function stringlengths 11 56k | repo_name stringlengths 5 60 | features list |
|---|---|---|
def test_get_lang(self):
self.get_lang(self.map1) | c2corg/v6_api | [
21,
18,
21,
89,
1439983299
] |
def test_get_404(self):
self.get_404() | c2corg/v6_api | [
21,
18,
21,
89,
1439983299
] |
def test_get_info(self):
body, locale = self.get_info(self.map1, 'en')
self.assertEqual(locale.get('lang'), 'en') | c2corg/v6_api | [
21,
18,
21,
89,
1439983299
] |
def test_post_error(self):
body = self.post_error({}, user='moderator')
errors = body.get('errors')
self.assertEqual(len(errors), 2)
self.assertCorniceRequired(errors[0], 'locales')
self.assertCorniceRequired(errors[1], 'geometry') | c2corg/v6_api | [
21,
18,
21,
89,
1439983299
] |
def test_post_non_whitelisted_attribute(self):
body = {
'editor': 'IGN',
'scale': '25000',
'code': '3432OT',
'protected': True,
'geometry': {
'id': 5678, 'version': 6789,
'geom_detail': '{"type":"Polygon","coordinates":[... | c2corg/v6_api | [
21,
18,
21,
89,
1439983299
] |
def test_post_success(self):
body = {
'editor': 'IGN',
'scale': '25000',
'code': '3432OT',
'geometry': {
'id': 5678, 'version': 6789,
'geom_detail': '{"type":"Polygon","coordinates":[[[668518.249382151,5728802.39591739],[668518.2493... | c2corg/v6_api | [
21,
18,
21,
89,
1439983299
] |
def test_put_wrong_document_version(self):
body = {
'document': {
'document_id': self.map1.document_id,
'version': -9999,
'editor': 'IGN',
'scale': '25000',
'code': '3432OT',
'locales': [
... | c2corg/v6_api | [
21,
18,
21,
89,
1439983299
] |
def test_put_wrong_ids(self):
body = {
'document': {
'document_id': self.map1.document_id,
'version': self.map1.version,
'editor': 'IGN',
'scale': '25000',
'code': '3432OT',
'locales': [
... | c2corg/v6_api | [
21,
18,
21,
89,
1439983299
] |
def test_put_success_all(self):
body = {
'message': 'Update',
'document': {
'document_id': self.map1.document_id,
'version': self.map1.version,
'quality': quality_types[1],
'editor': 'IGN',
'scale': '25000',
... | c2corg/v6_api | [
21,
18,
21,
89,
1439983299
] |
def test_put_success_lang_only(self):
body = {
'message': 'Changing lang',
'document': {
'document_id': self.map1.document_id,
'version': self.map1.version,
'quality': quality_types[1],
'editor': 'IGN',
'scal... | c2corg/v6_api | [
21,
18,
21,
89,
1439983299
] |
def _assert_geometry(self, body):
self.assertIsNotNone(body.get('geometry'))
geometry = body.get('geometry')
self.assertIsNotNone(geometry.get('version'))
self.assertIsNotNone(geometry.get('geom_detail'))
geom = geometry.get('geom_detail')
polygon = shape(json.loads(geom... | c2corg/v6_api | [
21,
18,
21,
89,
1439983299
] |
def __init__(self, param):
"""
Initialization
:Parameters:
`param` : ``dict``
Parameters
"""
self.param = param | ndparker/tdi | [
8,
2,
8,
2,
1381778054
] |
def getlist(self, name):
""" :See: ``tdi.tools.htmlform.ParameterAdapterInterface`` """
if name in self.param:
return [self.param[name]]
return [] | ndparker/tdi | [
8,
2,
8,
2,
1381778054
] |
def __init__(self, param):
"""
Initialization
:Parameters:
`param` : dict of sequences
Parameters. Empty sequences act as if the key was not present.
Otherwise ``getfirst`` will return the first element and
``getlist`` will return a shallow copy of ... | ndparker/tdi | [
8,
2,
8,
2,
1381778054
] |
def getlist(self, name):
""" :See: ``tdi.tools.htmlform.ParameterAdapterInterface`` """
try:
result = self.param[name]
except KeyError:
pass
else:
return list(result)
return [] | ndparker/tdi | [
8,
2,
8,
2,
1381778054
] |
def __init__(self, param):
"""
Initialization
:Parameters:
`param` : multidict
Parameters. The object is expected to provide a getall() method
"""
self.param = param | ndparker/tdi | [
8,
2,
8,
2,
1381778054
] |
def getlist(self, name):
""" :See: ``tdi.tools.htmlform.ParameterAdapterInterface`` """
return self.param.getall(name) | ndparker/tdi | [
8,
2,
8,
2,
1381778054
] |
def getlist(self, name):
""" :See: `ParameterAdapterInterface.getlist` """
# pylint: disable = unused-argument
return [] | ndparker/tdi | [
8,
2,
8,
2,
1381778054
] |
def __init__(self, newPersionName):
#self.name = newPersionName; | onehao/opensource | [
1,
1,
1,
1,
1414656394
] |
def sayYourName(self):
#此处，之所以没有像之前一样出现：
#AttributeError: Person instance has no attribute 'name'
#那是因为，虽然当前的实例self中，没有在__init__中初始化对应的name变量，实例self中没有对应的name变量
#但是由于实例所对应的类Person，有对应的name变量,所以也是可以正常执行代码的
#对应的，此处的self.name，实际上是Person.name
print 'My name is %s'%(self.name)... | onehao/opensource | [
1,
1,
1,
1,
1414656394
] |
def changeGlobalName(self,newName):
global name
name = "new class global name" | onehao/opensource | [
1,
1,
1,
1,
1414656394
] |
def say(self):
#此处，之所以没有像之前一样出现：
#AttributeError: Person instance has no attribute 'name'
#那是因为，虽然当前的实例self中，没有在__init__中初始化对应的name变量，实例self中没有对应的name变量
#但是由于实例所对应的类Person，有对应的name变量,所以也是可以正常执行代码的
#对应的，此处的self.name，实际上是Person.name
print 'My name is %s'%(self.name); # -> c... | onehao/opensource | [
1,
1,
1,
1,
1414656394
] |
def selfAndInitDemo():
persionInstance = Person("crifan");
persionInstance.sayYourName();
personInstance2 = Person("michael")
personInstance2.sayYourName()
personInstance2.changeGlobalName("newName")
personInstance2.sayYourName()
print "whole global name is %s"%(name); # -> whole global name... | onehao/opensource | [
1,
1,
1,
1,
1414656394
] |
def _compute_xent_loss_helper(
predictions: NestedMap, input_batch: NestedMap,
return_predictions: bool) -> Tuple[Metrics, Dict[str, Any]]:
"""Helper for computing the xent loss for Language model and Sequence model.
Args:
predictions: A `.NestedMap` containing the keys `per_example_argmax`,
`tot... | tensorflow/lingvo | [
2689,
429,
2689,
115,
1532471428
] |
def cond_func(val):
"""Whether the while loop should continue."""
# We continue the greedy search iff both:
# (1) We have yet to exceed the max steps set by p.decoder.seqlen, AND;
# (2) At least one row in the batch has not terminated.
length_ok = val.step < seq_len - 1
all_rows_done = jnp.a... | tensorflow/lingvo | [
2689,
429,
2689,
115,
1532471428
] |
def compute_predictions(self, input_batch: NestedMap) -> Predictions:
"""Computes predictions for `input_batch`.
This method must be defined in a concrete derived class.
The output can be in the form of probablistic distributions, e.g., softmax
logits for discrete outputs, mixture of logistics for con... | tensorflow/lingvo | [
2689,
429,
2689,
115,
1532471428
] |
def fprop(self, input_batch: NestedMap) -> Tuple[Metrics, Dict[str, Any]]:
"""Forward propagation through one tower of the model.
Args:
input_batch: A `.NestedMap` object containing input tensors to this tower.
Returns:
(dict, dict):
- A dict containing str keys and (metric, weight) pai... | tensorflow/lingvo | [
2689,
429,
2689,
115,
1532471428
] |
def process_decode_out(
self, input_obj: base_input.BaseInput,
decode_out: NestedMap) -> Tuple[NestedMap, Sequence[Tuple[str, Any]]]:
"""Processes one batch of decoded outputs.
Args:
input_obj: The input object where a tokenizer is accessible.
decode_out: The output from decode(). May h... | tensorflow/lingvo | [
2689,
429,
2689,
115,
1532471428
] |
def Params(cls) -> InstantiableParams:
p = super().Params()
p.Define('mlp_tpl', layers.linears.MLPBlock.Params(),
'MLP model parameters.')
p.Define('softmax_tpl', layers.SingleShardSharedEmbeddingSoftmax.Params(),
'Input softmax embedding lookup layer.')
return p | tensorflow/lingvo | [
2689,
429,
2689,
115,
1532471428
] |
def compute_predictions(self, input_batch: NestedMap) -> Predictions:
input_emb = self.softmax.emb_lookup(input_batch.ids)
output = self.mlp_layers.fprop(input_emb)
predictions = self.softmax.fprop(
inputs=output,
class_weights=input_batch.weights[:, :, jnp.newaxis],
class_ids=inpu... | tensorflow/lingvo | [
2689,
429,
2689,
115,
1532471428
] |
def Params(cls) -> InstantiableParams:
p = super().Params()
p.Define('lm', layers.TransformerLm.Params(), 'LM layer.')
p.Define(
'return_predictions', False, 'Whether to return predictions during'
'eval. Returning predictions is more expensive, but may be useful'
'for debugging.')
... | tensorflow/lingvo | [
2689,
429,
2689,
115,
1532471428
] |
def compute_predictions(self, input_batch: NestedMap) -> Predictions:
"""Computes predictions for `input_batch`."""
p = self.params
if 'tgt' in input_batch:
input_batch = input_batch.tgt
if 'paddings' in input_batch:
paddings = input_batch.paddings
else:
paddings = jnp.equal(input... | tensorflow/lingvo | [
2689,
429,
2689,
115,
1532471428
] |
def decode(self, input_batch: NestedMap) -> Tuple[NestedMap, NestedMap]:
"""Greedy decodes the input_batch.
Args:
input_batch: The input batch, with fields like `.ids`.
Returns:
- metrics, a NestedMap containing str keys and (metrics, weight) pairs.
- A NestedMap like `input_batch`, with... | tensorflow/lingvo | [
2689,
429,
2689,
115,
1532471428
] |
def Params(cls) -> InstantiableParams:
p = super().Params()
p.Define('model', layers.TransformerEncoderDecoder.Params(),
'Sequence model layer for this task.')
p.Define(
'return_predictions', False, 'Whether to return predictions during'
'eval. Returning predictions is more expe... | tensorflow/lingvo | [
2689,
429,
2689,
115,
1532471428
] |
def compute_predictions(self, input_batch):
"""Computes predictions for `input_batch`."""
p = self.params
if p.model.packed_input:
packed_input_kwargs = {
'input_segment_ids': input_batch.src.segment_ids,
'input_segment_pos': input_batch.src.segment_pos,
'target_segment_i... | tensorflow/lingvo | [
2689,
429,
2689,
115,
1532471428
] |
def decode(self, input_batch: NestedMap) -> Tuple[NestedMap, NestedMap]:
"""Decodes input_batch.
Args:
input_batch: The input batch, with a field `.src` and `.tgt` corresponding
to source and target, which itself contains the `.ids` and `.paddings.`
Returns:
- metrics, a nestedmap of m... | tensorflow/lingvo | [
2689,
429,
2689,
115,
1532471428
] |
def Params(cls) -> InstantiableParams:
p = super().Params()
p.Define('network', layers.ResNet.Params(),
'The classifier network, which is ResNet-50 by default.')
p.Define('softmax', layers.SingleShardFullSoftmax.Params(),
'The softmax layer used for the classification.')
p.Defi... | tensorflow/lingvo | [
2689,
429,
2689,
115,
1532471428
] |
def compute_predictions(self, input_batch: NestedMap) -> Predictions:
"""Computes predictions for `input_batch`.
Args:
input_batch: A `.NestedMap` object containing input tensors to this tower.
Returns:
- A NestedMap containing str keys and features, softmax output and the
class weight... | tensorflow/lingvo | [
2689,
429,
2689,
115,
1532471428
] |
def Params(cls) -> InstantiableParams:
p = super().Params()
p.Define('lm', layers.TransformerLm.Params(), 'Bert lm layer.')
p.Define(
'label_smoothing_prob', 0.0,
'If > 0.0, smooth out one-hot prob by spreading this amount of'
' prob mass to all other tokens.')
p.Define('mask_tok... | tensorflow/lingvo | [
2689,
429,
2689,
115,
1532471428
] |
def compute_predictions(self, input_batch: NestedMap) -> Predictions:
"""Computes predictions for `input_batch`."""
p = self.params
assert p.lm.packed_input
segment_ids = input_batch.segment_ids
segment_pos = input_batch.segment_pos
paddings = input_batch.paddings
# Note that internal BertTr... | tensorflow/lingvo | [
2689,
429,
2689,
115,
1532471428
] |
def setUpTestData(cls):
regions = (
Region(name='Region 1', slug='region-1', description='A'),
Region(name='Region 2', slug='region-2', description='B'),
Region(name='Region 3', slug='region-3', description='C'),
)
for region in regions:
region.sa... | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def test_name(self):
params = {'name': ['Region 1', 'Region 2']}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 2) | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def test_description(self):
params = {'description': ['A', 'B']}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 2) | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def setUpTestData(cls):
regions = (
Region(name='Region 1', slug='region-1'),
Region(name='Region 2', slug='region-2'),
Region(name='Region 3', slug='region-3'),
)
for region in regions:
region.save()
tenant_groups = (
TenantG... | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def test_name(self):
params = {'name': ['Site 1', 'Site 2']}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 2) | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def test_facility(self):
params = {'facility': ['Facility 1', 'Facility 2']}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 2) | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def test_latitude(self):
params = {'latitude': [10, 20]}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 2) | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def test_contact_name(self):
params = {'contact_name': ['Contact 1', 'Contact 2']}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 2) | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def test_contact_email(self):
params = {'contact_email': ['contact1@example.com', 'contact2@example.com']}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 2) | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def test_region(self):
regions = Region.objects.all()[:2]
params = {'region_id': [regions[0].pk, regions[1].pk]}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 2)
params = {'region': [regions[0].slug, regions[1].slug]}
self.assertEqual(self.filterset(params, s... | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def test_tenant_group(self):
tenant_groups = TenantGroup.objects.all()[:2]
params = {'tenant_group_id': [tenant_groups[0].pk, tenant_groups[1].pk]}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 2)
params = {'tenant_group': [tenant_groups[0].slug, tenant_groups[1].slu... | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def setUpTestData(cls):
regions = (
Region(name='Region 1', slug='region-1'),
Region(name='Region 2', slug='region-2'),
Region(name='Region 3', slug='region-3'),
)
for region in regions:
region.save()
sites = (
Site(name='Site... | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def test_name(self):
params = {'name': ['Rack Group 1', 'Rack Group 2']}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 2) | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def test_description(self):
params = {'description': ['A', 'B']}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 2) | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def test_site(self):
sites = Site.objects.all()[:2]
params = {'site_id': [sites[0].pk, sites[1].pk]}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 4)
params = {'site': [sites[0].slug, sites[1].slug]}
self.assertEqual(self.filterset(params, self.queryset).qs.c... | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def setUpTestData(cls):
rack_roles = (
RackRole(name='Rack Role 1', slug='rack-role-1', color='ff0000'),
RackRole(name='Rack Role 2', slug='rack-role-2', color='00ff00'),
RackRole(name='Rack Role 3', slug='rack-role-3', color='0000ff'),
)
RackRole.objects.bul... | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def test_name(self):
params = {'name': ['Rack Role 1', 'Rack Role 2']}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 2) | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def test_color(self):
params = {'color': ['ff0000', '00ff00']}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 2) | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def setUpTestData(cls):
regions = (
Region(name='Region 1', slug='region-1'),
Region(name='Region 2', slug='region-2'),
Region(name='Region 3', slug='region-3'),
)
for region in regions:
region.save()
sites = (
Site(name='Site... | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def test_name(self):
params = {'name': ['Rack 1', 'Rack 2']}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 2) | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def test_asset_tag(self):
params = {'asset_tag': ['1001', '1002']}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 2) | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def test_width(self):
params = {'width': [RackWidthChoices.WIDTH_19IN, RackWidthChoices.WIDTH_21IN]}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 2) | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def test_desc_units(self):
params = {'desc_units': 'true'}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 1)
params = {'desc_units': 'false'}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 2) | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def test_outer_depth(self):
params = {'outer_depth': [100, 200]}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 2) | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def test_region(self):
regions = Region.objects.all()[:2]
params = {'region_id': [regions[0].pk, regions[1].pk]}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 2)
params = {'region': [regions[0].slug, regions[1].slug]}
self.assertEqual(self.filterset(params, s... | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def test_group(self):
groups = RackGroup.objects.all()[:2]
params = {'group_id': [groups[0].pk, groups[1].pk]}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 2)
params = {'group': [groups[0].slug, groups[1].slug]}
self.assertEqual(self.filterset(params, self.q... | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def test_role(self):
roles = RackRole.objects.all()[:2]
params = {'role_id': [roles[0].pk, roles[1].pk]}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 2)
params = {'role': [roles[0].slug, roles[1].slug]}
self.assertEqual(self.filterset(params, self.queryset).... | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def test_tenant(self):
tenants = Tenant.objects.all()[:2]
params = {'tenant_id': [tenants[0].pk, tenants[1].pk]}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 2)
params = {'tenant': [tenants[0].slug, tenants[1].slug]}
self.assertEqual(self.filterset(params, s... | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def setUpTestData(cls):
sites = (
Site(name='Site 1', slug='site-1'),
Site(name='Site 2', slug='site-2'),
Site(name='Site 3', slug='site-3'),
)
Site.objects.bulk_create(sites)
rack_groups = (
RackGroup(name='Rack Group 1', slug='rack-grou... | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def test_site(self):
sites = Site.objects.all()[:2]
params = {'site_id': [sites[0].pk, sites[1].pk]}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 2)
params = {'site': [sites[0].slug, sites[1].slug]}
self.assertEqual(self.filterset(params, self.queryset).qs.c... | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def test_user(self):
users = User.objects.all()[:2]
params = {'user_id': [users[0].pk, users[1].pk]}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 2)
params = {'user': [users[0].username, users[1].username]}
self.assertEqual(self.filterset(params, self.querys... | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def test_tenant_group(self):
tenant_groups = TenantGroup.objects.all()[:2]
params = {'tenant_group_id': [tenant_groups[0].pk, tenant_groups[1].pk]}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 2)
params = {'tenant_group': [tenant_groups[0].slug, tenant_groups[1].slu... | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def setUpTestData(cls):
manufacturers = (
Manufacturer(name='Manufacturer 1', slug='manufacturer-1', description='A'),
Manufacturer(name='Manufacturer 2', slug='manufacturer-2', description='B'),
Manufacturer(name='Manufacturer 3', slug='manufacturer-3', description='C'),
... | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def test_name(self):
params = {'name': ['Manufacturer 1', 'Manufacturer 2']}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 2) | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def test_description(self):
params = {'description': ['A', 'B']}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 2) | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def setUpTestData(cls):
manufacturers = (
Manufacturer(name='Manufacturer 1', slug='manufacturer-1'),
Manufacturer(name='Manufacturer 2', slug='manufacturer-2'),
Manufacturer(name='Manufacturer 3', slug='manufacturer-3'),
)
Manufacturer.objects.bulk_create(ma... | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def test_model(self):
params = {'model': ['Model 1', 'Model 2']}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 2) | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def test_part_number(self):
params = {'part_number': ['Part Number 1', 'Part Number 2']}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 2) | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def test_is_full_depth(self):
params = {'is_full_depth': 'true'}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 2)
params = {'is_full_depth': 'false'}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 1) | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def test_manufacturer(self):
manufacturers = Manufacturer.objects.all()[:2]
params = {'manufacturer_id': [manufacturers[0].pk, manufacturers[1].pk]}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 2)
params = {'manufacturer': [manufacturers[0].slug, manufacturers[1].sl... | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def test_console_server_ports(self):
params = {'console_server_ports': 'true'}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 2)
params = {'console_server_ports': 'false'}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 1) | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def test_power_outlets(self):
params = {'power_outlets': 'true'}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 2)
params = {'power_outlets': 'false'}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 1) | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def test_pass_through_ports(self):
params = {'pass_through_ports': 'true'}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 2)
params = {'pass_through_ports': 'false'}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 1) | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def setUpTestData(cls):
manufacturer = Manufacturer.objects.create(name='Manufacturer 1', slug='manufacturer-1')
device_types = (
DeviceType(manufacturer=manufacturer, model='Model 1', slug='model-1'),
DeviceType(manufacturer=manufacturer, model='Model 2', slug='model-2'),
... | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def test_name(self):
params = {'name': ['Console Port 1', 'Console Port 2']}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 2) | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def setUpTestData(cls):
manufacturer = Manufacturer.objects.create(name='Manufacturer 1', slug='manufacturer-1')
device_types = (
DeviceType(manufacturer=manufacturer, model='Model 1', slug='model-1'),
DeviceType(manufacturer=manufacturer, model='Model 2', slug='model-2'),
... | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def test_name(self):
params = {'name': ['Console Server Port 1', 'Console Server Port 2']}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 2) | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def setUpTestData(cls):
manufacturer = Manufacturer.objects.create(name='Manufacturer 1', slug='manufacturer-1')
device_types = (
DeviceType(manufacturer=manufacturer, model='Model 1', slug='model-1'),
DeviceType(manufacturer=manufacturer, model='Model 2', slug='model-2'),
... | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def test_name(self):
params = {'name': ['Power Port 1', 'Power Port 2']}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 2) | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def test_maximum_draw(self):
params = {'maximum_draw': [100, 200]}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 2) | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def setUpTestData(cls):
manufacturer = Manufacturer.objects.create(name='Manufacturer 1', slug='manufacturer-1')
device_types = (
DeviceType(manufacturer=manufacturer, model='Model 1', slug='model-1'),
DeviceType(manufacturer=manufacturer, model='Model 2', slug='model-2'),
... | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def test_name(self):
params = {'name': ['Power Outlet 1', 'Power Outlet 2']}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 2) | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def test_feed_leg(self):
# TODO: Support filtering for multiple values
params = {'feed_leg': PowerOutletFeedLegChoices.FEED_LEG_A}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 1) | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def setUpTestData(cls):
manufacturer = Manufacturer.objects.create(name='Manufacturer 1', slug='manufacturer-1')
device_types = (
DeviceType(manufacturer=manufacturer, model='Model 1', slug='model-1'),
DeviceType(manufacturer=manufacturer, model='Model 2', slug='model-2'),
... | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def test_name(self):
params = {'name': ['Interface 1', 'Interface 2']}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 2) | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def test_type(self):
# TODO: Support filtering for multiple values
params = {'type': InterfaceTypeChoices.TYPE_1GE_FIXED}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 1) | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def setUpTestData(cls):
manufacturer = Manufacturer.objects.create(name='Manufacturer 1', slug='manufacturer-1')
device_types = (
DeviceType(manufacturer=manufacturer, model='Model 1', slug='model-1'),
DeviceType(manufacturer=manufacturer, model='Model 2', slug='model-2'),
... | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def test_name(self):
params = {'name': ['Front Port 1', 'Front Port 2']}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 2) | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def test_type(self):
# TODO: Support filtering for multiple values
params = {'type': PortTypeChoices.TYPE_8P8C}
self.assertEqual(self.filterset(params, self.queryset).qs.count(), 1) | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
def setUpTestData(cls):
manufacturer = Manufacturer.objects.create(name='Manufacturer 1', slug='manufacturer-1')
device_types = (
DeviceType(manufacturer=manufacturer, model='Model 1', slug='model-1'),
DeviceType(manufacturer=manufacturer, model='Model 2', slug='model-2'),
... | digitalocean/netbox | [
12158,
2099,
12158,
303,
1456755346
] |
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