Spaces#

class SpacesClient(*, sdk_config: SDKConfiguration, generated_client: ApiClient)[source]#

Bases: object

Client for managing Arize spaces.

This class is primarily intended for internal use within the SDK. Users are highly encouraged to access resource-specific functionality via arize.ArizeClient.

The spaces client is a thin wrapper around the generated REST API client, using the shared generated API client owned by arize.config.SDKConfiguration.

Parameters:

sdk_config (SDKConfiguration) – Resolved SDK configuration.
generated_client (ApiClient) – Shared generated API client instance.

list(*, organization_id: str | None = None, name: str | None = None, limit: int = 100, cursor: str | None = None) → SpacesList200Response[source]#

List spaces the user has access to.

This endpoint supports cursor-based pagination. When provided, organization_id filters results to a particular organization. name filters results to spaces whose name contains the given substring (case-insensitive).

Parameters:

organization_id (str | None) – Optional organization ID to filter results.
name (str | None) – Optional case-insensitive substring filter on space name.
limit (int) – Maximum number of spaces to return. The server may enforce an upper bound.
cursor (str | None) – Opaque pagination cursor from a previous response.

Returns:

A paginated space list response from the Arize REST API.

Raises:

ApiException – If the API request fails.

Return type:

SpacesList200Response

get(*, space: str) → Space[source]#

Get a space by ID or name.

Parameters:: space (str) – Space ID or name to retrieve.
Returns:: The space object.
Raises:: ApiException – If the API request fails (for example, space not found).
Return type:: Space

create(*, name: str, organization_id: str, description: str | None = None) → Space[source]#

Create a new space.

Space names must be unique within the target organization.

Parameters:

name (str) – Space name (must be unique within organization_id).
organization_id (str) – Organization ID to create the space in.
description (str | None) – Optional description of the space’s purpose.

Returns:

The created space object.

Raises:

ApiException – If the API request fails.

Return type:

Space

delete(*, space: str) → None[source]#

Delete a space by ID or name.

This operation is irreversible. It deletes the space and all resources that belong to it (models, monitors, dashboards, datasets, custom metrics, etc).

Parameters:: space (str) – Space ID or name to delete.
Returns:: This method returns None on success (204 No Content response).
Raises:: ApiException – If the API request fails (for example, space not found or insufficient permissions).
Return type:: None

update(*, space: str, name: str | None = None, description: str | None = None) → Space[source]#

Update a space by ID or name.

Parameters:

space (str) – Space ID or name to update.
name (str | None) – Updated name for the space.
description (str | None) – Updated description for the space.

Returns:

The updated space object.

Raises:

ValueError – If neither name nor description is provided.
ApiException – If the API request fails (for example, space not found or insufficient permissions).

Return type:

Space

add_user(*, space: str, user_id: str, role: PredefinedSpaceRole | CustomSpaceRole) → SpaceMembership[source]#

Add a user to a space (or update their role if already a member).

If the user is already a member of the space, their role is updated to the specified value (upsert). The user must already be a member of the space’s parent organization — auto-enrollment is not performed.

Role constraints

Users with an annotator account role can only be assigned the annotator predefined space role.
Users with a non-annotator account role cannot be assigned the annotator predefined space role.

Requires space admin role for predefined roles, or ROLE_BINDING_CREATE permission for custom roles.

Parameters:

space (str) – Space ID or name.
user_id (str) – Global ID of the user to add.
role (PredefinedSpaceRole | CustomSpaceRole) – Role assignment for the user. Use PredefinedSpaceRole(name="<role>") for predefined roles (admin, member, read-only, annotator), or CustomRoleAssignment(type="custom", id="<role_id>") for a custom RBAC role.

Returns:

The created or updated space membership record.

Raises:

ApiException – If the API request fails (for example, space or user not found, user not in the parent organization, role constraint violation, or insufficient permissions).

Return type:

SpaceMembership

remove_user(*, space: str, user_id: str) → None[source]#

Remove a user from a space.

Removes both the legacy space-membership row and any RBAC role bindings for the user on this space.

Requires space admin role (legacy auth) or ROLE_BINDING_DELETE permission (RBAC).

Parameters:

space (str) – Space ID or name.
user_id (str) – Global ID of the user to remove.

Returns:

This method returns None on success (204 No Content response).

Raises:

ApiException – If the API request fails (for example, space or user not found, or user is not a member of the space).

Return type:

None

Response Types#

class Space(*, id: Annotated[str, Strict(strict=True)], name: Annotated[str, Strict(strict=True)], description: Annotated[str, Strict(strict=True)], created_at: datetime)[source]#

Bases: BaseModel

A space is a container within an organization for grouping related projects, datasets, and experiments. Spaces enable team collaboration or isolated experimentation with role-based access control.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Parameters:

id (Annotated[str, Strict(strict=True)])
name (Annotated[str, Strict(strict=True)])
description (Annotated[str, Strict(strict=True)])
created_at (datetime)

id: StrictStr#

name: StrictStr#

description: StrictStr#

created_at: datetime#

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'validate_assignment': True, 'validate_by_alias': True, 'validate_by_name': True}#: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

to_str() → str[source]#

Returns the string representation of the model using alias

Return type:: str

to_json() → str[source]#

Returns the JSON representation of the model using alias

Return type:: str

classmethod from_json(json_str: str) → Self | None[source]#

Create an instance of Space from a JSON string

Parameters:: json_str (str)
Return type:: Self | None

to_dict() → Dict[str, Any][source]#

Return the dictionary representation of the model using alias.

This has the following differences from calling pydantic’s self.model_dump(by_alias=True):

None is only added to the output dict for nullable fields that were set at model initialization. Other fields with value None are ignored.

Return type:: Dict[str, Any]

classmethod from_dict(obj: Dict[str, Any] | None) → Self | None[source]#

Create an instance of Space from a dict

Parameters:: obj (Dict[str, Any] | None)
Return type:: Self | None

class SpacesList200Response(*, spaces: List[Space], pagination: PaginationMetadata)[source]#

Bases: BaseModel

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Parameters:

spaces (List[Space])
pagination (PaginationMetadata)

spaces: List[Space]#

pagination: PaginationMetadata#

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'validate_assignment': True, 'validate_by_alias': True, 'validate_by_name': True}#: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

to_str() → str[source]#

Returns the string representation of the model using alias

Return type:: str

to_json() → str[source]#

Returns the JSON representation of the model using alias

Return type:: str

classmethod from_json(json_str: str) → Self | None[source]#

Create an instance of SpacesList200Response from a JSON string

Parameters:: json_str (str)
Return type:: Self | None

to_dict() → Dict[str, Any][source]#

Return the dictionary representation of the model using alias.

This has the following differences from calling pydantic’s self.model_dump(by_alias=True):

None is only added to the output dict for nullable fields that were set at model initialization. Other fields with value None are ignored.

Return type:: Dict[str, Any]

classmethod from_dict(obj: Dict[str, Any] | None) → Self | None[source]#

Create an instance of SpacesList200Response from a dict

Parameters:: obj (Dict[str, Any] | None)
Return type:: Self | None

to_df(by_alias: bool = False, exclude_none: str | bool = True, json_normalize: bool = False, convert_dtypes: bool = True, expand_field: str = 'additional_properties', expand_prefix: str = '') → pd.DataFrame#

Convert a list of objects to a pandas.DataFrame.

Behavior:

If an item is a Pydantic v2 model, use .model_dump(by_alias=…).
If an item is a mapping (dict-like), use it as-is.
Otherwise, raise a ValueError (unsupported row type).

Parameters:

self (object) – The object instance containing the field to convert.
by_alias (bool) – Use field aliases when dumping Pydantic models.
exclude_none (str | bool) – Control None/NaN column dropping. - False: keep Nones as-is - “all”: drop columns where all values are None/NaN - “any”: drop columns where any value is None/NaN - True: alias for “all”
json_normalize (bool) – If True, flatten nested dicts via pandas.json_normalize.
convert_dtypes (bool) – If True, call DataFrame.convert_dtypes() at the end.
expand_field (str) – If set, look for this field in each row and
columns. (expand its keys into top-level)
expand_prefix (str) – If set, prefix expanded column names with this string.

Returns:

The converted DataFrame.

Return type:

pandas.DataFrame