alphaavantage.py

alphaavantage.py

import io
import requests
import pandas as pd
import json

# https://www.alphavantage.co/query?function=TIME_SERIES_DAILY&symbol=MSFT&apikey=demo
# https://www.alphavantage.co/query?function=TIME_SERIES_DAILY&symbol=MSFT&outputsize=full&apikey=demo
# https://www.alphavantage.co/query?function=TIME_SERIES_DAILY&symbol=MSFT&apikey=demo&datatype=csv

apikey = 'API_KEY_HERE'
query_url = 'https://www.alphavantage.co/query?'

OPEN_COLUMN = '1. open'
HIGH_COLUMN = '2. high'
LOW_COLUMN = '3. low'
CLOSE_COLUMN = '4. close'
VOLUME_COLUMN = '5. volume'

def get_stock_price(symbol):
	'현재 주가를 돌려준다'
	data = get_time_series_intraday(symbol)
	first_key = next(iter(data))
	return float(data[first_key][CLOSE_COLUMN])

def get_time_series_intraday(symbol, interval='5min', outputsize='compact', datatype='json'):
	url = query_url + \
		'function=TIME_SERIES_INTRADAY' + \
		'&symbol=' + symbol + \
		'&interval=' + interval + \
		'&apikey=' + apikey + \
		'&outptusize=' + outputsize + \
		'&datatype=' + datatype
	response = requests.get(url)
	raw = json.loads(response.text)
	key = "Time Series (%s)" % interval
	return raw[key]

def get_time_series_daily_csv(symbol, outputsize='full', datatype='csv'):
	'수정종가'
	url = query_url + \
		'function=TIME_SERIES_DAILY_ADJUSTED' + \
		'&symbol=' + symbol + \
		'&apikey=' + apikey + \
		'&outputsize=' + outputsize + \
		'&datatype=' + datatype
	response = requests.get(url)
	# response.status_code
	return response.text

def get_time_series_daily(symbol):
	'csv 데이터를 얻고 DataFrame으로 변환한다.'
	csv = get_time_series_daily_csv(symbol)
	df = pd.read_csv(io.StringIO(csv))
	return df