from __future__ import annotations

import re
from decimal import Decimal, InvalidOperation
from typing import Any, Optional, Sequence

from ...browser.auth import ensure_cookies
from ...browser.client import connect, new_context, new_page
from ...browser.navigation import goto_with_auth_check
from ...core import AccountSummary, Envelope, ErrorType, Lot, Position, fail, ok
from ...core.config import get_playwright_url, load_config

POSITIONS_URL = "https://client.schwab.com/app/accounts/positions/#/"


def _parse_decimal(value: str | None) -> Optional[Decimal]:
    if not value:
        return None

    cleaned = value.strip()
    if not cleaned or cleaned in {"-", "--"}:
        return None

    negative = False
    if cleaned.startswith("(") and cleaned.endswith(")"):
        negative = True

    cleaned = (
        cleaned.replace("$", "")
        .replace(",", "")
        .replace("(", "")
        .replace(")", "")
        .replace("−", "-")
        .replace("%", "")
        .strip()
    )

    if not cleaned:
        return None

    try:
        parsed = Decimal(cleaned)
        if negative or parsed < 0:
            parsed = -abs(parsed)
        return parsed
    except InvalidOperation:
        return None


def _parse_float(value: str | None) -> Optional[float]:
    decimal_value = _parse_decimal(value)
    if decimal_value is None:
        return None
    try:
        return float(decimal_value)
    except (ValueError, InvalidOperation):
        return None


def _normalize_account_label(label: str) -> AccountSummary:
    normalized = re.sub(r"\s+", " ", label).strip()
    last4_match = re.search(r"(\d{3,4})\b", normalized.replace(" ", ""))
    last4 = last4_match.group(1)[-4:] if last4_match else None

    type_match = re.search(r"^[A-Za-z&'\- ]+", normalized)
    account_type = re.sub(r"\s+", "_", type_match.group(0).strip()) if type_match else "Account"

    account_id = f"{account_type}-{last4}" if last4 else account_type

    return AccountSummary(
        id=account_id,
        label=normalized,
        type=account_type,
        last4=last4,
        is_margin="margin" in normalized.lower(),
    )


def _match_account(candidate: AccountSummary, requested: AccountSummary | str | None) -> bool:
    if requested is None:
        return True

    if isinstance(requested, AccountSummary):
        requested_values = {
            requested.id.lower(),
            requested.label.lower(),
        }
        if requested.last4:
            requested_values.add(requested.last4.lower())
    else:
        lookup = requested.strip().lower()
        requested_values = {lookup}

    candidate_values = {candidate.id.lower(), candidate.label.lower()}
    if candidate.last4:
        candidate_values.add(candidate.last4.lower())

    return bool(candidate_values & requested_values)


def classify_asset(symbol: str | None, description: str | None) -> str:
    if symbol:
        sym = symbol.strip().upper()
    else:
        sym = ""
    desc = (description or "").strip().upper()

    if sym and re.fullmatch(r"[A-Z]{1,5}", sym):
        if "ETF" in desc:
            return "ETF"
        if any(kw in desc for kw in ["FUND", "MUTUAL"]):
            return "MUTUAL_FUND"
        return "EQUITY"

    if sym and re.search(r"\d", sym) and len(sym) > 5:
        return "OPTION"

    if any(kw in desc for kw in ["BOND", "CD", "TREASURY"]):
        return "BOND"

    if sym in {"CASH", "MMDA", "SWEEP"} or "CASH" in desc:
        return "CASH"

    if "ETF" in desc:
        return "ETF"
    if "FUND" in desc:
        return "MUTUAL_FUND"

    return "OTHER"


async def _evaluate_table(page) -> dict[str, Any] | None:
    return await page.evaluate(
        """
        () => {
            const table = document.querySelector('#positionsDetails');
            if (!table) {
                return null;
            }

            const headers = Array.from(table.querySelectorAll('thead tr th')).map((th) =>
                (th.innerText || th.textContent || '').trim()
            );

            const rowElements = Array.from(table.querySelectorAll('tbody tr'));
            const rows = [];
            let current = null;
            let currentAccount = null;

            const isLotRow = (row) => {
                const klass = (row.className || '').toLowerCase();
                if (klass.includes('lot') || klass.includes('sub') || klass.includes('child')) {
                    return true;
                }
                const dataRole = (row.getAttribute('data-row-type') || '').toLowerCase();
                return dataRole.includes('lot');
            };

            const isPositionRow = (row) => {
                const klass = (row.className || '').toLowerCase();
                return klass.includes('position-row');
            };

            const isAccountHeader = (row) => {
                const klass = (row.className || '').toLowerCase();
                const text = (row.textContent || '').trim();
                return !klass.includes('position-row') && 
                       (klass.includes('highlight-row') || klass.includes('border-top-dark')) &&
                       text.includes('account panel');
            };

            for (const row of rowElements) {
                // Check if this is an account header row
                if (isAccountHeader(row)) {
                    const text = row.textContent.trim();
                    // Extract account name from account panel text
                    const match = text.match(/account panel[\\s\\n]+([^\\n]+)/);
                    if (match) {
                        currentAccount = match[1].trim();
                    }
                    continue;
                }

                const cells = Array.from(row.querySelectorAll('td')).map((cell) =>
                    (cell.innerText || cell.textContent || '').trim()
                );

                if (!cells.length) {
                    continue;
                }

                if (isLotRow(row)) {
                    if (current) {
                        current.lots.push(cells);
                    }
                } else if (isPositionRow(row)) {
                    // Extract symbol from data-symbol attribute
                    const symbol = row.getAttribute('data-symbol') || '';
                    current = { 
                        type: 'position', 
                        cells: cells, 
                        lots: [],
                        symbol: symbol,
                        account: currentAccount
                    };
                    rows.push(current);
                }
            }

            return { headers, rows };
        }
        """
    )


def _map_row(headers: Sequence[str], cells: Sequence[str]) -> dict[str, str]:
    result: dict[str, str] = {}
    
    # Special handling: The table has columns in headers that don't correspond to cells
    # Headers: ['', 'Symbol', 'Description', 'Qty', 'Price', ...]
    # Cells:   ['VANGUARD...', '192.5', '$328.17', ...]
    # The first two headers (empty checkbox and Symbol) have no corresponding cells
    # So: Cell 0 → 'Description', Cell 1 → 'Qty', Cell 2 → 'Price', etc.
    
    # Find the symbol header index to know where the offset starts
    symbol_header_idx = None
    for idx, header in enumerate(headers):
        key = header.strip().lower()
        if 'symbol' in key and 'description' not in key:
            symbol_header_idx = idx
            break
    
    # Calculate offset - typically 2 (empty column + symbol column)
    offset = symbol_header_idx + 1 if symbol_header_idx is not None else 0
    
    for idx, header in enumerate(headers):
        # Normalize header: take first line, strip, lowercase
        # Headers often have format "Label\nsort\nfieldname"
        header_parts = header.strip().split('\n')
        key = header_parts[0].strip().lower() if header_parts else ""
        if not key:
            key = f"column_{idx}"
        
        # Map header to cell with offset
        if idx < offset:
            # These headers (empty, symbol) have no corresponding cells
            value = ""
        else:
            cell_idx = idx - offset
            value = cells[cell_idx].strip() if cell_idx < len(cells) else ""
            
        result[key] = value
    return result


def _parse_lots(lot_rows: Sequence[Sequence[str]]) -> list[Lot]:
    lots: list[Lot] = []
    for cells in lot_rows:
        if not cells:
            continue

        acquired_date = cells[0].strip() if len(cells) > 0 else None
        quantity = _parse_float(cells[1] if len(cells) > 1 else None)
        cost_basis = _parse_decimal(cells[2] if len(cells) > 2 else None)
        lot_id = cells[3].strip() if len(cells) > 3 else None

        lots.append(
            Lot(
                acquired_date=acquired_date or None,
                quantity=quantity,
                cost_basis=cost_basis,
                lot_id=lot_id or None,
            )
        )
    return lots


def _row_to_position(row_map: dict[str, str], lots_rows: Sequence[Sequence[str]], symbol: str = "") -> Position:
    # Symbol is now passed from data-symbol attribute on row
    # Description is in the first visible cell
    description = row_map.get('description') or row_map.get('name') or row_map.get('column_1') or ""
    
    # Price is typically in column labeled 'price' or similar
    market_price = _parse_decimal(
        row_map.get('price')
        or row_map.get('market price')
        or row_map.get('last price')
    )

    # Quantity - now in different column due to layout change
    quantity = _parse_float(row_map.get('quantity') or row_map.get('qty'))
    market_value = _parse_decimal(row_map.get('market value') or row_map.get('mkt val'))
    cost_basis_total = _parse_decimal(row_map.get('cost basis') or row_map.get('total cost'))
    unrealized_gain = _parse_decimal(
        row_map.get('gain/loss $')
        or row_map.get('unrealized gain')
        or row_map.get('gain/loss')
    )
    unrealized_gain_pct = _parse_float(
        row_map.get('gain/loss %')
        or row_map.get('unrealized gain %')
    )

    asset_type = classify_asset(symbol, description)

    lots = _parse_lots(lots_rows)

    return Position(
        symbol=symbol or "",
        description=description or None,
        asset_type=asset_type,
        quantity=quantity,
        market_price=market_price,
        market_value=market_value,
        cost_basis_total=cost_basis_total,
        unrealized_gain=unrealized_gain,
        unrealized_gain_pct=unrealized_gain_pct,
        lots=lots,
    )


async def get_positions(
    account: AccountSummary | str | None = None,
    *,
    include_non_equity: bool = False,
    debug: bool = False,
) -> Envelope[list[Position]]:
    cookies = await ensure_cookies()
    if not cookies:
        return fail("Unable to establish Schwab session.", ErrorType.AUTHENTICATION, retryable=False)

    config = load_config()
    playwright_url = get_playwright_url(config)

    playwright = browser = context = page = None
    try:
        playwright, browser = await connect(playwright_url)
        context = await new_context(browser, cookies=cookies)
        page = await new_page(context)

        if not await goto_with_auth_check(page, context, POSITIONS_URL, debug=debug):
            return fail("Failed to load Schwab positions page.", ErrorType.AUTHENTICATION, retryable=True)

        await page.wait_for_selector('#positionsDetails', timeout=45000)
        await page.wait_for_timeout(1000)
        await page.evaluate('window.scrollTo(0, document.body.scrollHeight)')
        await page.wait_for_timeout(1500)

        table_data = await _evaluate_table(page)
        if not table_data:
            return fail("Unable to locate positions table.", ErrorType.PARSING, retryable=True)

        headers = [header.strip().lower() for header in table_data.get('headers') or []]
        if not headers:
            return fail("Positions table headers not found.", ErrorType.PARSING, retryable=True)

        positions: list[Position] = []

        for row in table_data.get('rows', []):
            if row.get('type') != 'position':
                continue

            cells = row.get('cells') or []
            symbol = row.get('symbol') or ""
            account_label = row.get('account') or ""
            
            row_map = _map_row(headers, cells)
            position = _row_to_position(row_map, row.get('lots') or [], symbol=symbol)

            # Filter by account if requested
            if account is not None and account_label:
                # Normalize the account label from the row
                account_summary = _normalize_account_label(account_label)
                if not _match_account(account_summary, account):
                    continue
            elif account is not None and not account_label:
                # If filtering by account but row has no account, skip it
                continue

            if not include_non_equity and position.asset_type not in {"EQUITY", "ETF"}:
                continue

            positions.append(position)

        if not positions:
            return fail("No positions matched the requested criteria.", ErrorType.VALIDATION, retryable=False)

        return ok(positions)
    except Exception as exc:
        return fail(str(exc), ErrorType.UNKNOWN, retryable=True)
    finally:
        await _safe_close_page(page)
        await _safe_close_context(context)
        await _safe_close_browser(browser)
        await _safe_stop_playwright(playwright)


async def _safe_close_page(page) -> None:
    if page is None:
        return
    try:
        await page.close()
    except Exception:
        pass


async def _safe_close_context(context) -> None:
    if context is None:
        return
    try:
        await context.close()
    except Exception:
        pass


async def _safe_close_browser(browser) -> None:
    if browser is None:
        return
    try:
        await browser.close()
    except Exception:
        pass


async def _safe_stop_playwright(playwright) -> None:
    if playwright is None:
        return
    try:
        await playwright.stop()
    except Exception:
        pass