79 lines
2.5 KiB
Python
79 lines
2.5 KiB
Python
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"""
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Level 3 title recommendation algorithm - only count the number of most frequently used # numbers
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"""
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from collections import Counter
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from typing import Dict, Any, List
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import re
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def get_third_level_hash_counts_simple(content: str) -> List[int]:
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hash_counts = []
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in_code_block = False
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for line in content.split('\n'):
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line = line.strip()
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if not line:
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continue
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# Processing code blocks
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if line.startswith('```'):
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in_code_block = not in_code_block
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continue
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if in_code_block:
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continue
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# Match the title line: #+ space Content
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match = re.match(r'^(#{1,6})\s+(.+)$', line)
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if match:
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hash_count = len(match.group(1))
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title_text = match.group(2).strip()
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# Check if it is a third-level heading - supports two formats:
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# 1. Traditional numeric format: "1.2.3", "1 . 2 . 3", "1. 2. 3", etc.
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# 2. Letter+number format: "A.1.2.3" (treat A.x.x.x as a third-level heading)
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is_third_level = False
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# Traditional numeric third-level format: x.x.x
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if re.match(r'^\d+\s*\.\s*\d+\s*\.\s*\d+(?:\s|$|[^\d\.])', title_text):
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is_third_level = True
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# Letter+number third-level format: A.x.x.x (treat as third-level heading)
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elif re.match(r'^[A-Z]\.\d+\.\d+\.\d+(?:\s|$|[^\d\.])', title_text):
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is_third_level = True
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if is_third_level:
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hash_counts.append(hash_count)
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return hash_counts
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def get_recommended_hash_count_simple(content: str) -> Dict[str, Any]:
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hash_counts = get_third_level_hash_counts_simple(content)
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if not hash_counts:
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return {
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'recommendation': 5, # Default value
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'reason': 'No third-level headings detected, using default value',
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'statistics': {},
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'total_count': 0
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}
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# Count the frequency of various # usage
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usage_stats = Counter(hash_counts)
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# Select the most frequently used # count
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most_common = usage_stats.most_common(1)[0]
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recommended_hash_count = most_common[0]
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frequency = most_common[1]
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total_count = len(hash_counts)
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percentage = frequency / total_count * 100
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return {
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'recommendation': recommended_hash_count,
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'reason': f'Most frequently used: {frequency}/{total_count} times ({percentage:.1f}%)',
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'statistics': dict(usage_stats),
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'total_count': total_count
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}
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