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‎forex_CSV_nolib.py

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import os
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import requests
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import pandas as pd
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api_key = os.getenv('ALPHAVANTAGE_API_KEY')
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base_url = 'https://www.alphavantage.co/query?'
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params = {'function': 'FX_INTRADAY',
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'from_symbol': 'EUR',
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'to_symbol': 'USD',
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'interval': '15min',
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'datatype': 'csv',
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'apikey': api_key}
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response = requests.get(base_url, params=params)
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#Save CSV to file
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with open('eurusd.csv', 'wb') as file:
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file.write(response.content)
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df = pd.read_csv('eurusd.csv') #Create pandas dataframe
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df.set_index('timestamp', inplace=True) #Time-series index
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df.to_csv('eurusd.csv') #Save dataframe to csv file

‎forex_pandas_library.py

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from alpha_vantage.foreignexchange import ForeignExchange
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app = ForeignExchange(output_format='pandas')
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eurusd = app.get_currency_exchange_intraday('EUR', 'USD')
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print(eurusd[0])
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print(eurusd[0]['2020-04-03']) #Narrow output to specific date

‎forex_pandas_nolib.py

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import os
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import requests
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import pandas as pd
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api_key = os.getenv('ALPHAVANTAGE_API_KEY')
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base_url = 'https://www.alphavantage.co/query?'
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params = {'function': 'FX_INTRADAY',
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'from_symbol': 'EUR',
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'to_symbol': 'USD',
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'interval': '15min',
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'apikey': api_key}
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response = requests.get(base_url, params=params)
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response_dict = response.json()
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_, header = response.json()
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#Convert to pandas dataframe
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df = pd.DataFrame.from_dict(response_dict[header], orient='index')
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#Clean up column names
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df_cols = [i.split(' ')[1] for i in df.columns]
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df.columns = df_cols
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print(df)

‎readme.rst

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======================================================
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Alpha Vantage Introduction Guide - AlgoTrading101 Blog
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======================================================
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This is the code used in `Alpha Vantage Introduction Guide <https://algotrading101.com/learn/alpha-vantage-guide/>`_ published on the AlgoTrading101 Blog
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-----------------
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Table of Contents
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-----------------
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* `What is the Alpha Vantage API? <https://algotrading101.com/learn/alpha-vantage-guide/#what-is-the-alpha-vantage-api>`_
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* `Is the Alpha Vantage API free? <https://algotrading101.com/learn/alpha-vantage-guide/#is-the-alpha-vantage-api-free>`_
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* `What kind of data does the Alpha Vantage API offer? <https://algotrading101.com/learn/alpha-vantage-guide/#what-data-does-alpha-vantage-offer>`_
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* `What are the advantages of using the Alpha Vantage API? <https://algotrading101.com/learn/alpha-vantage-guide/#what-are-advantage-of-using-alpha-vantage>`_
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* `Why shouldn’t I use the Alpha Vantage API? <https://algotrading101.com/learn/alpha-vantage-guide/#why-shouldn't-i-use-alpha-vantage-api>`_
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* `What are some alternatives to the Alpha Vantage API? <https://algotrading101.com/learn/alpha-vantage-guide/#what-are-alternatives-to-alpha-vantage-api>`_
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* `How do I get started with the Alpha Vantage API? <https://algotrading101.com/learn/alpha-vantage-guide/#how-do-i-start-with-alpha-vantage-api>`_
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* `Do I need to use a library to access the Alpha Vantage API? <https://algotrading101.com/learn/alpha-vantage-guide/#do-i-need-a-library-for-alpha-vantage-api>`_
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* `How do I configure the Alpha Vantage Library? <https://algotrading101.com/learn/alpha-vantage-guide/#how-to-configure-alpha-vantage-library>`_
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* `How do I retrieve stock data using the Alpha Vantage library in Python? <https://algotrading101.com/learn/alpha-vantage-guide/#how-to-retrieve-stock-data-with-library>`_
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* `How can I get retrieve stock data without using the Alpha Vantage library in Python? <https://algotrading101.com/learn/alpha-vantage-guide/#how-to-retrieve-stock-data-without-library>`_
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* `Does the Alpha Vantage API work well with the pandas library? <https://algotrading101.com/learn/alpha-vantage-guide/#does-alpha-vantage-work-well-with-pandas>`_
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* `Should I use the CSV or JSON format for my data? <https://algotrading101.com/learn/alpha-vantage-guide/#should-i-use-json-or-csv-for-my-data>`_
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* `How can I use technical indicators with the Alpha Vantage library? <https://algotrading101.com/learn/alpha-vantage-guide/#how-to-technical-indicators-alpha-vantage>`_
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* `Final Thoughts <https://algotrading101.com/learn/alpha-vantage-guide/#final-thoughts-alpha-vantage-api>`_
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------------
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Requirements
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------------
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* `python <https://www.python.org>`_ >= 2.7, 3.4+
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* `pandas <https://github.com/pandas-dev/pandas>`_ (tested to work with >= 1.0.3 )
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* `requests <https://github.com/psf/requests>`_ (tested to work with >= 2.22.0 )
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* `alpha_vantage <https://github.com/RomelTorres/alpha_vantage>`_ (tested to work with >= 2.1.3 )
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-----------
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Author Info
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-----------
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:author: Jignesh Davda
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:author page: https://algotrading101.com/learn/author/jdavda/
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:published: 2020-04-08

‎requirements.txt

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pandas==1.0.3
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requests==2.22.0
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alpha_vantage==2.1.3

‎retrieve_stock_data_library.py

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from alpha_vantage.timeseries import TimeSeries
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app = TimeSeries() #Default - JSON format
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#Valid options for output_format are 'pandas', 'csv'.
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#app = TimeSeries(output_format='pandas')
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#app = TimeSeries(output_format='csv')
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help(app)
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aapl = app.get_daily_adjusted('BTCUSD', outputsize='full')
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print(aapl)

‎retrieve_stock_data_nolib.py

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import os
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import requests
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api_key = os.getenv('ALPHAVANTAGE_API_KEY')
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print(api_key)
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#method 1 - parameters in url
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response = requests.get('https://www.alphavantage.co/query?function=TIME_SERIES_DAILY_ADJUSTED&symbol=IBM&apikey=demo')
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print(response.json())
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#method 2 - using f strings
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base_url = 'https://www.alphavantage.co/query?'
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function = 'TIME_SERIES_DAILY_ADJUSTED'
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symbol = 'IBM'
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response = requests.get(f'{base_url}function={function}&symbol={symbol}&apikey={api_key}')
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print(response.json())
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#method 3 - using a params dictionary ** recommended method
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base_url = 'https://www.alphavantage.co/query?'
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params = {'function': 'TIME_SERIES_DAILY_ADJUSTED',
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'symbol': 'IBM',
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'apikey': api_key}
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response = requests.get(base_url, params=params)
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print(response.json())

‎tech_indicators.py

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from alpha_vantage.techindicators import TechIndicators
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app = TechIndicators(output_format='pandas')
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#help(app.get_macd)
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aapl_macd = app.get_macd('aapl', fastperiod=12, slowperiod=26, signalperiod=9)
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print(aapl_macd)

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