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)

origination: str#

resource_manifest: dict[str, int]#

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

!!! abstract “Usage Documentation”: [Models](../concepts/models.md)

A base class for creating Pydantic models.

Parameters:: data (Any)

__class_vars__#: The names of the class variables defined on the model.

__private_attributes__#: Metadata about the private attributes of the model.

__signature__#: The synthesized __init__ [Signature][inspect.Signature] of the model.

__pydantic_complete__#: Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__#: The core schema of the model.

__pydantic_custom_init__#: Whether the model has a custom __init__ function.

__pydantic_decorators__#: Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_generic_metadata__#: Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

__pydantic_parent_namespace__#: Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__#: The name of the post-init method for the model, if defined.

__pydantic_root_model__#: Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__#: The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__#: The pydantic-core SchemaValidator used to validate instances of the model.

__pydantic_fields__#: A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects.

__pydantic_computed_fields__#: A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_extra__#: A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to ‘allow’.

__pydantic_fields_set__#: The names of fields explicitly set during instantiation.

__pydantic_private__#: Values of private attributes set on the model instance.

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.

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. Supports conditional updates based on current field values to prevent conflicting concurrent modifications.

Parameters:: data (Any)

conditions: list[roboto.updates.UpdateCondition] | None = None#: Optional list of conditions that must be met for the update to proceed.

description: str | None = None#: New description for the dataset.

metadata_changeset: roboto.updates.MetadataChangeset | None = None#: Metadata changes to apply (add, update, or remove fields/tags).

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