"""Cross-Regulation Capability Mapping (Regulatory Convergence) — RS-005.

Answers the USP question: „Welche Capability deckt gleichzeitig mehrere Regelwerke ab?"
Given, per capability, the set of target regulations it covers (`covers_targets`,
curated knowledge from a Regulatory Convergence Pattern), it computes how many
capabilities cover >= 2 regulations at once — the basis for the customer sentence
„von N Maßnahmen decken M gleichzeitig CRA und MaschinenVO".

Pure, deterministic, computed-not-stored. No new graph/base class/meta-model class
(freeze v1.0 untouched). Python 3.9 compatible (no `|` unions).
"""

from __future__ import annotations

from typing import Dict, List

from pydantic import BaseModel, Field


class RegulatoryConvergence(BaseModel):
    targets: List[str] = Field(default_factory=list)
    per_target_count: Dict[str, int] = Field(default_factory=dict)  # capabilities each target requires
    multi_target_capabilities: List[str] = Field(default_factory=list)  # cover >= 2 targets
    single_target_capabilities: List[str] = Field(default_factory=list)
    headline: str = ""  # NO percentages


def regulatory_convergence(
    capability_targets: Dict[str, List[str]], targets: List[str]
) -> RegulatoryConvergence:
    """capability_targets: capability_id -> regulations it covers. `targets`: the regulations in scope."""
    target_set = set(targets)
    per: Dict[str, int] = {t: 0 for t in targets}
    multi: List[str] = []
    single: List[str] = []
    for cap, covers in capability_targets.items():
        in_scope = [t for t in covers if t in target_set]
        for t in in_scope:
            per[t] += 1
        if len(in_scope) >= 2:
            multi.append(cap)
        elif len(in_scope) == 1:
            single.append(cap)
    headline = (
        "%d von %d Capabilities decken >= 2 Regelwerke gleichzeitig ab (%s)."
        % (len(multi), len(capability_targets), " + ".join(targets))
    )
    return RegulatoryConvergence(
        targets=list(targets),
        per_target_count=per,
        multi_target_capabilities=sorted(multi),
        single_target_capabilities=sorted(single),
        headline=headline,
    )