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community[minor]: Add Alpha Vantage API Tool (#14332)
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### Description
This implementation adds functionality from the AlphaVantage API,
renowned for its comprehensive financial data. The class encapsulates
various methods, each dedicated to fetching specific types of financial
information from the API.

### Implemented Functions

- **`search_symbols`**: 
- Searches the AlphaVantage API for financial symbols using the provided
keywords.

- **`_get_market_news_sentiment`**: 
- Retrieves market news sentiment for a specified stock symbol from the
AlphaVantage API.

- **`_get_time_series_daily`**: 
- Fetches daily time series data for a specific symbol from the
AlphaVantage API.

- **`_get_quote_endpoint`**: 
- Obtains the latest price and volume information for a given symbol
from the AlphaVantage API.

- **`_get_time_series_weekly`**: 
- Gathers weekly time series data for a particular symbol from the
AlphaVantage API.

- **`_get_top_gainers_losers`**: 
- Provides details on top gainers, losers, and most actively traded
tickers in the US market from the AlphaVantage API.

  ### Issue: 
  - #11994 
  
### Dependencies: 
  - 'requests' library for HTTP requests. (import requests)
  - 'pytest' library for testing. (import pytest)

---------

Co-authored-by: Adam Badar <[email protected]>
Co-authored-by: Harrison Chase <[email protected]>
Co-authored-by: Bagatur <[email protected]>
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4 people authored Mar 30, 2024
1 parent a9bc212 commit 0884e5d
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190 changes: 166 additions & 24 deletions docs/docs/integrations/tools/alpha_vantage.ipynb
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Expand Up @@ -21,15 +21,7 @@
"metadata": {
"id": "34bb5968"
},
"outputs": [
{
"name": "stdin",
"output_type": "stream",
"text": [
" ········\n"
]
}
],
"outputs": [],
"source": [
"import getpass\n",
"import os\n",
Expand All @@ -56,14 +48,172 @@
"metadata": {
"id": "84b8f773"
},
"outputs": [
{
"data": {
"text/plain": [
"{'Realtime Currency Exchange Rate': {'1. From_Currency Code': 'USD',\n",
" '2. From_Currency Name': 'United States Dollar',\n",
" '3. To_Currency Code': 'JPY',\n",
" '4. To_Currency Name': 'Japanese Yen',\n",
" '5. Exchange Rate': '148.19900000',\n",
" '6. Last Refreshed': '2023-11-30 21:43:02',\n",
" '7. Time Zone': 'UTC',\n",
" '8. Bid Price': '148.19590000',\n",
" '9. Ask Price': '148.20420000'}}"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"alpha_vantage = AlphaVantageAPIWrapper()\n",
"alpha_vantage._get_exchange_rate(\"USD\", \"JPY\")"
]
},
{
"cell_type": "markdown",
"id": "8309d09d",
"metadata": {},
"source": [
"The `_get_time_series_daily` method returns the date, daily open, daily high, daily low, daily close, and daily volume of the global equity specified, covering the 100 latest data points."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "811ae207",
"metadata": {},
"outputs": [],
"source": [
"alpha_vantage._get_time_series_daily(\"IBM\")"
]
},
{
"cell_type": "markdown",
"id": "b5e46a71",
"metadata": {},
"source": [
"The `_get_time_series_weekly` method returns the last trading day of the week, weekly open, weekly high, weekly low, weekly close, and weekly volume of the global equity specified, covering 20+ years of historical data."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f0dfe35b",
"metadata": {},
"outputs": [],
"source": [
"alpha_vantage = AlphaVantageAPIWrapper()"
"alpha_vantage._get_time_series_weekly(\"IBM\")"
]
},
{
"cell_type": "markdown",
"id": "66cc06a7",
"metadata": {},
"source": [
"The `_get_quote_endpoint` method is a lightweight alternative to the time series APIs and returns the latest price and volume info for the specified symbol."
]
},
{
"cell_type": "code",
"execution_count": 5,
"execution_count": 6,
"id": "98d012ef",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'Global Quote': {'01. symbol': 'IBM',\n",
" '02. open': '156.9000',\n",
" '03. high': '158.6000',\n",
" '04. low': '156.8900',\n",
" '05. price': '158.5400',\n",
" '06. volume': '6640217',\n",
" '07. latest trading day': '2023-11-30',\n",
" '08. previous close': '156.4100',\n",
" '09. change': '2.1300',\n",
" '10. change percent': '1.3618%'}}"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"alpha_vantage._get_quote_endpoint(\"IBM\")"
]
},
{
"cell_type": "markdown",
"id": "3429ce50",
"metadata": {},
"source": [
"The `search_symbol` method returns a list of symbols and the matching company information based on the text entered."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "0ccd55b0",
"metadata": {},
"outputs": [],
"source": [
"alpha_vantage.search_symbols(\"IB\")"
]
},
{
"cell_type": "markdown",
"id": "96e1fd97",
"metadata": {},
"source": [
"The `_get_market_news_sentiment` method returns live and historical market news sentiment for a given asset."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "42995acb",
"metadata": {},
"outputs": [],
"source": [
"alpha_vantage._get_market_news_sentiment(\"IBM\")"
]
},
{
"cell_type": "markdown",
"id": "2fdbd888",
"metadata": {},
"source": [
"The `_get_top_gainers_losers` method returns the top 20 gainers, losers and most active stocks in the US market."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "61c3cb1c",
"metadata": {},
"outputs": [],
"source": [
"alpha_vantage._get_top_gainers_losers()"
]
},
{
"cell_type": "markdown",
"id": "3d1cf3d8",
"metadata": {},
"source": [
"The `run` method of the wrapper takes the following parameters: from_currency, to_currency. \n",
"\n",
"It Gets the currency exchange rates for the given currency pair."
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "068991a6",
"metadata": {
"id": "068991a6",
Expand All @@ -77,29 +227,21 @@
" '2. From_Currency Name': 'United States Dollar',\n",
" '3. To_Currency Code': 'JPY',\n",
" '4. To_Currency Name': 'Japanese Yen',\n",
" '5. Exchange Rate': '144.93000000',\n",
" '6. Last Refreshed': '2023-08-11 21:31:01',\n",
" '5. Exchange Rate': '148.19900000',\n",
" '6. Last Refreshed': '2023-11-30 21:43:02',\n",
" '7. Time Zone': 'UTC',\n",
" '8. Bid Price': '144.92600000',\n",
" '9. Ask Price': '144.93400000'}"
" '8. Bid Price': '148.19590000',\n",
" '9. Ask Price': '148.20420000'}"
]
},
"execution_count": 5,
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"alpha_vantage.run(\"USD\", \"JPY\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "84fc2b66-c08f-4cd3-ae13-494c54789c09",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
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111 changes: 111 additions & 0 deletions libs/community/langchain_community/utilities/alpha_vantage.py
Original file line number Diff line number Diff line change
Expand Up @@ -30,6 +30,117 @@ def validate_environment(cls, values: Dict) -> Dict:
)
return values

def search_symbols(self, keywords: str) -> Dict[str, Any]:
"""Make a request to the AlphaVantage API to search for symbols."""
response = requests.get(
"https://www.alphavantage.co/query/",
params={
"function": "SYMBOL_SEARCH",
"keywords": keywords,
"apikey": self.alphavantage_api_key,
},
)
response.raise_for_status()
data = response.json()

if "Error Message" in data:
raise ValueError(f"API Error: {data['Error Message']}")

return data

def _get_market_news_sentiment(self, symbol: str) -> Dict[str, Any]:
"""Make a request to the AlphaVantage API to get market news sentiment for a
given symbol."""
response = requests.get(
"https://www.alphavantage.co/query/",
params={
"function": "NEWS_SENTIMENT",
"symbol": symbol,
"apikey": self.alphavantage_api_key,
},
)
response.raise_for_status()
data = response.json()

if "Error Message" in data:
raise ValueError(f"API Error: {data['Error Message']}")

return data

def _get_time_series_daily(self, symbol: str) -> Dict[str, Any]:
"""Make a request to the AlphaVantage API to get the daily time series."""
response = requests.get(
"https://www.alphavantage.co/query/",
params={
"function": "TIME_SERIES_DAILY",
"symbol": symbol,
"apikey": self.alphavantage_api_key,
},
)
response.raise_for_status()
data = response.json()

if "Error Message" in data:
raise ValueError(f"API Error: {data['Error Message']}")

return data

def _get_quote_endpoint(self, symbol: str) -> Dict[str, Any]:
"""Make a request to the AlphaVantage API to get the
latest price and volume information."""
response = requests.get(
"https://www.alphavantage.co/query/",
params={
"function": "GLOBAL_QUOTE",
"symbol": symbol,
"apikey": self.alphavantage_api_key,
},
)
response.raise_for_status()
data = response.json()

if "Error Message" in data:
raise ValueError(f"API Error: {data['Error Message']}")

return data

def _get_time_series_weekly(self, symbol: str) -> Dict[str, Any]:
"""Make a request to the AlphaVantage API
to get the Weekly Time Series."""
response = requests.get(
"https://www.alphavantage.co/query/",
params={
"function": "TIME_SERIES_WEEKLY",
"symbol": symbol,
"apikey": self.alphavantage_api_key,
},
)
response.raise_for_status()
data = response.json()

if "Error Message" in data:
raise ValueError(f"API Error: {data['Error Message']}")

return data

def _get_top_gainers_losers(self) -> Dict[str, Any]:
"""Make a request to the AlphaVantage API to get the top gainers, losers,
and most actively traded tickers in the US market."""
response = requests.get(
"https://www.alphavantage.co/query/",
params={
"function": "TOP_GAINERS_LOSERS",
"apikey": self.alphavantage_api_key,
},
)
response.raise_for_status()
data = response.json()

if "Error Message" in data:
raise ValueError(f"API Error: {data['Error Message']}")

return data

def _get_exchange_rate(
self, from_currency: str, to_currency: str
) -> Dict[str, Any]:
Expand Down
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