from __future__ import annotations

from typing import Any
from uuid import NAMESPACE_URL, uuid5

from scripts.rectification.candidate_feature_service import build_candidate_feature_snapshot
from scripts.rectification.contracts import EVENT_CONTRACT_VERSION, RectificationRequest
from scripts.rectification.decision_policy import (
    EXECUTION_LEDGER_VERSION,
    POLICY_VERSION,
    build_candidate_decisions,
    build_decision_receipt,
    build_execution_ledger,
)
from scripts.rectification.diagnostics_service import run_diagnostics
from scripts.rectification.scoring_service import (
    ALGORITHM_VERSION,
    build_event_contribution_matrix,
    calculation_spec,
    score_from_matrix,
    scoreable_request,
    sha256,
)


def candidate_features(request: RectificationRequest) -> dict[str, Any]:
    spec = calculation_spec(request)
    spec_hash = sha256(spec)
    scoring_request = scoreable_request(request)
    return {
        "algorithm_version": ALGORITHM_VERSION,
        "event_contract_version": EVENT_CONTRACT_VERSION,
        "decision_policy_version": POLICY_VERSION,
        "calculation_spec": spec,
        "calculation_spec_hash": spec_hash,
        "candidate_feature_snapshot": build_candidate_feature_snapshot(scoring_request, spec_hash),
        "can_confirm_exact_minute": False,
    }


def score_candidates(request: RectificationRequest) -> dict[str, Any]:
    scoring_request = scoreable_request(request)
    built = build_event_contribution_matrix(scoring_request)
    rows = score_from_matrix(scoring_request, built)
    spec = calculation_spec(request)
    spec_hash = sha256(spec)
    diagnostic_values = run_diagnostics(scoring_request, rows, built)
    fingerprint = sha256(request)
    result_id = str(uuid5(NAMESPACE_URL, f"{ALGORITHM_VERSION}:{fingerprint}"))
    candidate_decisions = build_candidate_decisions(rows, result_id=result_id)
    decision_receipt = build_decision_receipt(request, candidate_decisions, built, diagnostic_values)
    execution_ledger = build_execution_ledger(request, built, diagnostic_values, candidate_decisions)
    representative = candidate_decisions[0] if candidate_decisions else None
    return {
        "result_id": result_id,
        "algorithm_version": ALGORITHM_VERSION,
        "event_contract_version": EVENT_CONTRACT_VERSION,
        "decision_policy_version": POLICY_VERSION,
        "calculation_spec": spec,
        "calculation_spec_hash": spec_hash,
        "candidate_scores": [{
            "time": row["time"],
            "score": row["score"],
            "supporting_event_ids": [item["event_id"] for item in row["evidence"] if item["points"] > 0],
            "conflicting_event_ids": [item["event_id"] for item in row["evidence"] if item["points"] < 0],
        } for row in rows],
        "candidate_decisions": candidate_decisions,
        "candidate_decision_receipt": decision_receipt,
        "decision_receipt": decision_receipt,
        "execution_ledger_version": EXECUTION_LEDGER_VERSION,
        "execution_ledger": execution_ledger,
        "event_contribution_matrix": built["matrix"],
        "candidate_feature_snapshot": build_candidate_feature_snapshot(
            scoring_request, spec_hash, built.get("static_contexts")
        ),
        "diagnostics": diagnostic_values,
        "robustness": {
            "neighbor_support_minutes": diagnostic_values.get("neighbor_support_minutes", 0),
            "leave_one_out_retention_rate": diagnostic_values.get("leave_one_event_out_retention_rate", 0),
            "leave_one_domain_out_retention_rate": diagnostic_values.get("leave_one_domain_out_retention_rate", 0),
            "date_sensitivity_retention_rate": diagnostic_values.get("date_sensitivity_retention_rate", 0),
        },
        "missing_layers": built["missing_layers"],
        "display_allowed": decision_receipt["display_allowed"],
        "selection_allowed": decision_receipt["selection_allowed"],
        "acceptance_allowed": decision_receipt["acceptance_allowed"],
        "propose_allowed": decision_receipt["propose_allowed"],
        "confirmation_allowed": decision_receipt["confirmation_allowed"],
        "representative_candidate_id": representative["candidate_id"] if representative else None,
        "representative_time": representative["time"] if representative else None,
        "overall_confidence": decision_receipt["overall_confidence"],
        "margin_percent": decision_receipt["margin_percent"],
        "can_confirm_exact_minute": decision_receipt["confirmation_allowed"],
    }


def diagnostics(request: RectificationRequest) -> dict[str, Any]:
    scored = score_candidates(request)
    return {
        "result_id": scored["result_id"],
        "algorithm_version": scored["algorithm_version"],
        "event_contract_version": scored["event_contract_version"],
        "decision_policy_version": scored["decision_policy_version"],
        "calculation_spec_hash": scored["calculation_spec_hash"],
        "candidate_decisions": scored["candidate_decisions"],
        "candidate_decision_receipt": scored["candidate_decision_receipt"],
        "decision_receipt": scored["decision_receipt"],
        "execution_ledger_version": scored["execution_ledger_version"],
        "execution_ledger": scored["execution_ledger"],
        "diagnostics": scored["diagnostics"],
        "missing_layers": scored["missing_layers"],
        "display_allowed": scored["display_allowed"],
        "selection_allowed": scored["selection_allowed"],
        "acceptance_allowed": scored["acceptance_allowed"],
        "propose_allowed": scored["propose_allowed"],
        "confirmation_allowed": scored["confirmation_allowed"],
        "representative_candidate_id": scored["representative_candidate_id"],
        "representative_time": scored["representative_time"],
        "overall_confidence": scored["overall_confidence"],
        "margin_percent": scored["margin_percent"],
        "can_confirm_exact_minute": scored["confirmation_allowed"],
    }