from __future__ import annotations

from typing import Any, Dict

from tg_resume_db.extract.parse import (
    extract_contacts,
    extract_name_guess,
    extract_remote,
    extract_english,
    extract_roles_skills,
    extract_salary,
    extract_location_best_effort,
    extract_experience_years,
)


def _pick(sections: Dict[str, str] | None, key: str, fallback: str) -> str:
    if not sections:
        return fallback
    return sections.get(key) or fallback


def parse_resume(clean_text: str, sections: Dict[str, str] | None = None) -> Dict[str, Any]:
    header_text = _pick(sections, "header", clean_text)
    contacts_text = _pick(sections, "contacts", clean_text)
    about_text = _pick(sections, "about", clean_text)
    skills_text = _pick(sections, "skills", clean_text)
    exp_text = _pick(sections, "experience", clean_text)
    exp_scope = "\n".join([about_text, exp_text]).strip() or exp_text

    name = extract_name_guess(header_text)
    contacts_raw = extract_contacts(contacts_text)
    roles, skills = extract_roles_skills("\n".join([about_text, skills_text, exp_text]))

    remote = extract_remote(clean_text)
    english = extract_english(clean_text)
    location = extract_location_best_effort(clean_text)
    exp_years, exp_years_eng, exp_conf, exp_dbg = extract_experience_years(exp_scope)
    sal_min, sal_max, sal_conf, sal_dbg = extract_salary(clean_text)

    return {
        "name": name,
        "contacts_raw": contacts_raw,
        "remote": remote,
        "english": english,
        "roles": roles,
        "skills": skills,
        "location": location,
        "exp_years": exp_years,
        "exp_years_eng": exp_years_eng,
        "exp_conf": exp_conf,
        "exp_dbg": exp_dbg,
        "salary_min": sal_min,
        "salary_max": sal_max,
        "salary_conf": sal_conf,
        "salary_dbg": sal_dbg,
        "parse_method": "hh_template",
    }