def test_get_classifier(self):
testname = 'testname'
testtaxonomy = 'testtaxonomy'
created = logic.classifier.create_classifier(testname, testtaxonomy)
fetched = logic.classifier.get_classifier(testname, testtaxonomy)
h.assert_true(isinstance(fetched, Classifier))
h.assert_false(created is fetched)
h.assert_equal(created, fetched)
def test_reads_unicode(self):
reader = udr.UnicodeDictReader(h.fixture_file('simple.csv'))
lines = [ l for l in reader ]
h.assert_true(isinstance(lines[0].keys()[0], unicode),
"Keys in UnicodeDictReader dicts should be unicode.")
h.assert_true(isinstance(lines[0].values()[0], unicode),
"Values in UnicodeDictReader dicts should be unicode.")
def test_compute_cube(self):
from openspending.model import Dataset
cra = h.load_fixture('cra')
cube = Cube.configure_default_cube(cra)
cube.compute()
h.assert_true('cubes.cra.default' in mongo.db().collection_names())
def test_create_classifier_does_not_delete_attributes_in_existing(self):
classifier = logic.classifier.create_classifier(u'Test Classifier',
taxonomy=u'taxonomy',
extra=u'extra')
h.assert_true('extra' in classifier)
upserted_classifier = logic.classifier.create_classifier(u'Test Classifier',
taxonomy=u'taxonomy')
h.assert_true('extra' in upserted_classifier)
def test_classify_entry(self):
entry = {'name': u'Test Entry',
'amount': 1000.00}
c_name = u'support-transparency'
c_taxonomy = u'Good Reasons'
c_label = u'Support Transparency Initiatives'
classifier = logic.classifier.create_classifier(name=c_name,
label=c_label,
taxonomy=c_taxonomy)
logic.entry.classify_entry(entry, classifier, name=u'reason')
h.assert_equal(entry.keys(), [u'reason', 'amount', 'name',
'classifiers'])
h.assert_equal(entry['classifiers'], [classifier['_id']])
h.assert_equal(entry['reason']['label'], c_label)
h.assert_equal(entry['reason']['name'], c_name)
h.assert_equal(entry['reason']['taxonomy'], c_taxonomy)
h.assert_true(isinstance(entry['reason']['ref'], DBRef))
def test_distincts(self):
testdataset = self._make_dataset(name='testdataset')
self._make_entry(name='one', region="Region 1", region2="Region 2",
dataset=testdataset)
self._make_entry(name='two', region="Region 2", region2="Region 3",
dataset=testdataset)
db = model.mongo.db()
h.assert_true('compute_distincts' in db.system_js.list())
# compute a distincts collection
db.system_js.compute_distincts('testdataset')
h.assert_true('distincts__testdataset' in db.collection_names())
# test the distincts collection manually
distinct_regions = db.distincts__testdataset.find({
'value.keys': u'region'
}).distinct('_id')
h.assert_equal(sorted(distinct_regions), [u'Region 1', u'Region 2'])
distincts = logic.entry.distinct('region', dataset_name='testdataset')
h.assert_equal(sorted(distincts), [u'Region 1', u'Region 2'])
def test_distincts_create_collection(self):
testdataset = self._make_dataset(name='testdataset')
self._make_entry(name='one', region="Region 1", region2="Region 2",
dataset=testdataset)
self._make_entry(name='two', region="Region 2", region2="Region 3",
dataset=testdataset)
db = model.mongo.db()
h.assert_true('compute_distincts' in db.system_js.list())
# compute a distincts collection
h.assert_true('distincts__testdataset' not in db.collection_names())
distincts = logic.entry.distinct('region', dataset_name='testdataset')
h.assert_true('distincts__testdataset' in db.collection_names())
h.assert_equal(sorted(distincts), [u'Region 1', u'Region 2'])
def test_is_compound(self):
h.assert_true(self.entity.is_compound)
def test_is_compound(self):
h.assert_true(self.entity.is_compound)
def test_package_init(self):
p = ckan.Package('foo')
h.assert_true(isinstance(p, ckan.Package))
def test_create_classifier(self):
classifier = logic.classifier.create_classifier(name=u'Test Classifier',
taxonomy=u'taxonomy')
h.assert_true(isinstance(classifier, Classifier))