alpha_vantage Python Library

The alpha_vantage package is organized into several specialized submodules for accessing different types of financial data from the Alpha Vantage API:

• alpha_vantage.alphavantage: Core Alpha Vantage functionality.
• alpha_vantage.cryptocurrencies: Cryptocurrency market data.
• alpha_vantage.foreignexchange: Foreign exchange (Forex) data.
• alpha_vantage.sectorperformance: Sector performance data.
• alpha_vantage.techindicators: Technical indicators (e.g., SMA, EMA, RSI).
• alpha_vantage.timeseries: Time series data (e.g., daily, intraday, weekly stock prices).

For Python 3.5+, you can use the asynchronous support located in alpha_vantage.async_support. This is useful for performing multiple API calls concurrently to improve performance. Remember to call .close() on the object when finished.

import asyncio
from alpha_vantage.async_support.timeseries import TimeSeries

symbols = ['AAPL', 'GOOG', 'TSLA', 'MSFT']

async def get_data(symbol):
    ts = TimeSeries(key='YOUR_KEY_HERE')
    data, _ = await ts.get_quote_endpoint(symbol)
    await ts.close()
    return data

loop = asyncio.get_event_loop()
tasks = [get_data(symbol) for symbol in symbols]
group1 = asyncio.gather(*tasks)
results = loop.run_until_complete(group1)
loop.close()
print(results)

You can install the package via pip. For full functionality including pandas support, install pandas alongside the library.

To install with pandas support:

pip install alpha_vantage pandas

To install from source:

git clone https://github.com/RomelTorres/alpha_vantage.git
pip install -e alpha_vantage

To install the package from the source repository in editable mode, clone the repository and use pip install -e:

git clone https://github.com/RomelTorres/alpha_vantage.git
pip install -e alpha_vantage

To install the alpha_vantage package from PyPI, use the following command:

pip install alpha_vantage

The TimeSeries class allows you to configure the output format and the pandas DataFrame indexing type during initialization.

• output_format: Set to 'pandas' to receive results as pandas DataFrames. Default is JSON dictionaries. Note that ForeignExchange and TechIndicators do not support 'csv' format.
• indexing_type: When using pandas, set to 'date' (default) for date string indexing or 'integer' for integer indexing.

Use the CryptoCurrencies class from alpha_vantage.cryptocurrencies to retrieve digital currency data.

from alpha_vantage.cryptocurrencies import CryptoCurrencies

cc = CryptoCurrencies(key='YOUR_API_KEY', output_format='pandas')
data, meta_data = cc.get_digital_currency_daily(symbol='BTC', market='CNY')

Use get_intraday to retrieve intraday time series data. You can specify a month parameter (e.g., '2014-01') to query historical data for a specific month.

from alpha_vantage.timeseries import TimeSeries

ts = TimeSeries(key='YOUR_API_KEY')
# Get current intraday data
data, meta_data = ts.get_intraday('GOOGL')

# Get historical intraday data for a specific month
data, meta_data = ts.get_intraday('GOOGL', month='2014-01', interval='30min')

Import TechIndicators from alpha_vantage.techindicators to access various technical indicators like Simple Moving Average (SMA) or Bollinger Bands (BBands).

from alpha_vantage.techindicators import TechIndicators

ti = TechIndicators(key='YOUR_API_KEY')

# Get SMA values for a specific month
data, meta_data = ti.get_sma('GOOGL', month='2014-01', interval='30min')

# Get Bollinger Bands
data, meta_data = ti.get_bbands(symbol='MSFT', interval='60min', time_period=60)