def test_assert_equal(self):
fa_util.assert_equal(1 + 1, 2)
with self.assertRaises(AssertionError) as cm:
fa_util.assert_equal(1 + 1, 1)
self.assertEqual(str(cm.exception), "The variable is expected to be 1 but is actually 2")
def _validate(obj, actual_currency, symbol, timeframe, report_type):
""" Verifies whether <obj> is good for value parsing.
obj: dictionary of scraped raw data
actual_currency: currency used, derived from <obj>
symbol, timeframe, report_type: the parameters that were used to obtain <obj>
"""
prefix, _, suffix = symbol.partition('.')
# symbol, timeframe, report_type
assert_equal(obj["symbol_prefix"], prefix, "symbol prefix")
assert_equal(obj["timeframe"], timeframe, "timeframe")
assert_equal(obj["report_type"], report_type, "report_type")
# currency
expected_currency = SYMBOL_SUFFIX_INFO[suffix][2] if suffix else DEFAULT_CURRENCY
if actual_currency != expected_currency: # currency is not so important in fundamental analysis
logger.warning("currency is expected to be {0} but is actually {1}".format(expected_currency, actual_currency))
# first column's name
data = obj["data"]
assert_equal(data[0][0], "periods", "first column's name")
# uniqueness of periods
periods = data[0][1]
assert len(periods) == len(set(periods)), "Periods are expected to be unique, but they are not"
# column length
column_lengths = set(len(p[1]) for p in data)
assert len(column_lengths) == 1, "All columns are expected to have the same length, but they do not"
