| | import argparse
|
| | import json
|
| | import os
|
| | from datetime import datetime
|
| | from difflib import SequenceMatcher
|
| |
|
| |
|
| | def check_file_valid(file_path: str) -> bool:
|
| | if not os.path.isfile(file_path):
|
| | print(f"❌ File does not exist: {file_path}")
|
| | return False
|
| | if os.path.getsize(file_path) == 0:
|
| | print(f"❌ File is empty: {file_path}")
|
| | return False
|
| | return True
|
| |
|
| |
|
| | def load_json_or_jsonl(file_path: str):
|
| | with open(file_path, "r", encoding="utf-8") as f:
|
| | content = f.read().strip()
|
| | if not content:
|
| | return []
|
| |
|
| |
|
| | try:
|
| | data = json.loads(content)
|
| | if isinstance(data, list):
|
| | return data
|
| | except json.JSONDecodeError:
|
| | pass
|
| |
|
| |
|
| | lines = []
|
| | with open(file_path, "r", encoding="utf-8") as f:
|
| | for i, line in enumerate(f, 1):
|
| | line = line.strip()
|
| | if not line:
|
| | continue
|
| | try:
|
| | item = json.loads(line)
|
| | if isinstance(item, list):
|
| | lines.extend(item)
|
| | else:
|
| | lines.append(item)
|
| | except Exception as e:
|
| | print(f"❌ Line {i} JSON parse failed: {line}")
|
| | raise e
|
| | return lines
|
| |
|
| |
|
| | def normalized_similarity(a: str, b: str) -> float:
|
| | return SequenceMatcher(None, a.strip(), b.strip()).ratio()
|
| |
|
| |
|
| | def evaluate_scrapy_output(pred_path: str, truth_path: str, result_path: str = None) -> bool:
|
| | threshold = 0.95
|
| | process_success = check_file_valid(pred_path) and check_file_valid(truth_path)
|
| |
|
| | if not process_success:
|
| | result = {
|
| | "Process": False,
|
| | "Result": False,
|
| | "TimePoint": datetime.now().isoformat(),
|
| | "comments": f"❌ File does not exist or is empty: pred={pred_path}, truth={truth_path}"
|
| | }
|
| | if result_path:
|
| | with open(result_path, "a", encoding="utf-8") as f:
|
| | f.write(json.dumps(result, ensure_ascii=False) + "\n")
|
| | return False
|
| |
|
| | try:
|
| | pred_lines = load_json_or_jsonl(pred_path)
|
| | true_lines = load_json_or_jsonl(truth_path)
|
| |
|
| | if len(pred_lines) != len(true_lines):
|
| | print(f"⚠️ Crawl results count mismatch (predicted {len(pred_lines)}, truth {len(true_lines)})")
|
| |
|
| | total_fields = 0
|
| | total_similarity = 0
|
| |
|
| | for pred, true in zip(pred_lines, true_lines):
|
| | for field in ["author", "text"]:
|
| | pred_val = str(pred.get(field, ""))
|
| | true_val = str(true.get(field, ""))
|
| | sim = normalized_similarity(pred_val, true_val)
|
| | total_similarity += sim
|
| | total_fields += 1
|
| |
|
| | avg_similarity = total_similarity / total_fields if total_fields else 0
|
| | result_passed = avg_similarity >= threshold
|
| |
|
| | print(f"📊 Average field similarity (edit distance): {avg_similarity:.2%}")
|
| | print("✅ Extraction valid, similarity >= 95%" if result_passed else "❌ Extraction failed")
|
| |
|
| | if result_path:
|
| | result = {
|
| | "Process": True,
|
| | "Result": result_passed,
|
| | "TimePoint": datetime.now().isoformat(),
|
| | "comments": f"Average field similarity: {avg_similarity:.4f}, {'meets' if result_passed else 'does not meet'} 95% threshold"
|
| | }
|
| | with open(result_path, "a", encoding="utf-8") as f:
|
| | f.write(json.dumps(result, ensure_ascii=False) + "\n")
|
| |
|
| | return result_passed
|
| |
|
| | except Exception as e:
|
| | print(f"❌ Runtime error: {e}")
|
| | if result_path:
|
| | result = {
|
| | "Process": True,
|
| | "Result": False,
|
| | "TimePoint": datetime.now().isoformat(),
|
| | "comments": f"Runtime error: {str(e)}"
|
| | }
|
| | with open(result_path, "a", encoding="utf-8") as f:
|
| | f.write(json.dumps(result, ensure_ascii=False) + "\n")
|
| | return False
|
| |
|
| |
|
| | if __name__ == "__main__":
|
| | parser = argparse.ArgumentParser(description="Evaluate field-level similarity of Scrapy crawl results")
|
| | parser.add_argument("--output", type=str, required=True, help="Prediction results (JSON/JSONL) path")
|
| | parser.add_argument("--groundtruth", type=str, required=True, help="Ground truth (JSON/JSONL) path")
|
| | parser.add_argument("--result", type=str, required=False, help="Output JSONL file path for results")
|
| |
|
| | args = parser.parse_args()
|
| | success = evaluate_scrapy_output(args.output, args.groundtruth, args.result) |
