@@ -91,7 +91,7 @@ jobs:
 strategy:
 matrix:
 os: ['ubuntu-20.04']
-python-version: [3.7, 3.8, 3.9, "3.10"]
+python-version: [3.8, 3.9, "3.10"]
 check: ['test']
 pip-flags: ['']
 depends: ['REQUIREMENTS']

@@ -1,14 +1,18 @@
 # See https://pre-commit.com for more information
 # See https://pre-commit.com/hooks.html for more hooks
 repos:
-- repo: https://.com/pre-commit/pre-commit-hooks
+- repo: https://.com/pre-commit/pre-commit-hooks
 rev: v4.4.0
 hooks:
-- id: trailing-whitespace
-- id: end-of-file-fixer
-- id: check-yaml
-- id: check-added-large-files
-- repo: https://.com/psf/black
+- id: trailing-whitespace
+- id: end-of-file-fixer
+- id: check-yaml
+- id: check-added-large-files
+- repo: https://.com/psf/black
 rev: 23.3.0
 hooks:
-- id: black
+- id: black
+- repo: https://.com/codespell-project/codespell
+rev: v2.2.5
+hooks:
+- id: codespell

@@ -1,5 +1,3 @@
-# emacs: -*- coding: utf-8; mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
-# vi: set fileencoding=utf-8 ft=python sts=4 ts=4 sw=4 et:
 #
 # nipype documentation build configuration file, created by
 # sphinx-quickstart on Mon Jul 20 12:30:18 2009.
@@ -151,8 +149,8 @@
 master_doc = "index"
 
 # General information about the project.
-project = u"nipype"
-copyright = u"2009-21, Neuroimaging in Python team"
+project = "nipype"
+copyright = "2009-21, Neuroimaging in Python team"
 
 # The version info for the project you're documenting, acts as replacement for
 # |version| and |release|, also used in various other places throughout the

@@ -1,4 +1,3 @@
-# -*- coding: utf-8 -*-
 # emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
 # vi: set ft=python sts=4 ts=4 sw=4 et:
 """
@@ -26,14 +25,14 @@
 import faulthandler
 
 faulthandler.enable()
-except (ImportError, IOError) as e:
+except (ImportError, OSError) as e:
 pass
 
 config = NipypeConfig()
 logging = Logging(config)
 
 
-class NipypeTester(object):
+class NipypeTester:
 def __call__(self, doctests=True, parallel=False):
 try:
 import pytest

@@ -1,4 +1,3 @@
-# -*- coding: utf-8 -*-
 # emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
 # vi: set ft=python sts=4 ts=4 sw=4 et:
 """

@@ -1,4 +1,3 @@
-# -*- coding: utf-8 -*-
 # emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
 # vi: set ft=python sts=4 ts=4 sw=4 et:
 """
@@ -150,7 +149,7 @@ class ComputeDVARS(BaseInterface):
 
 def __init__(self, **inputs):
 self._results = {}
-super(ComputeDVARS, self).__init__(**inputs)
+super().__init__(**inputs)
 
 def _gen_fname(self, suffix, ext=None):
 fname, in_ext = op.splitext(op.basename(self.inputs.in_file))
@@ -165,7 +164,7 @@ def _gen_fname(self, suffix, ext=None):
 if ext.startswith("."):
 ext = ext[1:]
 
-return op.abspath("{}_{}.{}".format(fname, suffix, ext))
+return op.abspath(f"{fname}_{suffix}.{ext}")
 
 def _run_interface(self, runtime):
 dvars = compute_dvars(
@@ -466,12 +465,12 @@ class CompCorInputSpec(BaseInterfaceInputSpec):
 "cosine",
 False,
 usedefault=True,
-desc="Detrend time series prior to component " "extraction",
+desc="Detrend time series prior to component extraction",
 )
 use_regress_poly = traits.Bool(
 deprecated="0.15.0",
 new_name="pre_filter",
-desc=("use polynomial regression " "pre-component extraction"),
+desc=("use polynomial regression pre-component extraction"),
 )
 regress_poly_degree = traits.Range(
 low=1, value=1, usedefault=True, desc="the degree polynomial to use"
@@ -584,7 +583,7 @@ class CompCor(SimpleInterface):
 
 def __init__(self, *args, **kwargs):
 """exactly the same as compcor except the header"""
-super(CompCor, self).__init__(*args, **kwargs)
+super().__init__(*args, **kwargs)
 self._header = "CompCor"
 
 def _run_interface(self, runtime):
@@ -713,7 +712,7 @@ def _run_interface(self, runtime):
 self.inputs.pre_filter
 ]
 ncols = filter_basis.shape[1] if filter_basis.size > 0 else 0
-header = ["{}{:02d}".format(ftype, i) for i in range(ncols)]
+header = [f"{ftype}{i:02d}" for i in range(ncols)]
 if skip_vols:
 old_basis = filter_basis
 # nrows defined above
@@ -724,7 +723,7 @@ def _run_interface(self, runtime):
 filter_basis[skip_vols:, :ncols] = old_basis
 filter_basis[:skip_vols, -skip_vols:] = np.eye(skip_vols)
 header.extend(
-["NonSteadyStateOutlier{:02d}".format(i) for i in range(skip_vols)]
+[f"NonSteadyStateOutlier{i:02d}" for i in range(skip_vols)]
 )
 np.savetxt(
 self._results["pre_filter_file"],
@@ -747,7 +746,7 @@ def _run_interface(self, runtime):
 not_retained = np.where(np.logical_not(metadata["retained"]))
 components_names[retained] = components_header
 components_names[not_retained] = [
-"dropped{}".format(i) for i in range(len(not_retained[0]))
+f"dropped{i}" for i in range(len(not_retained[0]))
 ]
 with open(self._results["metadata_file"], "w") as f:
 f.write("\t".join(["component"] + list(metadata.keys())) + "\n")
@@ -768,7 +767,7 @@ def _make_headers(self, num_col):
 if isdefined(self.inputs.header_prefix)
 else self._header
 )
-headers = ["{}{:02d}".format(header, i) for i in range(num_col)]
+headers = [f"{header}{i:02d}" for i in range(num_col)]
 return headers
 
 
@@ -781,7 +780,7 @@ class ACompCor(CompCor):
 
 def __init__(self, *args, **kwargs):
 """exactly the same as compcor except the header"""
-super(ACompCor, self).__init__(*args, **kwargs)
+super().__init__(*args, **kwargs)
 self._header = "aCompCor"
 
 
@@ -807,7 +806,7 @@ class TCompCorInputSpec(CompCorInputSpec):
 class TCompCorOutputSpec(CompCorOutputSpec):
 # and all the fields in CompCorOutputSpec
 high_variance_masks = OutputMultiPath(
-File(exists=True), desc=(("voxels exceeding the variance" " threshold"))
+File(exists=True), desc=("voxels exceeding the variance threshold")
 )
 
 
@@ -832,7 +831,7 @@ class TCompCor(CompCor):
 
 def __init__(self, *args, **kwargs):
 """exactly the same as compcor except the header"""
-super(TCompCor, self).__init__(*args, **kwargs)
+super().__init__(*args, **kwargs)
 self._header = "tCompCor"
 self._mask_files = []
 
@@ -854,10 +853,10 @@ def _process_masks(self, mask_images, timeseries=None):
 out_image = nb.Nifti1Image(mask_data, affine=img.affine, header=img.header)
 
 # save mask
-mask_file = os.path.abspath("mask_{:03d}.nii.gz".format(i))
+mask_file = os.path.abspath(f"mask_{i:03d}.nii.gz")
 out_image.to_filename(mask_file)
 IFLOGGER.debug(
-"tCompcor computed and saved mask of shape %s to " "mask_file %s",
+"tCompcor computed and saved mask of shape %s to mask_file %s",
 str(mask.shape),
 mask_file,
 )
@@ -866,7 +865,7 @@ def _process_masks(self, mask_images, timeseries=None):
 return out_images
 
 def _list_outputs(self):
-outputs = super(TCompCor, self)._list_outputs()
+outputs = super()._list_outputs()
 outputs["high_variance_masks"] = self._mask_files
 return outputs
 
@@ -1136,7 +1135,7 @@ def plot_confound(tseries, figsize, name, units=None, series_tr=None, normalize=
 
 xlabel = "Frame #"
 if series_tr is not None:
-xlabel = "Frame # ({} sec TR)".format(series_tr)
+xlabel = f"Frame # ({series_tr} sec TR)"
 ax.set_xlabel(xlabel)
 ylim = ax.get_ylim()
 
@@ -1280,19 +1279,15 @@ def combine_mask_files(mask_files, mask_method=None, mask_index=None):
 mask_index = 0
 else:
 raise ValueError(
-(
-"When more than one mask file is provided, "
-"one of merge_method or mask_index must be "
-"set"
-)
+"When more than one mask file is provided, "
+"one of merge_method or mask_index must be "
+"set"
 )
 if mask_index < len(mask_files):
 mask = nb.load(mask_files[mask_index])
 return [mask]
 raise ValueError(
-("mask_index {0} must be less than number of mask " "files {1}").format(
-mask_index, len(mask_files)
-)
+f"mask_index {mask_index} must be less than number of mask files {len(mask_files)}"
 )
 masks = []
 if mask_method == "none":

@@ -1,4 +1,3 @@
-# -*- coding: utf-8 -*-
 import os
 from functools import lru_cache
 import numpy as np