ruff unsafe fixes

nwb_linkml/src/nwb_linkml/io/hdf5.py

@@ -27,7 +27,7 @@ import subprocess
 import warnings
 from pathlib import Path
 from types import ModuleType
-from typing import TYPE_CHECKING, Dict, List, Optional, Union, overload
+from typing import TYPE_CHECKING, Dict, List, Never, Optional, Union, overload
 
 import h5py
 import numpy as np
@@ -100,10 +100,7 @@ class HDF5IO:
         provider = self.make_provider()
 
         h5f = h5py.File(str(self.path))
-        if path:
+        src = h5f.get(path) if path else h5f
-            src = h5f.get(path)
-        else:
-            src = h5f
 
         # get all children of selected item
         if isinstance(src, (h5py.File, h5py.Group)):
@@ -127,7 +124,7 @@ class HDF5IO:
         else:
             return queue.completed[path].result
 
-    def write(self, path: Path):
+    def write(self, path: Path) -> Never:
         """
         Write to NWB file
 
@@ -193,7 +190,7 @@ def read_specs_as_dicts(group: h5py.Group) -> dict:
     """
     spec_dict = {}
 
-    def _read_spec(name, node):
+    def _read_spec(name, node) -> None:
 
         if isinstance(node, h5py.Dataset):
             # make containing dict if they dont exist
@@ -233,7 +230,7 @@ def find_references(h5f: h5py.File, path: str) -> List[str]:
     """
     references = []
 
-    def _find_references(name, obj: h5py.Group | h5py.Dataset):
+    def _find_references(name, obj: h5py.Group | h5py.Dataset) -> None:
         pbar.update()
         refs = []
         for attr in obj.attrs.values():
@@ -254,7 +251,6 @@ def find_references(h5f: h5py.File, path: str) -> List[str]:
 
         for ref in refs:
             assert isinstance(ref, h5py.h5r.Reference)
-            refname = h5f[ref].name
             if name == path:
                 references.append(name)
                 return
@@ -281,10 +277,7 @@ def truncate_file(source: Path, target: Optional[Path] = None, n: int = 10) -> P
     Returns:
         :class:`pathlib.Path` path of the truncated file
     """
-    if target is None:
+    target = source.parent / (source.stem + "_truncated.hdf5") if target is None else Path(target)
-        target = source.parent / (source.stem + "_truncated.hdf5")
-    else:
-        target = Path(target)
 
     source = Path(source)
 
@@ -300,9 +293,8 @@ def truncate_file(source: Path, target: Optional[Path] = None, n: int = 10) -> P
 
     to_resize = []
 
-    def _need_resizing(name: str, obj: h5py.Dataset | h5py.Group):
+    def _need_resizing(name: str, obj: h5py.Dataset | h5py.Group) -> None:
-        if isinstance(obj, h5py.Dataset):
+        if isinstance(obj, h5py.Dataset) and obj.size > n:
-            if obj.size > n:
             to_resize.append(name)
 
     print("Resizing datasets...")

nwb_linkml/src/nwb_linkml/lang_elements.py

@@ -17,7 +17,7 @@ from nwb_schema_language.datamodel.nwb_schema_pydantic import FlatDtype as FlatD
 
 FlatDType = EnumDefinition(
     name="FlatDType",
-    permissible_values=[PermissibleValue(p) for p in FlatDtype_source.__members__.keys()],
+    permissible_values=[PermissibleValue(p) for p in FlatDtype_source.__members__],
 )
 
 DTypeTypes = []

nwb_linkml/src/nwb_linkml/maps/hdf5.py

@@ -5,6 +5,7 @@ We have sort of diverged from the initial idea of a generalized map as in :class
 so we will make our own mapping class here and re-evaluate whether they should be unified later
 """
 
+import contextlib
 import datetime
 import inspect
 from abc import abstractmethod
@@ -187,10 +188,7 @@ def check_empty(obj: h5py.Group) -> bool:
         children_empty = True
 
     # if we have no attrs and we are a leaf OR our children are empty, remove us
-    if no_attrs and (no_children or children_empty):
+    return bool(no_attrs and (no_children or children_empty))
-        return True
-    else:
-        return False
 
 
 class PruneEmpty(HDF5Map):
@@ -244,10 +242,7 @@ class ResolveDynamicTable(HDF5Map):
             # we might replace DynamicTable in the future, and there isn't a stable DynamicTable
             # class to inherit from anyway because of the whole multiple versions thing
             parents = [parent.__name__ for parent in model.__mro__]
-            if "DynamicTable" in parents:
+            return "DynamicTable" in parents
-                return True
-            else:
-                return False
         else:
             return False
 
@@ -322,10 +317,7 @@ class ResolveModelGroup(HDF5Map):
     def check(
         cls, src: H5SourceItem, provider: SchemaProvider, completed: Dict[str, H5ReadResult]
     ) -> bool:
-        if "neurodata_type" in src.attrs and src.h5_type == "group":
+        return bool("neurodata_type" in src.attrs and src.h5_type == "group")
-            return True
-        else:
-            return False
 
     @classmethod
     def apply(
@@ -336,14 +328,14 @@ class ResolveModelGroup(HDF5Map):
         depends = []
         with h5py.File(src.h5f_path, "r") as h5f:
             obj = h5f.get(src.path)
-            for key, type in model.model_fields.items():
+            for key in model.model_fields.keys():
                 if key == "children":
                     res[key] = {name: resolve_hardlink(child) for name, child in obj.items()}
                     depends.extend([resolve_hardlink(child) for child in obj.values()])
                 elif key in obj.attrs:
                     res[key] = obj.attrs[key]
                     continue
-                elif key in obj.keys():
+                elif key in obj:
                     # make sure it's not empty
                     if check_empty(obj[key]):
                         continue
@@ -386,10 +378,7 @@ class ResolveDatasetAsDict(HDF5Map):
         if src.h5_type == "dataset" and "neurodata_type" not in src.attrs:
             with h5py.File(src.h5f_path, "r") as h5f:
                 obj = h5f.get(src.path)
-                if obj.shape != ():
+                return obj.shape != ()
-                    return True
-                else:
-                    return False
         else:
             return False
 
@@ -420,10 +409,7 @@ class ResolveScalars(HDF5Map):
         if src.h5_type == "dataset" and "neurodata_type" not in src.attrs:
             with h5py.File(src.h5f_path, "r") as h5f:
                 obj = h5f.get(src.path)
-                if obj.shape == ():
+                return obj.shape == ()
-                    return True
-                else:
-                    return False
         else:
             return False
 
@@ -456,10 +442,7 @@ class ResolveContainerGroups(HDF5Map):
         if src.h5_type == "group" and "neurodata_type" not in src.attrs and len(src.attrs) == 0:
             with h5py.File(src.h5f_path, "r") as h5f:
                 obj = h5f.get(src.path)
-                if len(obj.keys()) > 0:
+                return len(obj.keys()) > 0
-                    return True
-                else:
-                    return False
         else:
             return False
 
@@ -515,10 +498,7 @@ class CompletePassThrough(HDF5Map):
     ) -> bool:
         passthrough_ops = ("ResolveDynamicTable", "ResolveDatasetAsDict", "ResolveScalars")
 
-        for op in passthrough_ops:
+        return any(hasattr(src, "applied") and op in src.applied for op in passthrough_ops)
-            if hasattr(src, "applied") and op in src.applied:
-                return True
-        return False
 
     @classmethod
     def apply(
@@ -542,15 +522,7 @@ class CompleteContainerGroups(HDF5Map):
     def check(
         cls, src: H5ReadResult, provider: SchemaProvider, completed: Dict[str, H5ReadResult]
     ) -> bool:
-        if (
+        return (src.model is None and src.neurodata_type is None and src.source.h5_type == "group" and all([depend in completed for depend in src.depends]))
-            src.model is None
-            and src.neurodata_type is None
-            and src.source.h5_type == "group"
-            and all([depend in completed for depend in src.depends])
-        ):
-            return True
-        else:
-            return False
 
     @classmethod
     def apply(
@@ -574,15 +546,7 @@ class CompleteModelGroups(HDF5Map):
     def check(
         cls, src: H5ReadResult, provider: SchemaProvider, completed: Dict[str, H5ReadResult]
     ) -> bool:
-        if (
+        return (src.model is not None and src.source.h5_type == "group" and src.neurodata_type != "NWBFile" and all([depend in completed for depend in src.depends]))
-            src.model is not None
-            and src.source.h5_type == "group"
-            and src.neurodata_type != "NWBFile"
-            and all([depend in completed for depend in src.depends])
-        ):
-            return True
-        else:
-            return False
 
     @classmethod
     def apply(
@@ -639,10 +603,7 @@ class CompleteNWBFile(HDF5Map):
     def check(
         cls, src: H5ReadResult, provider: SchemaProvider, completed: Dict[str, H5ReadResult]
     ) -> bool:
-        if src.neurodata_type == "NWBFile" and all([depend in completed for depend in src.depends]):
+        return (src.neurodata_type == "NWBFile" and all([depend in completed for depend in src.depends]))
-            return True
-        else:
-            return False
 
     @classmethod
     def apply(
@@ -724,14 +685,14 @@ class ReadQueue(BaseModel):
         default_factory=list, description="Phases that have already been completed"
     )
 
-    def apply_phase(self, phase: ReadPhases, max_passes=5):
+    def apply_phase(self, phase: ReadPhases, max_passes=5) -> None:
         phase_maps = [m for m in HDF5Map.__subclasses__() if m.phase == phase]
         phase_maps = sorted(phase_maps, key=lambda x: x.priority)
 
         results = []
 
         # TODO: Thread/multiprocess this
-        for name, item in self.queue.items():
+        for item in self.queue.values():
             for op in phase_maps:
                 if op.check(item, self.provider, self.completed):
                     # Formerly there was an "exclusive" property in the maps which let potentially multiple
@@ -768,10 +729,8 @@ class ReadQueue(BaseModel):
         # delete the ones that were already completed but might have been
         # incorrectly added back in the pile
         for c in completes:
-            try:
+            with contextlib.suppress(KeyError):
                 del self.queue[c]
-            except KeyError:
-                pass
 
         # if we have nothing left in our queue, we have completed this phase
         # and prepare only ever has one pass
@@ -798,7 +757,7 @@ def flatten_hdf(h5f: h5py.File | h5py.Group, skip="specifications") -> Dict[str,
     """
     items = {}
 
-    def _itemize(name: str, obj: h5py.Dataset | h5py.Group):
+    def _itemize(name: str, obj: h5py.Dataset | h5py.Group) -> None:
         if skip in name:
             return
 

nwb_linkml/src/nwb_linkml/maps/hdmf.py

@@ -23,10 +23,7 @@ def model_from_dynamictable(group: h5py.Group, base: Optional[BaseModel] = None)
     for col in colnames:
 
         nptype = group[col].dtype
-        if nptype.type == np.void:
+        nptype = struct_from_dtype(nptype) if nptype.type == np.void else nptype.type
-            nptype = struct_from_dtype(nptype)
-        else:
-            nptype = nptype.type
 
         type_ = Optional[NDArray[Any, nptype]]
 
@@ -53,7 +50,7 @@ def dynamictable_to_model(
 
     items = {}
     for col, col_type in model.model_fields.items():
-        if col not in group.keys():
+        if col not in group:
             if col in group.attrs:
                 items[col] = group.attrs[col]
             continue

nwb_linkml/src/nwb_linkml/monkeypatch.py

@@ -3,7 +3,7 @@ Monkeypatches to external modules
 """
 
 
-def patch_npytyping_perf():
+def patch_npytyping_perf() -> None:
     """
     npytyping makes an expensive call to inspect.stack()
     that makes imports of pydantic models take ~200x longer than
@@ -43,7 +43,7 @@ def patch_npytyping_perf():
     base_meta_classes.SubscriptableMeta._get_module = new_get_module
 
 
-def patch_nptyping_warnings():
+def patch_nptyping_warnings() -> None:
     """
     nptyping shits out a bunch of numpy deprecation warnings from using
     olde aliases
@@ -53,7 +53,7 @@ def patch_nptyping_warnings():
     warnings.filterwarnings("ignore", category=DeprecationWarning, module="nptyping.*")
 
 
-def patch_schemaview():
+def patch_schemaview() -> None:
     """
     Patch schemaview to correctly resolve multiple layers of relative imports.
 
@@ -114,7 +114,7 @@ def patch_schemaview():
     SchemaView.imports_closure = imports_closure
 
 
-def apply_patches():
+def apply_patches() -> None:
     patch_npytyping_perf()
     patch_nptyping_warnings()
     patch_schemaview()

nwb_linkml/src/nwb_linkml/plot.py

@@ -55,10 +55,7 @@ class Node:
 def make_node(element: Group | Dataset, parent=None, recurse: bool = True) -> List[Node]:
     if element.neurodata_type_def is None:
         if element.name is None:
-            if element.neurodata_type_inc is None:
+            name = "anonymous" if element.neurodata_type_inc is None else element.neurodata_type_inc
-                name = "anonymous"
-            else:
-                name = element.neurodata_type_inc
         else:
             name = element.name
         id = name + "-" + str(random.randint(0, 1000))
@@ -88,7 +85,6 @@ def make_graph(namespaces: "NamespacesAdapter", recurse: bool = True) -> List[Cy
     nodes = []
     element: Namespace | Group | Dataset
     print("walking graph")
-    i = 0
     for element in namespaces.walk_types(namespaces, (Group, Dataset)):
         if element.neurodata_type_def is None:
             # skip child nodes at top level, we'll get them in recursion

nwb_linkml/src/nwb_linkml/providers/git.py

@@ -157,7 +157,7 @@ class GitRepo:
         return self._commit
 
     @commit.setter
-    def commit(self, commit: str | None):
+    def commit(self, commit: str | None) -> None:
         # setting commit as None should do nothing if we have already cloned,
         # and if we are just cloning we will always be at the most recent commit anyway
         if commit is not None:
@@ -199,7 +199,7 @@ class GitRepo:
         return res.stdout.decode("utf-8").strip()
 
     @tag.setter
-    def tag(self, tag: str):
+    def tag(self, tag: str) -> None:
         # first check that we have the most recent tags
         self._git_call("fetch", "--all", "--tags")
         self._git_call("checkout", f"tags/{tag}")
@@ -227,10 +227,7 @@ class GitRepo:
         """
         res = self._git_call("branch", "--show-current")
         branch = res.stdout.decode("utf-8").strip()
-        if not branch:
+        return not branch
-            return True
-        else:
-            return False
 
     def check(self) -> bool:
         """
@@ -262,7 +259,7 @@ class GitRepo:
         # otherwise we're good
         return True
 
-    def cleanup(self, force: bool = False):
+    def cleanup(self, force: bool = False) -> None:
         """
         Delete contents of temporary directory
 
@@ -285,7 +282,7 @@ class GitRepo:
         shutil.rmtree(str(self.temp_directory))
         self._temp_directory = None
 
-    def clone(self, force: bool = False):
+    def clone(self, force: bool = False) -> None:
         """
         Clone the repository into the temporary directory
 

nwb_linkml/src/nwb_linkml/providers/schema.py

@@ -94,10 +94,7 @@ class Provider(ABC):
     PROVIDES_CLASS: P = None
 
     def __init__(self, path: Optional[Path] = None, allow_repo: bool = True, verbose: bool = True):
-        if path is not None:
+        config = Config(cache_dir=path) if path is not None else Config()
-            config = Config(cache_dir=path)
-        else:
-            config = Config()
         self.config = config
         self.cache_dir = config.cache_dir
         self.allow_repo = allow_repo
@@ -352,8 +349,7 @@ class LinkMLProvider(Provider):
             of the build. If ``force == False`` and the schema already exist, it will be ``None``
         """
 
-        if not force:
+        if not force and all(
-            if all(
             [
                 (self.namespace_path(ns, version) / "namespace.yaml").exists()
                 for ns, version in ns_adapter.versions.items()
@@ -427,7 +423,7 @@ class LinkMLProvider(Provider):
         self, sch: SchemaDefinition, ns_adapter: adapters.NamespacesAdapter, output_file: Path
     ) -> SchemaDefinition:
         for animport in sch.imports:
-            if animport.split(".")[0] in ns_adapter.versions.keys():
+            if animport.split(".")[0] in ns_adapter.versions:
                 imported_path = (
                     self.namespace_path(
                         animport.split(".")[0], ns_adapter.versions[animport.split(".")[0]]
@@ -485,7 +481,7 @@ class PydanticProvider(Provider):
     PROVIDES = "pydantic"
 
     def __init__(self, path: Optional[Path] = None, verbose: bool = True):
-        super(PydanticProvider, self).__init__(path, verbose)
+        super().__init__(path, verbose)
         # create a metapathfinder to find module we might create
         pathfinder = EctopicModelFinder(self.path)
         sys.meta_path.append(pathfinder)
@@ -771,7 +767,7 @@ class PydanticProvider(Provider):
         return module
 
     @staticmethod
-    def _clear_package_imports():
+    def _clear_package_imports() -> None:
         """
         When using allow_repo=False, delete any already-imported
         namespaces from sys.modules that are within the nwb_linkml package
@@ -826,7 +822,7 @@ class EctopicModelFinder(MetaPathFinder):
     MODEL_STEM = "nwb_linkml.models.pydantic"
 
     def __init__(self, path: Path, *args, **kwargs):
-        super(EctopicModelFinder, self).__init__(*args, **kwargs)
+        super().__init__(*args, **kwargs)
         self.path = path
 
     def find_spec(self, fullname, path, target=None):
@@ -883,7 +879,7 @@ class SchemaProvider(Provider):
             **kwargs: passed to superclass __init__ (see :class:`.Provider` )
         """
         self.versions = versions
-        super(SchemaProvider, self).__init__(**kwargs)
+        super().__init__(**kwargs)
 
     @property
     def path(self) -> Path:

nwb_linkml/src/nwb_linkml/types/df.py

@@ -85,7 +85,7 @@ class DataFrame(BaseModel, pd.DataFrame):
         df = df.fillna(np.nan).replace([np.nan], [None])
         return df
 
-    def update_df(self):
+    def update_df(self) -> None:
         """
         Update the internal dataframe in the case that the model values are changed
         in a way that we can't detect, like appending to one of the lists.
@@ -99,7 +99,7 @@ class DataFrame(BaseModel, pd.DataFrame):
         """
         if item in ("df", "_df"):
             return self.__pydantic_private__["_df"]
-        elif item in self.model_fields.keys():
+        elif item in self.model_fields:
             return self._df[item]
         else:
             try:
@@ -108,7 +108,7 @@ class DataFrame(BaseModel, pd.DataFrame):
                 return object.__getattribute__(self, item)
 
     @model_validator(mode="after")
-    def recreate_df(self):
+    def recreate_df(self) -> None:
         """
         Remake DF when validating (eg. when updating values on assignment)
         """
@@ -137,11 +137,11 @@ def dynamictable_to_df(
         model = model_from_dynamictable(group, base)
 
     items = {}
-    for col, col_type in model.model_fields.items():
+    for col, _col_type in model.model_fields.items():
-        if col not in group.keys():
+        if col not in group:
             continue
         idxname = col + "_index"
-        if idxname in group.keys():
+        if idxname in group:
             idx = group.get(idxname)[:]
             data = group.get(col)[idx - 1]
         else:

nwb_linkml/src/nwb_linkml/types/ndarray.py

@@ -40,16 +40,10 @@ def _list_of_lists_schema(shape, array_type_handler):
     for arg, label in zip(shape_args, shape_labels):
         # which handler to use? for the first we use the actual type
         # handler, everywhere else we use the prior list handler
-        if list_schema is None:
+        inner_schema = array_type_handler if list_schema is None else list_schema
-            inner_schema = array_type_handler
-        else:
-            inner_schema = list_schema
 
         # make a label annotation, if we have one
-        if label is not None:
+        metadata = {"name": label} if label is not None else None
-            metadata = {"name": label}
-        else:
-            metadata = None
 
         # make the current level list schema, accounting for shape
         if arg == "*":
@@ -66,7 +60,8 @@ class NDArrayMeta(_NDArrayMeta, implementation="NDArray"):
     """
     Kept here to allow for hooking into metaclass, which has
     been necessary on and off as we work this class into a stable
-    state"""
+    state
+    """
 
 
 class NDArray(NPTypingType, metaclass=NDArrayMeta):

nwb_linkml/src/nwb_linkml/ui.py

@@ -45,13 +45,13 @@ class AdapterProgress:
             self.progress, title="Building Namespaces", border_style="green", padding=(2, 2)
         )
 
-    def update(self, namespace: str, **kwargs):
+    def update(self, namespace: str, **kwargs) -> None:
         self.progress.update(self.task_ids[namespace], **kwargs)
 
-    def start(self):
+    def start(self) -> None:
         self.progress.start()
 
-    def stop(self):
+    def stop(self) -> None:
         self.progress.stop()
 
     def __enter__(self) -> Live:

nwb_linkml/tests/test_adapters/test_adapter_dataset.py

@@ -10,7 +10,7 @@ def test_nothing(nwb_core_fixture):
 
 def _compare_dicts(dict1, dict2) -> bool:
     """just in one direction - that all the entries in dict1 are in dict2"""
-    assert all([dict1[k] == dict2[k] for k in dict1.keys()])
+    assert all([dict1[k] == dict2[k] for k in dict1])
     # assert all([dict1[k] == dict2[k] for k in dict2.keys()])
 
 

nwb_linkml/tests/test_generators/test_generator_pydantic.py

@@ -84,10 +84,7 @@ def imported_schema(linkml_schema, request) -> TestModules:
     Convenience fixture for testing non-core generator features without needing to re-generate and
     import every time.
     """
-    if request.param == "split":
+    split = request.param == "split"
-        split = True
-    else:
-        split = False
 
     yield generate_and_import(linkml_schema, split)
 
@@ -188,7 +185,7 @@ def test_arraylike(imported_schema):
     # check that we have gotten an NDArray annotation and its shape is correct
     array = imported_schema["core"].MainTopLevel.model_fields["array"].annotation
     args = typing.get_args(array)
-    for i, shape in enumerate(("* x, * y", "* x, * y, 3 z", "* x, * y, 3 z, 4 a")):
+    for i, _ in enumerate(("* x, * y", "* x, * y, 3 z", "* x, * y, 3 z, 4 a")):
         assert isinstance(args[i], NDArrayMeta)
         assert args[i].__args__[0].__args__
         assert args[i].__args__[1] == np.number
@@ -213,8 +210,8 @@ def test_linkml_meta(imported_schema):
     """
     meta = imported_schema["core"].LinkML_Meta
     assert "tree_root" in meta.model_fields
-    assert imported_schema["core"].MainTopLevel.linkml_meta.default.tree_root == True
+    assert imported_schema["core"].MainTopLevel.linkml_meta.default.tree_root
-    assert imported_schema["core"].OtherClass.linkml_meta.default.tree_root == False
+    assert not imported_schema["core"].OtherClass.linkml_meta.default.tree_root
 
 
 def test_skip(linkml_schema):

nwb_linkml/tests/test_maps/test_maps.py

@@ -26,11 +26,11 @@ def test_preload_maps():
         yaml.dump(hdmf_style_naming, temp_f, Dumper=Dumper)
     loaded = load_yaml(Path(temp_name))
 
-    assert "neurodata_type_def" in loaded["groups"][0].keys()
+    assert "neurodata_type_def" in loaded["groups"][0]
-    assert "data_type_def" not in loaded["groups"][0].keys()
+    assert "data_type_def" not in loaded["groups"][0]
-    assert "neurodata_type_inc" in loaded["groups"][0].keys()
+    assert "neurodata_type_inc" in loaded["groups"][0]
-    assert "data_type_inc" not in loaded["groups"][0].keys()
+    assert "data_type_inc" not in loaded["groups"][0]
-    assert "neurodata_type_inc" in loaded["groups"][0]["datasets"][0].keys()
+    assert "neurodata_type_inc" in loaded["groups"][0]["datasets"][0]
-    assert "data_type_inc" not in loaded["groups"][0]["datasets"][0].keys()
+    assert "data_type_inc" not in loaded["groups"][0]["datasets"][0]
 
     os.remove(temp_name)

nwb_linkml/tests/test_types/test_ndarray.py

@@ -88,7 +88,7 @@ def test_ndarray_serialize():
     mod_str = mod.model_dump_json()
     mod_json = json.loads(mod_str)
     for a in ("array", "shape", "dtype", "unpack_fns"):
-        assert a in mod_json["large_array"].keys()
+        assert a in mod_json["large_array"]
     assert isinstance(mod_json["large_array"]["array"], str)
     assert isinstance(mod_json["small_array"], list)
 

nwb_schema_language/src/nwb_schema_language/patches.py

@@ -83,7 +83,7 @@ patch_contact_single_multiple = Patch(
 )
 
 
-def run_patches(phase: Phases, verbose: bool = False):
+def run_patches(phase: Phases, verbose: bool = False) -> None:
     patches = [p for p in Patch.instances if p.phase == phase]
     for patch in patches:
         if verbose:
@@ -96,7 +96,7 @@ def run_patches(phase: Phases, verbose: bool = False):
             pfile.write(string)
 
 
-def main():
+def main() -> None:
     parser = argparse.ArgumentParser(description="Run patches for a given phase of code generation")
     parser.add_argument("--phase", choices=list(Phases.__members__.keys()), type=Phases)
     args = parser.parse_args()