Initial commit — Prism financial analysis dashboard

Streamlit app with market bar, price chart, financial statements,
DCF valuation engine, comparable companies, and news feed.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

1 files changed, 65 insertions, 0 deletions

diff --git a/services/fmp_service.py b/services/fmp_service.py
new file mode 100644
index 0000000..bf31788
--- /dev/null
+++ b/services/fmp_service.py
@@ -0,0 +1,65 @@
+"""Financial Modeling Prep API — ratios, peers, company news."""
+import os
+import requests
+import streamlit as st
+from dotenv import load_dotenv
+
+load_dotenv()
+
+BASE_URL = "https://financialmodelingprep.com/api/v3"
+
+
+def _api_key() -> str:
+    key = os.getenv("FMP_API_KEY", "")
+    return key
+
+
+def _get(endpoint: str, params: dict = None) -> dict | list | None:
+    params = params or {}
+    params["apikey"] = _api_key()
+    try:
+        resp = requests.get(f"{BASE_URL}{endpoint}", params=params, timeout=10)
+        resp.raise_for_status()
+        return resp.json()
+    except Exception:
+        return None
+
+
+@st.cache_data(ttl=3600)
+def get_key_ratios(ticker: str) -> dict:
+    """Return latest TTM key ratios."""
+    data = _get(f"/ratios-ttm/{ticker.upper()}")
+    if data and isinstance(data, list) and len(data) > 0:
+        return data[0]
+    return {}
+
+
+@st.cache_data(ttl=21600)
+def get_peers(ticker: str) -> list[str]:
+    """Return list of comparable ticker symbols."""
+    data = _get(f"/stock_peers", params={"symbol": ticker.upper()})
+    if data and isinstance(data, list) and len(data) > 0:
+        return data[0].get("peersList", [])
+    return []
+
+
+@st.cache_data(ttl=3600)
+def get_ratios_for_tickers(tickers: list[str]) -> list[dict]:
+    """Return TTM ratios for a list of tickers (for comps table)."""
+    results = []
+    for t in tickers:
+        data = _get(f"/ratios-ttm/{t}")
+        if data and isinstance(data, list) and len(data) > 0:
+            row = data[0]
+            row["symbol"] = t
+            results.append(row)
+    return results
+
+
+@st.cache_data(ttl=600)
+def get_company_news(ticker: str, limit: int = 20) -> list[dict]:
+    """Return recent news articles for a ticker."""
+    data = _get("/stock_news", params={"tickers": ticker.upper(), "limit": limit})
+    if data and isinstance(data, list):
+        return data
+    return []