[pre-commit.ci] pre-commit autoupdate (#582)

* [pre-commit.ci] pre-commit autoupdate

updates:
- [github.com/astral-sh/ruff-pre-commit: v0.8.2 → v0.9.1](astral-sh/ruff-pre-commit@v0.8.2...v0.9.1)

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

.github/ISSUE_TEMPLATE/bug_report.md

@@ -20,9 +20,9 @@ A clear and concise description of what you expected to happen.
 
 **System**
 
--   OS: [e.g. Windows 10]
--   Python version [e.g. 3.9]
--   Versions of libraries involved [e.g. AnnData 0.8.0, Scirpy 0.12.0]
+- OS: [e.g. Windows 10]
+- Python version [e.g. 3.9]
+- Versions of libraries involved [e.g. AnnData 0.8.0, Scirpy 0.12.0]
 
 **Additional context**
 Add any other context about the problem here.

.github/PULL_REQUEST_TEMPLATE.md

@@ -1,5 +1,5 @@
 Closes #...
 
--   [ ] CHANGELOG.md updated
--   [ ] Tests added (For bug fixes or new features)
--   [ ] Tutorial updated (if necessary)
+- [ ] CHANGELOG.md updated
+- [ ] Tests added (For bug fixes or new features)
+- [ ] Tutorial updated (if necessary)

.pre-commit-config.yaml

@@ -12,7 +12,7 @@ repos:
       - id: prettier
         exclude: '^\.conda'
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.8.2
+    rev: v0.9.1
     hooks:
       - id: ruff
         types_or: [python, pyi, jupyter]

README.md

@@ -42,8 +42,8 @@ Please consider making a tax-deductible [donation](https://numfocus.org/donate-t
 
 Please refer to the [documentation][link-docs]. In particular, the
 
--   [Tutorial][link-tutorial], and the
--   [API documentation][link-api].
+- [Tutorial][link-tutorial], and the
+- [API documentation][link-api].
 
 ## Installation
 
@@ -88,8 +88,8 @@ See the [changelog][changelog].
 
 We are happy to assist with problems when using scirpy.
 
--   If you need help with scirpy or have questions regarding single-cell immune-cell receptor analysis in general, please join us in the [scverse discourse][scverse-discourse].
--   For bug report or feature requests, please use the [issue tracker][issue-tracker].
+- If you need help with scirpy or have questions regarding single-cell immune-cell receptor analysis in general, please join us in the [scverse discourse][scverse-discourse].
+- For bug report or feature requests, please use the [issue tracker][issue-tracker].
 
 We try to respond within two working days, however fixing bugs or implementing new features
 can take substantially longer, depending on the availability of our developers.

docs/contributing.md

@@ -90,11 +90,11 @@ Scirpy uses [hatch-vcs](https://github.com/ofek/hatch-vcs) to automaticlly retri
 
 Please write documentation for new or changed features and use-cases. This project uses [sphinx][] with the following features:
 
--   the [myst][] extension allows to write documentation in markdown/Markedly Structured Text
--   [Numpy-style docstrings][numpydoc] (through the [napoloen][numpydoc-napoleon] extension).
--   Jupyter notebooks as tutorials through [myst-nb][] (See [Tutorials with myst-nb](#tutorials-with-myst-nb-and-jupyter-notebooks))
--   [Sphinx autodoc typehints][], to automatically reference annotated input and output types
--   Citations (like {cite:p}`Virshup_2023`) can be included with [sphinxcontrib-bibtex](https://sphinxcontrib-bibtex.readthedocs.io/)
+- the [myst][] extension allows to write documentation in markdown/Markedly Structured Text
+- [Numpy-style docstrings][numpydoc] (through the [napoloen][numpydoc-napoleon] extension).
+- Jupyter notebooks as tutorials through [myst-nb][] (See [Tutorials with myst-nb](#tutorials-with-myst-nb-and-jupyter-notebooks))
+- [Sphinx autodoc typehints][], to automatically reference annotated input and output types
+- Citations (like {cite:p}`Virshup_2023`) can be included with [sphinxcontrib-bibtex](https://sphinxcontrib-bibtex.readthedocs.io/)
 
 See the [scanpy developer docs](https://scanpy.readthedocs.io/en/latest/dev/documentation.html) for more information
 on how to write documentation.
@@ -111,10 +111,10 @@ repository.
 
 #### Hints
 
--   If you refer to objects from other packages, please add an entry to `intersphinx_mapping` in `docs/conf.py`. Only
-    if you do so can sphinx automatically create a link to the external documentation.
--   If building the documentation fails because of a missing link that is outside your control, you can add an entry to
-    the `nitpick_ignore` list in `docs/conf.py`
+- If you refer to objects from other packages, please add an entry to `intersphinx_mapping` in `docs/conf.py`. Only
+  if you do so can sphinx automatically create a link to the external documentation.
+- If building the documentation fails because of a missing link that is outside your control, you can add an entry to
+  the `nitpick_ignore` list in `docs/conf.py`
 
 #### Building the docs locally
 

docs/extensions/typed_returns.py

@@ -12,7 +12,7 @@
 def _process_return(lines: Iterable[str]) -> Generator[str, None, None]:
     for line in lines:
         if m := re.fullmatch(r"(?P<param>\w+)\s+:\s+(?P<type>[\w.]+)", line):
-            yield f'-{m["param"]} (:class:`~{m["type"]}`)'
+            yield f"-{m['param']} (:class:`~{m['type']}`)"
         else:
             yield line
 

src/scirpy/io/_tracerlib/core.py

@@ -368,12 +368,12 @@ def get_summary(self):
         if not self.has_D_segment:
             V_segment = self.summary[0]
             J_segment = self.summary[1]
-            segments_string = f"V segment:\t{V_segment}\n" f"J segment:\t{J_segment}\n"
+            segments_string = f"V segment:\t{V_segment}\nJ segment:\t{J_segment}\n"
         else:
             V_segment = self.summary[0]
             D_segment = self.summary[1]
             J_segment = self.summary[2]
-            segments_string = f"V segment:\t{V_segment}\nD segment:\t{D_segment}\n" f"J segment:\t{J_segment}\n"
+            segments_string = f"V segment:\t{V_segment}\nD segment:\t{D_segment}\nJ segment:\t{J_segment}\n"
         summary_string += segments_string
         summary_string += f"ID:\t{self.identifier}\n"
         summary_string += (

src/scirpy/ir_dist/__init__.py

@@ -30,7 +30,7 @@ def TcrNeighbors(*args, **kwargs):
 
 def IrNeighbors(*args, **kwargs):
     raise RuntimeError(
-        "IrNeighbors has been removed in v0.7.0. Use either `ir_dist` " "or `sequence_dist` for that functionality. "
+        "IrNeighbors has been removed in v0.7.0. Use either `ir_dist` or `sequence_dist` for that functionality. "
     )
 
 

src/scirpy/ir_dist/_clonotype_neighbors.py

@@ -136,9 +136,9 @@ def _make_clonotype_table(self, params: DataHandler) -> tuple[Mapping, pd.DataFr
             for tmp_arm in self._receptor_arm_cols:
                 primary_is_nan = clonotypes[f"{tmp_arm}_1_{self.sequence_key}"] == "nan"
                 secondary_is_nan = clonotypes[f"{tmp_arm}_2_{self.sequence_key}"] == "nan"
-                assert not np.sum(
-                    ~secondary_is_nan[primary_is_nan]
-                ), "There must not be a secondary chain if there is no primary one"
+                assert not np.sum(~secondary_is_nan[primary_is_nan]), (
+                    "There must not be a secondary chain if there is no primary one"
+                )
 
         return cell_indices, clonotypes
 
@@ -327,7 +327,7 @@ def AND_max(a, b):
             distance_matrix_name, forward, _ = self.neighbor_finder.lookups["match_columns"]
             distance_matrix_name_reverse, _, reverse = self.neighbor_finder.lookups["match_columns"]
             if distance_matrix_name != distance_matrix_name_reverse:
-                raise ValueError("Forward and reverse lookup tablese must be defined " "on the same distance matrices.")
+                raise ValueError("Forward and reverse lookup tablese must be defined on the same distance matrices.")
             reverse_lookup_values = np.vstack(list(reverse.lookup.values()))
             reverse_lookup_keys = np.zeros(reverse.size, dtype=np.int64)
             reverse_lookup_keys[list(reverse.lookup.keys())] = np.arange(len(list(reverse.lookup.keys())))
@@ -416,7 +416,7 @@ def match_gene_segment(
             distance_matrix_name, forward, _ = self.neighbor_finder.lookups[f"{tmp_arm}_{c1}_{segment_suffix}"]
             distance_matrix_name_reverse, _, reverse = self.neighbor_finder.lookups[f"{tmp_arm}_{c2}_{segment_suffix}"]
             if distance_matrix_name != distance_matrix_name_reverse:
-                raise ValueError("Forward and reverse lookup tablese must be defined " "on the same distance matrices.")
+                raise ValueError("Forward and reverse lookup tablese must be defined on the same distance matrices.")
             empty_row = np.array([np.zeros(reverse.size, dtype=bool)])
             reverse_lookup_values = np.vstack((*reverse.lookup.values(), empty_row))
             reverse_lookup_keys = np.full(id_len, -1, dtype=np.int32)

src/scirpy/ir_dist/_util.py

@@ -282,7 +282,7 @@ def lookup(
         if reverse_lookup_table_name is not None:
             distance_matrix_name_reverse, _, reverse_lookup_table = self.lookups[reverse_lookup_table_name]
             if distance_matrix_name != distance_matrix_name_reverse:
-                raise ValueError("Forward and reverse lookup tablese must be defined " "on the same distance matrices.")
+                raise ValueError("Forward and reverse lookup tablese must be defined on the same distance matrices.")
 
         distance_matrix = self.distance_matrices[distance_matrix_name]
 

src/scirpy/pl/_clonotype_imbalance.py

@@ -84,7 +84,7 @@ def clonotype_imbalance(
     params = DataHandler(adata, airr_mod)
     if key_added not in params.adata.uns:
         sc.logging.warning(
-            "Clonotype imbalance not found." " Running `ir.tl.clonotype_imbalance` and storing under {key_added}"
+            "Clonotype imbalance not found. Running `ir.tl.clonotype_imbalance` and storing under {key_added}"
         )
 
         tl.clonotype_imbalance(

src/scirpy/tests/test_util.py

@@ -302,9 +302,7 @@ def test_layout_components(arrange_boxes, component_layout):
     try:
         layout_components(g, arrange_boxes=arrange_boxes, component_layout=component_layout)
     except ImportError:
-        warnings.warn(
-            f"The '{component_layout}' layout-test was skipped because rectangle " "packer is not installed. "
-        )
+        warnings.warn(f"The '{component_layout}' layout-test was skipped because rectangle packer is not installed. ")
 
 
 def test_translate_dna_to_protein(adata_tra):

src/scirpy/tl/_clonotypes.py

@@ -403,7 +403,7 @@ def define_clonotypes(
         # For the case of "clonotypes" we want to compute the distance automatically
         # if it doesn't exist yet. Since it's just a sparse ID matrix, this
         # should be instant.
-        logging.info("ir_dist for sequence='nt' and metric='identity' not found. " "Computing with default parameters.")  # type: ignore
+        logging.info("ir_dist for sequence='nt' and metric='identity' not found. Computing with default parameters.")  # type: ignore
         ir_dist(params, metric="identity", sequence="nt", key_added=distance_key)
 
     return define_clonotype_clusters(

src/scirpy/tl/_diversity.py

@@ -124,9 +124,7 @@ def alpha_diversity(
                 if "percentage" in kwargs:
                     diversity[k] = _dxx(tmp_counts, percentage=cast(int, kwargs.get("percentage")))
                 else:
-                    raise ValueError(
-                        "DXX requires the `percentage` keyword argument, which can " "range from 0 to 100."
-                    )
+                    raise ValueError("DXX requires the `percentage` keyword argument, which can range from 0 to 100.")
             else:
                 # make skbio an optional dependency
                 try:

src/scirpy/util/graph/__init__.py

@@ -109,7 +109,7 @@ def _get_igraph_from_adjacency(adj: csr_matrix, simplify=True):
 
     if g.vcount() != adj.shape[0]:
         logging.warning(
-            f"The constructed graph has only {g.vcount()} nodes. " "Your adjacency matrix contained redundant nodes."
+            f"The constructed graph has only {g.vcount()} nodes. Your adjacency matrix contained redundant nodes."
         )  # type: ignore
 
     if simplify:

src/scirpy/util/graph/_fr_size_aware_layout.py

@@ -101,9 +101,9 @@ def layout_fr_size_aware(
         # ensure that it is an array
         scale = np.array(scale)
 
-    assert len(origin) == len(
-        scale
-    ), f"Arguments `origin` (d={len(origin)}) and `scale` (d={len(scale)}) need to have the same number of dimensions!"
+    assert len(origin) == len(scale), (
+        f"Arguments `origin` (d={len(origin)}) and `scale` (d={len(scale)}) need to have the same number of dimensions!"
+    )
     dimensionality = len(origin)
 
     unique_nodes = _get_unique_nodes(edge_list)
@@ -114,9 +114,9 @@ def layout_fr_size_aware(
     else:
         # 1) check input dimensionality
         dimensionality_node_positions = np.array(list(node_positions.values())).shape[1]
-        assert (
-            dimensionality_node_positions == dimensionality
-        ), f"The dimensionality of values of `node_positions` (d={dimensionality_node_positions}) must match the dimensionality of `origin`/ `scale` (d={dimensionality})!"
+        assert dimensionality_node_positions == dimensionality, (
+            f"The dimensionality of values of `node_positions` (d={dimensionality_node_positions}) must match the dimensionality of `origin`/ `scale` (d={dimensionality})!"
+        )
 
         is_valid = _is_within_bbox(list(node_positions.values()), origin=origin, scale=scale)
         if not np.all(is_valid):