def get_divide_and_conquer_list_of_raw_samples_from_datasource_by_dataset_id_with_http_info(self, dataset_id : Annotated[constr(strict=True), Field(..., description="ObjectId of the dataset")], dnc_shards : Annotated[conint(strict=True, ge=1), Field(..., description="The amount of shards we should split the data into when using the divide and conquer strategy. ")], var_from : Annotated[Optional[conint(strict=True, ge=0)], Field(description="Unix timestamp, only samples with a creation date after `from` will be returned. This parameter is ignored if `cursor` is specified. ")] = None, to : Annotated[Optional[conint(strict=True, ge=0)], Field(description="Unix timestamp, only samples with a creation date before `to` will be returned. This parameter is ignored if `cursor` is specified. ")] = None, relevant_filenames_file_name : Annotated[Optional[constr(strict=True, min_length=4)], Field(description="The name of the file within your datasource which contains a list of relevant filenames to list. See https://docs.lightly.ai/docker/getting_started/first_steps.html#specify-relevant-files for more details  ")] = None, **kwargs) -> ApiResponse:  # noqa: E501
        """divide and conquer the listing of samples files into multiple cursors  # noqa: E501

        Use divide and conquer to get multiple cursors for listing the raw samples  from the datasource for a specific taskName in parallel. The cursors should be used at the endpoint getListOfRawSamplesFromDatasourceByDatasetId. There is no guarantee that the cursors returned are in order, that any cursor will return the same number of items, or that there will be more than one cursor returned.   # noqa: E501
        This method makes a synchronous HTTP request by default. To make an
        asynchronous HTTP request, please pass async_req=True

        >>> thread = api.get_divide_and_conquer_list_of_raw_samples_from_datasource_by_dataset_id_with_http_info(dataset_id, dnc_shards, var_from, to, relevant_filenames_file_name, async_req=True)
        >>> result = thread.get()

        :param dataset_id: ObjectId of the dataset (required)
        :type dataset_id: str
        :param dnc_shards: The amount of shards we should split the data into when using the divide and conquer strategy.  (required)
        :type dnc_shards: int
        :param var_from: Unix timestamp, only samples with a creation date after `from` will be returned. This parameter is ignored if `cursor` is specified. 
        :type var_from: int
        :param to: Unix timestamp, only samples with a creation date before `to` will be returned. This parameter is ignored if `cursor` is specified. 
        :type to: int
        :param relevant_filenames_file_name: The name of the file within your datasource which contains a list of relevant filenames to list. See https://docs.lightly.ai/docker/getting_started/first_steps.html#specify-relevant-files for more details  
        :type relevant_filenames_file_name: str
        :param async_req: Whether to execute the request asynchronously.
        :type async_req: bool, optional
        :param _preload_content: if False, the ApiResponse.data will
                                 be set to none and raw_data will store the 
                                 HTTP response body without reading/decoding.
                                 Default is True.
        :type _preload_content: bool, optional
        :param _return_http_data_only: response data instead of ApiResponse
                                       object with status code, headers, etc
        :type _return_http_data_only: bool, optional
        :param _request_timeout: timeout setting for this request. If one
                                 number provided, it will be total request
                                 timeout. It can also be a pair (tuple) of
                                 (connection, read) timeouts.
        :param _request_auth: set to override the auth_settings for an a single
                              request; this effectively ignores the authentication
                              in the spec for a single request.
        :type _request_auth: dict, optional
        :type _content_type: string, optional: force content-type for the request
        :return: Returns the result object.
                 If the method is called asynchronously,
                 returns the request thread.
        :rtype: tuple(DivideAndConquerCursorData, status_code(int), headers(HTTPHeaderDict))
        """

        _params = locals()

        _all_params = [
            'dataset_id',
            'dnc_shards',
            'var_from',
            'to',
            'relevant_filenames_file_name'
        ]
        _all_params.extend(
            [
                'async_req',
                '_return_http_data_only',
                '_preload_content',
                '_request_timeout',
                '_request_auth',
                '_content_type',
                '_headers'
            ]
        )

        # validate the arguments
        for _key, _val in _params['kwargs'].items():
            if _key not in _all_params:
                raise ApiTypeError(
                    "Got an unexpected keyword argument '%s'"
                    " to method get_divide_and_conquer_list_of_raw_samples_from_datasource_by_dataset_id" % _key
                )
            _params[_key] = _val
        del _params['kwargs']

        _collection_formats = {}

        # process the path parameters
        _path_params = {}
        if _params['dataset_id']:
            _path_params['datasetId'] = _params['dataset_id']


        # process the query parameters
        _query_params = []
        if _params.get('var_from') is not None:  # noqa: E501
            _query_params.append((
                'from',
                _params['var_from'].value if hasattr(_params['var_from'], 'value') else _params['var_from']
            ))

        if _params.get('to') is not None:  # noqa: E501
            _query_params.append((
                'to',
                _params['to'].value if hasattr(_params['to'], 'value') else _params['to']
            ))

        if _params.get('relevant_filenames_file_name') is not None:  # noqa: E501
            _query_params.append((
                'relevantFilenamesFileName',
                _params['relevant_filenames_file_name'].value if hasattr(_params['relevant_filenames_file_name'], 'value') else _params['relevant_filenames_file_name']
            ))

        if _params.get('dnc_shards') is not None:  # noqa: E501
            _query_params.append((
                'dncShards',
                _params['dnc_shards'].value if hasattr(_params['dnc_shards'], 'value') else _params['dnc_shards']
            ))

        # process the header parameters
        _header_params = dict(_params.get('_headers', {}))
        # process the form parameters
        _form_params = []
        _files = {}
        # process the body parameter
        _body_params = None
        # set the HTTP header `Accept`
        _header_params['Accept'] = self.api_client.select_header_accept(
            ['application/json'])  # noqa: E501

        # authentication setting
        _auth_settings = ['auth0Bearer', 'ApiKeyAuth']  # noqa: E501

        _response_types_map = {
            '200': "DivideAndConquerCursorData",
            '400': "ApiErrorResponse",
            '401': "ApiErrorResponse",
            '403': "ApiErrorResponse",
            '404': "ApiErrorResponse",
        }

        return self.api_client.call_api(
            '/v1/datasets/{datasetId}/datasource/list/dnc', 'GET',
            _path_params,
            _query_params,
            _header_params,
            body=_body_params,
            post_params=_form_params,
            files=_files,
            response_types_map=_response_types_map,
            auth_settings=_auth_settings,
            async_req=_params.get('async_req'),
            _return_http_data_only=_params.get('_return_http_data_only'),  # noqa: E501
            _preload_content=_params.get('_preload_content', True),
            _request_timeout=_params.get('_request_timeout'),
            collection_formats=_collection_formats,
            _request_auth=_params.get('_request_auth'))
divide and conquer the listing of samples files into multiple cursors  # noqa: E501

        Use divide and conquer to get multiple cursors for listing the raw samples  from the datasource for a specific taskName in parallel. The cursors should be used at the endpoint getListOfRawSamplesFromDatasourceByDatasetId. There is no guarantee that the cursors returned are in order, that any cursor will return the same number of items, or that there will be more than one cursor returned.   # noqa: E501
        This method makes a synchronous HTTP request by default. To make an
        asynchronous HTTP request, please pass async_req=True

        >>> thread = api.get_divide_and_conquer_list_of_raw_samples_from_datasource_by_dataset_id_with_http_info(dataset_id, dnc_shards, var_from, to, relevant_filenames_file_name, async_req=True)
        >>> result = thread.get()

        :param dataset_id: ObjectId of the dataset (required)
        :type dataset_id: str
        :param dnc_shards: The amount of shards we should split the data into when using the divide and conquer strategy.  (required)
        :type dnc_shards: int
        :param var_from: Unix timestamp, only samples with a creation date after `from` will be returned. This parameter is ignored if `cursor` is specified. 
        :type var_from: int
        :param to: Unix timestamp, only samples with a creation date before `to` will be returned. This parameter is ignored if `cursor` is specified. 
        :type to: int
        :param relevant_filenames_file_name: The name of the file within your datasource which contains a list of relevant filenames to list. See https://docs.lightly.ai/docker/getting_started/first_steps.html#specify-relevant-files for more details  
        :type relevant_filenames_file_name: str
        :param async_req: Whether to execute the request asynchronously.
        :type async_req: bool, optional
        :param _preload_content: if False, the ApiResponse.data will
                                 be set to none and raw_data will store the 
                                 HTTP response body without reading/decoding.
                                 Default is True.
        :type _preload_content: bool, optional
        :param _return_http_data_only: response data instead of ApiResponse
                                       object with status code, headers, etc
        :type _return_http_data_only: bool, optional
        :param _request_timeout: timeout setting for this request. If one
                                 number provided, it will be total request
                                 timeout. It can also be a pair (tuple) of
                                 (connection, read) timeouts.
        :param _request_auth: set to override the auth_settings for an a single
                              request; this effectively ignores the authentication
                              in the spec for a single request.
        :type _request_auth: dict, optional
        :type _content_type: string, optional: force content-type for the request
        :return: Returns the result object.
                 If the method is called asynchronously,
                 returns the request thread.
        :rtype: tuple(DivideAndConquerCursorData, status_code(int), headers(HTTPHeaderDict))
        
lightly/openapi_generated/swagger_client/api/datasources_api.py