"""Financial Modeling Prep API — ratios, peers, company news."""
import os
import requests
import streamlit as st
from dotenv import load_dotenv

load_dotenv()

BASE_URL = "https://financialmodelingprep.com/api/v3"


def _api_key() -> str:
    key = os.getenv("FMP_API_KEY", "")
    return key


def _get(endpoint: str, params: dict = None) -> dict | list | None:
    params = params or {}
    params["apikey"] = _api_key()
    try:
        resp = requests.get(f"{BASE_URL}{endpoint}", params=params, timeout=10)
        resp.raise_for_status()
        return resp.json()
    except Exception:
        return None


@st.cache_data(ttl=3600)
def get_key_ratios(ticker: str) -> dict:
    """Return latest TTM key ratios."""
    data = _get(f"/ratios-ttm/{ticker.upper()}")
    if data and isinstance(data, list) and len(data) > 0:
        return data[0]
    return {}


@st.cache_data(ttl=21600)
def get_peers(ticker: str) -> list[str]:
    """Return list of comparable ticker symbols."""
    data = _get(f"/stock_peers", params={"symbol": ticker.upper()})
    if data and isinstance(data, list) and len(data) > 0:
        return data[0].get("peersList", [])
    return []


@st.cache_data(ttl=3600)
def get_ratios_for_tickers(tickers: list[str]) -> list[dict]:
    """Return TTM ratios for a list of tickers (for comps table)."""
    results = []
    for t in tickers:
        data = _get(f"/ratios-ttm/{t}")
        if data and isinstance(data, list) and len(data) > 0:
            row = data[0]
            row["symbol"] = t
            results.append(row)
    return results


@st.cache_data(ttl=600)
def get_company_news(ticker: str, limit: int = 20) -> list[dict]:
    """Return recent news articles for a ticker."""
    data = _get("/stock_news", params={"tickers": ticker.upper(), "limit": limit})
    if data and isinstance(data, list):
        return data
    return []