import json
import logging
from mlflow.protos.databricks_pb2 import (
ABORTED,
ALREADY_EXISTS,
BAD_REQUEST,
CANCELLED,
CUSTOMER_UNAUTHORIZED,
DATA_LOSS,
DEADLINE_EXCEEDED,
ENDPOINT_NOT_FOUND,
INTERNAL_ERROR,
INVALID_PARAMETER_VALUE,
INVALID_STATE,
NOT_FOUND,
NOT_IMPLEMENTED,
PERMISSION_DENIED,
REQUEST_LIMIT_EXCEEDED,
RESOURCE_ALREADY_EXISTS,
RESOURCE_CONFLICT,
RESOURCE_DOES_NOT_EXIST,
RESOURCE_EXHAUSTED,
TEMPORARILY_UNAVAILABLE,
UNAUTHENTICATED,
ErrorCode,
)
ERROR_CODE_TO_HTTP_STATUS = {
ErrorCode.Name(INTERNAL_ERROR): 500,
ErrorCode.Name(INVALID_STATE): 500,
ErrorCode.Name(DATA_LOSS): 500,
ErrorCode.Name(NOT_IMPLEMENTED): 501,
ErrorCode.Name(TEMPORARILY_UNAVAILABLE): 503,
ErrorCode.Name(DEADLINE_EXCEEDED): 504,
ErrorCode.Name(REQUEST_LIMIT_EXCEEDED): 429,
ErrorCode.Name(CANCELLED): 499,
ErrorCode.Name(RESOURCE_EXHAUSTED): 429,
ErrorCode.Name(ABORTED): 409,
ErrorCode.Name(RESOURCE_CONFLICT): 409,
ErrorCode.Name(ALREADY_EXISTS): 409,
ErrorCode.Name(NOT_FOUND): 404,
ErrorCode.Name(ENDPOINT_NOT_FOUND): 404,
ErrorCode.Name(RESOURCE_DOES_NOT_EXIST): 404,
ErrorCode.Name(PERMISSION_DENIED): 403,
ErrorCode.Name(CUSTOMER_UNAUTHORIZED): 401,
ErrorCode.Name(UNAUTHENTICATED): 401,
ErrorCode.Name(BAD_REQUEST): 400,
ErrorCode.Name(RESOURCE_ALREADY_EXISTS): 400,
ErrorCode.Name(INVALID_PARAMETER_VALUE): 400,
}
HTTP_STATUS_TO_ERROR_CODE = {v: k for k, v in ERROR_CODE_TO_HTTP_STATUS.items()}
HTTP_STATUS_TO_ERROR_CODE[400] = ErrorCode.Name(BAD_REQUEST)
HTTP_STATUS_TO_ERROR_CODE[404] = ErrorCode.Name(ENDPOINT_NOT_FOUND)
HTTP_STATUS_TO_ERROR_CODE[500] = ErrorCode.Name(INTERNAL_ERROR)
_logger = logging.getLogger(__name__)
[docs]def get_error_code(http_status):
return ErrorCode.Value(
HTTP_STATUS_TO_ERROR_CODE.get(http_status, ErrorCode.Name(INTERNAL_ERROR))
)
[docs]class MlflowException(Exception):
"""
Generic exception thrown to surface failure information about external-facing operations.
The error message associated with this exception may be exposed to clients in HTTP responses
for debugging purposes. If the error text is sensitive, raise a generic `Exception` object
instead.
"""
def __init__(self, message, error_code=INTERNAL_ERROR, **kwargs):
"""
Args:
message: The message or exception describing the error that occurred. This will be
included in the exception's serialized JSON representation.
error_code: An appropriate error code for the error that occurred; it will be
included in the exception's serialized JSON representation. This should
be one of the codes listed in the `mlflow.protos.databricks_pb2` proto.
kwargs: Additional key-value pairs to include in the serialized JSON representation
of the MlflowException.
"""
try:
self.error_code = ErrorCode.Name(error_code)
except (ValueError, TypeError):
self.error_code = ErrorCode.Name(INTERNAL_ERROR)
message = str(message)
self.message = message
self.json_kwargs = kwargs
super().__init__(message)
[docs] def serialize_as_json(self):
exception_dict = {"error_code": self.error_code, "message": self.message}
exception_dict.update(self.json_kwargs)
return json.dumps(exception_dict)
[docs] def get_http_status_code(self):
return ERROR_CODE_TO_HTTP_STATUS.get(self.error_code, 500)
[docs] @classmethod
def invalid_parameter_value(cls, message, **kwargs):
"""Constructs an `MlflowException` object with the `INVALID_PARAMETER_VALUE` error code.
Args:
message: The message describing the error that occurred. This will be included in the
exception's serialized JSON representation.
kwargs: Additional key-value pairs to include in the serialized JSON representation
of the MlflowException.
"""
return cls(message, error_code=INVALID_PARAMETER_VALUE, **kwargs)
[docs]class RestException(MlflowException):
"""Exception thrown on non 200-level responses from the REST API"""
def __init__(self, json):
self.json = json
error_code = json.get("error_code", ErrorCode.Name(INTERNAL_ERROR))
message = "{}: {}".format(
error_code,
json["message"] if "message" in json else "Response: " + str(json),
)
try:
super().__init__(message, error_code=ErrorCode.Value(error_code))
except ValueError:
try:
# The `error_code` can be an http error code, in which case we convert it to the
# corresponding `ErrorCode`.
error_code = HTTP_STATUS_TO_ERROR_CODE[int(error_code)]
super().__init__(message, error_code=ErrorCode.Value(error_code))
except ValueError or KeyError:
_logger.warning(
f"Received error code not recognized by MLflow: {error_code}, this may "
"indicate your request encountered an error before reaching MLflow server, "
"e.g., within a proxy server or authentication / authorization service."
)
super().__init__(message)
def __reduce__(self):
"""
Overriding `__reduce__` to make `RestException` instance pickle-able.
"""
return RestException, (self.json,)
[docs]class ExecutionException(MlflowException):
"""Exception thrown when executing a project fails"""
pass
[docs]class MissingConfigException(MlflowException):
"""Exception thrown when expected configuration file/directory not found"""
pass
[docs]class InvalidUrlException(MlflowException):
"""Exception thrown when a http request fails to send due to an invalid URL"""
pass
class _UnsupportedMultipartUploadException(MlflowException):
"""Exception thrown when multipart upload is unsupported by an artifact repository"""
MESSAGE = "Multipart upload is not supported for the current artifact repository"
def __init__(self):
super().__init__(self.MESSAGE, error_code=NOT_IMPLEMENTED)