SearchClient Class

Reference

A client to interact with an existing Azure search index.

Inheritance: azure.search.documents._headers_mixin.HeadersMixin

SearchClient

Constructor

SearchClient(endpoint: str, index_name: str, credential: AzureKeyCredential | TokenCredential, **kwargs: Any)

Parameters

Name	Description
endpoint Required	str The URL endpoint of an Azure search service
index_name Required	str The name of the index to connect to
credential Required	AzureKeyCredential or TokenCredential A credential to authorize search client requests

Keyword-Only Parameters

Name	Description
api_version	str The Search API version to use for requests.
audience	str 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.

Examples

Creating the SearchClient with an API key.


   from azure.core.credentials import AzureKeyCredential
   from azure.search.documents import SearchClient

   service_endpoint = os.environ["AZURE_SEARCH_SERVICE_ENDPOINT"]
   index_name = os.environ["AZURE_SEARCH_INDEX_NAME"]
   key = os.environ["AZURE_SEARCH_API_KEY"]

   search_client = SearchClient(service_endpoint, index_name, AzureKeyCredential(key))

Methods

autocomplete	Get search auto-completion results from the Azure search index.
close	Close the session. :return: None :rtype: None
delete_documents	Delete documents from the Azure search index Delete removes the specified document from the index. Any field you specify in a delete operation, other than the key field, will be ignored. If you want to remove an individual field from a document, use merge_documents instead and set the field explicitly to None. Delete operations are idempotent. That is, even if a document key does not exist in the index, attempting a delete operation with that key will result in a 200 status code.
get_document	Retrieve a document from the Azure search index by its key.
get_document_count	Return the number of documents in the Azure search index.
index_documents	Specify a document operations to perform as a batch. :raises ~azure.search.documents.RequestEntityTooLargeError
merge_documents	Merge documents in to existing documents in the Azure search index. Merge updates an existing document with the specified fields. If the document doesn't exist, the merge will fail. Any field you specify in a merge will replace the existing field in the document. This also applies to collections of primitive and complex types.
merge_or_upload_documents	Merge documents in to existing documents in the Azure search index, or upload them if they do not yet exist. This action behaves like merge_documents if a document with the given key already exists in the index. If the document does not exist, it behaves like upload_documents with a new document.
search	Search the Azure search index for documents.
send_request	Runs a network request using the client's existing pipeline.
suggest	Get search suggestion results from the Azure search index.
upload_documents	Upload documents to the Azure search index. An upload action is similar to an "upsert" where the document will be inserted if it is new and updated/replaced if it exists. All fields are replaced in the update case.

autocomplete

Get search auto-completion results from the Azure search index.

autocomplete(search_text: str, suggester_name: str, *, mode: str | AutocompleteMode | None = None, filter: str | None = None, use_fuzzy_matching: bool | None = None, highlight_post_tag: str | None = None, highlight_pre_tag: str | None = None, minimum_coverage: float | None = None, search_fields: List[str] | None = None, top: int | None = None, **kwargs) -> List[Dict]

Parameters

Name	Description
search_text Required	str The search text on which to base autocomplete results.
suggester_name Required	str The name of the suggester as specified in the suggesters collection that's part of the index definition.

Keyword-Only Parameters

Name	Description
mode	str or AutocompleteMode Specifies the mode for Autocomplete. The default is 'oneTerm'. Use 'twoTerms' to get shingles and 'oneTermWithContext' to use the current context while producing auto-completed terms. Possible values include: 'oneTerm', 'twoTerms', 'oneTermWithContext'.
filter	str An OData expression that filters the documents used to produce completed terms for the Autocomplete result.
use_fuzzy_matching	bool A value indicating whether to use fuzzy matching for the autocomplete query. Default is false. When set to true, the query will find terms even if there's a substituted or missing character in the search text. While this provides a better experience in some scenarios, it comes at a performance cost as fuzzy autocomplete queries are slower and consume more resources.
highlight_post_tag	str A string tag that is appended to hit highlights. Must be set with highlightPreTag. If omitted, hit highlighting is disabled.
highlight_pre_tag	str A string tag that is prepended to hit highlights. Must be set with highlightPostTag. If omitted, hit highlighting is disabled.
minimum_coverage	float A number between 0 and 100 indicating the percentage of the index that must be covered by an autocomplete query in order for the query to be reported as a success. This parameter can be useful for ensuring search availability even for services with only one replica. The default is 80.
search_fields	list[str] The list of field names to consider when querying for auto-completed terms. Target fields must be included in the specified suggester.
top	int The number of auto-completed terms to retrieve. This must be a value between 1 and 100. The default is 5.

Returns

Type	Description
list[dict]	List of auto-completion results.

Examples

Get a auto-completions.


   from azure.core.credentials import AzureKeyCredential
   from azure.search.documents import SearchClient

   search_client = SearchClient(service_endpoint, index_name, AzureKeyCredential(key))

   results = search_client.autocomplete(search_text="bo", suggester_name="sg")

   print("Autocomplete suggestions for 'bo'")
   for result in results:
       print("    Completion: {}".format(result["text"]))

close

Close the session. :return: None :rtype: None

close() -> None

Keyword-Only Parameters

Name	Description
mode	str or AutocompleteMode Specifies the mode for Autocomplete. The default is 'oneTerm'. Use 'twoTerms' to get shingles and 'oneTermWithContext' to use the current context while producing auto-completed terms. Possible values include: 'oneTerm', 'twoTerms', 'oneTermWithContext'.
filter	str An OData expression that filters the documents used to produce completed terms for the Autocomplete result.
use_fuzzy_matching	bool A value indicating whether to use fuzzy matching for the autocomplete query. Default is false. When set to true, the query will find terms even if there's a substituted or missing character in the search text. While this provides a better experience in some scenarios, it comes at a performance cost as fuzzy autocomplete queries are slower and consume more resources.
highlight_post_tag	str A string tag that is appended to hit highlights. Must be set with highlightPreTag. If omitted, hit highlighting is disabled.
highlight_pre_tag	str A string tag that is prepended to hit highlights. Must be set with highlightPostTag. If omitted, hit highlighting is disabled.
minimum_coverage	float A number between 0 and 100 indicating the percentage of the index that must be covered by an autocomplete query in order for the query to be reported as a success. This parameter can be useful for ensuring search availability even for services with only one replica. The default is 80.
search_fields	list[str] The list of field names to consider when querying for auto-completed terms. Target fields must be included in the specified suggester.
top	int The number of auto-completed terms to retrieve. This must be a value between 1 and 100. The default is 5.

delete_documents

Delete documents from the Azure search index

Delete removes the specified document from the index. Any field you specify in a delete operation, other than the key field, will be ignored. If you want to remove an individual field from a document, use merge_documents instead and set the field explicitly to None.

Delete operations are idempotent. That is, even if a document key does not exist in the index, attempting a delete operation with that key will result in a 200 status code.

delete_documents(documents: List[Dict], **kwargs: Any) -> List[IndexingResult]

Parameters

Name	Description
documents Required	list[dict] A list of documents to delete.

Keyword-Only Parameters

Name	Description
mode	str or AutocompleteMode Specifies the mode for Autocomplete. The default is 'oneTerm'. Use 'twoTerms' to get shingles and 'oneTermWithContext' to use the current context while producing auto-completed terms. Possible values include: 'oneTerm', 'twoTerms', 'oneTermWithContext'.
filter	str An OData expression that filters the documents used to produce completed terms for the Autocomplete result.
use_fuzzy_matching	bool A value indicating whether to use fuzzy matching for the autocomplete query. Default is false. When set to true, the query will find terms even if there's a substituted or missing character in the search text. While this provides a better experience in some scenarios, it comes at a performance cost as fuzzy autocomplete queries are slower and consume more resources.
highlight_post_tag	str A string tag that is appended to hit highlights. Must be set with highlightPreTag. If omitted, hit highlighting is disabled.
highlight_pre_tag	str A string tag that is prepended to hit highlights. Must be set with highlightPostTag. If omitted, hit highlighting is disabled.
minimum_coverage	float A number between 0 and 100 indicating the percentage of the index that must be covered by an autocomplete query in order for the query to be reported as a success. This parameter can be useful for ensuring search availability even for services with only one replica. The default is 80.
search_fields	list[str] The list of field names to consider when querying for auto-completed terms. Target fields must be included in the specified suggester.
top	int The number of auto-completed terms to retrieve. This must be a value between 1 and 100. The default is 5.

Returns

Type	Description
list[IndexingResult]	List of IndexingResult

Examples

Delete existing documents to an index


   result = search_client.delete_documents(documents=[{"hotelId": "1000"}])

   print("Delete new document succeeded: {}".format(result[0].succeeded))

get_document

Retrieve a document from the Azure search index by its key.

get_document(key: str, selected_fields: List[str] | None = None, **kwargs: Any) -> Dict

Parameters

Name	Description
key Required	str The primary key value for the document to retrieve
selected_fields Required	list[str] an allow-list of fields to include in the results

Keyword-Only Parameters

Name	Description
mode	str or AutocompleteMode Specifies the mode for Autocomplete. The default is 'oneTerm'. Use 'twoTerms' to get shingles and 'oneTermWithContext' to use the current context while producing auto-completed terms. Possible values include: 'oneTerm', 'twoTerms', 'oneTermWithContext'.
filter	str An OData expression that filters the documents used to produce completed terms for the Autocomplete result.
use_fuzzy_matching	bool A value indicating whether to use fuzzy matching for the autocomplete query. Default is false. When set to true, the query will find terms even if there's a substituted or missing character in the search text. While this provides a better experience in some scenarios, it comes at a performance cost as fuzzy autocomplete queries are slower and consume more resources.
highlight_post_tag	str A string tag that is appended to hit highlights. Must be set with highlightPreTag. If omitted, hit highlighting is disabled.
highlight_pre_tag	str A string tag that is prepended to hit highlights. Must be set with highlightPostTag. If omitted, hit highlighting is disabled.
minimum_coverage	float A number between 0 and 100 indicating the percentage of the index that must be covered by an autocomplete query in order for the query to be reported as a success. This parameter can be useful for ensuring search availability even for services with only one replica. The default is 80.
search_fields	list[str] The list of field names to consider when querying for auto-completed terms. Target fields must be included in the specified suggester.
top	int The number of auto-completed terms to retrieve. This must be a value between 1 and 100. The default is 5.

Returns

Type	Description
dict	The document as stored in the Azure search index

Examples

Get a specific document from the search index.


   from azure.core.credentials import AzureKeyCredential
   from azure.search.documents import SearchClient

   search_client = SearchClient(service_endpoint, index_name, AzureKeyCredential(key))

   result = search_client.get_document(key="23")

   print("Details for hotel '23' are:")
   print("        Name: {}".format(result["hotelName"]))
   print("      Rating: {}".format(result["rating"]))
   print("    Category: {}".format(result["category"]))

get_document_count

Return the number of documents in the Azure search index.

get_document_count(**kwargs: Any) -> int

Keyword-Only Parameters

Name	Description
mode	str or AutocompleteMode Specifies the mode for Autocomplete. The default is 'oneTerm'. Use 'twoTerms' to get shingles and 'oneTermWithContext' to use the current context while producing auto-completed terms. Possible values include: 'oneTerm', 'twoTerms', 'oneTermWithContext'.
filter	str An OData expression that filters the documents used to produce completed terms for the Autocomplete result.
use_fuzzy_matching	bool A value indicating whether to use fuzzy matching for the autocomplete query. Default is false. When set to true, the query will find terms even if there's a substituted or missing character in the search text. While this provides a better experience in some scenarios, it comes at a performance cost as fuzzy autocomplete queries are slower and consume more resources.
highlight_post_tag	str A string tag that is appended to hit highlights. Must be set with highlightPreTag. If omitted, hit highlighting is disabled.
highlight_pre_tag	str A string tag that is prepended to hit highlights. Must be set with highlightPostTag. If omitted, hit highlighting is disabled.
minimum_coverage	float A number between 0 and 100 indicating the percentage of the index that must be covered by an autocomplete query in order for the query to be reported as a success. This parameter can be useful for ensuring search availability even for services with only one replica. The default is 80.
search_fields	list[str] The list of field names to consider when querying for auto-completed terms. Target fields must be included in the specified suggester.
top	int The number of auto-completed terms to retrieve. This must be a value between 1 and 100. The default is 5.

Returns

Type	Description
int	The count of documents in the index

index_documents

Specify a document operations to perform as a batch.

:raises ~azure.search.documents.RequestEntityTooLargeError

index_documents(batch: IndexDocumentsBatch, **kwargs: Any) -> List[IndexingResult]

Parameters

Name	Description
batch Required	IndexDocumentsBatch A batch of document operations to perform.

Keyword-Only Parameters

Name	Description
mode	str or AutocompleteMode Specifies the mode for Autocomplete. The default is 'oneTerm'. Use 'twoTerms' to get shingles and 'oneTermWithContext' to use the current context while producing auto-completed terms. Possible values include: 'oneTerm', 'twoTerms', 'oneTermWithContext'.
filter	str An OData expression that filters the documents used to produce completed terms for the Autocomplete result.
use_fuzzy_matching	bool A value indicating whether to use fuzzy matching for the autocomplete query. Default is false. When set to true, the query will find terms even if there's a substituted or missing character in the search text. While this provides a better experience in some scenarios, it comes at a performance cost as fuzzy autocomplete queries are slower and consume more resources.
highlight_post_tag	str A string tag that is appended to hit highlights. Must be set with highlightPreTag. If omitted, hit highlighting is disabled.
highlight_pre_tag	str A string tag that is prepended to hit highlights. Must be set with highlightPostTag. If omitted, hit highlighting is disabled.
minimum_coverage	float A number between 0 and 100 indicating the percentage of the index that must be covered by an autocomplete query in order for the query to be reported as a success. This parameter can be useful for ensuring search availability even for services with only one replica. The default is 80.
search_fields	list[str] The list of field names to consider when querying for auto-completed terms. Target fields must be included in the specified suggester.
top	int The number of auto-completed terms to retrieve. This must be a value between 1 and 100. The default is 5.

Returns

Type	Description
list[IndexingResult]	List of IndexingResult

merge_documents

Merge documents in to existing documents in the Azure search index.

Merge updates an existing document with the specified fields. If the document doesn't exist, the merge will fail. Any field you specify in a merge will replace the existing field in the document. This also applies to collections of primitive and complex types.

merge_documents(documents: List[Dict], **kwargs: Any) -> List[IndexingResult]

Parameters

Name	Description
documents Required	list[dict] A list of documents to merge.

Keyword-Only Parameters

Name	Description
mode	str or AutocompleteMode Specifies the mode for Autocomplete. The default is 'oneTerm'. Use 'twoTerms' to get shingles and 'oneTermWithContext' to use the current context while producing auto-completed terms. Possible values include: 'oneTerm', 'twoTerms', 'oneTermWithContext'.
filter	str An OData expression that filters the documents used to produce completed terms for the Autocomplete result.
use_fuzzy_matching	bool A value indicating whether to use fuzzy matching for the autocomplete query. Default is false. When set to true, the query will find terms even if there's a substituted or missing character in the search text. While this provides a better experience in some scenarios, it comes at a performance cost as fuzzy autocomplete queries are slower and consume more resources.
highlight_post_tag	str A string tag that is appended to hit highlights. Must be set with highlightPreTag. If omitted, hit highlighting is disabled.
highlight_pre_tag	str A string tag that is prepended to hit highlights. Must be set with highlightPostTag. If omitted, hit highlighting is disabled.
minimum_coverage	float A number between 0 and 100 indicating the percentage of the index that must be covered by an autocomplete query in order for the query to be reported as a success. This parameter can be useful for ensuring search availability even for services with only one replica. The default is 80.
search_fields	list[str] The list of field names to consider when querying for auto-completed terms. Target fields must be included in the specified suggester.
top	int The number of auto-completed terms to retrieve. This must be a value between 1 and 100. The default is 5.

Returns

Type	Description
list[IndexingResult]	List of IndexingResult

Examples

Merge fields into existing documents to an index


   result = search_client.merge_documents(documents=[{"hotelId": "1000", "rating": 4.5}])

   print("Merge into new document succeeded: {}".format(result[0].succeeded))

merge_or_upload_documents

Merge documents in to existing documents in the Azure search index, or upload them if they do not yet exist.

This action behaves like merge_documents if a document with the given key already exists in the index. If the document does not exist, it behaves like upload_documents with a new document.

merge_or_upload_documents(documents: List[Dict], **kwargs: Any) -> List[IndexingResult]

Parameters

Name	Description
documents Required	list[dict] A list of documents to merge or upload.

Keyword-Only Parameters

Name	Description
mode	str or AutocompleteMode Specifies the mode for Autocomplete. The default is 'oneTerm'. Use 'twoTerms' to get shingles and 'oneTermWithContext' to use the current context while producing auto-completed terms. Possible values include: 'oneTerm', 'twoTerms', 'oneTermWithContext'.
filter	str An OData expression that filters the documents used to produce completed terms for the Autocomplete result.
use_fuzzy_matching	bool A value indicating whether to use fuzzy matching for the autocomplete query. Default is false. When set to true, the query will find terms even if there's a substituted or missing character in the search text. While this provides a better experience in some scenarios, it comes at a performance cost as fuzzy autocomplete queries are slower and consume more resources.
highlight_post_tag	str A string tag that is appended to hit highlights. Must be set with highlightPreTag. If omitted, hit highlighting is disabled.
highlight_pre_tag	str A string tag that is prepended to hit highlights. Must be set with highlightPostTag. If omitted, hit highlighting is disabled.
minimum_coverage	float A number between 0 and 100 indicating the percentage of the index that must be covered by an autocomplete query in order for the query to be reported as a success. This parameter can be useful for ensuring search availability even for services with only one replica. The default is 80.
search_fields	list[str] The list of field names to consider when querying for auto-completed terms. Target fields must be included in the specified suggester.
top	int The number of auto-completed terms to retrieve. This must be a value between 1 and 100. The default is 5.

Returns

Type	Description
list[IndexingResult]	List of IndexingResult

search

Search the Azure search index for documents.

search(search_text: str | None = None, *, include_total_count: bool | None = None, facets: List[str] | None = None, filter: str | None = None, highlight_fields: str | None = None, highlight_post_tag: str | None = None, highlight_pre_tag: str | None = None, minimum_coverage: float | None = None, order_by: List[str] | None = None, query_type: str | QueryType | None = None, scoring_parameters: List[str] | None = None, scoring_profile: str | None = None, semantic_query: str | None = None, search_fields: List[str] | None = None, search_mode: str | SearchMode | None = None, query_answer: str | QueryAnswerType | None = None, query_answer_count: int | None = None, query_answer_threshold: float | None = None, query_caption: str | QueryCaptionType | None = None, query_caption_highlight_enabled: bool | None = None, semantic_configuration_name: str | None = None, select: List[str] | None = None, skip: int | None = None, top: int | None = None, scoring_statistics: str | ScoringStatistics | None = None, session_id: str | None = None, vector_queries: List[VectorQuery] | None = None, vector_filter_mode: str | VectorFilterMode | None = None, semantic_error_mode: str | SemanticErrorMode | None = None, semantic_max_wait_in_milliseconds: int | None = None, **kwargs: Any) -> SearchItemPaged[Dict]

Parameters

Name	Description
search_text Required	str A full-text search query expression; Use "*" or omit this parameter to match all documents.

Keyword-Only Parameters

Name	Description
include_total_count	bool A value that specifies whether to fetch the total count of results. Default is false. Setting this value to true may have a performance impact. Note that the count returned is an approximation.
facets	list[str] The list of facet expressions to apply to the search query. Each facet expression contains a field name, optionally followed by a comma-separated list of name:value pairs.
filter	str The OData $filter expression to apply to the search query.
highlight_fields	str The comma-separated list of field names to use for hit highlights. Only searchable fields can be used for hit highlighting.
highlight_post_tag	str A string tag that is appended to hit highlights. Must be set with highlightPreTag. Default is .
highlight_pre_tag	str A string tag that is prepended to hit highlights. Must be set with highlightPostTag. Default is .
minimum_coverage	float A number between 0 and 100 indicating the percentage of the index that must be covered by a search query in order for the query to be reported as a success. This parameter can be useful for ensuring search availability even for services with only one replica. The default is 100.
order_by	list[str] The list of OData $orderby expressions by which to sort the results. Each expression can be either a field name or a call to either the geo.distance() or the search.score() functions. Each expression can be followed by asc to indicate ascending, and desc to indicate descending. The default is ascending order. Ties will be broken by the match scores of documents. If no OrderBy is specified, the default sort order is descending by document match score. There can be at most 32 $orderby clauses.
query_type	str or QueryType A value that specifies the syntax of the search query. The default is 'simple'. Use 'full' if your query uses the Lucene query syntax. Possible values include: 'simple', 'full', "semantic".
scoring_parameters	list[str] The list of parameter values to be used in scoring functions (for example, referencePointParameter) using the format name-values. For example, if the scoring profile defines a function with a parameter called 'mylocation' the parameter string would be "mylocation–122.2,44.8" (without the quotes).
scoring_profile	str The name of a scoring profile to evaluate match scores for matching documents in order to sort the results.
semantic_query	str Allows setting a separate search query that will be solely used for semantic reranking, semantic captions and semantic answers. Is useful for scenarios where there is a need to use different queries between the base retrieval and ranking phase, and the L2 semantic phase.
search_fields	list[str] The list of field names to which to scope the full-text search. When using fielded search (fieldName:searchExpression) in a full Lucene query, the field names of each fielded search expression take precedence over any field names listed in this parameter.
search_mode	str or SearchMode A value that specifies whether any or all of the search terms must be matched in order to count the document as a match. Possible values include: 'any', 'all'.
query_answer	str or QueryAnswerType This parameter is only valid if the query type is 'semantic'. If set, the query returns answers extracted from key passages in the highest ranked documents. Possible values include: "none", "extractive".
query_answer_count	int This parameter is only valid if the query type is 'semantic' and query answer is 'extractive'. Configures the number of answers returned. Default count is 1.
query_answer_threshold	float This parameter is only valid if the query type is 'semantic' and query answer is 'extractive'. Configures the number of confidence threshold. Default count is 0.7.
query_caption	str or QueryCaptionType This parameter is only valid if the query type is 'semantic'. If set, the query returns captions extracted from key passages in the highest ranked documents. Defaults to 'None'. Possible values include: "none", "extractive".
query_caption_highlight_enabled	bool This parameter is only valid if the query type is 'semantic' when query caption is set to 'extractive'. Determines whether highlighting is enabled. Defaults to 'true'.
semantic_configuration_name	str The name of the semantic configuration that will be used when processing documents for queries of type semantic.
select	list[str] The list of fields to retrieve. If unspecified, all fields marked as retrievable in the schema are included.
skip	int The number of search results to skip. This value cannot be greater than 100,000. If you need to scan documents in sequence, but cannot use $skip due to this limitation, consider using $orderby on a totally-ordered key and $filter with a range query instead.
top	int The number of search results to retrieve. This can be used in conjunction with $skip to implement client-side paging of search results. If results are truncated due to server-side paging, the response will include a continuation token that can be used to issue another Search request for the next page of results.
scoring_statistics	str or ScoringStatistics A value that specifies whether we want to calculate scoring statistics (such as document frequency) globally for more consistent scoring, or locally, for lower latency. The default is 'local'. Use 'global' to aggregate scoring statistics globally before scoring. Using global scoring statistics can increase latency of search queries. Possible values include: "local", "global".
session_id	str A value to be used to create a sticky session, which can help getting more consistent results. As long as the same sessionId is used, a best-effort attempt will be made to target the same replica set. Be wary that reusing the same sessionID values repeatedly can interfere with the load balancing of the requests across replicas and adversely affect the performance of the search service. The value used as sessionId cannot start with a '_' character.
semantic_error_mode	str or SemanticErrorMode Allows the user to choose whether a semantic call should fail completely (default / current behavior), or to return partial results. Known values are: "partial" and "fail".
semantic_max_wait_in_milliseconds	int Allows the user to set an upper bound on the amount of time it takes for semantic enrichment to finish processing before the request fails.
vector_queries	list[VectorQuery] The query parameters for vector and hybrid search queries.
vector_filter_mode	str or VectorFilterMode Determines whether or not filters are applied before or after the vector search is performed. Default is 'preFilter'. Known values are: "postFilter" and "preFilter".

Returns

Type	Description
SearchItemPaged[dict]	List of search results.

Examples

Get search result facets.


   from azure.core.credentials import AzureKeyCredential
   from azure.search.documents import SearchClient

   search_client = SearchClient(service_endpoint, index_name, AzureKeyCredential(key))

   results = search_client.search(search_text="WiFi", facets=["category,count:3", "parkingIncluded"])

   facets: Dict[str, List[str]] = cast(Dict[str, List[str]], results.get_facets())

   print("Catgory facet counts for hotels:")
   for facet in facets["category"]:
       print("    {}".format(facet))

send_request

Runs a network request using the client's existing pipeline.

send_request(request: HttpRequest, *, stream: bool = False, **kwargs) -> HttpResponse

Parameters

Name	Description
request Required	HttpRequest The network request you want to make.

Keyword-Only Parameters

Name	Description
stream	bool Whether the response payload will be streamed. Defaults to False.

Returns

Type	Description
HttpResponse	The response of your network call. Does not do error handling on your response.

suggest

Get search suggestion results from the Azure search index.

suggest(search_text: str, suggester_name: str, *, filter: str | None = None, use_fuzzy_matching: bool | None = None, highlight_post_tag: str | None = None, highlight_pre_tag: str | None = None, minimum_coverage: float | None = None, order_by: List[str] | None = None, search_fields: List[str] | None = None, select: List[str] | None = None, top: int | None = None, **kwargs) -> List[Dict]

Parameters

Name	Description
search_text Required	str Required. The search text to use to suggest documents. Must be at least 1 character, and no more than 100 characters.
suggester_name Required	str Required. The name of the suggester as specified in the suggesters collection that's part of the index definition.

Keyword-Only Parameters

Name	Description
filter	str An OData expression that filters the documents considered for suggestions.
use_fuzzy_matching	bool A value indicating whether to use fuzzy matching for the suggestions query. Default is false. When set to true, the query will find terms even if there's a substituted or missing character in the search text. While this provides a better experience in some scenarios, it comes at a performance cost as fuzzy suggestions queries are slower and consume more resources.
highlight_post_tag	str A string tag that is appended to hit highlights. Must be set with highlightPreTag. If omitted, hit highlighting of suggestions is disabled.
highlight_pre_tag	str A string tag that is prepended to hit highlights. Must be set with highlightPostTag. If omitted, hit highlighting of suggestions is disabled.
minimum_coverage	float A number between 0 and 100 indicating the percentage of the index that must be covered by a suggestions query in order for the query to be reported as a success. This parameter can be useful for ensuring search availability even for services with only one replica. The default is 80.
order_by	list[str] The list of OData $orderby expressions by which to sort the results. Each expression can be either a field name or a call to either the geo.distance() or the search.score() functions. Each expression can be followed by asc to indicate ascending, or desc to indicate descending. The default is ascending order. Ties will be broken by the match scores of documents. If no $orderby is specified, the default sort order is descending by document match score. There can be at most 32 $orderby clauses.
search_fields	list[str] The list of field names to search for the specified search text. Target fields must be included in the specified suggester.
select	list[str] The list of fields to retrieve. If unspecified, only the key field will be included in the results.
top	int The number of suggestions to retrieve. The value must be a number between 1 and 100. The default is 5.

Returns

Type	Description
list[dict]	List of suggestion results.

Examples

Get search suggestions.


   from azure.core.credentials import AzureKeyCredential
   from azure.search.documents import SearchClient

   search_client = SearchClient(service_endpoint, index_name, AzureKeyCredential(key))

   results = search_client.suggest(search_text="coffee", suggester_name="sg")

   print("Search suggestions for 'coffee'")
   for result in results:
       hotel = search_client.get_document(key=result["hotelId"])
       print("    Text: {} for Hotel: {}".format(repr(result["text"]), hotel["hotelName"]))

upload_documents

Upload documents to the Azure search index.

An upload action is similar to an "upsert" where the document will be inserted if it is new and updated/replaced if it exists. All fields are replaced in the update case.

upload_documents(documents: List[Dict], **kwargs: Any) -> List[IndexingResult]

Parameters

Name	Description
documents Required	list[dict] A list of documents to upload.

Keyword-Only Parameters

Name	Description
mode	str or AutocompleteMode Specifies the mode for Autocomplete. The default is 'oneTerm'. Use 'twoTerms' to get shingles and 'oneTermWithContext' to use the current context while producing auto-completed terms. Possible values include: 'oneTerm', 'twoTerms', 'oneTermWithContext'.
filter	str An OData expression that filters the documents used to produce completed terms for the Autocomplete result.
use_fuzzy_matching	bool A value indicating whether to use fuzzy matching for the autocomplete query. Default is false. When set to true, the query will find terms even if there's a substituted or missing character in the search text. While this provides a better experience in some scenarios, it comes at a performance cost as fuzzy autocomplete queries are slower and consume more resources.
highlight_post_tag	str A string tag that is appended to hit highlights. Must be set with highlightPreTag. If omitted, hit highlighting is disabled.
highlight_pre_tag	str A string tag that is prepended to hit highlights. Must be set with highlightPostTag. If omitted, hit highlighting is disabled.
minimum_coverage	float A number between 0 and 100 indicating the percentage of the index that must be covered by an autocomplete query in order for the query to be reported as a success. This parameter can be useful for ensuring search availability even for services with only one replica. The default is 80.
search_fields	list[str] The list of field names to consider when querying for auto-completed terms. Target fields must be included in the specified suggester.
top	int The number of auto-completed terms to retrieve. This must be a value between 1 and 100. The default is 5.

Returns

Type	Description
list[IndexingResult]	List of IndexingResult

Examples

Upload new documents to an index


   DOCUMENT = {
       "category": "Hotel",
       "hotelId": "1000",
       "rating": 4.0,
       "rooms": [],
       "hotelName": "Azure Inn",
   }

   result = search_client.upload_documents(documents=[DOCUMENT])

   print("Upload of new document succeeded: {}".format(result[0].succeeded))

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SearchClient Class

Constructor

Parameters

Keyword-Only Parameters

Examples

Methods

autocomplete

Parameters

Keyword-Only Parameters

Returns

Examples

close

Keyword-Only Parameters

delete_documents

Parameters

Keyword-Only Parameters

Returns

Examples

get_document

Parameters

Keyword-Only Parameters

Returns

Examples

get_document_count

Keyword-Only Parameters

Returns

index_documents

Parameters

Keyword-Only Parameters

Returns

merge_documents

Parameters

Keyword-Only Parameters

Returns

Examples

merge_or_upload_documents

Parameters

Keyword-Only Parameters

Returns

search

Parameters

Keyword-Only Parameters

Returns

Examples

send_request

Parameters

Keyword-Only Parameters

Returns

suggest

Parameters

Keyword-Only Parameters

Returns

Examples

upload_documents

Parameters

Keyword-Only Parameters

Returns

Examples

Additional resources