def fetch_data_sparse(self,
country_codes,
indicator_codes,
event_boundaries,
pause=0):
"""
We fetch data only for the years that we need, specified in event_boundaries
@deprecated: this method makes a lot of queries - it is generally better to make fewer queries, even if it means fetching some data we don't need.
"""
country_list = []
for cnt_code in country_codes:
country = Country(cnt_code)
for ind_code in indicator_codes:
indicator = Indicator()
for event in event_boundaries[cnt_code]:
begin, end = event
indicator_part = self.fetch_indicator(
country.code, ind_code, begin, end)
time.sleep(pause)
indicator.merge_with_indicator(indicator_part)
indicator.code = ind_code
country.set_indicator(indicator)
country_list.append(country)
self.indicators = indicator_codes
self.countries = country_list
return self.countries
def fetch_data_sparse(self, country_codes, indicator_codes, event_boundaries, pause=0):
"""
We fetch data only for the years that we need, specified in event_boundaries
@deprecated: this method makes a lot of queries - it is generally better to make fewer queries, even if it means fetching some data we don't need.
"""
country_list = []
for cnt_code in country_codes:
country = Country(cnt_code)
for ind_code in indicator_codes:
indicator = Indicator()
for event in event_boundaries[cnt_code]:
begin, end = event
indicator_part = self.fetch_indicator(country.code,
ind_code,
begin,
end)
time.sleep(pause)
indicator.merge_with_indicator(indicator_part)
indicator.code = ind_code
country.set_indicator(indicator)
country_list.append(country)
self.indicators = indicator_codes
self.countries = country_list
return self.countries
def test_apply_slope(self):
indicator = Indicator(dates=[1,3,4], values=[17,16,13])
indicator.apply_slope(2)
self.assertEqual(indicator.values, [-0.5,-3.0])
self.assertEqual(indicator.dates, [3,4])
def test_apply_derivative(self):
indicator = Indicator(dates=[1,2,3], values=[17,16,13])
indicator.apply_derivative()
self.assertEqual(indicator.values, [-1,-3])
self.assertEqual(indicator.dates, [2,3])
