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pipeline.py
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pipeline.py
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import pandas as pd
from alpha_vantage.timeseries import TimeSeries
import os
import requests
from bs4 import BeautifulSoup
import io
class Pipeline:
def __init__(self, universe, start_date, end_date, resolution):
self.universe = universe
self.start_date = start_date
self.end_date = end_date
self.resolution = resolution
self.ts = TimeSeries(key=os.environ['AV_API_KEY'], output_format='pandas')
def init_universe(self):
if isinstancce(self.universe, list):
tickers = self.universe
elif istance(self.universe, string):
tickers = self._get_constituents()
return tickers
def build_prices():
prices = []
tickers = self.init_universe()
for ticker in tickers:
prices.append()
def _get_constituents(self):
last_business_day = (pd.to_datetime(self.start_date) + \
pd.offsets.BMonthEnd(-1)).date().strftime('%Y%m%d')
if self.universe == 'sp500':
url = 'https://www.ishares.com/us/products/239726/ishares-core-sp-500-etf/1467271812596.ajax?fileType=csv&fileName=IVV_holdings&dataType=fund&asOfDate={}'
elif self.universe =='russell2000':
url = 'https://www.ishares.com/us/products/239710/ishares-russell-2000-etf/1467271812596.ajax?fileType=csv&fileName=IWM_holdings&dataType=fund&asOfDate={}'
try:
content = requests.get(url.format(last_business_day))
except requests.exception.RequestException as e:
print(e)
historical_holdings = pd.read_csv(io.StringIO(content.text), skiprows=10)
tickers = historical_holdings['Ticker'].values
return tickers