"""Attach the atom-grain network_security regulatory breadth to CRA findings.

This is the "semantic breadth (2)" from the handoff: the shared Controls-API
(compliance.atom_classification, use_case=network_security, ~11k precise,
framework-traceable obligations). It runs at the ENDPOINT/VIEW layer — NOT in
the pure cra_finding_mapper, which stays deterministic. The CRA Annex I anchor +
the curated measure + the NIST/OWASP golden-set crosswalk remain the lead; this
is breadth + source evidence, not a replacement.

Only network_security is atom-grain — we query only that, always scoped by
sub_topic + limit (per the caveats).
"""
import time

from compliance.api.cra_annex_i_data import ANNEX_I_REQUIREMENTS
from compliance.services.use_case_controls import UseCaseControlsService

# CRA-AI requirement -> network_security sub_topic (via the NIST families per
# CRA-AI). Exact sub_topic keys verified against the live atom_classification.
_REQ_TO_SUBTOPIC = {
    "CRA-AI-1": "secure_development", "CRA-AI-2": "network_segmentation",
    "CRA-AI-3": "network_segmentation", "CRA-AI-4": "access_control",
    "CRA-AI-5": "secure_development", "CRA-AI-6": "secure_development",
    "CRA-AI-7": "authentication", "CRA-AI-8": "authentication", "CRA-AI-9": "authentication",
    "CRA-AI-10": "access_control", "CRA-AI-11": "authentication", "CRA-AI-12": "access_control",
    "CRA-AI-13": "cryptography", "CRA-AI-14": "cryptography", "CRA-AI-15": "cryptography",
    "CRA-AI-16": "cryptography", "CRA-AI-17": "data_protection",
    "CRA-AI-18": "secure_development", "CRA-AI-19": "secure_development", "CRA-AI-20": "secure_development",
    "CRA-AI-21": "supply_chain_security", "CRA-AI-22": "vulnerability_management",
    "CRA-AI-23": "supply_chain_security",
    "CRA-AI-24": "logging_monitoring", "CRA-AI-25": "logging_monitoring",
    "CRA-AI-26": "logging_monitoring", "CRA-AI-27": "logging_monitoring",
    "CRA-AI-28": "vulnerability_management", "CRA-AI-29": "vulnerability_management",
    "CRA-AI-30": "vulnerability_management", "CRA-AI-31": "vulnerability_management",
    "CRA-AI-32": "vulnerability_management", "CRA-AI-33": "vulnerability_management",
    "CRA-AI-34": "vulnerability_management",
    "CRA-AI-35": "incident_response", "CRA-AI-36": "incident_response",
    "CRA-AI-37": "incident_response", "CRA-AI-38": "incident_response",
    "CRA-AI-39": "vulnerability_management", "CRA-AI-40": "incident_response",
}


# Two breadth lanes per finding: the CRA-specific corpus (always — most on-point
# for a CRA assessment) + the technical-depth corpus for the sub_topic
# (code_security for secure-dev, else network_security). All atom-grain.
# isms/dora/kritis are also atom-grain — available for future per-regime routing.
_TECHNICAL_USECASE = {"secure_development": "code_security"}  # default: network_security


def subtopic_for(req_id: str):
    return _REQ_TO_SUBTOPIC.get(req_id)


def usecases_for(sub_topic: str) -> list:
    return ["cra", _TECHNICAL_USECASE.get(sub_topic, "network_security")]


# Process-level memo for the (use_case, sub_topic) breadth lists. The atom corpus
# is static reference data, so it is safe to reuse across requests — this turns the
# warm path into zero DB work; only the first call after a (re)start pays for it.
_BREADTH_CACHE: dict = {}        # (use_case, sub_topic) -> (monotonic_ts, [controls])
_BREADTH_TTL = 1800.0


def enrich_findings_with_breadth(mapped: list, db, per_use_case: int = 3) -> None:
    """Attach `sub_topic` + `regulatory_breadth` (atom controls from the CRA corpus
    + the technical-depth corpus) to each finding, each control tagged with its
    use_case. The needed (use_case, sub_topic) pairs are fetched in ONE batched
    query (process-cached); the old path ran ~6 queries per pair (latency #61).
    Best-effort: on any error a finding just gets empty breadth — never breaks the
    assessment.
    """
    now = time.monotonic()
    needed: set = set()
    for m in mapped:
        st = _REQ_TO_SUBTOPIC.get(m.get("primary_requirement"))
        m["sub_topic"] = st
        if not st:
            m["regulatory_breadth"] = []
            continue
        for uc in usecases_for(st):
            key = (uc, st)
            hit = _BREADTH_CACHE.get(key)
            if not hit or now - hit[0] >= _BREADTH_TTL:
                needed.add(key)

    if needed:
        try:
            fetched = UseCaseControlsService(db).breadth_controls_batch(
                needed, per=per_use_case)
        except Exception:
            fetched = {}
        for key in needed:                       # cache hits AND empty results
            _BREADTH_CACHE[key] = (now, fetched.get(key, []))

    for m in mapped:
        st = m.get("sub_topic")
        if not st:
            continue
        merged, seen = [], set()
        for uc in usecases_for(st):
            cached = _BREADTH_CACHE.get((uc, st))
            for c in (cached[1] if cached else []):
                cid = c.get("control_id")
                if cid and cid not in seen:
                    seen.add(cid)
                    merged.append(c)
        m["regulatory_breadth"] = merged
