Auto-update pre-commit hooks

.pre-commit-config.yaml

@@ -1,6 +1,6 @@
 repos:
   - repo: https://github.com/Quantco/pre-commit-mirrors-black
-    rev: 23.1.0
+    rev: 23.3.0
     hooks:
       - id: black-conda
         args:
@@ -16,7 +16,7 @@ repos:
       - id: isort-conda
         additional_dependencies: [-c, conda-forge, toml=0.10.2]
   - repo: https://github.com/Quantco/pre-commit-mirrors-mypy
-    rev: "1.0.1"
+    rev: "1.3.0"
     hooks:
       - id: mypy-conda
         files: plateau
@@ -30,7 +30,7 @@ repos:
           - numpy=1.23
           - minimalkv=1.4.2
   - repo: https://github.com/Quantco/pre-commit-mirrors-pyupgrade
-    rev: 3.3.1
+    rev: 3.4.0
     hooks:
       - id: pyupgrade-conda
         args:
@@ -41,7 +41,7 @@ repos:
       - id: prettier-conda
         files: "\\.md$"
   - repo: https://github.com/Quantco/pre-commit-mirrors-docformatter
-    rev: 1.5.0.1
+    rev: 1.7.1
     hooks:
       - id: docformatter-conda
   - repo: https://github.com/Quantco/pre-commit-mirrors-pre-commit-hooks

plateau/core/_deprecation.py

@@ -40,8 +40,8 @@
 
 
 def deprecate_kwarg(old_arg_name, new_arg_name, mapping=None, stacklevel=2):
-    """
-    Decorator to deprecate a keyword argument of a function.
+    """Decorator to deprecate a keyword argument of a function.
+
     Parameters
     ----------
     old_arg_name : str

plateau/core/dataset.py

@@ -856,9 +856,10 @@ def create_partition_key(
 class DatasetMetadataBuilder(CopyMixin):
     """Incrementally build up a dataset.
 
-    In constrast to a :class:`plateau.core.dataset.DatasetMetadata`
-    instance, this object is mutable and may not be a full dataset (e.g.
-    partitions don't need to be fully materialised).
+    In constrast to a
+    :class: `plateau.core.dataset.DatasetMetadata`     instance, this
+        object is mutable and may not be a full dataset (e.g.
+        partitions don't need to be fully materialised).
     """
 
     def __init__(

plateau/io/dask/delayed.py

@@ -270,13 +270,13 @@ def update_dataset_from_delayed(
     factory=None,
     table_name=SINGLE_TABLE,
 ):
-    """
-    A dask.delayed graph to add and store a list of dictionaries containing
-    dataframes to a plateau dataset in store. The input should be a list
-    (or splitter pipeline) containing
-    :class:`~plateau.io_components.metapartition.MetaPartition`. If you want to use this
-    pipeline step for just deleting partitions without adding new ones you
-    have to give an empty meta partition as input (``[Metapartition(None)]``).
+    """A dask.delayed graph to add and store a list of dictionaries containing
+    dataframes to a plateau dataset in store. The input should be a list (or
+    splitter pipeline) containing
+    :class:`~plateau.io_components.metapartition.MetaPartition`. If you want to
+    use this pipeline step for just deleting partitions without adding new ones
+    you have to give an empty meta partition as input
+    (``[Metapartition(None)]``).
 
     Parameters
     ----------

plateau/io_components/metapartition.py

@@ -391,9 +391,8 @@ def from_partition(
         logical_conjunction: Optional[List[Tuple[Any, str, Any]]] = None,
         table_name: str = SINGLE_TABLE,
     ):
-        """
-        Transform a plateau :class:`~plateau.core.partition.Partition` into a
-        :class:`~plateau.io_components.metapartition.MetaPartition`.
+        """Transform a plateau :class:`~plateau.core.partition.Partition` into
+        a :class:`~plateau.io_components.metapartition.MetaPartition`.
 
         Parameters
         ----------
@@ -993,8 +992,9 @@ def build_indices(self, columns: Iterable[str]):
         columns. The indices for the passed columns are rebuilt, so exisiting
         index entries in the metapartition are overwritten.
 
-        :param columns: A list of columns from which the indices over all dataframes in the metapartition
-            are overwritten
+        :param columns: A list of columns from which the indices over
+                all dataframes in the metapartition             are
+                overwritten
         :return: self
         """
         if self.label is None:

plateau/io_components/read.py

@@ -37,10 +37,7 @@ def dispatch_metapartitions_from_factory(
     predicates: PredicatesType = None,
     dispatch_by: Optional[List[str]] = None,
 ) -> Union[Iterator[MetaPartition], Iterator[List[MetaPartition]]]:
-    """
-
-    :meta private:
-    """
+    """:meta private:"""
 
     if dispatch_by is not None and not set(dispatch_by).issubset(
         set(dataset_factory.index_columns)

plateau/serialization/_generic.py

@@ -3,13 +3,13 @@
 
 Available constants
 
-**PredicatesType** - A type describing the format of predicates which is a list of ConjuntionType
-**ConjunctionType** - A type describing a single Conjunction which is a list of literals
-**LiteralType**  - A type for a single literal
+**PredicatesType** - A type describing the format of predicates which is
+a list of ConjuntionType **ConjunctionType** - A type describing a
+single Conjunction which is a list of literals **LiteralType**  - A type
+for a single literal
 
 **LiteralValue** - A type indicating the value of a predicate literal
 
-
 :meta public:
 """
 

tests/io/dask/dataframe/test_stats.py

@@ -257,9 +257,8 @@ def test_collect_dataset_metadata_fraction_precision(store_factory):
 
 
 def test_collect_dataset_metadata_at_least_one_partition(store_factory):
-    """
-    Make sure we return at leat one partition, even if none would be returned by rounding frac * n_partitions
-    """
+    """Make sure we return at leat one partition, even if none would be
+    returned by rounding frac * n_partitions."""
     df = pd.DataFrame(data={"A": range(100), "B": range(100)})
 
     store_dataframes_as_dataset(