def get_batch_anomaly_score(self, batch_anomaly_score, query_string=''):
"""Retrieves a batch anomaly score.
The batch_anomaly_score parameter should be a string containing the
batch_anomaly_score id or the dict returned by
create_batch_anomaly_score.
As batch_anomaly_score is an evolving object that is processed
until it reaches the FINISHED or FAULTY state, the function will
return a dict that encloses the batch_anomaly_score values and state
info available at the time it is called.
"""
check_resource_type(batch_anomaly_score,
BATCH_ANOMALY_SCORE_PATH,
message="A batch anomaly score id is needed.")
return self.get_resource(batch_anomaly_score,
query_string=query_string)
def download_batch_projection(self,
batch_projection,
filename=None,
retries=10):
"""Retrieves the batch projections file.
Downloads projections, that are stored in a remote CSV file. If
a path is given in filename, the contents of the file are downloaded
and saved locally. A file-like object is returned otherwise.
"""
check_resource_type(batch_projection,
BATCH_PROJECTION_PATH,
message="A batch projection id is needed.")
return self._download_resource(batch_projection,
filename,
retries=retries)
def download_batch_anomaly_score(self,
batch_anomaly_score,
filename=None,
retries=10):
"""Retrieves the batch anomaly score file.
Downloads anomaly scores, that are stored in a remote CSV file. If
a path is given in filename, the contents of the file are downloaded
and saved locally. A file-like object is returned otherwise.
"""
check_resource_type(batch_anomaly_score,
BATCH_ANOMALY_SCORE_PATH,
message="A batch anomaly score id is needed.")
return self._download_resource(batch_anomaly_score,
filename,
retries=retries)
def get_library(self, library, query_string=''):
"""Retrieves a library.
The library parameter should be a string containing the
library id or the dict returned by create_script.
As library is an evolving object that is processed
until it reaches the FINISHED or FAULTY state, the function will
return a dict that encloses the library content and state info
available at the time it is called.
"""
check_resource_type(library,
LIBRARY_PATH,
message="A library id is needed.")
library_id = get_library_id(library)
if library_id:
return self._get("%s%s" % (self.url, library_id),
query_string=query_string)
def get_script(self, script, query_string=''):
"""Retrieves a script.
The script parameter should be a string containing the
script id or the dict returned by create_script.
As script is an evolving object that is processed
until it reaches the FINISHED or FAULTY state, the function will
return a dict that encloses the script content and state info
available at the time it is called.
"""
check_resource_type(script,
SCRIPT_PATH,
message="A script id is needed.")
script_id = get_script_id(script)
if script_id:
return self._get("%s%s" % (self.url, script_id),
query_string=query_string)
def get_batch_centroid(self, batch_centroid, query_string=''):
"""Retrieves a batch centroid.
The batch_centroid parameter should be a string containing the
batch_centroid id or the dict returned by create_batch_centroid.
As batch_centroid is an evolving object that is processed
until it reaches the FINISHED or FAULTY state, the function will
return a dict that encloses the batch_centroid values and state
info available at the time it is called.
"""
check_resource_type(batch_centroid,
BATCH_CENTROID_PATH,
message="A batch centroid id is needed.")
batch_centroid_id = get_batch_centroid_id(batch_centroid)
if batch_centroid_id:
return self._get("%s%s" % (self.url, batch_centroid_id),
query_string=query_string)
def get_dataset(self, dataset, query_string=''):
"""Retrieves a dataset.
The dataset parameter should be a string containing the
dataset id or the dict returned by create_dataset.
As dataset is an evolving object that is processed
until it reaches the FINISHED or FAULTY state, the function will
return a dict that encloses the dataset values and state info
available at the time it is called.
"""
check_resource_type(dataset,
DATASET_PATH,
message="A dataset id is needed.")
dataset_id = get_dataset_id(dataset)
if dataset_id:
return self._get("%s%s" % (self.url, dataset_id),
query_string=query_string)
def get_correlation(self, correlation, query_string=''):
"""Retrieves a correlation.
The correlation parameter should be a string containing the
correlation id or the dict returned by create_correlation.
As correlation is an evolving object that is processed
until it reaches the FINISHED or FAULTY state, the function will
return a dict that encloses the correlation values and state info
available at the time it is called.
"""
check_resource_type(correlation,
CORRELATION_PATH,
message="A correlation id is needed.")
correlation_id = get_correlation_id(correlation)
if correlation_id:
return self._get("%s%s" % (self.url, correlation_id),
query_string=query_string)
def get_sample(self, sample, query_string=''):
"""Retrieves a sample.
The sample parameter should be a string containing the
sample id or the dict returned by create_sample.
As sample is an evolving object that is processed
until it reaches the FINISHED or FAULTY state, the function will
return a dict that encloses the sample values and state info
available at the time it is called.
"""
check_resource_type(sample,
SAMPLE_PATH,
message="A sample id is needed.")
sample_id = get_sample_id(sample)
if sample_id:
return self._get("%s%s" % (self.url, sample_id),
query_string=query_string)
def get_batch_topic_distribution(self,
batch_topic_distribution,
query_string=''):
"""Retrieves a batch topic distribution.
The batch_topic_distribution parameter should be a string
containing the batch_topic_distribution id or the dict
returned by create_batch_topic_distribution.
As batch_topic_distribution is an evolving object that is processed
until it reaches the FINISHED or FAULTY state, the function will
return a dict that encloses the batch_topic_distribution values
and state info available at the time it is called.
"""
check_resource_type(batch_topic_distribution,
BATCH_TOPIC_DISTRIBUTION_PATH,
message="A batch topic distribution id is needed.")
return self.get_resource(batch_topic_distribution,
query_string=query_string)
def get_project(self, project, query_string=''):
"""Retrieves a project.
The project parameter should be a string containing the
project id or the dict returned by create_project.
As every resource, is an evolving object that is processed
until it reaches the FINISHED or FAULTY state. The function will
return a dict that encloses the project values and state info
available at the time it is called.
"""
check_resource_type(project,
PROJECT_PATH,
message="A project id is needed.")
project_id = get_project_id(project)
if project_id:
return self._get("%s%s" % (self.url, project_id),
query_string=query_string,
organization=True)
def get_external_connector(self, external_connector, query_string=''):
"""Retrieves an external connector.
The external connector parameter should be a string containing the
external connector id or the dict returned by
create_external_connector.
As an external connector is an evolving object that is processed
until it reaches the FINISHED or FAULTY state, the function will
return a dict that encloses the connector contents and state info
available at the time it is called.
"""
check_resource_type(external_connector,
EXTERNAL_CONNECTOR_PATH,
message="An external connector id is needed.")
external_connector_id = get_external_connector_id(external_connector)
if external_connector_id:
return self._get("%s%s" % (self.url, external_connector_id),
query_string=query_string)
def download_batch_topic_distribution(self,
batch_topic_distribution,
filename=None):
"""Retrieves the batch topic distribution file.
Downloads topic distributions, that are stored in a remote CSV file.
If a path is given in filename, the contents of the file are
downloaded and saved locally. A file-like object is returned
otherwise.
"""
check_resource_type(batch_topic_distribution,
BATCH_TOPIC_DISTRIBUTION_PATH,
message="A batch topic distribution id is needed.")
batch_topic_distribution_id = get_batch_topic_distribution_id( \
batch_topic_distribution)
if batch_topic_distribution_id:
return self._download("%s%s%s" % \
(self.url, batch_topic_distribution_id, DOWNLOAD_DIR), \
filename=filename)
def get_cluster(self, cluster, query_string='',
shared_username=None, shared_api_key=None):
"""Retrieves a cluster.
The model parameter should be a string containing the
cluster id or the dict returned by create_cluster.
As cluster is an evolving object that is processed
until it reaches the FINISHED or FAULTY state, the function will
return a dict that encloses the cluster values and state info
available at the time it is called.
If this is a shared cluster, the username and sharing api key must
also be provided.
"""
check_resource_type(cluster, CLUSTER_PATH,
message="A cluster id is needed.")
return self.get_resource(cluster,
query_string=query_string,
shared_username=shared_username,
shared_api_key=shared_api_key)
def get_deepnet(self, deepnet, query_string='',
shared_username=None, shared_api_key=None):
"""Retrieves a deepnet.
The model parameter should be a string containing the
deepnet id or the dict returned by
create_deepnet.
As a deepnet is an evolving object that is processed
until it reaches the FINISHED or FAULTY state, the function will
return a dict that encloses the deepnet
values and state info available at the time it is called.
If this is a shared deepnet, the username and
sharing api key must also be provided.
"""
check_resource_type(deepnet, DEEPNET_PATH,
message="A deepnet id is needed.")
deepnet_id = get_deepnet_id(deepnet)
if deepnet_id:
return self._get("%s%s" % (self.url, deepnet_id),
query_string=query_string,
shared_username=shared_username,
shared_api_key=shared_api_key)
def get_optiml(self, optiml, query_string='',
shared_username=None, shared_api_key=None):
"""Retrieves an optiml.
The model parameter should be a string containing the
optiml id or the dict returned by
create_optiml.
As an optiml is an evolving object that is processed
until it reaches the FINISHED or FAULTY state, the function will
return a dict that encloses the optiml
values and state info available at the time it is called.
If this is a shared optiml, the username and
sharing api key must also be provided.
"""
check_resource_type(optiml, OPTIML_PATH,
message="An optiml id is needed.")
optiml_id = get_optiml_id(optiml)
if optiml_id:
return self._get("%s%s" % (self.url, optiml_id),
query_string=query_string,
shared_username=shared_username,
shared_api_key=shared_api_key)
def get_logistic_regression(self, logistic_regression, query_string='',
shared_username=None, shared_api_key=None):
"""Retrieves a logistic regression.
The model parameter should be a string containing the
logistic regression id or the dict returned by
create_logistic_regression.
As a logistic regression is an evolving object that is processed
until it reaches the FINISHED or FAULTY state, the function will
return a dict that encloses the logistic regression
values and state info available at the time it is called.
If this is a shared logistic regression, the username and
sharing api key must also be provided.
"""
check_resource_type(logistic_regression, LOGISTIC_REGRESSION_PATH,
message="A logistic regression id is needed.")
logistic_regression_id = get_logistic_regression_id(
logistic_regression)
if logistic_regression_id:
return self._get("%s%s" % (self.url, logistic_regression_id),
query_string=query_string,
shared_username=shared_username,
shared_api_key=shared_api_key)
def get_time_series(self, time_series, query_string='',
shared_username=None, shared_api_key=None):
"""Retrieves a time series.
The model parameter should be a string containing the
time series id or the dict returned by
create_time_series.
As a time series is an evolving object that is processed
until it reaches the FINISHED or FAULTY state, the function will
return a dict that encloses the time series
values and state info available at the time it is called.
If this is a shared time series, the username and
sharing api key must also be provided.
"""
check_resource_type(time_series, TIME_SERIES_PATH,
message="A time series id is needed.")
time_series_id = get_time_series_id(
time_series)
if time_series_id:
return self._get("%s%s" % (self.url, time_series_id),
query_string=query_string,
shared_username=shared_username,
shared_api_key=shared_api_key)
def get_topic_model(self,
topic_model,
query_string='',
shared_username=None,
shared_api_key=None):
"""Retrieves a Topic Model.
The topic_model parameter should be a string containing the
topic model ID or the dict returned by create_topic_model.
As the topic model is an evolving object that is processed
until it reaches the FINISHED or FAULTY state, the function will
return a dict that encloses the topic model values and state info
available at the time it is called.
If this is a shared topic model, the username and sharing api key
must also be provided.
"""
check_resource_type(topic_model,
TOPIC_MODEL_PATH,
message="A Topic Model id is needed.")
return self.get_resource(topic_model,
query_string=query_string,
shared_username=shared_username,
shared_api_key=shared_api_key)
def update_pca(self, pca, changes):
"""Updates a PCA.
"""
check_resource_type(pca, PCA_PATH, message="A PCA id is needed.")
return self.update_resource(pca, changes)
def delete_pca(self, pca):
"""Deletes a PCA.
"""
check_resource_type(pca, PCA_PATH, message="A PCA id is needed.")
return self.delete_resource(pca)
