def test_members(self):
members = list(self.entity.members())
h.assert_equal(len(members), 5)
members = list(
self.entity.members(self.entity.alias.c.name == 'Dept032'))
h.assert_equal(len(members), 1)
def test_count_with_query_kwarg_containing_boolean_value(self):
self._make_entry(name='one', foo=True)
self._make_entry(name='two', foo=True)
self._make_entry(name='three', foo=False)
h.clean_and_reindex_solr()
count = logic.entry.count(foo=True)
h.assert_equal(count, 2)
def test_package_is_importable(self):
p = ckan.Package
h.assert_equal(p('foo').is_importable(), False)
h.assert_equal(p('bar').is_importable(), True)
h.assert_equal(p('baz').is_importable(), False)
h.assert_equal(p('missingdata').is_importable(), False)
h.assert_equal(p('withmapping').is_importable(), True)
def test_distincts_with_query_kwarg(self):
self._make_entry(name='one', region='RegionA')
self._make_entry(name='two', region='RegionA')
self._make_entry(name='three', region='RegionB')
# without a dataset_name it returns the distincts across all datasets
distincts = logic.entry.distinct('name', region=u'RegionA')
h.assert_equal(distincts, ['one', 'two'])
def test_facets_with_query_kwarg_containing_boolean_value(self):
self._make_entry(name='one', foo=True)
self._make_entry(name='two', foo=True)
self._make_entry(name='three', foo=False)
h.clean_and_reindex_solr()
facets = logic.entry.facets_for_fields(['name'], foo=True)
h.assert_equal(facets, {u'name': {u'one': 1,
u'two': 1}})
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_count_with_query(self):
self._make_entry(name='one', region="A")
self._make_entry(name='two', region="A")
self._make_entry(name='three', region="B")
self._make_entry(name='four')
h.clean_and_reindex_solr()
count = logic.entry.count(region="A")
h.assert_equal(count, 2)
def test_facets_with_query_kwarg(self):
self._make_entry(name='one', region="RegionA")
self._make_entry(name='two', region="RegionA")
self._make_entry(name='three', region="Region B")
h.clean_and_reindex_solr()
facets = logic.entry.facets_for_fields(['name'], region=u'RegionA')
h.assert_equal(facets, {u'name': {u'one': 1,
u'two': 1}})
def test_count_with_dataset_name(self):
self._make_entry(name='one')
self._make_entry(name='two')
other_dataset = self._make_dataset('other_dataset')
self._make_entry(name='three', dataset=other_dataset)
self._make_entry(name='four', dataset=other_dataset)
h.clean_and_reindex_solr()
count = logic.entry.count(dataset_name='other_dataset')
h.assert_equal(count, 2)
def test_members(self):
self.ds.generate()
self.entity.load(self.ds.bind, {'name': 'one', 'label': 'Label One'})
self.entity.load(self.ds.bind, {'name': 'two', 'label': 'Label Two'})
members = list(self.entity.members())
h.assert_equal(len(members), 2)
members = list(self.entity.members(self.entity.alias.c.name == 'one'))
h.assert_equal(len(members), 1)
def test_aggregation(self):
# Test that values are aggregated in the cube.
cube = self._make_cube()
collection = cube.db[cube.collection_name]
from_a = list(collection.find({'from.name': 'a'}, as_class=dict))
from_b = list(collection.find({'from.name': 'b'}, as_class=dict))
h.assert_equal(len(from_a), 1)
h.assert_equal(from_a[0]['amount'], 2000)
h.assert_equal(len(from_b), 2)
h.assert_equal(from_b[0]['amount'], 1000)
h.assert_equal(from_b[1]['amount'], 1000)
def test_default_dimensons(self):
# test the dimensions for a default cube.
# We exclude 'name', 'label' and 'time'.
# But include 'to' and 'from', 'year', and if necessary 'name'.
cube = self._make_cube()
h.assert_equal(sorted(cube.dimensions), ['from', 'to', 'year'])
dataset = cube.dataset
dataset['time_axis'] = u'time.from.month'
new_default_cube = Cube.configure_default_cube(dataset)
h.assert_equal(sorted(new_default_cube.dimensions),
['from', 'month', 'to', 'year'])
def test_facets(self):
self._make_entry(name='one', region="Region A")
self._make_entry(name='two', region="Region A")
self._make_entry(name='three', region="Region B")
h.clean_and_reindex_solr()
facets = logic.entry.facets_for_fields(['name', 'region'])
h.assert_equal(facets, {u'name': {u'one': 1,
u'two': 1,
u'three': 1},
u'region': {'Region A': 2,
'Region B': 1}})
def test_facets_with_query_kwarg_and_space(self):
self._make_entry(name='one', region="Region A")
self._make_entry(name='two', region="Region A")
self._make_entry(name='three', region="Region B")
h.clean_and_reindex_solr()
facets = logic.entry.facets_for_fields(['name'], region='Region A')
h.skip("This test has been failing for a long time, commented out. "\
"Skipping to register known failure that needs fixing eventually.")
h.assert_equal(facets, {u'name': {u'one': 1,
u'two': 1}})
def assert_order(result, keys, expect):
if isinstance(keys, basestring):
keys = [keys]
results = []
for key in keys:
results.append([deep_get(cell, key) for
cell in result['drilldown']])
if len(results) == 1:
result = results[0]
else:
result = zip(*results)
h.assert_equal(result, expect,
'Not the expected order. result: %s, expected: %s' %
(result, expect))
def test_metadata_for_resource(self):
p = ckan.Package('bar')
r = p['resources'][1]
h.assert_equal(p.metadata_for_resource(r), {
'currency': 'usd',
'description': 'Notes for bar',
'label': 'The Bar dataset',
'name': 'bar',
'source_description': 'Some bar data',
'source_format': 'text/csv',
'source_id': '456-data',
'source_url': 'http://example.com/data.csv',
'temporal_granularity': 'year'
})
def test_facets_fail_for_solr_textgen_fields(self):
# facets for a solr field return facets for the tokens stored
# in the field. Depending on the type this may mean that
# it's not the string stored in the field, but tokens after
# splitting, stemming or lowercasing
self._make_entry(name='one', description="Description One")
self._make_entry(name='two', description="Description Two")
h.clean_and_reindex_solr()
facets = logic.entry.facets_for_fields(['description'])
# The result is not ["Description One", "Description Two"]
h.assert_equal(facets, {u'description': {u'description': 2,
u'two': 1,
u'one': 1}})
def test_distincts_by_dataset_name(self):
self._make_entry(name='one', region='Region A')
self._make_entry(name='two', region='Region A')
self._make_entry(name='three', region='Region B')
other_dataset = self._make_dataset('other_dataset')
self._make_entry(name='four', region='Region C',
dataset=other_dataset)
# without a dataset_name it returns the distincts across all datasets
distincts = logic.entry.distinct('region')
h.assert_equal(distincts, ['Region A', 'Region B', 'Region C'])
# we can limit it with dataset_name
distincts = logic.entry.distinct('region', dataset_name='other_dataset')
h.assert_equal(distincts, ['Region C'])
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_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_limit(self):
# A limit turns a result into a paginated result with
# the pagesize of limit
cube = self._make_cube()
result = cube.query(pagesize=2)
h.assert_equal(result['summary']['pagesize'], 2)
h.assert_equal(len(result['drilldown']), 2)
h.assert_equal(result['summary']['page'], 1)
h.assert_equal(result['summary']['pages'], 3)
def test_facets_by_dataset(self):
self._make_entry(name='one')
self._make_entry(name='two')
other_dataset = self._make_dataset('other_dataset')
self._make_entry(name='three', dataset=other_dataset)
self._make_entry(name='four', dataset=other_dataset)
h.clean_and_reindex_solr()
# without a dataset_name it returns the distincts across all datasets
facets = logic.entry.facets_for_fields(['name'])
h.assert_equal(facets, {u'name': {u'one': 1,
u'two': 1,
u'three': 1,
u'four': 1}})
# we can limit it with dataset_name
facets = logic.entry.facets_for_fields(['name'],
dataset_name='other_dataset')
h.assert_equal(facets, {u'name': {u'three': 1,
u'four': 1}})
def test_fallback_for_missing_entity_name(self):
# We use the objectid of an entity as a fallback value for 'name'
loader = self._make_loader()
loader.create_dimension('name', 'Name', '')
loader.create_dimension('label', 'Label', '')
loader.create_dimension('from', 'From', '')
from_entity = self._make_entity(loader, name="",
label='Entity w/o name')
entry = {'name': 'Entry',
'label': 'Entry Label',
'from': from_entity,
'time': {'from': {'year': 2009,
'day': 20090101}}}
self._make_entry(loader, **entry)
cube = Cube.configure_default_cube(loader.dataset)
cube.compute()
cube_collection = mongo.db()[cube.collection_name]
h.assert_equal(cube_collection.find().count(), 1)
cube_from = cube_collection.find_one()['from']
h.assert_equal(cube_from['name'], cube_from['_id'])
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_drilldown(self):
def sorted_extract(drilldown):
extracted = []
for cell in drilldown:
cell_extract = []
for key in ('from.name', 'to.name', 'num_entries', 'amount'):
cell_extract.append(deep_get(cell, key))
extracted.append(cell_extract)
return sorted(extracted)
cube = self._make_cube()
h.assert_equal(cube.db[cube.collection_name].find().count(), 5)
# drilldown on from and to
result = cube.query(drilldowns=['from', 'to'])
drilldown = result['drilldown']
h.assert_equal(len(drilldown), 5)
h.assert_equal(sorted_extract(drilldown),
[[u'a', u'b', 2, 2000.0],
[u'b', u'b', 1, 1000.0],
[u'b', u'c', 1, 1000.0],
[u'c', u'a', 1, 1000.0],
[u'c', u'b', 1, 1000.0]])
# drilldown on from (to is not included in the drilldown)
result = cube.query(drilldowns=['from'])
drilldown = result['drilldown']
h.assert_equal(len(drilldown), 3)
h.assert_equal(sorted_extract(drilldown),
[[u'a', None, 2, 2000.0],
[u'b', None, 2, 2000.0],
[u'c', None, 2, 2000.0]])
# drilldown on to (from is not included in the drilldown)
result = cube.query(drilldowns=['to'])
drilldown = result['drilldown']
h.assert_equal(len(drilldown), 3)
h.assert_equal(sorted_extract(drilldown),
[[None, u'a', 1, 1000.0],
[None, u'b', 4, 4000.0],
[None, u'c', 1, 1000.0]])
def test_entry_properties(self):
h.assert_equal(self.ent.name, 'testentry')
h.assert_equal(self.ent.label, 'An Entry')
h.assert_equal(self.ent.amount, 123.45)
h.assert_equal(self.ent.currency, 'GBP')
def test_facet_dimensions(self):
h.assert_equal([d.name for d in self.ds.facet_dimensions], ["to"])
def test_classifier_properties(self):
h.assert_equal(self.cla.label, 'Foo Classifier')
h.assert_equal(self.cla.level, '1')
h.assert_equal(self.cla.taxonomy, 'class.foo')
h.assert_equal(self.cla.description, 'Denotes the foo property.')
h.assert_equal(self.cla.parent, 'class')
def test_facet_dimensions(self):
h.assert_equal([d.name for d in self.ds.facet_dimensions], ['to'])
def test_get_resource(self):
p = ckan.Package('bar')
h.assert_equal(p.get_resource('456-data')['url'], 'http://example.com/data.csv')
def test_paginate(self):
cube = self._make_cube()
# with pagesize < # of drilldowns
result = cube.query(page=1, pagesize=2)
h.assert_equal(len(result['drilldown']), 2)
summary = result['summary']
h.assert_equal(summary['pagesize'], 2)
h.assert_equal(summary['page'], 1)
h.assert_equal(summary['pages'], 3)
# with pagesize < # of drilldowns, but page > max pages
result = cube.query(page=5, pagesize=2)
h.assert_equal(len(result['drilldown']), 0)
summary = result['summary']
h.assert_equal(summary['pagesize'], 2)
h.assert_equal(summary['page'], 5)
h.assert_equal(summary['pages'], 3)
# with pagesize > # of drilldowns
result = cube.query(page=1, pagesize=7)
h.assert_equal(len(result['drilldown']), 5)
summary = result['summary']
h.assert_equal(summary['pagesize'], 7)
h.assert_equal(summary['page'], 1)
h.assert_equal(summary['pages'], 1)
def test_members(self):
members = list(self.entity.members())
h.assert_equal(len(members), 5)
members = list(self.entity.members(self.entity.alias.c.name == 'Dept032'))
h.assert_equal(len(members), 1)
