1 files changed, 167 insertions, 0 deletions
diff --git a/backend/app/services/data_service.py b/backend/app/services/data_service.py
index 16e062e..bf75bc7 100644
--- a/backend/app/services/data_service.py
+++ b/backend/app/services/data_service.py
@@ -113,6 +113,173 @@ def _safe_ratio(num: float | None, den: float | None) -> float | None:
     return num / den
 
 
+def _build_income(frame: pd.DataFrame, frame_q: pd.DataFrame, quarterly: bool) -> dict:
+    if frame is None or frame.empty:
+        return {"columns": [], "rows": []}
+    n = min(len(frame.columns), 8 if quarterly else 4)
+    col_labels = [_fmt_col(c, quarterly) for c in frame.columns[:n]]
+    if not quarterly:
+        col_labels.append("TTM")
+
+    def v(label: str) -> list[float | None]:
+        base = _row_vals(frame, label, n)
+        return base + ([_statement_ttm(frame_q, label)] if not quarterly else [])
+
+    def vm(*labels: str) -> list[float | None]:
+        base = _row_vals_multi(frame, n, *labels)
+        if not quarterly:
+            ttm = None
+            for lbl in labels:
+                ttm = _statement_ttm(frame_q, lbl)
+                if ttm is not None:
+                    break
+            base = base + [ttm]
+        return base
+
+    rev = v("Total Revenue")
+    gross = v("Gross Profit")
+    net = v("Net Income")
+
+    return {
+        "columns": col_labels,
+        "rows": [
+            _fin_row("Total Revenue", 0, True, rev),
+            _fin_row("Cost of Revenue", 1, False, v("Cost Of Revenue")),
+            _fin_row("Gross Profit", 0, True, gross),
+            _fin_margin("gross margin", [_safe_ratio(g, r) for g, r in zip(gross, rev)]),
+            _fin_row("Operating Expenses", 1, False, v("Operating Expense")),
+            _fin_row("Operating Income", 0, True, v("Operating Income")),
+            _fin_row("EBITDA", 1, False, vm("EBITDA", "Normalized EBITDA")),
+            _fin_row("Interest Expense", 1, False, v("Interest Expense")),
+            _fin_row("Pretax Income", 0, False, v("Pretax Income")),
+            _fin_row("Tax Provision", 1, False, v("Tax Provision")),
+            _fin_row("Net Income", 0, True, net),
+            _fin_margin("net margin", [_safe_ratio(ni, r) for ni, r in zip(net, rev)]),
+            _fin_row("EPS Basic", 1, False, v("Basic EPS")),
+        ],
+    }
+
+
+def _build_balance(frame: pd.DataFrame, frame_q: pd.DataFrame, quarterly: bool) -> dict:
+    if frame is None or frame.empty:
+        return {"columns": [], "rows": []}
+    n = min(len(frame.columns), 8 if quarterly else 4)
+    col_labels = [_fmt_col(c, quarterly) for c in frame.columns[:n]]
+    if not quarterly:
+        col_labels.append("MRQ")
+
+    def v(*labels: str) -> list[float | None]:
+        base = _row_vals_multi(frame, n, *labels)
+        if not quarterly:
+            val = None
+            for lbl in labels:
+                val = _balance_value(frame_q, lbl)
+                if val is not None:
+                    break
+            base = base + [val]
+        return base
+
+    return {
+        "columns": col_labels,
+        "rows": [
+            _fin_section("ASSETS"),
+            _fin_row("Current Assets", 0, True, v("Current Assets")),
+            _fin_row("Cash & Equivalents", 1, False, v("Cash And Cash Equivalents", "Cash Cash Equivalents And Short Term Investments")),
+            _fin_row("Short Term Investments", 1, False, v("Other Short Term Investments", "Short Term Investments")),
+            _fin_row("Receivables", 1, False, v("Receivables", "Net Receivables")),
+            _fin_row("Inventory", 1, False, v("Inventory")),
+            _fin_row("Total Assets", 0, True, v("Total Assets")),
+            _fin_section("LIABILITIES"),
+            _fin_row("Current Liabilities", 0, True, v("Current Liabilities")),
+            _fin_row("Accounts Payable", 1, False, v("Payables And Accrued Expenses", "Accounts Payable")),
+            _fin_row("Short Term Debt", 1, False, v("Current Debt", "Short Term Debt And Capital Lease Obligation")),
+            _fin_row("Long Term Debt", 1, False, v("Long Term Debt", "Long Term Debt And Capital Lease Obligation")),
+            _fin_row("Total Liabilities", 0, True, v("Total Liabilities Net Minority Interest", "Total Liabilities")),
+            _fin_section("EQUITY"),
+            _fin_row("Stockholders Equity", 0, True, v("Stockholders Equity", "Common Stock Equity")),
+        ],
+    }
+
+
+def _build_cash_flow(cf: pd.DataFrame, cf_q: pd.DataFrame, inc: pd.DataFrame, inc_q: pd.DataFrame, quarterly: bool) -> dict:
+    if cf is None or cf.empty:
+        return {"columns": [], "rows": []}
+    n = min(len(cf.columns), 8 if quarterly else 4)
+    col_labels = [_fmt_col(c, quarterly) for c in cf.columns[:n]]
+    if not quarterly:
+        col_labels.append("TTM")
+
+    def cv(*labels: str) -> list[float | None]:
+        base = _row_vals_multi(cf, n, *labels)
+        if not quarterly:
+            ttm = None
+            for lbl in labels:
+                ttm = _statement_ttm(cf_q, lbl)
+                if ttm is not None:
+                    break
+            base = base + [ttm]
+        return base
+
+    def iv(*labels: str) -> list[float | None]:
+        base = _row_vals_multi(inc, n, *labels)
+        if not quarterly:
+            ttm = None
+            for lbl in labels:
+                ttm = _statement_ttm(inc_q, lbl)
+                if ttm is not None:
+                    break
+            base = base + [ttm]
+        return base
+
+    op_cf = cv("Operating Cash Flow", "Cash Flow From Continuing Operating Activities")
+    capex = cv("Capital Expenditure")
+    # CapEx is negative in yfinance; FCF = Operating CF + CapEx
+    fcf = [a + b if a is not None and b is not None else None for a, b in zip(op_cf, capex)]
+    rev = iv("Total Revenue")
+
+    return {
+        "columns": col_labels,
+        "rows": [
+            _fin_section("OPERATING"),
+            _fin_row("Net Income", 1, False, iv("Net Income")),
+            _fin_row("D&A", 1, False, cv("Depreciation And Amortization", "Reconciled Depreciation")),
+            _fin_row("Changes in Working Capital", 1, False, cv("Change In Working Capital")),
+            _fin_row("Operating Cash Flow", 0, True, op_cf),
+            _fin_section("INVESTING"),
+            _fin_row("CapEx", 1, False, capex),
+            _fin_row("Free Cash Flow", 0, True, fcf),
+            _fin_margin("FCF margin", [_safe_ratio(f, r) for f, r in zip(fcf, rev)]),
+            _fin_row("Investing Cash Flow", 0, True, cv("Investing Cash Flow", "Cash Flow From Continuing Investing Activities")),
+            _fin_section("FINANCING"),
+            _fin_row("Dividends Paid", 1, False, cv("Cash Dividends Paid", "Common Stock Dividend Paid")),
+            _fin_row("Buybacks", 1, False, cv("Repurchase Of Capital Stock", "Common Stock Repurchase")),
+            _fin_row("Financing Cash Flow", 0, True, cv("Financing Cash Flow", "Cash Flow From Continuing Financing Activities")),
+            _fin_row("Net Change in Cash", 0, True, cv("Changes In Cash", "End Cash Position")),
+        ],
+    }
+
+
+@cached(FINANCIALS_CACHE)
+def get_financials(symbol: str, period: str = "annual") -> dict:
+    sym = normalize_symbol(symbol)
+    quarterly = period == "quarterly"
+
+    inc = get_income_statement(sym, quarterly=quarterly)
+    bal = get_balance_sheet(sym, quarterly=quarterly)
+    cf = get_cash_flow(sym, quarterly=quarterly)
+
+    inc_q = get_income_statement(sym, quarterly=True) if not quarterly else inc
+    bal_q = get_balance_sheet(sym, quarterly=True) if not quarterly else bal
+    cf_q = get_cash_flow(sym, quarterly=True) if not quarterly else cf
+
+    return {
+        "period": period,
+        "income": _build_income(inc, inc_q, quarterly),
+        "balance": _build_balance(bal, bal_q, quarterly),
+        "cash_flow": _build_cash_flow(cf, cf_q, inc, inc_q, quarterly),
+    }
+
+
 def _balance_value(frame: pd.DataFrame, *labels: str) -> float | None:
     if frame is None or frame.empty:
         return None