[pre-commit.ci] pre-commit autoupdate (#556)

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

Author: pre-commit-ci[bot]

.pre-commit-config.yaml

@@ -45,13 +45,13 @@ repos:
     hooks:
     -   id: sort-all
 -   repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.1.14
+    rev: v0.2.0
     hooks:
       - id: ruff-format
       - id: ruff
         args: [--unsafe-fixes]
 -   repo: https://github.com/dosisod/refurb
-    rev: v1.27.0
+    rev: v1.28.0
     hooks:
     -   id: refurb
         args: [--ignore, FURB126]
@@ -96,9 +96,8 @@ repos:
     -   id: nbqa-isort
     -   id: nbqa-mypy
         args: [--ignore-missing-imports]
-    -   id: nbqa-ruff
 -   repo: https://github.com/kynan/nbstripout
-    rev: 0.6.1
+    rev: 0.6.2
     hooks:
     -   id: nbstripout
         exclude: (docs)

docs/source/reference_guides/api.md

@@ -136,8 +136,7 @@ For example:
 
 ```python
 @pytask.mark.timeout(10, "slow", method="thread")
-def task_function():
-    ...
+def task_function(): ...
 ```
 
 Will create and attach a {class}`Mark <pytask.Mark>` object to the collected
@@ -154,8 +153,7 @@ Example for using multiple custom markers:
 ```python
 @pytask.mark.timeout(10, "slow", method="thread")
 @pytask.mark.slow
-def task_function():
-    ...
+def task_function(): ...
 ```
 
 ### Classes

docs/source/tutorials/repeating_tasks_with_different_inputs.md

@@ -268,8 +268,7 @@ the {func}`@task <pytask.task>` decorator to pass keyword arguments to the task.
 for id_, kwargs in ID_TO_KWARGS.items():
 
     @task(id=id_, kwargs=kwargs)
-    def task_create_random_data(seed, produces):
-        ...
+    def task_create_random_data(seed, produces): ...
 ```
 
 Writing a function that creates `ID_TO_KWARGS` would be even more pythonic.
@@ -289,8 +288,7 @@ ID_TO_KWARGS = create_parametrization()
 for id_, kwargs in ID_TO_KWARGS.items():
 
     @task(id=id_, kwargs=kwargs)
-    def task_create_random_data(i, produces):
-        ...
+    def task_create_random_data(i, produces): ...
 ```
 
 The {doc}`best-practices guide on parametrizations <../how_to_guides/bp_scaling_tasks>`

docs/source/tutorials/selecting_tasks.md

@@ -91,8 +91,7 @@ from pytask import task
 for i in range(2):
 
     @task
-    def task_parametrized(i=i):
-        ...
+    def task_parametrized(i=i): ...
 ```
 
 To run the task where `i = 1`, run this command.

docs/source/tutorials/skipping_tasks.md

@@ -42,8 +42,9 @@ from config import NO_LONG_RUNNING_TASKS
 
 
 @pytask.mark.skipif(NO_LONG_RUNNING_TASKS, reason="Skip long-running tasks.")
-def task_that_takes_really_long_to_run(path: Path = Path("time_intensive_product.pkl")):
-    ...
+def task_that_takes_really_long_to_run(
+    path: Path = Path("time_intensive_product.pkl"),
+): ...
 ```
 
 ## Further reading

docs/source/tutorials/write_a_task.md

@@ -117,16 +117,14 @@ from pytask import task
 
 
 @task
-def create_random_data():
-    ...
+def create_random_data(): ...
 
 
 # The id will be ".../task_data_preparation.py::create_data".
 
 
 @task(name="create_data")
-def create_random_data():
-    ...
+def create_random_data(): ...
 ```
 
 ## Customize task module names

docs_src/how_to_guides/bp_scaling_tasks_2.py

@@ -34,6 +34,6 @@ def task_prepare_data(
         path_to_processed_data: Annotated[Path, Product],
     ) -> None:
         df = pd.read_csv(path_to_input_data)
-        ...
+        # ... transform the data.
         subset = df.loc[df["subset"].eq(subset)]
         subset.to_pickle(path_to_processed_data)

docs_src/tutorials/using_a_data_catalog_5_py310.py

@@ -12,5 +12,5 @@ def task_transform_csv(
     node: Annotated[PickleNode, Product] = data_catalog["transformed_csv"],
 ) -> None:
     df = pd.read_csv(path)
-    ...
+    # ... transform the data.
     node.save(df)

docs_src/tutorials/using_a_data_catalog_5_py310_return.py

@@ -9,5 +9,5 @@ def task_transform_csv(
     path: Annotated[Path, data_catalog["csv"]],
 ) -> Annotated[pd.DataFrame, data_catalog["transformed_csv"]]:
     df = pd.read_csv(path)
-    ...
+    # ... transform the data
     return df

docs_src/tutorials/using_a_data_catalog_5_py38.py

@@ -12,5 +12,5 @@ def task_transform_csv(
     node: Annotated[PickleNode, Product] = data_catalog["transformed_csv"],
 ) -> None:
     df = pd.read_csv(path)
-    ...
+    # ... transform the data
     node.save(df)