# pylint: disable=too-many-lines
# coding=utf-8
# --------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for license information.
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
from typing import Any, AsyncIterable, Callable, Dict, Optional, TypeVar, Union, cast
from azure.core.async_paging import AsyncItemPaged, AsyncList
from azure.core.exceptions import (
ClientAuthenticationError,
HttpResponseError,
ResourceExistsError,
ResourceNotFoundError,
ResourceNotModifiedError,
map_error,
)
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import AsyncHttpResponse
from azure.core.polling import AsyncLROPoller, AsyncNoPolling, AsyncPollingMethod
from azure.core.polling.async_base_polling import AsyncLROBasePolling
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from azure.core.tracing.decorator_async import distributed_trace_async
from azure.core.utils import case_insensitive_dict
from ... import models as _models
from ..._vendor import _convert_request
from ...operations._dataset_operations import (
build_create_or_update_dataset_request,
build_delete_dataset_request,
build_get_dataset_request,
build_get_datasets_by_workspace_request,
build_rename_dataset_request,
)
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
[docs]class DatasetOperations:
"""
.. warning::
**DO NOT** instantiate this class directly.
Instead, you should access the following operations through
:class:`~azure.synapse.artifacts.aio.ArtifactsClient`'s
:attr:`dataset` attribute.
"""
models = _models
def __init__(self, *args, **kwargs) -> None:
input_args = list(args)
self._client = input_args.pop(0) if input_args else kwargs.pop("client")
self._config = input_args.pop(0) if input_args else kwargs.pop("config")
self._serialize = input_args.pop(0) if input_args else kwargs.pop("serializer")
self._deserialize = input_args.pop(0) if input_args else kwargs.pop("deserializer")
[docs] @distributed_trace
def get_datasets_by_workspace(self, **kwargs: Any) -> AsyncIterable["_models.DatasetResource"]:
"""Lists datasets.
:keyword callable cls: A custom type or function that will be passed the direct response
:return: An iterator like instance of either DatasetResource or the result of cls(response)
:rtype:
~azure.core.async_paging.AsyncItemPaged[~azure.synapse.artifacts.models.DatasetResource]
:raises ~azure.core.exceptions.HttpResponseError:
"""
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
api_version = kwargs.pop("api_version", _params.pop("api-version", "2020-12-01")) # type: str
cls = kwargs.pop("cls", None) # type: ClsType[_models.DatasetListResponse]
error_map = {
401: ClientAuthenticationError,
404: ResourceNotFoundError,
409: ResourceExistsError,
304: ResourceNotModifiedError,
}
error_map.update(kwargs.pop("error_map", {}) or {})
def prepare_request(next_link=None):
if not next_link:
request = build_get_datasets_by_workspace_request(
api_version=api_version,
template_url=self.get_datasets_by_workspace.metadata["url"],
headers=_headers,
params=_params,
)
request = _convert_request(request)
path_format_arguments = {
"endpoint": self._serialize.url(
"self._config.endpoint", self._config.endpoint, "str", skip_quote=True
),
}
request.url = self._client.format_url(request.url, **path_format_arguments) # type: ignore
else:
request = HttpRequest("GET", next_link)
request = _convert_request(request)
path_format_arguments = {
"endpoint": self._serialize.url(
"self._config.endpoint", self._config.endpoint, "str", skip_quote=True
),
}
request.url = self._client.format_url(request.url, **path_format_arguments) # type: ignore
request.method = "GET"
return request
async def extract_data(pipeline_response):
deserialized = self._deserialize("DatasetListResponse", pipeline_response)
list_of_elem = deserialized.value
if cls:
list_of_elem = cls(list_of_elem)
return deserialized.next_link or None, AsyncList(list_of_elem)
async def get_next(next_link=None):
request = prepare_request(next_link)
pipeline_response = await self._client._pipeline.run( # type: ignore # pylint: disable=protected-access
request, stream=False, **kwargs
)
response = pipeline_response.http_response
if response.status_code not in [200]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
raise HttpResponseError(response=response)
return pipeline_response
return AsyncItemPaged(get_next, extract_data)
get_datasets_by_workspace.metadata = {"url": "/datasets"} # type: ignore
async def _create_or_update_dataset_initial(
self, dataset_name: str, properties: _models.Dataset, if_match: Optional[str] = None, **kwargs: Any
) -> Optional[_models.DatasetResource]:
error_map = {
401: ClientAuthenticationError,
404: ResourceNotFoundError,
409: ResourceExistsError,
304: ResourceNotModifiedError,
}
error_map.update(kwargs.pop("error_map", {}) or {})
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
api_version = kwargs.pop("api_version", _params.pop("api-version", "2020-12-01")) # type: str
content_type = kwargs.pop("content_type", _headers.pop("Content-Type", "application/json")) # type: str
cls = kwargs.pop("cls", None) # type: ClsType[Optional[_models.DatasetResource]]
_dataset = _models.DatasetResource(properties=properties)
_json = self._serialize.body(_dataset, "DatasetResource")
request = build_create_or_update_dataset_request(
dataset_name=dataset_name,
if_match=if_match,
api_version=api_version,
content_type=content_type,
json=_json,
template_url=self._create_or_update_dataset_initial.metadata["url"],
headers=_headers,
params=_params,
)
request = _convert_request(request)
path_format_arguments = {
"endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str", skip_quote=True),
}
request.url = self._client.format_url(request.url, **path_format_arguments) # type: ignore
pipeline_response = await self._client._pipeline.run( # type: ignore # pylint: disable=protected-access
request, stream=False, **kwargs
)
response = pipeline_response.http_response
if response.status_code not in [200, 202]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
raise HttpResponseError(response=response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize("DatasetResource", pipeline_response)
if cls:
return cls(pipeline_response, deserialized, {})
return deserialized
_create_or_update_dataset_initial.metadata = {"url": "/datasets/{datasetName}"} # type: ignore
[docs] @distributed_trace_async
async def begin_create_or_update_dataset(
self, dataset_name: str, properties: _models.Dataset, if_match: Optional[str] = None, **kwargs: Any
) -> AsyncLROPoller[_models.DatasetResource]:
"""Creates or updates a dataset.
:param dataset_name: The dataset name. Required.
:type dataset_name: str
:param properties: Dataset properties. Required.
:type properties: ~azure.synapse.artifacts.models.Dataset
:param if_match: ETag of the dataset entity. Should only be specified for update, for which it
should match existing entity or can be * for unconditional update. Default value is None.
:type if_match: str
:keyword callable cls: A custom type or function that will be passed the direct response
:keyword str continuation_token: A continuation token to restart a poller from a saved state.
:keyword polling: By default, your polling method will be AsyncLROBasePolling. Pass in False
for this operation to not poll, or pass in your own initialized polling object for a personal
polling strategy.
:paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
:keyword int polling_interval: Default waiting time between two polls for LRO operations if no
Retry-After header is present.
:return: An instance of AsyncLROPoller that returns either DatasetResource or the result of
cls(response)
:rtype: ~azure.core.polling.AsyncLROPoller[~azure.synapse.artifacts.models.DatasetResource]
:raises ~azure.core.exceptions.HttpResponseError:
"""
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
api_version = kwargs.pop("api_version", _params.pop("api-version", "2020-12-01")) # type: str
content_type = kwargs.pop("content_type", _headers.pop("Content-Type", "application/json")) # type: str
cls = kwargs.pop("cls", None) # type: ClsType[_models.DatasetResource]
polling = kwargs.pop("polling", True) # type: Union[bool, AsyncPollingMethod]
lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
cont_token = kwargs.pop("continuation_token", None) # type: Optional[str]
if cont_token is None:
raw_result = await self._create_or_update_dataset_initial( # type: ignore
dataset_name=dataset_name,
properties=properties,
if_match=if_match,
api_version=api_version,
content_type=content_type,
cls=lambda x, y, z: x,
headers=_headers,
params=_params,
**kwargs
)
kwargs.pop("error_map", None)
def get_long_running_output(pipeline_response):
deserialized = self._deserialize("DatasetResource", pipeline_response)
if cls:
return cls(pipeline_response, deserialized, {})
return deserialized
path_format_arguments = {
"endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str", skip_quote=True),
}
if polling is True:
polling_method = cast(
AsyncPollingMethod,
AsyncLROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs),
) # type: AsyncPollingMethod
elif polling is False:
polling_method = cast(AsyncPollingMethod, AsyncNoPolling())
else:
polling_method = polling
if cont_token:
return AsyncLROPoller.from_continuation_token(
polling_method=polling_method,
continuation_token=cont_token,
client=self._client,
deserialization_callback=get_long_running_output,
)
return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method)
begin_create_or_update_dataset.metadata = {"url": "/datasets/{datasetName}"} # type: ignore
[docs] @distributed_trace_async
async def get_dataset(
self, dataset_name: str, if_none_match: Optional[str] = None, **kwargs: Any
) -> Optional[_models.DatasetResource]:
"""Gets a dataset.
:param dataset_name: The dataset name. Required.
:type dataset_name: str
:param if_none_match: ETag of the dataset entity. Should only be specified for get. If the ETag
matches the existing entity tag, or if * was provided, then no content will be returned.
Default value is None.
:type if_none_match: str
:keyword callable cls: A custom type or function that will be passed the direct response
:return: DatasetResource or None or the result of cls(response)
:rtype: ~azure.synapse.artifacts.models.DatasetResource or None
:raises ~azure.core.exceptions.HttpResponseError:
"""
error_map = {
401: ClientAuthenticationError,
404: ResourceNotFoundError,
409: ResourceExistsError,
304: ResourceNotModifiedError,
}
error_map.update(kwargs.pop("error_map", {}) or {})
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
api_version = kwargs.pop("api_version", _params.pop("api-version", "2020-12-01")) # type: str
cls = kwargs.pop("cls", None) # type: ClsType[Optional[_models.DatasetResource]]
request = build_get_dataset_request(
dataset_name=dataset_name,
if_none_match=if_none_match,
api_version=api_version,
template_url=self.get_dataset.metadata["url"],
headers=_headers,
params=_params,
)
request = _convert_request(request)
path_format_arguments = {
"endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str", skip_quote=True),
}
request.url = self._client.format_url(request.url, **path_format_arguments) # type: ignore
pipeline_response = await self._client._pipeline.run( # type: ignore # pylint: disable=protected-access
request, stream=False, **kwargs
)
response = pipeline_response.http_response
if response.status_code not in [200, 304]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
raise HttpResponseError(response=response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize("DatasetResource", pipeline_response)
if cls:
return cls(pipeline_response, deserialized, {})
return deserialized
get_dataset.metadata = {"url": "/datasets/{datasetName}"} # type: ignore
async def _delete_dataset_initial( # pylint: disable=inconsistent-return-statements
self, dataset_name: str, **kwargs: Any
) -> None:
error_map = {
401: ClientAuthenticationError,
404: ResourceNotFoundError,
409: ResourceExistsError,
304: ResourceNotModifiedError,
}
error_map.update(kwargs.pop("error_map", {}) or {})
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
api_version = kwargs.pop("api_version", _params.pop("api-version", "2020-12-01")) # type: str
cls = kwargs.pop("cls", None) # type: ClsType[None]
request = build_delete_dataset_request(
dataset_name=dataset_name,
api_version=api_version,
template_url=self._delete_dataset_initial.metadata["url"],
headers=_headers,
params=_params,
)
request = _convert_request(request)
path_format_arguments = {
"endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str", skip_quote=True),
}
request.url = self._client.format_url(request.url, **path_format_arguments) # type: ignore
pipeline_response = await self._client._pipeline.run( # type: ignore # pylint: disable=protected-access
request, stream=False, **kwargs
)
response = pipeline_response.http_response
if response.status_code not in [200, 202, 204]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
raise HttpResponseError(response=response)
if cls:
return cls(pipeline_response, None, {})
_delete_dataset_initial.metadata = {"url": "/datasets/{datasetName}"} # type: ignore
[docs] @distributed_trace_async
async def begin_delete_dataset(self, dataset_name: str, **kwargs: Any) -> AsyncLROPoller[None]:
"""Deletes a dataset.
:param dataset_name: The dataset name. Required.
:type dataset_name: str
:keyword callable cls: A custom type or function that will be passed the direct response
:keyword str continuation_token: A continuation token to restart a poller from a saved state.
:keyword polling: By default, your polling method will be AsyncLROBasePolling. Pass in False
for this operation to not poll, or pass in your own initialized polling object for a personal
polling strategy.
:paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
:keyword int polling_interval: Default waiting time between two polls for LRO operations if no
Retry-After header is present.
:return: An instance of AsyncLROPoller that returns either None or the result of cls(response)
:rtype: ~azure.core.polling.AsyncLROPoller[None]
:raises ~azure.core.exceptions.HttpResponseError:
"""
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
api_version = kwargs.pop("api_version", _params.pop("api-version", "2020-12-01")) # type: str
cls = kwargs.pop("cls", None) # type: ClsType[None]
polling = kwargs.pop("polling", True) # type: Union[bool, AsyncPollingMethod]
lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
cont_token = kwargs.pop("continuation_token", None) # type: Optional[str]
if cont_token is None:
raw_result = await self._delete_dataset_initial( # type: ignore
dataset_name=dataset_name,
api_version=api_version,
cls=lambda x, y, z: x,
headers=_headers,
params=_params,
**kwargs
)
kwargs.pop("error_map", None)
def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-return-statements
if cls:
return cls(pipeline_response, None, {})
path_format_arguments = {
"endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str", skip_quote=True),
}
if polling is True:
polling_method = cast(
AsyncPollingMethod,
AsyncLROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs),
) # type: AsyncPollingMethod
elif polling is False:
polling_method = cast(AsyncPollingMethod, AsyncNoPolling())
else:
polling_method = polling
if cont_token:
return AsyncLROPoller.from_continuation_token(
polling_method=polling_method,
continuation_token=cont_token,
client=self._client,
deserialization_callback=get_long_running_output,
)
return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method)
begin_delete_dataset.metadata = {"url": "/datasets/{datasetName}"} # type: ignore
async def _rename_dataset_initial( # pylint: disable=inconsistent-return-statements
self, dataset_name: str, new_name: Optional[str] = None, **kwargs: Any
) -> None:
error_map = {
401: ClientAuthenticationError,
404: ResourceNotFoundError,
409: ResourceExistsError,
304: ResourceNotModifiedError,
}
error_map.update(kwargs.pop("error_map", {}) or {})
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
api_version = kwargs.pop("api_version", _params.pop("api-version", "2020-12-01")) # type: str
content_type = kwargs.pop("content_type", _headers.pop("Content-Type", "application/json")) # type: str
cls = kwargs.pop("cls", None) # type: ClsType[None]
_request = _models.ArtifactRenameRequest(new_name=new_name)
_json = self._serialize.body(_request, "ArtifactRenameRequest")
request = build_rename_dataset_request(
dataset_name=dataset_name,
api_version=api_version,
content_type=content_type,
json=_json,
template_url=self._rename_dataset_initial.metadata["url"],
headers=_headers,
params=_params,
)
request = _convert_request(request)
path_format_arguments = {
"endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str", skip_quote=True),
}
request.url = self._client.format_url(request.url, **path_format_arguments) # type: ignore
pipeline_response = await self._client._pipeline.run( # type: ignore # pylint: disable=protected-access
request, stream=False, **kwargs
)
response = pipeline_response.http_response
if response.status_code not in [200, 202]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
raise HttpResponseError(response=response)
if cls:
return cls(pipeline_response, None, {})
_rename_dataset_initial.metadata = {"url": "/datasets/{datasetName}/rename"} # type: ignore
[docs] @distributed_trace_async
async def begin_rename_dataset(
self, dataset_name: str, new_name: Optional[str] = None, **kwargs: Any
) -> AsyncLROPoller[None]:
"""Renames a dataset.
:param dataset_name: The dataset name. Required.
:type dataset_name: str
:param new_name: New name of the artifact. Default value is None.
:type new_name: str
:keyword callable cls: A custom type or function that will be passed the direct response
:keyword str continuation_token: A continuation token to restart a poller from a saved state.
:keyword polling: By default, your polling method will be AsyncLROBasePolling. Pass in False
for this operation to not poll, or pass in your own initialized polling object for a personal
polling strategy.
:paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
:keyword int polling_interval: Default waiting time between two polls for LRO operations if no
Retry-After header is present.
:return: An instance of AsyncLROPoller that returns either None or the result of cls(response)
:rtype: ~azure.core.polling.AsyncLROPoller[None]
:raises ~azure.core.exceptions.HttpResponseError:
"""
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
api_version = kwargs.pop("api_version", _params.pop("api-version", "2020-12-01")) # type: str
content_type = kwargs.pop("content_type", _headers.pop("Content-Type", "application/json")) # type: str
cls = kwargs.pop("cls", None) # type: ClsType[None]
polling = kwargs.pop("polling", True) # type: Union[bool, AsyncPollingMethod]
lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
cont_token = kwargs.pop("continuation_token", None) # type: Optional[str]
if cont_token is None:
raw_result = await self._rename_dataset_initial( # type: ignore
dataset_name=dataset_name,
new_name=new_name,
api_version=api_version,
content_type=content_type,
cls=lambda x, y, z: x,
headers=_headers,
params=_params,
**kwargs
)
kwargs.pop("error_map", None)
def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-return-statements
if cls:
return cls(pipeline_response, None, {})
path_format_arguments = {
"endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str", skip_quote=True),
}
if polling is True:
polling_method = cast(
AsyncPollingMethod,
AsyncLROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs),
) # type: AsyncPollingMethod
elif polling is False:
polling_method = cast(AsyncPollingMethod, AsyncNoPolling())
else:
polling_method = polling
if cont_token:
return AsyncLROPoller.from_continuation_token(
polling_method=polling_method,
continuation_token=cont_token,
client=self._client,
deserialization_callback=get_long_running_output,
)
return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method)
begin_rename_dataset.metadata = {"url": "/datasets/{datasetName}/rename"} # type: ignore