import requests import pandas as pd from providers.base_provider import BaseProvider from config.settings import POLYGON_API_KEY class PolygonProvider(BaseProvider): def fetch_data(self, symbol, interval="DAILY", api_key=POLYGON_API_KEY, asset_type="forex"): if asset_type == "forex": return self._fetch_forex_data(symbol, interval, api_key) elif asset_type == "stock": return self.fetch_stock_data(symbol, interval, api_key) else: raise ValueError(f"Unsupported asset type: {asset_type}") def _fetch_forex_data(self, symbol, interval="DAILY", api_key=POLYGON_API_KEY): """ Fetch forex data from Polygon.io. :param symbol: Forex pair (e.g., "USDJPY") :param interval: Time interval (e.g., "DAILY", "MINUTE") :param api_key: API key for Polygon.io :return: Pandas DataFrame with OHLCV data """ # Construct the API URL if interval == "DAILY": url = f"https://api.polygon.io/v2/aggs/ticker/C:{symbol}/range/1/day/2000-01-01/2023-12-31?adjusted=true&sort=asc&limit=50000&apiKey={api_key}" elif interval == "MINUTE": url = f"https://api.polygon.io/v2/aggs/ticker/C:{symbol}/range/1/minute/2000-01-01/2023-12-31?adjusted=true&sort=asc&limit=50000&apiKey={api_key}" else: raise ValueError(f"Unsupported interval: {interval}") # Fetch data response = requests.get(url) data = response.json() if "error" in data: error_msg = data.get("error", "Unknown error") raise Exception(f"Error fetching data: {error_msg}") if "results" not in data or not data["results"]: raise Exception("No data available for the given symbol and interval.") # Parse results into a DataFrame df = pd.DataFrame(data["results"]) df.rename(columns={ "o": "Open", "h": "High", "l": "Low", "c": "Close", "v": "Volume", "t": "Timestamp" }, inplace=True) # Convert timestamp to datetime df["Timestamp"] = pd.to_datetime(df["Timestamp"], unit="ms") df.set_index("Timestamp", inplace=True) # Ensure numeric types df[["Open", "High", "Low", "Close", "Volume"]] = df[["Open", "High", "Low", "Close", "Volume"]].astype(float) # Log the fetched data print(f"Fetched {len(df)} rows of data for {symbol}.") if df.empty: raise Exception("Fetched data is empty. Please check the symbol and interval.") return df.sort_index() def fetch_stock_data(self, symbol, interval="DAILY", api_key=POLYGON_API_KEY): url = f"https://api.polygon.io/v2/aggs/ticker/{symbol}/range/1/day/2000-01-01/2023-12-31?adjusted=true&sort=asc&limit=50000&apiKey={api_key}" response = requests.get(url) data = response.json() if "error" in data: error_msg = data.get("error", "Unknown error") raise Exception(f"Error fetching stock data: {error_msg}") if "results" not in data or not data["results"]: raise Exception("No stock data available for the given symbol and interval.") df = pd.DataFrame(data["results"]) df.rename(columns={ "o": "Open", "h": "High", "l": "Low", "c": "Close", "v": "Volume", "t": "Timestamp" }, inplace=True) df["Timestamp"] = pd.to_datetime(df["Timestamp"], unit="ms") df.set_index("Timestamp", inplace=True) df[["Open", "High", "Low", "Close", "Volume"]] = df[["Open", "High", "Low", "Close", "Volume"]].astype(float) return df.sort_index() def fetch_news(self, symbol, api_key=POLYGON_API_KEY): url = f"https://api.polygon.io/v2/reference/news?ticker={symbol}&apiKey={api_key}" response = requests.get(url) data = response.json() if "error" in data: error_msg = data.get("error", "Unknown error") raise Exception(f"Error fetching news: {error_msg}") return data.get("results", []) def fetch_dividends(self, symbol, api_key=POLYGON_API_KEY): url = f"https://api.polygon.io/v2/reference/dividends/{symbol}?apiKey={api_key}" response = requests.get(url) data = response.json() if "error" in data: error_msg = data.get("error", "Unknown error") raise Exception(f"Error fetching dividends: {error_msg}") dividends = data["results"] # Sort dividends by ex-dividend date (most recent first) dividends.sort(key=lambda x: x['exDate'], reverse=True) # Return only the latest 5 dividends return dividends[:5] def fetch_options(self, symbol, expiration_date=None, api_key=POLYGON_API_KEY): if expiration_date: url = f"https://api.polygon.io/v2/snapshot/options/{symbol}/{expiration_date}?apiKey={api_key}" else: url = f"https://api.polygon.io/v2/snapshot/options/{symbol}?apiKey={api_key}" response = requests.get(url) data = response.json() if "error" in data: error_msg = data.get("error", "Unknown error") raise Exception(f"Error fetching options: {error_msg}") return data.get("results", []) def fetch_earnings(self, symbol, api_key=POLYGON_API_KEY): url = f"https://api.polygon.io/v2/reference/earnings/{symbol}?apiKey={api_key}" response = requests.get(url) # Check for HTTP errors if response.status_code != 200: raise Exception(f"HTTP Error: {response.status_code} - {response.reason}") # Print the raw response for debugging print("Raw API Response:", response.text) try: data = response.json() except ValueError as e: raise Exception(f"Error parsing JSON: {str(e)}") # Handle API-specific errors if "error" in data: raise Exception(f"API Error: {data['error']}") if "results" not in data: raise Exception("Unexpected API response format.") return data["results"] def fetch_sector_performance(self, api_key=POLYGON_API_KEY): url = f"https://api.polygon.io/v2/snapshot/locale/us/markets/stocks/sectors?apiKey={api_key}" response = requests.get(url) data = response.json() if "error" in data: error_msg = data.get("error", "Unknown error") raise Exception(f"Error fetching sector performance: {error_msg}") return data.get("results", {}) def fetch_latest_price(self, symbol, api_key=POLYGON_API_KEY): url = f"https://api.polygon.io/v2/snapshot/locale/us/markets/stocks/tickers/{symbol}?apiKey={api_key}" response = requests.get(url) data = response.json() print(data) if "error" in data: error_msg = data.get("error", "Unknown error") raise Exception(f"Error fetching latest price: {error_msg}") latest_price = data["ticker"]["lastQuote"]["P"] return float(latest_price) def fetch_aggregate_data(self, api_key=POLYGON_API_KEY): url = f"https://api.polygon.io/v2/aggs/grouped/locale/us/market/stocks/2023-10-25?adjusted=true&apiKey={api_key}" response = requests.get(url) data = response.json() if "error" in data: error_msg = data.get("error", "Unknown error") raise Exception(f"Error fetching aggregate data: {error_msg}") results = data.get("results", []) df = pd.DataFrame(results) df.rename(columns={ "o": "Open", "h": "High", "l": "Low", "c": "Close", "v": "Volume", "t": "Timestamp" }, inplace=True) df["Timestamp"] = pd.to_datetime(df["Timestamp"], unit="ms") df.set_index("Timestamp", inplace=True) df[["Open", "High", "Low", "Close", "Volume"]] = df[["Open", "High", "Low", "Close", "Volume"]].astype(float) return df.sort_index()