocessing_wf(
     )
 
     epi2anat = pe.Node(
-        Registration(from_file=resource_filename("sdcflows", "data/affine.json")),
+        Registration(from_file=pkgrf("sdcflows", "data/affine.json")),
         name="epi2anat",
         n_procs=omp_nthreads,
     )