STY: Apply pyupgrade suggestions

fmriprep/cli/parser.py

@@ -109,9 +109,7 @@ def _slice_time_ref(value, parser):
     is_release = not any((currentv.is_devrelease, currentv.is_prerelease, currentv.is_postrelease))
 
     parser = ArgumentParser(
-        description="fMRIPrep: fMRI PREProcessing workflows v{}".format(
-            config.environment.version
-        ),
+        description=f"fMRIPrep: fMRI PREProcessing workflows v{config.environment.version}",
         formatter_class=ArgumentDefaultsHelpFormatter,
         **kwargs,
     )

fmriprep/data/__init__.py

@@ -110,7 +110,7 @@ class Loader:
     .. automethod:: cached
     """
 
-    def __init__(self, anchor: Union[str, ModuleType]):
+    def __init__(self, anchor: str | ModuleType):
         self._anchor = anchor
         self.files = files(anchor)
         self.exit_stack = ExitStack()

fmriprep/interfaces/reports.py

@@ -169,10 +169,9 @@
         if counts:
             header = '\t\t<ul class="elem-desc">'
             footer = '\t\t</ul>'
+            s = '' if n_runs == 1 else 's'
             lines = [
-                '\t\t\t<li>Task: {task_id} ({n_runs:d} run{s})</li>'.format(
-                    task_id=task_id, n_runs=n_runs, s='' if n_runs == 1 else 's'
-                )
+                f'\t\t\t<li>Task: {task_id} ({n_runs:d} run{s})</li>'
                 for task_id, n_runs in sorted(counts.items())
             ]
             tasks = '\n'.join([header] + lines + [footer])
@@ -255,20 +254,20 @@
 
         pedir = get_world_pedir(self.inputs.orientation, self.inputs.pe_direction)
 
-        dummy_scan_tmp = "{n_dum}"
+        dummy_scan_tmp = f"{n_dum}"
         if self.inputs.dummy_scans == self.inputs.algo_dummy_scans:
             dummy_scan_msg = ' '.join(
-                [dummy_scan_tmp, "(Confirmed: {n_alg} automatically detected)"]
-            ).format(n_dum=self.inputs.dummy_scans, n_alg=self.inputs.algo_dummy_scans)
+                [dummy_scan_tmp, f"(Confirmed: {self.inputs.algo_dummy_scans} automatically detected)"]
+            )
         # the number of dummy scans was specified by the user and
         # it is not equal to the number detected by the algorithm
         elif self.inputs.dummy_scans is not None:
             dummy_scan_msg = ' '.join(
-                [dummy_scan_tmp, "(Warning: {n_alg} automatically detected)"]
-            ).format(n_dum=self.inputs.dummy_scans, n_alg=self.inputs.algo_dummy_scans)
+                [dummy_scan_tmp, f"(Warning: {self.inputs.algo_dummy_scans} automatically detected)"]
+            )
         # the number of dummy scans was not specified by the user
         else:
-            dummy_scan_msg = dummy_scan_tmp.format(n_dum=self.inputs.algo_dummy_scans)
+            dummy_scan_msg = dummy_scan_tmp
 
         multiecho = "Single-echo EPI sequence."
         n_echos = len(self.inputs.echo_idx)

fmriprep/interfaces/workbench.py

@@ -282,15 +282,15 @@
         if opt in ("current_area", "new_area"):
             if not self.inputs.area_surfs and not self.inputs.area_metrics:
                 raise ValueError(
-                    "{} was set but neither area_surfs or" " area_metrics were set".format(opt)
+                    f"{opt} was set but neither area_surfs or area_metrics were set"
                 )
         if opt == "method":
             if (
                 val == "ADAP_BARY_AREA"
                 and not self.inputs.area_surfs
                 and not self.inputs.area_metrics
             ):
-                raise ValueError("Exactly one of area_surfs or area_metrics" " must be specified")
+                raise ValueError("Exactly one of area_surfs or area_metrics must be specified")
         if opt == "valid_roi_out" and val:
             # generate a filename and add it to argstr
             roi_out = self._gen_filename(self.inputs.in_file, suffix="_roi")

fmriprep/utils/asynctools.py

@@ -1,5 +1,6 @@
 import asyncio
-from typing import Callable, TypeVar
+from typing import TypeVar
+from collections.abc import Callable
 
 R = TypeVar('R')
 

fmriprep/utils/bids.py

@@ -289,7 +289,7 @@ def check_pipeline_version(pipeline_name, cvers, data_desc):
         # Very old style
         dvers = desc.get("PipelineDescription", {}).get("Version", "0+unknown")
     if Version(cvers).public != Version(dvers).public:
-        return "Previous output generated by version {} found.".format(dvers)
+        return f"Previous output generated by version {dvers} found."
 
 
 def extract_entities(file_list):

fmriprep/workflows/base.py

@@ -168,20 +168,18 @@
     from fmriprep.workflows.bold.base import init_bold_wf
 
     workflow = Workflow(name=f'sub_{subject_id}_wf')
-    workflow.__desc__ = """
+    workflow.__desc__ = f"""
 Results included in this manuscript come from preprocessing
-performed using *fMRIPrep* {fmriprep_ver}
+performed using *fMRIPrep* {config.environment.version}
 (@fmriprep1; @fmriprep2; RRID:SCR_016216),
-which is based on *Nipype* {nipype_ver}
+which is based on *Nipype* {config.environment.nipype_version}
 (@nipype1; @nipype2; RRID:SCR_002502).
 
-""".format(
-        fmriprep_ver=config.environment.version, nipype_ver=config.environment.nipype_version
-    )
-    workflow.__postdesc__ = """
+"""
+    workflow.__postdesc__ = f"""
 
 Many internal operations of *fMRIPrep* use
-*Nilearn* {nilearn_ver} [@nilearn, RRID:SCR_001362],
+*Nilearn* {NILEARN_VERSION} [@nilearn, RRID:SCR_001362],
 mostly within the functional processing workflow.
 For more details of the pipeline, see [the section corresponding
 to workflows in *fMRIPrep*'s documentation]\
@@ -199,9 +197,7 @@
 
 ### References
 
-""".format(
-        nilearn_ver=NILEARN_VERSION
-    )
+"""
 
     subject_data = collect_data(
         config.execution.layout,
@@ -219,12 +215,10 @@
     anat_only = config.workflow.anat_only
     # Make sure we always go through these two checks
     if not anat_only and not subject_data['bold']:
-        task_id = config.execution.task_id
+        task_id = config.execution.task_id or '<all>'
         raise RuntimeError(
-            "No BOLD images found for participant {} and task {}. "
-            "All workflows require BOLD images.".format(
-                subject_id, task_id if task_id else '<all>'
-            )
+            f"No BOLD images found for participant {subject_id} and "
+            f"task {task_id}. All workflows require BOLD images."
         )
 
     bold_runs = [
@@ -613,14 +607,12 @@
 
     # Append the functional section to the existing anatomical excerpt
     # That way we do not need to stream down the number of bold datasets
-    func_pre_desc = """
+    func_pre_desc = f"""
 Functional data preprocessing
 
-: For each of the {num_bold} BOLD runs found per subject (across all
-tasks and sessions), the following preprocessing was performed.
-""".format(
-        num_bold=len(bold_runs)
-    )
+: For each of the {len(bold_runs)} BOLD runs found per subject (across 
+all tasks and sessions), the following preprocessing was performed.
+"""
 
     for bold_series in bold_runs:
         bold_file = bold_series[0]