test.py
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import kf_sdk
from kf_sdk.rest import ApiException
from kf_sdk.models import NewSession
from pprint import pprint
# Defining the host is optional and defaults to http://localhost/user-micro-services/v1
# See configuration.py for a list of all supported configuration parameters.
configuration_users = kf_sdk.Configuration(
host = "https://bigdata.nsu.ru:8460/user-micro-services/v1"
)
# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.
# Configure Bearer authorization: HTTPBearer
#configuration = kappa_users.Configuration(
# access_token = os.environ["BEARER_TOKEN"]
#)
# Enter a context with an instance of the API client
with kf_sdk.ApiClient(configuration_users) as api_client:
# Create an instance of the API class
api_instance = kf_sdk.SessionManagementApi(api_client)
login_id = "anonymous"
passwd = "anonymous"
new_session = NewSession(login_id=login_id,passwd=passwd)
try:
# New Session
api_response = api_instance.get_new_session(new_session)
token = api_response.token
user_id = api_response.user_id
user_type_id = api_response.user_type_id
print("The response of SessionManagementApi->new_session_session_new_post:\n")
pprint(api_response)
except ApiException as e:
print("Exception when calling ExpertManagementApi->new_session_session_new_post: %s\n" % e)
configuration_data = kf_sdk.Configuration(
host = "https://bigdata.nsu.ru:8460/data-micro-services/v1",
access_token = token
)
with kf_sdk.ApiClient(configuration_data) as api_client:
# Create an instance of the API class
api_instance = kf_sdk.DatasetManagementApi(api_client)
dataset_id = 581
dataset_version_no = '1.0.0'
try:
# Get Dataset Version
api_response = api_instance.get_dataset_version_datasets_versions_user_id_user_type_id_dataset_id_dataset_version_no_get(user_id, user_type_id, dataset_id, dataset_version_no)
# api_response = api_instance.get_dataset_version_archive_datasets_versions_archive_user_id_user_type_id_dataset_id_dataset_version_no_get(user_id, user_type_id, dataset_id, dataset_version_no)
# api_response = api_instance.get_dataset_version_archive_datasets_versions_archive_user_id_user_type_id_dataset_id_dataset_version_no_get_with_http_info(user_id, user_type_id, dataset_id, dataset_version_no)
# api_response = api_instance.get_dataset_version_archive_datasets_versions_archive_user_id_user_type_id_dataset_id_dataset_version_no_get_without_preload_content(user_id, user_type_id, dataset_id, dataset_version_no)
pprint(api_response)
# with open("tmp.zip","wb") as f:
# f.write(api_response.data)
except Exception as e:
print("Exception when calling DatasetManagementApi->get_dataset_version_datasets_versions_user_id_user_type_id_dataset_id_dataset_version_no_get: %s\n" % e)