"""Financial statements — Income Statement, Balance Sheet, Cash Flow."""
import numpy as np
import pandas as pd
import streamlit as st
from services.data_service import get_income_statement, get_balance_sheet, get_cash_flow
from utils.formatters import fmt_large

# Rows where a decline is actually good (e.g. costs, expenses)
_INVERSE_ROWS = {
    "cost of revenue", "cost of goods sold", "operating expenses",
    "selling general administrative", "research development",
    "interest expense", "income tax expense", "total expenses",
    "reconciled cost of revenue",
}


def _is_inverse(label: str) -> bool:
    return label.strip().lower() in _INVERSE_ROWS


def _fmt_cell(value) -> str:
    try:
        v = float(value)
    except (TypeError, ValueError):
        return "—"
    return fmt_large(v)


def _yoy_raw(current, previous):
    """Return raw float YoY % change, or None."""
    try:
        c, p = float(current), float(previous)
        if p == 0:
            return None
        return (c - p) / abs(p) * 100
    except (TypeError, ValueError):
        return None


def _yoy_str(pct) -> str:
    if pct is None:
        return "—"
    arrow = "▲" if pct >= 0 else "▼"
    return f"{arrow} {abs(pct):.1f}%"


def _build_statement(df: pd.DataFrame):
    """
    Returns (display_df, color_df).
    display_df: formatted string DataFrame for rendering.
    color_df:   same shape, cells are 'green', 'red', or '' for styling.
    """
    df = df.copy()
    df.columns = [str(c)[:10] for c in df.columns]
    cols = list(df.columns)

    display = pd.DataFrame(index=df.index)
    colors = pd.DataFrame(index=df.index)

    for i, col in enumerate(cols):
        display[col] = df[col].apply(_fmt_cell)
        colors[col] = ""

        if i + 1 < len(cols):
            prev_col = cols[i + 1]
            yoy_label = f"YoY {col[:4]}"

            raw_yoy = df.apply(lambda row: _yoy_raw(row[col], row[prev_col]), axis=1)
            display[yoy_label] = raw_yoy.apply(_yoy_str)

            def cell_color(row_label, pct):
                if pct is None:
                    return ""
                inverse = _is_inverse(row_label)
                positive_change = pct >= 0
                good = positive_change if not inverse else not positive_change
                return "green" if good else "red"

            colors[yoy_label] = pd.Series(
                [cell_color(idx, pct) for idx, pct in zip(df.index, raw_yoy)],
                index=df.index,
            )

    return display, colors


def _style(display: pd.DataFrame, colors: pd.DataFrame):
    GREEN_BG = "background-color: rgba(46, 204, 113, 0.18); color: #7ce3a1;"
    RED_BG   = "background-color: rgba(231, 76,  60,  0.18); color: #ff8a8a;"

    def apply_colors(row):
        return [
            GREEN_BG if colors.loc[row.name, col] == "green"
            else RED_BG if colors.loc[row.name, col] == "red"
            else ""
            for col in display.columns
        ]

    return display.style.apply(apply_colors, axis=1)


def render_financials(ticker: str):
    col1, col2 = st.columns([1, 3])
    with col1:
        freq = st.radio("Frequency", ["Annual", "Quarterly"], horizontal=False)
    quarterly = freq == "Quarterly"

    tab_income, tab_balance, tab_cashflow = st.tabs(
        ["Income Statement", "Balance Sheet", "Cash Flow"]
    )

    with tab_income:
        df = get_income_statement(ticker, quarterly=quarterly)
        if df.empty:
            st.info("Income statement data unavailable.")
        else:
            display, colors = _build_statement(df)
            st.dataframe(_style(display, colors), use_container_width=True)

    with tab_balance:
        df = get_balance_sheet(ticker, quarterly=quarterly)
        if df.empty:
            st.info("Balance sheet data unavailable.")
        else:
            display, colors = _build_statement(df)
            st.dataframe(_style(display, colors), use_container_width=True)

    with tab_cashflow:
        df = get_cash_flow(ticker, quarterly=quarterly)
        if df.empty:
            st.info("Cash flow data unavailable.")
        else:
            display, colors = _build_statement(df)
            st.dataframe(_style(display, colors), use_container_width=True)