def test_from_archive(self):
fake_load = lambda data_type, symbol: data_type[0]
with patch("fa.analysis.finance.load_fundamental_data", MagicMock(side_effect=fake_load)) as mock_load_fundamental_data, \
patch("fa.analysis.finance.Metric.__init__", MagicMock(return_value=None)) as mock_constructor:
obj = Metric.from_archive("C6L.SI", 1, b=2)
mock_load_fundamental_data.assert_has_calls([
call("price", "C6L.SI"),
call("balance_sheet", "C6L.SI"),
call("income_statement", "C6L.SI"),
call("cash_flow", "C6L.SI"),
])
mock_constructor.assert_called_once_with(1, b=2, historical='p', balance_sheet='b', cash_flow='c', income_statement='i')
self.assertIsInstance(obj, Metric)
initialize.init()
symbols = OrderedDict(
[
("C6L.SI", "Singapore Airlines"),
("J7X.SI", "Tiger Airways"),
("S53.SI", "SMRT"),
("C52.SI", "ComfortDelGro"),
("N03.SI", "Neptune Orient Lines"),
("Z74.SI", "Singtel"),
("CC3.SI", "Starhub"),
("B2F.SI", "M1"),
]
)
metrics = [Metric.from_archive(s) for s in symbols]
pe_ratios_list = [m.calc_pe_ratio() for m in metrics]
# figure 1
fig = plt.figure(figsize=(12, 10))
title = "P/E Ratio of stocks over Date\n"
xticks = reduce(lambda a, b: a | b, [ts.index for ts in pe_ratios_list])
with pd.plot_params.use("x_compat", True):
for series, label in zip(pe_ratios_list, symbols.values()):
graph = series.plot(label=label, legend=True, title=title, xticks=xticks)
graph.set_xlabel("Date")
graph.set_ylabel("P/E Ratio")
# prepare graph data
