# -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
# --------------------------------------------------------------------------
from typing import TYPE_CHECKING
from azure.core import MatchConditions
from azure.core.credentials import AzureKeyCredential
from azure.core.tracing.decorator import distributed_trace
from ._generated import SearchClient as _SearchServiceClient
from .models import SearchIndexerSkillset
from ._utils import (
get_access_conditions,
normalize_endpoint,
)
from .models import (
EntityRecognitionSkillVersion,
SearchIndexerDataSourceConnection,
SentimentSkillVersion
)
from .._api_versions import DEFAULT_VERSION
from .._headers_mixin import HeadersMixin
from .._utils import get_authentication_policy
from .._version import SDK_MONIKER
if TYPE_CHECKING:
# pylint:disable=unused-import,ungrouped-imports
from ._generated.models import SearchIndexer, SearchIndexerStatus, DocumentKeysOrIds
from typing import Any, Optional, Sequence, Union
from azure.core.credentials import TokenCredential
[docs]class SearchIndexerClient(HeadersMixin): # pylint: disable=R0904
"""A client to interact with Azure search service Indexers.
:param endpoint: The URL endpoint of an Azure search service
:type endpoint: str
:param credential: A credential to authorize search client requests
:type credential: ~azure.core.credentials.AzureKeyCredential or ~azure.core.credentials.TokenCredential
:keyword str api_version: The Search API version to use for requests.
:keyword str audience: sets the Audience to use for authentication with Azure Active Directory (AAD). The
audience is not considered when using a shared key. If audience is not provided, the public cloud audience
will be assumed.
"""
_ODATA_ACCEPT = "application/json;odata.metadata=minimal" # type: str
def __init__(self, endpoint, credential, **kwargs):
# type: (str, Union[AzureKeyCredential, TokenCredential], **Any) -> None
self._api_version = kwargs.pop("api_version", DEFAULT_VERSION)
self._endpoint = normalize_endpoint(endpoint) # type: str
self._credential = credential
audience = kwargs.pop("audience", None)
if isinstance(credential, AzureKeyCredential):
self._aad = False
self._client = _SearchServiceClient(
endpoint=endpoint,
sdk_moniker=SDK_MONIKER,
api_version=self._api_version,
**kwargs
) # type: _SearchServiceClient
else:
self._aad = True
authentication_policy = get_authentication_policy(credential, audience=audience)
self._client = _SearchServiceClient(
endpoint=endpoint,
authentication_policy=authentication_policy,
sdk_moniker=SDK_MONIKER,
api_version=self._api_version,
**kwargs
) # type: _SearchServiceClient
def __enter__(self):
# type: () -> SearchIndexerClient
self._client.__enter__() # pylint:disable=no-member
return self
def __exit__(self, *args):
# type: (*Any) -> None
return self._client.__exit__(*args) # pylint:disable=no-member
[docs] def close(self):
# type: () -> None
"""Close the :class:`~azure.search.documents.indexes.SearchIndexerClient` session."""
return self._client.close()
[docs] @distributed_trace
def create_indexer(self, indexer, **kwargs):
# type: (SearchIndexer, **Any) -> SearchIndexer
"""Creates a new SearchIndexer.
:param indexer: The definition of the indexer to create.
:type indexer: ~azure.search.documents.indexes.models.SearchIndexer
:return: The created SearchIndexer
:rtype: ~azure.search.documents.indexes.models.SearchIndexer
.. admonition:: Example:
.. literalinclude:: ../samples/sample_indexer_operations.py
:start-after: [START create_indexer]
:end-before: [END create_indexer]
:language: python
:dedent: 4
:caption: Create a SearchIndexer
"""
kwargs["headers"] = self._merge_client_headers(kwargs.get("headers"))
result = self._client.indexers.create(indexer, **kwargs)
return result
[docs] @distributed_trace
def create_or_update_indexer(self, indexer, **kwargs):
# type: (SearchIndexer, **Any) -> SearchIndexer
"""Creates a new indexer or updates a indexer if it already exists.
:param indexer: The definition of the indexer to create or update.
:type indexer: ~azure.search.documents.indexes.models.SearchIndexer
:keyword skip_indexer_reset_requirement_for_cache: Ignores cache reset requirements.
:paramtype skip_indexer_reset_requirement_for_cache: bool
:keyword disable_cache_reprocessing_change_detection: Disables cache reprocessing change
detection.
:paramtype disable_cache_reprocessing_change_detection: bool
:return: The created SearchIndexer
:rtype: ~azure.search.documents.indexes.models.SearchIndexer
"""
kwargs["headers"] = self._merge_client_headers(kwargs.get("headers"))
error_map, access_condition = get_access_conditions(
indexer, kwargs.pop("match_condition", MatchConditions.Unconditionally)
)
kwargs.update(access_condition)
name = indexer.name
result = self._client.indexers.create_or_update(
indexer_name=name, indexer=indexer, error_map=error_map, **kwargs
)
return result
[docs] @distributed_trace
def get_indexer(self, name, **kwargs):
# type: (str, **Any) -> SearchIndexer
"""Retrieves a indexer definition.
:param name: The name of the indexer to retrieve.
:type name: str
:return: The SearchIndexer that is fetched.
:rtype: ~azure.search.documents.indexes.models.SearchIndexer
.. admonition:: Example:
.. literalinclude:: ../samples/sample_indexer_operations.py
:start-after: [START get_indexer]
:end-before: [END get_indexer]
:language: python
:dedent: 4
:caption: Retrieve a SearchIndexer
"""
kwargs["headers"] = self._merge_client_headers(kwargs.get("headers"))
result = self._client.indexers.get(name, **kwargs)
return result
[docs] @distributed_trace
def get_indexers(self, **kwargs):
# type: (**Any) -> Sequence[SearchIndexer]
"""Lists all indexers available for a search service.
:keyword select: Selects which top-level properties of the skillsets to retrieve. Specified as a
list of JSON property names, or '*' for all properties. The default is all
properties.
:paramtype select: list[str]
:return: List of all the SearchIndexers.
:rtype: `list[~azure.search.documents.indexes.models.SearchIndexer]`
.. admonition:: Example:
.. literalinclude:: ../samples/sample_indexer_operations.py
:start-after: [START list_indexer]
:end-before: [END list_indexer]
:language: python
:dedent: 4
:caption: List all the SearchIndexers
"""
kwargs["headers"] = self._merge_client_headers(kwargs.get("headers"))
if kwargs.get('select', None):
kwargs['select'] = ','.join(kwargs['select'])
result = self._client.indexers.list(**kwargs)
return result.indexers
[docs] @distributed_trace
def get_indexer_names(self, **kwargs):
# type: (**Any) -> Sequence[str]
"""Lists all indexer names available for a search service.
:return: List of all the SearchIndexers.
:rtype: `list[str]`
.. admonition:: Example:
.. literalinclude:: ../samples/sample_indexer_operations.py
:start-after: [START list_indexer]
:end-before: [END list_indexer]
:language: python
:dedent: 4
:caption: List all the SearchIndexers
"""
kwargs["headers"] = self._merge_client_headers(kwargs.get("headers"))
result = self._client.indexers.list(**kwargs)
return [x.name for x in result.indexers]
[docs] @distributed_trace
def delete_indexer(self, indexer, **kwargs):
# type: (Union[str, SearchIndexer], **Any) -> None
"""Deletes an indexer. To use access conditions, the SearchIndexer model
must be provided instead of the name. It is enough to provide
the name of the indexer to delete unconditionally.
:param indexer: The indexer to delete.
:type indexer: str or ~azure.search.documents.indexes.models.SearchIndexer
:keyword match_condition: The match condition to use upon the etag
:paramtype match_condition: ~azure.core.MatchConditions
:return: None
:rtype: None
.. admonition:: Example:
.. literalinclude:: ../samples/sample_indexer_operations.py
:start-after: [START delete_indexer]
:end-before: [END delete_indexer]
:language: python
:dedent: 4
:caption: Delete a SearchIndexer
"""
kwargs["headers"] = self._merge_client_headers(kwargs.get("headers"))
error_map, access_condition = get_access_conditions(
indexer, kwargs.pop("match_condition", MatchConditions.Unconditionally)
)
kwargs.update(access_condition)
try:
name = indexer.name
except AttributeError:
name = indexer
self._client.indexers.delete(name, error_map=error_map, **kwargs)
[docs] @distributed_trace
def run_indexer(self, name, **kwargs):
# type: (str, **Any) -> None
"""Run an indexer.
:param name: The name of the indexer to run.
:type name: str
:return: None
:rtype: None
.. admonition:: Example:
.. literalinclude:: ../samples/sample_indexer_operations.py
:start-after: [START run_indexer]
:end-before: [END run_indexer]
:language: python
:dedent: 4
:caption: Run a SearchIndexer
"""
kwargs["headers"] = self._merge_client_headers(kwargs.get("headers"))
self._client.indexers.run(name, **kwargs)
[docs] @distributed_trace
def reset_indexer(self, name, **kwargs):
# type: (str, **Any) -> None
"""Resets the change tracking state associated with an indexer.
:param name: The name of the indexer to reset.
:type name: str
:return: None
:rtype: None
.. admonition:: Example:
.. literalinclude:: ../samples/sample_indexer_operations.py
:start-after: [START reset_indexer]
:end-before: [END reset_indexer]
:language: python
:dedent: 4
:caption: Reset a SearchIndexer's change tracking state
"""
kwargs["headers"] = self._merge_client_headers(kwargs.get("headers"))
self._client.indexers.reset(name, **kwargs)
[docs] @distributed_trace
def reset_documents(self, indexer, keys_or_ids, **kwargs):
# type: (Union[str, SearchIndexer], DocumentKeysOrIds, **Any) -> None
"""Resets specific documents in the datasource to be selectively re-ingested by the indexer.
:param indexer: The indexer to reset documents for.
:type indexer: str or ~azure.search.documents.indexes.models.SearchIndexer
:param keys_or_ids:
:type keys_or_ids: ~azure.search.documents.indexes.models.DocumentKeysOrIds
:return: None, or the result of cls(response)
:keyword overwrite: If false, keys or ids will be appended to existing ones. If true, only the
keys or ids in this payload will be queued to be re-ingested. The default is false.
:paramtype overwrite: bool
:rtype: None
:raises: ~azure.core.exceptions.HttpResponseError
"""
kwargs["headers"] = self._merge_client_headers(kwargs.get("headers"))
kwargs["keys_or_ids"] = keys_or_ids
try:
name = indexer.name
except AttributeError:
name = indexer
return self._client.indexers.reset_docs(name, **kwargs)
[docs] @distributed_trace
def get_indexer_status(self, name, **kwargs):
# type: (str, **Any) -> SearchIndexerStatus
"""Get the status of the indexer.
:param name: The name of the indexer to fetch the status.
:type name: str
:return: SearchIndexerStatus
:rtype: ~azure.search.documents.indexes.models.SearchIndexerStatus
.. admonition:: Example:
.. literalinclude:: ../samples/sample_indexer_operations.py
:start-after: [START get_indexer_status]
:end-before: [END get_indexer_status]
:language: python
:dedent: 4
:caption: Get a SearchIndexer's status
"""
kwargs["headers"] = self._merge_client_headers(kwargs.get("headers"))
return self._client.indexers.get_status(name, **kwargs)
[docs] @distributed_trace
def create_data_source_connection(self, data_source_connection, **kwargs):
# type: (SearchIndexerDataSourceConnection, **Any) -> SearchIndexerDataSourceConnection
"""Creates a new data source connection.
:param data_source_connection: The definition of the data source connection to create.
:type data_source_connection: ~azure.search.documents.indexes.models.SearchIndexerDataSourceConnection
:return: The created SearchIndexerDataSourceConnection
:rtype: ~azure.search.documents.indexes.models.SearchIndexerDataSourceConnection
.. admonition:: Example:
.. literalinclude:: ../samples/sample_data_source_operations.py
:start-after: [START create_data_source_connection]
:end-before: [END create_data_source_connection]
:language: python
:dedent: 4
:caption: Create a Data Source
"""
kwargs["headers"] = self._merge_client_headers(kwargs.get("headers"))
# pylint:disable=protected-access
packed_data_source = data_source_connection._to_generated()
result = self._client.data_sources.create(packed_data_source, **kwargs)
return SearchIndexerDataSourceConnection._from_generated(result)
[docs] @distributed_trace
def create_or_update_data_source_connection(self, data_source_connection, **kwargs):
# type: (SearchIndexerDataSourceConnection, **Any) -> SearchIndexerDataSourceConnection
"""Creates a new data source connection or updates a data source connection if it already exists.
:param data_source_connection: The definition of the data source connection to create or update.
:type data_source_connection: ~azure.search.documents.indexes.models.SearchIndexerDataSourceConnection
:keyword match_condition: The match condition to use upon the etag
:paramtype match_condition: ~azure.core.MatchConditions
:keyword skip_indexer_reset_requirement_for_cache: Ignores cache reset requirements.
:paramtype skip_indexer_reset_requirement_for_cache: bool
:return: The created SearchIndexerDataSourceConnection
:rtype: ~azure.search.documents.indexes.models.SearchIndexerDataSourceConnection
"""
kwargs["headers"] = self._merge_client_headers(kwargs.get("headers"))
error_map, access_condition = get_access_conditions(
data_source_connection,
kwargs.pop("match_condition", MatchConditions.Unconditionally),
)
kwargs.update(access_condition)
name = data_source_connection.name
packed_data_source = (
data_source_connection._to_generated() # pylint:disable=protected-access
)
result = self._client.data_sources.create_or_update(
data_source_name=name,
data_source=packed_data_source,
error_map=error_map,
**kwargs
)
# pylint:disable=protected-access
return SearchIndexerDataSourceConnection._from_generated(result)
[docs] @distributed_trace
def get_data_source_connection(self, name, **kwargs):
# type: (str, **Any) -> SearchIndexerDataSourceConnection
"""Retrieves a data source connection definition.
:param name: The name of the data source connection to retrieve.
:type name: str
:return: The SearchIndexerDataSourceConnection that is fetched.
:rtype: ~azure.search.documents.indexes.models.SearchIndexerDataSourceConnection
.. admonition:: Example:
.. literalinclude:: ../samples/sample_data_source_operations.py
:start-after: [START get_data_source_connection]
:end-before: [END get_data_source_connection]
:language: python
:dedent: 4
:caption: Retrieve a SearchIndexerDataSourceConnection
"""
kwargs["headers"] = self._merge_client_headers(kwargs.get("headers"))
result = self._client.data_sources.get(name, **kwargs)
return SearchIndexerDataSourceConnection._from_generated( # pylint:disable=protected-access
result
)
[docs] @distributed_trace
def get_data_source_connections(self, **kwargs):
# type: (**Any) -> Sequence[SearchIndexerDataSourceConnection]
"""Lists all data source connections available for a search service.
:keyword select: Selects which top-level properties of the skillsets to retrieve. Specified as a
list of JSON property names, or '*' for all properties. The default is all
properties.
:paramtype select: list[str]
:return: List of all the data source connections.
:rtype: `list[~azure.search.documents.indexes.models.SearchIndexerDataSourceConnection]`
.. admonition:: Example:
.. literalinclude:: ../samples/sample_data_source_operations.py
:start-after: [START list_data_source_connection]
:end-before: [END list_data_source_connection]
:language: python
:dedent: 4
:caption: List all the SearchIndexerDataSourceConnections
"""
kwargs["headers"] = self._merge_client_headers(kwargs.get("headers"))
if kwargs.get('select', None):
kwargs['select'] = ','.join(kwargs['select'])
result = self._client.data_sources.list(**kwargs)
# pylint:disable=protected-access
return [
SearchIndexerDataSourceConnection._from_generated(x)
for x in result.data_sources
]
[docs] @distributed_trace
def get_data_source_connection_names(self, **kwargs):
# type: (**Any) -> Sequence[str]
"""Lists all data source connection names available for a search service.
:return: List of all the data source connection names.
:rtype: `list[str]`
"""
kwargs["headers"] = self._merge_client_headers(kwargs.get("headers"))
result = self._client.data_sources.list(**kwargs)
return [x.name for x in result.data_sources]
[docs] @distributed_trace
def delete_data_source_connection(self, data_source_connection, **kwargs):
# type: (Union[str, SearchIndexerDataSourceConnection], **Any) -> None
"""Deletes a data source connection. To use access conditions, the SearchIndexerDataSourceConnection
model must be provided instead of the name. It is enough to provide the name of the data source connection
to delete unconditionally
:param data_source_connection: The data source connection to delete.
:type data_source_connection: str or ~azure.search.documents.indexes.models.SearchIndexerDataSourceConnection
:keyword match_condition: The match condition to use upon the etag
:paramtype match_condition: ~azure.core.MatchConditions
:return: None
:rtype: None
.. admonition:: Example:
.. literalinclude:: ../samples/sample_data_source_operations.py
:start-after: [START delete_data_source_connection]
:end-before: [END delete_data_source_connection]
:language: python
:dedent: 4
:caption: Delete a SearchIndexerDataSourceConnection
"""
kwargs["headers"] = self._merge_client_headers(kwargs.get("headers"))
error_map, access_condition = get_access_conditions(
data_source_connection,
kwargs.pop("match_condition", MatchConditions.Unconditionally),
)
kwargs.update(access_condition)
try:
name = data_source_connection.name
except AttributeError:
name = data_source_connection
self._client.data_sources.delete(
data_source_name=name, error_map=error_map, **kwargs
)
[docs] @distributed_trace
def get_skillsets(self, **kwargs):
# type: (**Any) -> List[SearchIndexerSkillset]
"""List the SearchIndexerSkillsets in an Azure Search service.
:keyword select: Selects which top-level properties of the skillsets to retrieve. Specified as a
list of JSON property names, or '*' for all properties. The default is all
properties.
:paramtype select: list[str]
:return: List of SearchIndexerSkillsets
:rtype: list[~azure.search.documents.indexes.models.SearchIndexerSkillset]
:raises: ~azure.core.exceptions.HttpResponseError
.. admonition:: Example:
.. literalinclude:: ../samples/sample_skillset_operations.py
:start-after: [START get_skillsets]
:end-before: [END get_skillsets]
:language: python
:dedent: 4
:caption: List SearchIndexerSkillsets
"""
kwargs["headers"] = self._merge_client_headers(kwargs.get("headers"))
if kwargs.get('select', None):
kwargs['select'] = ','.join(kwargs['select'])
result = self._client.skillsets.list(**kwargs)
return [SearchIndexerSkillset._from_generated(skillset) for skillset in result.skillsets] # pylint:disable=protected-access
[docs] @distributed_trace
def get_skillset_names(self, **kwargs):
# type: (**Any) -> List[str]
"""List the SearchIndexerSkillset names in an Azure Search service.
:return: List of SearchIndexerSkillset names
:rtype: list[str]
:raises: ~azure.core.exceptions.HttpResponseError
"""
kwargs["headers"] = self._merge_client_headers(kwargs.get("headers"))
result = self._client.skillsets.list(**kwargs)
return [x.name for x in result.skillsets]
[docs] @distributed_trace
def get_skillset(self, name, **kwargs):
# type: (str, **Any) -> SearchIndexerSkillset
"""Retrieve a named SearchIndexerSkillset in an Azure Search service
:param name: The name of the SearchIndexerSkillset to get
:type name: str
:return: The retrieved SearchIndexerSkillset
:rtype: ~azure.search.documents.indexes.models.SearchIndexerSkillset
:raises: :class:`~azure.core.exceptions.ResourceNotFoundError`
.. admonition:: Example:
.. literalinclude:: ../samples/sample_skillset_operations.py
:start-after: [START get_skillset]
:end-before: [END get_skillset]
:language: python
:dedent: 4
:caption: Get a SearchIndexerSkillset
"""
kwargs["headers"] = self._merge_client_headers(kwargs.get("headers"))
result = self._client.skillsets.get(name, **kwargs)
return SearchIndexerSkillset._from_generated(result) # pylint:disable=protected-access
[docs] @distributed_trace
def delete_skillset(self, skillset, **kwargs):
# type: (Union[str, SearchIndexerSkillset], **Any) -> None
"""Delete a named SearchIndexerSkillset in an Azure Search service. To use access conditions,
the SearchIndexerSkillset model must be provided instead of the name. It is enough to provide
the name of the skillset to delete unconditionally
:param skillset: The SearchIndexerSkillset to delete
:type skillset: str or ~azure.search.documents.indexes.models.SearchIndexerSkillset
:keyword match_condition: The match condition to use upon the etag
:paramtype match_condition: ~azure.core.MatchConditions
.. admonition:: Example:
.. literalinclude:: ../samples/sample_skillset_operations.py
:start-after: [START delete_skillset]
:end-before: [END delete_skillset]
:language: python
:dedent: 4
:caption: Delete a SearchIndexerSkillset
"""
kwargs["headers"] = self._merge_client_headers(kwargs.get("headers"))
error_map, access_condition = get_access_conditions(
skillset, kwargs.pop("match_condition", MatchConditions.Unconditionally)
)
kwargs.update(access_condition)
try:
name = skillset.name
except AttributeError:
name = skillset
self._client.skillsets.delete(name, error_map=error_map, **kwargs)
[docs] @distributed_trace
def create_skillset(self, skillset, **kwargs):
# type: (SearchIndexerSkillset, **Any) -> SearchIndexerSkillset
"""Create a new SearchIndexerSkillset in an Azure Search service
:param skillset: The SearchIndexerSkillset object to create
:type skillset: ~azure.search.documents.indexes.models.SearchIndexerSkillset
:return: The created SearchIndexerSkillset
:rtype: ~azure.search.documents.indexes.models.SearchIndexerSkillset
.. admonition:: Example:
.. literalinclude:: ../samples/sample_skillset_operations.py
:start-after: [START create_skillset]
:end-before: [END create_skillset]
:language: python
:dedent: 4
:caption: Create a SearchIndexerSkillset
"""
kwargs["headers"] = self._merge_client_headers(kwargs.get("headers"))
_validate_skillset(skillset)
skillset = skillset._to_generated() if hasattr(skillset, '_to_generated') else skillset # pylint:disable=protected-access
result = self._client.skillsets.create(skillset, **kwargs)
return SearchIndexerSkillset._from_generated(result) # pylint:disable=protected-access
[docs] @distributed_trace
def create_or_update_skillset(self, skillset, **kwargs):
# type: (SearchIndexerSkillset, **Any) -> SearchIndexerSkillset
"""Create a new SearchIndexerSkillset in an Azure Search service, or update an
existing one.
:param skillset: The SearchIndexerSkillset object to create or update
:type skillset: ~azure.search.documents.indexes.models.SearchIndexerSkillset
:keyword match_condition: The match condition to use upon the etag
:paramtype match_condition: ~azure.core.MatchConditions
:keyword skip_indexer_reset_requirement_for_cache: Ignores cache reset requirements.
:paramtype skip_indexer_reset_requirement_for_cache: bool
:keyword disable_cache_reprocessing_change_detection: Disables cache reprocessing change
detection.
:paramtype disable_cache_reprocessing_change_detection: bool
:return: The created or updated SearchIndexerSkillset
:rtype: ~azure.search.documents.indexes.models.SearchIndexerSkillset
"""
kwargs["headers"] = self._merge_client_headers(kwargs.get("headers"))
error_map, access_condition = get_access_conditions(
skillset, kwargs.pop("match_condition", MatchConditions.Unconditionally)
)
kwargs.update(access_condition)
_validate_skillset(skillset)
skillset = skillset._to_generated() if hasattr(skillset, '_to_generated') else skillset # pylint:disable=protected-access
result = self._client.skillsets.create_or_update(
skillset_name=skillset.name,
skillset=skillset,
error_map=error_map,
**kwargs
)
return SearchIndexerSkillset._from_generated(result) # pylint:disable=protected-access
[docs] @distributed_trace
def reset_skills(self, skillset, skill_names, **kwargs):
# type: (Union[str, SearchIndexerSkillset], List[str], **Any) -> None
"""Reset an existing skillset in a search service.
:param skillset: The SearchIndexerSkillset to reset
:type skillset: str or ~azure.search.documents.indexes.models.SearchIndexerSkillset
:param skill_names: the names of skills to be reset.
:type skill_names: list[str]
:return: None, or the result of cls(response)
:rtype: None
:raises: ~azure.core.exceptions.HttpResponseError
"""
kwargs["headers"] = self._merge_client_headers(kwargs.get("headers"))
try:
name = skillset.name
except AttributeError:
name = skillset
return self._client.skillsets.reset_skills(name, skill_names, **kwargs)
def _validate_skillset(skillset):
"""Validates any multi-version skills in the skillset to verify that unsupported
parameters are not supplied by the user.
"""
skills = getattr(skillset, 'skills', None)
if not skills:
return
error_strings = []
for skill in skills:
try:
skill_version = skill.get('skill_version')
except AttributeError:
skill_version = getattr(skill, 'skill_version', None)
if not skill_version:
continue
if skill_version == SentimentSkillVersion.V1:
unsupported = ['model_version', 'include_opinion_mining']
elif skill_version == SentimentSkillVersion.V3:
unsupported = []
elif skill_version == EntityRecognitionSkillVersion.V1:
unsupported = ['model_version']
elif skill_version == EntityRecognitionSkillVersion.V3:
unsupported = ['include_typeless_entities']
errors = []
for item in unsupported:
try:
if skill.get(item, None):
errors.append(item)
except AttributeError:
if skill.__dict__.get(item, None):
errors.append(item)
if errors:
error_strings.append("Unsupported parameters for skill version {}: {}".format(
skill_version, ", ".join(errors))
)
if error_strings:
raise ValueError("\n".join(error_strings))