Fix black/ruff formatting across src and tests

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

Author: audristroyer

src/ndi/cloud/api/files.py

@@ -175,8 +175,6 @@ def get_file_details(
     )
 
 
-
-
 def get_file_collection_upload_url(
     client: CloudClient,
     org_id: str,

src/ndi/cloud/download.py

@@ -182,8 +182,6 @@ def _log(msg: str) -> None:
     return report
 
 
-
-
 def _download_chunk_zip(
     url: str,
     timeout: float = 20.0,

src/ndi/fun/doc.py

@@ -44,8 +44,6 @@ def all_types() -> list[str]:
     return sorted(types)
 
 
-
-
 def find_fuid(session: Any, fuid: str) -> tuple[Any | None, str]:
     """Search session for a document containing a file with the given UID.
 

src/ndi/fun/doc_table.py

@@ -400,9 +400,7 @@ def subject_summary(
     om_docs = session.database_search(Query("").isa("openminds_subject"))
 
     # Per-subject openminds data: {subject_id: {type: [doc_props, ...]}}
-    om_by_subject: dict[str, dict[str, list[dict]]] = {
-        sid: {} for sid in subject_info
-    }
+    om_by_subject: dict[str, dict[str, list[dict]]] = {sid: {} for sid in subject_info}
 
     for doc in om_docs:
         props = doc.document_properties if hasattr(doc, "document_properties") else doc

src/ndi/fun/table.py

@@ -185,7 +185,7 @@ def _agg(series: pd.Series) -> Any:
 
             result = (
                 result.groupby(unique_variables, sort=False)
-                .agg({c: _agg for c in other_cols})
+                .agg(dict.fromkeys(other_cols, _agg))
                 .reset_index()
             )
 

tests/matlab_tests/test_jess_haley.py

@@ -26,7 +26,6 @@
 import json
 import os
 from pathlib import Path
-from typing import Any
 
 import pytest
 
@@ -141,13 +140,11 @@ def test_document_type_counts(self, jess_haley_dataset):
             actual_count = actual.get(dtype, 0)
             if dtype == "session":
                 # Dataset init adds 1 extra session doc
-                assert actual_count >= expected, (
-                    f"{dtype}: expected >= {expected}, got {actual_count}"
-                )
+                assert (
+                    actual_count >= expected
+                ), f"{dtype}: expected >= {expected}, got {actual_count}"
             else:
-                assert actual_count == expected, (
-                    f"{dtype}: expected {expected}, got {actual_count}"
-                )
+                assert actual_count == expected, f"{dtype}: expected {expected}, got {actual_count}"
 
     def test_all_documents_have_base_id(self, all_docs_raw):
         """Every document has a base.id field."""
@@ -227,9 +224,9 @@ def test_groups_by_variable_names(self, otr_tables):
     def test_group_row_counts(self, otr_tables):
         data_tables, _ = otr_tables
         actual_sizes = sorted([len(dt) for dt in data_tables], reverse=True)
-        assert actual_sizes == EXPECTED_OTR_GROUP_SIZES_SORTED, (
-            f"Group sizes mismatch: {actual_sizes} != {EXPECTED_OTR_GROUP_SIZES_SORTED}"
-        )
+        assert (
+            actual_sizes == EXPECTED_OTR_GROUP_SIZES_SORTED
+        ), f"Group sizes mismatch: {actual_sizes} != {EXPECTED_OTR_GROUP_SIZES_SORTED}"
 
     def test_data_dict_extraction(self, otr_tables):
         """At least one group has bacterial plate columns."""
@@ -261,9 +258,9 @@ def test_encounter_table_has_numeric_data(self, otr_tables):
         # Find the encounter table (largest group, ~20411 rows)
         encounter_table = max(data_tables, key=len)
         decel_col = "CElegansBehavioralAssay_DecelerationUponEncounter"
-        assert decel_col in encounter_table.columns, (
-            f"'{decel_col}' not in largest group columns: {list(encounter_table.columns)}"
-        )
+        assert (
+            decel_col in encounter_table.columns
+        ), f"'{decel_col}' not in largest group columns: {list(encounter_table.columns)}"
         assert pd.api.types.is_numeric_dtype(encounter_table[decel_col])
 
     def test_bacterial_plate_table_has_expected_columns(self, otr_tables):
@@ -633,7 +630,9 @@ def test_session_id_consistency(self, jess_haley_dataset):
         # Note: session_id is the session object's ID, NOT the session
         # document's base.id. The Jess Haley dataset has 3 unique session_ids.
         assert len(session_ids) >= 2, f"Expected >= 2 unique session_ids, got {session_ids}"
-        assert len(session_ids) <= 10, f"Too many session_ids ({len(session_ids)}), data may be corrupt"
+        assert (
+            len(session_ids) <= 10
+        ), f"Too many session_ids ({len(session_ids)}), data may be corrupt"
 
 
 # ===========================================================================
@@ -668,7 +667,7 @@ def test_plot_document_type_distribution(self, jess_haley_dataset):
         ax.barh(doc_types, doc_counts, color="steelblue")
         ax.set_xlabel("Count")
         ax.set_title("Jess Haley Dataset: Document Type Distribution")
-        for i, (t, c) in enumerate(zip(doc_types, doc_counts)):
+        for i, (_t, c) in enumerate(zip(doc_types, doc_counts)):
             ax.text(c + 100, i, str(c), va="center", fontsize=8)
         plt.tight_layout()
         plt.savefig(out / "doc_type_distribution.png", dpi=150)
@@ -681,7 +680,6 @@ def test_plot_subject_experiment_types(self, jess_haley_dataset):
         import matplotlib
 
         matplotlib.use("Agg")
-        import re
         from collections import Counter
 
         import matplotlib.pyplot as plt
@@ -870,7 +868,7 @@ def test_render_video_frame_sequence(self, all_docs_raw):
         time_per_frame = time_scale[2] if len(time_scale) > 2 else 1.0
 
         fig, axes = plt.subplots(2, 4, figsize=(16, 8))
-        for idx, (ax, fi) in enumerate(zip(axes.flat, frame_indices)):
+        for _idx, (ax, fi) in enumerate(zip(axes.flat, frame_indices)):
             cap.set(cv2.CAP_PROP_POS_FRAMES, fi)
             ret, frame = cap.read()
             if ret:

tests/test_fun.py

@@ -332,9 +332,7 @@ def test_with_mock_session(self):
             }
         }
         doc2 = MagicMock()
-        doc2.document_properties = {
-            "document_class": {"class_name": "subject"}
-        }
+        doc2.document_properties = {"document_class": {"class_name": "subject"}}
         session = MagicMock()
         session.database_search.return_value = [doc1, doc2]