style: apply black formatting and isort import sorting across codebase

Fixes quality-checks CI job by ensuring all Python files in src/, tests/,
scripts/, and examples/ pass black --check and isort --check-only.

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

Author: docxology

examples/core/example_config.py

@@ -13,8 +13,10 @@
 from __future__ import annotations
 
 from pathlib import Path
+
 from metainformant.core import io, paths
-from metainformant.core.config import load_mapping_from_file, apply_env_overrides
+from metainformant.core.config import apply_env_overrides, load_mapping_from_file
+
 
 def main():
     """Demonstrate configuration loading with environment overrides."""
@@ -29,16 +31,13 @@ def main():
         "log_dir": "output/example_workflow/logs",
         "max_memory_gb": 8,
         "debug": False,
-        "analysis": {
-            "method": "fast",
-            "quality_threshold": 0.95,
-            "save_intermediates": True
-        }
+        "analysis": {"method": "fast", "quality_threshold": 0.95, "save_intermediates": True},
     }
 
     # Save sample config
     config_file = output_dir / "sample_config.yaml"
     import yaml
+
     with open(config_file, "w") as f:
         yaml.dump(sample_config, f, default_flow_style=False)
 
@@ -113,8 +112,8 @@ def main():
         "environment_variables_used": {
             "CORE_THREADS": "int (number of threads)",
             "CORE_WORK_DIR": "str (working directory path)",
-            "CORE_LOG_DIR": "str (logging directory path)"
-        }
+            "CORE_LOG_DIR": "str (logging directory path)",
+        },
     }
 
     io.dump_json(result_data, result_file)
@@ -125,5 +124,6 @@ def main():
     print("\n=== Configuration Example Complete ===")
     print("Try setting environment variables and re-running to see overrides in action!")
 
+
 if __name__ == "__main__":
     main()

examples/core/example_io.py

@@ -14,8 +14,10 @@
 
 import csv
 from pathlib import Path
+
 from metainformant.core import io
 
+
 def main():
     """Demonstrate file I/O operations."""
     # Setup output directory
@@ -26,21 +28,13 @@ def main():
 
     # Sample data for demonstration
     sample_data = {
-        "analysis": {
-            "type": "dna_sequence_analysis",
-            "timestamp": "2024-12-26T10:00:00Z",
-            "version": "1.0"
-        },
+        "analysis": {"type": "dna_sequence_analysis", "timestamp": "2024-12-26T10:00:00Z", "version": "1.0"},
         "sequences": [
             {"id": "seq1", "sequence": "ATCGATCG", "length": 8, "gc_content": 0.5},
             {"id": "seq2", "sequence": "GCTAGCTA", "length": 8, "gc_content": 0.5},
-            {"id": "seq3", "sequence": "TTTTAAAA", "length": 8, "gc_content": 0.0}
+            {"id": "seq3", "sequence": "TTTTAAAA", "length": 8, "gc_content": 0.0},
         ],
-        "statistics": {
-            "total_sequences": 3,
-            "average_length": 8.0,
-            "average_gc": 0.333
-        }
+        "statistics": {"total_sequences": 3, "average_length": 8.0, "average_gc": 0.333},
     }
 
     # 1. JSON file operations
@@ -71,12 +65,9 @@ def main():
     # Convert sequence data to CSV format
     csv_data = []
     for seq in sample_data["sequences"]:
-        csv_data.append({
-            "id": seq["id"],
-            "sequence": seq["sequence"],
-            "length": seq["length"],
-            "gc_content": seq["gc_content"]
-        })
+        csv_data.append(
+            {"id": seq["id"], "sequence": seq["sequence"], "length": seq["length"], "gc_content": seq["gc_content"]}
+        )
 
     csv_file = output_dir / "io_example.csv"
     io.write_csv(csv_data, csv_file)
@@ -94,7 +85,7 @@ def main():
         {"step": 1, "operation": "load_data", "status": "success", "duration_ms": 150},
         {"step": 2, "operation": "validate_data", "status": "success", "duration_ms": 50},
         {"step": 3, "operation": "analyze_sequences", "status": "success", "duration_ms": 500},
-        {"step": 4, "operation": "generate_report", "status": "success", "duration_ms": 200}
+        {"step": 4, "operation": "generate_report", "status": "success", "duration_ms": 200},
     ]
 
     jsonl_file = output_dir / "io_example.jsonl"
@@ -127,12 +118,13 @@ def main():
     print("\n7. File size comparison...")
 
     import os
+
     sizes = {
         "JSON": os.path.getsize(json_file),
         "JSON.gz": os.path.getsize(json_gz_file),
         "CSV": os.path.getsize(csv_file),
         "JSONL": os.path.getsize(jsonl_file),
-        "JSONL.gz": os.path.getsize(jsonl_gz_file)
+        "JSONL.gz": os.path.getsize(jsonl_gz_file),
     }
 
     print("File sizes (bytes):")
@@ -153,7 +145,7 @@ def main():
                 "json_gz": str(json_gz_file.relative_to(output_dir)),
                 "csv": str(csv_file.relative_to(output_dir)),
                 "jsonl": str(jsonl_file.relative_to(output_dir)),
-                "jsonl_gz": str(jsonl_gz_file.relative_to(output_dir))
+                "jsonl_gz": str(jsonl_gz_file.relative_to(output_dir)),
             },
             "file_sizes_bytes": sizes,
             "compression_ratio": compression_ratio,
@@ -163,13 +155,13 @@ def main():
                 "CSV data handling",
                 "JSONL (JSON Lines) format",
                 "Atomic write operations",
-                "Error handling and validation"
+                "Error handling and validation",
             ],
             "data_summary": {
                 "sequences_processed": len(sample_data["sequences"]),
                 "workflow_steps": len(jsonl_data),
-                "total_data_points": sum(len(seq["sequence"]) for seq in sample_data["sequences"])
-            }
+                "total_data_points": sum(len(seq["sequence"]) for seq in sample_data["sequences"]),
+            },
         }
     }
 
@@ -185,5 +177,6 @@ def main():
     print("- Use .gz extension for automatic compression")
     print("- All writes are atomic to prevent corruption")
 
+
 if __name__ == "__main__":
     main()

examples/core/example_logging.py

@@ -14,8 +14,10 @@
 
 import time
 from pathlib import Path
+
 from metainformant.core import logging
 
+
 def main():
     """Demonstrate logging functionality."""
     # Setup output directory
@@ -66,7 +68,7 @@ def simulate_analysis_step(step_name: str, duration: float):
         ("data_validation", 0.05),
         ("sequence_analysis", 0.2),
         ("statistics_calculation", 0.15),
-        ("report_generation", 0.1)
+        ("report_generation", 0.1),
     ]
 
     total_time = 0
@@ -86,15 +88,11 @@ def simulate_analysis_step(step_name: str, duration: float):
         "average_length": 450,
         "gc_content_range": [0.35, 0.65],
         "quality_threshold": 0.95,
-        "timestamp": "2024-12-26T10:00:00Z"
+        "timestamp": "2024-12-26T10:00:00Z",
     }
 
     logging.log_with_metadata(
-        file_logger,
-        "Analysis completed successfully",
-        analysis_metadata,
-        level="INFO",
-        structured=True
+        file_logger, "Analysis completed successfully", analysis_metadata, level="INFO", structured=True
     )
 
     # 6. Environment-based configuration
@@ -135,7 +133,7 @@ def load_sequences():
         return ["ATCG" * 25] * 100  # Simulate loading 100 sequences
 
     def calculate_gc_content(sequences):
-        return sum(seq.count('G') + seq.count('C') for seq in sequences) / sum(len(seq) for seq in sequences)
+        return sum(seq.count("G") + seq.count("C") for seq in sequences) / sum(len(seq) for seq in sequences)
 
     def find_motifs(sequences, motif="ATCG"):
         return sum(seq.count(motif) for seq in sequences)
@@ -152,7 +150,7 @@ def find_motifs(sequences, motif="ATCG"):
     print("\n9. Creating logging summary...")
 
     # Read the log file to show what was captured
-    with open(log_file, 'r') as f:
+    with open(log_file, "r") as f:
         log_lines = f.readlines()
 
     summary = {
@@ -168,23 +166,24 @@ def find_motifs(sequences, motif="ATCG"):
                 "Environment-based configuration",
                 "Multiple component loggers",
                 "Performance timing",
-                "Workflow step tracking"
+                "Workflow step tracking",
             ],
             "workflow_simulation": {
                 "steps_completed": len(workflow_steps),
                 "total_workflow_time": total_time,
                 "performance_operations": {
                     "sequence_loading": load_time,
                     "gc_content_calculation": gc_time,
-                    "motif_finding": motif_time
-                }
+                    "motif_finding": motif_time,
+                },
             },
-            "sample_log_entries": log_lines[-5:] if len(log_lines) >= 5 else log_lines
+            "sample_log_entries": log_lines[-5:] if len(log_lines) >= 5 else log_lines,
         }
     }
 
     summary_file = output_dir / "logging_demo_summary.json"
     from metainformant.core import io
+
     io.dump_json(summary, summary_file, indent=2)
 
     print(f"✓ Logging summary saved to: {summary_file}")
@@ -199,5 +198,6 @@ def find_motifs(sequences, motif="ATCG"):
     print("- Use log_with_metadata() for structured data logging")
     print("- Configure logging level via CORE_LOG_LEVEL environment variable")
 
+
 if __name__ == "__main__":
     main()