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Add initial State Street holdings functionality
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44
metrik/tasks/state_street.py
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44
metrik/tasks/state_street.py
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import requests
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from luigi.parameter import Parameter
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import pandas as pd
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from metrik.tasks.base import MongoNoBackCreateTask
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class StateStreetHoldings(MongoNoBackCreateTask):
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ticker = Parameter() # type: str
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@staticmethod
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def retrieve_data(ticker, current_datetime, live):
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# TODO: Actually make this static
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base_url = 'https://www.spdrs.com/site-content/xls/{fund}_All_Holdings.xls'
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fund_url = base_url.format(fund=ticker)
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excel_content = pd.read_excel(fund_url, header=None)
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# The actual stuff we care about is arranged in tabular format, thus
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# we actually want to get the rows where the far-right column is
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# not null.
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final_column_index = len(excel_content.columns) - 1
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# And build a series of True/False for "We do want this row" and
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# "we do not want this row" respectively
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do_retain = excel_content[[final_column_index]].isnull() == False
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retain_index = do_retain[do_retain[final_column_index] == True].index
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# Actual content is in rows 2 onwards
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holding_df = excel_content.ix[retain_index[1:]]
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# Headers are in row 1
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holding_df.columns = excel_content.ix[retain_index[0]]
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# And also get the metadata that are in the rows prior to content
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metadata = excel_content.ix[0:retain_index[0]-1].dropna(axis=1)
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metadata_dict = {row[0].strip(':'): row[1]
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for i, row in metadata.iterrows()}
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return dict(
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holdings=holding_df.to_dict(orient='record'),
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**metadata_dict
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)
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def get_collection_name(self):
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return 'state_street_holdings'
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49
test/tasks/test_state_street.py
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test/tasks/test_state_street.py
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# coding=utf-8
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from unittest import TestCase
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from datetime import datetime
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from metrik.tasks.state_street import StateStreetHoldings
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class StateStreetHoldingTest(TestCase):
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def test_spy_holdings(self):
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holdings_dict = StateStreetHoldings.retrieve_data(
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'SPY', datetime.now(), True
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)
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self.assertEqual(holdings_dict['Ticker Symbol'], 'SPY')
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self.assertEqual(holdings_dict['Fund Name'], u'SPDR® S&P 500® ETF')
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self.assertGreaterEqual(len(holdings_dict['holdings']), 500)
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# Long live AAPL
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self.assertTrue(holdings_dict['holdings'][0]['Identifier'] == u'AAPL')
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def test_sdy_holdings(self):
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holdings_dict = StateStreetHoldings.retrieve_data(
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'SDY', datetime.now(), True
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)
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self.assertEqual(holdings_dict['Ticker Symbol'], 'SDY')
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self.assertEqual(holdings_dict['Fund Name'], u'SPDR® S&P® Dividend ETF')
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self.assertTrue(holdings_dict['holdings'][0]['Identifier'] == 'HCP')
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def test_spyd_holdings(self):
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holdings_dict = StateStreetHoldings.retrieve_data(
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'SPYD', datetime.now(), True
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)
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self.assertEqual(holdings_dict['Ticker Symbol'], 'SPYD')
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self.assertEqual(holdings_dict['Fund Name'], u'SPDR® S&P® 500 High Dividend ETF')
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def test_r3k_holdings(self):
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holdings_dict = StateStreetHoldings.retrieve_data(
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'THRK', datetime.now(), True
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)
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self.assertEqual(holdings_dict['Ticker Symbol'], 'THRK')
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self.assertEqual(holdings_dict['Fund Name'], u'SPDR Russell 3000® ETF')
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# Interesting story: the fund is not required to actually invest in all
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# 3000 Russell equities, but just seeks to track the index in general.
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# That's why the test is against 2000, not 3000.
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# This also means that we can't check lists of say iShares against this
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# because they're not guaranteed to be consistent.
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self.assertGreaterEqual(len(holdings_dict['holdings']), 2000)
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