def test_key_inequality(self):
''' Make sure keys don't equal each other when they shouldn't. '''
conditions = []
# test with determininstic ID
k1 = model.Key("TestKind", "blabs")
k2 = model.Key("TestKind", "blobs")
conditions.append((k1 != k2))
# test kinded keys
k3 = model.Key("TestKind")
k4 = model.Key("TestOtherKind")
conditions.append((k3 != k4))
# test ancestored keys with different IDs
k5 = model.Key("TestSubkind", "blabs", parent=k1)
k6 = model.Key("TestSubkind", "blobs", parent=k1)
conditions.append((k5 != k6))
# test ancestored keys with different kinds
k7 = model.Key("TestSubkindOne", "blabs", parent=k1)
k8 = model.Key("TestSubkindTwo", "blabs", parent=k1)
conditions.append((k7 != k8))
# test ancestored keys with different parents
k9 = model.Key("TestSubkind", "blabs", parent=k1)
k10 = model.Key("TestSubkind", "blabs", parent=k2)
conditions.append((k9 != k10))
[self.assertTrue(condition) for condition in conditions]
def test_key_construct_multiple_formats(self):
''' Test constuction of a `Key` with multiple formats, which is not supported. '''
# sample key
ok = model.Key("Sample", "sample_id")
# try and make a key with multiple formats
with self.assertRaises(TypeError):
model.Key(raw=ok.flatten(False)[1], urlsafe=ok.urlsafe())
def test_key_with_overflowing_schema(self):
''' Test construction of a `Key` with too many schema items. '''
# try and make a key with a ton of arguments
with self.assertRaises(TypeError):
model.Key("SampleKind", "id", "coolstring", "whatdowedo",
"whenwehave", "thismanyarguments")
def test_model_setkey(self):
''' Test the protected method `_set_key`, which is used by Model API internals. '''
# sample person
p = Person(firstname='John')
# try writing an invalid key
with self.assertRaises(TypeError):
p._set_key(5.5)
# try writing via kwargs
k = model.Key(Person, "john")
# try constructing via urlsafe
p._set_key(urlsafe=k.urlsafe())
# try constructing via raw
p._set_key(raw=k.flatten(False)[1])
# try already-constructed via kwargs
p._set_key(constructed=k)
# try providing both a value and formats, which should fail
with self.assertRaises(TypeError):
p._set_key(k, urlsafe=k.urlsafe())
# try providing multiple formats, which should fail
with self.assertRaises(TypeError):
p._set_key(urlsafe=k.urlsafe(), raw=k.flatten(False)[1])
# try passing nothing, which should fail
with self.assertRaises(TypeError):
p._set_key(None)
def test_key_overwrite_known_attribute(self):
''' Try overwriting a known (schema-d) attribute. '''
k = model.Key("CoolKind", "coolid")
with self.assertRaises(AttributeError):
k.kind = "MyKind"
with self.assertRaises(AttributeError):
k.id = 10
def test_key_with_model_class_kind(self):
''' Test making a `Key` via using a model class as the kind. '''
## KindedModel
# Used to test using classes for kinds in `model.Key`.
class KindedModel(model.Model):
''' Sample for testing key creation from model classes. '''
string = basestring
# make keys
k1 = model.Key("KindedModel", "test_id")
k2 = model.Key(KindedModel, "test_id")
ko = model.Key(KindedModel)
# test keys
self.assertEqual(k1.kind, "KindedModel")
self.assertEqual(k1.id, "test_id")
self.assertEqual(k2.kind, k1.kind)
self.assertEqual(ko.kind, k1.kind)
self.assertEqual(k2.id, k2.id)
def test_key_ancestry(self):
''' Make a key with ancestry and test it a bunch. '''
# manufacture keys
pk = model.Key("ParentKind", "parent_id")
ck = model.Key("ChildKind", "child_id", parent=pk)
gk = model.Key("GrandchildKind", "grandchild_id", parent=ck)
ggk = model.Key("GreatGrandchildKind",
"great_grandchild_id",
parent=gk)
# for each key, make sure parent is set
self.assertEqual(pk.parent, None)
self.assertEqual(ck.parent, pk)
self.assertEqual(gk.parent, ck)
self.assertEqual(ggk.parent, gk)
# for each key, make sure ancestry works
pk_ancestry = [i for i in pk.ancestry]
ck_ancestry = [i for i in ck.ancestry]
gk_ancestry = [i for i in gk.ancestry]
ggk_ancestry = [i for i in ggk.ancestry]
# test ancestry paths
self.assertEqual(len(pk_ancestry), 1)
self.assertEqual(len(ck_ancestry), 2)
self.assertEqual(len(gk_ancestry), 3)
self.assertEqual(len(ggk_ancestry), 4)
# len of a key should always be 1 unless it has ancestry, then it's the length of the ancestry chain
self.assertEqual(len(pk), 1)
self.assertEqual(len(ck), 2)
self.assertEqual(len(gk), 3)
self.assertEqual(len(ggk), 4)
# ... however all keys should test nonzero-ness (all keys should be nonzero)
for k in (pk, ck, gk, ggk):
self.assertTrue(k)
def test_key_format(self):
''' Make sure there's a proper format spec on `model.Key`. '''
# build object
k1 = model.Key("Test", "testkey")
# test class
self.assertTrue(hasattr(model.Key, '__schema__'))
self.assertIsInstance(model.Key.__schema__, tuple)
self.assertTrue((len(model.Key.__schema__) > 1))
# test object
self.assertTrue(hasattr(k1, '__schema__'))
self.assertIsInstance(model.Key.__schema__, tuple)
self.assertTrue((len(model.Key.__schema__) > 1))
def test_key_adapter(self):
''' Make sure the adapter is attached correctly to `model.Key`. '''
# build test obj
k = model.Key("TestKind", "test")
# make sure an adapter is attached at the class level
self.assertTrue(hasattr(model.Key, '__adapter__'))
self.assertIsInstance(model.Key.__adapter__,
model.adapter.ModelAdapter)
# make sure the same is true at the object level
self.assertTrue(hasattr(k, '__adapter__'))
self.assertIsInstance(model.Key.__adapter__,
model.adapter.ModelAdapter)
def factory(cls, parent=None, id=None, **kwargs):
''' '''
# figure out key ID and parent
id, parent = (
parent if (not id or (isinstance(basestring, parent) and not parent)) else id,
parent if not isinstance(parent, basestring) else None
)
# inject ID if we have one
if hasattr(cls, 'id'): kwargs['id'] = id
# factory object
return cls(key=model.Key(cls, id, parent=parent), **kwargs)
def test_model_setvalue(self):
''' Test the protected method `_set_value`, which is used by Model API internals. '''
# sample person
p = Person(firstname='John')
# try writing a new key
x = p._set_value('key', model.Key(Person, "john"))
self.assertEqual(x, p)
# try writing to invalid property
with self.assertRaises(AttributeError):
p._set_value('invalidproperty', 'value')
# quick test via descriptor API, which should also raise `AttributeError`
with self.assertRaises(AttributeError):
Person.__dict__['firstname'].__set__(None, 'invalid')
def test_key_auto_id(self):
''' Test an integer-based ID field. '''
class AutoincrementTest(model.Model):
''' Test that keys autoincrement properly when not assigned
deterministic name values. '''
message = basestring, {'default': 'Hello, world!'}
# put deterministic key
a = AutoincrementTest(
key=model.Key(AutoincrementTest.kind(), 'testing-string-key'))
dk = a.put()
# put nondeterministic key #1
nk = AutoincrementTest().put()
# put nondeterministic key #2
nk2 = AutoincrementTest().put()
self.assertIsInstance(nk.id, int) # nondeterministic should be an int
self.assertIsInstance(dk.id,
basestring) # deterministic should be a string
self.assertTrue((nk2.id > nk.id)) # should be greater
def test_key_equality(self):
''' Make sure keys equal each other when they should. '''
conditions = []
# test with determininstic ID
k1 = model.Key("TestKind", "blabs")
k2 = model.Key("TestKind", "blabs")
conditions.append((k1 == k2))
# test kinded keys
k3 = model.Key("TestKind")
k4 = model.Key("TestKind")
conditions.append((k3 == k4))
# test ancestored keys
k5 = model.Key("TestSubkind", "blobs", parent=k1)
k6 = model.Key("TestSubkind", "blobs", parent=k2)
conditions.append((k5 == k6))
[self.assertTrue(condition) for condition in conditions]
def test_key_set_unknown_attribute(self):
''' Try setting an unknown and known attribute. '''
k = model.Key("CoolKind", "coolid")
with self.assertRaises(AttributeError):
k.blabble = True # try writing unknown attribute
def make_key(id=None, model=UserSession):
''' '''
return models.Key(
model, id
or Session.generate_token(Session.config.get('salt', '')))
def execute_query(cls, kind, spec, options, **kwargs): # pragma: no cover
''' Execute a :py:class:`model.Query` across one (or multiple)
indexed properties.
:param kind: Kind name (``str``) for which we are querying
across, or ``None`` if this is a ``kindless`` query.
:param spec: Tupled pair of ``filter`` and ``sort`` directives
to apply to this :py:class:`Query` (:py:class:`query.Filter` and
:py:class:`query.Sort` and their descendents, respectively), like
``(<filters>, <sorts>)``.
:param options: Object descendent from, or directly instantiated
as :py:class:`QueryOptions`, specifying options for the execution
of this :py:class:`Query`.
:param **kwargs: Low-level options for handling this query, such
as ``pipeline`` (for pipelining support) and ``execute`` (to trigger
a buffer flush for a generated or constructed pipeline or operation
buffer).
:returns: Iterable (``list``) of matching :py:class:`model.Key`
yielded by execution of the current :py:class:`Query`. Returns
empty iterable (``[]``) in the case that no results could be found. '''
# @TODO(sgammon): desparately needs rewriting. absolute utter plebbery.
from canteen import model
from canteen.model import query
if not kind:
# @TODO(sgammon): implement kindless queries
raise NotImplementedError(
'Kindless queries are not yet implemented in `Redis`.')
# extract filter and sort directives and build ancestor
filters, sorts = spec
ancestry_parent = model.Key.from_urlsafe(
options.ancestor) if options.ancestor else None
_data_frame = [] # allocate results window
if filters:
kinded_key = model.Key(kind, parent=ancestry_parent)
## HUGE HACK: use generate_indexes to make index names.
# fix this plz
_filters, _filter_i_lookup = {}, set()
for _f in filters:
origin, meta, property_map = cls.generate_indexes(
kinded_key, {_f.target.name: (_f.target, _f.value.data)})
for operation, index, config in cls.write_indexes(
(origin, [], property_map), None, False):
if operation == 'ZADD':
_flag, _index_key, value = 'Z', index[1], index[2]
else:
_flag, _index_key, value = 'S', index[1], index[2]
if (_flag, _index_key) not in _filter_i_lookup:
_filters[(_flag, _index_key)] = []
_filter_i_lookup.add((_flag, _index_key))
_filters[(_flag, _index_key)].append(
(_f.operator, value, _f.chain))
# process sorted sets first: leads to lower cardinality
sorted_indexes = dict([
(index, _filters[index])
for index in filter(lambda x: x[0] == 'Z', _filters.iterkeys())
])
unsorted_indexes = dict([
(index, _filters[index])
for index in filter(lambda x: x[0] == 'S', _filters.iterkeys())
])
_and_filters, _or_filters = [], []
if sorted_indexes:
for prop, _directives in sorted_indexes.iteritems():
_operator, _value, chain = _directives[0]
if chain:
for subquery in chain:
if subquery.sub_operator is query.AND:
_and_filters.append(subquery)
if subquery.sub_operator is query.OR:
_or_filters.append(subquery)
# double-filters
if len(_filters[prop]) == 2:
# extract info
_operators = [
operator for operator, value in _directives
]
_values = [value for operator, value in _directives]
_, prop = prop
# special case: maybe we can do a sorted range request
if (query.GREATER_THAN
in _operators) or (query.GREATER_THAN_EQUAL_TO
in _operators):
if (query.LESS_THAN
in _operators) or (query.LESS_THAN_EQUAL_TO
in _operators):
# range value query over sorted index
greater, lesser = max(_values), min(_values)
_data_frame.append(
cls.execute(
*(cls.Operations.SORTED_RANGE_BY_SCORE,
None, prop, min(_values),
max(_values), options.offset,
options.limit)))
continue
# single-filters
if len(_filters[prop]) == 1:
# extract info
_operator = [
operator for operator, value in _directives
][0]
_value = float(
[value for operator, value in _directives][0])
_, prop = prop
if _operator is query.EQUALS:
# static value query over sorted index
_data_frame.append(
cls.execute(
*(cls.Operations.SORTED_RANGE_BY_SCORE,
None, prop, _value, _value,
options.offset, options.limit)))
continue
## @TODO(sgammon): build this query branch
raise RuntimeError("Specified query is not yet supported.")
if unsorted_indexes:
_intersections = set()
for prop, _directives in unsorted_indexes.iteritems():
_operator, _value, chain = _directives[0]
if chain:
for subquery in chain:
if subquery.sub_operator is query.AND:
_and_filters.append(subquery)
if subquery.sub_operator is query.OR:
_or_filters.append(subquery)
_flag, index = prop
_intersections.add(index)
# special case: only one unsorted set - pull content instead of a intersection merge
if _intersections and len(_intersections) == 1:
_data_frame.append(
cls.execute(*(cls.Operations.SET_MEMBERS, None,
_intersections.pop())))
# more than one intersection: do an `SINTER` call instead of `SMEMBERS`
if _intersections and len(_intersections) > 1:
_data_frame.append(
cls.execute(*(cls.Operations.SET_INTERSECT, None,
_intersections)))
if _data_frame: # there were results, start merging
_result_window = set()
for frame in _data_frame:
if not len(_result_window):
_result_window = set(frame)
continue # initial frame: fill background
_result_window = (_result_window & set(frame))
matching_keys = [k for k in _result_window]
else:
matching_keys = []
else:
if not sorts:
# grab all entities of this kind
prefix = model.Key(kind, 0,
parent=ancestry_parent).urlsafe().replace(
'=', '')[0:-3]
matching_keys = cls.execute(cls.Operations.KEYS, kind.kind(),
prefix +
'*') # regex search it. why not
# if we're doing keys only, we're done
if options.keys_only and not (_and_filters or _or_filters):
return [
model.Key.from_urlsafe(k, _persisted=True)
for k in matching_keys
]
# otherwise, build entities and return
result_entities = []
# fetch keys
with cls.channel(kind.kind()).pipeline() as pipeline:
# fill pipeline
_seen_results = 0
for key in matching_keys:
if (not (_and_filters or _or_filters)) and (
options.limit > 0 and _seen_results >= options.limit):
break
_seen_results += 1
cls.execute(cls.Operations.GET,
kind.kind(),
key,
target=pipeline)
_blob_results = pipeline.execute()
# execute pipeline, zip keys and build results
for key, entity in zip([
model.Key.from_urlsafe(k, _persisted=True)
for k in matching_keys
], _blob_results):
_seen_results = 0
if not entity:
continue
if (options.limit > 0) and _seen_results >= options.limit:
break
# decode raw entity
decoded = cls.get(None, None, entity)
# attach key, decode entity and construct
decoded['key'] = key
if _and_filters or _or_filters:
if _and_filters and not all(
(filter.match(decoded) for filter in _and_filters)):
continue # doesn't match one of the filters
if _or_filters and not any(
(filter.match(decoded) for filter in _or_filters)):
continue # doesn't match any of the `or` filters
# matches, by the grace of god
_seen_results += 1
result_entities.append(kind(_persisted=True, **decoded))
return result_entities
