V2.1.1 (#51)

* update readme

* updated pkg version and added blank recommendations and test

* added recommendations and tests

Author: TexasCoding

poetry.lock

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "py-alpaca-api"
-version = "2.1.0"
+version = "2.1.1"
 description = "Python package, for communicating with Alpaca Markets REST API."
 authors = ["TexasCoding <[email protected]>"]
 readme = "README.md"

pyproject.toml

@@ -6,6 +6,7 @@
 # from py_alpaca_api.trading.stock import Stock
 from py_alpaca_api.trading.account import Account
 from py_alpaca_api.trading.orders import Orders
+from py_alpaca_api.trading.recommendations import Recommendations
 from py_alpaca_api.trading.watchlists import Watchlist
 
 
@@ -31,3 +32,4 @@ def _initialize_components(self, headers: Dict[str, str], base_url: str):
         self.orders = Orders(headers=headers, base_url=base_url)
         self.watchlists = Watchlist(headers=headers, base_url=base_url)
         self.news = News(headers=headers)
+        self.recommendations = Recommendations()

src/py_alpaca_api/trading/__init__.py

@@ -49,7 +49,7 @@ def scrape_article(url: str) -> str:
         Returns:
             str: The text content of the article, or None if the article body is not found.
         """
-        time.sleep(1)
+        time.sleep(1)  # Sleep for 1 second to avoid rate limiting
         headers = {
             "accept": "*/*",
             "accept-encoding": "gzip, deflate, br",

src/py_alpaca_api/trading/news.py

@@ -0,0 +1,48 @@
+import time
+from typing import Any, Dict, Union
+import pandas as pd
+import yfinance as yf
+
+
+class Recommendations:
+    def __init__(self) -> None:
+        pass
+
+    @staticmethod
+    def get_recommendations(symbol: str) -> Union[Dict[Any, Any], pd.DataFrame]:
+        """
+        Retrieves the latest recommendations for a given stock symbol.
+
+        Args:
+            symbol (str): The stock symbol for which to retrieve recommendations.
+
+        Returns:
+            dict: A dictionary containing the latest recommendations for the stock symbol.
+        """
+        time.sleep(1)  # To avoid hitting the API rate limit
+        ticker = yf.Ticker(symbol)
+        recommendations = ticker.recommendations
+
+        return recommendations
+
+    def get_sentiment(self, symbol: str) -> str:
+        """
+        Retrieves the sentiment for a given stock symbol based on the latest recommendations.
+
+        Args:
+            symbol (str): The stock symbol for which to retrieve the sentiment.
+
+        Returns:
+            str: The sentiment for the stock symbol, either "BULLISH", "BEARISH", or "NEUTRAL".
+        """
+
+        recommendations = self.get_recommendations(symbol)
+        if recommendations.empty:
+            return "NEUTRAL"
+        buy = recommendations["strongBuy"].sum() + recommendations["buy"].sum()
+        sell = (
+            recommendations["strongSell"].sum()
+            + recommendations["sell"].sum()
+            + recommendations["hold"].sum()
+        )
+        return "BULLISH" if (buy / (buy + sell)) > 0.7 else "BEARISH"

src/py_alpaca_api/trading/recommendations.py

@@ -0,0 +1,30 @@
+import os
+import pandas as pd
+import pytest
+from py_alpaca_api import PyAlpacaAPI
+
+api_key = os.environ.get("ALPACA_API_KEY")
+api_secret = os.environ.get("ALPACA_SECRET_KEY")
+
+
+@pytest.fixture
+def news():
+    return PyAlpacaAPI(api_key=api_key, api_secret=api_secret).trading.recommendations
+
+
+def test_get_recommendations(news):
+    recommendations = news.get_recommendations("AAPL")
+    assert len(recommendations) > 0
+    assert isinstance(recommendations, pd.DataFrame)
+    assert "period" in recommendations.columns
+    assert "strongBuy" in recommendations.columns
+    assert "buy" in recommendations.columns
+    assert "hold" in recommendations.columns
+    assert "sell" in recommendations.columns
+    assert "strongSell" in recommendations.columns
+
+
+def test_get_sentiment(news):
+    sentiment = news.get_sentiment("AAPL")
+    assert isinstance(sentiment, str)
+    assert sentiment in ["BULLISH", "BEARISH", "NEUTRAL"]