"""Helpers moved unchanged out of render_pl9_markdown (phase 1)."""

import re

try:
    from scripts.report_render.envelope import _unwrap
except ModuleNotFoundError:  # pragma: no cover - direct scripts/ execution
    from report_render.envelope import _unwrap

SIGNS = ['Aries', 'Taurus', 'Gemini', 'Cancer', 'Leo', 'Virgo', 'Libra', 'Scorpio', 'Sagittarius', 'Capricorn', 'Aquarius', 'Pisces']
SIGNS_CN = {'Aries': '白羊座', 'Taurus': '金牛座', 'Gemini': '双子座', 'Cancer': '巨蟹座', 'Leo': '狮子座', 'Virgo': '处女座', 'Libra': '天秤座', 'Scorpio': '天蝎座', 'Sagittarius': '射手座', 'Capricorn': '摩羯座', 'Aquarius': '水瓶座', 'Pisces': '双鱼座'}

PLANET_LABEL_CN = {
    'Sun': '太阳',
    'Moon': '月亮',
    'Mars': '火星',
    'Mercury': '水星',
    'Jupiter': '木星',
    'Venus': '金星',
    'Saturn': '土星',
    'Rahu': '北交点',
    'Ketu': '南交点',
}

def _humanize_reader_token(token: str) -> str:
    value = str(token or '').strip()
    if not value:
        return value
    if value in SIGNS_CN:
        return SIGNS_CN[value]
    if value in PLANET_LABEL_CN:
        return PLANET_LABEL_CN[value]
    return value

def _humanize_reader_group(raw_group: str) -> str:
    seen = set()
    parts = []
    for item in str(raw_group or '').split(','):
        humanized = _humanize_reader_token(item)
        if humanized and humanized not in seen:
            seen.add(humanized)
            parts.append(humanized)
    return ' / '.join(parts)

def _humanize_tajika_candidate(name: str) -> str:
    return {
        'Ithasala_candidate': '趋近相位候选',
        'Easarapha_candidate': '分离相位候选',
    }.get(str(name or ''), '年度相位候选')

def _humanize_tajika_motion(motion: str) -> str:
    return {'applying': '趋近', 'separating': '分离'}.get(str(motion or ''), str(motion or '-'))

def _display_rashi_from_value(raw_value):
    if isinstance(raw_value, int) and 0 <= raw_value < len(SIGNS):
        return _humanize_reader_token(SIGNS[raw_value])
    return _humanize_reader_token(raw_value)

def _humanize_reader_summary_line(summary_line: str) -> str:
    summary_line = _unwrap(summary_line)
    if isinstance(summary_line, dict):
        summary_line = (
            summary_line.get('brief')
            or summary_line.get('text')
            or summary_line.get('summary')
            or ''
        )
    text = str(summary_line or '').strip()
    if not text:
        return text
    if text == "年度层已经有可读壳层，但仍需要带着冲突标签阅读。":
        return "这一年的年度主线已经形成。"
    if text == "This pack converts Dasha trigger facts into report-ready interpretation seeds without final event claims.":
        return "这层已经把 Dasha 触发事实压成可读提示，但仍不直接升级为具体事件断语。"
    if text == "Source: dasha_master_pack.interpretation_triggers.":
        return "当前解释仍然直接来自 dasha_master_pack.interpretation_triggers 的证据层。"
    if text == "All claims remain evidence-labeled and parameter-sensitive where the source pack is unclosed.":
        return "只要 source pack 还没闭环，相关结论就继续保持 evidence-labeled 与 parameter_sensitive。"
    if text == "Tajika Yogas: annual candidate structures visible":
        return "Tajika Yogas 当前已经能读到年度候选交互结构。"
    if text == "Sahams: annual sensitive points visible":
        return "Sahams 当前已经能读到年度敏感点。"
    match = re.match(r'^([^:]+):\s*conflict between\s+(.+?)\s+vs\s+(.+)$', text)
    if match:
        topic = match.group(1).strip()
        left = _humanize_reader_group(match.group(2))
        right = _humanize_reader_group(match.group(3))
        topic_label = {
            'Muntha': 'Muntha',
            'Year Lord': 'Year Lord',
            'Annual Asc': '返照上升',
        }.get(topic, topic)
        if left == right:
            return f"{topic_label} 当前结果指向{left}。"
        return f"{topic_label} 当前存在候选分歧：一组结果指向{left}，另一组结果指向{right}。"
    simple_match = re.match(r'^([^:]+):\s*(.+)$', text)
    if simple_match:
        topic = simple_match.group(1).strip()
        value = _humanize_reader_group(simple_match.group(2))
        if topic == 'Year Lord' and value:
            return f"Year Lord 当前优先候选指向{value}。"
        if topic == 'Muntha' and value:
            return f"Muntha 当前优先候选指向{value}。"
        if topic == 'Tajika Yogas' and 'annual candidate structures visible' in str(simple_match.group(2)).lower():
            return "Tajika Yogas 当前已经能读到年度候选交互结构。"
        if topic == 'Sahams' and 'annual sensitive points visible' in str(simple_match.group(2)).lower():
            return "Sahams 当前已经能读到年度敏感点。"
    return text

def _humanize_annual_highlight_line(highlight: str) -> str:
    text = str(highlight or '').strip()
    if not text:
        return text
    if text == "Solar Return / Tajika annual shell is available.":
        return "本年度返照与 Tajika 时间结构已经生成。"
    if text == "Muntha and Year Lord are visible, but Year Lord remains producer-disagree sensitive.":
        return "Muntha 和 Year Lord 现在都已经可见，但 Year Lord 仍要带着分歧标签阅读。"
    if text == "The report should read annual structure first, then the evidence appendix.":
        return "这一层适合从年度结构展开，再回头核对证据附录。"
    return text

def _humanize_annual_narrative_highlight(highlight: str) -> str:
    return _humanize_annual_highlight_line(str(highlight)).rstrip('。')

def _humanize_domain_title(title: str) -> str:
    text = str(title or '').strip()
    if not text:
        return text
    mapping = {
        "Career and public direction": "事业与公众方向",
        "Wealth and growth opportunities": "财富与增长机会",
        "Relationship and alliance themes": "关系与合作主题",
        "Health and vitality caution": "健康与精力提醒",
        "Risk, delay, and friction markers": "阻力、延迟与摩擦提示",
        "Timing windows and cross-check needs": "时间窗口与交叉核对重点",
    }
    return mapping.get(text, text)

def _workbook_readable_label(worksheet_id: str) -> str:
    if worksheet_id == 'birth_and_parameters':
        return '出生与计算口径'
    if worksheet_id == 'd1_rasi_bhava':
        return '本命盘主结构'
    if worksheet_id == 'strengths_and_scores':
        return '力量与技术表'
    if worksheet_id == 'divisional_and_special_charts':
        return '分盘与特殊点位'
    if worksheet_id == 'timing_and_predictive_systems':
        return '时间系统与流年层'
    if worksheet_id == 'advanced_systems':
        return '进阶体系'
    if worksheet_id == 'ai_and_audit':
        return '审计与证据附录'
    return '补充工作簿'

def _workbook_readable_sentence(worksheet_id: str) -> str:
    if worksheet_id == 'birth_and_parameters':
        return '出生参数、岁差、交点模式与计算口径已经固定，是整份报告的可信底座。'
    if worksheet_id == 'd1_rasi_bhava':
        return '本命盘主结构已经就位，适合先看性格主轴、房屋结构和基础趋势。'
    if worksheet_id == 'strengths_and_scores':
        return '力量、功能性吉凶与技术表可以直接用来判断支撑与压力来源。'
    if worksheet_id == 'divisional_and_special_charts':
        return '分盘与特殊点位可作为扩展阅读，适合补充看细节。'
    if worksheet_id == 'timing_and_predictive_systems':
        return '大运、行运与年度层已经可以形成时间主线。'
    if worksheet_id == 'advanced_systems':
        return 'Jaimini、KP、Yoga 等进阶体系可作为补充主轴。'
    if worksheet_id == 'ai_and_audit':
        return 'AI 读写、审计与证据层用于核对来源与边界，不直接替代正文。'
    return f'{worksheet_id} 已纳入当前报告。'

def _workbook_reading_paragraph(worksheet_ids: list[str]) -> str:
    parts = []
    for worksheet_id in worksheet_ids:
        sentence = _workbook_readable_sentence(worksheet_id).rstrip('。')
        parts.append(f"先看{_workbook_readable_label(worksheet_id)}，这里会告诉你{sentence}")
    if not parts:
        return '当前暂无可用工作簿阅读顺序。'
    return '；'.join(parts) + '。'

def _md_cell(value) -> str:
    text = str(value if value not in (None, '') else '-').replace('\n', ' ').strip()
    return text.replace('|', '/')

def _render_compact_payload(value, depth: int = 0) -> str:
    if value in (None, '', [], {}):
        return '-'
    if depth >= 2:
        return _md_cell(type(value).__name__)
    if isinstance(value, dict):
        parts = []
        for key in sorted(value, key=str):
            if key in {
                'narrative_items',
                'domain_paragraphs',
                'response_envelope',
                'input_hash',
                'profile_hash',
                'raw_calculation',
                'shared_full_report_authority',
            }:
                continue
            parts.append(f"{key}={_render_compact_payload(value.get(key), depth + 1)}")
        return '; '.join(parts) if parts else '-'
    if isinstance(value, (list, tuple)):
        items = [_render_compact_payload(item, depth + 1) for item in list(value)[:8]]
        suffix = ' …' if len(value) > 8 else ''
        return ', '.join(items) + suffix if items else '-'
    return _md_cell(value)

def _sign_text(row: dict, sign_key: str = 'sign', cn_key: str = 'sign_cn') -> str:
    if not isinstance(row, dict):
        return '-'
    sign = row.get(cn_key) or _humanize_reader_token(row.get(sign_key)) or row.get(sign_key)
    return _md_cell(sign)

def _value_text(*values):
    for value in values:
        if value not in (None, '', [], {}):
            return str(value)
    return None

def _compose_narrative_paragraph(*parts: str | None) -> str | None:
    cleaned = []
    for part in parts:
        text = str(part or '').strip()
        if not text:
            continue
        text = text.rstrip()
        if text.endswith('。'):
            text = text[:-1]
        cleaned.append(text)
    if not cleaned:
        return None
    return '；'.join(cleaned) + '。'

def _planet_list_text(items: list[str], limit: int = 3) -> str | None:
    names = []
    seen = set()
    for item in items:
        humanized = _humanize_reader_token(item)
        if humanized and humanized not in seen:
            seen.add(humanized)
            names.append(humanized)
        if len(names) >= limit:
            break
    if not names:
        return None
    return '、'.join(names)

def _append_unique_text(items: list[str], value: str) -> None:
    text = str(value or '').strip().rstrip('。')
    if text and text not in items:
        items.append(text)