def url(df_amazon, dj, nasdaq, sp, p_diff):
url = 'https://markets.businessinsider.com/stocks/amzn-stock'
index_url = [
'https://markets.businessinsider.com/index/dow_jones',
'https://markets.businessinsider.com/index/s&p_500',
'https://markets.businessinsider.com/index/nasdaq_100'
]
html = urlopen(url)
soup = BeautifulSoup(html, 'lxml')
#print(soup)
price = extract_price(soup)
name = extract_name(soup)
#dp=extract_index()
date_time = analysis.date_time_format(timezone('EST'))
dp1, sp1, np1 = extract_index(index_url)
dj_price = analysis.index_price_difference(dp1, dj)
sp_price = analysis.index_price_difference(sp1, sp)
nd_price = analysis.index_price_difference(np1, nasdaq)
price_diff = analysis.calculate_price_diff(price, p_diff)
if len(df_amazon) < 5:
new_data = [
sp_price, nd_price, dj_price, name, date_time, price, price_diff, 0
]
#return new_data
else:
ma = analysis.moving_average(df_amazon)
new_data = [
sp_price, nd_price, dj_price, name, date_time, price, price_diff,
ma
]
df_amazon.loc[len(df_amazon)] = new_data
return df_amazon
def test_moving_average_with_ramp():
""" [quant.analysis] Test moving average with ramp
"""
result = analysis.moving_average(3, lin_ramp)
np.testing.assert_array_equal(result, [np.nan, np.nan, 1, 2, 3, 4, 5, 6, 7, 8])
def test_moving_average_with_zeros():
""" [quant.analysis] Test moving average with zeros
"""
result = analysis.moving_average(3, zeros_array)
np.testing.assert_array_equal(result, [np.nan, np.nan, 0, 0, 0, 0, 0, 0, 0, 0])
def test_moving_average_with_ones():
""" [quant.analysis] Test moving average with ones
"""
result = analysis.moving_average(3, ones_array)
np.testing.assert_array_equal(result, [np.nan, np.nan, 1, 1, 1, 1, 1, 1, 1, 1])
def test_zero_length_moving_average():
""" [quant.analysis] Test zero-length moving average
"""
result = analysis.moving_average(0, lin_ramp)
np.testing.assert_array_equal(result, nan_array)
def test_unit_length_moving_average():
""" [quant.analysis] Test unit-length moving average
"""
result = analysis.moving_average(1, lin_ramp)
np.testing.assert_array_equal(result, lin_ramp)
def test_moving_average_with_ramp():
""" [quant.analysis] Test moving average with ramp
"""
result = analysis.moving_average(3, lin_ramp)
np.testing.assert_array_equal(result,
[np.nan, np.nan, 1, 2, 3, 4, 5, 6, 7, 8])
def test_moving_average_with_ones():
""" [quant.analysis] Test moving average with ones
"""
result = analysis.moving_average(3, ones_array)
np.testing.assert_array_equal(result,
[np.nan, np.nan, 1, 1, 1, 1, 1, 1, 1, 1])
def test_moving_average_with_zeros():
""" [quant.analysis] Test moving average with zeros
"""
result = analysis.moving_average(3, zeros_array)
np.testing.assert_array_equal(result,
[np.nan, np.nan, 0, 0, 0, 0, 0, 0, 0, 0])
def test_unit_length_moving_average():
""" [quant.analysis] Test unit-length moving average
"""
result = analysis.moving_average(1, lin_ramp)
np.testing.assert_array_equal(result, lin_ramp)
def test_zero_length_moving_average():
""" [quant.analysis] Test zero-length moving average
"""
result = analysis.moving_average(0, lin_ramp)
np.testing.assert_array_equal(result, nan_array)