Fix build: Bundle schwab_scraper source and use local dependencies

schwab_scraper/features/accounts_positions/__init__.py

@@ -0,0 +1,14 @@
+"""Unified accounts and positions feature package."""
+
+from .accounts_scraper import list_accounts
+from .overview_scraper import get_account_overview
+from .positions_scraper import get_positions
+from .portfolio_scraper import get_portfolio_snapshot
+
+__all__ = [
+    "list_accounts",
+    "get_account_overview",
+    "get_positions",
+    "get_portfolio_snapshot",
+]
+

schwab_scraper/features/accounts_positions/accounts_scraper.py

@@ -0,0 +1,153 @@
+from __future__ import annotations
+
+import asyncio
+import re
+from typing import Optional
+
+from ...core import AccountSummary, Envelope, ErrorType, fail, ok
+from ...browser.client import connect, new_context, new_page
+from ...browser.navigation import goto_with_auth_check
+from ...browser.auth import ensure_cookies
+from ...core.config import get_playwright_url, load_config
+
+# Use the same URL as transactions feature for consistency and reliability
+TRANSACTION_HISTORY_URL = "https://client.schwab.com/app/accounts/history/#/"
+
+
+def _normalize_account_option(text: str, value: str) -> Optional[AccountSummary]:
+    text = text.strip()
+    if not text:
+        return None
+
+    normalized_text = re.sub(r"\s+", " ", text)
+
+    last4_match = re.search(r"(\d{3,4})", normalized_text.replace(" ", ""))
+    last4 = last4_match.group(1)[-4:] if last4_match else None
+
+    type_match = re.search(r"^([A-Za-z&'\- ]+)", normalized_text)
+    account_type = (type_match.group(1).strip() if type_match else "Account").replace(" ", "_")
+
+    account_id_candidates = [candidate for candidate in (value.strip(), last4, normalized_text) if candidate]
+    account_id = account_id_candidates[0] if account_id_candidates else normalized_text
+
+
+    label = normalized_text
+    is_margin = "margin" in normalized_text.lower()
+
+    return AccountSummary(
+        id=account_id,
+        label=label,
+        type=account_type,
+        last4=last4,
+        is_margin=is_margin,
+    )
+
+
+async def list_accounts(debug: bool = False) -> Envelope[list[AccountSummary]]:
+    """
+    Discover accounts from Schwab transaction history page.
+
+    Uses the robust account discovery logic from the transactions feature
+    which handles multiple selector patterns and has enhanced reliability.
+    """
+    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, TRANSACTION_HISTORY_URL, debug=debug):
+            return fail("Failed to load transaction history for account discovery.", ErrorType.AUTHENTICATION, retryable=True)
+
+        # Allow page to fully load
+        await asyncio.sleep(2)
+
+        # Use the robust account discovery from transactions feature
+        from ..transactions.scraper import discover_accounts_from_page
+
+        discovered_accounts = await discover_accounts_from_page(page, debug=debug)
+
+        if not discovered_accounts:
+            return fail("Account dropdown not found on transaction history page.", ErrorType.PARSING, retryable=True)
+
+        # Convert discovered accounts to AccountSummary objects
+        accounts: list[AccountSummary] = []
+        seen_ids: set[str] = set()
+
+        for acc in discovered_accounts:
+            # Create AccountSummary from discovered account info
+            account_id = acc.get('ending', acc.get('label', ''))
+
+            if account_id and account_id not in seen_ids:
+                summary = AccountSummary(
+                    id=account_id,
+                    label=acc.get('label', ''),
+                    type=acc.get('type', 'Account'),
+                    last4=acc.get('ending', ''),
+                    is_margin=False,  # Will be enhanced in future if needed
+                )
+                accounts.append(summary)
+                seen_ids.add(account_id)
+
+        if not accounts:
+            return fail("No accounts discovered from Schwab transaction history.", ErrorType.PARSING, retryable=True)
+
+        if debug:
+            print(f"DEBUG: Successfully discovered {len(accounts)} accounts:")
+            for acc in accounts:
+                print(f"DEBUG: - {acc.label} (type: {acc.type}, last4: {acc.last4})")
+
+        return ok(accounts)
+    except Exception as exc:
+        if debug:
+            print(f"DEBUG: Account discovery error: {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
+

schwab_scraper/features/accounts_positions/overview_scraper.py

@@ -0,0 +1,426 @@
+from __future__ import annotations
+
+import asyncio
+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 AccountOverview, AccountSummary, Envelope, ErrorType, fail, ok
+from ...core.config import get_playwright_url, load_config
+
+SUMMARY_URL = "https://client.schwab.com/accounts/summary/summary.aspx/"
+
+
+def _parse_currency(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(",", "")
+    cleaned = cleaned.replace("(", "").replace(")", "")
+    cleaned = cleaned.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_percentage(value: str | None) -> Optional[float]:
+    if not value:
+        return None
+    cleaned = value.strip()
+    if not cleaned:
+        return None
+
+    negative = False
+    if cleaned.startswith("(") and cleaned.endswith(")"):
+        negative = True
+
+    cleaned = cleaned.replace("%", "").replace("(", "").replace(")", "")
+    cleaned = cleaned.replace("−", "-").strip()
+
+    if not cleaned:
+        return None
+
+    try:
+        parsed = float(cleaned)
+    except ValueError:
+        return None
+
+    if negative or parsed < 0:
+        parsed = -abs(parsed)
+    return parsed
+
+
+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 _rows_to_dicts(headers: Sequence[str], rows: Sequence[Sequence[str]]) -> list[dict[str, str]]:
+    normalized_headers = [header.strip().lower() for header in headers]
+    results: list[dict[str, str]] = []
+    for row in rows:
+        row_map: dict[str, str] = {}
+        for idx, header in enumerate(normalized_headers):
+            if idx < len(row):
+                row_map[header] = row[idx].strip()
+        results.append(row_map)
+    return results
+
+
+async def _extract_table(page) -> dict[str, Any] | None:
+    return await page.evaluate(
+        """
+        () => {
+            const wrapper = document.querySelector('.sdps-tables__wrapper');
+            if (!wrapper) {
+                return null;
+            }
+
+            const headerRow = wrapper.querySelector('.sdps-tables__row--header');
+            const headers = headerRow
+                ? Array.from(headerRow.querySelectorAll('.sdps-tables__header-text'))
+                      .map((el) => (el.textContent || '').trim())
+                : [];
+
+            if (!headers.length) {
+                const legacyHeaders = wrapper.querySelectorAll('thead th');
+                if (legacyHeaders.length) {
+                    for (const th of legacyHeaders) {
+                        headers.push((th.textContent || '').trim());
+                    }
+                }
+            }
+
+            const bodyRows = wrapper.querySelectorAll('.sdps-tables__row--body');
+            const rows = [];
+            if (bodyRows.length) {
+                bodyRows.forEach((row) => {
+                    const cells = Array.from(
+                        row.querySelectorAll('.sdps-tables__cell, div[role="cell"], td')
+                    ).map((cell) => (cell.textContent || '').trim());
+                    rows.push(cells);
+                });
+            }
+
+            if (!rows.length) {
+                const fallbackRows = wrapper.querySelectorAll('tbody tr');
+                fallbackRows.forEach((row) => {
+                    const cells = Array.from(row.querySelectorAll('td')).map((cell) => (cell.textContent || '').trim());
+                    if (cells.length) {
+                        rows.push(cells);
+                    }
+                });
+            }
+
+            return { headers, rows };
+        }
+        """
+    )
+
+
+async def _extract_totals(page) -> dict[str, str | None]:
+    return await page.evaluate(
+        r"""
+        () => {
+            const result = { total: null, dayChange: null, dayChangePct: null, cash: null };
+
+            const totalLabel = document.querySelector('#total-value-label');
+            if (totalLabel) {
+                const valueEl = totalLabel.closest('[class*="sdps-panel"], h2, div');
+                if (valueEl) {
+                    const currencyMatch = valueEl.textContent?.match(/\$[\d,]+\.?\d*/);
+                    if (currencyMatch) {
+                        result.total = currencyMatch[0];
+                    }
+                }
+            }
+
+            const dayChangeLabel = document.querySelector('#day-change-label');
+            if (dayChangeLabel) {
+                const container = dayChangeLabel.parentElement;
+                if (container) {
+                    const matchCurrency = container.textContent?.match(/\$[\d,]+\.?\d*/);
+                    const matchPct = container.textContent?.match(/-?\d+(?:\.\d+)?%/);
+                    if (matchCurrency) {
+                        result.dayChange = matchCurrency[0];
+                    }
+                    if (matchPct) {
+                        result.dayChangePct = matchPct[0];
+                    }
+                }
+            }
+
+            const cashLabel = Array.from(document.querySelectorAll('.sdps-tables__header-text')).find((el) =>
+                el.textContent?.toLowerCase().includes('cash & cash investments')
+            );
+            if (cashLabel) {
+                const container = cashLabel.closest('div');
+                if (container) {
+                    const matchCurrency = container.textContent?.match(/\$[\d,]+\.?\d*/);
+                    if (matchCurrency) {
+                        result.cash = matchCurrency[0];
+                    }
+                }
+            }
+
+            return result;
+        }
+        """
+    )
+
+
+def _row_to_overview(row_map: dict[str, str]) -> tuple[AccountSummary, AccountOverview]:
+    label = row_map.get('name') or row_map.get('account') or row_map.get('account name') or row_map.get('', '')
+    label = label or "Account"
+
+    account_summary = _normalize_account_label(label)
+
+    total_value = _parse_currency(
+        row_map.get('account value')
+        or row_map.get('total value')
+        or row_map.get('market value')
+    )
+
+    day_change = _parse_currency(
+        row_map.get('day change $')
+        or row_map.get('day change')
+        or row_map.get('day change amount')
+    )
+
+    day_change_pct = _parse_percentage(
+        row_map.get('day change %')
+        or row_map.get('day change percent')
+    )
+
+    cash_value = _parse_currency(
+        row_map.get('cash & cash investments')
+        or row_map.get('cash')
+    )
+
+    settled_cash = _parse_currency(row_map.get('settled cash'))
+    buying_power = _parse_currency(row_map.get('buying power') or row_map.get('available to trade'))
+    margin_balance = _parse_currency(row_map.get('margin balance') or row_map.get('margin'))
+
+    overview = AccountOverview(
+        account=account_summary,
+        total_value=total_value,
+        day_change=day_change,
+        day_change_pct=day_change_pct,
+        cash=cash_value,
+        settled_cash=settled_cash,
+        buying_power=buying_power,
+        margin_balance=margin_balance,
+    )
+
+    return account_summary, overview
+
+
+async def get_account_overview(
+    account: AccountSummary | str | None = None, *, debug: bool = False
+) -> Envelope[AccountOverview]:
+    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, SUMMARY_URL, debug=debug):
+            return fail("Failed to load Schwab account summary page.", ErrorType.AUTHENTICATION, retryable=True)
+
+        await asyncio.sleep(1)
+
+        table_data = await _extract_table(page)
+        if not table_data:
+            return fail("Unable to locate account overview table.", ErrorType.PARSING, retryable=True)
+
+        row_dicts = _rows_to_dicts(table_data["headers"], table_data["rows"])
+        matched_overviews: list[AccountOverview] = []
+
+        for row_map in row_dicts:
+            # Skip empty rows or totals indicated by lack of numeric data
+            values = "".join(row_map.values())
+            if not values:
+                continue
+
+            summary, overview = _row_to_overview(row_map)
+            if _match_account(summary, account):
+                matched_overviews.append(overview)
+
+        if not matched_overviews:
+            return fail("Account not found in overview table.", ErrorType.VALIDATION, retryable=False)
+
+        if account is None and len(matched_overviews) > 1:
+            aggregated = _aggregate_overviews(matched_overviews)
+            totals = await _extract_totals(page)
+            if totals:
+                if totals.get("total"):
+                    aggregated.total_value = _parse_currency(totals.get("total"))
+                if totals.get("dayChange"):
+                    aggregated.day_change = _parse_currency(totals.get("dayChange"))
+                if totals.get("dayChangePct"):
+                    aggregated.day_change_pct = _parse_percentage(totals.get("dayChangePct"))
+                if totals.get("cash"):
+                    aggregated.cash = _parse_currency(totals.get("cash"))
+            return ok(aggregated)
+
+        return ok(matched_overviews[0])
+    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)
+
+
+def _aggregate_overviews(overviews: Sequence[AccountOverview]) -> AccountOverview:
+    total_value = Decimal("0")
+    day_change = Decimal("0")
+    cash_total = Decimal("0")
+    settled_total = Decimal("0")
+    buying_total = Decimal("0")
+    margin_total = Decimal("0")
+
+    for item in overviews:
+        if item.total_value is not None:
+            total_value += item.total_value
+        if item.day_change is not None:
+            day_change += item.day_change
+        if item.cash is not None:
+            cash_total += item.cash
+        if item.settled_cash is not None:
+            settled_total += item.settled_cash
+        if item.buying_power is not None:
+            buying_total += item.buying_power
+        if item.margin_balance is not None:
+            margin_total += item.margin_balance
+
+    aggregated_summary = AccountSummary(
+        id="AGGREGATE",
+        label="All Accounts",
+        type="AGGREGATE",
+        last4=None,
+        is_margin=False,
+    )
+
+    total_value_out = total_value if total_value != 0 else None
+    day_change_out = day_change if day_change != 0 else None
+    cash_out = cash_total if cash_total != 0 else None
+    settled_out = settled_total if settled_total != 0 else None
+    buying_out = buying_total if buying_total != 0 else None
+    margin_out = margin_total if margin_total != 0 else None
+
+    day_change_pct: Optional[float] = None
+    if total_value_out and day_change_out:
+        try:
+            day_change_pct = float((day_change_out / total_value_out) * 100)
+        except (InvalidOperation, ZeroDivisionError):
+            day_change_pct = None
+
+    return AccountOverview(
+        account=aggregated_summary,
+        total_value=total_value_out,
+        day_change=day_change_out,
+        day_change_pct=day_change_pct,
+        cash=cash_out,
+        settled_cash=settled_out,
+        buying_power=buying_out,
+        margin_balance=margin_out,
+    )
+
+
+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
+

schwab_scraper/features/accounts_positions/portfolio_scraper.py

@@ -0,0 +1,134 @@
+from __future__ import annotations
+
+from decimal import Decimal, InvalidOperation
+from typing import Iterable, Optional
+
+from ...core import AccountSummary, Envelope, ErrorType, PortfolioSnapshot, Position, fail, ok
+from .positions_scraper import get_positions
+
+
+def _aggregate_positions(positions: Iterable[Position]) -> tuple[list[Position], Optional[Decimal]]:
+    aggregated: dict[str, Position] = {}
+    total_value = Decimal("0")
+    has_value = False
+
+    for position in positions:
+        if position.market_value is not None:
+            total_value += position.market_value
+            has_value = True
+
+        key = position.symbol.upper() if position.symbol else "UNKNOWN"
+        if key not in aggregated:
+            aggregated[key] = Position(
+                symbol=position.symbol,
+                description=position.description,
+                asset_type=position.asset_type,
+                quantity=position.quantity,
+                market_price=position.market_price,
+                market_value=position.market_value,
+                cost_basis_total=position.cost_basis_total,
+                unrealized_gain=position.unrealized_gain,
+                unrealized_gain_pct=position.unrealized_gain_pct,
+                lots=list(position.lots),
+            )
+            continue
+
+        existing = aggregated[key]
+
+        if position.quantity is not None:
+            if existing.quantity is None:
+                existing.quantity = position.quantity
+            else:
+                existing.quantity += position.quantity
+
+        if position.market_value is not None:
+            if existing.market_value is None:
+                existing.market_value = position.market_value
+            else:
+                existing.market_value += position.market_value
+
+        if position.cost_basis_total is not None:
+            if existing.cost_basis_total is None:
+                existing.cost_basis_total = position.cost_basis_total
+            else:
+                existing.cost_basis_total += position.cost_basis_total
+
+        if position.unrealized_gain is not None:
+            if existing.unrealized_gain is None:
+                existing.unrealized_gain = position.unrealized_gain
+            else:
+                existing.unrealized_gain += position.unrealized_gain
+
+        if position.market_price is not None:
+            existing.market_price = position.market_price
+
+        if position.unrealized_gain_pct is not None:
+            existing.unrealized_gain_pct = position.unrealized_gain_pct
+
+        if position.description and not existing.description:
+            existing.description = position.description
+
+        if position.asset_type:
+            existing.asset_type = position.asset_type
+
+        if position.lots:
+            existing.lots.extend(position.lots)
+
+    for item in aggregated.values():
+        if item.unrealized_gain is not None and item.cost_basis_total not in (None, Decimal("0")):
+            try:
+                item.unrealized_gain_pct = float((item.unrealized_gain / item.cost_basis_total) * 100)
+            except (InvalidOperation, ZeroDivisionError):
+                item.unrealized_gain_pct = None
+
+    total_value_out = total_value if has_value else None
+    return list(aggregated.values()), total_value_out
+
+
+async def get_portfolio_snapshot(
+    account: AccountSummary | str | None = None,
+    *,
+    aggregate_by_symbol: bool = True,
+    include_non_equity: bool = False,
+    debug: bool = False,
+) -> Envelope[PortfolioSnapshot]:
+    positions_envelope = await get_positions(
+        account=account,
+        include_non_equity=include_non_equity,
+        debug=debug,
+    )
+
+    if not positions_envelope["success"]:
+        return fail(
+            positions_envelope.get("error") or "Failed to retrieve positions.",
+            positions_envelope.get("error_type") or ErrorType.UNKNOWN,
+            positions_envelope.get("retryable", True),
+        )
+
+    positions = positions_envelope["data"] or []
+
+    if aggregate_by_symbol:
+        aggregated_positions, total_value = _aggregate_positions(positions)
+        count = len(aggregated_positions)
+        snapshot = PortfolioSnapshot(
+            equities=aggregated_positions,
+            total_value=total_value,
+            count=count,
+        )
+        return ok(snapshot)
+
+    total_value = Decimal("0")
+    has_value = False
+    for position in positions:
+        if position.market_value is not None:
+            total_value += position.market_value
+            has_value = True
+
+    total_value_out = total_value if has_value else None
+    snapshot = PortfolioSnapshot(
+        equities=positions,
+        total_value=total_value_out,
+        count=len(positions),
+    )
+    return ok(snapshot)
+

schwab_scraper/features/accounts_positions/positions_scraper.py

@@ -0,0 +1,432 @@
+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
+

schwab_scraper/features/equity/morningstar.py

@@ -0,0 +1,239 @@
+from typing import Optional, Tuple
+import logging
+
+
+async def find_report(page, debug: bool = False) -> Tuple[Optional[str], Optional[str]]:
+    """Locate the Morningstar Equity Report link and date on the stock page.
+    
+    Uses multiple fallback strategies to handle Schwab website changes.
+    
+    Returns:
+        Tuple of (url, date) where:
+        - url: The href attribute if it's a traditional link, or a special marker
+               '__CLICK_TO_OPEN__' if it's a JavaScript/blob link that requires clicking
+        - date: The report date string if found
+    """
+    logger = logging.getLogger(__name__)
+    
+    # Strategy 1: Original selector
+    report_link_selector = "div[id='Morningstar Equity Report'] a.sr-report-link"
+    if await page.is_visible(report_link_selector):
+        if debug:
+            logger.debug("Found Morningstar report using original selector")
+        report_link_element = page.locator(report_link_selector)
+        await report_link_element.scroll_into_view_if_needed()
+        url = await report_link_element.get_attribute("href")
+        
+        # Date element (escaped spaces)
+        date_locator = page.locator(r"#Morningstar\ Equity\ Report > span:nth-child(3) > sdps-date-time > time > span:nth-child(2)")
+        date_text = (await date_locator.inner_text()).strip() if await date_locator.count() > 0 else None
+        
+        # Check if href is empty (modern web component using blob URLs)
+        if not url or url == '':
+            if debug:
+                logger.debug("Link found but href is empty - this is a modern web component that generates blob URLs on click")
+            # Return a special marker to indicate we need to click the link to get the URL
+            return '__CLICK_TO_OPEN__', date_text
+        
+        return url, date_text
+    
+    # Strategy 2: Look for any link containing "morningstar" in research section
+    if debug:
+        logger.debug("Original selector failed, trying fallback selectors...")
+    
+    fallback_selectors = [
+        "a.sr-report-link[href*='morningstar']",
+        "a[href*='morningstar'][href*='pdf']",
+        "#morningstar-section a.sr-report-link",
+        "div[id*='Morningstar'] a",
+    ]
+    
+    for selector in fallback_selectors:
+        try:
+            if await page.is_visible(selector, timeout=2000):
+                if debug:
+                    logger.debug(f"Found Morningstar report using fallback selector: {selector}")
+                report_link_element = page.locator(selector).first
+                await report_link_element.scroll_into_view_if_needed()
+                url = await report_link_element.get_attribute("href")
+                
+                # Try to find date with various selectors
+                date_text = None
+                date_selectors = [
+                    r"#Morningstar\ Equity\ Report > span:nth-child(3) > sdps-date-time > time > span:nth-child(2)",
+                    "sdps-date-time time span",
+                    "time span",
+                ]
+                for date_sel in date_selectors:
+                    try:
+                        date_locator = page.locator(date_sel)
+                        if await date_locator.count() > 0:
+                            date_text = (await date_locator.first.inner_text()).strip()
+                            if date_text:
+                                break
+                    except:
+                        continue
+                
+                return url, date_text
+        except Exception as e:
+            if debug:
+                logger.debug(f"Fallback selector {selector} failed: {e}")
+            continue
+    
+    # Strategy 3: Use JavaScript to search for Morningstar links
+    if debug:
+        logger.debug("All CSS selectors failed, trying JavaScript search...")
+    
+    try:
+        result = await page.evaluate("""
+            () => {
+                // Look for any link containing 'morningstar' and 'pdf'
+                const links = Array.from(document.querySelectorAll('a[href]'));
+                const morningstarLink = links.find(link => 
+                    link.href.toLowerCase().includes('morningstar') && 
+                    link.href.toLowerCase().includes('pdf')
+                );
+                
+                if (morningstarLink) {
+                    // Try to find associated date
+                    let dateText = null;
+                    const parent = morningstarLink.closest('[id*="Morningstar"]') || morningstarLink.parentElement;
+                    if (parent) {
+                        const timeElement = parent.querySelector('time');
+                        if (timeElement) {
+                            dateText = timeElement.textContent.trim();
+                        }
+                    }
+                    
+                    return {
+                        url: morningstarLink.href,
+                        date: dateText
+                    };
+                }
+                
+                return null;
+            }
+        """)
+        
+        if result and result.get('url'):
+            if debug:
+                logger.debug(f"Found Morningstar report using JavaScript search: {result['url']}")
+            return result['url'], result.get('date')
+    except Exception as e:
+        if debug:
+            logger.debug(f"JavaScript search failed: {e}")
+    
+    # No report found
+    if debug:
+        logger.debug("No Morningstar report link found using any strategy")
+        # Capture page state for debugging
+        try:
+            await page.screenshot(path="debug_morningstar_not_found.png", full_page=True)
+            logger.debug("Saved debug screenshot to: debug_morningstar_not_found.png")
+            
+            # Log available elements for debugging
+            page_info = await page.evaluate("""
+                () => {
+                    return {
+                        hasMorningstarSection: !!document.querySelector('#morningstar-section'),
+                        hasMorningstarDiv: !!document.querySelector('div[id*="Morningstar"]'),
+                        morningstarLinks: Array.from(document.querySelectorAll('a[href]'))
+                            .filter(a => a.href.toLowerCase().includes('morningstar'))
+                            .length,
+                        allReportLinks: Array.from(document.querySelectorAll('a.sr-report-link')).length
+                    }
+                }
+            """)
+            logger.debug(f"Page state: {page_info}")
+        except Exception as e:
+            logger.debug(f"Failed to capture debug info: {e}")
+    
+    return None, None
+
+
+async def download_report_as_bytes(page, url: str, debug: bool = False) -> Optional[bytes]:
+    """Open the PDF in a new page and return bytes via data URL conversion.
+    
+    Args:
+        page: The current Playwright page
+        url: Either a traditional URL or '__CLICK_TO_OPEN__' marker for blob URLs
+        debug: Enable debug logging
+    
+    Returns:
+        PDF bytes if successful, None otherwise
+    """
+    logger = logging.getLogger(__name__)
+    
+    if not url:
+        return None
+    
+    # Handle blob URL case (modern web component)
+    if url == '__CLICK_TO_OPEN__':
+        if debug:
+            logger.debug("Handling blob URL - clicking link to open PDF")
+        
+        # Click the Morningstar report link to open the PDF
+        report_link_selector = "div[id='Morningstar Equity Report'] a.sr-report-link"
+        
+        try:
+            # Wait for new page to open after clicking
+            new_page_promise = page.context.wait_for_event("page", timeout=15000)
+            await page.click(report_link_selector)
+            new_page = await new_page_promise
+            
+            if debug:
+                logger.debug(f"New page opened with URL: {new_page.url}")
+            
+            # Wait for PDF to load
+            await new_page.wait_for_load_state('load', timeout=10000)
+            
+            # The PDF is now loaded as a blob URL - extract it
+            blob_url = new_page.url
+            
+        except Exception as e:
+            if debug:
+                logger.debug(f"Error clicking link to open PDF: {e}")
+            return None
+    else:
+        # Traditional URL case
+        if debug:
+            logger.debug(f"Opening PDF from traditional URL: {url}")
+        
+        new_page_promise = page.context.wait_for_event("page")
+        await page.evaluate("url => window.open(url, '_blank')", url)
+        new_page = await new_page_promise
+        await new_page.wait_for_load_state('load')
+        blob_url = url
+
+    # Fetch and convert to Base64 in browser context
+    try:
+        pdf_base64 = await new_page.evaluate(
+            """
+            async (url) => {
+                const response = await fetch(url);
+                const blob = await response.blob();
+                return await new Promise((resolve) => {
+                    const reader = new FileReader();
+                    reader.onloadend = () => resolve(reader.result.split(',')[1]);
+                    reader.readAsDataURL(blob);
+                });
+            }
+            """,
+            blob_url,
+        )
+        await new_page.close()
+        
+        if not pdf_base64:
+            return None
+        
+        import base64
+        return base64.b64decode(pdf_base64)
+        
+    except Exception as e:
+        if debug:
+            logger.debug(f"Error extracting PDF bytes: {e}")
+        try:
+            await new_page.close()
+        except:
+            pass
+        return None

schwab_scraper/features/equity/parser.py

@@ -0,0 +1,80 @@
+import re
+from io import BytesIO
+from typing import Dict
+import pdfplumber
+
+
+def clean_value(label: str, value: str) -> str:
+    """Cleans the extracted value based on the label."""
+    if label == "Morningstar Rating":
+        return f"{value.count('Q')} stars"
+    if label == "Economic Moat":
+        if "Wide" in value:
+            return "Wide"
+        if "Narrow" in value:
+            return "Narrow"
+        if "None" in value:
+            return "None"
+    if label in ["Fair Value", "1-Star Price", "5-Star Price"]:
+        match = re.match(r"[\d,]+\.\d{2}", value)
+        if match:
+            return match.group(0)
+    if label == "Assessment":
+        return value.split()[0]
+    if label == "52-Week-Range":
+        return value.replace('\u2014', '-')
+    if label == "52-Week Range":
+        return value.replace('\u2014', '-')
+    return value
+
+
+def parse(pdf_content: bytes) -> Dict[str, str]:
+    """
+    Parses a Morningstar PDF report to extract key data points.
+    Returns a dict keyed by the label names present in the report.
+    """
+    with pdfplumber.open(BytesIO(pdf_content)) as pdf:
+        page = pdf.pages[2]  # Page 3
+        words = page.extract_words(x_tolerance=1, y_tolerance=1, keep_blank_chars=False)
+
+        data: Dict[str, str] = {}
+        labels = [
+            "Fair Value", "1-Star Price", "5-Star Price", "Assessment",
+            "Dividend Yield", "Capital Allocation", "52-Week Range", "Investment Style",
+            "Economic Moat", "Morningstar Rating"
+        ]
+
+        for i, word in enumerate(words):
+            # Combine words to form potential labels
+            for j in range(i + 1, min(i + 4, len(words))):
+                potential_label = " ".join(w['text'] for w in words[i:j])
+                if potential_label in labels:
+                    if potential_label == "Economic Moat":
+                        # Find the value to the right of the label
+                        label_end_x = words[j-1]['x1']
+                        value_words = [
+                            w['text'] for w in words[j:]
+                            if abs(w['top'] - word['top']) < 2 and w['x0'] > label_end_x and w['x0'] - label_end_x < 100
+                        ]
+                        if value_words:
+                            value = " ".join(value_words)
+                            if "Wide" in value:
+                                data[potential_label] = "Wide"
+                            elif "Narrow" in value:
+                                data[potential_label] = "Narrow"
+                            elif "None" in value:
+                                data[potential_label] = "None"
+                            break
+                    else:
+                        # Find the value to the right of the label
+                        label_end_x = words[j-1]['x1']
+                        value_words = [
+                            w['text'] for w in words[j:]
+                            if abs(w['top'] - word['top']) < 2 and w['x0'] > label_end_x and w['x0'] - label_end_x < 100
+                        ]
+                        if value_words:
+                            # Join the value words and clean them
+                            value = " ".join(value_words)
+                            data[potential_label] = clean_value(potential_label, value)
+                            break  # Move to the next word once a label is found
+        return data

schwab_scraper/features/equity/phase1_api_scraper.py

@@ -0,0 +1,490 @@
+"""Phase 1: API-Based Data Extraction (EXPERIMENTAL - NON-FUNCTIONAL)
+
+⚠️ **STATUS: NON-FUNCTIONAL DUE TO CORS RESTRICTIONS** ⚠️
+
+This module was an attempt to extract equity data by calling Schwab's REST APIs directly.
+While the APIs exist and were discovered via HAR analysis, they are NOT accessible from 
+this scraper due to fundamental browser security limitations (CORS).
+
+## Why This Approach Failed:
+
+1. **CORS (Cross-Origin Resource Sharing) Restrictions**: 
+   - Research page: `client.schwab.com`, APIs: `ausgateway.schwab.com` (different origins)
+   - Browser blocks cross-origin fetch() calls even from page.evaluate()
+   - Results in "TypeError: Failed to fetch"
+
+2. **Authentication Complexity**:
+   - Direct HTTP (aiohttp) with cookies: 401/403 errors
+   - Playwright page.request.fetch(): 401 errors (separate context)
+   - Likely requires dynamic tokens beyond cookies
+
+## Recommendation:
+
+**Use `phase1_scraper.py` (DOM scraping) instead**. It works reliably with authenticated
+sessions and extracts all Phase 1 fields without CORS limitations.
+
+## API Endpoints (discovered but inaccessible):
+- Quote: /api/is.ResearchExperience/v1/quote
+- Dividends: /api/is.ResearchExperience/v1/events/dividends
+- Earnings: /api/is.ResearchExperience/v1/events/earnings
+- Share Profile: /api/is.ResearchExperience/v1/shareprofile
+"""
+
+from typing import Dict, Any, Optional, List
+import logging
+import uuid
+import aiohttp
+from playwright.async_api import Page
+
+from ...core import (
+    QuoteData, EnhancedDividends, EarningsData, 
+    CalculatedMetrics, EquityPhase1Data
+)
+
+logger = logging.getLogger(__name__)
+
+
+def _parse_float(value: Any) -> Optional[float]:
+    """Safely parse a value to float."""
+    if value is None:
+        return None
+    try:
+        if isinstance(value, str):
+            # Remove % sign if present
+            value = value.replace('%', '').strip()
+        return float(value)
+    except (ValueError, TypeError):
+        return None
+
+
+def _parse_market_cap(value: str) -> Optional[str]:
+    """Parse market cap string like '$3.03T' or '$462.11B'."""
+    if not value:
+        return None
+    # Keep the formatted string as-is for readability
+    return value.strip()
+
+
+def _parse_volume(value: Any) -> Optional[int]:
+    """Parse volume value."""
+    if value is None:
+        return None
+    try:
+        return int(float(value))
+    except (ValueError, TypeError):
+        return None
+
+
+def parse_quote_api_response(data: Dict[str, Any]) -> QuoteData:
+    """Parse quote API response into QuoteData object.
+    
+    API Response Structure:
+    {
+      "reference": {
+        "symbol": "JNJ",
+        "companyName": "JOHNSON & JOHNSON",
+        "exchangeName": "NYSE"
+      },
+      "quote": {
+        "lastPrice": 193.155,
+        "netChange": 1.275,
+        "netChangePercent": 0.6644778,
+        "postMarketChange": 0.0,
+        "postMarketPercentChange": 0.0,
+        "tradeTime": "2025-10-22T17:06:42.008Z"
+      },
+      "regularQuote": {
+        "lastPrice": 193.155,
+        "lastSize": 100.0,
+        "netChange": 1.275,
+        "percentChange": 0.6644778,
+        ...
+      }
+    }
+    """
+    quote = QuoteData()
+    
+    try:
+        reference = data.get('reference', {})
+        quote_data = data.get('quote', {})
+        regular_quote = data.get('regularQuote', {})
+        
+        # Basic info
+        quote.exchange = reference.get('exchangeName')
+        
+        # Price data
+        quote.price = _parse_float(quote_data.get('lastPrice'))
+        quote.change = _parse_float(quote_data.get('netChange'))
+        quote.change_percent = _parse_float(quote_data.get('netChangePercent'))
+        
+        # After hours (post market)
+        quote.after_hours_change = _parse_float(quote_data.get('postMarketChange'))
+        quote.after_hours_change_percent = _parse_float(quote_data.get('postMarketPercentChange'))
+        
+        # Extended quote data
+        quote.previous_close = _parse_float(regular_quote.get('closePrice'))
+        quote.open = _parse_float(regular_quote.get('openPrice'))
+        quote.bid = _parse_float(regular_quote.get('bidPrice'))
+        quote.ask = _parse_float(regular_quote.get('askPrice'))
+        quote.volume = _parse_volume(regular_quote.get('totalVolume'))
+        quote.day_range_low = _parse_float(regular_quote.get('lowPrice'))
+        quote.day_range_high = _parse_float(regular_quote.get('highPrice'))
+        quote.week_52_low = _parse_float(regular_quote.get('priceLow52W'))
+        quote.week_52_high = _parse_float(regular_quote.get('priceHigh52W'))
+        
+        # Bid/Ask size
+        bid_size = regular_quote.get('bidSize', 0)
+        ask_size = regular_quote.get('askSize', 0)
+        if bid_size or ask_size:
+            quote.bid_ask_size = f"{bid_size}/{ask_size}"
+        
+        # Volume vs average
+        avg_volume_label = regular_quote.get('averageVolumeDaily')
+        if avg_volume_label:
+            quote.volume_vs_avg = avg_volume_label
+            
+    except Exception as e:
+        logger.debug(f"Error parsing quote API response: {e}")
+    
+    return quote
+
+
+def parse_dividends_api_response(data: Dict[str, Any]) -> EnhancedDividends:
+    """Parse dividends API response into EnhancedDividends object.
+    
+    API Response Structure:
+    {
+      "symbol": "JNJ",
+      "currentAnnualDividendMethod": "IAD",
+      "status": "DIVIDENDS_PAID_CURRENTLY",
+      "dividends": [
+        {
+          "dividendPayment": 1.3,
+          "dividendPayDate": "December 09, 2025",
+          "dividendExDate": "November 25, 2025",
+          "dividendFrequency": "Quarterly",
+          "annualDividendRate": 5.2,
+          "dividendYield": "2.71%"
+        },
+        ...
+      ]
+    }
+    """
+    dividends = EnhancedDividends()
+    
+    try:
+        dividend_list = data.get('dividends', [])
+        if not dividend_list:
+            return dividends
+        
+        # Most recent dividend is first
+        latest = dividend_list[0]
+        
+        # Next/upcoming dividend data
+        dividends.next_payment = _parse_float(latest.get('dividendPayment'))
+        dividends.next_pay_date = latest.get('dividendPayDate')
+        dividends.next_ex_date = latest.get('dividendExDate')
+        dividends.frequency = latest.get('dividendFrequency')
+        dividends.annual_rate = _parse_float(latest.get('annualDividendRate'))
+        dividends.annual_yield = _parse_float(latest.get('dividendYield'))
+        
+        # Previous dividend (if there's more than one in history)
+        if len(dividend_list) > 1:
+            previous = dividend_list[1]
+            dividends.previous_payment = _parse_float(previous.get('dividendPayment'))
+            dividends.previous_pay_date = previous.get('dividendPayDate')
+            dividends.previous_ex_date = previous.get('dividendExDate')
+            
+    except Exception as e:
+        logger.debug(f"Error parsing dividends API response: {e}")
+    
+    return dividends
+
+
+def parse_earnings_api_response(data: Dict[str, Any]) -> EarningsData:
+    """Parse earnings API response into EarningsData object.
+    
+    API Response Structure:
+    {
+      "symbol": "GOOGL",
+      "fundamentals": {},
+      "upcoming": {
+        "earningsDate": "10/29/2025",
+        "numberOfAnalysts": 43,
+        "epsNonGaapEstimate": 2.18
+      },
+      "historical": [
+        {
+          "epsGaapActual": 2.31,
+          "epsNonGaapActual": 2.31,
+          "earningsDate": "07/23/2025",
+          "numberOfAnalysts": 43,
+          "epsNonGaapEstimate": 2.18,
+          "epsNonGaapEstimateHigh": 2.42,
+          "epsNonGaapEstimateLow": 2.0
+        }
+      ]
+    }
+    """
+    earnings = EarningsData()
+    
+    try:
+        upcoming = data.get('upcoming', {})
+        historical = data.get('historical', [])
+        fundamentals = data.get('fundamentals', {})
+        
+        # Upcoming earnings
+        if upcoming:
+            earnings.next_announcement_date = upcoming.get('earningsDate')
+            earnings.announcement_timing = upcoming.get('announcementTiming')
+            earnings.analysts_covering = upcoming.get('numberOfAnalysts')
+            earnings.consensus_estimate = _parse_float(upcoming.get('epsNonGaapEstimate'))
+            earnings.estimate_high = _parse_float(upcoming.get('epsNonGaapEstimateHigh'))
+            earnings.estimate_low = _parse_float(upcoming.get('epsNonGaapEstimateLow'))
+        
+        # Historical earnings (most recent)
+        if historical:
+            latest = historical[0]
+            earnings.eps_ttm = _parse_float(latest.get('epsNonGaapActual') or latest.get('epsGaapActual'))
+            
+            # If we don't have upcoming, use latest historical for analyst data
+            if not upcoming:
+                earnings.analysts_covering = latest.get('numberOfAnalysts')
+                earnings.consensus_estimate = _parse_float(latest.get('epsNonGaapEstimate'))
+                earnings.estimate_high = _parse_float(latest.get('epsNonGaapEstimateHigh'))
+                earnings.estimate_low = _parse_float(latest.get('epsNonGaapEstimateLow'))
+            
+            # Beat/miss information
+            beat_amount = latest.get('epsNonGaapBeat')
+            if beat_amount is not None:
+                earnings.recent_beats = [{
+                    'beat_amount': _parse_float(beat_amount),
+                    'beat_percent': _parse_float(latest.get('epsNonGaapBeatPercent')),
+                    'date': latest.get('earningsDate')
+                }]
+        
+        # Fundamentals (PE ratios, revenue)
+        if fundamentals:
+            earnings.pe_ttm = _parse_float(fundamentals.get('peRatio'))
+            earnings.forward_pe = _parse_float(fundamentals.get('forwardPE'))
+            earnings.peg_ratio = _parse_float(fundamentals.get('pegRatio'))
+            earnings.revenue_ttm = _parse_float(fundamentals.get('revenue'))
+            
+    except Exception as e:
+        logger.debug(f"Error parsing earnings API response: {e}")
+    
+    return earnings
+
+
+def parse_shareprofile_api_response(data: Dict[str, Any], quote: QuoteData) -> QuoteData:
+    """Parse share profile API response and enhance QuoteData with market cap, etc.
+    
+    API Response Structure:
+    {
+      "companySummary": {
+        "marketCapLabel": "Large Cap",
+        "marketCapValue": "$462.11B",
+        "companyEnterpriseValue": "$462.11B"
+      },
+      "shareInfo": [{
+        "sharesOutstanding": "2.41B",
+        "sharesHeld": "71.29%"
+      }]
+    }
+    """
+    try:
+        company_summary = data.get('companySummary', {})
+        
+        # Market cap
+        quote.market_cap = _parse_market_cap(company_summary.get('marketCapValue'))
+        
+        # Sector info might be in other fields
+        # Note: Sector information may not be in shareprofile API
+        # It might be in securityprofiles or other endpoints
+        
+    except Exception as e:
+        logger.debug(f"Error parsing share profile API response: {e}")
+    
+    return quote
+
+
+def calculate_payout_ratio(annual_dividend: Optional[float], eps_ttm: Optional[float]) -> Optional[float]:
+    """Calculate dividend payout ratio.
+    
+    Formula: (Annual Dividend Rate / EPS TTM) × 100
+    """
+    if annual_dividend and eps_ttm and eps_ttm > 0:
+        ratio = (annual_dividend / eps_ttm) * 100
+        return round(ratio, 2)
+    return None
+
+
+async def call_schwab_api(page: Page, url: str, debug: bool = False) -> Optional[Dict[str, Any]]:
+    """Call a Schwab API endpoint from within the browser's JavaScript context.
+    
+    This uses page.evaluate() to run fetch() directly in the browser, which ensures
+    all cookies, authentication tokens, and session state are automatically included.
+    This is the most reliable way to call Schwab APIs.
+    
+    Args:
+        page: Playwright page with authenticated session
+        url: API endpoint URL
+        debug: Enable debug logging
+        
+    Returns:
+        Parsed JSON response or None on error
+    """
+    try:
+        if debug:
+            logger.debug(f"Calling API: {url}")
+        
+        # Generate correlation IDs
+        correlator_id = str(uuid.uuid4())
+        client_correlid = str(uuid.uuid4())
+        
+        # Call API from within browser's JavaScript context using fetch()
+        # This automatically includes all cookies and session state
+        result = await page.evaluate("""
+            async ({url, correlatorId, clientCorrelId}) => {
+                try {
+                    const response = await fetch(url, {
+                        method: 'GET',
+                        credentials: 'include',  // Include cookies
+                        headers: {
+                            'accept': 'application/json',
+                            'accept-language': 'en-US,en;q=0.9',
+                            'cache-control': 'no-cache',
+                            'content-type': 'application/json',
+                            'correlatorid': correlatorId,
+                            'pragma': 'no-cache',
+                            'schwab-client-appid': 'AD00007800',
+                            'schwab-client-channel': 'IO',
+                            'schwab-client-correlid': clientCorrelId,
+                            'schwab-resource-version': '2',
+                        }
+                    });
+                    
+                    if (!response.ok) {
+                        const errorText = await response.text();
+                        return {
+                            success: false,
+                            status: response.status,
+                            error: errorText
+                        };
+                    }
+                    
+                    const data = await response.json();
+                    return {
+                        success: true,
+                        status: response.status,
+                        data: data
+                    };
+                } catch (error) {
+                    return {
+                        success: false,
+                        error: error.toString()
+                    };
+                }
+            }
+        """, {'url': url, 'correlatorId': correlator_id, 'clientCorrelId': client_correlid})
+        
+        if not result.get('success'):
+            if debug:
+                status = result.get('status', 'unknown')
+                error = result.get('error', 'unknown error')
+                logger.debug(f"API returned status {status}: {str(error)[:200]}")
+            return None
+        
+        data = result.get('data')
+        
+        if debug and data:
+            logger.debug(f"API response keys: {list(data.keys()) if isinstance(data, dict) else 'list'}")
+        
+        return data
+        
+    except Exception as e:
+        if debug:
+            logger.debug(f"Error calling API {url}: {e}")
+        return None
+
+
+async def extract_phase1_data_api(page: Page, ticker: str, debug: bool = False) -> EquityPhase1Data:
+    """Extract Phase 1 data using Schwab's REST APIs.
+    
+    This is the API-based replacement for the DOM scraping approach.
+    It calls Schwab's APIs directly using the authenticated session.
+    
+    Args:
+        page: Playwright page with authenticated session
+        ticker: Stock ticker symbol
+        debug: Enable debug logging
+        
+    Returns:
+        EquityPhase1Data with all extracted fields
+    """
+    if debug:
+        logger.debug(f"Starting API-based Phase 1 extraction for {ticker}")
+    
+    base_url = "https://ausgateway.schwab.com/api/is.ResearchExperience/v1"
+    
+    # Build API URLs
+    quote_url = f"{base_url}/quote?symbols={ticker}&isComplex=true"
+    dividends_url = f"{base_url}/events/dividends?symbol={ticker}"
+    earnings_url = f"{base_url}/events/earnings?symbols={ticker}"
+    profile_url = f"{base_url}/shareprofile?symbols={ticker}&includeSubsidiaries=true"
+    
+    # Make API calls using Playwright's request context (includes cookies automatically)
+    quote_data = await call_schwab_api(page, quote_url, debug)
+    dividends_data = await call_schwab_api(page, dividends_url, debug)
+    earnings_data = await call_schwab_api(page, earnings_url, debug)
+    profile_data = await call_schwab_api(page, profile_url, debug)
+    
+    # Parse responses
+    # Quote API returns a list, get first item
+    if quote_data and isinstance(quote_data, list) and len(quote_data) > 0:
+        quote = parse_quote_api_response(quote_data[0])
+    elif quote_data and isinstance(quote_data, dict):
+        quote = parse_quote_api_response(quote_data)
+    else:
+        quote = QuoteData()
+    
+    # Enhance quote with share profile data
+    if profile_data:
+        quote = parse_shareprofile_api_response(profile_data, quote)
+    
+    # Parse dividends
+    dividends = parse_dividends_api_response(dividends_data) if dividends_data else EnhancedDividends()
+    
+    # Parse earnings
+    earnings = parse_earnings_api_response(earnings_data) if earnings_data else EarningsData()
+    
+    # Calculate derived metrics
+    calculated = CalculatedMetrics()
+    if dividends.annual_rate and earnings.eps_ttm:
+        calculated.payout_ratio = calculate_payout_ratio(
+            dividends.annual_rate,
+            earnings.eps_ttm
+        )
+    
+    # Create Phase 1 data object
+    phase1_data = EquityPhase1Data(
+        ticker=ticker,
+        quote=quote,
+        dividends=dividends,
+        earnings=earnings,
+        calculated_metrics=calculated
+    )
+    
+    if debug:
+        logger.debug(f"API-based Phase 1 extraction complete for {ticker}")
+        # Count populated fields (dataclasses with slots don't have __dict__)
+        from dataclasses import fields as dataclass_fields
+        quote_count = sum(1 for f in dataclass_fields(quote) if getattr(quote, f.name) is not None)
+        div_count = sum(1 for f in dataclass_fields(dividends) if getattr(dividends, f.name) is not None)
+        earn_count = sum(1 for f in dataclass_fields(earnings) if getattr(earnings, f.name) not in (None, []))
+        logger.debug(f"  Quote fields populated: {quote_count}/21")
+        logger.debug(f"  Dividend fields populated: {div_count}/9")
+        logger.debug(f"  Earnings fields populated: {earn_count}/13")
+    
+    return phase1_data
+

schwab_scraper/features/equity/phase1_scraper.py

@@ -0,0 +1,786 @@
+"""Phase 1: Essential Dividend Metrics Implementation (DEPRECATED)
+
+⚠️ DEPRECATED: This DOM-scraping based approach has been replaced by phase1_api_scraper.py
+which uses Schwab's REST APIs directly. The API approach is more reliable, complete,
+and maintainable than DOM scraping.
+
+This module is kept for reference only. New code should use phase1_api_scraper.py.
+
+Old approach extracts from DOM:
+- Quote/Price Data (symbol bar)
+- Enhanced Dividend Information (forward-looking dates)
+- Core Earnings Metrics (EPS, forecasts)
+- Basic Valuation Ratios (P/E, Forward P/E, PEG)
+- Calculated Metrics (payout ratio)
+"""
+
+from typing import Dict, Any, Optional
+import re
+import logging
+
+from ...core import QuoteData, EnhancedDividends, EarningsData, CalculatedMetrics, EquityPhase1Data
+
+
+logger = logging.getLogger(__name__)
+
+
+def _parse_float(value: Any) -> Optional[float]:
+    """Safely parse a value to float, handling $ and % symbols."""
+    if value is None:
+        return None
+    try:
+        # Remove common formatting characters
+        clean = str(value).strip().replace('$', '').replace(',', '').replace('%', '')
+        if clean and clean != '--' and clean.lower() != 'n/a':
+            return float(clean)
+    except (ValueError, AttributeError):
+        pass
+    return None
+
+
+def _parse_int(value: Any) -> Optional[int]:
+    """Safely parse a value to int."""
+    if value is None:
+        return None
+    try:
+        clean = str(value).strip().replace(',', '')
+        if clean and clean != '--' and clean.lower() != 'n/a':
+            return int(float(clean))
+    except (ValueError, AttributeError):
+        pass
+    return None
+
+
+def _parse_volume(volume_str: str) -> Optional[int]:
+    """Parse volume string like '8M', '22.4M', '1.2B' to integer."""
+    if not volume_str:
+        return None
+    
+    try:
+        volume_str = volume_str.strip().upper()
+        multiplier = 1
+        
+        if volume_str.endswith('K'):
+            multiplier = 1_000
+            volume_str = volume_str[:-1]
+        elif volume_str.endswith('M'):
+            multiplier = 1_000_000
+            volume_str = volume_str[:-1]
+        elif volume_str.endswith('B'):
+            multiplier = 1_000_000_000
+            volume_str = volume_str[:-1]
+        
+        value = float(volume_str)
+        return int(value * multiplier)
+    except (ValueError, AttributeError):
+        return None
+
+
+def _parse_revenue(revenue_str: str) -> Optional[float]:
+    """Parse revenue string like '$92.15B', '$1.5M' to dollar value."""
+    if not revenue_str:
+        return None
+    
+    try:
+        revenue_str = revenue_str.strip().upper().replace('$', '').replace(',', '')
+        multiplier = 1
+        
+        if revenue_str.endswith('K'):
+            multiplier = 1_000
+            revenue_str = revenue_str[:-1]
+        elif revenue_str.endswith('M'):
+            multiplier = 1_000_000
+            revenue_str = revenue_str[:-1]
+        elif revenue_str.endswith('B'):
+            multiplier = 1_000_000_000
+            revenue_str = revenue_str[:-1]
+        elif revenue_str.endswith('T'):
+            multiplier = 1_000_000_000_000
+            revenue_str = revenue_str[:-1]
+        
+        value = float(revenue_str)
+        return value * multiplier
+    except (ValueError, AttributeError):
+        return None
+
+
+async def extract_quote_data(page, ticker: str = "", debug: bool = False) -> QuoteData:
+    """Extract quote/price data from symbol bar.
+    
+    Args:
+        page: Playwright page object
+        ticker: Stock ticker symbol (for pattern matching)
+        debug: Enable debug logging
+        
+    Returns:
+        QuoteData object with extracted fields
+    """
+    quote = QuoteData()
+    
+    try:
+        if debug:
+            logger.debug("Starting quote data extraction...")
+        
+        # Wait for symbol bar content (look for key labels)
+        try:
+            await page.wait_for_selector('#app-symbol-bar-component, text=Previous close', state='attached', timeout=15000)
+        except Exception:
+            if debug:
+                logger.debug("Timeout waiting for symbol bar selector, attempting to parse whatever is there")
+        
+        # Extract symbol bar text content (fallback to body if specific component not found)
+        symbol_bar_text = await page.evaluate('''
+            () => {
+                const symbolBar = document.querySelector('#app-symbol-bar-component');
+                if (symbolBar && symbolBar.textContent && symbolBar.textContent.includes('Previous close')) return symbolBar.textContent;
+                
+                // If specific component not found, try to find the container with market data
+                // Look for container with "Previous close"
+                const labels = Array.from(document.querySelectorAll('span, div, p'));
+                const prevCloseLabel = labels.find(el => el.textContent && el.textContent.includes('Previous close'));
+                if (prevCloseLabel) {
+                    // Return the parent's text content (go up a few levels to capture all data)
+                    let parent = prevCloseLabel.parentElement;
+                    let count = 0;
+                    while (parent && count < 8) {
+                        if (parent.textContent.length > 300) return parent.textContent;
+                        parent = parent.parentElement;
+                        count++;
+                    }
+                }
+                
+                return document.body.textContent || '';
+            }
+        ''')
+        
+        if debug:
+            logger.debug(f"Symbol bar text (first 500 chars): {symbol_bar_text[:500]}")
+        
+        # Extract structured data
+        quote_data = await page.evaluate(r'''
+            (ticker) => {
+                const data = {};
+                
+                // Helper to get text content from page
+                const getText = () => {
+                   const symbolBar = document.querySelector('#app-symbol-bar-component');
+                   // Verify it looks like the right component by checking for "Previous close"
+                   if (symbolBar && symbolBar.textContent && symbolBar.textContent.includes('Previous close')) {
+                       return symbolBar.textContent;
+                   }
+                   
+                   // Fallback logic
+                   const labels = Array.from(document.querySelectorAll('span, div, p'));
+                   const prevCloseLabel = labels.find(el => el.textContent && el.textContent.includes('Previous close'));
+                   if (prevCloseLabel) {
+                        let parent = prevCloseLabel.parentElement;
+                        let count = 0;
+                        while (parent && count < 8) {
+                            if (parent.textContent.length > 300) return parent.textContent;
+                            parent = parent.parentElement;
+                            count++;
+                        }
+                   }
+                   
+                   // Last resort: body text
+                   return document.body.textContent || '';
+                };
+                
+                const fullText = getText();
+                
+                // Try to find price in quote container first for accuracy
+                const priceElement = document.querySelector('.symbol-quote-container, [data-testid="quote-price"]');
+                if (priceElement) {
+                    const priceText = priceElement.textContent || '';
+                    const priceMatch = priceText.match(/\$([0-9,]+\.[0-9]+)/);
+                    if (priceMatch) data.price = priceMatch[1].replace(',', '');
+                } else {
+                    // Fallback regex for price if element not found
+                    // Look for price near top or just regex
+                    const priceMatch = fullText.match(/\$([0-9,]+\.[0-9]{2})(\s|[+-]|$)/);
+                    if (priceMatch) data.price = priceMatch[1].replace(',', '');
+                }
+                
+                // After hours (using \s* for robustness)
+                const afterHoursMatch = fullText.match(/After hours:?\s*\$([0-9,.]+)/i);
+                if (afterHoursMatch) data.after_hours_price = afterHoursMatch[1].replace(',', '');
+                
+                const afterHoursChangeMatch = fullText.match(/After hours:.*?([+-]\$[0-9,.]+)\s*\(([+-][0-9.]+)%\)/i);
+                if (afterHoursChangeMatch) {
+                    data.after_hours_change = afterHoursChangeMatch[1].replace('$', '').replace(',', '');
+                    data.after_hours_change_percent = afterHoursChangeMatch[2];
+                }
+                
+                // Bid/Ask (using \s* for robustness)
+                const bidMatch = fullText.match(/Bid\s*\$([0-9,.]+)/i);
+                if (bidMatch) data.bid = bidMatch[1].replace(',', '');
+                
+                const askMatch = fullText.match(/Ask\s*\$([0-9,.]+)/i);
+                if (askMatch) data.ask = askMatch[1].replace(',', '');
+                
+                const bidAskSizeMatch = fullText.match(/Bid\/Ask Size\s*([0-9]+\/[0-9]+)/i);
+                if (bidAskSizeMatch) data.bid_ask_size = bidAskSizeMatch[1];
+                
+                // Previous close and open (using \s* instead of \s+)
+                const prevCloseMatch = fullText.match(/Previous close\s*\$([0-9,.]+)/i);
+                if (prevCloseMatch) data.previous_close = prevCloseMatch[1].replace(',', '');
+                
+                const openMatch = fullText.match(/Today's open\s*\$([0-9,.]+)/i);
+                if (openMatch) data.open = openMatch[1].replace(',', '');
+                
+                // Volume (using \s*)
+                const volumeMatch = fullText.match(/Today's volume\s*([0-9.]+[KMB]?)/i);
+                if (volumeMatch) data.volume = volumeMatch[1];
+                
+                const volumeVsAvgMatch = fullText.match(/Today's volume\s*[0-9.]+[KMB]?\s*(Above Avg\.|Below Avg\.|Average)/i);
+                if (volumeVsAvgMatch) data.volume_vs_avg = volumeVsAvgMatch[1];
+                
+                // Day range
+                // Pattern: "Today's range low $200.81 Today's range high $203.45" or similar
+                // We'll look for "low $X" and "high $Y" appearing after "Today's range"
+                const dayRangeMatch = fullText.match(/Today's range.*?low\s*\$([0-9,.]+).*?high\s*\$([0-9,.]+)/i);
+                if (dayRangeMatch) {
+                    data.day_range_low = dayRangeMatch[1].replace(',', '');
+                    data.day_range_high = dayRangeMatch[2].replace(',', '');
+                }
+                
+                // 52-week range
+                const weekRangeMatch = fullText.match(/52-week range.*?low\s*\$([0-9,.]+).*?high\s*\$([0-9,.]+)/i);
+                if (weekRangeMatch) {
+                    data.week_52_low = weekRangeMatch[1].replace(',', '');
+                    data.week_52_high = weekRangeMatch[2].replace(',', '');
+                }
+                
+                // Market cap (may be in Share Profile section)
+                const marketCapMatch = fullText.match(/Market Cap\s*\$([0-9.]+[KMBT])/i);
+                if (marketCapMatch) data.market_cap = marketCapMatch[1];
+                
+                // Change and change percent
+                
+                // Try specific formatted pattern first: TICKER $PRICE CHANGE CHANGE%
+                // e.g. "JNJ $201.95 -1.03 -0.51%"
+                const standardPattern = fullText.match(/\$([0-9,.]+)\s*([+-]?[0-9,.]+)\s*([+-]?[0-9.]+)%/);
+                if (standardPattern) {
+                     if (!data.price) data.price = standardPattern[1].replace(',', '');
+                     data.change = standardPattern[2];
+                     data.change_percent = standardPattern[3];
+                }
+                
+                let percentMatch = null;
+                if (ticker && !data.change_percent) {
+                    // Match: TICKER$digits.digits{2}percent%
+                    const tickerPattern = new RegExp(ticker + '\\\\.?[\\s]*\\$([0-9,]+\\\\.[0-9]{2})[\\s]*([0-9.]+)%', 'i');
+                    percentMatch = fullText.match(tickerPattern);
+                    if (percentMatch) {
+                        data.change_percent = percentMatch[2]; 
+                    }
+                }
+                
+                if (!data.change_percent) {
+                    // Fallback: match any price+percent pattern with space
+                    const fallbackMatch = fullText.match(/\$[0-9,.]+\s*([+-]?[0-9.]+)%/);
+                    if (fallbackMatch) {
+                        data.change_percent = fallbackMatch[1];
+                    }
+                }
+                
+                // Pattern 2: "+$1.23 (+0.45%)" or "-$1.23 (-0.45%)"
+                let changeMatch = fullText.match(/([+-]\$[0-9,.]+)\s*\(([+-][0-9.]+)%\)/);
+                // Pattern 3: "$193.08 +1.23 +0.64%" (price followed by change)
+                if (!changeMatch) {
+                    changeMatch = fullText.match(/\$[0-9,.]+\s*([+-][0-9,.]+)\s*([+-][0-9.]+)%/);
+                }
+                // Pattern 4: "Change: +1.23 (+0.64%)"
+                if (!changeMatch) {
+                    changeMatch = fullText.match(/Change:?\s*([+-][0-9,.]+)\s*\(([+-][0-9.]+)%\)/i);
+                }
+                if (changeMatch) {
+                    data.change = changeMatch[1].replace('$', '').replace(',', '');
+                    if (!data.change_percent) {
+                        data.change_percent = changeMatch[2].replace(/[+]/g, '');
+                    }
+                }
+                
+                // Exchange - look for NYSE, NASDAQ, etc.
+                const exchangeMatch = fullText.match(/\b(NYSE|NASDAQ|AMEX|OTC|BATS)\b/i);
+                if (exchangeMatch) data.exchange = exchangeMatch[1].toUpperCase();
+                
+                return data;
+            }
+        ''', ticker)
+        
+        # Parse and assign values
+        quote.price = _parse_float(quote_data.get('price'))
+        quote.change = _parse_float(quote_data.get('change'))
+        quote.change_percent = _parse_float(quote_data.get('change_percent'))
+        quote.after_hours_price = _parse_float(quote_data.get('after_hours_price'))
+        quote.after_hours_change = _parse_float(quote_data.get('after_hours_change'))
+        quote.after_hours_change_percent = _parse_float(quote_data.get('after_hours_change_percent'))
+        quote.bid = _parse_float(quote_data.get('bid'))
+        quote.ask = _parse_float(quote_data.get('ask'))
+        quote.bid_ask_size = quote_data.get('bid_ask_size')
+        quote.previous_close = _parse_float(quote_data.get('previous_close'))
+        quote.open = _parse_float(quote_data.get('open'))
+        quote.volume = _parse_volume(quote_data.get('volume', ''))
+        quote.volume_vs_avg = quote_data.get('volume_vs_avg')
+        quote.day_range_low = _parse_float(quote_data.get('day_range_low'))
+        quote.day_range_high = _parse_float(quote_data.get('day_range_high'))
+        quote.week_52_low = _parse_float(quote_data.get('week_52_low'))
+        quote.week_52_high = _parse_float(quote_data.get('week_52_high'))
+        quote.market_cap = quote_data.get('market_cap')
+        
+        # Try to extract sector and exchange from page header
+        header_data = await page.evaluate(r'''
+            () => {
+                const data = {};
+                
+                // Look for sector near company name
+                const sectorElement = document.querySelector('[data-testid="sector"], .sector');
+                if (sectorElement) {
+                    data.sector = sectorElement.textContent.replace('Sector', '').trim();
+                } else {
+                    // Manual search for text containing "Sector"
+                    const spans = Array.from(document.querySelectorAll('span'));
+                    const sectorSpan = spans.find(el => el.textContent && el.textContent.includes('Sector'));
+                    if (sectorSpan) {
+                         data.sector = sectorSpan.textContent.replace('Sector', '').replace(':', '').trim();
+                    }
+                }
+                
+                // Look for exchange near ticker
+                const exchangeElement = document.querySelector('[data-testid="exchange"], .exchange');
+                if (exchangeElement) {
+                    data.exchange = exchangeElement.textContent.trim();
+                }
+                
+                // Fallback: parse from page text
+                const pageText = document.body.textContent || '';
+                if (!data.sector) {
+                    const sectorMatch = pageText.match(/Sector[:\s]+([A-Za-z\s&]+)/);
+                    if (sectorMatch) data.sector = sectorMatch[1].trim();
+                }
+                if (!data.exchange) {
+                    const exchangeMatch = pageText.match(/(NYSE|NASDAQ|AMEX|OTC)/i);
+                    if (exchangeMatch) data.exchange = exchangeMatch[1].toUpperCase();
+                }
+                
+                return data;
+            }
+        ''')
+        
+        quote.sector = header_data.get('sector')
+        quote.exchange = header_data.get('exchange')
+        
+        if debug:
+            logger.debug(f"Extracted quote data: price={quote.price}, volume={quote.volume}, "
+                        f"52w_range={quote.week_52_low}-{quote.week_52_high}")
+    
+    except Exception as e:
+        if debug:
+            logger.debug(f"Error extracting quote data: {e}")
+    
+    return quote
+
+
+async def extract_enhanced_dividends(page, debug: bool = False) -> EnhancedDividends:
+    """Extract enhanced dividend data including next payment dates.
+    
+    Args:
+        page: Playwright page object
+        debug: Enable debug logging
+        
+    Returns:
+        EnhancedDividends object with extracted fields
+    """
+    dividends = EnhancedDividends()
+    
+    try:
+        if debug:
+            logger.debug("Starting enhanced dividend extraction...")
+        
+        # Wait for dividends panel to load
+        await page.wait_for_selector('#dividends', timeout=15000)
+        
+        # Scroll to dividends panel
+        await page.evaluate('''
+            () => {
+                const dividendsPanel = document.querySelector('#dividends');
+                if (dividendsPanel) {
+                    dividendsPanel.scrollIntoView({ behavior: 'smooth', block: 'center' });
+                }
+            }
+        ''')
+        await page.wait_for_timeout(1000)
+        
+        # CRITICAL: Click on the panel header to trigger content loading
+        # Schwab's panels don't auto-load - they need to be clicked
+        if debug:
+            logger.debug("Clicking dividends panel header to trigger content load...")
+        try:
+            dividends_header = await page.query_selector('#dividends h2, #dividends .sdps-panel__title, #dividends-togglechevron-button')
+            if dividends_header:
+                await dividends_header.click()
+                await page.wait_for_timeout(2000)
+                if debug:
+                    logger.debug("Clicked dividends panel header successfully")
+        except Exception as e:
+            if debug:
+                logger.debug(f"Could not click dividends header: {e}")
+        
+        # Wait for content to load after click
+        await page.wait_for_timeout(1000)
+        
+        # Extract dividend data
+        dividend_data = await page.evaluate('''
+            () => {
+                const data = {};
+                const dividendsPanel = document.querySelector('#dividends');
+                if (!dividendsPanel) return data;
+                
+                const fullText = dividendsPanel.textContent || '';
+                
+                // DEBUG: Return sample of text for debugging
+                data._debug_text_sample = fullText.substring(0, 800);
+                
+                // Next dividend payment
+                const nextPaymentMatch = fullText.match(/Next Dividend Payment\\s*\\$([0-9.]+)/i);
+                if (nextPaymentMatch) data.next_payment = nextPaymentMatch[1];
+                
+                // Next pay date
+                const nextPayDateMatch = fullText.match(/Next Pay Date\\s*([A-Za-z]+ [0-9]{1,2}, [0-9]{4})/i);
+                if (nextPayDateMatch) data.next_pay_date = nextPayDateMatch[1];
+                
+                // Next ex-date
+                const nextExDateMatch = fullText.match(/Next Ex-Date\\s*([A-Za-z]+ [0-9]{1,2}, [0-9]{4})/i);
+                if (nextExDateMatch) data.next_ex_date = nextExDateMatch[1];
+                
+                // Previous dividend payment
+                const prevPaymentMatch = fullText.match(/Previous Dividend Payment\\s*\\$([0-9.]+)/i);
+                if (prevPaymentMatch) data.previous_payment = prevPaymentMatch[1];
+                
+                // Previous pay date
+                const prevPayDateMatch = fullText.match(/Previous Pay Date\\s*([A-Za-z]+ [0-9]{1,2}, [0-9]{4})/i);
+                if (prevPayDateMatch) data.previous_pay_date = prevPayDateMatch[1];
+                
+                // Previous ex-date
+                const prevExDateMatch = fullText.match(/Previous Ex-Date\\s*([A-Za-z]+ [0-9]{1,2}, [0-9]{4})/i);
+                if (prevExDateMatch) data.previous_ex_date = prevExDateMatch[1];
+                
+                // Frequency
+                const frequencyMatch = fullText.match(/Frequency\\s*(Quarterly|Monthly|Annual|Semi-Annual)/i);
+                if (frequencyMatch) data.frequency = frequencyMatch[1];
+                
+                // Annual Dividend Rate (IAD)
+                const annualRateMatch = fullText.match(/Annual Dividend Rate.*?\\$([0-9.]+)/i);
+                if (annualRateMatch) data.annual_rate = annualRateMatch[1];
+                
+                // Annual Dividend Yield - appears after "Annual Dividend Yield" text
+                // Text pattern: "Annual Dividend Yield...2.71%"
+                const yieldMatch = fullText.match(/Annual Dividend Yield[\\s\\S]{0,300}?([0-9]+\\.[0-9]+)%/i);
+                if (yieldMatch) data.annual_yield = yieldMatch[1];
+                
+                return data;
+            }
+        ''')
+        
+        if debug and dividend_data.get('_debug_text_sample'):
+            logger.debug(f"Dividend panel text sample: {dividend_data['_debug_text_sample']}")
+        
+        # Parse and assign values
+        dividends.next_payment = _parse_float(dividend_data.get('next_payment'))
+        dividends.next_pay_date = dividend_data.get('next_pay_date')
+        dividends.next_ex_date = dividend_data.get('next_ex_date')
+        dividends.previous_payment = _parse_float(dividend_data.get('previous_payment'))
+        dividends.previous_pay_date = dividend_data.get('previous_pay_date')
+        dividends.previous_ex_date = dividend_data.get('previous_ex_date')
+        dividends.frequency = dividend_data.get('frequency')
+        dividends.annual_rate = _parse_float(dividend_data.get('annual_rate'))
+        dividends.annual_yield = _parse_float(dividend_data.get('annual_yield'))
+        
+        if debug:
+            logger.debug(f"Extracted dividend data: next_payment={dividends.next_payment}, "
+                        f"next_pay_date={dividends.next_pay_date}, annual_rate={dividends.annual_rate}")
+    
+    except Exception as e:
+        if debug:
+            logger.debug(f"Error extracting dividend data: {e}")
+    
+    return dividends
+
+
+async def extract_earnings_data(page, debug: bool = False) -> EarningsData:
+    """Extract earnings metrics and forecasts.
+    
+    Args:
+        page: Playwright page object
+        debug: Enable debug logging
+        
+    Returns:
+        EarningsData object with extracted fields
+    """
+    earnings = EarningsData()
+    
+    try:
+        if debug:
+            logger.debug("Starting earnings data extraction...")
+        
+        # Wait for earnings panel to load
+        await page.wait_for_selector('#expected-earnings', timeout=15000)
+        
+        # Scroll to earnings panel
+        await page.evaluate('''
+            () => {
+                const earningsPanel = document.querySelector('#expected-earnings');
+                if (earningsPanel) {
+                    earningsPanel.scrollIntoView({ behavior: 'smooth', block: 'center' });
+                }
+            }
+        ''')
+        await page.wait_for_timeout(1000)
+        
+        # CRITICAL: Click on the panel header to trigger content loading
+        # Schwab's panels don't auto-load - they need to be clicked
+        if debug:
+            logger.debug("Clicking earnings panel header to trigger content load...")
+        try:
+            earnings_header = await page.query_selector('#expected-earnings h2, #expected-earnings .sdps-panel__title, #expected-earnings-heading, #expected-earnings-togglechevron-button')
+            if earnings_header:
+                await earnings_header.click()
+                await page.wait_for_timeout(2000)
+                if debug:
+                    logger.debug("Clicked earnings panel header successfully")
+        except Exception as e:
+            if debug:
+                logger.debug(f"Could not click earnings header: {e}")
+        
+        # Wait for content to load after click
+        await page.wait_for_timeout(1000)
+
+        # Check for and click "Show More" if present
+        try:
+            # Use JS to find and click - most robust way
+            clicked = await page.evaluate('''
+                () => {
+                    const panel = document.querySelector('#expected-earnings');
+                    if (!panel) return false;
+                    
+                    // Find any element with "Show More" text
+                    const elements = Array.from(panel.querySelectorAll('a, button, span, div'));
+                    const showMore = elements.find(el => el.textContent.trim().toLowerCase() === "show more");
+                    
+                    if (showMore) {
+                        showMore.click();
+                        return true;
+                    }
+                    return false;
+                }
+            ''')
+            
+            if clicked:
+                if debug:
+                    logger.debug("found and clicked 'Show More' via JS")
+                await page.wait_for_timeout(2000)
+            elif debug:
+                logger.debug("'Show More' not found or not clickable")
+                
+        except Exception as e:
+            if debug:
+                logger.debug(f"Error checking for Show More: {e}")
+        
+        # Extract earnings data
+        earnings_data = await page.evaluate(r'''
+            (debug) => {
+                const data = {};
+                // Helper to get text content including Shadow DOMs
+                const getDeepText = (root) => {
+                    if (!root) return '';
+                    if (root.nodeType === Node.TEXT_NODE) return root.textContent;
+                    if (root.nodeType === Node.ELEMENT_NODE && root.shadowRoot) {
+                        return getDeepText(root.shadowRoot);
+                    }
+                    
+                    let text = '';
+                    const children = root.childNodes;
+                    for (let i = 0; i < children.length; i++) {
+                        text += getDeepText(children[i]);
+                    }
+                    return text;
+                };
+
+                const earningsPanel = document.querySelector('#expected-earnings');
+                let fullText = '';
+                
+                if (earningsPanel) {
+                     fullText = getDeepText(earningsPanel);
+                }
+                
+                // Fallback to body deep text if panel seems empty
+                if (fullText.length < 500 || !fullText.includes("Announcement")) {
+                    fullText = getDeepText(document.body);
+                }
+                
+                // Next earnings announcement - robust regex checking for various patterns
+                let nextAnnouncementMatch = fullText.match(/Next Earnings Announcement.*?([0-9]{2}\/[0-9]{2}\/[0-9]{4})/i);
+                if (!nextAnnouncementMatch) {
+                     // Try alternate pattern: Announcement: 12/12/2025
+                     nextAnnouncementMatch = fullText.match(/Announcement:?\s*([0-9]{2}\/[0-9]{2}\/[0-9]{4})/i);
+                }
+                if (nextAnnouncementMatch) data.next_announcement_date = nextAnnouncementMatch[1];
+                
+                // Announcement timing
+                const timingMatch = fullText.match(/(Before Market Open|After Market Close)/i);
+                if (timingMatch) data.announcement_timing = timingMatch[1];
+                
+                // Number of analysts
+                const analystsMatch = fullText.match(/With ([0-9]+) analysts covering/i);
+                if (analystsMatch) data.analysts_covering = analystsMatch[1];
+                
+                // Consensus estimate
+                const consensusMatch = fullText.match(/consensus.*?estimate is \\$([0-9.]+)/i);
+                if (consensusMatch) data.consensus_estimate = consensusMatch[1];
+                
+                // High/Low estimates
+                const highLowMatch = fullText.match(/high and low estimates are \\$([0-9.]+) and \\$([0-9.]+)/i);
+                if (highLowMatch) {
+                    data.estimate_high = highLowMatch[1];
+                    data.estimate_low = highLowMatch[2];
+                }
+                
+                // EPS TTM (multiple patterns)
+                let epsMatch = fullText.match(/EPS\s*\(TTM\)\s*(?:Value)?\s*\$?([0-9.-]+)/i);
+                if (!epsMatch) epsMatch = fullText.match(/Earnings per Share\s*\(?TTM\)?\s*(?:Value)?\s*\$?([0-9.-]+)/i);
+                if (!epsMatch) epsMatch = fullText.match(/EPS\s+(?:Value)?\s*([0-9.-]+)/i);
+                if (epsMatch) data.eps_ttm = epsMatch[1];
+                
+                // Revenue TTM
+                let revenueMatch = fullText.match(/Revenue\s*\(TTM\)\s*(?:Value)?\s*\$([0-9.]+[KMBT]?)/i);
+                if (!revenueMatch) revenueMatch = fullText.match(/Revenue\s+(?:Value)?\s*\$([0-9.]+[KMBT])/i);
+                if (revenueMatch) data.revenue_ttm = revenueMatch[1];
+                
+                // P/E TTM (multiple patterns)
+                let peMatch = fullText.match(/Price[\/\s]*Earnings\s*\(TTM\)\s*(?:Value)?\s*([0-9.]+)/i);
+                if (!peMatch) peMatch = fullText.match(/P[\/\s]*E\s*\(?TTM\)?\s*(?:Value)?\s*([0-9.]+)/i);
+                if (!peMatch) peMatch = fullText.match(/PE Ratio\s*\(TTM\)\s*(?:Value)?\s*([0-9.]+)/i);
+                if (peMatch) data.pe_ttm = peMatch[1];
+                
+                // Forward P/E
+                let forwardPeMatch = fullText.match(/Forward\s+P[\/\s]*E\s*(?:Value)?\s*([0-9.]+)/i);
+                if (!forwardPeMatch) forwardPeMatch = fullText.match(/P[\/\s]*E\s*\(Forward\)\s*(?:Value)?\s*([0-9.]+)/i);
+                if (forwardPeMatch) data.forward_pe = forwardPeMatch[1];
+                
+                // PEG Ratio
+                let pegMatch = fullText.match(/Price\s+to\s+Earnings[\/\s]*Growth\s*\(PEG\)\s*(?:Value)?\s*([0-9.]+)/i);
+                if (!pegMatch) pegMatch = fullText.match(/PEG\s*Ratio?\s*(?:Value)?\s*([0-9.]+)/i);
+                if (pegMatch) data.peg_ratio = pegMatch[1];
+                
+                // Recent beats/misses (simplified - just extract beat amounts)
+                const beatMatches = fullText.matchAll(/Beat.*?\$([0-9.]+)/gi);
+                data.recent_beats = [];
+                for (const match of beatMatches) {
+                    data.recent_beats.push(match[1]);
+                }
+                
+                return data;
+            }
+        ''', debug)
+        
+        # Parse and assign values
+        earnings.next_announcement_date = earnings_data.get('next_announcement_date')
+        earnings.announcement_timing = earnings_data.get('announcement_timing')
+        earnings.analysts_covering = _parse_int(earnings_data.get('analysts_covering'))
+        earnings.consensus_estimate = _parse_float(earnings_data.get('consensus_estimate'))
+        earnings.estimate_high = _parse_float(earnings_data.get('estimate_high'))
+        earnings.estimate_low = _parse_float(earnings_data.get('estimate_low'))
+        earnings.eps_ttm = _parse_float(earnings_data.get('eps_ttm'))
+        earnings.revenue_ttm = _parse_revenue(earnings_data.get('revenue_ttm', ''))
+        earnings.pe_ttm = _parse_float(earnings_data.get('pe_ttm'))
+        earnings.forward_pe = _parse_float(earnings_data.get('forward_pe'))
+        earnings.peg_ratio = _parse_float(earnings_data.get('peg_ratio'))
+        
+        # Store recent beats as list of dicts
+        if earnings_data.get('recent_beats'):
+            earnings.recent_beats = [
+                {'beat_amount': _parse_float(beat)} 
+                for beat in earnings_data.get('recent_beats', [])
+            ]
+        
+        if debug:
+            logger.debug(f"Extracted earnings data: eps_ttm={earnings.eps_ttm}, "
+                        f"pe_ttm={earnings.pe_ttm}, forward_pe={earnings.forward_pe}")
+    
+    except Exception as e:
+        if debug:
+            logger.debug(f"Error extracting earnings data: {e}")
+    
+    return earnings
+
+
+def calculate_payout_ratio(annual_dividend: Optional[float], eps_ttm: Optional[float]) -> Optional[float]:
+    """Calculate dividend payout ratio.
+    
+    Formula: (Annual Dividend Rate / EPS TTM) × 100
+    
+    Args:
+        annual_dividend: Annual dividend rate per share
+        eps_ttm: Earnings per share (trailing twelve months)
+        
+    Returns:
+        Payout ratio as percentage, or None if cannot calculate
+    """
+    if annual_dividend and eps_ttm and eps_ttm > 0:
+        ratio = (annual_dividend / eps_ttm) * 100
+        return round(ratio, 2)
+    return None
+
+
+async def extract_phase1_data(page, debug: bool = False) -> EquityPhase1Data:
+    """Extract all Phase 1 data points.
+    
+    Args:
+        page: Playwright page object
+        debug: Enable debug output
+        
+    Returns:
+        EquityPhase1Data object with all extracted data
+    """
+    if debug:
+        logger.debug("Starting Phase 1 data extraction...")
+    
+    # Wait for page to stabilize
+    await page.wait_for_timeout(3000)
+    
+    # Extract ticker from page URL
+    ticker = await page.evaluate('''
+        () => {
+            const url = window.location.href;
+            const match = url.match(/stocks\\/([A-Z]+)/i);
+            return match ? match[1].toUpperCase() : '';
+        }
+    ''')
+    
+    # Extract each section
+    quote = await extract_quote_data(page, ticker=ticker, debug=debug)
+    dividends = await extract_enhanced_dividends(page, debug=debug)
+    earnings = await extract_earnings_data(page, debug=debug)
+    
+    # Calculate derived metrics
+    calculated = CalculatedMetrics()
+    if dividends.annual_rate and earnings.eps_ttm:
+        calculated.payout_ratio = calculate_payout_ratio(
+            dividends.annual_rate,
+            earnings.eps_ttm
+        )
+    
+    # Create Phase 1 data object
+    phase1_data = EquityPhase1Data(
+        ticker=ticker,
+        quote=quote,
+        dividends=dividends,
+        earnings=earnings,
+        calculated_metrics=calculated
+    )
+    
+    if debug:
+        logger.debug(f"Phase 1 extraction complete for {ticker}")
+    
+    return phase1_data

schwab_scraper/features/equity/scraper.py

@@ -0,0 +1,977 @@
+from typing import Dict, Any, Optional
+from ...utils.logging import save_debug_artifact
+
+
+def should_replace_dividend_value(existing_value: Optional[str], new_value: Optional[str]) -> bool:
+    """
+    Decide whether to replace an existing dividend field value with a new one.
+
+    Rules:
+    - Never replace with empty/None values
+    - Replace if there is no existing value
+    - Replace if the existing value is "Show More" or contains "Show More"
+    - Otherwise, keep the existing (good) data
+    """
+    if not new_value or not str(new_value).strip():
+        return False
+    if not existing_value:
+        return True
+    existing_text = str(existing_value)
+    if existing_text == 'Show More' or 'Show More' in existing_text:
+        return True
+    return False
+
+
+async def extract_dividend_data(page, debug: bool = False) -> Dict[str, Any]:
+    """
+    Extract dividend information from Schwab stock page.
+    Returns dictionary with dividend data fields.
+    """
+    dividend_data: Dict[str, Any] = {}
+
+    try:
+        if debug:
+            print("DEBUG: Starting dividend data extraction...")
+            # Take initial screenshot to see page state
+            png = await page.screenshot(full_page=True)
+            path = save_debug_artifact("debug_dividend_start.png", png)
+            print(f"DEBUG: Initial screenshot saved as {path}")
+
+        # Wait for the dividends section to load dynamically
+        if debug:
+            print("DEBUG: Waiting for dividends section to load...")
+
+        try:
+            # First wait for the dividends panel to appear
+            await page.wait_for_selector('#dividends', timeout=15000)
+            if debug:
+                print("DEBUG: #dividends panel found")
+
+            # Wait for dividend content to load dynamically
+            dividend_loaded = False
+            max_attempts = 5  # Reduced from 10 for faster tests
+            attempt = 0
+
+            while not dividend_loaded and attempt < max_attempts:
+                attempt += 1
+                if debug:
+                    print(f"DEBUG: Attempt {attempt}/{max_attempts} - Waiting for dynamic dividend content...")
+
+                # Check if the dividends section has been populated with actual content
+                dividend_status = await page.evaluate('''
+                    () => {
+                        const result = { loaded: false, debug: {} };
+
+                        // Look for the dividends panel content that should be populated
+                        const dividendsPanel = document.querySelector('#dividends');
+                        if (dividendsPanel) {
+                            const panelBody = dividendsPanel.querySelector('.sdps-panel__body');
+                            if (panelBody) {
+                                const textContent = panelBody.textContent || '';
+                                result.debug.panelBodyLength = textContent.length;
+                                result.debug.panelBodySample = textContent.substring(0, 200);
+
+                                // Check if the panel has been populated with actual dividend text
+                                // (not just empty comments)
+                                const hasRealContent = textContent.length > 50 && (
+                                    textContent.includes('Previous Dividend') ||
+                                    textContent.includes('Pay Date') ||
+                                    textContent.includes('Ex-Date') ||
+                                    textContent.includes('Frequency') ||
+                                    textContent.includes('Annual Dividend') ||
+                                    textContent.includes('$') ||
+                                    textContent.includes('%')
+                                );
+
+                                if (hasRealContent) {
+                                    result.loaded = true;
+                                    return result;
+                                }
+                            }
+                        }
+
+                        // Alternative: check for stock-dividends component
+                        const stockDividends = document.querySelector('stock-dividends');
+                        if (stockDividends) {
+                            const text = stockDividends.textContent || '';
+                            result.debug.stockDividendsLength = text.length;
+                            result.debug.stockDividendsSample = text.substring(0, 100);
+
+                            if (text.length > 20 && text.includes('$')) {
+                                result.loaded = true;
+                                return result;
+                            }
+                        }
+
+                        // Alternative: check for any elements with dividend-related content
+                        const allElements = document.querySelectorAll('#dividends *');
+                        result.debug.totalElements = allElements.length;
+
+                        for (let elem of allElements) {
+                            const text = elem.textContent || '';
+                            if (text.includes('Previous Dividend Payment') || 
+                                (text.includes('$') && text.includes('.'))) {
+                                result.loaded = true;
+                                result.debug.foundInElement = elem.tagName + '.' + elem.className;
+                                return result;
+                            }
+                        }
+
+                        return result;
+                    }
+                ''')
+
+                if debug:
+                    print(f"DEBUG: Dividend status: {dividend_status}")
+
+                dividend_loaded = dividend_status.get('loaded', False)
+
+                if dividend_loaded:
+                    if debug:
+                        print("DEBUG: Dynamic dividend content loaded!")
+                        png = await page.screenshot(full_page=True)
+                        path = save_debug_artifact("debug_dividend_content_loaded.png", png)
+                        print(f"DEBUG: Screenshot after content loaded: {path}")
+                    break
+
+                # Wait between attempts to allow for async loading
+                await page.wait_for_timeout(1000)  # Reduced from 2000ms for faster tests
+
+            if not dividend_loaded:
+                if debug:
+                    print("DEBUG: Basic dividend content did not auto-load - this suggests the page is not behaving as expected")
+                    print("DEBUG: Expected behavior: Basic dividend info should be visible without clicking 'Show More'")
+
+                    # Try to force a page refresh or trigger loading
+                    print("DEBUG: Attempting to trigger dividend content loading...")
+                    try:
+                        # Try scrolling to the dividend section to trigger lazy loading
+                        await page.evaluate('''
+                            () => {
+                                const dividendsPanel = document.querySelector('#dividends');
+                                if (dividendsPanel) {
+                                    dividendsPanel.scrollIntoView({ behavior: 'smooth', block: 'center' });
+                                }
+                            }
+                        ''')
+                        await page.wait_for_timeout(3000)
+
+                        # Try clicking on the dividends panel header to ensure it's active
+                        try:
+                            dividends_header = await page.query_selector('#dividends h2, #dividends .sdps-panel__title')
+                            if dividends_header:
+                                await dividends_header.click()
+                                await page.wait_for_timeout(2000)
+                                print("DEBUG: Clicked on dividends panel header")
+                        except:
+                            pass
+
+                        # Check one more time if content loaded
+                        final_status = await page.evaluate('''
+                            () => {
+                                const dividendsPanel = document.querySelector('#dividends');
+                                if (dividendsPanel) {
+                                    const panelBody = dividendsPanel.querySelector('.sdps-panel__body');
+                                    if (panelBody) {
+                                        const textContent = panelBody.textContent || '';
+                                        return {
+                                            length: textContent.length,
+                                            sample: textContent.substring(0, 500),
+                                            hasBasicData: textContent.includes('$') && (
+                                                textContent.includes('Previous') || 
+                                                textContent.includes('Pay Date') ||
+                                                textContent.includes('Ex-Date')
+                                            )
+                                        };
+                                    }
+                                }
+                                return { length: 0, sample: '', hasBasicData: false };
+                            }
+                        ''')
+
+                        if debug:
+                            print(f"DEBUG: Final dividend panel status: {final_status}")
+
+                        if final_status.get('hasBasicData'):
+                            print("DEBUG: Basic dividend data now detected after manual triggering!")
+                            dividend_loaded = True
+
+                            # Extract the data immediately while it's loaded
+                            immediate_extraction = await page.evaluate(r'''
+                                () => {
+                                    const results = {};
+                                    const dividendsPanel = document.querySelector('#dividends');
+
+                                    if (dividendsPanel) {
+                                        const panelBody = dividendsPanel.querySelector('.sdps-panel__body');
+                                        if (panelBody) {
+                                            const fullText = panelBody.textContent || '';
+
+                                            // Extract data using pattern matching from the full text
+                                            const patterns = {
+                                                'Previous Dividend Payment': /Previous Dividend Payment\s*\$([0-9]+\.[0-9]+)/,
+                                                'Previous Pay Date': /Previous Pay Date\s*([A-Za-z]+ [0-9]{1,2}, [0-9]{4})/,
+                                                'Previous Ex-Date': /Previous Ex-Date\s*([A-Za-z]+ [0-9]{1,2}, [0-9]{4})/,
+                                                'Frequency': /Frequency\s*([A-Za-z]+)/,
+                                                'Annual Dividend Rate': /(?:Annual Dividend Rate|IAD).*?\$([0-9]+\.[0-9]+)/,
+                                                'Annual Dividend Yield': /([0-9]+\.[0-9]+%)(?=\s|Annual|$)/
+                                            };
+
+                                            for (const [field, pattern] of Object.entries(patterns)) {
+                                                const match = fullText.match(pattern);
+                                                if (match) {
+                                                    if (field === 'Previous Dividend Payment' || field === 'Annual Dividend Rate') {
+                                                        results[field] = '$' + match[1];
+                                                    } else {
+                                                        results[field] = match[1];
+                                                    }
+                                                }
+                                            }
+                                        }
+                                    }
+
+                                    return results;
+                                }
+                            ''')
+
+                            if debug:
+                                print(f"DEBUG: Immediate extraction results: {immediate_extraction}")
+
+                            if immediate_extraction:
+                                dividend_data.update(immediate_extraction)
+                                # Clean up the Frequency field if it has extra text
+                                if 'Frequency' in dividend_data and 'Quarterly' in dividend_data['Frequency']:
+                                    dividend_data['Frequency'] = 'Quarterly'
+
+                    except Exception as e:
+                        if debug:
+                            print(f"DEBUG: Error during manual triggering: {e}")
+
+                    png = await page.screenshot(full_page=True)
+                    path = save_debug_artifact("debug_dividend_timeout.png", png)
+                    print(f"DEBUG: Screenshot after timeout: {path}")
+
+        except Exception as e:
+            if debug:
+                print(f"DEBUG: Error waiting for dividend content: {e}")
+
+        # Check for dividend grid directly without clicking
+        if debug:
+            print("DEBUG: Checking for #dividend-grid...")
+
+        dividend_grid_found = False
+        try:
+            await page.wait_for_selector('#dividend-grid', timeout=10000)
+            dividend_grid_found = True
+            if debug:
+                print("DEBUG: #dividend-grid found!")
+                png = await page.screenshot(full_page=True)
+                path = save_debug_artifact("debug_dividend_grid_found.png", png)
+                print(f"DEBUG: Screenshot with dividend grid: {path}")
+        except:
+            if debug:
+                print("DEBUG: #dividend-grid not found initially")
+                png = await page.screenshot(full_page=True)
+                path = save_debug_artifact("debug_dividend_no_grid.png", png)
+                print(f"DEBUG: Screenshot without grid: {path}")
+
+        # Try to scroll to the dividend section to ensure it's in view
+        if debug:
+            print("DEBUG: Scrolling to stock-dividends component...")
+
+        try:
+            await page.evaluate('''
+                () => {
+                    const stockDividends = document.querySelector('stock-dividends');
+                    if (stockDividends) {
+                        stockDividends.scrollIntoView({ behavior: 'smooth', block: 'center' });
+                    }
+                }
+            ''')
+            await page.wait_for_timeout(3000)
+
+            if debug:
+                png = await page.screenshot(full_page=True)
+                path = save_debug_artifact("debug_dividend_after_scroll.png", png)
+                print(f"DEBUG: Screenshot after scroll: {path}")
+
+            # Check again for dividend grid after scrolling
+            try:
+                await page.wait_for_selector('#dividend-grid', timeout=5000)
+                dividend_grid_found = True
+                if debug:
+                    print("DEBUG: #dividend-grid found after scroll!")
+                    png = await page.screenshot(full_page=True)
+                    path = save_debug_artifact("debug_dividend_grid_after_scroll.png", png)
+                    print(f"DEBUG: Screenshot with grid after scroll: {path}")
+            except:
+                if debug:
+                    print("DEBUG: #dividend-grid still not found after scroll")
+
+        except Exception as e:
+            if debug:
+                print(f"DEBUG: Error during scroll attempt: {e}")
+
+        # Common dividend section selectors used by financial websites
+        dividend_selectors = [
+            '#dividend-grid',  # Primary target based on user feedback
+            'stock-dividends',  # Secondary target - the web component
+            '#dividend-section',
+            '#dividends-section', 
+            '.dividend-summary',
+            '.dividends-summary',
+            'div[data-testid*="dividend"]',
+            'div[aria-label*="dividend"]',
+            '[class*="dividend"]',
+            'section:has-text("Dividend")',
+            'div:has-text("Previous Dividend Payment")'
+        ]
+
+        # Try to find dividend section
+        dividend_section = None
+        for selector in dividend_selectors:
+            try:
+                if await page.is_visible(selector):
+                    dividend_section = selector
+                    if debug:
+                        print(f"DEBUG: Found dividend section with selector: {selector}")
+                    break
+            except:
+                continue
+
+        if not dividend_section:
+            if debug:
+                print("DEBUG: No dividend section found, trying broader search...")
+
+                # In debug mode, capture the page content to help identify selectors
+                page_content = await page.content()
+                path_html = save_debug_artifact("debug_dividend_page.html", page_content)
+                print(f"DEBUG: Page HTML saved to {path_html} for analysis")
+
+                # Also save a screenshot to see the visual layout
+                png = await page.screenshot(full_page=True)
+                path_png = save_debug_artifact("debug_dividend_page.png", png)
+                print(f"DEBUG: Page screenshot saved to {path_png}")
+
+            # Fallback: look for dividend-related text anywhere on page
+            dividend_text_exists = await page.evaluate('''
+                () => {
+                    const text = document.body.innerText.toLowerCase();
+                    return text.includes('dividend') || text.includes('ex-date') || text.includes('pay date') || text.includes('previous dividend') || text.includes('iad');
+                }
+            ''')
+
+            if debug:
+                print(f"DEBUG: Dividend-related text found on page: {dividend_text_exists}")
+
+                # Try scrolling down to reveal more content
+                await page.evaluate('window.scrollTo(0, document.body.scrollHeight)')
+                await page.wait_for_timeout(2000)
+
+                # Extract all text content that might contain dividend info
+                dividend_related_text = await page.evaluate('''
+                    () => {
+                        const text = document.body.innerText;
+                        const lines = text.split('\n');
+                        const dividendLines = lines.filter(line => {
+                            const lower = line.toLowerCase();
+                            return lower.includes('dividend') || lower.includes('ex-date') || 
+                                   lower.includes('pay date') || lower.includes('previous') ||
+                                   lower.includes('iad') || lower.includes('frequency') ||
+                                   lower.includes('quarterly') || lower.includes('$0.26') ||
+                                   lower.includes('0.4865%') || lower.includes('$1.04') ||
+                                   lower.includes('annual dividend') || lower.includes('yield');
+                        });
+                        return dividendLines;
+                    }
+                ''')
+                print(f"DEBUG: Found dividend-related text lines: {dividend_related_text}")
+
+                # Try a more comprehensive search for dividend data
+                all_dividend_info = await page.evaluate('''
+                    () => {
+                        // Look for elements containing common dividend field names
+                        const fieldNames = [
+                            'Previous Dividend Payment', 'Next Dividend Payment',
+                            'Previous Pay Date', 'Next Pay Date',
+                            'Previous Ex-Date', 'Next Ex-Date', 'Ex-Date',
+                            'Frequency', 'Annual Dividend Rate', 'IAD',
+                            'Annual Dividend Yield', 'Dividend Yield'
+                        ];
+
+                        const results = {};
+
+                        fieldNames.forEach(fieldName => {
+                            // Search for elements containing this field name
+                            const elements = Array.from(document.querySelectorAll('*')).filter(el => 
+                                el.textContent && el.textContent.includes(fieldName) && 
+                                el.children.length === 0  // Text nodes only
+                            );
+
+                            elements.forEach(el => {
+                                // Look for value in nearby elements
+                                const parent = el.parentElement;
+                                if (parent) {
+                                    const siblings = Array.from(parent.children);
+                                    const currentIndex = siblings.indexOf(el);
+
+                                    // Check next siblings for values
+                                    for (let i = currentIndex + 1; i < siblings.length; i++) {
+                                        const sibling = siblings[i];
+                                        const text = sibling.textContent.trim();
+                                        if (text && text !== fieldName && text.length > 0 && text.length < 50) {
+                                            results[fieldName] = text;
+                                            break;
+                                        }
+                                    }
+
+                                    // Check same element for values after the field name
+                                    const fullText = el.textContent;
+                                    const fieldIndex = fullText.indexOf(fieldName);
+                                    if (fieldIndex >= 0) {
+                                        const afterField = fullText.substring(fieldIndex + fieldName.length).trim();
+                                        if (afterField && afterField.length > 0 && afterField.length < 50) {
+                                            results[fieldName] = afterField;
+                                        }
+                                    }
+                                }
+                            });
+                        });
+
+                        return results;
+                    }
+                ''')
+                print(f"DEBUG: Comprehensive dividend search results: {all_dividend_info}")
+
+                # If we found data in the comprehensive search, use it only if we don't already have good data
+                if all_dividend_info:
+                    for field, value in all_dividend_info.items():
+                        if value and value.strip():
+                            existing_value = dividend_data.get(field, '')
+                            if should_replace_dividend_value(existing_value, value):
+                                dividend_data[field] = value.strip()
+                                if debug:
+                                    print(f"DEBUG: Added dividend field from comprehensive search: {field} = {value}")
+                            elif debug:
+                                print(f"DEBUG: Keeping existing good data for {field}: {existing_value} (ignoring comprehensive search value: {value})")
+
+            if not dividend_text_exists:
+                if debug:
+                    print("DEBUG: No dividend-related content found on page")
+                return dividend_data
+
+            # Use body as fallback section for broad search
+            dividend_section = 'body'
+            if debug:
+                print("DEBUG: Using body as dividend section for broad search")
+
+        # If we found the dividend grid, use specific selectors based on user feedback
+        if dividend_section == '#dividend-grid':
+            if debug:
+                print("DEBUG: Using specific dividend grid selectors...")
+
+            try:
+                # First check if dividend grid is actually present and populated
+                grid_status = await page.evaluate('''
+                    () => {
+                        const dividendGrid = document.querySelector('#dividend-grid');
+                        if (!dividendGrid) return { found: false, message: 'No #dividend-grid element found' };
+
+                        const textContent = dividendGrid.textContent || '';
+                        const hasContent = textContent.trim().length > 50;
+                        const childCount = dividendGrid.children.length;
+
+                        return {
+                            found: true,
+                            hasContent,
+                            textLength: textContent.length,
+                            childCount,
+                            preview: textContent.substring(0, 200),
+                            message: `Grid found with ${childCount} children, ${textContent.length} chars`
+                        };
+                    }
+                ''')
+
+                if debug:
+                    print(f"DEBUG: Dividend grid status: {grid_status}")
+
+                # Extract dividend data using improved selectors
+                specific_dividend_data = await page.evaluate(r'''
+                    () => {
+                        const results = {};
+
+                        // Check if dividend grid exists and has content
+                        const dividendGrid = document.querySelector('#dividend-grid');
+                        if (dividendGrid) {
+                            const allGridText = dividendGrid.textContent || '';
+                            const lines = allGridText.split('\n').map(line => line.trim()).filter(line => line.length > 0);
+
+                            // Try structured approach first - look for rows/cells
+                            const dividendRows = dividendGrid.querySelectorAll('div[class*="row"], tr, .dividend-row, div:has(div)');
+                            dividendRows.forEach((row, rowIndex) => {
+                                const rowText = row.textContent || '';
+
+                                // Look for dividend payment info
+                                if (rowText.includes('Dividend Payment') || (rowText.includes('Previous') && rowText.includes('$'))) {
+                                    const amountMatch = rowText.match(/\$[0-9]+\.[0-9]+/);
+                                    if (amountMatch && !results['Previous Dividend Payment']) {
+                                        results['Previous Dividend Payment'] = amountMatch[0];
+                                    }
+
+                                    // Look for dates in the same row
+                                    const dateMatches = rowText.match(/([A-Za-z]+ [0-9]{1,2}, [0-9]{4})/g);
+                                    if (dateMatches) {
+                                        if (dateMatches.length >= 1 && !results['Previous Pay Date']) results['Previous Pay Date'] = dateMatches[0];
+                                        if (dateMatches.length >= 2 && !results['Previous Ex-Date']) results['Previous Ex-Date'] = dateMatches[1];
+                                    }
+                                }
+                            });
+
+                            // Fallback: Parse all lines systematically
+                            for (let i = 0; i < lines.length; i++) {
+                                const line = lines[i];
+                                const nextLine = i + 1 < lines.length ? lines[i + 1] : '';
+
+                                // Match dividend payment
+                                if ((line.includes('Previous Dividend Payment') || line.includes('Dividend Payment')) && !results['Previous Dividend Payment']) {
+                                    const amountPattern = /\$[0-9]+\.[0-9]+/;
+                                    let amount = line.match(amountPattern) || nextLine.match(amountPattern);
+                                    if (amount) results['Previous Dividend Payment'] = amount[0];
+                                }
+
+                                // Match pay date
+                                if (line.includes('Pay Date') && !results['Previous Pay Date']) {
+                                    const datePattern = /[A-Za-z]{3,9} [0-9]{1,2}, [0-9]{4}/;
+                                    let date = line.match(datePattern) || nextLine.match(datePattern);
+                                    if (date) results['Previous Pay Date'] = date[0];
+                                }
+
+                                // Match ex-date
+                                if (line.includes('Ex-Date') && !results['Previous Ex-Date']) {
+                                    const datePattern = /[A-Za-z]{3,9} [0-9]{1,2}, [0-9]{4}/;
+                                    let date = line.match(datePattern) || nextLine.match(datePattern);
+                                    if (date) results['Previous Ex-Date'] = date[0];
+                                }
+
+                                // Match frequency
+                                if (line.includes('Frequency') && !results['Frequency']) {
+                                    const freqLine = line + ' ' + nextLine;
+                                    if (freqLine.toLowerCase().includes('quarterly')) results['Frequency'] = 'Quarterly';
+                                    else if (freqLine.toLowerCase().includes('monthly')) results['Frequency'] = 'Monthly';
+                                    else if (freqLine.toLowerCase().includes('annual')) results['Frequency'] = 'Annual';
+                                    else if (freqLine.toLowerCase().includes('semi')) results['Frequency'] = 'Semi-Annual';
+                                }
+
+                                // Match annual dividend rate
+                                if ((line.includes('Annual Dividend Rate') || line.includes('IAD')) && !results['Annual Dividend Rate']) {
+                                    const amountPattern = /\$[0-9]+\.[0-9]+/;
+                                    let amount = line.match(amountPattern) || nextLine.match(amountPattern);
+                                    if (amount) results['Annual Dividend Rate'] = amount[0];
+                                }
+
+                                // Match annual dividend yield
+                                if (line.includes('Annual Dividend Yield') && !results['Annual Dividend Yield']) {
+                                    const percentPattern = /[0-9]+\.[0-9]+%/;
+                                    let percent = line.match(percentPattern) || nextLine.match(percentPattern);
+                                    if (percent) results['Annual Dividend Yield'] = percent[0];
+                                }
+                            }
+                        }
+
+                        return results;
+                    }
+                ''')
+
+                if debug:
+                    print(f"DEBUG: Specific dividend grid extraction results: {specific_dividend_data}")
+
+                # Add the extracted data to dividend_data only if we don't already have good data
+                if specific_dividend_data:
+                    for field, value in specific_dividend_data.items():
+                        existing_value = dividend_data.get(field, '')
+                        if should_replace_dividend_value(existing_value, value):
+                            dividend_data[field] = value
+                            if debug:
+                                print(f"DEBUG: Updated {field} from specific extraction: {value}")
+                        elif debug:
+                            print(f"DEBUG: Keeping existing good data for {field}: {existing_value} (ignoring specific extraction value: {value})")
+
+            except Exception as e:
+                if debug:
+                    print(f"DEBUG: Error in specific dividend grid extraction: {e}")
+
+        # Extract dividend data using the correct structure from gemini analysis
+        if debug:
+            print("DEBUG: Extracting dividend data from dividend-grid structure...")
+
+        # First try to extract data from the dynamically loaded dividend content
+        try:
+            dividend_dynamic_data = await page.evaluate(r'''
+                () => {
+                    const results = {};
+
+                    // Strategy 1: Look for any dividend grid structure that was loaded
+                    const dividendGrid = document.querySelector('#dividend-grid');
+                    if (dividendGrid) {
+                        const rows = dividendGrid.querySelectorAll('div.sdps-row, .row');
+
+                        for (let row of rows) {
+                            const cells = row.querySelectorAll('div[class*="col-"]');
+                            if (cells.length >= 2) {
+                                const label = cells[0].textContent.trim();
+                                const value = cells[1].textContent.trim();
+
+                                // Map the labels to our expected field names
+                                if (label.includes('Previous Dividend Payment') || label.includes('Dividend Payment')) {
+                                    results['Previous Dividend Payment'] = value;
+                                } else if (label.includes('Previous Pay Date') || label.includes('Pay Date')) {
+                                    results['Previous Pay Date'] = value;
+                                } else if (label.includes('Previous Ex-Date') || label.includes('Ex-Date')) {
+                                    results['Previous Ex-Date'] = value;
+                                } else if (label.includes('Frequency')) {
+                                    results['Frequency'] = value;
+                                } else if (label.includes('Annual Dividend Rate') || label.includes('IAD')) {
+                                    results['Annual Dividend Rate'] = value;
+                                } else if (label.includes('Annual Dividend Yield')) {
+                                    results['Annual Dividend Yield'] = value;
+                                }
+                            }
+                        }
+
+                        if (Object.keys(results).length > 0) {
+                            return results;
+                        }
+                    }
+
+                    // Strategy 2: Look for stock-dividends component content
+                    const stockDividends = document.querySelector('stock-dividends');
+                    if (stockDividends) {
+                        const allText = stockDividends.textContent || '';
+                        const lines = allText.split('\n').map(line => line.trim()).filter(line => line);
+
+                        for (let i = 0; i < lines.length; i++) {
+                            const line = lines[i];
+                            const nextLine = i + 1 < lines.length ? lines[i + 1] : '';
+
+                            if (line.includes('Previous Dividend Payment') || line.includes('Dividend Payment')) {
+                                const amountMatch = (line + ' ' + nextLine).match(/\$[0-9]+\.[0-9]+/);
+                                if (amountMatch) results['Previous Dividend Payment'] = amountMatch[0];
+                            } else if (line.includes('Pay Date')) {
+                                const dateMatch = (line + ' ' + nextLine).match(/[A-Za-z]+ [0-9]{1,2}, [0-9]{4}/);
+                                if (dateMatch) results['Previous Pay Date'] = dateMatch[0];
+                            } else if (line.includes('Ex-Date')) {
+                                const dateMatch = (line + ' ' + nextLine).match(/[A-Za-z]+ [0-9]{1,2}, [0-9]{4}/);
+                                if (dateMatch) results['Previous Ex-Date'] = dateMatch[0];
+                            } else if (line.includes('Frequency')) {
+                                if (line.toLowerCase().includes('quarterly') || nextLine.toLowerCase().includes('quarterly')) {
+                                    results['Frequency'] = 'Quarterly';
+                                } else if (line.toLowerCase().includes('monthly') || nextLine.toLowerCase().includes('monthly')) {
+                                    results['Frequency'] = 'Monthly';
+                                } else if (line.toLowerCase().includes('annual') || nextLine.toLowerCase().includes('annual')) {
+                                    results['Frequency'] = 'Annual';
+                                }
+                            } else if (line.includes('Annual Dividend Rate') || line.includes('IAD')) {
+                                const amountMatch = (line + ' ' + nextLine).match(/\$[0-9]+\.[0-9]+/);
+                                if (amountMatch) results['Annual Dividend Rate'] = amountMatch[0];
+                            } else if (line.includes('Annual Dividend Yield')) {
+                                const percentMatch = (line + ' ' + nextLine).match(/[0-9]+\.[0-9]+%/);
+                                if (percentMatch) results['Annual Dividend Yield'] = percentMatch[0];
+                            }
+                        }
+
+                        if (Object.keys(results).length > 0) {
+                            return results;
+                        }
+                    }
+
+                    // Strategy 3: Look within entire dividends panel for any structured content
+                    const dividendsPanel = document.querySelector('#dividends');
+                    if (dividendsPanel) {
+                        const allElements = dividendsPanel.querySelectorAll('*');
+
+                        for (let elem of allElements) {
+                            const text = elem.textContent || '';
+
+                            // Look for dollar amounts near dividend-related text
+                            if (text.includes('Previous Dividend Payment') || text.includes('Dividend Payment')) {
+                                const parent = elem.parentElement;
+                                if (parent) {
+                                    const siblings = Array.from(parent.children);
+                                    const currentIndex = siblings.indexOf(elem);
+
+                                    // Check next siblings for values
+                                    for (let j = currentIndex + 1; j < siblings.length; j++) {
+                                        const sibling = siblings[j];
+                                        const siblingText = sibling.textContent.trim();
+                                        const amountMatch = siblingText.match(/\$[0-9]+\.[0-9]+/);
+                                        if (amountMatch) {
+                                            results['Previous Dividend Payment'] = amountMatch[0];
+                                            break;
+                                        }
+                                    }
+                                }
+                            }
+
+                            // Similar logic for other fields...
+                            // (truncated for brevity but would include Pay Date, Ex-Date, etc.)
+                        }
+                    }
+
+                    return results;
+                }
+            ''')
+
+            if debug:
+                print(f"DEBUG: Dynamic dividend extraction results: {dividend_dynamic_data}")
+
+            if dividend_dynamic_data:
+                for field, value in dividend_dynamic_data.items():
+                    existing_value = dividend_data.get(field, '')
+                    if should_replace_dividend_value(existing_value, value):
+                        dividend_data[field] = value
+                        if debug:
+                            print(f"DEBUG: Updated {field} from dynamic extraction: {value}")
+                    elif debug:
+                        print(f"DEBUG: Keeping existing good data for {field}: {existing_value} (ignoring dynamic extraction value: {value})")
+
+        except Exception as e:
+            if debug:
+                print(f"DEBUG: Error in dynamic dividend extraction: {e}")
+
+        # Define dividend fields and their possible selectors as fallback
+        dividend_fields = {
+            'Previous Dividend Payment': [
+                '#dividend-grid div:has-text("Previous Dividend Payment") ~ div',
+                '#dividend-grid div:has-text("Dividend Payment") ~ div',
+                '#dividends span:has-text("Previous Dividend Payment") + span',
+                '#dividends div:has-text("Previous Dividend Payment") + div',
+                '#dividends *:has-text("Previous Dividend Payment") ~ *',
+                'stock-dividends span:has-text("Previous Dividend Payment") + span',
+                'stock-dividends div:has-text("Previous Dividend Payment") + div',
+                'span:has-text("Previous Dividend Payment") + span',
+                'div:has-text("Previous Dividend Payment") + div',
+                '*:has-text("Previous Dividend Payment") ~ *',
+                'span:has-text("Next Dividend Payment") + span',
+                'div:has-text("Next Dividend Payment") + div',
+                '*:has-text("Next Dividend Payment") ~ *',
+                '[data-field="dividend-payment"]',
+                '.dividend-payment'
+            ],
+            'Previous Pay Date': [
+                '#dividend-grid div:has-text("Previous Pay Date") ~ div',
+                '#dividend-grid div:has-text("Pay Date") ~ div',
+                '#dividends span:has-text("Previous Pay Date") + span',
+                '#dividends div:has-text("Previous Pay Date") + div',
+                '#dividends *:has-text("Previous Pay Date") ~ *',
+                'stock-dividends span:has-text("Previous Pay Date") + span',
+                'stock-dividends div:has-text("Previous Pay Date") + div',
+                'span:has-text("Previous Pay Date") + span',
+                'div:has-text("Previous Pay Date") + div', 
+                '*:has-text("Previous Pay Date") ~ *',
+                'span:has-text("Next Pay Date") + span',
+                'div:has-text("Next Pay Date") + div', 
+                '*:has-text("Next Pay Date") ~ *',
+                '*:has-text("Pay Date") ~ *',
+                '[data-field="pay-date"]',
+                '.pay-date'
+            ],
+            'Previous Ex-Date': [
+                '#dividend-grid div:has-text("Previous Ex-Date") ~ div',
+                '#dividend-grid div:has-text("Ex-Date") ~ div',
+                '#dividends span:has-text("Previous Ex-Date") + span',
+                '#dividends div:has-text("Previous Ex-Date") + div',
+                '#dividends *:has-text("Previous Ex-Date") ~ *',
+                'stock-dividends span:has-text("Previous Ex-Date") + span',
+                'stock-dividends div:has-text("Previous Ex-Date") + div',
+                'span:has-text("Previous Ex-Date") + span',
+                'div:has-text("Previous Ex-Date") + div',
+                '*:has-text("Previous Ex-Date") ~ *',
+                'span:has-text("Next Ex-Date") + span',
+                'div:has-text("Next Ex-Date") + div',
+                '*:has-text("Next Ex-Date") ~ *',
+                '*:has-text("Ex-Date") ~ *',
+                '[data-field="ex-date"]',
+                '.ex-date'
+            ],
+            'Frequency': [
+                '#dividend-grid div:has-text("Frequency") ~ div',
+                '#dividends span:has-text("Frequency") + span',
+                '#dividends div:has-text("Frequency") + div',
+                '#dividends *:has-text("Frequency") ~ *',
+                'stock-dividends span:has-text("Frequency") + span',
+                'stock-dividends div:has-text("Frequency") + div',
+                'span:has-text("Frequency") + span',
+                'div:has-text("Frequency") + div',
+                '*:has-text("Frequency") ~ *',
+                '[data-field="frequency"]',
+                '.dividend-frequency',
+                '.frequency'
+            ],
+            'Annual Dividend Rate': [
+                '#dividend-grid div:has-text("Annual Dividend Rate") ~ div',
+                '#dividend-grid div:has-text("IAD") ~ div',
+                '#dividends span:has-text("Annual Dividend Rate") + span',
+                '#dividends div:has-text("Annual Dividend Rate") + div',
+                '#dividends *:has-text("Annual Dividend Rate") ~ *',
+                '#dividends span:has-text("IAD") + span',
+                '#dividends *:has-text("IAD") ~ *',
+                'stock-dividends span:has-text("Annual Dividend Rate") + span',
+                'stock-dividends div:has-text("Annual Dividend Rate") + div',
+                'stock-dividends span:has-text("IAD") + span',
+                'span:has-text("Annual Dividend Rate") + span',
+                'div:has-text("Annual Dividend Rate") + div',
+                '*:has-text("Annual Dividend Rate") ~ *',
+                'span:has-text("IAD") + span',
+                '*:has-text("IAD") ~ *',
+                '[data-field="annual-rate"]',
+                '.annual-dividend-rate'
+            ],
+            'Annual Dividend Yield': [
+                '#dividend-grid div:has-text("Annual Dividend Yield") ~ div',
+                '#dividends span:has-text("Annual Dividend Yield") + span',
+                '#dividends div:has-text("Annual Dividend Yield") + div',
+                '#dividends *:has-text("Annual Dividend Yield") ~ *',
+                'stock-dividends span:has-text("Annual Dividend Yield") + span',
+                'stock-dividends div:has-text("Annual Dividend Yield") + div',
+                'span:has-text("Annual Dividend Yield") + span',
+                'div:has-text("Annual Dividend Yield") + div',
+                '*:has-text("Annual Dividend Yield") ~ *',
+                '[data-field="dividend-yield"]',
+                '.dividend-yield'
+            ]
+        }
+
+        # Extract each dividend field using multiple selector strategies
+        for field_name, selectors in dividend_fields.items():
+            field_found = False
+
+            # Try each selector for this field
+            for selector in selectors:
+                if field_found:
+                    break
+
+                try:
+                    # Scope search within dividend section if found, otherwise search whole page
+                    full_selector = f'{dividend_section} {selector}' if dividend_section != 'body' else selector
+
+                    if await page.is_visible(full_selector, timeout=1000):
+                        value = await page.inner_text(full_selector)
+                        clean_value = value.strip()
+
+                        if clean_value and clean_value != field_name:  # Ensure we got actual value, not the label
+                            existing_value = dividend_data.get(field_name, '')
+                            if should_replace_dividend_value(existing_value, clean_value):
+                                dividend_data[field_name] = clean_value
+                                field_found = True
+                                if debug:
+                                    print(f"DEBUG: Found {field_name}: {clean_value} (selector: {full_selector})")
+                            elif debug:
+                                print(f"DEBUG: Keeping existing good data for {field_name}: {existing_value} (ignoring selector-based value: {clean_value})")
+                            break
+                except:
+                    continue
+
+            # If standard selectors failed, try JavaScript-based text search as fallback
+            if not field_found:
+                try:
+                    # Try multiple variations of the field name
+                    search_terms = [field_name]
+                    if "Previous" in field_name:
+                        search_terms.append(field_name.replace("Previous", "Next"))
+                    if "Annual Dividend Rate" in field_name:
+                        search_terms.append("IAD")
+                    if "Annual Dividend Yield" in field_name:
+                        search_terms.append("Dividend Yield")
+
+                    for search_term in search_terms:
+                        if field_found:
+                            break
+
+                        value = await page.evaluate(rf'''
+                            () => {{
+                                const searchText = "{search_term}";
+
+                                // First check within the dividends section specifically
+                                const dividendsPanel = document.querySelector('#dividends');
+                                const stockDividends = document.querySelector('stock-dividends');
+                                const searchContainers = [dividendsPanel, stockDividends, document];
+
+                                for (let container of searchContainers) {{
+                                    if (!container) continue;
+
+                                    const elements = Array.from(container.querySelectorAll('*'));
+
+                                    for (let elem of elements) {{
+                                        if (elem.textContent && elem.textContent.includes(searchText)) {{
+                                            // Look for next sibling or nearby element with value
+                                            let candidate = elem.nextElementSibling;
+                                            if (candidate && candidate.textContent && 
+                                                !candidate.textContent.includes(searchText) &&
+                                                candidate.textContent.trim().length > 0) {{
+                                                return candidate.textContent.trim();
+                                            }}
+
+                                            // Try parent's next sibling
+                                            candidate = elem.parentElement?.nextElementSibling;
+                                            if (candidate && candidate.textContent && 
+                                                !candidate.textContent.includes(searchText) &&
+                                                candidate.textContent.trim().length > 0) {{
+                                                return candidate.textContent.trim();
+                                            }}
+
+                                            // Try looking in the same element's parent for nearby text
+                                            const parent = elem.parentElement;
+                                            if (parent) {{
+                                                const parentText = parent.textContent;
+                                                const lines = parentText.split('\n');
+                                                for (let i = 0; i < lines.length; i++) {{
+                                                    if (lines[i].includes(searchText) && i + 1 < lines.length) {{
+                                                        const nextLine = lines[i + 1].trim();
+                                                        if (nextLine && !nextLine.includes(searchText)) {{
+                                                            return nextLine;
+                                                        }}
+                                                    }}
+                                                }}
+                                            }}
+                                        }}
+                                    }}
+
+                                    // If found in this container, stop searching
+                                    if (container !== document) {{
+                                        break;
+                                    }}
+                                }}
+                                return null;
+                            }}
+                        ''')
+
+                        if value and value.strip():
+                            existing_value = dividend_data.get(field_name, '')
+                            if should_replace_dividend_value(existing_value, value):
+                                dividend_data[field_name] = value.strip()
+                                field_found = True
+                                if debug:
+                                    print(f"DEBUG: Found {field_name} via JS search with term '{search_term}': {value}")
+                            elif debug:
+                                print(f"DEBUG: Keeping existing good data for {field_name}: {existing_value} (ignoring JS search value: {value})")
+                            break
+
+                except Exception as e:
+                    if debug:
+                        print(f"DEBUG: Could not find {field_name}: {e}")
+                    continue
+
+        if debug:
+            print(f"DEBUG: Extracted dividend data: {dividend_data}")
+
+        return dividend_data
+
+    except Exception as e:
+        if debug:
+            print(f"DEBUG: Error extracting dividend data: {e}")
+        return dividend_data
+
+
+async def extract(page, debug: bool = False) -> Dict[str, Any]:
+    """Compatibility wrapper to call `extract_dividend_data`"""
+    return await extract_dividend_data(page, debug=debug)

schwab_scraper/features/equity/service.py

@@ -0,0 +1,452 @@
+import time
+from typing import Any, Dict, Optional
+import logging
+from ...core.config import load_config, get_playwright_url
+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 Envelope, ErrorType, MorningstarData, EquityPhase1Data, fail, ok
+from .morningstar import find_report, download_report_as_bytes
+from ...storage.cache import ensure_cache_dir, cache_filename, read_cached_pdf, write_cached_pdf
+from .parser import parse as parse_pdf
+from .scraper import extract_dividend_data
+from .phase1_scraper import extract_phase1_data  # DOM scraping - the working approach
+import re
+
+def extract_company_name_from_title(page_title: str, ticker: str):
+    if not page_title:
+        return None
+    try:
+        title = (
+            page_title.replace(" | Charles Schwab", "")
+            .replace(" - Charles Schwab", "")
+            .replace("Stock Quote & Summary", "")
+            .replace("Stock Research", "")
+            .replace("Research", "")
+            .replace("- Research", "")
+        )
+        pattern = rf"^(.+?)\s*\({re.escape(ticker.upper())}\)"
+        match = re.match(pattern, title, re.IGNORECASE)
+        if match:
+            company_name = match.group(1).strip()
+            company_name = company_name.replace(" -", "").strip()
+            if len(company_name) > 1 and not company_name.isdigit():
+                return company_name
+        for separator in [" |", " -"]:
+            if separator in title:
+                potential_name = title.split(separator)[0].strip()
+                if potential_name.upper() != ticker.upper() and len(potential_name) > 1:
+                    return potential_name
+        return None
+    except Exception:
+        return None
+
+
+async def get_equity_phase1_data(ticker: str, debug: bool = False) -> Envelope[EquityPhase1Data]:
+    """Get Phase 1 enhanced equity data for a ticker.
+    
+    Extracts:
+    - Quote/Price Data (symbol bar)
+    - Enhanced Dividend Information (forward-looking dates)
+    - Core Earnings Metrics (EPS, forecasts)
+    - Basic Valuation Ratios (P/E, Forward P/E, PEG)
+    - Calculated Metrics (payout ratio)
+    
+    Args:
+        ticker: Stock ticker symbol
+        debug: Enable debug logging
+        
+    Returns:
+        Envelope containing EquityPhase1Data or error
+    """
+    ticker = ticker.upper()
+    logger = logging.getLogger(__name__)
+    if debug:
+        logger.setLevel(logging.DEBUG)
+        logger.debug(f"Starting get_equity_phase1_data for {ticker}")
+
+    # Session management
+    cookies = await ensure_cookies()
+    if not cookies:
+        return fail(
+            "Unable to establish a session. Provide credentials in config.json or a valid cookies.json.",
+            ErrorType.AUTHENTICATION,
+            retryable=False,
+        )
+
+    config = load_config()
+    playwright_url = get_playwright_url(config)
+
+    # Browser orchestration
+    context = None
+    page = None
+    p, browser = await connect(playwright_url)
+    try:
+        context = await new_context(browser, cookies=cookies)
+        page = await new_page(context)
+
+        # Navigate to stock research page
+        timeout = 30000 if debug else 45000
+        success = await goto_with_auth_check(
+            page,
+            context,
+            f"https://client.schwab.com/app/research/#/stocks/{ticker}",
+            debug=debug,
+            timeout=timeout,
+        )
+        if not success:
+            return fail(
+                "Authentication failed while navigating to research page",
+                ErrorType.AUTHENTICATION,
+                retryable=True,
+            )
+
+        # Validate ticker by checking for stock page content
+        if debug:
+            logger.debug(f"Current page URL: {page.url}")
+        
+        try:
+            # Wait for stock-specific content to appear
+            await page.wait_for_selector(
+                'span.sdps-title-3.sc-sdps-solo-layout:not(.sdps-font-bold), #morningstar-section',
+                timeout=10000,
+                state='visible'
+            )
+        except Exception as wait_err:
+            if debug:
+                logger.debug(f"Timeout waiting for stock content: {wait_err}")
+            return fail(
+                f"Invalid ticker: {ticker}. This appears not to be a valid stock ticker.",
+                ErrorType.VALIDATION,
+                retryable=False,
+            )
+        
+        # Validate content
+        try:
+            has_valid_content = await page.evaluate('''
+                () => {
+                    const nameSpan = document.querySelector('span.sdps-title-3.sc-sdps-solo-layout:not(.sdps-font-bold)');
+                    if (nameSpan && nameSpan.textContent && nameSpan.textContent.trim().length > 2) {
+                        return true;
+                    }
+                    const morningstarSection = document.querySelector('#morningstar-section');
+                    if (morningstarSection) {
+                        return true;
+                    }
+                    return false;
+                }
+            ''')
+            
+            if not has_valid_content:
+                return fail(
+                    f"Invalid ticker: {ticker}. This appears not to be a valid stock ticker.",
+                    ErrorType.VALIDATION,
+                    retryable=False,
+                )
+        except Exception as e:
+            logger.debug(f"Error checking for valid content: {e}")
+            return fail(
+                f"Invalid ticker: {ticker}. Unable to validate ticker.",
+                ErrorType.VALIDATION,
+                retryable=False,
+            )
+
+        # Extract Phase 1 data using improved DOM scraping
+        # Note: API approach failed due to CORS restrictions
+        phase1_data = await extract_phase1_data(page, debug=debug)
+        
+        return ok(phase1_data)
+
+    finally:
+        try:
+            if page is not None:
+                await page.close()
+        except Exception:
+            pass
+        try:
+            if context is not None:
+                await context.close()
+        except Exception:
+            pass
+        for handle in (browser,):
+            try:
+                if handle is not None:
+                    await handle.close()
+            except Exception:
+                pass
+        try:
+            if p is not None:
+                await p.stop()
+        except Exception:
+            pass
+
+
+async def get_morningstar_data(ticker: str, debug: bool = False) -> Envelope[MorningstarData]:
+    ticker = ticker.upper()
+    ensure_cache_dir()
+    logger = logging.getLogger(__name__)
+    if debug:
+        logger.setLevel(logging.DEBUG)
+        logger.debug(f"Starting get_morningstar_data for {ticker}")
+
+    # Session management
+    cookies = await ensure_cookies()
+    if not cookies:
+        return fail(
+            "Unable to establish a session. Provide credentials in config.json or a valid cookies.json.",
+            ErrorType.AUTHENTICATION,
+            retryable=False,
+        )
+
+    config = load_config()
+    playwright_url = get_playwright_url(config)
+
+    # Browser orchestration
+    context = None
+    page = None
+    p, browser = await connect(playwright_url)
+    try:
+        context = await new_context(browser, cookies=cookies)
+        page = await new_page(context)
+
+        # Use shared auth-aware navigation helper for consistency
+        # Use shorter timeout for tests to speed up execution
+        timeout = 30000 if debug else 45000
+        success = await goto_with_auth_check(
+            page,
+            context,
+            f"https://client.schwab.com/app/research/#/stocks/{ticker}",
+            debug=debug,
+            timeout=timeout,
+        )
+        if not success:
+            return fail(
+                "Authentication failed while navigating to research page",
+                ErrorType.AUTHENTICATION,
+                retryable=True,
+            )
+
+        # Validate ticker by checking for stock page content
+        # Schwab doesn't redirect on invalid tickers, but the page content is empty/invalid
+        if debug:
+            logger.debug(f"Current page URL: {page.url}")
+        
+        # Wait for page content to load - Schwab's research page loads asynchronously
+        # Give it time to populate the DOM before validation
+        try:
+            # Wait for either company name or Morningstar section to appear
+            # This indicates the page has loaded stock-specific content
+            await page.wait_for_selector(
+                'span.sdps-title-3.sc-sdps-solo-layout:not(.sdps-font-bold), #morningstar-section',
+                timeout=10000,
+                state='visible'
+            )
+        except Exception as wait_err:
+            # If neither selector appears after 10 seconds, likely an invalid ticker
+            if debug:
+                logger.debug(f"Timeout waiting for stock content: {wait_err}")
+            return fail(
+                f"Invalid ticker: {ticker}. This appears not to be a valid stock ticker.",
+                ErrorType.VALIDATION,
+                retryable=False,
+            )
+        
+        # Additional validation: check if we have valid stock page content
+        try:
+            has_valid_content = await page.evaluate('''
+                () => {
+                    // Look for company name span (valid stock pages have this)
+                    const nameSpan = document.querySelector('span.sdps-title-3.sc-sdps-solo-layout:not(.sdps-font-bold)');
+                    if (nameSpan && nameSpan.textContent && nameSpan.textContent.trim().length > 2) {
+                        return true;
+                    }
+                    
+                    // Look for Morningstar section (valid stock pages have this)
+                    const morningstarSection = document.querySelector('#morningstar-section');
+                    if (morningstarSection) {
+                        return true;
+                    }
+                    
+                    // Look for company profile description (valid stock pages have this)
+                    const profileText = document.querySelector('p.sdps-text-body.sc-sdps-solo-layout');
+                    if (profileText && profileText.textContent && profileText.textContent.trim().length > 50) {
+                        return true;
+                    }
+                    
+                    // Look for any stock-related content
+                    const stockContent = document.querySelector('#stock-details, #quote, [data-testid="stock-quote"]');
+                    if (stockContent) {
+                        return true;
+                    }
+                    
+                    return false;
+                }
+            ''')
+            
+            if debug:
+                logger.debug(f"Valid stock content detected: {has_valid_content}")
+            
+            if not has_valid_content:
+                if debug:
+                    logger.debug(f"Invalid ticker detected - no stock content found")
+                return fail(
+                    f"Invalid ticker: {ticker}. This appears not to be a valid stock ticker.",
+                    ErrorType.VALIDATION,
+                    retryable=False,
+                )
+        except Exception as e:
+            logger.debug(f"Error checking for valid content: {e}")
+            # If we can't check, assume invalid and return error
+            return fail(
+                f"Invalid ticker: {ticker}. Unable to validate ticker.",
+                ErrorType.VALIDATION,
+                retryable=False,
+            )
+
+        # Company name - extract from page elements
+        company_name = None
+        try:
+            # Strategy 1: Extract from company name span element
+            company_name = await page.evaluate('''
+                () => {
+                    // Look for company name in title span
+                    const nameSpan = document.querySelector('span.sdps-title-3.sc-sdps-solo-layout:not(.sdps-font-bold)');
+                    if (nameSpan && nameSpan.textContent && nameSpan.textContent.trim().length > 2) {
+                        return nameSpan.textContent.trim();
+                    }
+
+                    // Fallback: Extract from company profile description
+                    const profileText = document.querySelector('p.sdps-text-body.sc-sdps-solo-layout');
+                    if (profileText && profileText.textContent) {
+                        const text = profileText.textContent.trim();
+                        // Extract company name before " designs" or " is" or " provides"
+                        const match = text.match(/^([A-Za-z0-9\\s&\\.,'-]+?)(?:\\s+(?:designs|is|provides|manufactures|operates|offers|engages))/i);
+                        if (match) {
+                            return match[1].trim();
+                        }
+                    }
+
+                    return null;
+                }
+            ''')
+            if debug and company_name:
+                logger.debug(f"Extracted company name: {company_name}")
+        except Exception as e:
+            logger.debug(f"Company name extraction error: {e}")
+
+        # Morningstar section wait
+        try:
+            await page.wait_for_selector('#morningstar-section', timeout=30000)
+        except Exception:
+            logger.debug("#morningstar-section not found within timeout")
+
+        # Dividends
+        try:
+            dividend_data = await extract_dividend_data(page, debug=debug)
+        except Exception as exc:
+            logger.debug(f"Dividend extraction error: {exc}")
+            dividend_data = {}
+
+        # Find report and download/cache
+        report_url, report_date = await find_report(page, debug=debug)
+        data: Dict[str, Any] = {}
+        if report_date:
+            data["Morningstar Equity Report Date"] = report_date.strip()
+        if report_url:
+            # Only store actual URL, not the __CLICK_TO_OPEN__ marker
+            if report_url != '__CLICK_TO_OPEN__':
+                data["Morningstar Equity Report URL"] = report_url
+            pdf_bytes = await download_report_as_bytes(page, report_url, debug=debug)
+        else:
+            pdf_bytes = None
+
+        parsed_data: Dict[str, Any] = {}
+        if pdf_bytes:
+            if report_date:
+                from datetime import datetime
+                try:
+                    dt = datetime.strptime(report_date, "%b %d, %Y")
+                    formatted_date = dt.strftime("%m-%d-%Y")
+                except Exception:
+                    formatted_date = report_date.replace(" ", "-")
+            else:
+                formatted_date = time.strftime("%m-%d-%Y")
+            write_cached_pdf(ticker, formatted_date, pdf_bytes)
+            try:
+                parsed_data = parse_pdf(pdf_bytes)
+                parsed_data["source"] = "live"
+            except Exception as exc:
+                logger.debug(f"PDF parsing failed: {exc}")
+                parsed_data = {"error": "Failed to parse Morningstar report"}
+        else:
+            cached = read_cached_pdf(ticker)
+            if cached:
+                try:
+                    parsed_data = parse_pdf(cached)
+                    parsed_data["source"] = "cache"
+                except Exception as exc:
+                    logger.debug(f"Cached PDF parsing failed: {exc}")
+                    parsed_data = {"error": "Failed to parse cached Morningstar report"}
+            else:
+                parsed_data = {"error": f"Failed to download and no cache available for {ticker}"}
+
+        morningstar = MorningstarData(
+            ticker=ticker,
+            company_name=company_name,
+            previous_dividend_payment=dividend_data.get("Previous Dividend Payment"),
+            previous_pay_date=dividend_data.get("Previous Pay Date"),
+            previous_ex_date=dividend_data.get("Previous Ex-Dividend Date"),
+            frequency=dividend_data.get("Frequency"),
+            annual_dividend_rate=dividend_data.get("Annual Dividend Rate"),
+            annual_dividend_yield=dividend_data.get("Annual Dividend Yield"),
+            fair_value=parsed_data.get("Fair Value"),
+            economic_moat=parsed_data.get("Economic Moat"),
+            capital_allocation=parsed_data.get("Capital Allocation"),
+            rating=_safe_int(parsed_data.get("Morningstar Rating")),
+            one_star_price=parsed_data.get("1-Star Price"),
+            five_star_price=parsed_data.get("5-Star Price"),
+            assessment=parsed_data.get("Assessment"),
+            range_52_week=parsed_data.get("52-Week Range"),
+            dividend_yield=parsed_data.get("Dividend Yield"),
+            investment_style=parsed_data.get("Investment Style"),
+            report_url=data.get("Morningstar Equity Report URL"),
+            report_date=data.get("Morningstar Equity Report Date"),
+            source=parsed_data.get("source"),
+        )
+
+        if parsed_data.get("error"):
+            return fail(parsed_data["error"], ErrorType.PARSING, retryable=True)
+
+        return ok(morningstar)
+
+    finally:
+        try:
+            if page is not None:
+                await page.close()
+        except Exception:
+            pass
+        try:
+            if context is not None:
+                await context.close()
+        except Exception:
+            pass
+        for handle in (browser,):
+            try:
+                if handle is not None:
+                    await handle.close()
+            except Exception:
+                pass
+        try:
+            if p is not None:
+                await p.stop()
+        except Exception:
+            pass
+
+
+def _safe_int(value: Any) -> Optional[int]:
+    if value is None:
+        return None
+    try:
+        return int(str(value).strip())
+    except (TypeError, ValueError):
+        return None

schwab_scraper/features/transactions/parser.py

@@ -0,0 +1,47 @@
+from __future__ import annotations
+
+import csv
+import io
+from dataclasses import asdict
+from typing import List, Dict, Any
+
+from ...core.models import TransactionRecord, TransactionData, AccountInfo
+
+
+def parse_csv_content(csv_bytes: bytes) -> List[TransactionRecord]:
+    """
+    Parse Schwab transaction CSV bytes into a list of TransactionRecord.
+
+    Expected headers:
+    Date,Action,Symbol,Description,Quantity,Price,Fees & Comm,Amount
+    """
+    text_stream = io.StringIO(csv_bytes.decode("utf-8"))
+    reader = csv.DictReader(text_stream)
+
+    records: List[TransactionRecord] = []
+    for row in reader:
+        records.append(
+            TransactionRecord(
+                date=(row.get("Date") or "").strip(),
+                action=(row.get("Action") or "").strip(),
+                symbol=(row.get("Symbol") or None) or None,
+                description=(row.get("Description") or "").strip(),
+                quantity=(row.get("Quantity") or None) or None,
+                price=(row.get("Price") or None) or None,
+                fees_comm=(row.get("Fees & Comm") or None) or None,
+                amount=(row.get("Amount") or None) or None,
+            )
+        )
+    return records
+
+
+def to_dicts(transaction_data: TransactionData) -> Dict[str, Any]:
+    """Convert TransactionData to plain dicts for JSON output."""
+    return {
+        "account_info": asdict(transaction_data.account_info),
+        "transactions": [asdict(r) for r in transaction_data.transactions],
+        "date_range": transaction_data.date_range,
+        "export_date": transaction_data.export_date,
+        "total_transactions": transaction_data.total_transactions,
+        "source": transaction_data.source,
+    }

schwab_scraper/features/transactions/service.py

@@ -0,0 +1,833 @@
+from __future__ import annotations
+
+import json
+from typing import Optional, Dict, Any, List
+from datetime import datetime, timezone
+import re
+
+from ...browser.auth import ensure_cookies
+from ...core.config import load_config, get_playwright_url
+from ...browser.client import connect, new_context, new_page
+from ...browser.navigation import goto_with_auth_check
+from .scraper import (
+    perform_export_download,
+    perform_export_download_enhanced,
+    discover_accounts_from_page,
+    discover_accounts_with_numbers,
+)
+from .parser import parse_csv_content
+from ...storage.cache import (
+    write_cached_transaction_csv,
+    read_cached_transaction_csv,
+    TRANSACTION_CACHE_DIR,
+)
+from ...core.models import AccountInfo, TransactionData
+from ...core import Envelope, ErrorType, fail, ok
+import os
+
+
+async def _get_transaction_history_enhanced_impl(
+    account: Optional[str] = None,
+    start_date: Optional[str] = None,
+    end_date: Optional[str] = None,
+    time_period: Optional[str] = None,
+    debug: bool = False,
+) -> Envelope[TransactionData]:
+    """
+    Enhanced export with reliable account switching and filename preservation.
+
+    Args:
+        account: Account identifier (ending digits like '674', type like 'PLA Assets', or full label like 'PLA_Assets_XXX674').
+                 ✅ ENHANCED: Now supports reliable automatic account switching with verification.
+        start_date, end_date: Reserved for future "Custom" range support.
+        time_period: One of pre-defined periods (e.g., "Current Month", "Last 6 Months"). If None, uses page default.
+        debug: Enable debug logging and screenshots.
+
+    Returns:
+        Dict with transaction data, account info, and export metadata.
+    """
+    print("Starting enhanced transaction export...")
+    if debug:
+        print(f"  Account: {account}")
+        print(f"  Time period: {time_period}")
+
+    # Load configuration and cookies
+    config = load_config()
+    playwright_url = get_playwright_url(config)
+    cookies = await ensure_cookies()
+
+    if not cookies:
+        return fail(
+            "Could not establish session. Check credentials or manually refresh cookies.json.",
+            ErrorType.AUTHENTICATION,
+            retryable=False,
+        )
+
+    # Connect to browser
+    p, browser = await connect(playwright_url)
+    context = None
+    page = None
+
+    try:
+        context = await new_context(browser, cookies=cookies)
+        page = await new_page(context)
+
+        # Use the enhanced export function
+        export_result = await perform_export_download_enhanced(
+            page=page,
+            time_period=time_period,
+            account=account,
+            debug=debug,
+            context=context,
+            preserve_filename=True
+        )
+
+        if not export_result.get("success"):
+            # Try fallback to cached data
+            if account:
+                if debug:
+                    print("Enhanced export failed, trying cached fallback...")
+
+                # Determine account label for cache lookup
+                account_label = account
+                if account.isdigit():
+                    # Try to discover accounts to find full label
+                    try:
+                        accounts = await discover_accounts_with_numbers(page, debug=debug)
+                        for acc in accounts:
+                            if acc['ending'] == account[-3:]:
+                                account_label = acc['label']
+                                break
+                    except Exception:
+                        pass
+
+                cached_bytes = read_cached_transaction_csv(account_label)
+                if cached_bytes:
+                    if debug:
+                        print(f"Using cached data for {account_label}")
+                    
+                    # Parse the cached CSV bytes
+                    records = parse_csv_content(cached_bytes)
+                    
+                    # Build account info from the label
+                    account_type = account_label.split('_')[0] if '_' in account_label else "Unknown"
+                    account_ending = account_label[-3:] if account_label[-3:].isdigit() else "000"
+                    
+                    data = TransactionData(
+                        account_info=AccountInfo(
+                            account_type=account_type,
+                            account_ending=account_ending,
+                            full_description=account_label,
+                            is_selected=True,
+                        ),
+                        transactions=records,
+                        date_range=time_period or "Unknown",
+                        export_date="Unknown",
+                        total_transactions=len(records),
+                        source="cache",
+                    )
+                    return ok(data)
+
+            return fail(
+                export_result.get("error", "Enhanced export failed."),
+                ErrorType.UNKNOWN,
+                retryable=True,
+            )
+
+        # Parse the exported CSV
+        saved_path = export_result.get("saved_path")
+        if not saved_path or not os.path.exists(saved_path):
+            return fail("Export file not found after download", ErrorType.PARSING, retryable=True)
+
+        with open(saved_path, 'r', encoding='utf-8') as f:
+            csv_content = f.read()
+
+        parsed_data = parse_csv_content(csv_content.encode('utf-8'))
+        if not parsed_data:
+            return fail("Failed to parse CSV: No transactions found", ErrorType.PARSING, retryable=True)
+
+        # Build response
+        account_info = export_result.get("account_info", {})
+        transactions = parsed_data
+
+        # Cache the results
+        if account_info.get("account_ending"):
+            account_label = f"{account_info.get('account_type', 'Unknown')}_XXX{account_info.get('account_ending')}"
+            try:
+                # Generate timestamp for filename
+                timestamp = datetime.now(timezone.utc).strftime('%Y%m%d-%H%M%S')
+                
+                # Convert transactions back to CSV format for caching
+                import csv
+                import io
+                
+                # Create CSV content from transactions
+                output = io.StringIO()
+                writer = csv.writer(output)
+                
+                # Write header
+                writer.writerow(["Date", "Action", "Symbol", "Description", "Quantity", "Price", "Fees & Comm", "Amount"])
+                
+                # Write transaction data
+                for transaction in transactions:
+                    writer.writerow([
+                        transaction.date,
+                        transaction.action,
+                        transaction.symbol or "",
+                        transaction.description,
+                        transaction.quantity or "",
+                        transaction.price or "",
+                        transaction.fees_comm or "",
+                        transaction.amount or ""
+                    ])
+                
+                csv_bytes = output.getvalue().encode('utf-8')
+                write_cached_transaction_csv(account_label, timestamp, csv_bytes)
+                
+                if debug:
+                    print(f"Cached transaction data for {account_label}")
+            except Exception as e:
+                if debug:
+                    print(f"Failed to cache data: {e}")
+
+        data = TransactionData(
+            account_info=AccountInfo(
+                account_type=account_info.get("account_type", "Unknown"),
+                account_ending=account_info.get("account_ending", "000"),
+                full_description=account_info.get("full_description", ""),
+                is_selected=account_info.get("is_selected", True),
+            ),
+            transactions=transactions,
+            date_range=time_period or "Unknown",
+            export_date=datetime.now(timezone.utc).strftime('%Y-%m-%d %H:%M:%S UTC'),
+            total_transactions=len(transactions),
+            source="live",
+        )
+
+        if debug:
+            print(f"✅ Enhanced export successful: {len(transactions)} transactions")
+
+        return ok(data)
+
+    except Exception as e:
+        if debug:
+            print(f"Enhanced export exception: {e}")
+            import traceback
+            traceback.print_exc()
+        return fail(f"Enhanced export failed: {str(e)}", ErrorType.UNKNOWN, retryable=True)
+
+    finally:
+        if page:
+            await page.close()
+        if context:
+            await context.close()
+        if browser:
+            await browser.close()
+
+
+async def _ensure_cookies() -> Optional[List[Dict[str, Any]]]:
+    # Delegate to shared helper
+    return await ensure_cookies()
+
+
+def _get_latest_cache_csv_filename(account_label: str) -> Optional[str]:
+    """Return the most recent CSV filename under the account's cache directory, if any."""
+    import os
+    dir_path = os.path.join(TRANSACTION_CACHE_DIR, account_label)
+    if not os.path.isdir(dir_path):
+        return None
+    csv_files = [f for f in os.listdir(dir_path) if f.lower().endswith('.csv')]
+    if not csv_files:
+        return None
+    # Sort by mtime if possible; fall back to lexical
+    try:
+        csv_files.sort(key=lambda f: os.path.getmtime(os.path.join(dir_path, f)))
+    except Exception:
+        csv_files.sort()
+    return csv_files[-1]
+
+
+def _is_cache_fresh_for_label(account_label: str, max_age_hours: int = 24) -> bool:
+    """Return True if the most recent CSV for `account_label` is within `max_age_hours`."""
+    import os, time
+    dir_path = os.path.join(TRANSACTION_CACHE_DIR, account_label)
+    if not os.path.isdir(dir_path):
+        return False
+    csv_files = [f for f in os.listdir(dir_path) if f.lower().endswith('.csv')]
+    if not csv_files:
+        return False
+    # Use mtime (file creation/update time) to assess freshness
+    newest_path = max((os.path.join(dir_path, f) for f in csv_files), key=lambda p: os.path.getmtime(p))
+    age_seconds = time.time() - os.path.getmtime(newest_path)
+    return age_seconds <= max_age_hours * 3600
+
+
+def _match_account_label_from_cache(account_query: Optional[str]) -> Optional[str]:
+    """Resolve a matching account label from cache directories given a query like '604' or 'PLA_Assets_XXX674'.
+    Only returns a label if a fresh (<=24h) CSV exists for that label.
+    """
+    import os
+    if not os.path.isdir(TRANSACTION_CACHE_DIR):
+        return None
+    labels = [name for name in os.listdir(TRANSACTION_CACHE_DIR)
+              if os.path.isdir(os.path.join(TRANSACTION_CACHE_DIR, name))]
+    if not labels:
+        return None
+
+    def label_matches(label: str, query: str) -> bool:
+        if not query:
+            return True
+        if query == label:
+            return True
+        # match by ending digits
+        if query.isdigit() and label.endswith(query):
+            return True
+        # substring match (e.g., 'PLA_Assets')
+        if query.lower() in label.lower():
+            return True
+        return False
+
+    # If no query provided: return latest fresh label if any
+    if not account_query:
+        fresh_labels = [lbl for lbl in labels if _is_cache_fresh_for_label(lbl)]
+        if not fresh_labels:
+            return None
+        fresh_labels.sort(key=lambda n: os.path.getmtime(os.path.join(TRANSACTION_CACHE_DIR, n)), reverse=True)
+        return fresh_labels[0]
+
+    # Query provided: only return a matching fresh label
+    for lbl in labels:
+        if label_matches(lbl, account_query) and _is_cache_fresh_for_label(lbl):
+            return lbl
+
+    # No fresh matching label
+    return None
+
+
+async def _get_transaction_history_impl(
+    account: Optional[str] = None,
+    start_date: Optional[str] = None,
+    end_date: Optional[str] = None,
+    time_period: Optional[str] = None,
+    debug: bool = False,
+) -> Envelope[TransactionData]:
+    """
+    Export and parse transaction history for the selected account.
+
+    Args:
+        account: Account identifier (ending digits like '604', name like 'Joint', or full label like 'PLA_Assets_XXX674').
+                 ⚠️  IMPORTANT: Due to Schwab's website design, automatic account switching causes browser crashes.
+                 If the wrong account is selected, you'll get clear instructions to manually select the correct account first.
+        start_date, end_date: Reserved for future "Custom" range support.
+        time_period: One of pre-defined periods (e.g., "Current Month", "Last 6 Months"). If None, uses page default.
+    """
+    # Basic input validation for optional custom date params
+    def _parse_date(date_str: str) -> Optional[datetime]:
+        # Accept YYYY-MM-DD or MM/DD/YYYY
+        if re.fullmatch(r"\d{4}-\d{2}-\d{2}", date_str):
+            try:
+                return datetime.strptime(date_str, "%Y-%m-%d")
+            except ValueError:
+                return None
+        if re.fullmatch(r"\d{2}/\d{2}/\d{4}", date_str):
+            try:
+                return datetime.strptime(date_str, "%m/%d/%Y")
+            except ValueError:
+                return None
+        return None
+
+    if start_date:
+        start_dt = _parse_date(start_date)
+        if not start_dt:
+            return fail(f"Invalid start_date format: '{start_date}'. Use YYYY-MM-DD or MM/DD/YYYY.", ErrorType.VALIDATION, retryable=False)
+    else:
+        start_dt = None
+
+    if end_date:
+        end_dt = _parse_date(end_date)
+        if not end_dt:
+            return fail(f"Invalid end_date format: '{end_date}'. Use YYYY-MM-DD or MM/DD/YYYY.", ErrorType.VALIDATION, retryable=False)
+    else:
+        end_dt = None
+
+    if start_dt and end_dt and start_dt > end_dt:
+        return fail(
+            "start_date must be on or before end_date",
+            ErrorType.VALIDATION,
+            retryable=False,
+        )
+
+    cookies = await _ensure_cookies()
+    if not cookies:
+        account_label = _match_account_label_from_cache(account)
+        if account_label:
+            cached_bytes = read_cached_transaction_csv(account_label)
+            if cached_bytes:
+                records = parse_csv_content(cached_bytes)
+                export_date = datetime.now(timezone.utc).strftime('%Y-%m-%d %H:%M:%S UTC')
+                account_info = AccountInfo(
+                    account_type=account_label.split('_')[0],
+                    account_ending=account_label[-3:],
+                    full_description=account_label,
+                    is_selected=True,
+                )
+                data = TransactionData(
+                    account_info=account_info,
+                    transactions=records,
+                    date_range=time_period or "Cache",
+                    export_date=export_date,
+                    total_transactions=len(records),
+                    source="cache",
+                )
+                return ok(data)
+        return fail(
+            "Unable to establish a session. Provide credentials in config.json or a valid cookies.json.",
+            ErrorType.AUTHENTICATION,
+            retryable=False,
+        )
+
+    config = load_config()
+    playwright_url = get_playwright_url(config)
+
+    p, browser = await connect(playwright_url)
+    context = None
+    page = None
+    try:
+        context = await new_context(browser, cookies=cookies)
+        page = await new_page(context)
+
+        try:
+            download = await perform_export_download(
+                page,
+                time_period=time_period,
+                account=account,
+                debug=debug,
+                context=context,
+            )
+            csv_bytes = download["content"]
+            account_label = download["label"]
+            ts = download["ts"]
+
+            # Cache
+            write_cached_transaction_csv(account_label, ts, csv_bytes)
+
+            # Parse
+            records = parse_csv_content(csv_bytes)
+
+            # Build metadata
+            export_date = datetime.now(timezone.utc).strftime('%Y-%m-%d %H:%M:%S UTC')
+            account_info = AccountInfo(
+                account_type=account_label.split('_')[0],
+                account_ending=account_label[-3:],
+                full_description=account_label,
+                is_selected=True,
+            )
+            data = TransactionData(
+                account_info=account_info,
+                transactions=records,
+                date_range=time_period or "Page Default",
+                export_date=export_date,
+                total_transactions=len(records),
+                source="live",
+            )
+            return ok(data)
+        except Exception as e:
+            # First failure: attempt one reconnect and retry, then fallback to cache
+            if debug:
+                try:
+                    print(f"DEBUG: perform_export_download failed: {type(e).__name__}: {e}")
+                except Exception:
+                    pass
+            # Attempt one reconnect if browser/context appears closed
+            try:
+                # Cleanup previous if possible
+                try:
+                    if context is not None:
+                        await context.close()
+                except Exception:
+                    pass
+                try:
+                    await browser.close()
+                except Exception:
+                    pass
+                try:
+                    await p.stop()
+                except Exception:
+                    pass
+
+                # Reconnect
+                p, browser = await connect(playwright_url)
+                context = await new_context(browser, cookies=cookies)
+                page = await new_page(context)
+                # Retry export
+                if debug:
+                    print("DEBUG: Retrying perform_export_download after reconnect...")
+                download = await perform_export_download(
+                    page,
+                    time_period=time_period,
+                    account=account,
+                    debug=debug,
+                    context=context,
+                )
+                csv_bytes = download["content"]
+                account_label = download["label"]
+                ts = download["ts"]
+
+                # Cache
+                write_cached_transaction_csv(account_label, ts, csv_bytes)
+
+                # Parse
+                records = parse_csv_content(csv_bytes)
+
+                export_date = datetime.now(timezone.utc).strftime('%Y-%m-%d %H:%M:%S UTC')
+                account_info = AccountInfo(
+                    account_type=account_label.split('_')[0],
+                    account_ending=account_label[-3:],
+                    full_description=account_label,
+                    is_selected=True,
+                )
+                data = TransactionData(
+                    account_info=account_info,
+                    transactions=records,
+                    date_range=time_period or "Page Default",
+                    export_date=export_date,
+                    total_transactions=len(records),
+                    source="live",
+                )
+                return ok(data)
+            except Exception as e2:
+                if debug:
+                    try:
+                        print(f"DEBUG: Retry after reconnect failed: {type(e2).__name__}: {e2}")
+                    except Exception:
+                        pass
+                # Fall back to cache if available and fresh
+                account_label = _match_account_label_from_cache(account)
+                if account_label:
+                    cached_bytes = read_cached_transaction_csv(account_label)
+                    if cached_bytes:
+                        records = parse_csv_content(cached_bytes)
+                        export_date = datetime.now(timezone.utc).strftime('%Y-%m-%d %H:%M:%S UTC')
+                        account_info = AccountInfo(
+                            account_type=account_label.split('_')[0],
+                            account_ending=account_label[-3:],
+                            full_description=account_label,
+                            is_selected=True,
+                        )
+                        data = TransactionData(
+                            account_info=account_info,
+                            transactions=records,
+                            date_range=time_period or "Cache",
+                            export_date=export_date,
+                            total_transactions=len(records),
+                            source="cache",
+                        )
+                        return ok(data)
+                return fail("Export failed and no fresh cache available", ErrorType.UNKNOWN, retryable=True)
+
+    except Exception as e:
+        return fail(str(e), ErrorType.UNKNOWN, retryable=True)
+
+    finally:
+        try:
+            if context is not None:
+                await context.close()
+        except Exception:
+            pass
+        try:
+            await browser.close()
+        except Exception:
+            pass
+        try:
+            await p.stop()
+        except Exception:
+            pass
+
+
+def _get_cache_accounts(debug: bool = False) -> List[Dict[str, Any]]:
+    """Get accounts from cache directory fallback with enhanced validation."""
+    from ...storage.cache import TRANSACTION_CACHE_DIR
+    import os
+    from datetime import datetime
+    
+    if not os.path.isdir(TRANSACTION_CACHE_DIR):
+        if debug:
+            print(f"DEBUG: Cache directory does not exist: {TRANSACTION_CACHE_DIR}")
+        return []
+    
+    out = []
+    cache_dirs = []
+    
+    # Collect all cache directories with metadata
+    for name in os.listdir(TRANSACTION_CACHE_DIR):
+        path = os.path.join(TRANSACTION_CACHE_DIR, name)
+        if os.path.isdir(path):
+            try:
+                # Get directory modification time and file count
+                stat = os.stat(path)
+                csv_files = [f for f in os.listdir(path) if f.endswith('.csv')]
+                cache_dirs.append({
+                    'name': name,
+                    'path': path,
+                    'mtime': stat.st_mtime,
+                    'csv_count': len(csv_files),
+                    'csv_files': csv_files
+                })
+            except Exception as e:
+                if debug:
+                    print(f"DEBUG: Error processing cache dir {name}: {e}")
+                continue
+    
+    # Sort by modification time (most recent first) to prioritize active accounts
+    cache_dirs.sort(key=lambda x: x['mtime'], reverse=True)
+    
+    if debug:
+        print(f"DEBUG: Found {len(cache_dirs)} cache directories")
+    
+    for cache_info in cache_dirs:
+        name = cache_info['name']
+        csv_files = cache_info['csv_files']
+        
+        if not csv_files:
+            if debug:
+                print(f"DEBUG: Skipping {name} - no CSV files")
+            continue
+        
+        try:
+            # Normalize using filename parser to ensure consistent label
+            normalized_label = name
+            account_type = None
+            account_ending = None
+            
+            # Strategy 1: Use directory name if it matches expected pattern
+            if re.match(r"^[A-Za-z_]+_XXX\d{3,4}$", name):
+                normalized_label = name
+                parts = name.split('_XXX')
+                account_type = parts[0].replace('_', ' ')
+                account_ending = parts[1] if len(parts) > 1 else name[-3:]
+            else:
+                # Strategy 2: Parse from most recent CSV filename
+                try:
+                    from .scraper import parse_suggested_filename
+                    latest_csv = sorted(csv_files)[-1]  # Get most recent file
+                    parsed_filename = parse_suggested_filename(latest_csv)
+                    normalized_label = parsed_filename["label"]
+                    
+                    # Extract type and ending from parsed label
+                    if '_XXX' in normalized_label:
+                        parts = normalized_label.split('_XXX')
+                        account_type = parts[0].replace('_', ' ')
+                        account_ending = parts[1] if len(parts) > 1 else normalized_label[-3:]
+                except Exception as e:
+                    if debug:
+                        print(f"DEBUG: Failed to parse filename for {name}: {e}")
+                    # Strategy 3: Fallback to directory name parsing
+                    normalized_label = name
+                    account_type = name
+                    account_ending = name[-3:] if name[-3:].isdigit() else "000"
+            
+            # Validate the parsed data
+            if not account_ending or not account_ending.isdigit() or len(account_ending) < 3:
+                if debug:
+                    print(f"DEBUG: Invalid account ending for {name}: {account_ending}")
+                continue
+            
+            # Create account entry
+            account_entry = {
+                "label": normalized_label,
+                "type": account_type or normalized_label.split('_')[0],
+                "ending": account_ending[-3:],  # Ensure 3 digits
+                "cache_info": {
+                    "last_updated": datetime.fromtimestamp(cache_info['mtime']).isoformat(),
+                    "csv_count": cache_info['csv_count']
+                }
+            }
+            
+            out.append(account_entry)
+            
+            if debug:
+                print(f"DEBUG: Added cache account: {normalized_label} ({account_type} ending {account_ending[-3:]}) - {cache_info['csv_count']} files")
+                
+        except Exception as e:
+            if debug:
+                print(f"DEBUG: Error processing cache account {name}: {e}")
+            continue
+    
+    if debug:
+        print(f"DEBUG: Successfully processed {len(out)} accounts from cache")
+        if not out:
+            print(f"DEBUG: Cache directory contents: {os.listdir(TRANSACTION_CACHE_DIR) if os.path.isdir(TRANSACTION_CACHE_DIR) else 'N/A'}")
+    
+    return out
+
+
+async def _list_available_accounts_impl(debug: bool = False) -> List[Dict[str, Any]]:
+    """Return list of available accounts from live page when possible; fall back to cache with enhanced reliability."""
+    if debug:
+        print("DEBUG: Starting account listing with enhanced discovery...")
+    
+    # Try live discovery with enhanced error handling
+    cookies = await _ensure_cookies()
+    if cookies:
+        if debug:
+            print("DEBUG: Session cookies available, attempting live account discovery...")
+        
+        config = load_config()
+        playwright_url = get_playwright_url(config)
+        p, browser = await connect(playwright_url)
+        context = None
+        page = None
+        try:
+            context = await new_context(browser, cookies=cookies)
+            page = await new_page(context)
+            
+            # Use centralized auth-aware navigation with retry
+            max_auth_attempts = 2
+            auth_success = False
+            
+            for auth_attempt in range(max_auth_attempts):
+                if debug:
+                    print(f"DEBUG: Authentication attempt {auth_attempt + 1}/{max_auth_attempts}...")
+                
+                auth_success = await goto_with_auth_check(page, context, "https://client.schwab.com/app/accounts/history/#/", debug=debug)
+                if auth_success:
+                    break
+                elif auth_attempt < max_auth_attempts - 1:
+                    if debug:
+                        print("DEBUG: Authentication failed, retrying...")
+                    await page.wait_for_timeout(3000)
+            
+            if not auth_success:
+                if debug:
+                    print("DEBUG: All authentication attempts failed")
+                raise Exception("Authentication failed after multiple attempts")
+            
+            if debug:
+                print("DEBUG: Successfully authenticated, discovering accounts from live dropdown...")
+            
+            # Enhanced account discovery with fallback strategies
+            accounts = []
+            
+            try:
+                accounts = await discover_accounts_from_page(page, debug=debug)
+                if debug:
+                    print(f"DEBUG: Live account discovery returned {len(accounts)} accounts")
+            except Exception as e:
+                if debug:
+                    print(f"DEBUG: Live account discovery failed: {e}")
+                accounts = []
+            
+            # Enhanced result processing
+            if accounts:
+                if debug:
+                    print(f"DEBUG: Successfully discovered {len(accounts)} accounts from live page:")
+                    for acc in accounts:
+                        print(f"DEBUG: - {acc['label']} ({acc['type']} ending {acc['ending']})")
+                
+                # Always try to enrich with cache data for completeness
+                cache_accounts = _get_cache_accounts(debug=debug)
+                if cache_accounts:
+                    if debug:
+                        print(f"DEBUG: Found {len(cache_accounts)} accounts in cache, merging...")
+                    
+                    # Merge live and cache, preferring live data but keeping unique cache entries
+                    combined = {acc['ending']: acc for acc in cache_accounts}
+                    live_endings = set()
+                    
+                    for live_acc in accounts:
+                        combined[live_acc['ending']] = live_acc  # Live data takes precedence
+                        live_endings.add(live_acc['ending'])
+                    
+                    result = list(combined.values())
+                    if debug:
+                        print(f"DEBUG: Final merged result: {len(result)} accounts")
+                        for acc in result:
+                            source = "live" if acc['ending'] in live_endings else "cache"
+                            print(f"DEBUG: - {acc['label']} ({acc['type']} ending {acc['ending']}) [{source}]")
+                    
+                    return result
+                else:
+                    if debug:
+                        print("DEBUG: No cache data available, returning live accounts only")
+                    return accounts
+            else:
+                if debug:
+                    print("DEBUG: No accounts discovered from live page, falling back to cache only")
+                
+        except Exception as e:
+            if debug:
+                print(f"DEBUG: Live account discovery failed with error: {e}")
+            # Continue to cache fallback
+            
+        finally:
+            # Enhanced cleanup
+            cleanup_tasks = []
+            if context is not None:
+                cleanup_tasks.append(context.close())
+            if browser is not None:
+                cleanup_tasks.append(browser.close())
+            if p is not None:
+                cleanup_tasks.append(p.stop())
+            
+            for task in cleanup_tasks:
+                try:
+                    await task
+                except Exception:
+                    pass
+    else:
+        if debug:
+            print("DEBUG: No session cookies available, skipping live discovery")
+
+    # Enhanced cache fallback
+    if debug:
+        print("DEBUG: Using cache-only fallback for account listing...")
+    
+    cache_accounts = _get_cache_accounts(debug=debug)
+    if cache_accounts:
+        if debug:
+            print(f"DEBUG: Successfully retrieved {len(cache_accounts)} accounts from cache")
+        return cache_accounts
+    else:
+        if debug:
+            print("DEBUG: No accounts found in cache either")
+        return []
+
+
+async def list_available_accounts(debug: bool = False) -> Envelope[List[Dict[str, Any]]]:
+    try:
+        accounts = await _list_available_accounts_impl(debug=debug)
+        return ok(accounts)
+    except Exception as exc:
+        return fail(str(exc), ErrorType.UNKNOWN, retryable=True)
+
+
+async def get_transaction_history(
+    account: Optional[str] = None,
+    start_date: Optional[str] = None,
+    end_date: Optional[str] = None,
+    time_period: Optional[str] = None,
+    debug: bool = False,
+) -> Envelope[TransactionData]:
+    return await _get_transaction_history_impl(
+        account=account,
+        start_date=start_date,
+        end_date=end_date,
+        time_period=time_period,
+        debug=debug,
+    )
+
+
+async def get_transaction_history_enhanced(
+    account: Optional[str] = None,
+    start_date: Optional[str] = None,
+    end_date: Optional[str] = None,
+    time_period: Optional[str] = None,
+    debug: bool = False,
+) -> Envelope[TransactionData]:
+    return await _get_transaction_history_enhanced_impl(
+        account=account,
+        start_date=start_date,
+        end_date=end_date,
+        time_period=time_period,
+        debug=debug,
+    )