"""
Section splitter for shared URLs in unified compliance checks.

When the same URL is used for multiple document types (e.g. /datenschutz
used for DSI + Cookie + DSB), this module splits the text at headings
and assigns the best-matching section to each doc_type.
"""

import logging
import re

logger = logging.getLogger(__name__)

# Heading keyword → doc_type mapping
_HEADING_TYPE_MAP = [
    ("cookie", "cookie"),
    ("datenschutzbeauftragte", "dsb"),
    ("widerruf", "widerruf"),
    ("impressum", "impressum"),
    ("agb", "agb"),
    ("nutzungsbedingung", "agb"),
    ("social media", "social_media"),
    ("soziale medien", "social_media"),
    ("soziale netzwerke", "social_media"),
    ("google analytics", "cookie"),
    ("tracking", "cookie"),
    ("verwendung von cookies", "cookie"),
    ("nutzung von google", "cookie"),
    ("webanalyse", "cookie"),
]


def split_shared_texts(
    doc_entries: list[dict],
    url_cache: dict[str, str],
) -> None:
    """When the same URL is used for multiple doc_types, split text into
    sections and assign the best-matching section to each doc_type.

    Mutates doc_entries in place.
    """
    # Group entries by normalized URL
    url_groups: dict[str, list[int]] = {}
    for i, entry in enumerate(doc_entries):
        if not entry.get("url"):
            continue
        key = entry["url"].strip().rstrip("/").lower()
        url_groups.setdefault(key, []).append(i)

    for url_key, indices in url_groups.items():
        if len(indices) < 2:
            continue

        full_text = doc_entries[indices[0]].get("text", "")
        if not full_text or len(full_text) < 200:
            continue

        sections = _split_at_headings(full_text)
        if not sections:
            continue

        for idx in indices:
            doc_type = doc_entries[idx]["doc_type"]
            best = _find_section_for_type(sections, doc_type)
            if best:
                doc_entries[idx]["text"] = best
                doc_entries[idx]["word_count"] = len(best.split())

        typed = [s for s in sections if s.get("type")]
        logger.info(
            "Split shared URL into %d typed sections for %d doc_types: %s",
            len(typed), len(indices),
            ", ".join(f"{s['type']}({len(s['text'].split())}w)" for s in typed),
        )


def _split_at_headings(text: str) -> list[dict]:
    """Split text at classified headings into typed sections."""
    lines = text.split("\n")
    sections: list[dict] = []
    current_type: str | None = None
    current_heading = ""
    current_lines: list[str] = []
    preamble_lines: list[str] = []

    for line in lines:
        stripped = line.strip()
        classified = _classify_heading(stripped)

        if classified:
            # Save previous section
            if current_type and current_lines:
                _add_section(sections, current_heading, current_type, current_lines)
            elif not current_type and current_lines:
                preamble_lines.extend(current_lines)

            current_type = classified
            current_heading = stripped
            current_lines = []
        else:
            current_lines.append(line)

    # Save last section
    if current_type and current_lines:
        _add_section(sections, current_heading, current_type, current_lines)
    elif current_lines:
        preamble_lines.extend(current_lines)

    # Add preamble as untyped section (main DSI text)
    if preamble_lines:
        preamble_text = "\n".join(preamble_lines)
        if len(preamble_text.split()) >= 30:
            sections.insert(0, {
                "heading": "(Haupttext)",
                "text": preamble_text,
                "type": "dse",
            })

    return sections


def _add_section(
    sections: list[dict], heading: str, sec_type: str, lines: list[str],
) -> None:
    """Add a section, merging with existing same-type sections."""
    text = "\n".join(lines)
    if len(text.split()) < 20:
        return
    # Merge if same type already exists
    for s in sections:
        if s["type"] == sec_type:
            s["text"] += "\n\n" + text
            return
    sections.append({"heading": heading, "text": text, "type": sec_type})


def _classify_heading(line: str) -> str | None:
    """Classify a line as a section heading. Returns doc_type or None."""
    if not line or len(line) < 5 or len(line) > 80:
        return None
    if line.endswith(".") or line.endswith(","):
        return None
    if len(line.split()) > 10:
        return None
    if not (line[0].isupper() or line[0].isdigit()):
        return None

    heading_lower = line.lower().strip()
    heading_lower = re.sub(r"^[\d\.\)\-]+\s*", "", heading_lower).strip()

    for keyword, doc_type in _HEADING_TYPE_MAP:
        if keyword in heading_lower:
            return doc_type
    return None


def _find_section_for_type(sections: list[dict], doc_type: str) -> str | None:
    """Find the best text section for a given doc_type.

    DSI always gets the full text (main document).
    Other types get their matching section if found.
    """
    if doc_type in ("dse", "datenschutz", "privacy"):
        return None  # Keep full text for DSI

    for section in sections:
        if section.get("type") == doc_type and section.get("text"):
            return section["text"]

    return None  # No match → keep full text