ibm_gdsc_sdk_saas.EcosystemServiceApi

All URIs are relative to http://localhost

Method	HTTP request	Description
ecosystem_service_create_dataset	POST /api/v3/integrations/datasets	Summary: Create dataset Description: Save a definition in the database.
ecosystem_service_data_insert	POST /api/v3/integrations/datasets/{dataset_name}	Summary: Data insert Description: Process Data received from webhook API and insert.
ecosystem_service_delete_datasets	DELETE /api/v3/integrations/datasets	Summary: Delete datasets Description: Delete an array of datasets.
ecosystem_service_get_dataset_data	GET /api/v3/integrations/datasets/{dataset_name}/data	Summary: Get dataset data Description: Return data report for a given dataset.
ecosystem_service_get_dataset_detail	GET /api/v3/integrations/datasets/{dataset_name}/details	Summary: Get dataset detail Description: Return detail on a dataset definition.
ecosystem_service_get_datasets	GET /api/v3/integrations/datasets	Summary: Get datasets Description: Return dataset list that matches the specified filter.
ecosystem_service_get_purgable_rows	POST /api/v3/integrations/purge	Summary: Get purgable rows Description: Check the number of rows that can be purged.
ecosystem_service_purge_data	DELETE /api/v3/integrations/datasets/data	Summary: Purge data Description: Purge data.
ecosystem_service_test_integration	POST /api/v3/integrations/setup/test	Summary: Test integration Description: Test the integration connection with the arguments passed in the TestIntegrationRequest. When possible a test message is sent to the integration to ensure it is functional. Currently this API only supports API_IMPORT type integrations

ecosystem_service_create_dataset

Ecosystemv3CreateDatasetResponse ecosystem_service_create_dataset(ecosystemv3_create_dataset_request)

Summary: Create dataset Description: Save a definition in the database.

Example

Basic Authentication (BasicAuth):
Api Key Authentication (ApiKeyAuth):

import ibm_gdsc_sdk_saas,os
from ibm_gdsc_sdk_saas.models.ecosystemv3_create_dataset_request import Ecosystemv3CreateDatasetRequest
from ibm_gdsc_sdk_saas.models.ecosystemv3_create_dataset_response import Ecosystemv3CreateDatasetResponse
from ibm_gdsc_sdk_saas.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost
# See configuration.py for a list of all supported configuration parameters.
configuration = ibm_gdsc_sdk_saas.Configuration(
    host = "http://localhost"
)

# 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 HTTP basic authorization: BasicAuth
configuration = ibm_gdsc_sdk_saas.Configuration(
    username = os.environ["USERNAME"],
    password = os.environ["PASSWORD"]
)

# Configure API key authorization: ApiKeyAuth
configuration.api_key['ApiKeyAuth'] = os.environ["API_KEY"]

# Uncomment below to setup prefix (e.g. Bearer) for API key, if needed
# configuration.api_key_prefix['ApiKeyAuth'] = 'Bearer'

# Enter a context with an instance of the API client
with ibm_gdsc_sdk_saas.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = ibm_gdsc_sdk_saas.EcosystemServiceApi(api_client)
    ecosystemv3_create_dataset_request = ibm_gdsc_sdk_saas.Ecosystemv3CreateDatasetRequest() # Ecosystemv3CreateDatasetRequest | 

    try:
        # Summary: Create dataset Description: Save a definition in the database.
        api_response = api_instance.ecosystem_service_create_dataset(ecosystemv3_create_dataset_request)
        print("The response of EcosystemServiceApi->ecosystem_service_create_dataset:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling EcosystemServiceApi->ecosystem_service_create_dataset: %s\n" % e)

Parameters

Name	Type	Description	Notes
ecosystemv3_create_dataset_request	Ecosystemv3CreateDatasetRequest

Return type

Ecosystemv3CreateDatasetResponse

Authorization

BasicAuth, ApiKeyAuth

HTTP request headers

Content-Type: application/json
Accept: application/json

HTTP response details

Status code	Description	Response headers
200	A successful response.	-
0	An unexpected error response.	-

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ecosystem_service_data_insert

Ecosystemv3DataInsertResponse ecosystem_service_data_insert(dataset_name, ecosystemv3_data_insert_request)

Summary: Data insert Description: Process Data received from webhook API and insert.

Example

Basic Authentication (BasicAuth):
Api Key Authentication (ApiKeyAuth):

import ibm_gdsc_sdk_saas,os
from ibm_gdsc_sdk_saas.models.ecosystemv3_data_insert_request import Ecosystemv3DataInsertRequest
from ibm_gdsc_sdk_saas.models.ecosystemv3_data_insert_response import Ecosystemv3DataInsertResponse
from ibm_gdsc_sdk_saas.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost
# See configuration.py for a list of all supported configuration parameters.
configuration = ibm_gdsc_sdk_saas.Configuration(
    host = "http://localhost"
)

# 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 HTTP basic authorization: BasicAuth
configuration = ibm_gdsc_sdk_saas.Configuration(
    username = os.environ["USERNAME"],
    password = os.environ["PASSWORD"]
)

# Configure API key authorization: ApiKeyAuth
configuration.api_key['ApiKeyAuth'] = os.environ["API_KEY"]

# Uncomment below to setup prefix (e.g. Bearer) for API key, if needed
# configuration.api_key_prefix['ApiKeyAuth'] = 'Bearer'

# Enter a context with an instance of the API client
with ibm_gdsc_sdk_saas.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = ibm_gdsc_sdk_saas.EcosystemServiceApi(api_client)
    dataset_name = 'dataset_name_example' # str | Data set target name.
    ecosystemv3_data_insert_request = ibm_gdsc_sdk_saas.Ecosystemv3DataInsertRequest() # Ecosystemv3DataInsertRequest | 

    try:
        # Summary: Data insert Description: Process Data received from webhook API and insert.
        api_response = api_instance.ecosystem_service_data_insert(dataset_name, ecosystemv3_data_insert_request)
        print("The response of EcosystemServiceApi->ecosystem_service_data_insert:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling EcosystemServiceApi->ecosystem_service_data_insert: %s\n" % e)

Parameters

Name	Type	Description	Notes
dataset_name	str	Data set target name.
ecosystemv3_data_insert_request	Ecosystemv3DataInsertRequest

Return type

Ecosystemv3DataInsertResponse

Authorization

BasicAuth, ApiKeyAuth

HTTP request headers

Content-Type: application/json
Accept: application/json

HTTP response details

Status code	Description	Response headers
200	A successful response.	-
0	An unexpected error response.	-

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ecosystem_service_delete_datasets

Ecosystemv3DeleteDatasetsResponse ecosystem_service_delete_datasets(dataset_names=dataset_names)

Summary: Delete datasets Description: Delete an array of datasets.

Example

Basic Authentication (BasicAuth):
Api Key Authentication (ApiKeyAuth):

import ibm_gdsc_sdk_saas,os
from ibm_gdsc_sdk_saas.models.ecosystemv3_delete_datasets_response import Ecosystemv3DeleteDatasetsResponse
from ibm_gdsc_sdk_saas.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost
# See configuration.py for a list of all supported configuration parameters.
configuration = ibm_gdsc_sdk_saas.Configuration(
    host = "http://localhost"
)

# 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 HTTP basic authorization: BasicAuth
configuration = ibm_gdsc_sdk_saas.Configuration(
    username = os.environ["USERNAME"],
    password = os.environ["PASSWORD"]
)

# Configure API key authorization: ApiKeyAuth
configuration.api_key['ApiKeyAuth'] = os.environ["API_KEY"]

# Uncomment below to setup prefix (e.g. Bearer) for API key, if needed
# configuration.api_key_prefix['ApiKeyAuth'] = 'Bearer'

# Enter a context with an instance of the API client
with ibm_gdsc_sdk_saas.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = ibm_gdsc_sdk_saas.EcosystemServiceApi(api_client)
    dataset_names = ['dataset_names_example'] # List[str] | Name of the dataset, required field. (optional)

    try:
        # Summary: Delete datasets Description: Delete an array of datasets.
        api_response = api_instance.ecosystem_service_delete_datasets(dataset_names=dataset_names)
        print("The response of EcosystemServiceApi->ecosystem_service_delete_datasets:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling EcosystemServiceApi->ecosystem_service_delete_datasets: %s\n" % e)

Parameters

Name	Type	Description	Notes
dataset_names	List[str]	Name of the dataset, required field.	[optional]

Return type

Ecosystemv3DeleteDatasetsResponse

Authorization

BasicAuth, ApiKeyAuth

HTTP request headers

Content-Type: Not defined
Accept: application/json

HTTP response details

Status code	Description	Response headers
200	A successful response.	-
0	An unexpected error response.	-

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ecosystem_service_get_dataset_data

Ecosystemv3GetDatasetDataResponse ecosystem_service_get_dataset_data(dataset_name, offset=offset, limit=limit, return_header=return_header, var_field=var_field, value=value, sort_field=sort_field, sort_order=sort_order)

Summary: Get dataset data Description: Return data report for a given dataset.

Example

Basic Authentication (BasicAuth):
Api Key Authentication (ApiKeyAuth):

import ibm_gdsc_sdk_saas,os
from ibm_gdsc_sdk_saas.models.ecosystemv3_get_dataset_data_response import Ecosystemv3GetDatasetDataResponse
from ibm_gdsc_sdk_saas.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost
# See configuration.py for a list of all supported configuration parameters.
configuration = ibm_gdsc_sdk_saas.Configuration(
    host = "http://localhost"
)

# 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 HTTP basic authorization: BasicAuth
configuration = ibm_gdsc_sdk_saas.Configuration(
    username = os.environ["USERNAME"],
    password = os.environ["PASSWORD"]
)

# Configure API key authorization: ApiKeyAuth
configuration.api_key['ApiKeyAuth'] = os.environ["API_KEY"]

# Uncomment below to setup prefix (e.g. Bearer) for API key, if needed
# configuration.api_key_prefix['ApiKeyAuth'] = 'Bearer'

# Enter a context with an instance of the API client
with ibm_gdsc_sdk_saas.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = ibm_gdsc_sdk_saas.EcosystemServiceApi(api_client)
    dataset_name = 'dataset_name_example' # str | Name of the dataset.
    offset = 56 # int | The amount to offset the rows by for pagination. (optional)
    limit = 56 # int | The max amount of rows to return for pagination. (optional)
    return_header = True # bool | If needs to return header information. It is for pagination. The first page needs header, the rest doesn't need. (optional)
    var_field = 'var_field_example' # str | Search field. (optional)
    value = 'value_example' # str | Search value. (optional)
    sort_field = 'sort_field_example' # str | Field to sort. (optional)
    sort_order = NONE # str | Sort order. (optional) (default to NONE)

    try:
        # Summary: Get dataset data Description: Return data report for a given dataset.
        api_response = api_instance.ecosystem_service_get_dataset_data(dataset_name, offset=offset, limit=limit, return_header=return_header, var_field=var_field, value=value, sort_field=sort_field, sort_order=sort_order)
        print("The response of EcosystemServiceApi->ecosystem_service_get_dataset_data:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling EcosystemServiceApi->ecosystem_service_get_dataset_data: %s\n" % e)

Parameters

Name	Type	Description	Notes
dataset_name	str	Name of the dataset.
offset	int	The amount to offset the rows by for pagination.	[optional]
limit	int	The max amount of rows to return for pagination.	[optional]
return_header	bool	If needs to return header information. It is for pagination. The first page needs header, the rest doesn't need.	[optional]
var_field	str	Search field.	[optional]
value	str	Search value.	[optional]
sort_field	str	Field to sort.	[optional]
sort_order	str	Sort order.	[optional] [default to NONE]

Return type

Ecosystemv3GetDatasetDataResponse

Authorization

BasicAuth, ApiKeyAuth

HTTP request headers

Content-Type: Not defined
Accept: application/json

HTTP response details

Status code	Description	Response headers
200	A successful response.	-
0	An unexpected error response.	-

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ecosystem_service_get_dataset_detail

Ecosystemv3GetDatasetDetailResponse ecosystem_service_get_dataset_detail(dataset_name)

Summary: Get dataset detail Description: Return detail on a dataset definition.

Example

Basic Authentication (BasicAuth):
Api Key Authentication (ApiKeyAuth):

import ibm_gdsc_sdk_saas,os
from ibm_gdsc_sdk_saas.models.ecosystemv3_get_dataset_detail_response import Ecosystemv3GetDatasetDetailResponse
from ibm_gdsc_sdk_saas.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost
# See configuration.py for a list of all supported configuration parameters.
configuration = ibm_gdsc_sdk_saas.Configuration(
    host = "http://localhost"
)

# 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 HTTP basic authorization: BasicAuth
configuration = ibm_gdsc_sdk_saas.Configuration(
    username = os.environ["USERNAME"],
    password = os.environ["PASSWORD"]
)

# Configure API key authorization: ApiKeyAuth
configuration.api_key['ApiKeyAuth'] = os.environ["API_KEY"]

# Uncomment below to setup prefix (e.g. Bearer) for API key, if needed
# configuration.api_key_prefix['ApiKeyAuth'] = 'Bearer'

# Enter a context with an instance of the API client
with ibm_gdsc_sdk_saas.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = ibm_gdsc_sdk_saas.EcosystemServiceApi(api_client)
    dataset_name = 'dataset_name_example' # str | Name of the dataset.

    try:
        # Summary: Get dataset detail Description: Return detail on a dataset definition.
        api_response = api_instance.ecosystem_service_get_dataset_detail(dataset_name)
        print("The response of EcosystemServiceApi->ecosystem_service_get_dataset_detail:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling EcosystemServiceApi->ecosystem_service_get_dataset_detail: %s\n" % e)

Parameters

Name	Type	Description	Notes
dataset_name	str	Name of the dataset.

Return type

Ecosystemv3GetDatasetDetailResponse

Authorization

BasicAuth, ApiKeyAuth

HTTP request headers

Content-Type: Not defined
Accept: application/json

HTTP response details

Status code	Description	Response headers
200	A successful response.	-
0	An unexpected error response.	-

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ecosystem_service_get_datasets

Ecosystemv3GetDatasetsResponse ecosystem_service_get_datasets(filter_start_time=filter_start_time, filter_end_time=filter_end_time, filter_dataset_names=filter_dataset_names, offset=offset, limit=limit, include_filter_counts=include_filter_counts)

Summary: Get datasets Description: Return dataset list that matches the specified filter.

Example

Basic Authentication (BasicAuth):
Api Key Authentication (ApiKeyAuth):

import ibm_gdsc_sdk_saas,os
from ibm_gdsc_sdk_saas.models.ecosystemv3_get_datasets_response import Ecosystemv3GetDatasetsResponse
from ibm_gdsc_sdk_saas.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost
# See configuration.py for a list of all supported configuration parameters.
configuration = ibm_gdsc_sdk_saas.Configuration(
    host = "http://localhost"
)

# 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 HTTP basic authorization: BasicAuth
configuration = ibm_gdsc_sdk_saas.Configuration(
    username = os.environ["USERNAME"],
    password = os.environ["PASSWORD"]
)

# Configure API key authorization: ApiKeyAuth
configuration.api_key['ApiKeyAuth'] = os.environ["API_KEY"]

# Uncomment below to setup prefix (e.g. Bearer) for API key, if needed
# configuration.api_key_prefix['ApiKeyAuth'] = 'Bearer'

# Enter a context with an instance of the API client
with ibm_gdsc_sdk_saas.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = ibm_gdsc_sdk_saas.EcosystemServiceApi(api_client)
    filter_start_time = '2013-10-20T19:20:30+01:00' # datetime | Return datasets created at this time or later (>=). (optional)
    filter_end_time = '2013-10-20T19:20:30+01:00' # datetime | Return datasets created before this time (<). (optional)
    filter_dataset_names = ['filter_dataset_names_example'] # List[str] | The state filter groups commonly paired states. Only returns records that include the specified names. (optional)
    offset = 56 # int | The amount to offset the rows by for pagination. (optional)
    limit = 56 # int | The max amount of rows to return for pagination. (optional)
    include_filter_counts = True # bool | Computing the filter counts is relatively expensive, only compute when needed. (optional)

    try:
        # Summary: Get datasets Description: Return dataset list that matches the specified filter.
        api_response = api_instance.ecosystem_service_get_datasets(filter_start_time=filter_start_time, filter_end_time=filter_end_time, filter_dataset_names=filter_dataset_names, offset=offset, limit=limit, include_filter_counts=include_filter_counts)
        print("The response of EcosystemServiceApi->ecosystem_service_get_datasets:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling EcosystemServiceApi->ecosystem_service_get_datasets: %s\n" % e)

Parameters

Name	Type	Description	Notes
filter_start_time	datetime	Return datasets created at this time or later (>=).	[optional]
filter_end_time	datetime	Return datasets created before this time (<).	[optional]
filter_dataset_names	List[str]	The state filter groups commonly paired states. Only returns records that include the specified names.	[optional]
offset	int	The amount to offset the rows by for pagination.	[optional]
limit	int	The max amount of rows to return for pagination.	[optional]
include_filter_counts	bool	Computing the filter counts is relatively expensive, only compute when needed.	[optional]

Return type

Ecosystemv3GetDatasetsResponse

Authorization

BasicAuth, ApiKeyAuth

HTTP request headers

Content-Type: Not defined
Accept: application/json

HTTP response details

Status code	Description	Response headers
200	A successful response.	-
0	An unexpected error response.	-

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ecosystem_service_get_purgable_rows

Ecosystemv3GetPurgableRowsResponse ecosystem_service_get_purgable_rows(ecosystemv3_get_purgable_rows_request)

Summary: Get purgable rows Description: Check the number of rows that can be purged.

Example

Basic Authentication (BasicAuth):
Api Key Authentication (ApiKeyAuth):

import ibm_gdsc_sdk_saas,os
from ibm_gdsc_sdk_saas.models.ecosystemv3_get_purgable_rows_request import Ecosystemv3GetPurgableRowsRequest
from ibm_gdsc_sdk_saas.models.ecosystemv3_get_purgable_rows_response import Ecosystemv3GetPurgableRowsResponse
from ibm_gdsc_sdk_saas.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost
# See configuration.py for a list of all supported configuration parameters.
configuration = ibm_gdsc_sdk_saas.Configuration(
    host = "http://localhost"
)

# 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 HTTP basic authorization: BasicAuth
configuration = ibm_gdsc_sdk_saas.Configuration(
    username = os.environ["USERNAME"],
    password = os.environ["PASSWORD"]
)

# Configure API key authorization: ApiKeyAuth
configuration.api_key['ApiKeyAuth'] = os.environ["API_KEY"]

# Uncomment below to setup prefix (e.g. Bearer) for API key, if needed
# configuration.api_key_prefix['ApiKeyAuth'] = 'Bearer'

# Enter a context with an instance of the API client
with ibm_gdsc_sdk_saas.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = ibm_gdsc_sdk_saas.EcosystemServiceApi(api_client)
    ecosystemv3_get_purgable_rows_request = ibm_gdsc_sdk_saas.Ecosystemv3GetPurgableRowsRequest() # Ecosystemv3GetPurgableRowsRequest | 

    try:
        # Summary: Get purgable rows Description: Check the number of rows that can be purged.
        api_response = api_instance.ecosystem_service_get_purgable_rows(ecosystemv3_get_purgable_rows_request)
        print("The response of EcosystemServiceApi->ecosystem_service_get_purgable_rows:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling EcosystemServiceApi->ecosystem_service_get_purgable_rows: %s\n" % e)

Parameters

Name	Type	Description	Notes
ecosystemv3_get_purgable_rows_request	Ecosystemv3GetPurgableRowsRequest

Return type

Ecosystemv3GetPurgableRowsResponse

Authorization

BasicAuth, ApiKeyAuth

HTTP request headers

Content-Type: application/json
Accept: application/json

HTTP response details

Status code	Description	Response headers
200	A successful response.	-
0	An unexpected error response.	-

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ecosystem_service_purge_data

Ecosystemv3PurgeDataResponse ecosystem_service_purge_data(dataset_names=dataset_names)

Summary: Purge data Description: Purge data.

Example

Basic Authentication (BasicAuth):
Api Key Authentication (ApiKeyAuth):

import ibm_gdsc_sdk_saas,os
from ibm_gdsc_sdk_saas.models.ecosystemv3_purge_data_response import Ecosystemv3PurgeDataResponse
from ibm_gdsc_sdk_saas.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost
# See configuration.py for a list of all supported configuration parameters.
configuration = ibm_gdsc_sdk_saas.Configuration(
    host = "http://localhost"
)

# 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 HTTP basic authorization: BasicAuth
configuration = ibm_gdsc_sdk_saas.Configuration(
    username = os.environ["USERNAME"],
    password = os.environ["PASSWORD"]
)

# Configure API key authorization: ApiKeyAuth
configuration.api_key['ApiKeyAuth'] = os.environ["API_KEY"]

# Uncomment below to setup prefix (e.g. Bearer) for API key, if needed
# configuration.api_key_prefix['ApiKeyAuth'] = 'Bearer'

# Enter a context with an instance of the API client
with ibm_gdsc_sdk_saas.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = ibm_gdsc_sdk_saas.EcosystemServiceApi(api_client)
    dataset_names = ['dataset_names_example'] # List[str] | Name of the datasets, required field. (optional)

    try:
        # Summary: Purge data Description: Purge data.
        api_response = api_instance.ecosystem_service_purge_data(dataset_names=dataset_names)
        print("The response of EcosystemServiceApi->ecosystem_service_purge_data:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling EcosystemServiceApi->ecosystem_service_purge_data: %s\n" % e)

Parameters

Name	Type	Description	Notes
dataset_names	List[str]	Name of the datasets, required field.	[optional]

Return type

Ecosystemv3PurgeDataResponse

Authorization

BasicAuth, ApiKeyAuth

HTTP request headers

Content-Type: Not defined
Accept: application/json

HTTP response details

Status code	Description	Response headers
200	A successful response.	-
0	An unexpected error response.	-

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ecosystem_service_test_integration

Ecosystemv3TestIntegrationResponse ecosystem_service_test_integration(ecosystemv3_test_integration_request)

Summary: Test integration Description: Test the integration connection with the arguments passed in the TestIntegrationRequest. When possible a test message is sent to the integration to ensure it is functional. Currently this API only supports API_IMPORT type integrations

Example

Basic Authentication (BasicAuth):
Api Key Authentication (ApiKeyAuth):

import ibm_gdsc_sdk_saas,os
from ibm_gdsc_sdk_saas.models.ecosystemv3_test_integration_request import Ecosystemv3TestIntegrationRequest
from ibm_gdsc_sdk_saas.models.ecosystemv3_test_integration_response import Ecosystemv3TestIntegrationResponse
from ibm_gdsc_sdk_saas.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost
# See configuration.py for a list of all supported configuration parameters.
configuration = ibm_gdsc_sdk_saas.Configuration(
    host = "http://localhost"
)

# 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 HTTP basic authorization: BasicAuth
configuration = ibm_gdsc_sdk_saas.Configuration(
    username = os.environ["USERNAME"],
    password = os.environ["PASSWORD"]
)

# Configure API key authorization: ApiKeyAuth
configuration.api_key['ApiKeyAuth'] = os.environ["API_KEY"]

# Uncomment below to setup prefix (e.g. Bearer) for API key, if needed
# configuration.api_key_prefix['ApiKeyAuth'] = 'Bearer'

# Enter a context with an instance of the API client
with ibm_gdsc_sdk_saas.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = ibm_gdsc_sdk_saas.EcosystemServiceApi(api_client)
    ecosystemv3_test_integration_request = ibm_gdsc_sdk_saas.Ecosystemv3TestIntegrationRequest() # Ecosystemv3TestIntegrationRequest | 

    try:
        # Summary: Test integration Description: Test the integration connection with the arguments passed in the TestIntegrationRequest.  When possible a test message is sent to the integration to ensure it is functional. Currently this API only supports API_IMPORT type integrations
        api_response = api_instance.ecosystem_service_test_integration(ecosystemv3_test_integration_request)
        print("The response of EcosystemServiceApi->ecosystem_service_test_integration:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling EcosystemServiceApi->ecosystem_service_test_integration: %s\n" % e)

Parameters

Name	Type	Description	Notes
ecosystemv3_test_integration_request	Ecosystemv3TestIntegrationRequest

Return type

Ecosystemv3TestIntegrationResponse

Authorization

BasicAuth, ApiKeyAuth

HTTP request headers

Content-Type: application/json
Accept: application/json

HTTP response details

Status code	Description	Response headers
200	A successful response.	-
0	An unexpected error response.	-

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ibm_gdsc_sdk_saas.EcosystemServiceApi

ecosystem_service_create_dataset

Example

Parameters

Return type

Authorization

HTTP request headers

HTTP response details

ecosystem_service_data_insert

Example

Parameters

Return type

Authorization

HTTP request headers

HTTP response details

ecosystem_service_delete_datasets

Example

Parameters

Return type

Authorization

HTTP request headers

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ecosystem_service_get_dataset_data

Example

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Return type

Authorization

HTTP request headers

HTTP response details

ecosystem_service_get_dataset_detail

Example

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Return type

Authorization

HTTP request headers

HTTP response details

ecosystem_service_get_datasets

Example

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Return type

Authorization

HTTP request headers

HTTP response details

ecosystem_service_get_purgable_rows

Example

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Return type

Authorization

HTTP request headers

HTTP response details

ecosystem_service_purge_data

Example

Parameters

Return type

Authorization

HTTP request headers

HTTP response details

ecosystem_service_test_integration

Example

Parameters

Return type

Authorization

HTTP request headers

HTTP response details