def get_json_value(value):
"""Parse JSON value based on type."""
if is_float_nan(value):
value = JSON_NULL
elif isinstance(value, np.int64):
value = int(value)
elif isinstance(value, np.bool_):
value = bool(value)
return value
def get_json_value(value):
"""Parse JSON value based on type."""
if is_float_nan(value):
value = JSON_NULL
elif isinstance(value, np.int64):
value = int(value)
elif isinstance(value, np.bool_):
value = bool(value)
return value
def _is_potential_date(value):
return not (is_float_nan(value) or isinstance(value, bool))
def test_update_after_agg_group(self):
dataset_id = self._post_file('wp_data.csv')
group = 'wp_id'
self._wait_for_dataset_state(dataset_id)
test_calculations = {
'newest(submit_date,functional)': 'wp_functional',
'max(submit_date)': 'latest_submit_date',
'ratio(functional in ["yes"], 1)': 'wp_func_ratio'}
expected_results = {'wp_id': ['A', 'B', 'C', 'n/a'],
'wp_functional': ['yes', 'no', 'yes', 'yes'],
'wp_func_ratio': [1.0, 0.0, 1.0, 1.0],
'wp_func_ratio_denominator': [1, 1, 1, 1],
'wp_func_ratio_numerator': [1.0, 0.0, 1.0, 1.0],
'latest_submit_date': [1356998400, 1357084800,
1357171200, 1357257600]}
expected_results_after = {
'wp_id': ['A', 'B', 'C', 'D', 'n/a'],
'wp_functional': ['no', 'no', 'yes', 'yes'],
'wp_func_ratio': [0.5, 0.0, 1.0, 1.0, 1.0],
'wp_func_ratio_denominator': [2.0, 1.0, 1.0, 1.0, 1.0],
'wp_func_ratio_numerator': [1.0, 0.0, 1.0, 1.0, 1.0],
'latest_submit_date': [1357603200.0, 1357084800.0,
1357171200.0, 1357257600.0]}
for formula, name in test_calculations.items():
results = json.loads(self.controller.create(
dataset_id, formula, name, group=group))
self.assertTrue(self.controller.SUCCESS in results)
dataset = Dataset.find_one(dataset_id)
previous_num_rows = dataset.num_rows
while True:
dataset = Dataset.find_one(dataset_id)
if dataset.aggregated_dataset(group) and all(
[not c.is_pending for c in dataset.calculations()]):
break
sleep(self.SLEEP_DELAY)
agg_dframe = dataset.aggregated_dataset(group).dframe()
self.assertEqual(set(expected_results.keys()),
set(agg_dframe.columns.tolist()))
for column, results in expected_results.items():
self.assertEqual(results,
agg_dframe[column].tolist())
update = {
'wp_id': 'D',
'functional': 'yes',
}
self.__post_update(dataset_id, update)
update = {
'submit_date': '2013-01-08',
'wp_id': 'A',
'functional': 'no',
}
self.__post_update(dataset_id, update)
while True:
dataset = Dataset.find_one(dataset_id)
current_num_rows = dataset.num_rows
if not len(dataset.pending_updates):
break
sleep(self.SLEEP_DELAY)
dataset = Dataset.find_one(dataset_id)
agg_dframe = dataset.aggregated_dataset(group).dframe()
self.assertEqual(current_num_rows, previous_num_rows + 2)
self.assertEqual(set(expected_results_after.keys()),
set(agg_dframe.columns.tolist()))
for column, results in expected_results_after.items():
column = [x for x in agg_dframe[column].tolist() if not
is_float_nan(x)]
self.assertEqual(results, column)
def _is_potential_date(value):
return not (is_float_nan(value) or isinstance(value, bool))
