neosqlite.collection.temporary_table_aggregation.operators_text module

class neosqlite.collection.temporary_table_aggregation.operators_text.OperatorsTextMixin

Bases: OperatorsBaseMixin

_matches_text_search(document: dict[str, Any], search_term: str) → bool

Apply Python-based text search to a document.

This method uses the unified_text_search function to determine if a document matches a given search term. It’s used as a fallback when text search cannot be efficiently handled with SQL queries, particularly in cases involving unwound elements or complex text search operations.

Parameters:

• document (dict[str, Any]) – The document to search in

• search_term (str) – The term to search for

Returns:

True if the document matches the text search, False otherwise

Return type:

bool

_batch_insert_documents(table_name: str, documents: list[tuple]) → None

Insert multiple documents into a temporary table efficiently.

This method provides an optimized way to insert multiple documents into a temporary table by using a single INSERT statement with multiple value sets. It’s used primarily in the text search processing where documents need to be filtered and inserted into a result table.

Parameters:

• table_name (str) – The name of the table to insert into

• documents (list[tuple]) – List of (id, data) tuples to insert

_process_text_search_stage(create_temp: Callable, current_table: str, match_spec: dict[str, Any]) → str

Process a $text search stage using FTS5 on temporary table.

This method creates an FTS5 virtual table on the temporary data and uses SQLite’s FTS5 for efficient text search. The tokenizer configuration is detected from the existing FTS index on the collection to ensure consistent behavior.

Note

When $text is used after $unwind (or other stages that create temp tables), the search operates on the unwound elements in the temp table, not on the original collection documents. This differs from MongoDB’s semantics where $text always uses the collection-level text index on original documents.

Parameters:

• create_temp (Callable) – Function to create temporary tables

• current_table (str) – Name of the current temporary table containing input data

• match_spec (dict[str, Any]) – The $match stage specification containing the $text operator with a $search term

Returns:

Name of the newly created temporary table with text search results

Return type:

str

Raises:

ValueError – If the $text operator specification is invalid or the search term is not a string

_detect_fts_tokenizer() → str

Detect the tokenizer configuration from existing FTS indexes on the collection.

Returns:

The tokenizer clause for FTS5 (e.g., “, tokenize=porter” or “”)

Return type:

str