def test_yahoo_key_info_url(self):
"""
Test key info url from yahoo
"""
yahoo_test_url = r"http://finance.yahoo.com/d/quotes.csv?s="
yahoo_test_url += "GOOG+FB"
yahoo_test_url += r"&f=see9db4j1j4p5p6s7m8"
produced = key_info_url(["GOOG", "FB"])
self.assertEqual(yahoo_test_url, produced)
def get_weights():
'''
Uses least squares with the top stocks to predict recent close prices
'''
top_url = key_info_url(top_symbols())
data = request_csv(top_url)
numeric_data = process(data)
A = numeric_data[:, :9]
b = numeric_data[:, 9]
weights = np.linalg.lstsq(A, b)[0]
return weights
def predict_change(symbol):
'''
Takes a single stock and predicts its change from 50 day average
returns both guess and actual change
'''
weights = get_weights()
symbol_url = key_info_url(symbol).replace('+', '')
data = request_csv(symbol_url)
numeric_data = process(data)
guess = weights.dot(numeric_data[0, :9])
actual = numeric_data[0, 9]
return [guess, actual]
