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community[minor]: Add Alpha Vantage API Tool (#14332)

Browse Source 
### 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 <94140103+adam-badar@users.noreply.github.com>
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
pull/14283/head
anshaneel 6 months ago committed by GitHub
parent a9bc212bf2
commit 0884e5de7f
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3 changed files with 343 additions and 24 deletions
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190
docs/docs/integrations/tools/alpha_vantage.ipynb
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@ -21,15 +21,7 @@
"metadata": {
"id": "34bb5968"
},
"outputs": [
{
"name": "stdin",
"output_type": "stream",
"text": [
" ········\n"
]
}
],
"outputs": [],
"source": [
"import getpass\n",
"import os\n",
@ -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",
@ -77,14 +227,14 @@
" '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"
}
@ -92,14 +242,6 @@
"source": [
"alpha_vantage.run(\"USD\", \"JPY\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "84fc2b66-c08f-4cd3-ae13-494c54789c09",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {

111
libs/community/langchain_community/utilities/alpha_vantage.py
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@ -30,6 +30,117 @@ class AlphaVantageAPIWrapper(BaseModel):
)
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]:

66
libs/community/tests/integration_tests/utilities/test_alpha_vantage.py
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@ -0,0 +1,66 @@
"""Integration test for Alpha Vantage API Wrapper."""
import pytest
from langchain_community.utilities.alpha_vantage import AlphaVantageAPIWrapper
@pytest.fixture
def api_wrapper() -> AlphaVantageAPIWrapper:
# Ensure that the ALPHAVANTAGE_API_KEY environment variable is set
return AlphaVantageAPIWrapper()
def test_search_symbols(api_wrapper: AlphaVantageAPIWrapper) -> None:
"""Test the search symbols API call for successful response."""
response = api_wrapper.search_symbols("AAPL")
assert response is not None
assert isinstance(response, dict)
def test_market_news_sentiment(api_wrapper: AlphaVantageAPIWrapper) -> None:
"""Test the market news sentiment API call for successful response."""
response = api_wrapper._get_market_news_sentiment("AAPL")
assert response is not None
assert isinstance(response, dict)
def test_time_series_daily(api_wrapper: AlphaVantageAPIWrapper) -> None:
"""Test the time series daily API call for successful response."""
response = api_wrapper._get_time_series_daily("AAPL")
assert response is not None
assert isinstance(response, dict)
def test_quote_endpoint(api_wrapper: AlphaVantageAPIWrapper) -> None:
"""Test the quote endpoint API call for successful response."""
response = api_wrapper._get_quote_endpoint("AAPL")
assert response is not None
assert isinstance(response, dict)
def test_time_series_weekly(api_wrapper: AlphaVantageAPIWrapper) -> None:
"""Test the time series weekly API call for successful response."""
response = api_wrapper._get_time_series_weekly("AAPL")
assert response is not None
assert isinstance(response, dict)
def test_top_gainers_losers(api_wrapper: AlphaVantageAPIWrapper) -> None:
"""Test the top gainers and losers API call for successful response."""
response = api_wrapper._get_top_gainers_losers()
assert response is not None
assert isinstance(response, dict)
def test_exchange_rate(api_wrapper: AlphaVantageAPIWrapper) -> None:
"""Test the exchange rate API call for successful response."""
response = api_wrapper._get_exchange_rate("USD", "EUR")
assert response is not None
assert isinstance(response, dict)
def test_run_method(api_wrapper: AlphaVantageAPIWrapper) -> None:
"""Test the run method for successful response."""
response = api_wrapper.run("USD", "EUR")
assert response is not None
assert isinstance(response, dict)
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