code refactoring 4

sdk/search/azure-search-documents/CHANGELOG.md

@@ -1,6 +1,6 @@
 # Release History
 
-## 1.0.0b4 (Unreleased)
+## 1.0.0b4 (2020-06-09)
 
 **Breaking Changes**
 
@@ -24,7 +24,9 @@
   PathHierarchyTokenizerV2 -> PathHierarchyTokenizer
 - Renamed DataSource methods to DataSourceConnection    #11693
 - Autocomplete & suggest methods now takes arguments search_text & suggester_name rather than query objects   #11747
-- Create_or_updates methods does not support partial updates
+- Create_or_updates methods does not support partial updates    #11800
+- Renamed AnalyzeRequest to AnalyzeTextOptions  #11800
+- Renamed Batch methods #11800
 
 
 ## 1.0.0b3 (2020-05-04)

sdk/search/azure-search-documents/README.md

@@ -40,10 +40,11 @@ The above creates a resource with the "Standard" pricing tier. See [choosing a p
 In order to interact with the Cognitive Search service you'll need to create an instance of the Search Client class.
 To make this possible you will need an [api-key of the Cognitive Search service](https://docs.microsoft.com/en-us/azure/search/search-security-api-keys).
 
-The SDK provides two clients.
+The SDK provides three clients.
 
 1. SearchClient for all document operations.
-2. SearchServiceClient for all CRUD operations on service resources.
+2. SearchIndexClient for all CRUD operations on index resources.
+3. SearchIndexerClient for all CRUD operations on indexer resources.
 
 #### Create a SearchClient
 
@@ -64,18 +65,33 @@ client = SearchClient(endpoint="<service endpoint>",
                       credential=credential)
 ```
 
-#### Create a SearchServiceClient
+#### Create a SearchIndexClient
 
 Once you have the values of the Cognitive Search Service [service endpoint](https://docs.microsoft.com/en-us/azure/search/search-create-service-portal#get-a-key-and-url-endpoint)
 and [api key](https://docs.microsoft.com/en-us/azure/search/search-security-api-keys) you can create the Search Service client:
 
 ```python
 from azure.core.credentials import AzureKeyCredential
-from azure.search.documents import SearchServiceClient
+from azure.search.documents.indexes import SearchIndexClient
 
 credential = AzureKeyCredential("<api key>")
 
-client = SearchServiceClient(endpoint="<service endpoint>"
+client = SearchIndexClient(endpoint="<service endpoint>"
+                             credential=credential)
+```
+
+#### Create a SearchIndexerClient
+
+Once you have the values of the Cognitive Search Service [service endpoint](https://docs.microsoft.com/en-us/azure/search/search-create-service-portal#get-a-key-and-url-endpoint)
+and [api key](https://docs.microsoft.com/en-us/azure/search/search-security-api-keys) you can create the Search Service client:
+
+```python
+from azure.core.credentials import AzureKeyCredential
+from azure.search.documents.indexes import SearchIndexerClient
+
+credential = AzureKeyCredential("<api key>")
+
+client = SearchIndexerClient(endpoint="<service endpoint>"
                              credential=credential)
 ```
 
@@ -100,7 +116,7 @@ source to extract and load data into an index.
 There are several types of operations that can be executed against the service:
 
 - **Index management operations** Create, delete, update, or configure a search index. ([API Reference](https://azuresdkdocs.blob.core.windows.net/$web/python/azure-search-documents/latest/azure.search.documents.html#azure.search.documents.SearchIndexesClient), [Service Docs](https://docs.microsoft.com/en-us/rest/api/searchservice/index-operations))
--   **Document operations** Add, update, or delete documents in the index, query the index, or look up specific documents by ID. ([API Reference](https://azuresdkdocs.blob.core.windows.net/$web/python/azure-search-documents/latest/azure.search.documents.html#azure.search.documents.SearchClient), [Service Docs](https://docs.microsoft.com/en-us/rest/api/searchservice/document-operations))
+- **Document operations** Add, update, or delete documents in the index, query the index, or look up specific documents by ID. ([API Reference](https://azuresdkdocs.blob.core.windows.net/$web/python/azure-search-documents/latest/azure.search.documents.html#azure.search.documents.SearchClient), [Service Docs](https://docs.microsoft.com/en-us/rest/api/searchservice/document-operations))
 - **Datasource operations** Create, delete, update, or configure data sources for Search Indexers ([API Reference](https://azuresdkdocs.blob.core.windows.net/$web/python/azure-search-documents/latest/azure.search.documents.html#azure.search.documents.SearchDataSourcesClient), [Service Docs](https://docs.microsoft.com/en-us/rest/api/searchservice/indexer-operations))
 - **Indexer operations** Automate aspects of an indexing operation by configuring a data source and an indexer that you can schedule or run on demand. This feature is supported for a limited number of data source types. ([API Reference](https://azuresdkdocs.blob.core.windows.net/$web/python/azure-search-documents/latest/azure.search.documents.html#azure.search.documents.SearchIndexersClient), [Service Docs](https://docs.microsoft.com/en-us/rest/api/searchservice/indexer-operations))
 - **Skillset operations** Part of a cognitive search workload, a skillset defines a series of a series of enrichment processing steps. A skillset is consumed by an indexer. ([API Reference](https://azuresdkdocs.blob.core.windows.net/$web/python/azure-search-documents/latest/azure.search.documents.html#azure.search.documents.SearchSkillsetsClient), [Service Docs](https://docs.microsoft.com/en-us/rest/api/searchservice/skillset-operations))
@@ -154,12 +170,10 @@ Get search suggestions for related terms, e.g. find search suggestions for
 the term "coffee":
 ```python
 from azure.core.credentials import AzureKeyCredential
-from azure.search.documents import SearchClient, SuggestQuery
+from azure.search.documents import SearchClient
 client = SearchClient("<service endpoint>", "<index_name>", AzureKeyCredential("<api key>"))
 
-query = SuggestQuery(search_text="coffee", suggester_name="sg")
-
-results = client.suggest(query=query)
+results = client.suggest(search_text="coffee", suggester_name="sg")
 
 print("Search suggestions for 'coffee'")
 for result in results:
@@ -172,25 +186,22 @@ for result in results:
 
 ```python
 from azure.core.credentials import AzureKeyCredential
-from azure.search.documents import SearchServiceClient, CorsOptions, Index, ScoringProfile
-client = SearchServiceClient("<service endpoint>", AzureKeyCredential("<api key>")).get_indexes_client()
+from azure.search.documents.indexes import SearchIndexClient, CorsOptions, SearchIndex, ScoringProfile
+client = SearchIndexClient("<service endpoint>", AzureKeyCredential("<api key>"))
 name = "hotels"
 fields = [
-    {
-        "name": "hotelId",
-        "type": "Edm.String",
-        "key": True,
-        "searchable": False
-    },
-    {
-        "name": "baseRate",
-        "type": "Edm.Double"
-    }
-]
+        SimpleField(name="hotelId", type=SearchFieldDataType.String, key=True),
+        SimpleField(name="baseRate", type=SearchFieldDataType.Double),
+        SearchableField(name="description", type=SearchFieldDataType.String),
+        ComplexField(name="address", fields=[
+            SimpleField(name="streetAddress", type=SearchFieldDataType.String),
+            SimpleField(name="city", type=SearchFieldDataType.String),
+        ])
+    ]
 cors_options = CorsOptions(allowed_origins=["*"], max_age_in_seconds=60)
 scoring_profiles = []
 
-index = Index(
+index = SearchIndex(
     name=name,
     fields=fields,
     scoring_profiles=scoring_profiles,

sdk/search/azure-search-documents/azure/search/documents/_internal/_index_documents_batch.py

@@ -36,7 +36,7 @@ def __repr__(self):
         # type: () -> str
         return "<IndexDocumentsBatch [{} actions]>".format(len(self.actions))[:1024]
 
-    def add_upload_documents(self, *documents):
+    def add_upload_actions(self, *documents):
         # type (Union[List[dict], List[List[dict]]]) -> None
         """Add documents to upload to the Azure search index.
 
@@ -50,7 +50,7 @@ def add_upload_documents(self, *documents):
         """
         self._extend_batch(flatten_args(documents), "upload")
 
-    def add_delete_documents(self, *documents):
+    def add_delete_actions(self, *documents):
         # type (Union[List[dict], List[List[dict]]]) -> None
         """Add documents to delete to the Azure search index.
 
@@ -69,7 +69,7 @@ def add_delete_documents(self, *documents):
         """
         self._extend_batch(flatten_args(documents), "delete")
 
-    def add_merge_documents(self, *documents):
+    def add_merge_actions(self, *documents):
         # type (Union[List[dict], List[List[dict]]]) -> None
         """Add documents to merge in to existing documets in the Azure search
         index.
@@ -85,7 +85,7 @@ def add_merge_documents(self, *documents):
         """
         self._extend_batch(flatten_args(documents), "merge")
 
-    def add_merge_or_upload_documents(self, *documents):
+    def add_merge_or_upload_actions(self, *documents):
         # type (Union[List[dict], List[List[dict]]]) -> None
         """Add documents to merge in to existing documets in the Azure search
         index, or upload if they do not yet exist.

sdk/search/azure-search-documents/azure/search/documents/_internal/_search_client.py

@@ -132,12 +132,12 @@ def get_document(self, key, selected_fields=None, **kwargs):
         return cast(dict, result)
 
     @distributed_trace
-    def search(self, query, **kwargs):
-        # type: (Union[str, SearchQuery], **Any) -> SearchItemPaged[dict]
+    def search(self, search_text, **kwargs):
+        # type: (str, **Any) -> SearchItemPaged[dict]
         """Search the Azure search index for documents.
 
-        :param query: An query for searching the index
-        :type documents: str or SearchQuery
+        :param str search_text: A full-text search query expression; Use "*" or omit this parameter to
+        match all documents.
         :rtype:  SearchItemPaged[dict]
 
         .. admonition:: Example:
@@ -167,14 +167,41 @@ def search(self, query, **kwargs):
                 :dedent: 4
                 :caption: Get search result facets.
         """
-        if isinstance(query, six.string_types):
-            query = SearchQuery(search_text=query)
-        elif not isinstance(query, SearchQuery):
-            raise TypeError(
-                "Expected a string or SearchQuery for 'query', but got {}".format(
-                    repr(query)
-                )
-            )
+        include_total_result_count = kwargs.pop("include_total_result_count", None)
+        facets = kwargs.pop("facets", None)
+        filter_arg = kwargs.pop("filter", None)
+        highlight_fields = kwargs.pop("highlight_fields", None)
+        highlight_post_tag = kwargs.pop("highlight_post_tag", None)
+        highlight_pre_tag = kwargs.pop("highlight_pre_tag", None)
+        minimum_coverage = kwargs.pop("minimum_coverage", None)
+        order_by = kwargs.pop("order_by", None)
+        query_type = kwargs.pop("query_type", None)
+        scoring_parameters = kwargs.pop("scoring_parameters", None)
+        scoring_profile = kwargs.pop("scoring_profile", None)
+        search_fields = kwargs.pop("search_fields", None)
+        search_mode = kwargs.pop("search_mode", None)
+        select = kwargs.pop("select", None)
+        skip = kwargs.pop("skip", None)
+        top = kwargs.pop("top", None)
+        query = SearchQuery(
+            search_text=search_text,
+            include_total_result_count=include_total_result_count,
+            facets=facets,
+            filter=filter_arg,
+            highlight_fields=highlight_fields,
+            highlight_post_tag=highlight_post_tag,
+            highlight_pre_tag=highlight_pre_tag,
+            minimum_coverage=minimum_coverage,
+            order_by=order_by,
+            query_type=query_type,
+            scoring_parameters=scoring_parameters,
+            scoring_profile=scoring_profile,
+            search_fields=search_fields,
+            search_mode=search_mode,
+            select=select,
+            skip=skip,
+            top=top
+        )
 
         kwargs["headers"] = self._merge_client_headers(kwargs.get("headers"))
         return SearchItemPaged(
@@ -201,7 +228,28 @@ def suggest(self, search_text, suggester_name, **kwargs):
                 :dedent: 4
                 :caption: Get search suggestions.
         """
-        query = SuggestQuery(search_text=search_text, suggester_name=suggester_name, **kwargs)
+        filter_arg = kwargs.pop("filter", None)
+        use_fuzzy_matching = kwargs.pop("use_fuzzy_matching", None)
+        highlight_post_tag = kwargs.pop("highlight_post_tag", None)
+        highlight_pre_tag = kwargs.pop("highlight_pre_tag", None)
+        minimum_coverage = kwargs.pop("minimum_coverage", None)
+        order_by = kwargs.pop("order_by", None)
+        search_fields = kwargs.pop("search_fields", None)
+        select = kwargs.pop("select", None)
+        top = kwargs.pop("top", None)
+        query = SuggestQuery(
+            search_text=search_text,
+            suggester_name=suggester_name,
+            filter=filter_arg,
+            use_fuzzy_matching=use_fuzzy_matching,
+            highlight_post_tag=highlight_post_tag,
+            highlight_pre_tag=highlight_pre_tag,
+            minimum_coverage=minimum_coverage,
+            order_by=order_by,
+            search_fields=search_fields,
+            select=select,
+            top=top
+        )
 
         kwargs["headers"] = self._merge_client_headers(kwargs.get("headers"))
         response = self._client.documents.suggest_post(
@@ -229,7 +277,26 @@ def autocomplete(self, search_text, suggester_name, **kwargs):
                 :dedent: 4
                 :caption: Get a auto-completions.
         """
-        query = AutocompleteQuery(search_text=search_text, suggester_name=suggester_name, **kwargs)
+        autocomplete_mode = kwargs.pop("autocomplete_mode", None)
+        filter_arg = kwargs.pop("filter", None)
+        use_fuzzy_matching = kwargs.pop("use_fuzzy_matching", None)
+        highlight_post_tag = kwargs.pop("highlight_post_tag", None)
+        highlight_pre_tag = kwargs.pop("highlight_pre_tag", None)
+        minimum_coverage = kwargs.pop("minimum_coverage", None)
+        search_fields = kwargs.pop("search_fields", None)
+        top = kwargs.pop("top", None)
+        query = AutocompleteQuery(
+            search_text=search_text,
+            suggester_name=suggester_name,
+            autocomplete_mode=autocomplete_mode,
+            filter=filter_arg,
+            use_fuzzy_matching=use_fuzzy_matching,
+            highlight_post_tag=highlight_post_tag,
+            highlight_pre_tag=highlight_pre_tag,
+            minimum_coverage=minimum_coverage,
+            search_fields=search_fields,
+            top=top
+        )
 
         kwargs["headers"] = self._merge_client_headers(kwargs.get("headers"))
         response = self._client.documents.autocomplete_post(
@@ -260,7 +327,7 @@ def upload_documents(self, documents, **kwargs):
                 :caption: Upload new documents to an index
         """
         batch = IndexDocumentsBatch()
-        batch.add_upload_documents(documents)
+        batch.add_upload_actions(documents)
 
         kwargs["headers"] = self._merge_client_headers(kwargs.get("headers"))
         results = self.index_documents(batch, **kwargs)
@@ -293,7 +360,7 @@ def delete_documents(self, documents, **kwargs):
                 :caption: Delete existing documents to an index
         """
         batch = IndexDocumentsBatch()
-        batch.add_delete_documents(documents)
+        batch.add_delete_actions(documents)
 
         kwargs["headers"] = self._merge_client_headers(kwargs.get("headers"))
         results = self.index_documents(batch, **kwargs)
@@ -322,7 +389,7 @@ def merge_documents(self, documents, **kwargs):
                 :caption: Merge fields into existing documents to an index
         """
         batch = IndexDocumentsBatch()
-        batch.add_merge_documents(documents)
+        batch.add_merge_actions(documents)
 
         kwargs["headers"] = self._merge_client_headers(kwargs.get("headers"))
         results = self.index_documents(batch, **kwargs)
@@ -342,7 +409,7 @@ def merge_or_upload_documents(self, documents, **kwargs):
         :rtype:  List[IndexingResult]
         """
         batch = IndexDocumentsBatch()
-        batch.add_merge_or_upload_documents(documents)
+        batch.add_merge_or_upload_actions(documents)
 
         kwargs["headers"] = self._merge_client_headers(kwargs.get("headers"))
         results = self.index_documents(batch, **kwargs)