"""审查结果数据结构。"""

from __future__ import annotations
from collections import Counter
from typing import Literal
from pydantic import BaseModel, Field
from fastapi_modules.fastapi_leaudit.govdoc_engine.models import Finding
from fastapi_modules.fastapi_leaudit.govdoc_engine.parser.entities import SemanticEntity


class CheckedRule(BaseModel):
    rule_id: str
    name: str
    severity: str
    category: str
    status: Literal["pass", "fail", "skipped"]
    skip_reason: str = ""


class StructureItem(BaseModel):
    """文档结构里一种 role 的统计。"""

    role: str
    label: str
    count: int
    expected: bool
    paragraph_indices: list[int] = Field(default_factory=list)
    samples: list[str] = Field(default_factory=list)
    char_total: int = 0
    dominant_font: str | None = None
    dominant_size_pt: float | None = None
    style_uniform: bool = True


class OutlineNode(BaseModel):
    """大纲节点（heading_1~4 的层级树）。"""

    paragraph_index: int
    level: int
    text: str
    children: list["OutlineNode"] = Field(default_factory=list)


class AuditSummary(BaseModel):
    score: int = 100
    total_findings: int = 0
    by_severity: dict[str, int] = Field(default_factory=dict)
    by_category: dict[str, int] = Field(default_factory=dict)
    passed_count: int = 0
    failed_count: int = 0
    skipped_count: int = 0


class AuditResult(BaseModel):
    audit_id: str
    document: dict = Field(default_factory=dict)
    summary: AuditSummary = Field(default_factory=AuditSummary)
    findings: list[Finding] = Field(default_factory=list)
    checked_rules: list[CheckedRule] = Field(default_factory=list)
    structure: list[StructureItem] = Field(default_factory=list)
    outline: list[OutlineNode] = Field(default_factory=list)
    entities: dict[str, SemanticEntity | None] = Field(default_factory=dict)

    def compute_summary(self) -> None:
        sev_count = Counter(f.severity for f in self.findings)
        cat_count = Counter(f.category for f in self.findings)
        score = 100
        score -= 10 * sev_count.get("error", 0)
        score -= 3 * sev_count.get("warning", 0)
        passed = sum(1 for r in self.checked_rules if r.status == "pass")
        failed = sum(1 for r in self.checked_rules if r.status == "fail")
        skipped = sum(1 for r in self.checked_rules if r.status == "skipped")
        self.summary = AuditSummary(
            score=max(0, score),
            total_findings=len(self.findings),
            by_severity=dict(sev_count),
            by_category=dict(cat_count),
            passed_count=passed,
            failed_count=failed,
            skipped_count=skipped,
        )