Update pre-commit

Author: benjeffery

.pre-commit-config.yaml

@@ -1,6 +1,6 @@
 repos:
   - repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v4.4.0
+    rev: v5.0.0
     hooks:
       - id: check-merge-conflict
       - id: debug-statements
@@ -14,29 +14,29 @@ repos:
       exclude: avl
       verbose: true
   - repo: https://github.com/asottile/reorder_python_imports
-    rev: v3.9.0
+    rev: v3.14.0
     hooks:
       - id: reorder-python-imports
         args: [ --unclassifiable-application-module=_tsinfer ]
   - repo: https://github.com/asottile/pyupgrade
-    rev: v3.2.2
+    rev: v3.19.1
     hooks:
       - id: pyupgrade
         args: [ --py3-plus, --py39-plus ]
   - repo: https://github.com/psf/black
-    rev: 22.10.0
+    rev: 25.1.0
     hooks:
       - id: black
         language_version: python3
   - repo: https://github.com/asottile/blacken-docs
-    rev: v1.12.1
+    rev: 1.19.1
     hooks:
       - id: blacken-docs
         args: [--skip-errors]
         additional_dependencies: [black==22.3.0]
         language_version: python3
   - repo: https://github.com/pycqa/flake8
-    rev: 6.0.0
+    rev: 7.1.2
     hooks:
       - id: flake8
         args: [--config=.flake8]

convert_hdf5.py

@@ -1,7 +1,5 @@
-"""
-Simple script to convert input data into HDF5 format so that
-we can feed it into the C development CLI.
-"""
+# Simple script to convert input data into HDF5 format so that
+# we can feed it into the C development CLI.
 import sys
 
 import h5py

evaluation.py

@@ -1,6 +1,4 @@
-"""
-Script for statistically evaluating various aspects of tsinfer performance.
-"""
+# Script for statistically evaluating various aspects of tsinfer performance.
 import argparse
 import concurrent.futures
 import json

tests/test_variantdata.py

@@ -584,9 +584,9 @@ def test_sgkit_sample_and_site_mask(self, tmp_path):
         # Mask out a random 1/3 of sites
         variant_mask = np.zeros(ts.num_sites, dtype=bool)
         random = np.random.RandomState(42)
-        variant_mask[
-            random.choice(ts.num_sites, ts.num_sites // 3, replace=False)
-        ] = True
+        variant_mask[random.choice(ts.num_sites, ts.num_sites // 3, replace=False)] = (
+            True
+        )
         # Mask out a random 1/3 of samples
         samples_mask = np.zeros(ts.num_individuals, dtype=bool)
         samples_mask[

tsinfer/formats.py

@@ -1019,9 +1019,9 @@ def __init__(self, sequence_length=0, **kwargs):
 
         self.data.attrs["sequence_length"] = float(sequence_length)
         self.data.attrs["metadata"] = {}
-        self.data.attrs[
-            "metadata_schema"
-        ] = tskit.MetadataSchema.permissive_json().schema
+        self.data.attrs["metadata_schema"] = (
+            tskit.MetadataSchema.permissive_json().schema
+        )
         chunks = (self._chunk_size,)
         populations_group = self.data.create_group("populations")
         metadata = populations_group.create_dataset(
@@ -3615,9 +3615,9 @@ def flush_buffers(buffer_pos):
                     end_buffer[buffer_pos] = insert_pos_end
                     time_buffer[buffer_pos] = anc.time
                     focal_sites_buffer[buffer_pos] = anc.focal_sites
-                    haplotype_buffer[
-                        insert_pos_start:insert_pos_end, buffer_pos, 0
-                    ] = anc.full_haplotype[insert_pos_start:insert_pos_end]
+                    haplotype_buffer[insert_pos_start:insert_pos_end, buffer_pos, 0] = (
+                        anc.full_haplotype[insert_pos_start:insert_pos_end]
+                    )
                     buffer_pos += 1
                     if buffer_pos == buffer_length:
                         flush_buffers(buffer_length)

tsinfer/inference.py

@@ -2502,9 +2502,11 @@ def __complete_group(self, group, ancestor_ids, results):
                 group,
                 len(ancestor_ids),
                 extra_nodes,
-                sum(result.mean_traceback_size for result in results) / len(results)
-                if len(results) > 0
-                else float("nan"),
+                (
+                    sum(result.mean_traceback_size for result in results) / len(results)
+                    if len(results) > 0
+                    else float("nan")
+                ),
                 self.tree_sequence_builder.num_edges,
             )
         )

tsinfer/progress.py

@@ -91,7 +91,7 @@ def get(self, key, total):
             dynamic_ncols=True,
             smoothing=0.01,
             unit_scale=True,
-            **self.tqdm_kwargs
+            **self.tqdm_kwargs,
         )
         return self.current_instance
 

visualisation.py

@@ -1,6 +1,4 @@
-"""
-Visualisation of the copying process and ancestor generation using PIL
-"""
+# Visualisation of the copying process and ancestor generation using PIL
 import os
 import sys