skit_pipelines.api.models package

Submodules

skit_pipelines.api.models.auth_models module

class Token(*, access_token: str, token_type: str)

Bases: pydantic.main.BaseModel

access_token: str

token_type: str

class TokenData(*, username: Optional[str] = None)

Bases: pydantic.main.BaseModel

username: Optional[str]

class User(*, username: str)

Bases: pydantic.main.BaseModel

username: str

class UserInDB(*, username: str, hashed_password: str)

Bases: skit_pipelines.api.models.auth_models.User

hashed_password: str

skit_pipelines.api.models.custom_models module

class ParseRunResponse(namespace: str, run: kfp_server_api.models.api_run_detail.ApiRunDetail)

Bases: object

Run Response parser

parse_response() → None

set_error_logs(uris)

set_state(current_status) → bool

artifact_node_to_uri(node: Dict[str, Any], store='s3') → Iterable[str]

filter_artifact_nodes(nodes: Dict[str, Any], **filter_map) → List[Dict[str, Any]]

get_kf_object_uri(obj: Dict[str, Any], store='s3') → str

skit_pipelines.api.models.errors module

kfp_api_error(reason: str, status=503) → kfp_server_api.exceptions.ApiException

skit_pipelines.api.models.requests module

class BaseRequestSchema

Bases: pydantic.main.BaseModel

classmethod transform_none(value)

class StorageOptions(*, type: str = 's3', bucket: str = 'vernacular-ml')

Bases: skit_pipelines.api.models.requests.BaseRequestSchema

bucket: str

type: str

generate_schema(pipeline_name, pipeline_fn)

get_all_pipelines_fn()

get_normalized_pipelines_fn_map()

set_nodegroup_for_pipelines(pipeline_fn)

skit_pipelines.api.models.responses module

class StatusResponseModel(*, message: str, run_id: str, run_url: str, error_logs: str = '', uris: Optional[List[str]] = None, webhook: bool = False)

Bases: pydantic.main.BaseModel

error_logs: str

message: str

run_id: str

run_url: str

uris: Optional[List[str]]

webhook: bool

customResponse(message: Dict[Any, Any], status_code: int = 200, status: str = 'ok') → starlette.responses.JSONResponse

statusWiseResponse(run_response: skit_pipelines.api.models.custom_models.ParseRunResponse, webhook=False)

successfulCreationResponse(run_id: str, name: str, namespace: str)

Module contents