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def test_resized_viewbox_no_width_height(self):
'Truncate decimals'
svg = ElementTree.fromstring((XML_HEADER + b'<svg viewBox="-10.23 32.18 75.876 75.956"></svg>'))
result = ElementTree.tostring(svg_util.make_square(svg))
self.assertTrue((b'width="80"' in result))
self.assertTrue((b'height="80"' in result))
self.assertTrue((b'viewBox="-10 32 75 75"' in result)) | -8,967,835,290,666,746,000 | Truncate decimals | peacecorps/peacecorps/tests/test_util_svg.py | test_resized_viewbox_no_width_height | 18F/peacecorps-site | python | def test_resized_viewbox_no_width_height(self):
svg = ElementTree.fromstring((XML_HEADER + b'<svg viewBox="-10.23 32.18 75.876 75.956"></svg>'))
result = ElementTree.tostring(svg_util.make_square(svg))
self.assertTrue((b'width="80"' in result))
self.assertTrue((b'height="80"' in result))
self.assertTrue((b'viewBox="-10 32 75 75"' in result)) |
def GetChromeProxyRequestHeaderValue(self, key):
'Get a specific Chrome-Proxy request header value.\n\n Returns:\n The value for a specific Chrome-Proxy request header value for a\n given key. Returns None if no such key is present.\n '
if ('Chrome-Proxy' not in self.response.request_headers):
return None
chrome_proxy_request_header = self.response.request_headers['Chrome-Proxy']
values = [v.strip() for v in chrome_proxy_request_header.split(',')]
for value in values:
kvp = value.split('=', 1)
if ((len(kvp) == 2) and (kvp[0].strip() == key)):
return kvp[1].strip()
return None | -2,043,771,418,356,114,200 | Get a specific Chrome-Proxy request header value.
Returns:
The value for a specific Chrome-Proxy request header value for a
given key. Returns None if no such key is present. | third_party/webrtc/src/chromium/src/tools/chrome_proxy/common/chrome_proxy_metrics.py | GetChromeProxyRequestHeaderValue | Teamxrtc/webrtc-streaming-node | python | def GetChromeProxyRequestHeaderValue(self, key):
'Get a specific Chrome-Proxy request header value.\n\n Returns:\n The value for a specific Chrome-Proxy request header value for a\n given key. Returns None if no such key is present.\n '
if ('Chrome-Proxy' not in self.response.request_headers):
return None
chrome_proxy_request_header = self.response.request_headers['Chrome-Proxy']
values = [v.strip() for v in chrome_proxy_request_header.split(',')]
for value in values:
kvp = value.split('=', 1)
if ((len(kvp) == 2) and (kvp[0].strip() == key)):
return kvp[1].strip()
return None |
def GetChromeProxyClientType(self):
'Get the client type directive from the Chrome-Proxy request header.\n\n Returns:\n The client type directive from the Chrome-Proxy request header for the\n request that lead to this response. For example, if the request header\n "Chrome-Proxy: c=android" is present, then this method would return\n "android". Returns None if no client type directive is present.\n '
return self.GetChromeProxyRequestHeaderValue('c') | 7,091,982,491,205,581,000 | Get the client type directive from the Chrome-Proxy request header.
Returns:
The client type directive from the Chrome-Proxy request header for the
request that lead to this response. For example, if the request header
"Chrome-Proxy: c=android" is present, then this method would return
"android". Returns None if no client type directive is present. | third_party/webrtc/src/chromium/src/tools/chrome_proxy/common/chrome_proxy_metrics.py | GetChromeProxyClientType | Teamxrtc/webrtc-streaming-node | python | def GetChromeProxyClientType(self):
'Get the client type directive from the Chrome-Proxy request header.\n\n Returns:\n The client type directive from the Chrome-Proxy request header for the\n request that lead to this response. For example, if the request header\n "Chrome-Proxy: c=android" is present, then this method would return\n "android". Returns None if no client type directive is present.\n '
return self.GetChromeProxyRequestHeaderValue('c') |
def matched_sample_distribution(floats_arr: np.array, samples_no: int, granularity: int=100, logmode: bool=False) -> np.array:
'\n Tries to guess a distribution of floats and sample from it.\n uses np.histogram with the number of bins equal to the granularity parameter. For each\n sample, selects which bin to sample and then picks from the bin a float according to a\n uniform distribution. if logmode is enabled, histogram will be in the log-space, as well as\n the sampling.\n\n :param floats_arr: array of floats for which to match the distribution\n :param samples_no: number of random samples to retrieve\n :param granularity: granularity at which to operate\n :param logmode: if sample in log-space\n :return: samples drawn from the empirically matched distribution\n '
if logmode:
floats_arr = np.log(floats_arr)
(hist, bin_edges) = np.histogram(floats_arr, bins=granularity, density=True)
pad = np.arange(granularity)
locations = np.choice(pad, samples_no, p=hist)
samples = []
for i in locations:
samples.append(np.random.uniform(bin_edges[i], bin_edges[(i + 1)]))
if logmode:
return np.exp(samples)
else:
return samples | 7,744,731,314,882,504,000 | Tries to guess a distribution of floats and sample from it.
uses np.histogram with the number of bins equal to the granularity parameter. For each
sample, selects which bin to sample and then picks from the bin a float according to a
uniform distribution. if logmode is enabled, histogram will be in the log-space, as well as
the sampling.
:param floats_arr: array of floats for which to match the distribution
:param samples_no: number of random samples to retrieve
:param granularity: granularity at which to operate
:param logmode: if sample in log-space
:return: samples drawn from the empirically matched distribution | bioflow/algorithms_bank/sampling_policies.py | matched_sample_distribution | chiffa/BioFlow | python | def matched_sample_distribution(floats_arr: np.array, samples_no: int, granularity: int=100, logmode: bool=False) -> np.array:
'\n Tries to guess a distribution of floats and sample from it.\n uses np.histogram with the number of bins equal to the granularity parameter. For each\n sample, selects which bin to sample and then picks from the bin a float according to a\n uniform distribution. if logmode is enabled, histogram will be in the log-space, as well as\n the sampling.\n\n :param floats_arr: array of floats for which to match the distribution\n :param samples_no: number of random samples to retrieve\n :param granularity: granularity at which to operate\n :param logmode: if sample in log-space\n :return: samples drawn from the empirically matched distribution\n '
if logmode:
floats_arr = np.log(floats_arr)
(hist, bin_edges) = np.histogram(floats_arr, bins=granularity, density=True)
pad = np.arange(granularity)
locations = np.choice(pad, samples_no, p=hist)
samples = []
for i in locations:
samples.append(np.random.uniform(bin_edges[i], bin_edges[(i + 1)]))
if logmode:
return np.exp(samples)
else:
return samples |
def _reduce_distribution(floats_arr: np.array):
'\n Basically gets a distribution in the [0, 1] in 100 bins, rounds to the nearest 0.01. Used for\n hashing and distribution matching\n\n :param floats_arr: floats for which to calculate the rounded distribution\n :return: rounded distribution\n '
normalized_arr = (floats_arr / np.max(floats_arr))
bins = np.linspace(0, 1.001, 101)
(hist, bin_edges) = np.histogram(normalized_arr, bins=bins, density=True)
rounded_hist = np.array((hist * 100)).astype(np.int)
return rounded_hist | -7,937,689,576,270,980,000 | Basically gets a distribution in the [0, 1] in 100 bins, rounds to the nearest 0.01. Used for
hashing and distribution matching
:param floats_arr: floats for which to calculate the rounded distribution
:return: rounded distribution | bioflow/algorithms_bank/sampling_policies.py | _reduce_distribution | chiffa/BioFlow | python | def _reduce_distribution(floats_arr: np.array):
'\n Basically gets a distribution in the [0, 1] in 100 bins, rounds to the nearest 0.01. Used for\n hashing and distribution matching\n\n :param floats_arr: floats for which to calculate the rounded distribution\n :return: rounded distribution\n '
normalized_arr = (floats_arr / np.max(floats_arr))
bins = np.linspace(0, 1.001, 101)
(hist, bin_edges) = np.histogram(normalized_arr, bins=bins, density=True)
rounded_hist = np.array((hist * 100)).astype(np.int)
return rounded_hist |
def _characterize_set(sample: Union[(List[int], List[Tuple[(int, float)]])]):
'\n None-robust helper function to characterize a sample set by its length, nature of items in\n teh sample and eventual distribution of weights within the sample.\n\n :param sample: sample to characterize\n :return: set length (0 if None), 1 if items are ids, 2 if ids and weights (0 if\n None), rounded distribution ([] if None or items are ids)\n '
if (sample is None):
return (0, 0, [])
if (len(sample) == 1):
if _is_int(sample[0]):
return (1, 1, [])
else:
return (1, 2, [])
if _is_int(sample[0]):
rounded_hist = ([1] * 100)
rounded_hist = np.array(rounded_hist).astype(np.int)
return (len(sample), 1, rounded_hist.tolist())
else:
rounded_hist = _reduce_distribution(np.array(sample).astype(np.float)[:, 1])
return (len(sample), 2, rounded_hist.tolist()) | 5,761,955,160,226,254,000 | None-robust helper function to characterize a sample set by its length, nature of items in
teh sample and eventual distribution of weights within the sample.
:param sample: sample to characterize
:return: set length (0 if None), 1 if items are ids, 2 if ids and weights (0 if
None), rounded distribution ([] if None or items are ids) | bioflow/algorithms_bank/sampling_policies.py | _characterize_set | chiffa/BioFlow | python | def _characterize_set(sample: Union[(List[int], List[Tuple[(int, float)]])]):
'\n None-robust helper function to characterize a sample set by its length, nature of items in\n teh sample and eventual distribution of weights within the sample.\n\n :param sample: sample to characterize\n :return: set length (0 if None), 1 if items are ids, 2 if ids and weights (0 if\n None), rounded distribution ([] if None or items are ids)\n '
if (sample is None):
return (0, 0, [])
if (len(sample) == 1):
if _is_int(sample[0]):
return (1, 1, [])
else:
return (1, 2, [])
if _is_int(sample[0]):
rounded_hist = ([1] * 100)
rounded_hist = np.array(rounded_hist).astype(np.int)
return (len(sample), 1, rounded_hist.tolist())
else:
rounded_hist = _reduce_distribution(np.array(sample).astype(np.float)[:, 1])
return (len(sample), 2, rounded_hist.tolist()) |
def characterize_flow_parameters(sample: Union[(List[int], List[Tuple[(int, float)]])], secondary_sample: Union[(List[int], List[Tuple[(int, float)]], None)], sparse_rounds: int):
'\n Characterizes the primary and secondary sets and computes their hash, that can be used ot\n match similar samples for random sampling.\n\n :param sample: primary set\n :param secondary_sample: secondary set\n :param sparse_rounds: if sparse rounds are to be performed\n :return: first set length, shape, hist, second set length, shape, hist, sparse rounds, hash\n '
(prim_len, prim_shape, prim_hist) = _characterize_set(sample)
(sec_len, sec_shape, sec_hist) = _characterize_set(secondary_sample)
_hash = hashlib.md5(json.dumps([prim_len, prim_shape, prim_hist, sec_len, sec_shape, sec_hist, sparse_rounds]).encode('utf-8')).hexdigest()
log.debug(('hashed a flow parameters from:\n%d/%d/%s; \n%d/%d/%s; \n%d \nto %s' % (prim_len, prim_shape, prim_hist, sec_len, sec_shape, sec_hist, sparse_rounds, _hash)))
return (prim_len, prim_shape, prim_hist, sec_len, sec_shape, sec_hist, sparse_rounds, _hash) | 7,264,387,114,084,906,000 | Characterizes the primary and secondary sets and computes their hash, that can be used ot
match similar samples for random sampling.
:param sample: primary set
:param secondary_sample: secondary set
:param sparse_rounds: if sparse rounds are to be performed
:return: first set length, shape, hist, second set length, shape, hist, sparse rounds, hash | bioflow/algorithms_bank/sampling_policies.py | characterize_flow_parameters | chiffa/BioFlow | python | def characterize_flow_parameters(sample: Union[(List[int], List[Tuple[(int, float)]])], secondary_sample: Union[(List[int], List[Tuple[(int, float)]], None)], sparse_rounds: int):
'\n Characterizes the primary and secondary sets and computes their hash, that can be used ot\n match similar samples for random sampling.\n\n :param sample: primary set\n :param secondary_sample: secondary set\n :param sparse_rounds: if sparse rounds are to be performed\n :return: first set length, shape, hist, second set length, shape, hist, sparse rounds, hash\n '
(prim_len, prim_shape, prim_hist) = _characterize_set(sample)
(sec_len, sec_shape, sec_hist) = _characterize_set(secondary_sample)
_hash = hashlib.md5(json.dumps([prim_len, prim_shape, prim_hist, sec_len, sec_shape, sec_hist, sparse_rounds]).encode('utf-8')).hexdigest()
log.debug(('hashed a flow parameters from:\n%d/%d/%s; \n%d/%d/%s; \n%d \nto %s' % (prim_len, prim_shape, prim_hist, sec_len, sec_shape, sec_hist, sparse_rounds, _hash)))
return (prim_len, prim_shape, prim_hist, sec_len, sec_shape, sec_hist, sparse_rounds, _hash) |
def _sample_floats(floats, float_sampling_method='exact', matched_distro_precision: int=100):
'\n A wrapper methods to sample a float distribution according to a method\n\n :param floats:\n :param float_sampling_method: exact (permutation of weights) | distro (trying to match the\n empirical distribution) | logdistro (trying to match the empirical distribution in the log\n space)\n :param matched_distro_precision: how closely to try to match the distribution (granularity\n parameter pass-through to the matched_sample_distribution)\n :return: sample of floats\n '
if (float_sampling_method == 'exact'):
ret_floats = floats.copy()
np.random.shuffle(ret_floats)
return ret_floats
if (float_sampling_method == 'distro'):
return matched_sample_distribution(floats, len(floats), granularity=matched_distro_precision)
if (float_sampling_method == 'logdistro'):
return matched_sample_distribution(floats, len(floats), granularity=matched_distro_precision, logmode=True) | 47,125,547,739,960,570 | A wrapper methods to sample a float distribution according to a method
:param floats:
:param float_sampling_method: exact (permutation of weights) | distro (trying to match the
empirical distribution) | logdistro (trying to match the empirical distribution in the log
space)
:param matched_distro_precision: how closely to try to match the distribution (granularity
parameter pass-through to the matched_sample_distribution)
:return: sample of floats | bioflow/algorithms_bank/sampling_policies.py | _sample_floats | chiffa/BioFlow | python | def _sample_floats(floats, float_sampling_method='exact', matched_distro_precision: int=100):
'\n A wrapper methods to sample a float distribution according to a method\n\n :param floats:\n :param float_sampling_method: exact (permutation of weights) | distro (trying to match the\n empirical distribution) | logdistro (trying to match the empirical distribution in the log\n space)\n :param matched_distro_precision: how closely to try to match the distribution (granularity\n parameter pass-through to the matched_sample_distribution)\n :return: sample of floats\n '
if (float_sampling_method == 'exact'):
ret_floats = floats.copy()
np.random.shuffle(ret_floats)
return ret_floats
if (float_sampling_method == 'distro'):
return matched_sample_distribution(floats, len(floats), granularity=matched_distro_precision)
if (float_sampling_method == 'logdistro'):
return matched_sample_distribution(floats, len(floats), granularity=matched_distro_precision, logmode=True) |
def matched_sampling(sample, secondary_sample, background, samples, float_sampling_method='exact'):
'\n The general random sampling strategy that sample sets of the same size and shape as primary\n and secondary sample set and, if they are weighted, try to match the random sample weights\n according to the\n\n\n :param sample: primary sample set\n :param secondary_sample: secondary sample_set\n :param background: background of ids (and potentially weights) from which to sample\n :param samples: random samples wanted\n :param sampling_mode: exact/distro/logdistro. the sampling parametrization method ingesting\n all the parameters in a single string argument in the general case, here, a pass- through\n parameter for the _sample_floats function if samples are weighted and the distribution of\n weights is being matched.\n :return:\n '
if _is_int(background[0]):
background_ids = np.array(background)
background_whg = np.ones_like(background_ids).astype(np.float)
else:
background_ids = np.array(background)[:, 0]
background_whg = np.array(background)[:, 1]
log.debug(('debug sum %s, type: %s, all:%s' % (np.sum(background_whg), type(background_whg), background_whg)))
background_whg /= np.sum(background_whg)
if (secondary_sample is None):
if _is_int(sample[0]):
for i in range(0, samples):
selected = np.random.choice(background_ids, len(sample), p=background_whg, replace=False)
(yield (i, selected, None))
else:
for i in range(0, samples):
id_loads = np.random.choice(background_ids, len(sample), p=background_whg, replace=False)
float_part = _sample_floats(np.array(sample)[:, 1], float_sampling_method)
ids_and_floats = [(_id, _float) for (_id, _float) in zip(id_loads, float_part)]
(yield (i, ids_and_floats, None))
elif _is_int(sample[0]):
for i in range(0, samples):
selected = np.random.choice(background_ids, (len(sample) + len(secondary_sample)), p=background_whg, replace=False)
np.random.shuffle(selected)
(yield (i, selected[:len(sample)], selected[(- len(secondary_sample)):]))
else:
for i in range(0, samples):
selected = np.random.choice(background_ids, (len(sample) + len(secondary_sample)), p=background_whg, replace=False)
np.random.shuffle(selected)
id_loads = selected[:len(sample)]
float_part = _sample_floats(np.array(sample)[:, 1], float_sampling_method)
ids_and_floats = [(_id, _float) for (_id, _float) in zip(id_loads, float_part)]
sec_id_loads = selected[(- len(secondary_sample)):]
sec_float_part = _sample_floats(np.array(secondary_sample)[:, 1], float_sampling_method)
sec_ids_and_floats = [(_id, _float) for (_id, _float) in zip(sec_id_loads, sec_float_part)]
(yield (i, ids_and_floats, sec_ids_and_floats)) | 703,084,849,194,356,000 | The general random sampling strategy that sample sets of the same size and shape as primary
and secondary sample set and, if they are weighted, try to match the random sample weights
according to the
:param sample: primary sample set
:param secondary_sample: secondary sample_set
:param background: background of ids (and potentially weights) from which to sample
:param samples: random samples wanted
:param sampling_mode: exact/distro/logdistro. the sampling parametrization method ingesting
all the parameters in a single string argument in the general case, here, a pass- through
parameter for the _sample_floats function if samples are weighted and the distribution of
weights is being matched.
:return: | bioflow/algorithms_bank/sampling_policies.py | matched_sampling | chiffa/BioFlow | python | def matched_sampling(sample, secondary_sample, background, samples, float_sampling_method='exact'):
'\n The general random sampling strategy that sample sets of the same size and shape as primary\n and secondary sample set and, if they are weighted, try to match the random sample weights\n according to the\n\n\n :param sample: primary sample set\n :param secondary_sample: secondary sample_set\n :param background: background of ids (and potentially weights) from which to sample\n :param samples: random samples wanted\n :param sampling_mode: exact/distro/logdistro. the sampling parametrization method ingesting\n all the parameters in a single string argument in the general case, here, a pass- through\n parameter for the _sample_floats function if samples are weighted and the distribution of\n weights is being matched.\n :return:\n '
if _is_int(background[0]):
background_ids = np.array(background)
background_whg = np.ones_like(background_ids).astype(np.float)
else:
background_ids = np.array(background)[:, 0]
background_whg = np.array(background)[:, 1]
log.debug(('debug sum %s, type: %s, all:%s' % (np.sum(background_whg), type(background_whg), background_whg)))
background_whg /= np.sum(background_whg)
if (secondary_sample is None):
if _is_int(sample[0]):
for i in range(0, samples):
selected = np.random.choice(background_ids, len(sample), p=background_whg, replace=False)
(yield (i, selected, None))
else:
for i in range(0, samples):
id_loads = np.random.choice(background_ids, len(sample), p=background_whg, replace=False)
float_part = _sample_floats(np.array(sample)[:, 1], float_sampling_method)
ids_and_floats = [(_id, _float) for (_id, _float) in zip(id_loads, float_part)]
(yield (i, ids_and_floats, None))
elif _is_int(sample[0]):
for i in range(0, samples):
selected = np.random.choice(background_ids, (len(sample) + len(secondary_sample)), p=background_whg, replace=False)
np.random.shuffle(selected)
(yield (i, selected[:len(sample)], selected[(- len(secondary_sample)):]))
else:
for i in range(0, samples):
selected = np.random.choice(background_ids, (len(sample) + len(secondary_sample)), p=background_whg, replace=False)
np.random.shuffle(selected)
id_loads = selected[:len(sample)]
float_part = _sample_floats(np.array(sample)[:, 1], float_sampling_method)
ids_and_floats = [(_id, _float) for (_id, _float) in zip(id_loads, float_part)]
sec_id_loads = selected[(- len(secondary_sample)):]
sec_float_part = _sample_floats(np.array(secondary_sample)[:, 1], float_sampling_method)
sec_ids_and_floats = [(_id, _float) for (_id, _float) in zip(sec_id_loads, sec_float_part)]
(yield (i, ids_and_floats, sec_ids_and_floats)) |
def __init__(__self__, *, resource_group_name: pulumi.Input[str], id: Optional[pulumi.Input[str]]=None, location: Optional[pulumi.Input[str]]=None, manual_private_link_service_connections: Optional[pulumi.Input[Sequence[pulumi.Input['PrivateLinkServiceConnectionArgs']]]]=None, private_endpoint_name: Optional[pulumi.Input[str]]=None, private_link_service_connections: Optional[pulumi.Input[Sequence[pulumi.Input['PrivateLinkServiceConnectionArgs']]]]=None, subnet: Optional[pulumi.Input['SubnetArgs']]=None, tags: Optional[pulumi.Input[Mapping[(str, pulumi.Input[str])]]]=None):
"\n The set of arguments for constructing a PrivateEndpoint resource.\n :param pulumi.Input[str] resource_group_name: The name of the resource group.\n :param pulumi.Input[str] id: Resource ID.\n :param pulumi.Input[str] location: Resource location.\n :param pulumi.Input[Sequence[pulumi.Input['PrivateLinkServiceConnectionArgs']]] manual_private_link_service_connections: A grouping of information about the connection to the remote resource. Used when the network admin does not have access to approve connections to the remote resource.\n :param pulumi.Input[str] private_endpoint_name: The name of the private endpoint.\n :param pulumi.Input[Sequence[pulumi.Input['PrivateLinkServiceConnectionArgs']]] private_link_service_connections: A grouping of information about the connection to the remote resource.\n :param pulumi.Input['SubnetArgs'] subnet: The ID of the subnet from which the private IP will be allocated.\n :param pulumi.Input[Mapping[str, pulumi.Input[str]]] tags: Resource tags.\n "
pulumi.set(__self__, 'resource_group_name', resource_group_name)
if (id is not None):
pulumi.set(__self__, 'id', id)
if (location is not None):
pulumi.set(__self__, 'location', location)
if (manual_private_link_service_connections is not None):
pulumi.set(__self__, 'manual_private_link_service_connections', manual_private_link_service_connections)
if (private_endpoint_name is not None):
pulumi.set(__self__, 'private_endpoint_name', private_endpoint_name)
if (private_link_service_connections is not None):
pulumi.set(__self__, 'private_link_service_connections', private_link_service_connections)
if (subnet is not None):
pulumi.set(__self__, 'subnet', subnet)
if (tags is not None):
pulumi.set(__self__, 'tags', tags) | 5,233,328,910,972,875,000 | The set of arguments for constructing a PrivateEndpoint resource.
:param pulumi.Input[str] resource_group_name: The name of the resource group.
:param pulumi.Input[str] id: Resource ID.
:param pulumi.Input[str] location: Resource location.
:param pulumi.Input[Sequence[pulumi.Input['PrivateLinkServiceConnectionArgs']]] manual_private_link_service_connections: A grouping of information about the connection to the remote resource. Used when the network admin does not have access to approve connections to the remote resource.
:param pulumi.Input[str] private_endpoint_name: The name of the private endpoint.
:param pulumi.Input[Sequence[pulumi.Input['PrivateLinkServiceConnectionArgs']]] private_link_service_connections: A grouping of information about the connection to the remote resource.
:param pulumi.Input['SubnetArgs'] subnet: The ID of the subnet from which the private IP will be allocated.
:param pulumi.Input[Mapping[str, pulumi.Input[str]]] tags: Resource tags. | sdk/python/pulumi_azure_native/network/v20190901/private_endpoint.py | __init__ | polivbr/pulumi-azure-native | python | def __init__(__self__, *, resource_group_name: pulumi.Input[str], id: Optional[pulumi.Input[str]]=None, location: Optional[pulumi.Input[str]]=None, manual_private_link_service_connections: Optional[pulumi.Input[Sequence[pulumi.Input['PrivateLinkServiceConnectionArgs']]]]=None, private_endpoint_name: Optional[pulumi.Input[str]]=None, private_link_service_connections: Optional[pulumi.Input[Sequence[pulumi.Input['PrivateLinkServiceConnectionArgs']]]]=None, subnet: Optional[pulumi.Input['SubnetArgs']]=None, tags: Optional[pulumi.Input[Mapping[(str, pulumi.Input[str])]]]=None):
"\n The set of arguments for constructing a PrivateEndpoint resource.\n :param pulumi.Input[str] resource_group_name: The name of the resource group.\n :param pulumi.Input[str] id: Resource ID.\n :param pulumi.Input[str] location: Resource location.\n :param pulumi.Input[Sequence[pulumi.Input['PrivateLinkServiceConnectionArgs']]] manual_private_link_service_connections: A grouping of information about the connection to the remote resource. Used when the network admin does not have access to approve connections to the remote resource.\n :param pulumi.Input[str] private_endpoint_name: The name of the private endpoint.\n :param pulumi.Input[Sequence[pulumi.Input['PrivateLinkServiceConnectionArgs']]] private_link_service_connections: A grouping of information about the connection to the remote resource.\n :param pulumi.Input['SubnetArgs'] subnet: The ID of the subnet from which the private IP will be allocated.\n :param pulumi.Input[Mapping[str, pulumi.Input[str]]] tags: Resource tags.\n "
pulumi.set(__self__, 'resource_group_name', resource_group_name)
if (id is not None):
pulumi.set(__self__, 'id', id)
if (location is not None):
pulumi.set(__self__, 'location', location)
if (manual_private_link_service_connections is not None):
pulumi.set(__self__, 'manual_private_link_service_connections', manual_private_link_service_connections)
if (private_endpoint_name is not None):
pulumi.set(__self__, 'private_endpoint_name', private_endpoint_name)
if (private_link_service_connections is not None):
pulumi.set(__self__, 'private_link_service_connections', private_link_service_connections)
if (subnet is not None):
pulumi.set(__self__, 'subnet', subnet)
if (tags is not None):
pulumi.set(__self__, 'tags', tags) |
@property
@pulumi.getter(name='resourceGroupName')
def resource_group_name(self) -> pulumi.Input[str]:
'\n The name of the resource group.\n '
return pulumi.get(self, 'resource_group_name') | 5,898,586,357,340,442,000 | The name of the resource group. | sdk/python/pulumi_azure_native/network/v20190901/private_endpoint.py | resource_group_name | polivbr/pulumi-azure-native | python | @property
@pulumi.getter(name='resourceGroupName')
def resource_group_name(self) -> pulumi.Input[str]:
'\n \n '
return pulumi.get(self, 'resource_group_name') |
@property
@pulumi.getter
def id(self) -> Optional[pulumi.Input[str]]:
'\n Resource ID.\n '
return pulumi.get(self, 'id') | 4,003,078,074,025,280,500 | Resource ID. | sdk/python/pulumi_azure_native/network/v20190901/private_endpoint.py | id | polivbr/pulumi-azure-native | python | @property
@pulumi.getter
def id(self) -> Optional[pulumi.Input[str]]:
'\n \n '
return pulumi.get(self, 'id') |
@property
@pulumi.getter
def location(self) -> Optional[pulumi.Input[str]]:
'\n Resource location.\n '
return pulumi.get(self, 'location') | 5,685,883,695,381,965,000 | Resource location. | sdk/python/pulumi_azure_native/network/v20190901/private_endpoint.py | location | polivbr/pulumi-azure-native | python | @property
@pulumi.getter
def location(self) -> Optional[pulumi.Input[str]]:
'\n \n '
return pulumi.get(self, 'location') |
@property
@pulumi.getter(name='manualPrivateLinkServiceConnections')
def manual_private_link_service_connections(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['PrivateLinkServiceConnectionArgs']]]]:
'\n A grouping of information about the connection to the remote resource. Used when the network admin does not have access to approve connections to the remote resource.\n '
return pulumi.get(self, 'manual_private_link_service_connections') | -6,351,649,816,882,946,000 | A grouping of information about the connection to the remote resource. Used when the network admin does not have access to approve connections to the remote resource. | sdk/python/pulumi_azure_native/network/v20190901/private_endpoint.py | manual_private_link_service_connections | polivbr/pulumi-azure-native | python | @property
@pulumi.getter(name='manualPrivateLinkServiceConnections')
def manual_private_link_service_connections(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['PrivateLinkServiceConnectionArgs']]]]:
'\n \n '
return pulumi.get(self, 'manual_private_link_service_connections') |
@property
@pulumi.getter(name='privateEndpointName')
def private_endpoint_name(self) -> Optional[pulumi.Input[str]]:
'\n The name of the private endpoint.\n '
return pulumi.get(self, 'private_endpoint_name') | -8,703,745,273,820,877,000 | The name of the private endpoint. | sdk/python/pulumi_azure_native/network/v20190901/private_endpoint.py | private_endpoint_name | polivbr/pulumi-azure-native | python | @property
@pulumi.getter(name='privateEndpointName')
def private_endpoint_name(self) -> Optional[pulumi.Input[str]]:
'\n \n '
return pulumi.get(self, 'private_endpoint_name') |
@property
@pulumi.getter(name='privateLinkServiceConnections')
def private_link_service_connections(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['PrivateLinkServiceConnectionArgs']]]]:
'\n A grouping of information about the connection to the remote resource.\n '
return pulumi.get(self, 'private_link_service_connections') | -5,282,137,409,068,493,000 | A grouping of information about the connection to the remote resource. | sdk/python/pulumi_azure_native/network/v20190901/private_endpoint.py | private_link_service_connections | polivbr/pulumi-azure-native | python | @property
@pulumi.getter(name='privateLinkServiceConnections')
def private_link_service_connections(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['PrivateLinkServiceConnectionArgs']]]]:
'\n \n '
return pulumi.get(self, 'private_link_service_connections') |
@property
@pulumi.getter
def subnet(self) -> Optional[pulumi.Input['SubnetArgs']]:
'\n The ID of the subnet from which the private IP will be allocated.\n '
return pulumi.get(self, 'subnet') | -2,245,546,924,618,331,100 | The ID of the subnet from which the private IP will be allocated. | sdk/python/pulumi_azure_native/network/v20190901/private_endpoint.py | subnet | polivbr/pulumi-azure-native | python | @property
@pulumi.getter
def subnet(self) -> Optional[pulumi.Input['SubnetArgs']]:
'\n \n '
return pulumi.get(self, 'subnet') |
@property
@pulumi.getter
def tags(self) -> Optional[pulumi.Input[Mapping[(str, pulumi.Input[str])]]]:
'\n Resource tags.\n '
return pulumi.get(self, 'tags') | -2,047,115,851,061,118,500 | Resource tags. | sdk/python/pulumi_azure_native/network/v20190901/private_endpoint.py | tags | polivbr/pulumi-azure-native | python | @property
@pulumi.getter
def tags(self) -> Optional[pulumi.Input[Mapping[(str, pulumi.Input[str])]]]:
'\n \n '
return pulumi.get(self, 'tags') |
@overload
def __init__(__self__, resource_name: str, opts: Optional[pulumi.ResourceOptions]=None, id: Optional[pulumi.Input[str]]=None, location: Optional[pulumi.Input[str]]=None, manual_private_link_service_connections: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['PrivateLinkServiceConnectionArgs']]]]]=None, private_endpoint_name: Optional[pulumi.Input[str]]=None, private_link_service_connections: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['PrivateLinkServiceConnectionArgs']]]]]=None, resource_group_name: Optional[pulumi.Input[str]]=None, subnet: Optional[pulumi.Input[pulumi.InputType['SubnetArgs']]]=None, tags: Optional[pulumi.Input[Mapping[(str, pulumi.Input[str])]]]=None, __props__=None):
"\n Private endpoint resource.\n\n :param str resource_name: The name of the resource.\n :param pulumi.ResourceOptions opts: Options for the resource.\n :param pulumi.Input[str] id: Resource ID.\n :param pulumi.Input[str] location: Resource location.\n :param pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['PrivateLinkServiceConnectionArgs']]]] manual_private_link_service_connections: A grouping of information about the connection to the remote resource. Used when the network admin does not have access to approve connections to the remote resource.\n :param pulumi.Input[str] private_endpoint_name: The name of the private endpoint.\n :param pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['PrivateLinkServiceConnectionArgs']]]] private_link_service_connections: A grouping of information about the connection to the remote resource.\n :param pulumi.Input[str] resource_group_name: The name of the resource group.\n :param pulumi.Input[pulumi.InputType['SubnetArgs']] subnet: The ID of the subnet from which the private IP will be allocated.\n :param pulumi.Input[Mapping[str, pulumi.Input[str]]] tags: Resource tags.\n "
... | -4,391,438,611,083,021,300 | Private endpoint resource.
:param str resource_name: The name of the resource.
:param pulumi.ResourceOptions opts: Options for the resource.
:param pulumi.Input[str] id: Resource ID.
:param pulumi.Input[str] location: Resource location.
:param pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['PrivateLinkServiceConnectionArgs']]]] manual_private_link_service_connections: A grouping of information about the connection to the remote resource. Used when the network admin does not have access to approve connections to the remote resource.
:param pulumi.Input[str] private_endpoint_name: The name of the private endpoint.
:param pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['PrivateLinkServiceConnectionArgs']]]] private_link_service_connections: A grouping of information about the connection to the remote resource.
:param pulumi.Input[str] resource_group_name: The name of the resource group.
:param pulumi.Input[pulumi.InputType['SubnetArgs']] subnet: The ID of the subnet from which the private IP will be allocated.
:param pulumi.Input[Mapping[str, pulumi.Input[str]]] tags: Resource tags. | sdk/python/pulumi_azure_native/network/v20190901/private_endpoint.py | __init__ | polivbr/pulumi-azure-native | python | @overload
def __init__(__self__, resource_name: str, opts: Optional[pulumi.ResourceOptions]=None, id: Optional[pulumi.Input[str]]=None, location: Optional[pulumi.Input[str]]=None, manual_private_link_service_connections: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['PrivateLinkServiceConnectionArgs']]]]]=None, private_endpoint_name: Optional[pulumi.Input[str]]=None, private_link_service_connections: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['PrivateLinkServiceConnectionArgs']]]]]=None, resource_group_name: Optional[pulumi.Input[str]]=None, subnet: Optional[pulumi.Input[pulumi.InputType['SubnetArgs']]]=None, tags: Optional[pulumi.Input[Mapping[(str, pulumi.Input[str])]]]=None, __props__=None):
"\n Private endpoint resource.\n\n :param str resource_name: The name of the resource.\n :param pulumi.ResourceOptions opts: Options for the resource.\n :param pulumi.Input[str] id: Resource ID.\n :param pulumi.Input[str] location: Resource location.\n :param pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['PrivateLinkServiceConnectionArgs']]]] manual_private_link_service_connections: A grouping of information about the connection to the remote resource. Used when the network admin does not have access to approve connections to the remote resource.\n :param pulumi.Input[str] private_endpoint_name: The name of the private endpoint.\n :param pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['PrivateLinkServiceConnectionArgs']]]] private_link_service_connections: A grouping of information about the connection to the remote resource.\n :param pulumi.Input[str] resource_group_name: The name of the resource group.\n :param pulumi.Input[pulumi.InputType['SubnetArgs']] subnet: The ID of the subnet from which the private IP will be allocated.\n :param pulumi.Input[Mapping[str, pulumi.Input[str]]] tags: Resource tags.\n "
... |
@overload
def __init__(__self__, resource_name: str, args: PrivateEndpointArgs, opts: Optional[pulumi.ResourceOptions]=None):
"\n Private endpoint resource.\n\n :param str resource_name: The name of the resource.\n :param PrivateEndpointArgs args: The arguments to use to populate this resource's properties.\n :param pulumi.ResourceOptions opts: Options for the resource.\n "
... | 5,082,290,568,587,639,000 | Private endpoint resource.
:param str resource_name: The name of the resource.
:param PrivateEndpointArgs args: The arguments to use to populate this resource's properties.
:param pulumi.ResourceOptions opts: Options for the resource. | sdk/python/pulumi_azure_native/network/v20190901/private_endpoint.py | __init__ | polivbr/pulumi-azure-native | python | @overload
def __init__(__self__, resource_name: str, args: PrivateEndpointArgs, opts: Optional[pulumi.ResourceOptions]=None):
"\n Private endpoint resource.\n\n :param str resource_name: The name of the resource.\n :param PrivateEndpointArgs args: The arguments to use to populate this resource's properties.\n :param pulumi.ResourceOptions opts: Options for the resource.\n "
... |
@staticmethod
def get(resource_name: str, id: pulumi.Input[str], opts: Optional[pulumi.ResourceOptions]=None) -> 'PrivateEndpoint':
"\n Get an existing PrivateEndpoint resource's state with the given name, id, and optional extra\n properties used to qualify the lookup.\n\n :param str resource_name: The unique name of the resulting resource.\n :param pulumi.Input[str] id: The unique provider ID of the resource to lookup.\n :param pulumi.ResourceOptions opts: Options for the resource.\n "
opts = pulumi.ResourceOptions.merge(opts, pulumi.ResourceOptions(id=id))
__props__ = PrivateEndpointArgs.__new__(PrivateEndpointArgs)
__props__.__dict__['etag'] = None
__props__.__dict__['location'] = None
__props__.__dict__['manual_private_link_service_connections'] = None
__props__.__dict__['name'] = None
__props__.__dict__['network_interfaces'] = None
__props__.__dict__['private_link_service_connections'] = None
__props__.__dict__['provisioning_state'] = None
__props__.__dict__['subnet'] = None
__props__.__dict__['tags'] = None
__props__.__dict__['type'] = None
return PrivateEndpoint(resource_name, opts=opts, __props__=__props__) | 3,226,211,340,263,033,000 | Get an existing PrivateEndpoint resource's state with the given name, id, and optional extra
properties used to qualify the lookup.
:param str resource_name: The unique name of the resulting resource.
:param pulumi.Input[str] id: The unique provider ID of the resource to lookup.
:param pulumi.ResourceOptions opts: Options for the resource. | sdk/python/pulumi_azure_native/network/v20190901/private_endpoint.py | get | polivbr/pulumi-azure-native | python | @staticmethod
def get(resource_name: str, id: pulumi.Input[str], opts: Optional[pulumi.ResourceOptions]=None) -> 'PrivateEndpoint':
"\n Get an existing PrivateEndpoint resource's state with the given name, id, and optional extra\n properties used to qualify the lookup.\n\n :param str resource_name: The unique name of the resulting resource.\n :param pulumi.Input[str] id: The unique provider ID of the resource to lookup.\n :param pulumi.ResourceOptions opts: Options for the resource.\n "
opts = pulumi.ResourceOptions.merge(opts, pulumi.ResourceOptions(id=id))
__props__ = PrivateEndpointArgs.__new__(PrivateEndpointArgs)
__props__.__dict__['etag'] = None
__props__.__dict__['location'] = None
__props__.__dict__['manual_private_link_service_connections'] = None
__props__.__dict__['name'] = None
__props__.__dict__['network_interfaces'] = None
__props__.__dict__['private_link_service_connections'] = None
__props__.__dict__['provisioning_state'] = None
__props__.__dict__['subnet'] = None
__props__.__dict__['tags'] = None
__props__.__dict__['type'] = None
return PrivateEndpoint(resource_name, opts=opts, __props__=__props__) |
@property
@pulumi.getter
def etag(self) -> pulumi.Output[str]:
'\n A unique read-only string that changes whenever the resource is updated.\n '
return pulumi.get(self, 'etag') | 5,960,741,373,667,297,000 | A unique read-only string that changes whenever the resource is updated. | sdk/python/pulumi_azure_native/network/v20190901/private_endpoint.py | etag | polivbr/pulumi-azure-native | python | @property
@pulumi.getter
def etag(self) -> pulumi.Output[str]:
'\n \n '
return pulumi.get(self, 'etag') |
@property
@pulumi.getter
def location(self) -> pulumi.Output[Optional[str]]:
'\n Resource location.\n '
return pulumi.get(self, 'location') | -6,585,394,763,848,456,000 | Resource location. | sdk/python/pulumi_azure_native/network/v20190901/private_endpoint.py | location | polivbr/pulumi-azure-native | python | @property
@pulumi.getter
def location(self) -> pulumi.Output[Optional[str]]:
'\n \n '
return pulumi.get(self, 'location') |
@property
@pulumi.getter(name='manualPrivateLinkServiceConnections')
def manual_private_link_service_connections(self) -> pulumi.Output[Optional[Sequence['outputs.PrivateLinkServiceConnectionResponse']]]:
'\n A grouping of information about the connection to the remote resource. Used when the network admin does not have access to approve connections to the remote resource.\n '
return pulumi.get(self, 'manual_private_link_service_connections') | 7,044,445,811,079,634,000 | A grouping of information about the connection to the remote resource. Used when the network admin does not have access to approve connections to the remote resource. | sdk/python/pulumi_azure_native/network/v20190901/private_endpoint.py | manual_private_link_service_connections | polivbr/pulumi-azure-native | python | @property
@pulumi.getter(name='manualPrivateLinkServiceConnections')
def manual_private_link_service_connections(self) -> pulumi.Output[Optional[Sequence['outputs.PrivateLinkServiceConnectionResponse']]]:
'\n \n '
return pulumi.get(self, 'manual_private_link_service_connections') |
@property
@pulumi.getter
def name(self) -> pulumi.Output[str]:
'\n Resource name.\n '
return pulumi.get(self, 'name') | 4,695,236,134,441,039,000 | Resource name. | sdk/python/pulumi_azure_native/network/v20190901/private_endpoint.py | name | polivbr/pulumi-azure-native | python | @property
@pulumi.getter
def name(self) -> pulumi.Output[str]:
'\n \n '
return pulumi.get(self, 'name') |
@property
@pulumi.getter(name='networkInterfaces')
def network_interfaces(self) -> pulumi.Output[Sequence['outputs.NetworkInterfaceResponse']]:
'\n An array of references to the network interfaces created for this private endpoint.\n '
return pulumi.get(self, 'network_interfaces') | -2,116,992,413,112,385,500 | An array of references to the network interfaces created for this private endpoint. | sdk/python/pulumi_azure_native/network/v20190901/private_endpoint.py | network_interfaces | polivbr/pulumi-azure-native | python | @property
@pulumi.getter(name='networkInterfaces')
def network_interfaces(self) -> pulumi.Output[Sequence['outputs.NetworkInterfaceResponse']]:
'\n \n '
return pulumi.get(self, 'network_interfaces') |
@property
@pulumi.getter(name='privateLinkServiceConnections')
def private_link_service_connections(self) -> pulumi.Output[Optional[Sequence['outputs.PrivateLinkServiceConnectionResponse']]]:
'\n A grouping of information about the connection to the remote resource.\n '
return pulumi.get(self, 'private_link_service_connections') | 3,713,283,600,789,212,000 | A grouping of information about the connection to the remote resource. | sdk/python/pulumi_azure_native/network/v20190901/private_endpoint.py | private_link_service_connections | polivbr/pulumi-azure-native | python | @property
@pulumi.getter(name='privateLinkServiceConnections')
def private_link_service_connections(self) -> pulumi.Output[Optional[Sequence['outputs.PrivateLinkServiceConnectionResponse']]]:
'\n \n '
return pulumi.get(self, 'private_link_service_connections') |
@property
@pulumi.getter(name='provisioningState')
def provisioning_state(self) -> pulumi.Output[str]:
'\n The provisioning state of the private endpoint resource.\n '
return pulumi.get(self, 'provisioning_state') | -3,047,066,359,649,695,000 | The provisioning state of the private endpoint resource. | sdk/python/pulumi_azure_native/network/v20190901/private_endpoint.py | provisioning_state | polivbr/pulumi-azure-native | python | @property
@pulumi.getter(name='provisioningState')
def provisioning_state(self) -> pulumi.Output[str]:
'\n \n '
return pulumi.get(self, 'provisioning_state') |
@property
@pulumi.getter
def subnet(self) -> pulumi.Output[Optional['outputs.SubnetResponse']]:
'\n The ID of the subnet from which the private IP will be allocated.\n '
return pulumi.get(self, 'subnet') | 3,362,244,572,786,356,700 | The ID of the subnet from which the private IP will be allocated. | sdk/python/pulumi_azure_native/network/v20190901/private_endpoint.py | subnet | polivbr/pulumi-azure-native | python | @property
@pulumi.getter
def subnet(self) -> pulumi.Output[Optional['outputs.SubnetResponse']]:
'\n \n '
return pulumi.get(self, 'subnet') |
@property
@pulumi.getter
def tags(self) -> pulumi.Output[Optional[Mapping[(str, str)]]]:
'\n Resource tags.\n '
return pulumi.get(self, 'tags') | -2,929,197,049,816,896,000 | Resource tags. | sdk/python/pulumi_azure_native/network/v20190901/private_endpoint.py | tags | polivbr/pulumi-azure-native | python | @property
@pulumi.getter
def tags(self) -> pulumi.Output[Optional[Mapping[(str, str)]]]:
'\n \n '
return pulumi.get(self, 'tags') |
@property
@pulumi.getter
def type(self) -> pulumi.Output[str]:
'\n Resource type.\n '
return pulumi.get(self, 'type') | 2,132,950,812,122,862,800 | Resource type. | sdk/python/pulumi_azure_native/network/v20190901/private_endpoint.py | type | polivbr/pulumi-azure-native | python | @property
@pulumi.getter
def type(self) -> pulumi.Output[str]:
'\n \n '
return pulumi.get(self, 'type') |
def concat(xs, axis=1):
'Concatenates given variables along an axis.\n\n Args:\n xs (tuple of Variables): Variables to be concatenated.\n axis (int): Axis that the input arrays are concatenated along.\n\n Returns:\n ~chainer.Variable: Output variable.\n\n '
return Concat(axis=axis)(*xs) | 3,311,227,305,912,610,300 | Concatenates given variables along an axis.
Args:
xs (tuple of Variables): Variables to be concatenated.
axis (int): Axis that the input arrays are concatenated along.
Returns:
~chainer.Variable: Output variable. | chainer/functions/concat.py | concat | umitanuki/chainer | python | def concat(xs, axis=1):
'Concatenates given variables along an axis.\n\n Args:\n xs (tuple of Variables): Variables to be concatenated.\n axis (int): Axis that the input arrays are concatenated along.\n\n Returns:\n ~chainer.Variable: Output variable.\n\n '
return Concat(axis=axis)(*xs) |
def encoder_from_encoder_spec(encoder_spec, chosen_locations, num_known_timesteps, forecast_window_size, output_window_size, static_features=None, static_overrides=None, covariates=None, forecasted_covariates=None, covariate_overrides=None, ts_categorical_features=None, random_seed=0, static_scalers=None, ts_scalers=None, trainable=True):
'Returns a `FeatureEncoder` built as specified in the `encoder_spec`.'
encoder_kwargs = encoder_spec.encoder_kwargs
if (encoder_spec.encoder_type == 'gam'):
gam_kwargs = {}
for kwarg in encoder_kwargs:
if (kwarg == 'link_fn'):
gam_kwargs['link_fn'] = encoder_kwargs['link_fn']
elif (kwarg == 'distribution'):
gam_kwargs['distribution'] = encoder_kwargs['distribution']
elif (kwarg == 'initial_bias'):
gam_kwargs['initial_bias'] = encoder_kwargs['initial_bias']
elif (kwarg == 'location_dependent_bias'):
gam_kwargs['location_dependent_bias'] = encoder_kwargs['location_dependent_bias']
elif (kwarg == 'lower_bound'):
gam_kwargs['lower_bound'] = encoder_kwargs['lower_bound']
elif (kwarg == 'upper_bound'):
gam_kwargs['upper_bound'] = encoder_kwargs['upper_bound']
elif (kwarg == 'use_fixed_covariate_mask'):
gam_kwargs['use_fixed_covariate_mask'] = encoder_kwargs['use_fixed_covariate_mask']
else:
raise ValueError(f'Unexpected kwarg: {kwarg} passed to encoder of type {encoder_spec.encoder_type}')
return gam_encoder.GamEncoder(chosen_locations, num_known_timesteps, forecast_window_size=forecast_window_size, output_window_size=output_window_size, static_features=static_features, static_scalers=static_scalers, static_overrides=static_overrides, covariates=covariates, ts_scalers=ts_scalers, forecasted_covariates=forecasted_covariates, covariate_overrides=covariate_overrides, static_feature_specs=encoder_spec.static_feature_specs, covariate_feature_specs=encoder_spec.covariate_feature_specs, ts_categorical_features=ts_categorical_features, covariate_feature_time_offset=encoder_spec.covariate_feature_time_offset, covariate_feature_window=encoder_spec.covariate_feature_window, random_seed=random_seed, name=encoder_spec.encoder_name, trainable=trainable, **gam_kwargs)
elif (encoder_spec.encoder_type == 'static'):
return variable_encoders.StaticEncoder()
elif (encoder_spec.encoder_type == 'passthrough'):
return variable_encoders.PassThroughEncoder(chosen_locations, num_known_timesteps, forecast_window_size, covariates=covariates, forecasted_covariates=forecasted_covariates, covariate_overrides=covariate_overrides, covariate_feature_specs=encoder_spec.covariate_feature_specs, ts_categorical_features=ts_categorical_features, name=encoder_spec.encoder_name)
elif (encoder_spec.encoder_type == 'vaccine'):
return variable_encoders.VaccineEncoder(chosen_locations, num_known_timesteps, forecast_window_size, covariates=covariates, forecasted_covariates=forecasted_covariates, covariate_overrides=covariate_overrides, covariate_feature_specs=encoder_spec.covariate_feature_specs, ts_categorical_features=ts_categorical_features, name=encoder_spec.encoder_name, vaccine_type=encoder_spec.vaccine_type)
else:
raise ValueError(f'encoder_spec passed in with invalid encoder_type: {encoder_spec.encoder_type}') | -6,044,850,341,288,337,000 | Returns a `FeatureEncoder` built as specified in the `encoder_spec`. | covid_epidemiology/src/models/encoders/variable_encoder_builder.py | encoder_from_encoder_spec | 04mayukh/google-research | python | def encoder_from_encoder_spec(encoder_spec, chosen_locations, num_known_timesteps, forecast_window_size, output_window_size, static_features=None, static_overrides=None, covariates=None, forecasted_covariates=None, covariate_overrides=None, ts_categorical_features=None, random_seed=0, static_scalers=None, ts_scalers=None, trainable=True):
encoder_kwargs = encoder_spec.encoder_kwargs
if (encoder_spec.encoder_type == 'gam'):
gam_kwargs = {}
for kwarg in encoder_kwargs:
if (kwarg == 'link_fn'):
gam_kwargs['link_fn'] = encoder_kwargs['link_fn']
elif (kwarg == 'distribution'):
gam_kwargs['distribution'] = encoder_kwargs['distribution']
elif (kwarg == 'initial_bias'):
gam_kwargs['initial_bias'] = encoder_kwargs['initial_bias']
elif (kwarg == 'location_dependent_bias'):
gam_kwargs['location_dependent_bias'] = encoder_kwargs['location_dependent_bias']
elif (kwarg == 'lower_bound'):
gam_kwargs['lower_bound'] = encoder_kwargs['lower_bound']
elif (kwarg == 'upper_bound'):
gam_kwargs['upper_bound'] = encoder_kwargs['upper_bound']
elif (kwarg == 'use_fixed_covariate_mask'):
gam_kwargs['use_fixed_covariate_mask'] = encoder_kwargs['use_fixed_covariate_mask']
else:
raise ValueError(f'Unexpected kwarg: {kwarg} passed to encoder of type {encoder_spec.encoder_type}')
return gam_encoder.GamEncoder(chosen_locations, num_known_timesteps, forecast_window_size=forecast_window_size, output_window_size=output_window_size, static_features=static_features, static_scalers=static_scalers, static_overrides=static_overrides, covariates=covariates, ts_scalers=ts_scalers, forecasted_covariates=forecasted_covariates, covariate_overrides=covariate_overrides, static_feature_specs=encoder_spec.static_feature_specs, covariate_feature_specs=encoder_spec.covariate_feature_specs, ts_categorical_features=ts_categorical_features, covariate_feature_time_offset=encoder_spec.covariate_feature_time_offset, covariate_feature_window=encoder_spec.covariate_feature_window, random_seed=random_seed, name=encoder_spec.encoder_name, trainable=trainable, **gam_kwargs)
elif (encoder_spec.encoder_type == 'static'):
return variable_encoders.StaticEncoder()
elif (encoder_spec.encoder_type == 'passthrough'):
return variable_encoders.PassThroughEncoder(chosen_locations, num_known_timesteps, forecast_window_size, covariates=covariates, forecasted_covariates=forecasted_covariates, covariate_overrides=covariate_overrides, covariate_feature_specs=encoder_spec.covariate_feature_specs, ts_categorical_features=ts_categorical_features, name=encoder_spec.encoder_name)
elif (encoder_spec.encoder_type == 'vaccine'):
return variable_encoders.VaccineEncoder(chosen_locations, num_known_timesteps, forecast_window_size, covariates=covariates, forecasted_covariates=forecasted_covariates, covariate_overrides=covariate_overrides, covariate_feature_specs=encoder_spec.covariate_feature_specs, ts_categorical_features=ts_categorical_features, name=encoder_spec.encoder_name, vaccine_type=encoder_spec.vaccine_type)
else:
raise ValueError(f'encoder_spec passed in with invalid encoder_type: {encoder_spec.encoder_type}') |
def generate_caseRunConfigurations(self, library):
' Generates caseRunConfigurations for testcases in library relevant to this event\n\n :param library: Library\n :type library: tplib.Library\n :return: CaseRunConfigurations\n :rtype: CaseRunConfigurationsList\n '
caseruns = CaseRunConfigurationsList()
for testplan in self.filter_testPlans(library):
testplan_configurations = ConfigurationsList(testplan.configurations, merge_method=self.settings.get('library', 'defaultCaseConfigMergeMethod'))
for testcase in testplan.verificationTestCases:
caserun_configurations = testplan_configurations.merge(testcase.configurations)
for configuration in caserun_configurations:
caseruns.append(CaseRunConfiguration(testcase, configuration, [testplan]))
return caseruns | -6,780,673,543,612,013,000 | Generates caseRunConfigurations for testcases in library relevant to this event
:param library: Library
:type library: tplib.Library
:return: CaseRunConfigurations
:rtype: CaseRunConfigurationsList | libpermian/events/base.py | generate_caseRunConfigurations | rhinstaller/permian | python | def generate_caseRunConfigurations(self, library):
' Generates caseRunConfigurations for testcases in library relevant to this event\n\n :param library: Library\n :type library: tplib.Library\n :return: CaseRunConfigurations\n :rtype: CaseRunConfigurationsList\n '
caseruns = CaseRunConfigurationsList()
for testplan in self.filter_testPlans(library):
testplan_configurations = ConfigurationsList(testplan.configurations, merge_method=self.settings.get('library', 'defaultCaseConfigMergeMethod'))
for testcase in testplan.verificationTestCases:
caserun_configurations = testplan_configurations.merge(testcase.configurations)
for configuration in caserun_configurations:
caseruns.append(CaseRunConfiguration(testcase, configuration, [testplan]))
return caseruns |
def handles_testplan_artifact_type(self, artifact_type):
'\n Decide if this event is relevant to the provided artifact_type (which\n is found in test plan).\n '
return dotted_startswith(self.type, artifact_type) | 2,603,444,795,506,606,600 | Decide if this event is relevant to the provided artifact_type (which
is found in test plan). | libpermian/events/base.py | handles_testplan_artifact_type | rhinstaller/permian | python | def handles_testplan_artifact_type(self, artifact_type):
'\n Decide if this event is relevant to the provided artifact_type (which\n is found in test plan).\n '
return dotted_startswith(self.type, artifact_type) |
def filter_testPlans(self, library):
' Filters testplan from library based on:\n - event type and testplan.artifact_type\n - testplan execute_on filter\n\n :param library: pipeline library\n :type library: tplib.Library\n :return: Filtered testplans\n :rtype: list of tplib.TestPlan\n '
return library.getTestPlansByQuery('event.handles_testplan_artifact_type(tp.artifact_type) and tp.eval_execute_on(event=event)', event=self) | 39,500,111,890,816,350 | Filters testplan from library based on:
- event type and testplan.artifact_type
- testplan execute_on filter
:param library: pipeline library
:type library: tplib.Library
:return: Filtered testplans
:rtype: list of tplib.TestPlan | libpermian/events/base.py | filter_testPlans | rhinstaller/permian | python | def filter_testPlans(self, library):
' Filters testplan from library based on:\n - event type and testplan.artifact_type\n - testplan execute_on filter\n\n :param library: pipeline library\n :type library: tplib.Library\n :return: Filtered testplans\n :rtype: list of tplib.TestPlan\n '
return library.getTestPlansByQuery('event.handles_testplan_artifact_type(tp.artifact_type) and tp.eval_execute_on(event=event)', event=self) |
@property
def additional_testplans_data(self):
' Event can provide additional testplans. Returns python\n dicts, as if they were tplib files read by yaml.safe_load.\n\n :return: list of testplan data\n :rtype: tuple\n '
return None | -4,555,565,715,031,543,000 | Event can provide additional testplans. Returns python
dicts, as if they were tplib files read by yaml.safe_load.
:return: list of testplan data
:rtype: tuple | libpermian/events/base.py | additional_testplans_data | rhinstaller/permian | python | @property
def additional_testplans_data(self):
' Event can provide additional testplans. Returns python\n dicts, as if they were tplib files read by yaml.safe_load.\n\n :return: list of testplan data\n :rtype: tuple\n '
return None |
@property
def additional_requrements_data(self):
' Event can provide additional requrements. Returns python\n dicts, as if they were tplib files read by yaml.safe_load.\n\n :return: list of requrements data\n :rtype: tuple\n '
return None | 5,101,496,771,720,215,000 | Event can provide additional requrements. Returns python
dicts, as if they were tplib files read by yaml.safe_load.
:return: list of requrements data
:rtype: tuple | libpermian/events/base.py | additional_requrements_data | rhinstaller/permian | python | @property
def additional_requrements_data(self):
' Event can provide additional requrements. Returns python\n dicts, as if they were tplib files read by yaml.safe_load.\n\n :return: list of requrements data\n :rtype: tuple\n '
return None |
@property
def additional_testcases_data(self):
' Event can provide additional testcases. Returns python\n dicts, as if they were tplib files read by yaml.safe_load.\n\n :return: list of testcases data\n :rtype: tuple\n '
return None | -3,993,988,197,691,913,000 | Event can provide additional testcases. Returns python
dicts, as if they were tplib files read by yaml.safe_load.
:return: list of testcases data
:rtype: tuple | libpermian/events/base.py | additional_testcases_data | rhinstaller/permian | python | @property
def additional_testcases_data(self):
' Event can provide additional testcases. Returns python\n dicts, as if they were tplib files read by yaml.safe_load.\n\n :return: list of testcases data\n :rtype: tuple\n '
return None |
def __init__(self, all_for_sec=None, days=None, per_day=None):
'\n Keyword args:\n all_for_sec (int): The length of time to keep the specified snapshots. Measured in seconds.\n days (int): The number of days to keep the snapshots after the `all_for_sec` period has passed.\n per_day (int): The number of snapshots to keep per day after the `all_for_sec` period has passed.\n '
if (all_for_sec is not None):
self.all_for_sec = all_for_sec
if (days is not None):
self.days = days
if (per_day is not None):
self.per_day = per_day | 5,860,685,410,813,140,000 | Keyword args:
all_for_sec (int): The length of time to keep the specified snapshots. Measured in seconds.
days (int): The number of days to keep the snapshots after the `all_for_sec` period has passed.
per_day (int): The number of snapshots to keep per day after the `all_for_sec` period has passed. | pypureclient/flasharray/FA_2_1/models/retention_policy.py | __init__ | Flav-STOR-WL/py-pure-client | python | def __init__(self, all_for_sec=None, days=None, per_day=None):
'\n Keyword args:\n all_for_sec (int): The length of time to keep the specified snapshots. Measured in seconds.\n days (int): The number of days to keep the snapshots after the `all_for_sec` period has passed.\n per_day (int): The number of snapshots to keep per day after the `all_for_sec` period has passed.\n '
if (all_for_sec is not None):
self.all_for_sec = all_for_sec
if (days is not None):
self.days = days
if (per_day is not None):
self.per_day = per_day |
def to_dict(self):
'Returns the model properties as a dict'
result = {}
for (attr, _) in six.iteritems(self.swagger_types):
if hasattr(self, attr):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map((lambda x: (x.to_dict() if hasattr(x, 'to_dict') else x)), value))
elif hasattr(value, 'to_dict'):
result[attr] = value.to_dict()
elif isinstance(value, dict):
result[attr] = dict(map((lambda item: ((item[0], item[1].to_dict()) if hasattr(item[1], 'to_dict') else item)), value.items()))
else:
result[attr] = value
if issubclass(RetentionPolicy, dict):
for (key, value) in self.items():
result[key] = value
return result | 7,346,697,134,304,610,000 | Returns the model properties as a dict | pypureclient/flasharray/FA_2_1/models/retention_policy.py | to_dict | Flav-STOR-WL/py-pure-client | python | def to_dict(self):
result = {}
for (attr, _) in six.iteritems(self.swagger_types):
if hasattr(self, attr):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map((lambda x: (x.to_dict() if hasattr(x, 'to_dict') else x)), value))
elif hasattr(value, 'to_dict'):
result[attr] = value.to_dict()
elif isinstance(value, dict):
result[attr] = dict(map((lambda item: ((item[0], item[1].to_dict()) if hasattr(item[1], 'to_dict') else item)), value.items()))
else:
result[attr] = value
if issubclass(RetentionPolicy, dict):
for (key, value) in self.items():
result[key] = value
return result |
def to_str(self):
'Returns the string representation of the model'
return pprint.pformat(self.to_dict()) | 5,849,158,643,760,736,000 | Returns the string representation of the model | pypureclient/flasharray/FA_2_1/models/retention_policy.py | to_str | Flav-STOR-WL/py-pure-client | python | def to_str(self):
return pprint.pformat(self.to_dict()) |
def __repr__(self):
'For `print` and `pprint`'
return self.to_str() | -8,960,031,694,814,905,000 | For `print` and `pprint` | pypureclient/flasharray/FA_2_1/models/retention_policy.py | __repr__ | Flav-STOR-WL/py-pure-client | python | def __repr__(self):
return self.to_str() |
def __eq__(self, other):
'Returns true if both objects are equal'
if (not isinstance(other, RetentionPolicy)):
return False
return (self.__dict__ == other.__dict__) | -5,835,544,153,022,462,000 | Returns true if both objects are equal | pypureclient/flasharray/FA_2_1/models/retention_policy.py | __eq__ | Flav-STOR-WL/py-pure-client | python | def __eq__(self, other):
if (not isinstance(other, RetentionPolicy)):
return False
return (self.__dict__ == other.__dict__) |
def __ne__(self, other):
'Returns true if both objects are not equal'
return (not (self == other)) | 7,764,124,047,908,058,000 | Returns true if both objects are not equal | pypureclient/flasharray/FA_2_1/models/retention_policy.py | __ne__ | Flav-STOR-WL/py-pure-client | python | def __ne__(self, other):
return (not (self == other)) |
def list(self, group_name: str, service_name: str, project_name: str, task_type: Optional[str]=None, **kwargs) -> AsyncIterable['models.TaskList']:
'Get tasks in a service.\n\n The services resource is the top-level resource that represents the Database Migration Service.\n This method returns a list of tasks owned by a service resource. Some tasks may have a status\n of Unknown, which indicates that an error occurred while querying the status of that task.\n\n :param group_name: Name of the resource group.\n :type group_name: str\n :param service_name: Name of the service.\n :type service_name: str\n :param project_name: Name of the project.\n :type project_name: str\n :param task_type: Filter tasks by task type.\n :type task_type: str\n :keyword callable cls: A custom type or function that will be passed the direct response\n :return: An iterator like instance of either TaskList or the result of cls(response)\n :rtype: ~azure.core.async_paging.AsyncItemPaged[~azure.mgmt.datamigration.models.TaskList]\n :raises: ~azure.core.exceptions.HttpResponseError\n '
cls = kwargs.pop('cls', None)
error_map = {401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError}
error_map.update(kwargs.pop('error_map', {}))
api_version = '2021-10-30-preview'
accept = 'application/json'
def prepare_request(next_link=None):
header_parameters = {}
header_parameters['Accept'] = self._serialize.header('accept', accept, 'str')
if (not next_link):
url = self.list.metadata['url']
path_format_arguments = {'subscriptionId': self._serialize.url('self._config.subscription_id', self._config.subscription_id, 'str'), 'groupName': self._serialize.url('group_name', group_name, 'str'), 'serviceName': self._serialize.url('service_name', service_name, 'str'), 'projectName': self._serialize.url('project_name', project_name, 'str')}
url = self._client.format_url(url, **path_format_arguments)
query_parameters = {}
query_parameters['api-version'] = self._serialize.query('api_version', api_version, 'str')
if (task_type is not None):
query_parameters['taskType'] = self._serialize.query('task_type', task_type, 'str')
request = self._client.get(url, query_parameters, header_parameters)
else:
url = next_link
query_parameters = {}
request = self._client.get(url, query_parameters, header_parameters)
return request
async def extract_data(pipeline_response):
deserialized = self._deserialize('TaskList', pipeline_response)
list_of_elem = deserialized.value
if cls:
list_of_elem = cls(list_of_elem)
return ((deserialized.next_link or None), AsyncList(list_of_elem))
async def get_next(next_link=None):
request = prepare_request(next_link)
pipeline_response = (await self._client._pipeline.run(request, stream=False, **kwargs))
response = pipeline_response.http_response
if (response.status_code not in [200]):
error = self._deserialize(models.ApiError, response)
map_error(status_code=response.status_code, response=response, error_map=error_map)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
return pipeline_response
return AsyncItemPaged(get_next, extract_data) | 245,612,584,995,217,300 | Get tasks in a service.
The services resource is the top-level resource that represents the Database Migration Service.
This method returns a list of tasks owned by a service resource. Some tasks may have a status
of Unknown, which indicates that an error occurred while querying the status of that task.
:param group_name: Name of the resource group.
:type group_name: str
:param service_name: Name of the service.
:type service_name: str
:param project_name: Name of the project.
:type project_name: str
:param task_type: Filter tasks by task type.
:type task_type: str
:keyword callable cls: A custom type or function that will be passed the direct response
:return: An iterator like instance of either TaskList or the result of cls(response)
:rtype: ~azure.core.async_paging.AsyncItemPaged[~azure.mgmt.datamigration.models.TaskList]
:raises: ~azure.core.exceptions.HttpResponseError | src/datamigration/azext_datamigration/vendored_sdks/datamigration/aio/operations/_tasks_operations.py | list | Hamster-Huey/azure-cli-extensions | python | def list(self, group_name: str, service_name: str, project_name: str, task_type: Optional[str]=None, **kwargs) -> AsyncIterable['models.TaskList']:
'Get tasks in a service.\n\n The services resource is the top-level resource that represents the Database Migration Service.\n This method returns a list of tasks owned by a service resource. Some tasks may have a status\n of Unknown, which indicates that an error occurred while querying the status of that task.\n\n :param group_name: Name of the resource group.\n :type group_name: str\n :param service_name: Name of the service.\n :type service_name: str\n :param project_name: Name of the project.\n :type project_name: str\n :param task_type: Filter tasks by task type.\n :type task_type: str\n :keyword callable cls: A custom type or function that will be passed the direct response\n :return: An iterator like instance of either TaskList or the result of cls(response)\n :rtype: ~azure.core.async_paging.AsyncItemPaged[~azure.mgmt.datamigration.models.TaskList]\n :raises: ~azure.core.exceptions.HttpResponseError\n '
cls = kwargs.pop('cls', None)
error_map = {401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError}
error_map.update(kwargs.pop('error_map', {}))
api_version = '2021-10-30-preview'
accept = 'application/json'
def prepare_request(next_link=None):
header_parameters = {}
header_parameters['Accept'] = self._serialize.header('accept', accept, 'str')
if (not next_link):
url = self.list.metadata['url']
path_format_arguments = {'subscriptionId': self._serialize.url('self._config.subscription_id', self._config.subscription_id, 'str'), 'groupName': self._serialize.url('group_name', group_name, 'str'), 'serviceName': self._serialize.url('service_name', service_name, 'str'), 'projectName': self._serialize.url('project_name', project_name, 'str')}
url = self._client.format_url(url, **path_format_arguments)
query_parameters = {}
query_parameters['api-version'] = self._serialize.query('api_version', api_version, 'str')
if (task_type is not None):
query_parameters['taskType'] = self._serialize.query('task_type', task_type, 'str')
request = self._client.get(url, query_parameters, header_parameters)
else:
url = next_link
query_parameters = {}
request = self._client.get(url, query_parameters, header_parameters)
return request
async def extract_data(pipeline_response):
deserialized = self._deserialize('TaskList', pipeline_response)
list_of_elem = deserialized.value
if cls:
list_of_elem = cls(list_of_elem)
return ((deserialized.next_link or None), AsyncList(list_of_elem))
async def get_next(next_link=None):
request = prepare_request(next_link)
pipeline_response = (await self._client._pipeline.run(request, stream=False, **kwargs))
response = pipeline_response.http_response
if (response.status_code not in [200]):
error = self._deserialize(models.ApiError, response)
map_error(status_code=response.status_code, response=response, error_map=error_map)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
return pipeline_response
return AsyncItemPaged(get_next, extract_data) |
async def create_or_update(self, group_name: str, service_name: str, project_name: str, task_name: str, parameters: 'models.ProjectTask', **kwargs) -> 'models.ProjectTask':
'Create or update task.\n\n The tasks resource is a nested, proxy-only resource representing work performed by a DMS\n instance. The PUT method creates a new task or updates an existing one, although since tasks\n have no mutable custom properties, there is little reason to update an existing one.\n\n :param group_name: Name of the resource group.\n :type group_name: str\n :param service_name: Name of the service.\n :type service_name: str\n :param project_name: Name of the project.\n :type project_name: str\n :param task_name: Name of the Task.\n :type task_name: str\n :param parameters: Information about the task.\n :type parameters: ~azure.mgmt.datamigration.models.ProjectTask\n :keyword callable cls: A custom type or function that will be passed the direct response\n :return: ProjectTask, or the result of cls(response)\n :rtype: ~azure.mgmt.datamigration.models.ProjectTask\n :raises: ~azure.core.exceptions.HttpResponseError\n '
cls = kwargs.pop('cls', None)
error_map = {401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError}
error_map.update(kwargs.pop('error_map', {}))
api_version = '2021-10-30-preview'
content_type = kwargs.pop('content_type', 'application/json')
accept = 'application/json'
url = self.create_or_update.metadata['url']
path_format_arguments = {'subscriptionId': self._serialize.url('self._config.subscription_id', self._config.subscription_id, 'str'), 'groupName': self._serialize.url('group_name', group_name, 'str'), 'serviceName': self._serialize.url('service_name', service_name, 'str'), 'projectName': self._serialize.url('project_name', project_name, 'str'), 'taskName': self._serialize.url('task_name', task_name, 'str')}
url = self._client.format_url(url, **path_format_arguments)
query_parameters = {}
query_parameters['api-version'] = self._serialize.query('api_version', api_version, 'str')
header_parameters = {}
header_parameters['Content-Type'] = self._serialize.header('content_type', content_type, 'str')
header_parameters['Accept'] = self._serialize.header('accept', accept, 'str')
body_content_kwargs = {}
body_content = self._serialize.body(parameters, 'ProjectTask')
body_content_kwargs['content'] = body_content
request = self._client.put(url, query_parameters, header_parameters, **body_content_kwargs)
pipeline_response = (await self._client._pipeline.run(request, stream=False, **kwargs))
response = pipeline_response.http_response
if (response.status_code not in [200, 201]):
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize(models.ApiError, response)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
if (response.status_code == 200):
deserialized = self._deserialize('ProjectTask', pipeline_response)
if (response.status_code == 201):
deserialized = self._deserialize('ProjectTask', pipeline_response)
if cls:
return cls(pipeline_response, deserialized, {})
return deserialized | -2,965,820,772,915,707,000 | Create or update task.
The tasks resource is a nested, proxy-only resource representing work performed by a DMS
instance. The PUT method creates a new task or updates an existing one, although since tasks
have no mutable custom properties, there is little reason to update an existing one.
:param group_name: Name of the resource group.
:type group_name: str
:param service_name: Name of the service.
:type service_name: str
:param project_name: Name of the project.
:type project_name: str
:param task_name: Name of the Task.
:type task_name: str
:param parameters: Information about the task.
:type parameters: ~azure.mgmt.datamigration.models.ProjectTask
:keyword callable cls: A custom type or function that will be passed the direct response
:return: ProjectTask, or the result of cls(response)
:rtype: ~azure.mgmt.datamigration.models.ProjectTask
:raises: ~azure.core.exceptions.HttpResponseError | src/datamigration/azext_datamigration/vendored_sdks/datamigration/aio/operations/_tasks_operations.py | create_or_update | Hamster-Huey/azure-cli-extensions | python | async def create_or_update(self, group_name: str, service_name: str, project_name: str, task_name: str, parameters: 'models.ProjectTask', **kwargs) -> 'models.ProjectTask':
'Create or update task.\n\n The tasks resource is a nested, proxy-only resource representing work performed by a DMS\n instance. The PUT method creates a new task or updates an existing one, although since tasks\n have no mutable custom properties, there is little reason to update an existing one.\n\n :param group_name: Name of the resource group.\n :type group_name: str\n :param service_name: Name of the service.\n :type service_name: str\n :param project_name: Name of the project.\n :type project_name: str\n :param task_name: Name of the Task.\n :type task_name: str\n :param parameters: Information about the task.\n :type parameters: ~azure.mgmt.datamigration.models.ProjectTask\n :keyword callable cls: A custom type or function that will be passed the direct response\n :return: ProjectTask, or the result of cls(response)\n :rtype: ~azure.mgmt.datamigration.models.ProjectTask\n :raises: ~azure.core.exceptions.HttpResponseError\n '
cls = kwargs.pop('cls', None)
error_map = {401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError}
error_map.update(kwargs.pop('error_map', {}))
api_version = '2021-10-30-preview'
content_type = kwargs.pop('content_type', 'application/json')
accept = 'application/json'
url = self.create_or_update.metadata['url']
path_format_arguments = {'subscriptionId': self._serialize.url('self._config.subscription_id', self._config.subscription_id, 'str'), 'groupName': self._serialize.url('group_name', group_name, 'str'), 'serviceName': self._serialize.url('service_name', service_name, 'str'), 'projectName': self._serialize.url('project_name', project_name, 'str'), 'taskName': self._serialize.url('task_name', task_name, 'str')}
url = self._client.format_url(url, **path_format_arguments)
query_parameters = {}
query_parameters['api-version'] = self._serialize.query('api_version', api_version, 'str')
header_parameters = {}
header_parameters['Content-Type'] = self._serialize.header('content_type', content_type, 'str')
header_parameters['Accept'] = self._serialize.header('accept', accept, 'str')
body_content_kwargs = {}
body_content = self._serialize.body(parameters, 'ProjectTask')
body_content_kwargs['content'] = body_content
request = self._client.put(url, query_parameters, header_parameters, **body_content_kwargs)
pipeline_response = (await self._client._pipeline.run(request, stream=False, **kwargs))
response = pipeline_response.http_response
if (response.status_code not in [200, 201]):
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize(models.ApiError, response)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
if (response.status_code == 200):
deserialized = self._deserialize('ProjectTask', pipeline_response)
if (response.status_code == 201):
deserialized = self._deserialize('ProjectTask', pipeline_response)
if cls:
return cls(pipeline_response, deserialized, {})
return deserialized |
async def get(self, group_name: str, service_name: str, project_name: str, task_name: str, expand: Optional[str]=None, **kwargs) -> 'models.ProjectTask':
'Get task information.\n\n The tasks resource is a nested, proxy-only resource representing work performed by a DMS\n instance. The GET method retrieves information about a task.\n\n :param group_name: Name of the resource group.\n :type group_name: str\n :param service_name: Name of the service.\n :type service_name: str\n :param project_name: Name of the project.\n :type project_name: str\n :param task_name: Name of the Task.\n :type task_name: str\n :param expand: Expand the response.\n :type expand: str\n :keyword callable cls: A custom type or function that will be passed the direct response\n :return: ProjectTask, or the result of cls(response)\n :rtype: ~azure.mgmt.datamigration.models.ProjectTask\n :raises: ~azure.core.exceptions.HttpResponseError\n '
cls = kwargs.pop('cls', None)
error_map = {401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError}
error_map.update(kwargs.pop('error_map', {}))
api_version = '2021-10-30-preview'
accept = 'application/json'
url = self.get.metadata['url']
path_format_arguments = {'subscriptionId': self._serialize.url('self._config.subscription_id', self._config.subscription_id, 'str'), 'groupName': self._serialize.url('group_name', group_name, 'str'), 'serviceName': self._serialize.url('service_name', service_name, 'str'), 'projectName': self._serialize.url('project_name', project_name, 'str'), 'taskName': self._serialize.url('task_name', task_name, 'str')}
url = self._client.format_url(url, **path_format_arguments)
query_parameters = {}
query_parameters['api-version'] = self._serialize.query('api_version', api_version, 'str')
if (expand is not None):
query_parameters['$expand'] = self._serialize.query('expand', expand, 'str')
header_parameters = {}
header_parameters['Accept'] = self._serialize.header('accept', accept, 'str')
request = self._client.get(url, query_parameters, header_parameters)
pipeline_response = (await self._client._pipeline.run(request, stream=False, **kwargs))
response = pipeline_response.http_response
if (response.status_code not in [200]):
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize(models.ApiError, response)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
deserialized = self._deserialize('ProjectTask', pipeline_response)
if cls:
return cls(pipeline_response, deserialized, {})
return deserialized | 4,512,955,439,058,534,000 | Get task information.
The tasks resource is a nested, proxy-only resource representing work performed by a DMS
instance. The GET method retrieves information about a task.
:param group_name: Name of the resource group.
:type group_name: str
:param service_name: Name of the service.
:type service_name: str
:param project_name: Name of the project.
:type project_name: str
:param task_name: Name of the Task.
:type task_name: str
:param expand: Expand the response.
:type expand: str
:keyword callable cls: A custom type or function that will be passed the direct response
:return: ProjectTask, or the result of cls(response)
:rtype: ~azure.mgmt.datamigration.models.ProjectTask
:raises: ~azure.core.exceptions.HttpResponseError | src/datamigration/azext_datamigration/vendored_sdks/datamigration/aio/operations/_tasks_operations.py | get | Hamster-Huey/azure-cli-extensions | python | async def get(self, group_name: str, service_name: str, project_name: str, task_name: str, expand: Optional[str]=None, **kwargs) -> 'models.ProjectTask':
'Get task information.\n\n The tasks resource is a nested, proxy-only resource representing work performed by a DMS\n instance. The GET method retrieves information about a task.\n\n :param group_name: Name of the resource group.\n :type group_name: str\n :param service_name: Name of the service.\n :type service_name: str\n :param project_name: Name of the project.\n :type project_name: str\n :param task_name: Name of the Task.\n :type task_name: str\n :param expand: Expand the response.\n :type expand: str\n :keyword callable cls: A custom type or function that will be passed the direct response\n :return: ProjectTask, or the result of cls(response)\n :rtype: ~azure.mgmt.datamigration.models.ProjectTask\n :raises: ~azure.core.exceptions.HttpResponseError\n '
cls = kwargs.pop('cls', None)
error_map = {401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError}
error_map.update(kwargs.pop('error_map', {}))
api_version = '2021-10-30-preview'
accept = 'application/json'
url = self.get.metadata['url']
path_format_arguments = {'subscriptionId': self._serialize.url('self._config.subscription_id', self._config.subscription_id, 'str'), 'groupName': self._serialize.url('group_name', group_name, 'str'), 'serviceName': self._serialize.url('service_name', service_name, 'str'), 'projectName': self._serialize.url('project_name', project_name, 'str'), 'taskName': self._serialize.url('task_name', task_name, 'str')}
url = self._client.format_url(url, **path_format_arguments)
query_parameters = {}
query_parameters['api-version'] = self._serialize.query('api_version', api_version, 'str')
if (expand is not None):
query_parameters['$expand'] = self._serialize.query('expand', expand, 'str')
header_parameters = {}
header_parameters['Accept'] = self._serialize.header('accept', accept, 'str')
request = self._client.get(url, query_parameters, header_parameters)
pipeline_response = (await self._client._pipeline.run(request, stream=False, **kwargs))
response = pipeline_response.http_response
if (response.status_code not in [200]):
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize(models.ApiError, response)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
deserialized = self._deserialize('ProjectTask', pipeline_response)
if cls:
return cls(pipeline_response, deserialized, {})
return deserialized |
async def delete(self, group_name: str, service_name: str, project_name: str, task_name: str, delete_running_tasks: Optional[bool]=None, **kwargs) -> None:
"Delete task.\n\n The tasks resource is a nested, proxy-only resource representing work performed by a DMS\n instance. The DELETE method deletes a task, canceling it first if it's running.\n\n :param group_name: Name of the resource group.\n :type group_name: str\n :param service_name: Name of the service.\n :type service_name: str\n :param project_name: Name of the project.\n :type project_name: str\n :param task_name: Name of the Task.\n :type task_name: str\n :param delete_running_tasks: Delete the resource even if it contains running tasks.\n :type delete_running_tasks: bool\n :keyword callable cls: A custom type or function that will be passed the direct response\n :return: None, or the result of cls(response)\n :rtype: None\n :raises: ~azure.core.exceptions.HttpResponseError\n "
cls = kwargs.pop('cls', None)
error_map = {401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError}
error_map.update(kwargs.pop('error_map', {}))
api_version = '2021-10-30-preview'
accept = 'application/json'
url = self.delete.metadata['url']
path_format_arguments = {'subscriptionId': self._serialize.url('self._config.subscription_id', self._config.subscription_id, 'str'), 'groupName': self._serialize.url('group_name', group_name, 'str'), 'serviceName': self._serialize.url('service_name', service_name, 'str'), 'projectName': self._serialize.url('project_name', project_name, 'str'), 'taskName': self._serialize.url('task_name', task_name, 'str')}
url = self._client.format_url(url, **path_format_arguments)
query_parameters = {}
query_parameters['api-version'] = self._serialize.query('api_version', api_version, 'str')
if (delete_running_tasks is not None):
query_parameters['deleteRunningTasks'] = self._serialize.query('delete_running_tasks', delete_running_tasks, 'bool')
header_parameters = {}
header_parameters['Accept'] = self._serialize.header('accept', accept, 'str')
request = self._client.delete(url, query_parameters, header_parameters)
pipeline_response = (await self._client._pipeline.run(request, stream=False, **kwargs))
response = pipeline_response.http_response
if (response.status_code not in [200, 204]):
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize(models.ApiError, response)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
if cls:
return cls(pipeline_response, None, {}) | 4,686,494,169,580,922,000 | Delete task.
The tasks resource is a nested, proxy-only resource representing work performed by a DMS
instance. The DELETE method deletes a task, canceling it first if it's running.
:param group_name: Name of the resource group.
:type group_name: str
:param service_name: Name of the service.
:type service_name: str
:param project_name: Name of the project.
:type project_name: str
:param task_name: Name of the Task.
:type task_name: str
:param delete_running_tasks: Delete the resource even if it contains running tasks.
:type delete_running_tasks: bool
:keyword callable cls: A custom type or function that will be passed the direct response
:return: None, or the result of cls(response)
:rtype: None
:raises: ~azure.core.exceptions.HttpResponseError | src/datamigration/azext_datamigration/vendored_sdks/datamigration/aio/operations/_tasks_operations.py | delete | Hamster-Huey/azure-cli-extensions | python | async def delete(self, group_name: str, service_name: str, project_name: str, task_name: str, delete_running_tasks: Optional[bool]=None, **kwargs) -> None:
"Delete task.\n\n The tasks resource is a nested, proxy-only resource representing work performed by a DMS\n instance. The DELETE method deletes a task, canceling it first if it's running.\n\n :param group_name: Name of the resource group.\n :type group_name: str\n :param service_name: Name of the service.\n :type service_name: str\n :param project_name: Name of the project.\n :type project_name: str\n :param task_name: Name of the Task.\n :type task_name: str\n :param delete_running_tasks: Delete the resource even if it contains running tasks.\n :type delete_running_tasks: bool\n :keyword callable cls: A custom type or function that will be passed the direct response\n :return: None, or the result of cls(response)\n :rtype: None\n :raises: ~azure.core.exceptions.HttpResponseError\n "
cls = kwargs.pop('cls', None)
error_map = {401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError}
error_map.update(kwargs.pop('error_map', {}))
api_version = '2021-10-30-preview'
accept = 'application/json'
url = self.delete.metadata['url']
path_format_arguments = {'subscriptionId': self._serialize.url('self._config.subscription_id', self._config.subscription_id, 'str'), 'groupName': self._serialize.url('group_name', group_name, 'str'), 'serviceName': self._serialize.url('service_name', service_name, 'str'), 'projectName': self._serialize.url('project_name', project_name, 'str'), 'taskName': self._serialize.url('task_name', task_name, 'str')}
url = self._client.format_url(url, **path_format_arguments)
query_parameters = {}
query_parameters['api-version'] = self._serialize.query('api_version', api_version, 'str')
if (delete_running_tasks is not None):
query_parameters['deleteRunningTasks'] = self._serialize.query('delete_running_tasks', delete_running_tasks, 'bool')
header_parameters = {}
header_parameters['Accept'] = self._serialize.header('accept', accept, 'str')
request = self._client.delete(url, query_parameters, header_parameters)
pipeline_response = (await self._client._pipeline.run(request, stream=False, **kwargs))
response = pipeline_response.http_response
if (response.status_code not in [200, 204]):
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize(models.ApiError, response)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
if cls:
return cls(pipeline_response, None, {}) |
async def update(self, group_name: str, service_name: str, project_name: str, task_name: str, parameters: 'models.ProjectTask', **kwargs) -> 'models.ProjectTask':
'Create or update task.\n\n The tasks resource is a nested, proxy-only resource representing work performed by a DMS\n instance. The PATCH method updates an existing task, but since tasks have no mutable custom\n properties, there is little reason to do so.\n\n :param group_name: Name of the resource group.\n :type group_name: str\n :param service_name: Name of the service.\n :type service_name: str\n :param project_name: Name of the project.\n :type project_name: str\n :param task_name: Name of the Task.\n :type task_name: str\n :param parameters: Information about the task.\n :type parameters: ~azure.mgmt.datamigration.models.ProjectTask\n :keyword callable cls: A custom type or function that will be passed the direct response\n :return: ProjectTask, or the result of cls(response)\n :rtype: ~azure.mgmt.datamigration.models.ProjectTask\n :raises: ~azure.core.exceptions.HttpResponseError\n '
cls = kwargs.pop('cls', None)
error_map = {401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError}
error_map.update(kwargs.pop('error_map', {}))
api_version = '2021-10-30-preview'
content_type = kwargs.pop('content_type', 'application/json')
accept = 'application/json'
url = self.update.metadata['url']
path_format_arguments = {'subscriptionId': self._serialize.url('self._config.subscription_id', self._config.subscription_id, 'str'), 'groupName': self._serialize.url('group_name', group_name, 'str'), 'serviceName': self._serialize.url('service_name', service_name, 'str'), 'projectName': self._serialize.url('project_name', project_name, 'str'), 'taskName': self._serialize.url('task_name', task_name, 'str')}
url = self._client.format_url(url, **path_format_arguments)
query_parameters = {}
query_parameters['api-version'] = self._serialize.query('api_version', api_version, 'str')
header_parameters = {}
header_parameters['Content-Type'] = self._serialize.header('content_type', content_type, 'str')
header_parameters['Accept'] = self._serialize.header('accept', accept, 'str')
body_content_kwargs = {}
body_content = self._serialize.body(parameters, 'ProjectTask')
body_content_kwargs['content'] = body_content
request = self._client.patch(url, query_parameters, header_parameters, **body_content_kwargs)
pipeline_response = (await self._client._pipeline.run(request, stream=False, **kwargs))
response = pipeline_response.http_response
if (response.status_code not in [200]):
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize(models.ApiError, response)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
deserialized = self._deserialize('ProjectTask', pipeline_response)
if cls:
return cls(pipeline_response, deserialized, {})
return deserialized | -7,988,383,540,604,401,000 | Create or update task.
The tasks resource is a nested, proxy-only resource representing work performed by a DMS
instance. The PATCH method updates an existing task, but since tasks have no mutable custom
properties, there is little reason to do so.
:param group_name: Name of the resource group.
:type group_name: str
:param service_name: Name of the service.
:type service_name: str
:param project_name: Name of the project.
:type project_name: str
:param task_name: Name of the Task.
:type task_name: str
:param parameters: Information about the task.
:type parameters: ~azure.mgmt.datamigration.models.ProjectTask
:keyword callable cls: A custom type or function that will be passed the direct response
:return: ProjectTask, or the result of cls(response)
:rtype: ~azure.mgmt.datamigration.models.ProjectTask
:raises: ~azure.core.exceptions.HttpResponseError | src/datamigration/azext_datamigration/vendored_sdks/datamigration/aio/operations/_tasks_operations.py | update | Hamster-Huey/azure-cli-extensions | python | async def update(self, group_name: str, service_name: str, project_name: str, task_name: str, parameters: 'models.ProjectTask', **kwargs) -> 'models.ProjectTask':
'Create or update task.\n\n The tasks resource is a nested, proxy-only resource representing work performed by a DMS\n instance. The PATCH method updates an existing task, but since tasks have no mutable custom\n properties, there is little reason to do so.\n\n :param group_name: Name of the resource group.\n :type group_name: str\n :param service_name: Name of the service.\n :type service_name: str\n :param project_name: Name of the project.\n :type project_name: str\n :param task_name: Name of the Task.\n :type task_name: str\n :param parameters: Information about the task.\n :type parameters: ~azure.mgmt.datamigration.models.ProjectTask\n :keyword callable cls: A custom type or function that will be passed the direct response\n :return: ProjectTask, or the result of cls(response)\n :rtype: ~azure.mgmt.datamigration.models.ProjectTask\n :raises: ~azure.core.exceptions.HttpResponseError\n '
cls = kwargs.pop('cls', None)
error_map = {401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError}
error_map.update(kwargs.pop('error_map', {}))
api_version = '2021-10-30-preview'
content_type = kwargs.pop('content_type', 'application/json')
accept = 'application/json'
url = self.update.metadata['url']
path_format_arguments = {'subscriptionId': self._serialize.url('self._config.subscription_id', self._config.subscription_id, 'str'), 'groupName': self._serialize.url('group_name', group_name, 'str'), 'serviceName': self._serialize.url('service_name', service_name, 'str'), 'projectName': self._serialize.url('project_name', project_name, 'str'), 'taskName': self._serialize.url('task_name', task_name, 'str')}
url = self._client.format_url(url, **path_format_arguments)
query_parameters = {}
query_parameters['api-version'] = self._serialize.query('api_version', api_version, 'str')
header_parameters = {}
header_parameters['Content-Type'] = self._serialize.header('content_type', content_type, 'str')
header_parameters['Accept'] = self._serialize.header('accept', accept, 'str')
body_content_kwargs = {}
body_content = self._serialize.body(parameters, 'ProjectTask')
body_content_kwargs['content'] = body_content
request = self._client.patch(url, query_parameters, header_parameters, **body_content_kwargs)
pipeline_response = (await self._client._pipeline.run(request, stream=False, **kwargs))
response = pipeline_response.http_response
if (response.status_code not in [200]):
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize(models.ApiError, response)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
deserialized = self._deserialize('ProjectTask', pipeline_response)
if cls:
return cls(pipeline_response, deserialized, {})
return deserialized |
async def cancel(self, group_name: str, service_name: str, project_name: str, task_name: str, **kwargs) -> 'models.ProjectTask':
"Cancel a task.\n\n The tasks resource is a nested, proxy-only resource representing work performed by a DMS\n instance. This method cancels a task if it's currently queued or running.\n\n :param group_name: Name of the resource group.\n :type group_name: str\n :param service_name: Name of the service.\n :type service_name: str\n :param project_name: Name of the project.\n :type project_name: str\n :param task_name: Name of the Task.\n :type task_name: str\n :keyword callable cls: A custom type or function that will be passed the direct response\n :return: ProjectTask, or the result of cls(response)\n :rtype: ~azure.mgmt.datamigration.models.ProjectTask\n :raises: ~azure.core.exceptions.HttpResponseError\n "
cls = kwargs.pop('cls', None)
error_map = {401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError}
error_map.update(kwargs.pop('error_map', {}))
api_version = '2021-10-30-preview'
accept = 'application/json'
url = self.cancel.metadata['url']
path_format_arguments = {'subscriptionId': self._serialize.url('self._config.subscription_id', self._config.subscription_id, 'str'), 'groupName': self._serialize.url('group_name', group_name, 'str'), 'serviceName': self._serialize.url('service_name', service_name, 'str'), 'projectName': self._serialize.url('project_name', project_name, 'str'), 'taskName': self._serialize.url('task_name', task_name, 'str')}
url = self._client.format_url(url, **path_format_arguments)
query_parameters = {}
query_parameters['api-version'] = self._serialize.query('api_version', api_version, 'str')
header_parameters = {}
header_parameters['Accept'] = self._serialize.header('accept', accept, 'str')
request = self._client.post(url, query_parameters, header_parameters)
pipeline_response = (await self._client._pipeline.run(request, stream=False, **kwargs))
response = pipeline_response.http_response
if (response.status_code not in [200]):
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize(models.ApiError, response)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
deserialized = self._deserialize('ProjectTask', pipeline_response)
if cls:
return cls(pipeline_response, deserialized, {})
return deserialized | 9,121,790,174,815,307,000 | Cancel a task.
The tasks resource is a nested, proxy-only resource representing work performed by a DMS
instance. This method cancels a task if it's currently queued or running.
:param group_name: Name of the resource group.
:type group_name: str
:param service_name: Name of the service.
:type service_name: str
:param project_name: Name of the project.
:type project_name: str
:param task_name: Name of the Task.
:type task_name: str
:keyword callable cls: A custom type or function that will be passed the direct response
:return: ProjectTask, or the result of cls(response)
:rtype: ~azure.mgmt.datamigration.models.ProjectTask
:raises: ~azure.core.exceptions.HttpResponseError | src/datamigration/azext_datamigration/vendored_sdks/datamigration/aio/operations/_tasks_operations.py | cancel | Hamster-Huey/azure-cli-extensions | python | async def cancel(self, group_name: str, service_name: str, project_name: str, task_name: str, **kwargs) -> 'models.ProjectTask':
"Cancel a task.\n\n The tasks resource is a nested, proxy-only resource representing work performed by a DMS\n instance. This method cancels a task if it's currently queued or running.\n\n :param group_name: Name of the resource group.\n :type group_name: str\n :param service_name: Name of the service.\n :type service_name: str\n :param project_name: Name of the project.\n :type project_name: str\n :param task_name: Name of the Task.\n :type task_name: str\n :keyword callable cls: A custom type or function that will be passed the direct response\n :return: ProjectTask, or the result of cls(response)\n :rtype: ~azure.mgmt.datamigration.models.ProjectTask\n :raises: ~azure.core.exceptions.HttpResponseError\n "
cls = kwargs.pop('cls', None)
error_map = {401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError}
error_map.update(kwargs.pop('error_map', {}))
api_version = '2021-10-30-preview'
accept = 'application/json'
url = self.cancel.metadata['url']
path_format_arguments = {'subscriptionId': self._serialize.url('self._config.subscription_id', self._config.subscription_id, 'str'), 'groupName': self._serialize.url('group_name', group_name, 'str'), 'serviceName': self._serialize.url('service_name', service_name, 'str'), 'projectName': self._serialize.url('project_name', project_name, 'str'), 'taskName': self._serialize.url('task_name', task_name, 'str')}
url = self._client.format_url(url, **path_format_arguments)
query_parameters = {}
query_parameters['api-version'] = self._serialize.query('api_version', api_version, 'str')
header_parameters = {}
header_parameters['Accept'] = self._serialize.header('accept', accept, 'str')
request = self._client.post(url, query_parameters, header_parameters)
pipeline_response = (await self._client._pipeline.run(request, stream=False, **kwargs))
response = pipeline_response.http_response
if (response.status_code not in [200]):
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize(models.ApiError, response)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
deserialized = self._deserialize('ProjectTask', pipeline_response)
if cls:
return cls(pipeline_response, deserialized, {})
return deserialized |
async def command(self, group_name: str, service_name: str, project_name: str, task_name: str, parameters: 'models.CommandProperties', **kwargs) -> 'models.CommandProperties':
'Execute a command on a task.\n\n The tasks resource is a nested, proxy-only resource representing work performed by a DMS\n instance. This method executes a command on a running task.\n\n :param group_name: Name of the resource group.\n :type group_name: str\n :param service_name: Name of the service.\n :type service_name: str\n :param project_name: Name of the project.\n :type project_name: str\n :param task_name: Name of the Task.\n :type task_name: str\n :param parameters: Command to execute.\n :type parameters: ~azure.mgmt.datamigration.models.CommandProperties\n :keyword callable cls: A custom type or function that will be passed the direct response\n :return: CommandProperties, or the result of cls(response)\n :rtype: ~azure.mgmt.datamigration.models.CommandProperties\n :raises: ~azure.core.exceptions.HttpResponseError\n '
cls = kwargs.pop('cls', None)
error_map = {401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError}
error_map.update(kwargs.pop('error_map', {}))
api_version = '2021-10-30-preview'
content_type = kwargs.pop('content_type', 'application/json')
accept = 'application/json'
url = self.command.metadata['url']
path_format_arguments = {'subscriptionId': self._serialize.url('self._config.subscription_id', self._config.subscription_id, 'str'), 'groupName': self._serialize.url('group_name', group_name, 'str'), 'serviceName': self._serialize.url('service_name', service_name, 'str'), 'projectName': self._serialize.url('project_name', project_name, 'str'), 'taskName': self._serialize.url('task_name', task_name, 'str')}
url = self._client.format_url(url, **path_format_arguments)
query_parameters = {}
query_parameters['api-version'] = self._serialize.query('api_version', api_version, 'str')
header_parameters = {}
header_parameters['Content-Type'] = self._serialize.header('content_type', content_type, 'str')
header_parameters['Accept'] = self._serialize.header('accept', accept, 'str')
body_content_kwargs = {}
body_content = self._serialize.body(parameters, 'CommandProperties')
body_content_kwargs['content'] = body_content
request = self._client.post(url, query_parameters, header_parameters, **body_content_kwargs)
pipeline_response = (await self._client._pipeline.run(request, stream=False, **kwargs))
response = pipeline_response.http_response
if (response.status_code not in [200]):
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize(models.ApiError, response)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
deserialized = self._deserialize('CommandProperties', pipeline_response)
if cls:
return cls(pipeline_response, deserialized, {})
return deserialized | 6,424,933,398,628,367,000 | Execute a command on a task.
The tasks resource is a nested, proxy-only resource representing work performed by a DMS
instance. This method executes a command on a running task.
:param group_name: Name of the resource group.
:type group_name: str
:param service_name: Name of the service.
:type service_name: str
:param project_name: Name of the project.
:type project_name: str
:param task_name: Name of the Task.
:type task_name: str
:param parameters: Command to execute.
:type parameters: ~azure.mgmt.datamigration.models.CommandProperties
:keyword callable cls: A custom type or function that will be passed the direct response
:return: CommandProperties, or the result of cls(response)
:rtype: ~azure.mgmt.datamigration.models.CommandProperties
:raises: ~azure.core.exceptions.HttpResponseError | src/datamigration/azext_datamigration/vendored_sdks/datamigration/aio/operations/_tasks_operations.py | command | Hamster-Huey/azure-cli-extensions | python | async def command(self, group_name: str, service_name: str, project_name: str, task_name: str, parameters: 'models.CommandProperties', **kwargs) -> 'models.CommandProperties':
'Execute a command on a task.\n\n The tasks resource is a nested, proxy-only resource representing work performed by a DMS\n instance. This method executes a command on a running task.\n\n :param group_name: Name of the resource group.\n :type group_name: str\n :param service_name: Name of the service.\n :type service_name: str\n :param project_name: Name of the project.\n :type project_name: str\n :param task_name: Name of the Task.\n :type task_name: str\n :param parameters: Command to execute.\n :type parameters: ~azure.mgmt.datamigration.models.CommandProperties\n :keyword callable cls: A custom type or function that will be passed the direct response\n :return: CommandProperties, or the result of cls(response)\n :rtype: ~azure.mgmt.datamigration.models.CommandProperties\n :raises: ~azure.core.exceptions.HttpResponseError\n '
cls = kwargs.pop('cls', None)
error_map = {401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError}
error_map.update(kwargs.pop('error_map', {}))
api_version = '2021-10-30-preview'
content_type = kwargs.pop('content_type', 'application/json')
accept = 'application/json'
url = self.command.metadata['url']
path_format_arguments = {'subscriptionId': self._serialize.url('self._config.subscription_id', self._config.subscription_id, 'str'), 'groupName': self._serialize.url('group_name', group_name, 'str'), 'serviceName': self._serialize.url('service_name', service_name, 'str'), 'projectName': self._serialize.url('project_name', project_name, 'str'), 'taskName': self._serialize.url('task_name', task_name, 'str')}
url = self._client.format_url(url, **path_format_arguments)
query_parameters = {}
query_parameters['api-version'] = self._serialize.query('api_version', api_version, 'str')
header_parameters = {}
header_parameters['Content-Type'] = self._serialize.header('content_type', content_type, 'str')
header_parameters['Accept'] = self._serialize.header('accept', accept, 'str')
body_content_kwargs = {}
body_content = self._serialize.body(parameters, 'CommandProperties')
body_content_kwargs['content'] = body_content
request = self._client.post(url, query_parameters, header_parameters, **body_content_kwargs)
pipeline_response = (await self._client._pipeline.run(request, stream=False, **kwargs))
response = pipeline_response.http_response
if (response.status_code not in [200]):
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize(models.ApiError, response)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
deserialized = self._deserialize('CommandProperties', pipeline_response)
if cls:
return cls(pipeline_response, deserialized, {})
return deserialized |
def _maybe_create_dir(path):
"Create directory (and parents) if they don't exist."
try:
os.makedirs(path)
except OSError:
if (not os.path.isdir(path)):
raise | 6,105,453,633,667,462,000 | Create directory (and parents) if they don't exist. | parcels/scripts/get_examples.py | _maybe_create_dir | becgorton/parcels | python | def _maybe_create_dir(path):
try:
os.makedirs(path)
except OSError:
if (not os.path.isdir(path)):
raise |
def copy_data_and_examples_from_package_to(target_path):
'Copy example data from Parcels directory.\n\n Return thos parths of the list `file_names` that were not found in the\n package.\n\n '
examples_in_package = pkg_resources.resource_filename('parcels', 'examples')
try:
shutil.copytree(examples_in_package, target_path)
except Exception as e:
print(e)
pass | 7,610,559,079,219,055,000 | Copy example data from Parcels directory.
Return thos parths of the list `file_names` that were not found in the
package. | parcels/scripts/get_examples.py | copy_data_and_examples_from_package_to | becgorton/parcels | python | def copy_data_and_examples_from_package_to(target_path):
'Copy example data from Parcels directory.\n\n Return thos parths of the list `file_names` that were not found in the\n package.\n\n '
examples_in_package = pkg_resources.resource_filename('parcels', 'examples')
try:
shutil.copytree(examples_in_package, target_path)
except Exception as e:
print(e)
pass |
def set_jupyter_kernel_to_python_version(path, python_version=2):
'Set notebook kernelspec to desired python version.\n\n This also drops all other meta data from the notebook.\n '
for file_name in glob(os.path.join(path, '*.ipynb')):
with open(file_name, 'r') as f:
notebook_data = json.load(f)
notebook_data['metadata'] = {'kernelspec': {'display_name': 'Python {}'.format(python_version), 'language': 'python', 'name': 'python{}'.format(python_version)}}
with open(file_name, 'w') as f:
json.dump(notebook_data, f, indent=2) | 1,613,269,214,994,440,000 | Set notebook kernelspec to desired python version.
This also drops all other meta data from the notebook. | parcels/scripts/get_examples.py | set_jupyter_kernel_to_python_version | becgorton/parcels | python | def set_jupyter_kernel_to_python_version(path, python_version=2):
'Set notebook kernelspec to desired python version.\n\n This also drops all other meta data from the notebook.\n '
for file_name in glob(os.path.join(path, '*.ipynb')):
with open(file_name, 'r') as f:
notebook_data = json.load(f)
notebook_data['metadata'] = {'kernelspec': {'display_name': 'Python {}'.format(python_version), 'language': 'python', 'name': 'python{}'.format(python_version)}}
with open(file_name, 'w') as f:
json.dump(notebook_data, f, indent=2) |
def _still_to_download(file_names, target_path):
'Only return the files that are not yet present on disk.'
for fn in list(file_names):
if os.path.exists(os.path.join(target_path, fn)):
file_names.remove(fn)
return file_names | 8,455,357,851,695,611,000 | Only return the files that are not yet present on disk. | parcels/scripts/get_examples.py | _still_to_download | becgorton/parcels | python | def _still_to_download(file_names, target_path):
for fn in list(file_names):
if os.path.exists(os.path.join(target_path, fn)):
file_names.remove(fn)
return file_names |
def download_files(source_url, file_names, target_path):
'Mirror file_names from source_url to target_path.'
_maybe_create_dir(target_path)
pbar = ProgressBar()
print(('Downloading %s ...' % source_url.split('/')[(- 1)]))
for filename in pbar(file_names):
_maybe_create_dir(os.path.join(target_path, os.path.dirname(filename)))
if (not os.path.exists(os.path.join(target_path, filename))):
download_url = ((source_url + '/') + filename)
src = urlopen(download_url)
with open(os.path.join(target_path, filename), 'wb') as dst:
dst.write(src.read()) | -9,082,911,184,324,230,000 | Mirror file_names from source_url to target_path. | parcels/scripts/get_examples.py | download_files | becgorton/parcels | python | def download_files(source_url, file_names, target_path):
_maybe_create_dir(target_path)
pbar = ProgressBar()
print(('Downloading %s ...' % source_url.split('/')[(- 1)]))
for filename in pbar(file_names):
_maybe_create_dir(os.path.join(target_path, os.path.dirname(filename)))
if (not os.path.exists(os.path.join(target_path, filename))):
download_url = ((source_url + '/') + filename)
src = urlopen(download_url)
with open(os.path.join(target_path, filename), 'wb') as dst:
dst.write(src.read()) |
def main(target_path=None):
'Get example scripts, example notebooks, and example data.\n\n Copy the examples from the package directory and get the example data either\n from the package directory or from the Parcels website.\n '
if (target_path is None):
parser = argparse.ArgumentParser(description='Get Parcels example data.')
parser.add_argument('target_path', help='Where to put the tutorials? (This path will be created.)')
args = parser.parse_args()
target_path = args.target_path
if os.path.exists(target_path):
print('Error: {} already exists.'.format(target_path))
return
copy_data_and_examples_from_package_to(target_path)
set_jupyter_kernel_to_python_version(target_path, python_version=sys.version_info[0])
remaining_example_data_files = _still_to_download(example_data_files, target_path)
download_files(example_data_url, remaining_example_data_files, target_path) | 37,062,962,504,163,710 | Get example scripts, example notebooks, and example data.
Copy the examples from the package directory and get the example data either
from the package directory or from the Parcels website. | parcels/scripts/get_examples.py | main | becgorton/parcels | python | def main(target_path=None):
'Get example scripts, example notebooks, and example data.\n\n Copy the examples from the package directory and get the example data either\n from the package directory or from the Parcels website.\n '
if (target_path is None):
parser = argparse.ArgumentParser(description='Get Parcels example data.')
parser.add_argument('target_path', help='Where to put the tutorials? (This path will be created.)')
args = parser.parse_args()
target_path = args.target_path
if os.path.exists(target_path):
print('Error: {} already exists.'.format(target_path))
return
copy_data_and_examples_from_package_to(target_path)
set_jupyter_kernel_to_python_version(target_path, python_version=sys.version_info[0])
remaining_example_data_files = _still_to_download(example_data_files, target_path)
download_files(example_data_url, remaining_example_data_files, target_path) |
def _WatchBucket(self):
'Creates a watch on a bucket given in self.args.'
self.CheckArguments()
identifier = None
client_token = None
if self.sub_opts:
for (o, a) in self.sub_opts:
if (o == '-i'):
identifier = a
if (o == '-t'):
client_token = a
identifier = (identifier or str(uuid.uuid4()))
watch_url = self.args[0]
bucket_arg = self.args[(- 1)]
if (not watch_url.lower().startswith('https://')):
raise CommandException('The application URL must be an https:// URL.')
bucket_url = StorageUrlFromString(bucket_arg)
if (not (bucket_url.IsBucket() and (bucket_url.scheme == 'gs'))):
raise CommandException(('The %s command can only be used with gs:// bucket URLs.' % self.command_name))
if (not bucket_url.IsBucket()):
raise CommandException(('URL must name a bucket for the %s command.' % self.command_name))
self.logger.info('Watching bucket %s with application URL %s ...', bucket_url, watch_url)
try:
channel = self.gsutil_api.WatchBucket(bucket_url.bucket_name, watch_url, identifier, token=client_token, provider=bucket_url.scheme)
except AccessDeniedException as e:
self.logger.warn(NOTIFICATION_AUTHORIZATION_FAILED_MESSAGE.format(watch_error=str(e), watch_url=watch_url))
raise
channel_id = channel.id
resource_id = channel.resourceId
client_token = channel.token
self.logger.info('Successfully created watch notification channel.')
self.logger.info('Watch channel identifier: %s', channel_id)
self.logger.info('Canonicalized resource identifier: %s', resource_id)
self.logger.info('Client state token: %s', client_token)
return 0 | -8,251,014,348,727,324,000 | Creates a watch on a bucket given in self.args. | gslib/commands/notification.py | _WatchBucket | BobiGilburd/gsutil | python | def _WatchBucket(self):
self.CheckArguments()
identifier = None
client_token = None
if self.sub_opts:
for (o, a) in self.sub_opts:
if (o == '-i'):
identifier = a
if (o == '-t'):
client_token = a
identifier = (identifier or str(uuid.uuid4()))
watch_url = self.args[0]
bucket_arg = self.args[(- 1)]
if (not watch_url.lower().startswith('https://')):
raise CommandException('The application URL must be an https:// URL.')
bucket_url = StorageUrlFromString(bucket_arg)
if (not (bucket_url.IsBucket() and (bucket_url.scheme == 'gs'))):
raise CommandException(('The %s command can only be used with gs:// bucket URLs.' % self.command_name))
if (not bucket_url.IsBucket()):
raise CommandException(('URL must name a bucket for the %s command.' % self.command_name))
self.logger.info('Watching bucket %s with application URL %s ...', bucket_url, watch_url)
try:
channel = self.gsutil_api.WatchBucket(bucket_url.bucket_name, watch_url, identifier, token=client_token, provider=bucket_url.scheme)
except AccessDeniedException as e:
self.logger.warn(NOTIFICATION_AUTHORIZATION_FAILED_MESSAGE.format(watch_error=str(e), watch_url=watch_url))
raise
channel_id = channel.id
resource_id = channel.resourceId
client_token = channel.token
self.logger.info('Successfully created watch notification channel.')
self.logger.info('Watch channel identifier: %s', channel_id)
self.logger.info('Canonicalized resource identifier: %s', resource_id)
self.logger.info('Client state token: %s', client_token)
return 0 |
def _ListChannels(self, bucket_arg):
'Lists active channel watches on a bucket given in self.args.'
bucket_url = StorageUrlFromString(bucket_arg)
if (not (bucket_url.IsBucket() and (bucket_url.scheme == 'gs'))):
raise CommandException(('The %s command can only be used with gs:// bucket URLs.' % self.command_name))
if (not bucket_url.IsBucket()):
raise CommandException(('URL must name a bucket for the %s command.' % self.command_name))
channels = self.gsutil_api.ListChannels(bucket_url.bucket_name, provider='gs').items
self.logger.info('Bucket %s has the following active Object Change Notifications:', bucket_url.bucket_name)
for (idx, channel) in enumerate(channels):
self.logger.info('\tNotification channel %d:', (idx + 1))
self.logger.info('\t\tChannel identifier: %s', channel.channel_id)
self.logger.info('\t\tResource identifier: %s', channel.resource_id)
self.logger.info('\t\tApplication URL: %s', channel.push_url)
self.logger.info('\t\tCreated by: %s', channel.subscriber_email)
self.logger.info('\t\tCreation time: %s', str(datetime.fromtimestamp((channel.creation_time_ms / 1000))))
return 0 | 6,163,886,225,114,070,000 | Lists active channel watches on a bucket given in self.args. | gslib/commands/notification.py | _ListChannels | BobiGilburd/gsutil | python | def _ListChannels(self, bucket_arg):
bucket_url = StorageUrlFromString(bucket_arg)
if (not (bucket_url.IsBucket() and (bucket_url.scheme == 'gs'))):
raise CommandException(('The %s command can only be used with gs:// bucket URLs.' % self.command_name))
if (not bucket_url.IsBucket()):
raise CommandException(('URL must name a bucket for the %s command.' % self.command_name))
channels = self.gsutil_api.ListChannels(bucket_url.bucket_name, provider='gs').items
self.logger.info('Bucket %s has the following active Object Change Notifications:', bucket_url.bucket_name)
for (idx, channel) in enumerate(channels):
self.logger.info('\tNotification channel %d:', (idx + 1))
self.logger.info('\t\tChannel identifier: %s', channel.channel_id)
self.logger.info('\t\tResource identifier: %s', channel.resource_id)
self.logger.info('\t\tApplication URL: %s', channel.push_url)
self.logger.info('\t\tCreated by: %s', channel.subscriber_email)
self.logger.info('\t\tCreation time: %s', str(datetime.fromtimestamp((channel.creation_time_ms / 1000))))
return 0 |
def _CreateTopic(self, pubsub_topic, service_account):
'Assures that a topic exists, creating it if necessary.\n\n Also adds GCS as a publisher on that bucket, if necessary.\n\n Args:\n pubsub_topic: name of the Cloud Pub/Sub topic to use/create.\n service_account: the GCS service account that needs publish permission.\n\n Returns:\n true if we modified IAM permissions, otherwise false.\n '
pubsub_api = PubsubApi(logger=self.logger)
try:
pubsub_api.GetTopic(topic_name=pubsub_topic)
self.logger.debug('Topic %s already exists', pubsub_topic)
except NotFoundException:
self.logger.debug('Creating topic %s', pubsub_topic)
pubsub_api.CreateTopic(topic_name=pubsub_topic)
self.logger.info('Created Cloud Pub/Sub topic %s', pubsub_topic)
policy = pubsub_api.GetTopicIamPolicy(topic_name=pubsub_topic)
binding = Binding(role='roles/pubsub.publisher', members=[('serviceAccount:%s' % service_account)])
if (binding not in policy.bindings):
policy.bindings.append(binding)
pubsub_api.SetTopicIamPolicy(topic_name=pubsub_topic, policy=policy)
return True
else:
self.logger.debug('GCS already has publish permission to topic %s.', pubsub_topic)
return False | -5,651,226,351,373,527,000 | Assures that a topic exists, creating it if necessary.
Also adds GCS as a publisher on that bucket, if necessary.
Args:
pubsub_topic: name of the Cloud Pub/Sub topic to use/create.
service_account: the GCS service account that needs publish permission.
Returns:
true if we modified IAM permissions, otherwise false. | gslib/commands/notification.py | _CreateTopic | BobiGilburd/gsutil | python | def _CreateTopic(self, pubsub_topic, service_account):
'Assures that a topic exists, creating it if necessary.\n\n Also adds GCS as a publisher on that bucket, if necessary.\n\n Args:\n pubsub_topic: name of the Cloud Pub/Sub topic to use/create.\n service_account: the GCS service account that needs publish permission.\n\n Returns:\n true if we modified IAM permissions, otherwise false.\n '
pubsub_api = PubsubApi(logger=self.logger)
try:
pubsub_api.GetTopic(topic_name=pubsub_topic)
self.logger.debug('Topic %s already exists', pubsub_topic)
except NotFoundException:
self.logger.debug('Creating topic %s', pubsub_topic)
pubsub_api.CreateTopic(topic_name=pubsub_topic)
self.logger.info('Created Cloud Pub/Sub topic %s', pubsub_topic)
policy = pubsub_api.GetTopicIamPolicy(topic_name=pubsub_topic)
binding = Binding(role='roles/pubsub.publisher', members=[('serviceAccount:%s' % service_account)])
if (binding not in policy.bindings):
policy.bindings.append(binding)
pubsub_api.SetTopicIamPolicy(topic_name=pubsub_topic, policy=policy)
return True
else:
self.logger.debug('GCS already has publish permission to topic %s.', pubsub_topic)
return False |
def _EnumerateNotificationsFromArgs(self, accept_notification_configs=True):
'Yields bucket/notification tuples from command-line args.\n\n Given a list of strings that are bucket names (gs://foo) or notification\n config IDs, yield tuples of bucket names and their associated notifications.\n\n Args:\n accept_notification_configs: whether notification configs are valid args.\n Yields:\n Tuples of the form (bucket_name, Notification)\n '
path_regex = self._GetNotificationPathRegex()
for list_entry in self.args:
match = path_regex.match(list_entry)
if match:
if (not accept_notification_configs):
raise CommandException(('%s %s accepts only bucket names, but you provided %s' % (self.command_name, self.subcommand_name, list_entry)))
bucket_name = match.group('bucket')
notification_id = match.group('notification')
found = False
for notification in self.gsutil_api.ListNotificationConfigs(bucket_name, provider='gs'):
if (notification.id == notification_id):
(yield (bucket_name, notification))
found = True
break
if (not found):
raise NotFoundException(('Could not find notification %s' % list_entry))
else:
storage_url = StorageUrlFromString(list_entry)
if (not storage_url.IsCloudUrl()):
raise CommandException(('The %s command must be used on cloud buckets or notification config names.' % self.command_name))
if (storage_url.scheme != 'gs'):
raise CommandException('The %s command only works on gs:// buckets.')
path = None
if storage_url.IsProvider():
path = 'gs://*'
elif storage_url.IsBucket():
path = list_entry
if (not path):
raise CommandException(('The %s command cannot be used on cloud objects, only buckets' % self.command_name))
for blr in self.WildcardIterator(path).IterBuckets(bucket_fields=['id']):
for notification in self.gsutil_api.ListNotificationConfigs(blr.storage_url.bucket_name, provider='gs'):
(yield (blr.storage_url.bucket_name, notification)) | -556,215,268,115,043,140 | Yields bucket/notification tuples from command-line args.
Given a list of strings that are bucket names (gs://foo) or notification
config IDs, yield tuples of bucket names and their associated notifications.
Args:
accept_notification_configs: whether notification configs are valid args.
Yields:
Tuples of the form (bucket_name, Notification) | gslib/commands/notification.py | _EnumerateNotificationsFromArgs | BobiGilburd/gsutil | python | def _EnumerateNotificationsFromArgs(self, accept_notification_configs=True):
'Yields bucket/notification tuples from command-line args.\n\n Given a list of strings that are bucket names (gs://foo) or notification\n config IDs, yield tuples of bucket names and their associated notifications.\n\n Args:\n accept_notification_configs: whether notification configs are valid args.\n Yields:\n Tuples of the form (bucket_name, Notification)\n '
path_regex = self._GetNotificationPathRegex()
for list_entry in self.args:
match = path_regex.match(list_entry)
if match:
if (not accept_notification_configs):
raise CommandException(('%s %s accepts only bucket names, but you provided %s' % (self.command_name, self.subcommand_name, list_entry)))
bucket_name = match.group('bucket')
notification_id = match.group('notification')
found = False
for notification in self.gsutil_api.ListNotificationConfigs(bucket_name, provider='gs'):
if (notification.id == notification_id):
(yield (bucket_name, notification))
found = True
break
if (not found):
raise NotFoundException(('Could not find notification %s' % list_entry))
else:
storage_url = StorageUrlFromString(list_entry)
if (not storage_url.IsCloudUrl()):
raise CommandException(('The %s command must be used on cloud buckets or notification config names.' % self.command_name))
if (storage_url.scheme != 'gs'):
raise CommandException('The %s command only works on gs:// buckets.')
path = None
if storage_url.IsProvider():
path = 'gs://*'
elif storage_url.IsBucket():
path = list_entry
if (not path):
raise CommandException(('The %s command cannot be used on cloud objects, only buckets' % self.command_name))
for blr in self.WildcardIterator(path).IterBuckets(bucket_fields=['id']):
for notification in self.gsutil_api.ListNotificationConfigs(blr.storage_url.bucket_name, provider='gs'):
(yield (blr.storage_url.bucket_name, notification)) |
def RunCommand(self):
'Command entry point for the notification command.'
self.subcommand_name = self.args.pop(0)
if (self.subcommand_name in NotificationCommand.SUBCOMMANDS):
metrics.LogCommandParams(subcommands=[self.subcommand_name])
return self._RunSubCommand(NotificationCommand.SUBCOMMANDS[self.subcommand_name])
else:
raise CommandException(('Invalid subcommand "%s" for the %s command.' % (self.subcommand_name, self.command_name))) | 5,564,108,628,043,477,000 | Command entry point for the notification command. | gslib/commands/notification.py | RunCommand | BobiGilburd/gsutil | python | def RunCommand(self):
self.subcommand_name = self.args.pop(0)
if (self.subcommand_name in NotificationCommand.SUBCOMMANDS):
metrics.LogCommandParams(subcommands=[self.subcommand_name])
return self._RunSubCommand(NotificationCommand.SUBCOMMANDS[self.subcommand_name])
else:
raise CommandException(('Invalid subcommand "%s" for the %s command.' % (self.subcommand_name, self.command_name))) |
def plot_plane(ax, distances: list, z_coords: list, label: str=None, decorate: bool=True, show_half: bool=False, **kwargs):
'\n Plot plane.\n\n Args:\n ax: matplotlib ax.\n distances (list): List of plane intervals.\n z_coords (list): List of z coordinate of each plane.\n label (str): Plot label.\n decorate (bool): If True, ax is decorated.\n show_half: If True, atom planes which are periodically equivalent are\n not showed.\n '
if decorate:
xlabel = 'Distance'
ylabel = 'Hight'
else:
xlabel = ylabel = None
_distances = deepcopy(distances)
_z_coords = deepcopy(z_coords)
_distances.insert(0, distances[(- 1)])
_distances.append(distances[0])
_z_coords.insert(0, (- distances[(- 1)]))
_z_coords.append((z_coords[(- 1)] + distances[0]))
c = np.sum(distances)
fixed_z_coords = ((_z_coords + (distances[0] / 2)) - (c / 2))
num = len(fixed_z_coords)
bulk_distance = _distances[int((num / 4))]
if show_half:
n = int(((num + 2) / 4))
_distances = _distances[n:(3 * n)]
fixed_z_coords = fixed_z_coords[n:(3 * n)]
line_chart(ax=ax, xdata=_distances, ydata=fixed_z_coords, xlabel=xlabel, ylabel=ylabel, label=label, sort_by='y', **kwargs)
if decorate:
xmin = (bulk_distance - 0.025)
xmax = (bulk_distance + 0.025)
if show_half:
ax.hlines(0, xmin=(xmin - 0.01), xmax=(xmax + 0.01), linestyle='--', color='k', linewidth=1.0)
else:
tb_idx = [1, int((num / 2)), (num - 1)]
for idx in tb_idx:
ax.hlines((fixed_z_coords[idx] - (distances[0] / 2)), xmin=(xmin - 0.01), xmax=(xmax + 0.01), linestyle='--', color='k', linewidth=1.0) | 4,762,202,496,574,044,000 | Plot plane.
Args:
ax: matplotlib ax.
distances (list): List of plane intervals.
z_coords (list): List of z coordinate of each plane.
label (str): Plot label.
decorate (bool): If True, ax is decorated.
show_half: If True, atom planes which are periodically equivalent are
not showed. | twinpy/plot/twinboundary.py | plot_plane | kei0822kei/twinpy | python | def plot_plane(ax, distances: list, z_coords: list, label: str=None, decorate: bool=True, show_half: bool=False, **kwargs):
'\n Plot plane.\n\n Args:\n ax: matplotlib ax.\n distances (list): List of plane intervals.\n z_coords (list): List of z coordinate of each plane.\n label (str): Plot label.\n decorate (bool): If True, ax is decorated.\n show_half: If True, atom planes which are periodically equivalent are\n not showed.\n '
if decorate:
xlabel = 'Distance'
ylabel = 'Hight'
else:
xlabel = ylabel = None
_distances = deepcopy(distances)
_z_coords = deepcopy(z_coords)
_distances.insert(0, distances[(- 1)])
_distances.append(distances[0])
_z_coords.insert(0, (- distances[(- 1)]))
_z_coords.append((z_coords[(- 1)] + distances[0]))
c = np.sum(distances)
fixed_z_coords = ((_z_coords + (distances[0] / 2)) - (c / 2))
num = len(fixed_z_coords)
bulk_distance = _distances[int((num / 4))]
if show_half:
n = int(((num + 2) / 4))
_distances = _distances[n:(3 * n)]
fixed_z_coords = fixed_z_coords[n:(3 * n)]
line_chart(ax=ax, xdata=_distances, ydata=fixed_z_coords, xlabel=xlabel, ylabel=ylabel, label=label, sort_by='y', **kwargs)
if decorate:
xmin = (bulk_distance - 0.025)
xmax = (bulk_distance + 0.025)
if show_half:
ax.hlines(0, xmin=(xmin - 0.01), xmax=(xmax + 0.01), linestyle='--', color='k', linewidth=1.0)
else:
tb_idx = [1, int((num / 2)), (num - 1)]
for idx in tb_idx:
ax.hlines((fixed_z_coords[idx] - (distances[0] / 2)), xmin=(xmin - 0.01), xmax=(xmax + 0.01), linestyle='--', color='k', linewidth=1.0) |
def plot_angle(ax, angles: list, z_coords: list, label: str=None, decorate: bool=True):
'\n Plot angle.\n\n Args:\n ax: matplotlib ax.\n z_coords (list): List of z coordinate of each plane.\n label (str): Plot label.\n decorate (bool): If True, ax is decorated.\n '
if decorate:
xlabel = 'Angle'
ylabel = 'Hight'
else:
xlabel = ylabel = None
_angles = deepcopy(angles)
_z_coords = deepcopy(z_coords)
_angles.append(angles[0])
_z_coords.append((z_coords[(- 1)] + z_coords[1]))
line_chart(ax=ax, xdata=_angles, ydata=_z_coords, xlabel=xlabel, ylabel=ylabel, label=label, sort_by='y')
if decorate:
num = len(_z_coords)
tb_idx = [0, int((num / 2)), (num - 1)]
bulk_angle = angles[int((num / 4))]
for idx in tb_idx:
ax.hlines(_z_coords[idx], xmin=(- 1), xmax=(bulk_angle + 2), linestyle='--', linewidth=1.5) | 8,997,156,145,619,759,000 | Plot angle.
Args:
ax: matplotlib ax.
z_coords (list): List of z coordinate of each plane.
label (str): Plot label.
decorate (bool): If True, ax is decorated. | twinpy/plot/twinboundary.py | plot_angle | kei0822kei/twinpy | python | def plot_angle(ax, angles: list, z_coords: list, label: str=None, decorate: bool=True):
'\n Plot angle.\n\n Args:\n ax: matplotlib ax.\n z_coords (list): List of z coordinate of each plane.\n label (str): Plot label.\n decorate (bool): If True, ax is decorated.\n '
if decorate:
xlabel = 'Angle'
ylabel = 'Hight'
else:
xlabel = ylabel = None
_angles = deepcopy(angles)
_z_coords = deepcopy(z_coords)
_angles.append(angles[0])
_z_coords.append((z_coords[(- 1)] + z_coords[1]))
line_chart(ax=ax, xdata=_angles, ydata=_z_coords, xlabel=xlabel, ylabel=ylabel, label=label, sort_by='y')
if decorate:
num = len(_z_coords)
tb_idx = [0, int((num / 2)), (num - 1)]
bulk_angle = angles[int((num / 4))]
for idx in tb_idx:
ax.hlines(_z_coords[idx], xmin=(- 1), xmax=(bulk_angle + 2), linestyle='--', linewidth=1.5) |
def plot_pair_distance(ax, pair_distances: list, z_coords: list, label: str=None, decorate: bool=True):
'\n Plot angle.\n\n Args:\n ax: matplotlib ax.\n pair_distances (list): List of A-B pair distances, which is originally\n primitive pair in HCP structure.\n z_coords (list): List of z coordinate of each plane.\n label (str): Plot label.\n decorate (bool): If True, ax is decorated.\n '
if decorate:
xlabel = 'Pair Distance'
ylabel = 'Hight'
else:
xlabel = ylabel = None
_pair_distances = deepcopy(pair_distances)
_z_coords = deepcopy(z_coords)
_pair_distances.append(pair_distances[0])
_z_coords.append((z_coords[(- 1)] + z_coords[1]))
line_chart(ax=ax, xdata=_pair_distances, ydata=_z_coords, xlabel=xlabel, ylabel=ylabel, label=label, sort_by='y')
if decorate:
num = len(_z_coords)
tb_idx = [0, int((num / 2)), (num - 1)]
bulk_pair_distance = pair_distances[int((num / 4))]
for idx in tb_idx:
ax.hlines(_z_coords[idx], xmin=(- 1), xmax=(bulk_pair_distance + 2), linestyle='--', linewidth=1.5) | 999,060,658,695,816,800 | Plot angle.
Args:
ax: matplotlib ax.
pair_distances (list): List of A-B pair distances, which is originally
primitive pair in HCP structure.
z_coords (list): List of z coordinate of each plane.
label (str): Plot label.
decorate (bool): If True, ax is decorated. | twinpy/plot/twinboundary.py | plot_pair_distance | kei0822kei/twinpy | python | def plot_pair_distance(ax, pair_distances: list, z_coords: list, label: str=None, decorate: bool=True):
'\n Plot angle.\n\n Args:\n ax: matplotlib ax.\n pair_distances (list): List of A-B pair distances, which is originally\n primitive pair in HCP structure.\n z_coords (list): List of z coordinate of each plane.\n label (str): Plot label.\n decorate (bool): If True, ax is decorated.\n '
if decorate:
xlabel = 'Pair Distance'
ylabel = 'Hight'
else:
xlabel = ylabel = None
_pair_distances = deepcopy(pair_distances)
_z_coords = deepcopy(z_coords)
_pair_distances.append(pair_distances[0])
_z_coords.append((z_coords[(- 1)] + z_coords[1]))
line_chart(ax=ax, xdata=_pair_distances, ydata=_z_coords, xlabel=xlabel, ylabel=ylabel, label=label, sort_by='y')
if decorate:
num = len(_z_coords)
tb_idx = [0, int((num / 2)), (num - 1)]
bulk_pair_distance = pair_distances[int((num / 4))]
for idx in tb_idx:
ax.hlines(_z_coords[idx], xmin=(- 1), xmax=(bulk_pair_distance + 2), linestyle='--', linewidth=1.5) |
def single_gpu_test(model, data_loader):
' Test model with single GPU, used for visualization.\n\n Args:\n model (nn.Module): Model to be tested.\n data_loader (nn.Dataloader): Pytorch data loader.\n\n Returns:\n dict: test results\n '
model.eval()
results = dict()
results['texts'] = []
results['img_info'] = []
results['glimpses'] = []
results['scores'] = []
dataset = data_loader.dataset
prog_bar = mmcv.ProgressBar(len(dataset))
for (i, data) in enumerate(data_loader):
with torch.no_grad():
result = model(return_loss=False, rescale=True, **data)
texts = result['text']
glimpses = result['glimpses']
glimpses = glimpses.cpu().numpy()
img_infos = result['img_info']
scores = result['scores']
scores = scores.cpu().numpy()
scores = scores.reshape((- 1))
batch_size = len(texts)
results['texts'].extend(texts)
results['img_info'].extend(img_infos)
results['glimpses'].extend(glimpses)
results['scores'].extend(scores)
for _ in range(batch_size):
prog_bar.update()
new_glimpse = np.stack(results['glimpses'])
results['glimpses'] = new_glimpse
return results | -7,651,348,466,465,535,000 | Test model with single GPU, used for visualization.
Args:
model (nn.Module): Model to be tested.
data_loader (nn.Dataloader): Pytorch data loader.
Returns:
dict: test results | davarocr/davarocr/davar_videotext/apis/test.py | single_gpu_test | hikopensource/DAVAR-Lab-OCR | python | def single_gpu_test(model, data_loader):
' Test model with single GPU, used for visualization.\n\n Args:\n model (nn.Module): Model to be tested.\n data_loader (nn.Dataloader): Pytorch data loader.\n\n Returns:\n dict: test results\n '
model.eval()
results = dict()
results['texts'] = []
results['img_info'] = []
results['glimpses'] = []
results['scores'] = []
dataset = data_loader.dataset
prog_bar = mmcv.ProgressBar(len(dataset))
for (i, data) in enumerate(data_loader):
with torch.no_grad():
result = model(return_loss=False, rescale=True, **data)
texts = result['text']
glimpses = result['glimpses']
glimpses = glimpses.cpu().numpy()
img_infos = result['img_info']
scores = result['scores']
scores = scores.cpu().numpy()
scores = scores.reshape((- 1))
batch_size = len(texts)
results['texts'].extend(texts)
results['img_info'].extend(img_infos)
results['glimpses'].extend(glimpses)
results['scores'].extend(scores)
for _ in range(batch_size):
prog_bar.update()
new_glimpse = np.stack(results['glimpses'])
results['glimpses'] = new_glimpse
return results |
def mms_load_fpi_calc_pad(probe='1', level='sitl', datatype='', data_rate='', suffix='', autoscale=True):
"\n Calculates the omni-directional pitch angle distribution (summed and averaged)\n from the individual tplot variables\n \n Parameters:\n probe: str \n probe, valid values for MMS probes are ['1','2','3','4']. \n\n level: str\n indicates level of data processing. the default if no level is specified is 'sitl'\n\n datatype: str\n Valid datatypes for FPI are:\n Quicklook: ['des', 'dis'] \n SITL: '' (none; loads both electron and ion data from single CDF)\n L1b/L2: ['des-dist', 'dis-dist', 'dis-moms', 'des-moms']\n\n data_rate: str\n instrument data rates for FPI include 'brst' and 'fast'. The\n default is 'fast'.\n\n suffix: str\n The tplot variable names will be given this suffix. By default, \n no suffix is added.\n\n autoscale: bool\n If set, use the default zrange; otherwise, use the min and max of the data for the zrange\n\n Returns:\n List of tplot variables created.\n\n "
out_vars = []
if isinstance(datatype, str):
if ((datatype == '*') or (datatype == '')):
if (level.lower() == 'ql'):
datatype = ['des', 'dis']
else:
datatype = ['des-dist', 'dis-dist']
if isinstance(datatype, str):
datatype = [datatype]
for dtype in datatype:
species = dtype[1]
if (level.lower() == 'sitl'):
spec_str_format = 'PitchAngDist'
obs_str_format = ('_fpi_' + species)
else:
spec_str_format = 'pitchAngDist'
obs_str_format = (('_d' + species) + 's_')
obsstr = (('mms' + str(probe)) + obs_str_format)
if (level.lower() == 'l2'):
spec_str_format = 'pitchangdist'
pad_vars = [((((((obsstr + spec_str_format) + '_') + erange) + 'en_') + data_rate) + suffix) for erange in ['low', 'mid', 'high']]
else:
pad_vars = [(((((obsstr + spec_str_format) + '_') + erange) + 'En') + suffix) for erange in ['low', 'mid', 'high']]
pad_avg_name = ((obsstr + 'PitchAngDist_avg') + suffix)
low_en = get_data(pad_vars[0])
mid_en = get_data(pad_vars[1])
high_en = get_data(pad_vars[2])
if ((low_en is None) or (mid_en is None) or (high_en is None)):
v3_low_pad = tnames(((pad_vars[0].lower() + '_') + data_rate))
v3_mid_pad = tnames(((pad_vars[1].lower() + '_') + data_rate))
v3_high_pad = tnames(((pad_vars[2].lower() + '_') + data_rate))
if ((v3_low_pad == []) or (v3_mid_pad == []) or (v3_high_pad == [])):
continue
low_en = get_data(v3_low_pad[0])
mid_en = get_data(v3_mid_pad[0])
high_en = get_data(v3_high_pad[0])
pad_avg_name = pad_avg_name.lower()
e_pad_sum = ((low_en.y + mid_en.y) + high_en.y)
e_pad_avg = (e_pad_sum / 3.0)
if (level == 'l2'):
pad_avg_name = pad_avg_name.lower()
if (species == 'e'):
species_str = 'electron'
elif (species == 'i'):
species_str = 'ion'
if (level == 'ql'):
store_data(((obsstr + 'PitchAngDist_sum') + suffix), data={'x': low_en.times, 'y': e_pad_sum, 'v': low_en.v})
options(((obsstr + 'PitchAngDist_sum') + suffix), 'ytitle', (((('MMS' + str(probe)) + ' \\ ') + species_str) + ' \\ PAD \\ SUM'))
options(((obsstr + 'PitchAngDist_sum') + suffix), 'yrange', [0, 180])
options(((obsstr + 'PitchAngDist_sum') + suffix), 'zlog', True)
options(((obsstr + 'PitchAngDist_sum') + suffix), 'spec', True)
options(((obsstr + 'PitchAngDist_sum') + suffix), 'Colormap', 'jet')
out_vars.append(((obsstr + 'PitchAngDist_sum') + suffix))
store_data(pad_avg_name, data={'x': low_en.times, 'y': e_pad_avg, 'v': low_en.v})
options(pad_avg_name, 'ztitle', 'eV/(cm!U2!N s sr eV)')
options(pad_avg_name, 'ytitle', (((('MMS' + str(probe)) + ' \\ ') + species_str) + ' \\ PAD \\ AVG'))
options(pad_avg_name, 'yrange', [0, 180])
options(pad_avg_name, 'zlog', True)
options(pad_avg_name, 'spec', True)
options(pad_avg_name, 'Colormap', 'jet')
out_vars.append(pad_avg_name)
return out_vars | -5,691,318,386,164,602,000 | Calculates the omni-directional pitch angle distribution (summed and averaged)
from the individual tplot variables
Parameters:
probe: str
probe, valid values for MMS probes are ['1','2','3','4'].
level: str
indicates level of data processing. the default if no level is specified is 'sitl'
datatype: str
Valid datatypes for FPI are:
Quicklook: ['des', 'dis']
SITL: '' (none; loads both electron and ion data from single CDF)
L1b/L2: ['des-dist', 'dis-dist', 'dis-moms', 'des-moms']
data_rate: str
instrument data rates for FPI include 'brst' and 'fast'. The
default is 'fast'.
suffix: str
The tplot variable names will be given this suffix. By default,
no suffix is added.
autoscale: bool
If set, use the default zrange; otherwise, use the min and max of the data for the zrange
Returns:
List of tplot variables created. | pyspedas/mms/fpi/mms_load_fpi_calc_pad.py | mms_load_fpi_calc_pad | shihikoo/pyspedas | python | def mms_load_fpi_calc_pad(probe='1', level='sitl', datatype=, data_rate=, suffix=, autoscale=True):
"\n Calculates the omni-directional pitch angle distribution (summed and averaged)\n from the individual tplot variables\n \n Parameters:\n probe: str \n probe, valid values for MMS probes are ['1','2','3','4']. \n\n level: str\n indicates level of data processing. the default if no level is specified is 'sitl'\n\n datatype: str\n Valid datatypes for FPI are:\n Quicklook: ['des', 'dis'] \n SITL: (none; loads both electron and ion data from single CDF)\n L1b/L2: ['des-dist', 'dis-dist', 'dis-moms', 'des-moms']\n\n data_rate: str\n instrument data rates for FPI include 'brst' and 'fast'. The\n default is 'fast'.\n\n suffix: str\n The tplot variable names will be given this suffix. By default, \n no suffix is added.\n\n autoscale: bool\n If set, use the default zrange; otherwise, use the min and max of the data for the zrange\n\n Returns:\n List of tplot variables created.\n\n "
out_vars = []
if isinstance(datatype, str):
if ((datatype == '*') or (datatype == )):
if (level.lower() == 'ql'):
datatype = ['des', 'dis']
else:
datatype = ['des-dist', 'dis-dist']
if isinstance(datatype, str):
datatype = [datatype]
for dtype in datatype:
species = dtype[1]
if (level.lower() == 'sitl'):
spec_str_format = 'PitchAngDist'
obs_str_format = ('_fpi_' + species)
else:
spec_str_format = 'pitchAngDist'
obs_str_format = (('_d' + species) + 's_')
obsstr = (('mms' + str(probe)) + obs_str_format)
if (level.lower() == 'l2'):
spec_str_format = 'pitchangdist'
pad_vars = [((((((obsstr + spec_str_format) + '_') + erange) + 'en_') + data_rate) + suffix) for erange in ['low', 'mid', 'high']]
else:
pad_vars = [(((((obsstr + spec_str_format) + '_') + erange) + 'En') + suffix) for erange in ['low', 'mid', 'high']]
pad_avg_name = ((obsstr + 'PitchAngDist_avg') + suffix)
low_en = get_data(pad_vars[0])
mid_en = get_data(pad_vars[1])
high_en = get_data(pad_vars[2])
if ((low_en is None) or (mid_en is None) or (high_en is None)):
v3_low_pad = tnames(((pad_vars[0].lower() + '_') + data_rate))
v3_mid_pad = tnames(((pad_vars[1].lower() + '_') + data_rate))
v3_high_pad = tnames(((pad_vars[2].lower() + '_') + data_rate))
if ((v3_low_pad == []) or (v3_mid_pad == []) or (v3_high_pad == [])):
continue
low_en = get_data(v3_low_pad[0])
mid_en = get_data(v3_mid_pad[0])
high_en = get_data(v3_high_pad[0])
pad_avg_name = pad_avg_name.lower()
e_pad_sum = ((low_en.y + mid_en.y) + high_en.y)
e_pad_avg = (e_pad_sum / 3.0)
if (level == 'l2'):
pad_avg_name = pad_avg_name.lower()
if (species == 'e'):
species_str = 'electron'
elif (species == 'i'):
species_str = 'ion'
if (level == 'ql'):
store_data(((obsstr + 'PitchAngDist_sum') + suffix), data={'x': low_en.times, 'y': e_pad_sum, 'v': low_en.v})
options(((obsstr + 'PitchAngDist_sum') + suffix), 'ytitle', (((('MMS' + str(probe)) + ' \\ ') + species_str) + ' \\ PAD \\ SUM'))
options(((obsstr + 'PitchAngDist_sum') + suffix), 'yrange', [0, 180])
options(((obsstr + 'PitchAngDist_sum') + suffix), 'zlog', True)
options(((obsstr + 'PitchAngDist_sum') + suffix), 'spec', True)
options(((obsstr + 'PitchAngDist_sum') + suffix), 'Colormap', 'jet')
out_vars.append(((obsstr + 'PitchAngDist_sum') + suffix))
store_data(pad_avg_name, data={'x': low_en.times, 'y': e_pad_avg, 'v': low_en.v})
options(pad_avg_name, 'ztitle', 'eV/(cm!U2!N s sr eV)')
options(pad_avg_name, 'ytitle', (((('MMS' + str(probe)) + ' \\ ') + species_str) + ' \\ PAD \\ AVG'))
options(pad_avg_name, 'yrange', [0, 180])
options(pad_avg_name, 'zlog', True)
options(pad_avg_name, 'spec', True)
options(pad_avg_name, 'Colormap', 'jet')
out_vars.append(pad_avg_name)
return out_vars |
def read_text_file(filename, encoding='utf-8'):
'\n Reads a file under python3 with encoding (default UTF-8).\n Also works under python2, without encoding.\n Uses the EAFP (https://docs.python.org/2/glossary.html#term-eafp)\n principle.\n '
try:
with open(filename, 'r', encoding) as f:
r = f.read()
except TypeError:
with open(filename, 'r') as f:
r = f.read()
return r | 6,698,377,301,607,065,000 | Reads a file under python3 with encoding (default UTF-8).
Also works under python2, without encoding.
Uses the EAFP (https://docs.python.org/2/glossary.html#term-eafp)
principle. | Corrfunc/__init__.py | read_text_file | dfm/suave | python | def read_text_file(filename, encoding='utf-8'):
'\n Reads a file under python3 with encoding (default UTF-8).\n Also works under python2, without encoding.\n Uses the EAFP (https://docs.python.org/2/glossary.html#term-eafp)\n principle.\n '
try:
with open(filename, 'r', encoding) as f:
r = f.read()
except TypeError:
with open(filename, 'r') as f:
r = f.read()
return r |
def write_text_file(filename, contents, encoding='utf-8'):
'\n Writes a file under python3 with encoding (default UTF-8).\n Also works under python2, without encoding.\n Uses the EAFP (https://docs.python.org/2/glossary.html#term-eafp)\n principle.\n '
try:
with open(filename, 'w', encoding) as f:
f.write(contents)
except TypeError:
with open(filename, 'w') as f:
f.write(contents) | -7,734,683,783,031,064,000 | Writes a file under python3 with encoding (default UTF-8).
Also works under python2, without encoding.
Uses the EAFP (https://docs.python.org/2/glossary.html#term-eafp)
principle. | Corrfunc/__init__.py | write_text_file | dfm/suave | python | def write_text_file(filename, contents, encoding='utf-8'):
'\n Writes a file under python3 with encoding (default UTF-8).\n Also works under python2, without encoding.\n Uses the EAFP (https://docs.python.org/2/glossary.html#term-eafp)\n principle.\n '
try:
with open(filename, 'w', encoding) as f:
f.write(contents)
except TypeError:
with open(filename, 'w') as f:
f.write(contents) |
def which(program, mode=(os.F_OK | os.X_OK), path=None):
'\n Mimics the Unix utility which.\n For python3.3+, shutil.which provides all of the required functionality.\n An implementation is provided in case shutil.which does\n not exist.\n\n :param program: (required) string\n Name of program (can be fully-qualified path as well)\n :param mode: (optional) integer flag bits\n Permissions to check for in the executable\n Default: os.F_OK (file exists) | os.X_OK (executable file)\n :param path: (optional) string\n A custom path list to check against. Implementation taken from\n shutil.py.\n\n Returns:\n A fully qualified path to program as resolved by path or\n user environment.\n Returns None when program can not be resolved.\n '
try:
from shutil import which as shwhich
return shwhich(program, mode, path)
except ImportError:
def is_exe(fpath):
return (os.path.isfile(fpath) and os.access(fpath, os.X_OK))
(fpath, _) = os.path.split(program)
if fpath:
if is_exe(program):
return program
else:
if (path is None):
path = os.environ.get('PATH', os.defpath)
if (not path):
return None
path = path.split(os.pathsep)
for pathdir in path:
pathdir = pathdir.strip('"')
exe_file = os.path.join(pathdir, program)
if is_exe(exe_file):
return exe_file
return None | 5,508,605,140,352,203,000 | Mimics the Unix utility which.
For python3.3+, shutil.which provides all of the required functionality.
An implementation is provided in case shutil.which does
not exist.
:param program: (required) string
Name of program (can be fully-qualified path as well)
:param mode: (optional) integer flag bits
Permissions to check for in the executable
Default: os.F_OK (file exists) | os.X_OK (executable file)
:param path: (optional) string
A custom path list to check against. Implementation taken from
shutil.py.
Returns:
A fully qualified path to program as resolved by path or
user environment.
Returns None when program can not be resolved. | Corrfunc/__init__.py | which | dfm/suave | python | def which(program, mode=(os.F_OK | os.X_OK), path=None):
'\n Mimics the Unix utility which.\n For python3.3+, shutil.which provides all of the required functionality.\n An implementation is provided in case shutil.which does\n not exist.\n\n :param program: (required) string\n Name of program (can be fully-qualified path as well)\n :param mode: (optional) integer flag bits\n Permissions to check for in the executable\n Default: os.F_OK (file exists) | os.X_OK (executable file)\n :param path: (optional) string\n A custom path list to check against. Implementation taken from\n shutil.py.\n\n Returns:\n A fully qualified path to program as resolved by path or\n user environment.\n Returns None when program can not be resolved.\n '
try:
from shutil import which as shwhich
return shwhich(program, mode, path)
except ImportError:
def is_exe(fpath):
return (os.path.isfile(fpath) and os.access(fpath, os.X_OK))
(fpath, _) = os.path.split(program)
if fpath:
if is_exe(program):
return program
else:
if (path is None):
path = os.environ.get('PATH', os.defpath)
if (not path):
return None
path = path.split(os.pathsep)
for pathdir in path:
pathdir = pathdir.strip('"')
exe_file = os.path.join(pathdir, program)
if is_exe(exe_file):
return exe_file
return None |
def removeElements(self, head, val):
'\n :type head: ListNode\n :type val: int\n :rtype: ListNode\n '
while head:
if (head.val == val):
head = head.next
else:
break
if (not head):
return head
cur = head
pre = cur
while cur:
if (cur.val != val):
pre = cur
cur = cur.next
else:
cur = cur.next
pre.next = cur
return head | -4,401,839,335,475,699,000 | :type head: ListNode
:type val: int
:rtype: ListNode | src/main/python/leetcode-python/easy/203.Remove Linked List Elements.py | removeElements | sonymoon/algorithm | python | def removeElements(self, head, val):
'\n :type head: ListNode\n :type val: int\n :rtype: ListNode\n '
while head:
if (head.val == val):
head = head.next
else:
break
if (not head):
return head
cur = head
pre = cur
while cur:
if (cur.val != val):
pre = cur
cur = cur.next
else:
cur = cur.next
pre.next = cur
return head |
@property
def ConfigFlags(self):
'\n Returns\n -------\n - str: NOT DEFINED\n '
return self._get_attribute(self._SDM_ATT_MAP['ConfigFlags']) | 1,462,245,169,808,264,000 | Returns
-------
- str: NOT DEFINED | ixnetwork_restpy/testplatform/sessions/ixnetwork/vport/protocols/switchconfiglearnedinformation_e983ca5da0eadbba93d1ce1d2903a5b7.py | ConfigFlags | Vibaswan/ixnetwork_restpy | python | @property
def ConfigFlags(self):
'\n Returns\n -------\n - str: NOT DEFINED\n '
return self._get_attribute(self._SDM_ATT_MAP['ConfigFlags']) |
@property
def DataPathId(self):
'\n Returns\n -------\n - str: NOT DEFINED\n '
return self._get_attribute(self._SDM_ATT_MAP['DataPathId']) | 8,598,606,963,486,531,000 | Returns
-------
- str: NOT DEFINED | ixnetwork_restpy/testplatform/sessions/ixnetwork/vport/protocols/switchconfiglearnedinformation_e983ca5da0eadbba93d1ce1d2903a5b7.py | DataPathId | Vibaswan/ixnetwork_restpy | python | @property
def DataPathId(self):
'\n Returns\n -------\n - str: NOT DEFINED\n '
return self._get_attribute(self._SDM_ATT_MAP['DataPathId']) |
@property
def DataPathIdAsHex(self):
'\n Returns\n -------\n - str: NOT DEFINED\n '
return self._get_attribute(self._SDM_ATT_MAP['DataPathIdAsHex']) | 804,803,447,564,948,000 | Returns
-------
- str: NOT DEFINED | ixnetwork_restpy/testplatform/sessions/ixnetwork/vport/protocols/switchconfiglearnedinformation_e983ca5da0eadbba93d1ce1d2903a5b7.py | DataPathIdAsHex | Vibaswan/ixnetwork_restpy | python | @property
def DataPathIdAsHex(self):
'\n Returns\n -------\n - str: NOT DEFINED\n '
return self._get_attribute(self._SDM_ATT_MAP['DataPathIdAsHex']) |
@property
def ErrorCode(self):
'\n Returns\n -------\n - str: NOT DEFINED\n '
return self._get_attribute(self._SDM_ATT_MAP['ErrorCode']) | 5,799,400,849,845,319,000 | Returns
-------
- str: NOT DEFINED | ixnetwork_restpy/testplatform/sessions/ixnetwork/vport/protocols/switchconfiglearnedinformation_e983ca5da0eadbba93d1ce1d2903a5b7.py | ErrorCode | Vibaswan/ixnetwork_restpy | python | @property
def ErrorCode(self):
'\n Returns\n -------\n - str: NOT DEFINED\n '
return self._get_attribute(self._SDM_ATT_MAP['ErrorCode']) |
@property
def ErrorType(self):
'\n Returns\n -------\n - str: NOT DEFINED\n '
return self._get_attribute(self._SDM_ATT_MAP['ErrorType']) | -7,110,418,267,919,914,000 | Returns
-------
- str: NOT DEFINED | ixnetwork_restpy/testplatform/sessions/ixnetwork/vport/protocols/switchconfiglearnedinformation_e983ca5da0eadbba93d1ce1d2903a5b7.py | ErrorType | Vibaswan/ixnetwork_restpy | python | @property
def ErrorType(self):
'\n Returns\n -------\n - str: NOT DEFINED\n '
return self._get_attribute(self._SDM_ATT_MAP['ErrorType']) |
@property
def Latency(self):
'\n Returns\n -------\n - number: NOT DEFINED\n '
return self._get_attribute(self._SDM_ATT_MAP['Latency']) | -4,419,917,132,471,396,000 | Returns
-------
- number: NOT DEFINED | ixnetwork_restpy/testplatform/sessions/ixnetwork/vport/protocols/switchconfiglearnedinformation_e983ca5da0eadbba93d1ce1d2903a5b7.py | Latency | Vibaswan/ixnetwork_restpy | python | @property
def Latency(self):
'\n Returns\n -------\n - number: NOT DEFINED\n '
return self._get_attribute(self._SDM_ATT_MAP['Latency']) |
@property
def LocalIp(self):
'\n Returns\n -------\n - str: NOT DEFINED\n '
return self._get_attribute(self._SDM_ATT_MAP['LocalIp']) | -5,974,784,433,635,664,000 | Returns
-------
- str: NOT DEFINED | ixnetwork_restpy/testplatform/sessions/ixnetwork/vport/protocols/switchconfiglearnedinformation_e983ca5da0eadbba93d1ce1d2903a5b7.py | LocalIp | Vibaswan/ixnetwork_restpy | python | @property
def LocalIp(self):
'\n Returns\n -------\n - str: NOT DEFINED\n '
return self._get_attribute(self._SDM_ATT_MAP['LocalIp']) |
@property
def MissSendLength(self):
'\n Returns\n -------\n - number: NOT DEFINED\n '
return self._get_attribute(self._SDM_ATT_MAP['MissSendLength']) | 1,972,557,766,165,532,200 | Returns
-------
- number: NOT DEFINED | ixnetwork_restpy/testplatform/sessions/ixnetwork/vport/protocols/switchconfiglearnedinformation_e983ca5da0eadbba93d1ce1d2903a5b7.py | MissSendLength | Vibaswan/ixnetwork_restpy | python | @property
def MissSendLength(self):
'\n Returns\n -------\n - number: NOT DEFINED\n '
return self._get_attribute(self._SDM_ATT_MAP['MissSendLength']) |
@property
def NegotiatedVersion(self):
'\n Returns\n -------\n - str: NOT DEFINED\n '
return self._get_attribute(self._SDM_ATT_MAP['NegotiatedVersion']) | -1,810,185,652,348,757,800 | Returns
-------
- str: NOT DEFINED | ixnetwork_restpy/testplatform/sessions/ixnetwork/vport/protocols/switchconfiglearnedinformation_e983ca5da0eadbba93d1ce1d2903a5b7.py | NegotiatedVersion | Vibaswan/ixnetwork_restpy | python | @property
def NegotiatedVersion(self):
'\n Returns\n -------\n - str: NOT DEFINED\n '
return self._get_attribute(self._SDM_ATT_MAP['NegotiatedVersion']) |
@property
def RemoteIp(self):
'\n Returns\n -------\n - str: NOT DEFINED\n '
return self._get_attribute(self._SDM_ATT_MAP['RemoteIp']) | -8,948,208,293,276,165,000 | Returns
-------
- str: NOT DEFINED | ixnetwork_restpy/testplatform/sessions/ixnetwork/vport/protocols/switchconfiglearnedinformation_e983ca5da0eadbba93d1ce1d2903a5b7.py | RemoteIp | Vibaswan/ixnetwork_restpy | python | @property
def RemoteIp(self):
'\n Returns\n -------\n - str: NOT DEFINED\n '
return self._get_attribute(self._SDM_ATT_MAP['RemoteIp']) |
@property
def ReplyState(self):
'\n Returns\n -------\n - str: NOT DEFINED\n '
return self._get_attribute(self._SDM_ATT_MAP['ReplyState']) | -4,484,793,304,505,861,000 | Returns
-------
- str: NOT DEFINED | ixnetwork_restpy/testplatform/sessions/ixnetwork/vport/protocols/switchconfiglearnedinformation_e983ca5da0eadbba93d1ce1d2903a5b7.py | ReplyState | Vibaswan/ixnetwork_restpy | python | @property
def ReplyState(self):
'\n Returns\n -------\n - str: NOT DEFINED\n '
return self._get_attribute(self._SDM_ATT_MAP['ReplyState']) |
def find(self, ConfigFlags=None, DataPathId=None, DataPathIdAsHex=None, ErrorCode=None, ErrorType=None, Latency=None, LocalIp=None, MissSendLength=None, NegotiatedVersion=None, RemoteIp=None, ReplyState=None):
'Finds and retrieves switchConfigLearnedInformation resources from the server.\n\n All named parameters are evaluated on the server using regex. The named parameters can be used to selectively retrieve switchConfigLearnedInformation resources from the server.\n To retrieve an exact match ensure the parameter value starts with ^ and ends with $\n By default the find method takes no parameters and will retrieve all switchConfigLearnedInformation resources from the server.\n\n Args\n ----\n - ConfigFlags (str): NOT DEFINED\n - DataPathId (str): NOT DEFINED\n - DataPathIdAsHex (str): NOT DEFINED\n - ErrorCode (str): NOT DEFINED\n - ErrorType (str): NOT DEFINED\n - Latency (number): NOT DEFINED\n - LocalIp (str): NOT DEFINED\n - MissSendLength (number): NOT DEFINED\n - NegotiatedVersion (str): NOT DEFINED\n - RemoteIp (str): NOT DEFINED\n - ReplyState (str): NOT DEFINED\n\n Returns\n -------\n - self: This instance with matching switchConfigLearnedInformation resources retrieved from the server available through an iterator or index\n\n Raises\n ------\n - ServerError: The server has encountered an uncategorized error condition\n '
return self._select(self._map_locals(self._SDM_ATT_MAP, locals())) | 2,930,267,066,556,517,400 | Finds and retrieves switchConfigLearnedInformation resources from the server.
All named parameters are evaluated on the server using regex. The named parameters can be used to selectively retrieve switchConfigLearnedInformation resources from the server.
To retrieve an exact match ensure the parameter value starts with ^ and ends with $
By default the find method takes no parameters and will retrieve all switchConfigLearnedInformation resources from the server.
Args
----
- ConfigFlags (str): NOT DEFINED
- DataPathId (str): NOT DEFINED
- DataPathIdAsHex (str): NOT DEFINED
- ErrorCode (str): NOT DEFINED
- ErrorType (str): NOT DEFINED
- Latency (number): NOT DEFINED
- LocalIp (str): NOT DEFINED
- MissSendLength (number): NOT DEFINED
- NegotiatedVersion (str): NOT DEFINED
- RemoteIp (str): NOT DEFINED
- ReplyState (str): NOT DEFINED
Returns
-------
- self: This instance with matching switchConfigLearnedInformation resources retrieved from the server available through an iterator or index
Raises
------
- ServerError: The server has encountered an uncategorized error condition | ixnetwork_restpy/testplatform/sessions/ixnetwork/vport/protocols/switchconfiglearnedinformation_e983ca5da0eadbba93d1ce1d2903a5b7.py | find | Vibaswan/ixnetwork_restpy | python | def find(self, ConfigFlags=None, DataPathId=None, DataPathIdAsHex=None, ErrorCode=None, ErrorType=None, Latency=None, LocalIp=None, MissSendLength=None, NegotiatedVersion=None, RemoteIp=None, ReplyState=None):
'Finds and retrieves switchConfigLearnedInformation resources from the server.\n\n All named parameters are evaluated on the server using regex. The named parameters can be used to selectively retrieve switchConfigLearnedInformation resources from the server.\n To retrieve an exact match ensure the parameter value starts with ^ and ends with $\n By default the find method takes no parameters and will retrieve all switchConfigLearnedInformation resources from the server.\n\n Args\n ----\n - ConfigFlags (str): NOT DEFINED\n - DataPathId (str): NOT DEFINED\n - DataPathIdAsHex (str): NOT DEFINED\n - ErrorCode (str): NOT DEFINED\n - ErrorType (str): NOT DEFINED\n - Latency (number): NOT DEFINED\n - LocalIp (str): NOT DEFINED\n - MissSendLength (number): NOT DEFINED\n - NegotiatedVersion (str): NOT DEFINED\n - RemoteIp (str): NOT DEFINED\n - ReplyState (str): NOT DEFINED\n\n Returns\n -------\n - self: This instance with matching switchConfigLearnedInformation resources retrieved from the server available through an iterator or index\n\n Raises\n ------\n - ServerError: The server has encountered an uncategorized error condition\n '
return self._select(self._map_locals(self._SDM_ATT_MAP, locals())) |
def read(self, href):
'Retrieves a single instance of switchConfigLearnedInformation data from the server.\n\n Args\n ----\n - href (str): An href to the instance to be retrieved\n\n Returns\n -------\n - self: This instance with the switchConfigLearnedInformation resources from the server available through an iterator or index\n\n Raises\n ------\n - NotFoundError: The requested resource does not exist on the server\n - ServerError: The server has encountered an uncategorized error condition\n '
return self._read(href) | 469,075,206,055,040,000 | Retrieves a single instance of switchConfigLearnedInformation data from the server.
Args
----
- href (str): An href to the instance to be retrieved
Returns
-------
- self: This instance with the switchConfigLearnedInformation resources from the server available through an iterator or index
Raises
------
- NotFoundError: The requested resource does not exist on the server
- ServerError: The server has encountered an uncategorized error condition | ixnetwork_restpy/testplatform/sessions/ixnetwork/vport/protocols/switchconfiglearnedinformation_e983ca5da0eadbba93d1ce1d2903a5b7.py | read | Vibaswan/ixnetwork_restpy | python | def read(self, href):
'Retrieves a single instance of switchConfigLearnedInformation data from the server.\n\n Args\n ----\n - href (str): An href to the instance to be retrieved\n\n Returns\n -------\n - self: This instance with the switchConfigLearnedInformation resources from the server available through an iterator or index\n\n Raises\n ------\n - NotFoundError: The requested resource does not exist on the server\n - ServerError: The server has encountered an uncategorized error condition\n '
return self._read(href) |
@pytest.fixture(name='light')
async def light_fixture(hass: HomeAssistant, mock_entry: MockEntityFixture, mock_light: Light):
'Fixture for a single light for testing the switch platform.'
Light.__config__.validate_assignment = False
light_obj = mock_light.copy(deep=True)
light_obj._api = mock_entry.api
light_obj.name = 'Test Light'
light_obj.is_ssh_enabled = False
light_obj.light_device_settings.is_indicator_enabled = False
mock_entry.api.bootstrap.reset_objects()
mock_entry.api.bootstrap.lights = {light_obj.id: light_obj}
(await hass.config_entries.async_setup(mock_entry.entry.entry_id))
(await hass.async_block_till_done())
assert_entity_counts(hass, Platform.SWITCH, 2, 1)
(yield light_obj)
Light.__config__.validate_assignment = True | 8,335,336,190,965,998,000 | Fixture for a single light for testing the switch platform. | tests/components/unifiprotect/test_switch.py | light_fixture | LW-Ho/home-assistant | python | @pytest.fixture(name='light')
async def light_fixture(hass: HomeAssistant, mock_entry: MockEntityFixture, mock_light: Light):
Light.__config__.validate_assignment = False
light_obj = mock_light.copy(deep=True)
light_obj._api = mock_entry.api
light_obj.name = 'Test Light'
light_obj.is_ssh_enabled = False
light_obj.light_device_settings.is_indicator_enabled = False
mock_entry.api.bootstrap.reset_objects()
mock_entry.api.bootstrap.lights = {light_obj.id: light_obj}
(await hass.config_entries.async_setup(mock_entry.entry.entry_id))
(await hass.async_block_till_done())
assert_entity_counts(hass, Platform.SWITCH, 2, 1)
(yield light_obj)
Light.__config__.validate_assignment = True |
@pytest.fixture(name='camera')
async def camera_fixture(hass: HomeAssistant, mock_entry: MockEntityFixture, mock_camera: Camera):
'Fixture for a single camera for testing the switch platform.'
Camera.__config__.validate_assignment = False
camera_obj = mock_camera.copy(deep=True)
camera_obj._api = mock_entry.api
camera_obj.channels[0]._api = mock_entry.api
camera_obj.channels[1]._api = mock_entry.api
camera_obj.channels[2]._api = mock_entry.api
camera_obj.name = 'Test Camera'
camera_obj.recording_settings.mode = RecordingMode.DETECTIONS
camera_obj.feature_flags.has_led_status = True
camera_obj.feature_flags.has_hdr = True
camera_obj.feature_flags.video_modes = [VideoMode.DEFAULT, VideoMode.HIGH_FPS]
camera_obj.feature_flags.has_privacy_mask = True
camera_obj.feature_flags.has_speaker = True
camera_obj.feature_flags.has_smart_detect = True
camera_obj.feature_flags.smart_detect_types = [SmartDetectObjectType.PERSON, SmartDetectObjectType.VEHICLE]
camera_obj.is_ssh_enabled = False
camera_obj.led_settings.is_enabled = False
camera_obj.hdr_mode = False
camera_obj.video_mode = VideoMode.DEFAULT
camera_obj.remove_privacy_zone()
camera_obj.speaker_settings.are_system_sounds_enabled = False
camera_obj.osd_settings.is_name_enabled = False
camera_obj.osd_settings.is_date_enabled = False
camera_obj.osd_settings.is_logo_enabled = False
camera_obj.osd_settings.is_debug_enabled = False
camera_obj.smart_detect_settings.object_types = []
mock_entry.api.bootstrap.reset_objects()
mock_entry.api.bootstrap.cameras = {camera_obj.id: camera_obj}
(await hass.config_entries.async_setup(mock_entry.entry.entry_id))
(await hass.async_block_till_done())
assert_entity_counts(hass, Platform.SWITCH, 12, 11)
(yield camera_obj)
Camera.__config__.validate_assignment = True | -5,056,614,102,248,992,000 | Fixture for a single camera for testing the switch platform. | tests/components/unifiprotect/test_switch.py | camera_fixture | LW-Ho/home-assistant | python | @pytest.fixture(name='camera')
async def camera_fixture(hass: HomeAssistant, mock_entry: MockEntityFixture, mock_camera: Camera):
Camera.__config__.validate_assignment = False
camera_obj = mock_camera.copy(deep=True)
camera_obj._api = mock_entry.api
camera_obj.channels[0]._api = mock_entry.api
camera_obj.channels[1]._api = mock_entry.api
camera_obj.channels[2]._api = mock_entry.api
camera_obj.name = 'Test Camera'
camera_obj.recording_settings.mode = RecordingMode.DETECTIONS
camera_obj.feature_flags.has_led_status = True
camera_obj.feature_flags.has_hdr = True
camera_obj.feature_flags.video_modes = [VideoMode.DEFAULT, VideoMode.HIGH_FPS]
camera_obj.feature_flags.has_privacy_mask = True
camera_obj.feature_flags.has_speaker = True
camera_obj.feature_flags.has_smart_detect = True
camera_obj.feature_flags.smart_detect_types = [SmartDetectObjectType.PERSON, SmartDetectObjectType.VEHICLE]
camera_obj.is_ssh_enabled = False
camera_obj.led_settings.is_enabled = False
camera_obj.hdr_mode = False
camera_obj.video_mode = VideoMode.DEFAULT
camera_obj.remove_privacy_zone()
camera_obj.speaker_settings.are_system_sounds_enabled = False
camera_obj.osd_settings.is_name_enabled = False
camera_obj.osd_settings.is_date_enabled = False
camera_obj.osd_settings.is_logo_enabled = False
camera_obj.osd_settings.is_debug_enabled = False
camera_obj.smart_detect_settings.object_types = []
mock_entry.api.bootstrap.reset_objects()
mock_entry.api.bootstrap.cameras = {camera_obj.id: camera_obj}
(await hass.config_entries.async_setup(mock_entry.entry.entry_id))
(await hass.async_block_till_done())
assert_entity_counts(hass, Platform.SWITCH, 12, 11)
(yield camera_obj)
Camera.__config__.validate_assignment = True |
@pytest.fixture(name='camera_none')
async def camera_none_fixture(hass: HomeAssistant, mock_entry: MockEntityFixture, mock_camera: Camera):
'Fixture for a single camera for testing the switch platform.'
Camera.__config__.validate_assignment = False
camera_obj = mock_camera.copy(deep=True)
camera_obj._api = mock_entry.api
camera_obj.channels[0]._api = mock_entry.api
camera_obj.channels[1]._api = mock_entry.api
camera_obj.channels[2]._api = mock_entry.api
camera_obj.name = 'Test Camera'
camera_obj.recording_settings.mode = RecordingMode.DETECTIONS
camera_obj.feature_flags.has_led_status = False
camera_obj.feature_flags.has_hdr = False
camera_obj.feature_flags.video_modes = [VideoMode.DEFAULT]
camera_obj.feature_flags.has_privacy_mask = False
camera_obj.feature_flags.has_speaker = False
camera_obj.feature_flags.has_smart_detect = False
camera_obj.is_ssh_enabled = False
camera_obj.osd_settings.is_name_enabled = False
camera_obj.osd_settings.is_date_enabled = False
camera_obj.osd_settings.is_logo_enabled = False
camera_obj.osd_settings.is_debug_enabled = False
mock_entry.api.bootstrap.reset_objects()
mock_entry.api.bootstrap.cameras = {camera_obj.id: camera_obj}
(await hass.config_entries.async_setup(mock_entry.entry.entry_id))
(await hass.async_block_till_done())
assert_entity_counts(hass, Platform.SWITCH, 5, 4)
(yield camera_obj)
Camera.__config__.validate_assignment = True | -4,512,770,344,431,090,000 | Fixture for a single camera for testing the switch platform. | tests/components/unifiprotect/test_switch.py | camera_none_fixture | LW-Ho/home-assistant | python | @pytest.fixture(name='camera_none')
async def camera_none_fixture(hass: HomeAssistant, mock_entry: MockEntityFixture, mock_camera: Camera):
Camera.__config__.validate_assignment = False
camera_obj = mock_camera.copy(deep=True)
camera_obj._api = mock_entry.api
camera_obj.channels[0]._api = mock_entry.api
camera_obj.channels[1]._api = mock_entry.api
camera_obj.channels[2]._api = mock_entry.api
camera_obj.name = 'Test Camera'
camera_obj.recording_settings.mode = RecordingMode.DETECTIONS
camera_obj.feature_flags.has_led_status = False
camera_obj.feature_flags.has_hdr = False
camera_obj.feature_flags.video_modes = [VideoMode.DEFAULT]
camera_obj.feature_flags.has_privacy_mask = False
camera_obj.feature_flags.has_speaker = False
camera_obj.feature_flags.has_smart_detect = False
camera_obj.is_ssh_enabled = False
camera_obj.osd_settings.is_name_enabled = False
camera_obj.osd_settings.is_date_enabled = False
camera_obj.osd_settings.is_logo_enabled = False
camera_obj.osd_settings.is_debug_enabled = False
mock_entry.api.bootstrap.reset_objects()
mock_entry.api.bootstrap.cameras = {camera_obj.id: camera_obj}
(await hass.config_entries.async_setup(mock_entry.entry.entry_id))
(await hass.async_block_till_done())
assert_entity_counts(hass, Platform.SWITCH, 5, 4)
(yield camera_obj)
Camera.__config__.validate_assignment = True |
@pytest.fixture(name='camera_privacy')
async def camera_privacy_fixture(hass: HomeAssistant, mock_entry: MockEntityFixture, mock_camera: Camera):
'Fixture for a single camera for testing the switch platform.'
Camera.__config__.validate_assignment = False
camera_obj = mock_camera.copy(deep=True)
camera_obj._api = mock_entry.api
camera_obj.channels[0]._api = mock_entry.api
camera_obj.channels[1]._api = mock_entry.api
camera_obj.channels[2]._api = mock_entry.api
camera_obj.name = 'Test Camera'
camera_obj.recording_settings.mode = RecordingMode.NEVER
camera_obj.feature_flags.has_led_status = False
camera_obj.feature_flags.has_hdr = False
camera_obj.feature_flags.video_modes = [VideoMode.DEFAULT]
camera_obj.feature_flags.has_privacy_mask = True
camera_obj.feature_flags.has_speaker = False
camera_obj.feature_flags.has_smart_detect = False
camera_obj.add_privacy_zone()
camera_obj.is_ssh_enabled = False
camera_obj.osd_settings.is_name_enabled = False
camera_obj.osd_settings.is_date_enabled = False
camera_obj.osd_settings.is_logo_enabled = False
camera_obj.osd_settings.is_debug_enabled = False
mock_entry.api.bootstrap.reset_objects()
mock_entry.api.bootstrap.cameras = {camera_obj.id: camera_obj}
(await hass.config_entries.async_setup(mock_entry.entry.entry_id))
(await hass.async_block_till_done())
assert_entity_counts(hass, Platform.SWITCH, 6, 5)
(yield camera_obj)
Camera.__config__.validate_assignment = True | -6,874,387,683,140,718,000 | Fixture for a single camera for testing the switch platform. | tests/components/unifiprotect/test_switch.py | camera_privacy_fixture | LW-Ho/home-assistant | python | @pytest.fixture(name='camera_privacy')
async def camera_privacy_fixture(hass: HomeAssistant, mock_entry: MockEntityFixture, mock_camera: Camera):
Camera.__config__.validate_assignment = False
camera_obj = mock_camera.copy(deep=True)
camera_obj._api = mock_entry.api
camera_obj.channels[0]._api = mock_entry.api
camera_obj.channels[1]._api = mock_entry.api
camera_obj.channels[2]._api = mock_entry.api
camera_obj.name = 'Test Camera'
camera_obj.recording_settings.mode = RecordingMode.NEVER
camera_obj.feature_flags.has_led_status = False
camera_obj.feature_flags.has_hdr = False
camera_obj.feature_flags.video_modes = [VideoMode.DEFAULT]
camera_obj.feature_flags.has_privacy_mask = True
camera_obj.feature_flags.has_speaker = False
camera_obj.feature_flags.has_smart_detect = False
camera_obj.add_privacy_zone()
camera_obj.is_ssh_enabled = False
camera_obj.osd_settings.is_name_enabled = False
camera_obj.osd_settings.is_date_enabled = False
camera_obj.osd_settings.is_logo_enabled = False
camera_obj.osd_settings.is_debug_enabled = False
mock_entry.api.bootstrap.reset_objects()
mock_entry.api.bootstrap.cameras = {camera_obj.id: camera_obj}
(await hass.config_entries.async_setup(mock_entry.entry.entry_id))
(await hass.async_block_till_done())
assert_entity_counts(hass, Platform.SWITCH, 6, 5)
(yield camera_obj)
Camera.__config__.validate_assignment = True |
async def test_switch_setup_light(hass: HomeAssistant, mock_entry: MockEntityFixture, light: Light):
'Test switch entity setup for light devices.'
entity_registry = er.async_get(hass)
description = LIGHT_SWITCHES[1]
(unique_id, entity_id) = ids_from_device_description(Platform.SWITCH, light, description)
entity = entity_registry.async_get(entity_id)
assert entity
assert (entity.unique_id == unique_id)
state = hass.states.get(entity_id)
assert state
assert (state.state == STATE_OFF)
assert (state.attributes[ATTR_ATTRIBUTION] == DEFAULT_ATTRIBUTION)
description = LIGHT_SWITCHES[0]
unique_id = f'{light.id}_{description.key}'
entity_id = f"switch.test_light_{description.name.lower().replace(' ', '_')}"
entity = entity_registry.async_get(entity_id)
assert entity
assert (entity.disabled is True)
assert (entity.unique_id == unique_id)
(await enable_entity(hass, mock_entry.entry.entry_id, entity_id))
state = hass.states.get(entity_id)
assert state
assert (state.state == STATE_OFF)
assert (state.attributes[ATTR_ATTRIBUTION] == DEFAULT_ATTRIBUTION) | 745,013,318,945,976,300 | Test switch entity setup for light devices. | tests/components/unifiprotect/test_switch.py | test_switch_setup_light | LW-Ho/home-assistant | python | async def test_switch_setup_light(hass: HomeAssistant, mock_entry: MockEntityFixture, light: Light):
entity_registry = er.async_get(hass)
description = LIGHT_SWITCHES[1]
(unique_id, entity_id) = ids_from_device_description(Platform.SWITCH, light, description)
entity = entity_registry.async_get(entity_id)
assert entity
assert (entity.unique_id == unique_id)
state = hass.states.get(entity_id)
assert state
assert (state.state == STATE_OFF)
assert (state.attributes[ATTR_ATTRIBUTION] == DEFAULT_ATTRIBUTION)
description = LIGHT_SWITCHES[0]
unique_id = f'{light.id}_{description.key}'
entity_id = f"switch.test_light_{description.name.lower().replace(' ', '_')}"
entity = entity_registry.async_get(entity_id)
assert entity
assert (entity.disabled is True)
assert (entity.unique_id == unique_id)
(await enable_entity(hass, mock_entry.entry.entry_id, entity_id))
state = hass.states.get(entity_id)
assert state
assert (state.state == STATE_OFF)
assert (state.attributes[ATTR_ATTRIBUTION] == DEFAULT_ATTRIBUTION) |
async def test_switch_setup_camera_all(hass: HomeAssistant, mock_entry: MockEntityFixture, camera: Camera):
'Test switch entity setup for camera devices (all enabled feature flags).'
entity_registry = er.async_get(hass)
for description in CAMERA_SWITCHES_BASIC:
(unique_id, entity_id) = ids_from_device_description(Platform.SWITCH, camera, description)
entity = entity_registry.async_get(entity_id)
assert entity
assert (entity.unique_id == unique_id)
state = hass.states.get(entity_id)
assert state
assert (state.state == STATE_OFF)
assert (state.attributes[ATTR_ATTRIBUTION] == DEFAULT_ATTRIBUTION)
description = CAMERA_SWITCHES[0]
description_entity_name = description.name.lower().replace(':', '').replace(' ', '_')
unique_id = f'{camera.id}_{description.key}'
entity_id = f'switch.test_camera_{description_entity_name}'
entity = entity_registry.async_get(entity_id)
assert entity
assert (entity.disabled is True)
assert (entity.unique_id == unique_id)
(await enable_entity(hass, mock_entry.entry.entry_id, entity_id))
state = hass.states.get(entity_id)
assert state
assert (state.state == STATE_OFF)
assert (state.attributes[ATTR_ATTRIBUTION] == DEFAULT_ATTRIBUTION) | -5,643,885,727,098,207,000 | Test switch entity setup for camera devices (all enabled feature flags). | tests/components/unifiprotect/test_switch.py | test_switch_setup_camera_all | LW-Ho/home-assistant | python | async def test_switch_setup_camera_all(hass: HomeAssistant, mock_entry: MockEntityFixture, camera: Camera):
entity_registry = er.async_get(hass)
for description in CAMERA_SWITCHES_BASIC:
(unique_id, entity_id) = ids_from_device_description(Platform.SWITCH, camera, description)
entity = entity_registry.async_get(entity_id)
assert entity
assert (entity.unique_id == unique_id)
state = hass.states.get(entity_id)
assert state
assert (state.state == STATE_OFF)
assert (state.attributes[ATTR_ATTRIBUTION] == DEFAULT_ATTRIBUTION)
description = CAMERA_SWITCHES[0]
description_entity_name = description.name.lower().replace(':', ).replace(' ', '_')
unique_id = f'{camera.id}_{description.key}'
entity_id = f'switch.test_camera_{description_entity_name}'
entity = entity_registry.async_get(entity_id)
assert entity
assert (entity.disabled is True)
assert (entity.unique_id == unique_id)
(await enable_entity(hass, mock_entry.entry.entry_id, entity_id))
state = hass.states.get(entity_id)
assert state
assert (state.state == STATE_OFF)
assert (state.attributes[ATTR_ATTRIBUTION] == DEFAULT_ATTRIBUTION) |
async def test_switch_setup_camera_none(hass: HomeAssistant, mock_entry: MockEntityFixture, camera_none: Camera):
'Test switch entity setup for camera devices (no enabled feature flags).'
entity_registry = er.async_get(hass)
for description in CAMERA_SWITCHES_BASIC:
if (description.ufp_required_field is not None):
continue
(unique_id, entity_id) = ids_from_device_description(Platform.SWITCH, camera_none, description)
entity = entity_registry.async_get(entity_id)
assert entity
assert (entity.unique_id == unique_id)
state = hass.states.get(entity_id)
assert state
assert (state.state == STATE_OFF)
assert (state.attributes[ATTR_ATTRIBUTION] == DEFAULT_ATTRIBUTION)
description = CAMERA_SWITCHES[0]
description_entity_name = description.name.lower().replace(':', '').replace(' ', '_')
unique_id = f'{camera_none.id}_{description.key}'
entity_id = f'switch.test_camera_{description_entity_name}'
entity = entity_registry.async_get(entity_id)
assert entity
assert (entity.disabled is True)
assert (entity.unique_id == unique_id)
(await enable_entity(hass, mock_entry.entry.entry_id, entity_id))
state = hass.states.get(entity_id)
assert state
assert (state.state == STATE_OFF)
assert (state.attributes[ATTR_ATTRIBUTION] == DEFAULT_ATTRIBUTION) | 2,929,762,239,909,379,600 | Test switch entity setup for camera devices (no enabled feature flags). | tests/components/unifiprotect/test_switch.py | test_switch_setup_camera_none | LW-Ho/home-assistant | python | async def test_switch_setup_camera_none(hass: HomeAssistant, mock_entry: MockEntityFixture, camera_none: Camera):
entity_registry = er.async_get(hass)
for description in CAMERA_SWITCHES_BASIC:
if (description.ufp_required_field is not None):
continue
(unique_id, entity_id) = ids_from_device_description(Platform.SWITCH, camera_none, description)
entity = entity_registry.async_get(entity_id)
assert entity
assert (entity.unique_id == unique_id)
state = hass.states.get(entity_id)
assert state
assert (state.state == STATE_OFF)
assert (state.attributes[ATTR_ATTRIBUTION] == DEFAULT_ATTRIBUTION)
description = CAMERA_SWITCHES[0]
description_entity_name = description.name.lower().replace(':', ).replace(' ', '_')
unique_id = f'{camera_none.id}_{description.key}'
entity_id = f'switch.test_camera_{description_entity_name}'
entity = entity_registry.async_get(entity_id)
assert entity
assert (entity.disabled is True)
assert (entity.unique_id == unique_id)
(await enable_entity(hass, mock_entry.entry.entry_id, entity_id))
state = hass.states.get(entity_id)
assert state
assert (state.state == STATE_OFF)
assert (state.attributes[ATTR_ATTRIBUTION] == DEFAULT_ATTRIBUTION) |
async def test_switch_light_status(hass: HomeAssistant, light: Light):
'Tests status light switch for lights.'
description = LIGHT_SWITCHES[1]
light.__fields__['set_status_light'] = Mock()
light.set_status_light = AsyncMock()
(_, entity_id) = ids_from_device_description(Platform.SWITCH, light, description)
(await hass.services.async_call('switch', 'turn_on', {ATTR_ENTITY_ID: entity_id}, blocking=True))
light.set_status_light.assert_called_once_with(True)
(await hass.services.async_call('switch', 'turn_off', {ATTR_ENTITY_ID: entity_id}, blocking=True))
light.set_status_light.assert_called_with(False) | -7,921,302,965,398,987,000 | Tests status light switch for lights. | tests/components/unifiprotect/test_switch.py | test_switch_light_status | LW-Ho/home-assistant | python | async def test_switch_light_status(hass: HomeAssistant, light: Light):
description = LIGHT_SWITCHES[1]
light.__fields__['set_status_light'] = Mock()
light.set_status_light = AsyncMock()
(_, entity_id) = ids_from_device_description(Platform.SWITCH, light, description)
(await hass.services.async_call('switch', 'turn_on', {ATTR_ENTITY_ID: entity_id}, blocking=True))
light.set_status_light.assert_called_once_with(True)
(await hass.services.async_call('switch', 'turn_off', {ATTR_ENTITY_ID: entity_id}, blocking=True))
light.set_status_light.assert_called_with(False) |
async def test_switch_camera_ssh(hass: HomeAssistant, camera: Camera, mock_entry: MockEntityFixture):
'Tests SSH switch for cameras.'
description = CAMERA_SWITCHES[0]
camera.__fields__['set_ssh'] = Mock()
camera.set_ssh = AsyncMock()
(_, entity_id) = ids_from_device_description(Platform.SWITCH, camera, description)
(await enable_entity(hass, mock_entry.entry.entry_id, entity_id))
(await hass.services.async_call('switch', 'turn_on', {ATTR_ENTITY_ID: entity_id}, blocking=True))
camera.set_ssh.assert_called_once_with(True)
(await hass.services.async_call('switch', 'turn_off', {ATTR_ENTITY_ID: entity_id}, blocking=True))
camera.set_ssh.assert_called_with(False) | -5,878,164,364,571,807,000 | Tests SSH switch for cameras. | tests/components/unifiprotect/test_switch.py | test_switch_camera_ssh | LW-Ho/home-assistant | python | async def test_switch_camera_ssh(hass: HomeAssistant, camera: Camera, mock_entry: MockEntityFixture):
description = CAMERA_SWITCHES[0]
camera.__fields__['set_ssh'] = Mock()
camera.set_ssh = AsyncMock()
(_, entity_id) = ids_from_device_description(Platform.SWITCH, camera, description)
(await enable_entity(hass, mock_entry.entry.entry_id, entity_id))
(await hass.services.async_call('switch', 'turn_on', {ATTR_ENTITY_ID: entity_id}, blocking=True))
camera.set_ssh.assert_called_once_with(True)
(await hass.services.async_call('switch', 'turn_off', {ATTR_ENTITY_ID: entity_id}, blocking=True))
camera.set_ssh.assert_called_with(False) |
@pytest.mark.parametrize('description', CAMERA_SWITCHES_NO_EXTRA)
async def test_switch_camera_simple(hass: HomeAssistant, camera: Camera, description: ProtectSwitchEntityDescription):
'Tests all simple switches for cameras.'
assert (description.ufp_set_method is not None)
camera.__fields__[description.ufp_set_method] = Mock()
setattr(camera, description.ufp_set_method, AsyncMock())
set_method = getattr(camera, description.ufp_set_method)
(_, entity_id) = ids_from_device_description(Platform.SWITCH, camera, description)
(await hass.services.async_call('switch', 'turn_on', {ATTR_ENTITY_ID: entity_id}, blocking=True))
set_method.assert_called_once_with(True)
(await hass.services.async_call('switch', 'turn_off', {ATTR_ENTITY_ID: entity_id}, blocking=True))
set_method.assert_called_with(False) | -7,129,835,431,222,116,000 | Tests all simple switches for cameras. | tests/components/unifiprotect/test_switch.py | test_switch_camera_simple | LW-Ho/home-assistant | python | @pytest.mark.parametrize('description', CAMERA_SWITCHES_NO_EXTRA)
async def test_switch_camera_simple(hass: HomeAssistant, camera: Camera, description: ProtectSwitchEntityDescription):
assert (description.ufp_set_method is not None)
camera.__fields__[description.ufp_set_method] = Mock()
setattr(camera, description.ufp_set_method, AsyncMock())
set_method = getattr(camera, description.ufp_set_method)
(_, entity_id) = ids_from_device_description(Platform.SWITCH, camera, description)
(await hass.services.async_call('switch', 'turn_on', {ATTR_ENTITY_ID: entity_id}, blocking=True))
set_method.assert_called_once_with(True)
(await hass.services.async_call('switch', 'turn_off', {ATTR_ENTITY_ID: entity_id}, blocking=True))
set_method.assert_called_with(False) |
async def test_switch_camera_highfps(hass: HomeAssistant, camera: Camera):
'Tests High FPS switch for cameras.'
description = CAMERA_SWITCHES[3]
camera.__fields__['set_video_mode'] = Mock()
camera.set_video_mode = AsyncMock()
(_, entity_id) = ids_from_device_description(Platform.SWITCH, camera, description)
(await hass.services.async_call('switch', 'turn_on', {ATTR_ENTITY_ID: entity_id}, blocking=True))
camera.set_video_mode.assert_called_once_with(VideoMode.HIGH_FPS)
(await hass.services.async_call('switch', 'turn_off', {ATTR_ENTITY_ID: entity_id}, blocking=True))
camera.set_video_mode.assert_called_with(VideoMode.DEFAULT) | -8,116,559,982,682,837,000 | Tests High FPS switch for cameras. | tests/components/unifiprotect/test_switch.py | test_switch_camera_highfps | LW-Ho/home-assistant | python | async def test_switch_camera_highfps(hass: HomeAssistant, camera: Camera):
description = CAMERA_SWITCHES[3]
camera.__fields__['set_video_mode'] = Mock()
camera.set_video_mode = AsyncMock()
(_, entity_id) = ids_from_device_description(Platform.SWITCH, camera, description)
(await hass.services.async_call('switch', 'turn_on', {ATTR_ENTITY_ID: entity_id}, blocking=True))
camera.set_video_mode.assert_called_once_with(VideoMode.HIGH_FPS)
(await hass.services.async_call('switch', 'turn_off', {ATTR_ENTITY_ID: entity_id}, blocking=True))
camera.set_video_mode.assert_called_with(VideoMode.DEFAULT) |
async def test_switch_camera_privacy(hass: HomeAssistant, camera: Camera):
'Tests Privacy Mode switch for cameras.'
description = CAMERA_SWITCHES[4]
camera.__fields__['set_privacy'] = Mock()
camera.set_privacy = AsyncMock()
(_, entity_id) = ids_from_device_description(Platform.SWITCH, camera, description)
(await hass.services.async_call('switch', 'turn_on', {ATTR_ENTITY_ID: entity_id}, blocking=True))
camera.set_privacy.assert_called_once_with(True, 0, RecordingMode.NEVER)
(await hass.services.async_call('switch', 'turn_off', {ATTR_ENTITY_ID: entity_id}, blocking=True))
camera.set_privacy.assert_called_with(False, camera.mic_volume, camera.recording_settings.mode) | -806,886,069,751,213,200 | Tests Privacy Mode switch for cameras. | tests/components/unifiprotect/test_switch.py | test_switch_camera_privacy | LW-Ho/home-assistant | python | async def test_switch_camera_privacy(hass: HomeAssistant, camera: Camera):
description = CAMERA_SWITCHES[4]
camera.__fields__['set_privacy'] = Mock()
camera.set_privacy = AsyncMock()
(_, entity_id) = ids_from_device_description(Platform.SWITCH, camera, description)
(await hass.services.async_call('switch', 'turn_on', {ATTR_ENTITY_ID: entity_id}, blocking=True))
camera.set_privacy.assert_called_once_with(True, 0, RecordingMode.NEVER)
(await hass.services.async_call('switch', 'turn_off', {ATTR_ENTITY_ID: entity_id}, blocking=True))
camera.set_privacy.assert_called_with(False, camera.mic_volume, camera.recording_settings.mode) |
async def test_switch_camera_privacy_already_on(hass: HomeAssistant, camera_privacy: Camera):
'Tests Privacy Mode switch for cameras with privacy mode defaulted on.'
description = CAMERA_SWITCHES[4]
camera_privacy.__fields__['set_privacy'] = Mock()
camera_privacy.set_privacy = AsyncMock()
(_, entity_id) = ids_from_device_description(Platform.SWITCH, camera_privacy, description)
(await hass.services.async_call('switch', 'turn_off', {ATTR_ENTITY_ID: entity_id}, blocking=True))
camera_privacy.set_privacy.assert_called_once_with(False, 100, RecordingMode.ALWAYS) | 150,585,740,807,563,780 | Tests Privacy Mode switch for cameras with privacy mode defaulted on. | tests/components/unifiprotect/test_switch.py | test_switch_camera_privacy_already_on | LW-Ho/home-assistant | python | async def test_switch_camera_privacy_already_on(hass: HomeAssistant, camera_privacy: Camera):
description = CAMERA_SWITCHES[4]
camera_privacy.__fields__['set_privacy'] = Mock()
camera_privacy.set_privacy = AsyncMock()
(_, entity_id) = ids_from_device_description(Platform.SWITCH, camera_privacy, description)
(await hass.services.async_call('switch', 'turn_off', {ATTR_ENTITY_ID: entity_id}, blocking=True))
camera_privacy.set_privacy.assert_called_once_with(False, 100, RecordingMode.ALWAYS) |
def __init__(self, svm_kernel='linear', svm_c=0.1, fs=250, bands=None, time_windows=None, riem_opt='Riemann', rho=0.1, filter_type='butter', filter_order=2, random_state=None):
' Constructor\n\n Args:\n\n Parameters\n ----------\n\n svm_kernel: str {\'linear\', \'sigmoid\', \'rbf\'}\n kernel used for classifier\n\n svm_c: float\n regularization parameter for the classifier\n\n fs: int\n sampling rate of the data\n\n bands: list of int\n bandwidths used in filterbanks (default: [2, 4, 8, 16, 32])\n\n time_windows: list of list of ints, shape = (N, 2)\n time windows used, in seconds (default: [[2,5, 6]])\n\n riem_opt: str {"riemann", "Riemann_Euclid", "Whitened_Euclid", "No_Adaptation"}\n type of riemannian used\n\n rho: float\n Normalization parameter for the covariance matrix of the riemannian\n\n filter_type: str {"butter", "fir"}\n Type of the filter\n\n filter_order: int\n Order of the filter\n\n random_state: int or None\n random seed used in the SVM\n '
if (svm_kernel == 'linear'):
self.classifier = LinearSVC(C=svm_c, loss='hinge', random_state=random_state, tol=1e-05)
else:
self.classifier = SVC(C=svm_c, kernel=svm_kernel, degree=10, gamma='auto', cache_size=10000, random_state=random_state)
if (bands is None):
bandwidths = np.array([2, 4, 8, 16, 32])
else:
bandwidths = np.array(bands)
filter_bank = load_filterbank(bandwidths, fs, order=filter_order, max_freq=40, ftype=filter_type)
if (time_windows is None):
time_windows = (np.array([[2.5, 6]]) * fs).astype(int)
else:
time_windows = (np.array(time_windows) * fs).astype(int)
self.riemannian = RiemannianMultiscale(filter_bank, time_windows, riem_opt=riem_opt, rho=rho, vectorized=True)
self.no_bands = filter_bank.shape[0]
self.no_time_windows = time_windows.shape[0]
self.no_riem = None
self.no_features = None | 985,681,782,856,049,500 | Constructor
Args:
Parameters
----------
svm_kernel: str {'linear', 'sigmoid', 'rbf'}
kernel used for classifier
svm_c: float
regularization parameter for the classifier
fs: int
sampling rate of the data
bands: list of int
bandwidths used in filterbanks (default: [2, 4, 8, 16, 32])
time_windows: list of list of ints, shape = (N, 2)
time windows used, in seconds (default: [[2,5, 6]])
riem_opt: str {"riemann", "Riemann_Euclid", "Whitened_Euclid", "No_Adaptation"}
type of riemannian used
rho: float
Normalization parameter for the covariance matrix of the riemannian
filter_type: str {"butter", "fir"}
Type of the filter
filter_order: int
Order of the filter
random_state: int or None
random seed used in the SVM | multiscale_bci_python/riemannian_model.py | __init__ | pulp-platform/multispectral-riemannian | python | def __init__(self, svm_kernel='linear', svm_c=0.1, fs=250, bands=None, time_windows=None, riem_opt='Riemann', rho=0.1, filter_type='butter', filter_order=2, random_state=None):
' Constructor\n\n Args:\n\n Parameters\n ----------\n\n svm_kernel: str {\'linear\', \'sigmoid\', \'rbf\'}\n kernel used for classifier\n\n svm_c: float\n regularization parameter for the classifier\n\n fs: int\n sampling rate of the data\n\n bands: list of int\n bandwidths used in filterbanks (default: [2, 4, 8, 16, 32])\n\n time_windows: list of list of ints, shape = (N, 2)\n time windows used, in seconds (default: [[2,5, 6]])\n\n riem_opt: str {"riemann", "Riemann_Euclid", "Whitened_Euclid", "No_Adaptation"}\n type of riemannian used\n\n rho: float\n Normalization parameter for the covariance matrix of the riemannian\n\n filter_type: str {"butter", "fir"}\n Type of the filter\n\n filter_order: int\n Order of the filter\n\n random_state: int or None\n random seed used in the SVM\n '
if (svm_kernel == 'linear'):
self.classifier = LinearSVC(C=svm_c, loss='hinge', random_state=random_state, tol=1e-05)
else:
self.classifier = SVC(C=svm_c, kernel=svm_kernel, degree=10, gamma='auto', cache_size=10000, random_state=random_state)
if (bands is None):
bandwidths = np.array([2, 4, 8, 16, 32])
else:
bandwidths = np.array(bands)
filter_bank = load_filterbank(bandwidths, fs, order=filter_order, max_freq=40, ftype=filter_type)
if (time_windows is None):
time_windows = (np.array([[2.5, 6]]) * fs).astype(int)
else:
time_windows = (np.array(time_windows) * fs).astype(int)
self.riemannian = RiemannianMultiscale(filter_bank, time_windows, riem_opt=riem_opt, rho=rho, vectorized=True)
self.no_bands = filter_bank.shape[0]
self.no_time_windows = time_windows.shape[0]
self.no_riem = None
self.no_features = None |
def fit(self, samples, labels):
' Training\n\n Parameters\n ----------\n\n samples: np.array, size=(N, C, T)\n training samples\n\n labels: np.array, size=(N)\n training labels\n '
assert (len(samples.shape) == 3)
no_channels = samples.shape[1]
self.no_riem = int(((no_channels * (no_channels + 1)) / 2))
self.no_features = ((self.no_riem * self.no_bands) * self.no_time_windows)
features = self.riemannian.fit(samples)
self.classifier.fit(features, labels) | -7,846,581,110,877,279,000 | Training
Parameters
----------
samples: np.array, size=(N, C, T)
training samples
labels: np.array, size=(N)
training labels | multiscale_bci_python/riemannian_model.py | fit | pulp-platform/multispectral-riemannian | python | def fit(self, samples, labels):
' Training\n\n Parameters\n ----------\n\n samples: np.array, size=(N, C, T)\n training samples\n\n labels: np.array, size=(N)\n training labels\n '
assert (len(samples.shape) == 3)
no_channels = samples.shape[1]
self.no_riem = int(((no_channels * (no_channels + 1)) / 2))
self.no_features = ((self.no_riem * self.no_bands) * self.no_time_windows)
features = self.riemannian.fit(samples)
self.classifier.fit(features, labels) |