roboto.domain.datasets.operations#

Module Contents#

class roboto.domain.datasets.operations.BeginManifestTransactionRequest(/, **data)#

Bases: pydantic.BaseModel

Request payload to begin a manifest-based transaction

Parameters:: data (Any)

device_id: str | None = None#: The ID of the device which created this dataset, if applicable.

origination: str#: Additional information about what uploaded the file, e.g. roboto client v1.0.0.

resource_manifest: dict[str, int]#: Dictionary mapping destination file paths to file sizes in bytes.

class roboto.domain.datasets.operations.BeginManifestTransactionResponse(/, **data)#

Bases: pydantic.BaseModel

Response to a manifest-based transaction request

Parameters:: data (Any)

transaction_id: str#

upload_mappings: dict[str, str]#

class roboto.domain.datasets.operations.BeginSingleFileUploadRequest(/, **data)#

Bases: pydantic.BaseModel

Request payload to begin a single file upload

Parameters:: data (Any)

file_path: str = None#

file_size: int = None#

origination: str | None = None#

class roboto.domain.datasets.operations.BeginSingleFileUploadResponse(/, **data)#

Bases: pydantic.BaseModel

Response to a single file upload

Parameters:: data (Any)

upload_id: str#

upload_url: str#

class roboto.domain.datasets.operations.BeginTransactionRequest(/, **data)#

Bases: pydantic.BaseModel

Request payload for beginning a file upload transaction.

Used to initiate a transaction for uploading multiple files to a dataset. Transactions help coordinate batch uploads and provide progress tracking.

Parameters:: data (Any)

expected_resource_count: int | None = None#: Optional expected number of resources to be uploaded in this transaction.

origination: str#: Description of the upload source (e.g., ‘roboto client v1.0.0’).

class roboto.domain.datasets.operations.CreateDatasetIfNotExistsRequest(/, **data)#

Bases: pydantic.BaseModel

Request payload to create a dataset if no existing dataset matches the specified query.

Searches for existing datasets using the provided RoboQL query. If a matching dataset is found, returns that dataset. If no match is found, creates a new dataset with the specified properties and returns it.

Parameters:: data (Any)

create_request: CreateDatasetRequest#

match_roboql_query: str#

class roboto.domain.datasets.operations.CreateDatasetRequest(**data)#

Bases: pydantic.BaseModel

Request payload for creating a new dataset.

Used to specify the initial properties of a dataset during creation, including optional metadata, tags, name, and description.

description: str | None = None#: Optional human-readable description of the dataset.

device_id: str | None = None#: Optional identifier of the device that generated this data.

metadata: dict[str, Any] = None#: Key-value metadata pairs to associate with the dataset for discovery and search.

name: str | None = None#: Optional short name for the dataset (max 120 characters).

tags: list[str] = None#: List of tags for dataset discovery and organization.

class roboto.domain.datasets.operations.CreateDirectoryRequest(/, **data)#

Bases: pydantic.BaseModel

Request payload to create a directory in a dataset

Parameters:: data (Any)

create_intermediate_dirs: bool = False#: If True, creates intermediate directories in the path if they don’t exist. If False, requires all parent directories to already exist.

error_if_exists: bool = False#

name: str#

origination: str | None = None#

parent_path: str | None = None#

class roboto.domain.datasets.operations.DeleteDirectoriesRequest(/, **data)#

Bases: pydantic.BaseModel

Request payload for deleting directories within a dataset.

Used to remove entire directory structures and all contained files from a dataset. This is a bulk operation that affects multiple files.

Parameters:: data (Any)

directory_paths: list[str]#: List of directory paths to delete from the dataset.

class roboto.domain.datasets.operations.QueryDatasetFilesRequest(/, **data)#

Bases: pydantic.BaseModel

Request payload for querying files within a dataset.

Used to retrieve files from a dataset with optional pattern-based filtering and pagination support. Supports gitignore-style patterns for flexible file selection.

Parameters:: data (Any)

exclude_patterns: list[str] | None = None#: List of gitignore-style patterns for files to exclude from results.

include_patterns: list[str] | None = None#: List of gitignore-style patterns for files to include in results.

page_token: str | None = None#: Token for retrieving the next page of results in paginated queries.

class roboto.domain.datasets.operations.QueryDatasetsRequest(/, **data)#

Bases: pydantic.BaseModel

Request payload for querying datasets with filters.

Used to search for datasets based on various criteria such as metadata, tags, and other dataset properties. The filters are applied server-side to efficiently return matching datasets.

Parameters:: data (Any)

filters: dict[str, Any] = None#: Dictionary of filter criteria to apply when searching for datasets.

model_config#: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class roboto.domain.datasets.operations.RenameDirectoryRequest(/, **data)#

Bases: pydantic.BaseModel

Request payload for renaming a directory within a dataset.

Used to change the path of a directory and all its contained files within a dataset. This updates the logical organization without moving actual file content.

Parameters:: data (Any)

new_path: str#: New path for the directory.

old_path: str#: Current path of the directory to rename.

class roboto.domain.datasets.operations.ReportTransactionProgressRequest(/, **data)#

Bases: pydantic.BaseModel

Request payload for reporting file upload transaction progress.

Used to notify the platform about the completion status of individual files within a batch upload transaction. This enables progress tracking and partial completion handling for large file uploads.

Parameters:: data (Any)

manifest_items: list[str]#: List of manifest item identifiers that have completed upload.

class roboto.domain.datasets.operations.TransactionCompletionResponse(/, **data)#

Bases: pydantic.BaseModel

Response indicating the completion status of a transaction.

Provides information about whether a file upload transaction has been fully completed, including all associated file processing.

Parameters:: data (Any)

is_complete: bool#: Whether the transaction has been fully completed.

class roboto.domain.datasets.operations.UpdateDatasetRequest(/, **data)#

Bases: pydantic.BaseModel

Request payload for updating dataset properties.

Used to modify dataset metadata, description, name, and other properties. Only specified fields will be updated; others remain unchanged.

Parameters:: data (Any)

description: str | roboto.sentinels.NotSetType | None#: New description for the dataset. Set to None to clear the description.

device_id: str | roboto.sentinels.NotSetType | None#: New device ID for the dataset. Set to None to clear the device association.

metadata_changeset: roboto.updates.MetadataChangeset | roboto.sentinels.NotSetType#: Metadata changes to apply (add, update, or remove fields/tags).

model_config#: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

name: Annotated[str, pydantic.StringConstraints(max_length=120)] | roboto.sentinels.NotSetType | None#: New name for the dataset (max 120 characters). Set to None to clear the name.