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JSDOC: CLASS: INDEX
An index contains the built index of all documents and provides a query interface to the index. Usually instances of lunr.Index will not be created using this constructor, instead lunr.Builder should be used to construct new indexes, or lunr.Index.load should be used to load previously built and serialized indexes.JSDOC: GLOBAL
A function that is used to extract a field from a document. Lunr expects a field to be at the top level of a document, if however the field is deeply nested within a document an extractor function can be used to extract the right field for indexing.JSDOC: CLASS: QUERY
A lunr.Query provides a programmatic way of defining queries to be performed against a lunr.Index.. Prefer constructing a lunr.Query using the lunr.Index#query method so the query object is pre-initialized with the right index fields. SEARCHING : LUNRSEE MORE ON LUNRJS.COM JSDOC: CLASS: PIPELINE Register a function with the pipeline. Functions that are used in the pipeline should be registered if the pipeline needs to be serialised, or a serialised pipeline needs to be loaded. JSDOC: CLASS: TOKENSET A token set is used to store the unique list of all tokens within an index. Token sets are also used to represent an incoming query to the index, this query token set and index token set are then intersected to find which tokens to look up in the inverted index. JSDOC: NAMESPACE: UTILS Convert an object to a string. In the case of null and undefined the function returns the empty string, in all other cases the result of calling toString on the passed object is returned. LUNR: A BIT LIKE SOLR, BUT MUCH SMALLER AND NOT AS BRIGHTDOCSGUIDES Simple. Designed to be small, yet full featured, Lunr enables you to provide a great search experience without the need for external, server-side, search services. CORE CONCEPTS : LUNR JSDOC: CLASS: BUILDER lunr.Builder performs indexing on a set of documents and returns instances of lunr.Index ready for querying. All configuration of the index is done via the builder, the fields to index, the document reference, the text processing pipeline and document scoring parameters are all set on the builder before indexing.JSDOC: CLASS: INDEX
An index contains the built index of all documents and provides a query interface to the index. Usually instances of lunr.Index will not be created using this constructor, instead lunr.Builder should be used to construct new indexes, or lunr.Index.load should be used to load previously built and serialized indexes.JSDOC: GLOBAL
A function that is used to extract a field from a document. Lunr expects a field to be at the top level of a document, if however the field is deeply nested within a document an extractor function can be used to extract the right field for indexing.JSDOC: CLASS: QUERY
A lunr.Query provides a programmatic way of defining queries to be performed against a lunr.Index.. Prefer constructing a lunr.Query using the lunr.Index#query method so the query object is pre-initialized with the right index fields. SEARCHING : LUNRSEE MORE ON LUNRJS.COM JSDOC: CLASS: PIPELINE Register a function with the pipeline. Functions that are used in the pipeline should be registered if the pipeline needs to be serialised, or a serialised pipeline needs to be loaded. JSDOC: CLASS: TOKENSET A token set is used to store the unique list of all tokens within an index. Token sets are also used to represent an incoming query to the index, this query token set and index token set are then intersected to find which tokens to look up in the inverted index. JSDOC: NAMESPACE: UTILS Convert an object to a string. In the case of null and undefined the function returns the empty string, in all other cases the result of calling toString on the passed object is returned.JSDOC: HOME
Home Lunr.js. A bit like Solr, but much smaller and not as bright. Example. A very simple search index can be created using the following: var idx = lunr(functionJSDOC: CLASS: QUERY
A lunr.Query provides a programmatic way of defining queries to be performed against a lunr.Index.. Prefer constructing a lunr.Query using the lunr.Index#query method so the query object is pre-initialized with the right index fields. JSDOC: SOURCE: BUILDER.JS Source: builder.js /*! * lunr.Builder * Copyright (C) @YEAR Oliver Nightingale */ /** * lunr.Builder performs indexing on a set of documents and * returns instancesJSDOC: CLASS: SET
a new set that is the intersection of this and the specified set. JSDOC: CLASS: PIPELINE Register a function with the pipeline. Functions that are used in the pipeline should be registered if the pipeline needs to be serialised, or a serialised pipeline needs to be loaded. JSDOC: SOURCE: TOKEN_SET.JS Source: token_set.js /*! * lunr.TokenSet * Copyright (C) @YEAR Oliver Nightingale */ /** * A token set is used to store the unique list of all tokens * within an index.JSDOC: CLASS: TOKEN
A token wraps a string representation of a token as it is passed through the text processing pipeline. JSDOC: NAMESPACE: UTILS Convert an object to a string. In the case of null and undefined the function returns the empty string, in all other cases the result of calling toString on the passed object is returned. JSDOC: CLASS: TOKENSET A token set is used to store the unique list of all tokens within an index. Token sets are also used to represent an incoming query to the index, this query token set and index token set are then intersected to find which tokens to look up in the inverted index. JSDOC: SOURCE: STEMMER.JS Source: stemmer.js /* eslint-disable */ /*! * lunr.stemmer * Copyright (C) @YEAR Oliver Nightingale * Includes code from - http://tartarus.org/~martin/PorterStemmer LUNR: A BIT LIKE SOLR, BUT MUCH SMALLER AND NOT AS BRIGHTDOCSGUIDES Simple. Designed to be small, yet full featured, Lunr enables you to provide a great search experience without the need for external, server-side, search services. GETTING STARTED : LUNR We will use the above array of documents to build our index. We want to search the text field, and the name field will be our identifier. Let’s define our index and add these documents to it.JSDOC: HOME
JSDOC: CLASS: INDEX
An index contains the built index of all documents and provides a query interface to the index. Usually instances of lunr.Index will not be created using this constructor, instead lunr.Builder should be used to construct new indexes, or lunr.Index.load should be used to load previously built and serialized indexes. JSDOC: CLASS: BUILDER lunr.Builder performs indexing on a set of documents and returns instances of lunr.Index ready for querying. All configuration of the index is done via the builder, the fields to index, the document reference, the text processing pipeline and document scoring parameters are all set on the builder before indexing.SEARCHING : LUNR
JSDOC: CLASS: QUERY
A lunr.Query provides a programmatic way of defining queries to be performed against a lunr.Index.. Prefer constructing a lunr.Query using the lunr.Index#query method so the query object is pre-initialized with the right index fields. JSDOC: CLASS: VECTOR Calculates the position within the vector to insert a given index. This is used internally by insert and upsert. If there are duplicate indexes then the position is returned as if the value for that index were to be updated, but it is the callers responsibility to check whether there is a duplicate at that index JSDOC: CLASS: TOKENSET A token set is used to store the unique list of all tokens within an index. Token sets are also used to represent an incoming query to the index, this query token set and index token set are then intersected to find which tokens to look up in the inverted index. JSDOC: CLASS: MATCHDATA An instance of lunr.MatchData will be created for every term that matches a document. However only one instance is required in alunr.Index~Result.
LUNR: A BIT LIKE SOLR, BUT MUCH SMALLER AND NOT AS BRIGHTDOCSGUIDES Simple. Designed to be small, yet full featured, Lunr enables you to provide a great search experience without the need for external, server-side, search services. GETTING STARTED : LUNR We will use the above array of documents to build our index. We want to search the text field, and the name field will be our identifier. Let’s define our index and add these documents to it.JSDOC: HOME
JSDOC: CLASS: INDEX
An index contains the built index of all documents and provides a query interface to the index. Usually instances of lunr.Index will not be created using this constructor, instead lunr.Builder should be used to construct new indexes, or lunr.Index.load should be used to load previously built and serialized indexes. JSDOC: CLASS: BUILDER lunr.Builder performs indexing on a set of documents and returns instances of lunr.Index ready for querying. All configuration of the index is done via the builder, the fields to index, the document reference, the text processing pipeline and document scoring parameters are all set on the builder before indexing.SEARCHING : LUNR
JSDOC: CLASS: QUERY
A lunr.Query provides a programmatic way of defining queries to be performed against a lunr.Index.. Prefer constructing a lunr.Query using the lunr.Index#query method so the query object is pre-initialized with the right index fields. JSDOC: CLASS: VECTOR Calculates the position within the vector to insert a given index. This is used internally by insert and upsert. If there are duplicate indexes then the position is returned as if the value for that index were to be updated, but it is the callers responsibility to check whether there is a duplicate at that index JSDOC: CLASS: TOKENSET A token set is used to store the unique list of all tokens within an index. Token sets are also used to represent an incoming query to the index, this query token set and index token set are then intersected to find which tokens to look up in the inverted index. JSDOC: CLASS: MATCHDATA An instance of lunr.MatchData will be created for every term that matches a document. However only one instance is required in alunr.Index~Result.
JSDOC: HOME
Home Lunr.js. A bit like Solr, but much smaller and not as bright. Example. A very simple search index can be created using the following: var idx = lunr(functionJSDOC: GLOBAL
A function that is used to extract a field from a document. Lunr expects a field to be at the top level of a document, if however the field is deeply nested within a document an extractor function can be used to extract the right field for indexing.JSDOC: CLASS: QUERY
A lunr.Query provides a programmatic way of defining queries to be performed against a lunr.Index.. Prefer constructing a lunr.Query using the lunr.Index#query method so the query object is pre-initialized with the right index fields. JSDOC: SOURCE: BUILDER.JS Source: builder.js /*! * lunr.Builder * Copyright (C) @YEAR Oliver Nightingale */ /** * lunr.Builder performs indexing on a set of documents and * returns instancesJSDOC: CLASS: SET
a new set that is the intersection of this and the specified set. JSDOC: CLASS: PIPELINE Register a function with the pipeline. Functions that are used in the pipeline should be registered if the pipeline needs to be serialised, or a serialised pipeline needs to be loaded. JSDOC: CLASS: MATCHDATA An instance of lunr.MatchData will be created for every term that matches a document. However only one instance is required in alunr.Index~Result.
JSDOC: CLASS: TOKENSET A token set is used to store the unique list of all tokens within an index. Token sets are also used to represent an incoming query to the index, this query token set and index token set are then intersected to find which tokens to look up in the inverted index. JSDOC: NAMESPACE: UTILS Convert an object to a string. In the case of null and undefined the function returns the empty string, in all other cases the result of calling toString on the passed object is returned. JSDOC: SOURCE: STEMMER.JS Source: stemmer.js /* eslint-disable */ /*! * lunr.stemmer * Copyright (C) @YEAR Oliver Nightingale * Includes code from - http://tartarus.org/~martin/PorterStemmer LUNR: A BIT LIKE SOLR, BUT MUCH SMALLER AND NOT AS BRIGHTDOCSGUIDES Simple. Designed to be small, yet full featured, Lunr enables you to provide a great search experience without the need for external, server-side, search services. GETTING STARTED : LUNR We will use the above array of documents to build our index. We want to search the text field, and the name field will be our identifier. Let’s define our index and add these documents to it.JSDOC: HOME
JSDOC: CLASS: INDEX
An index contains the built index of all documents and provides a query interface to the index. Usually instances of lunr.Index will not be created using this constructor, instead lunr.Builder should be used to construct new indexes, or lunr.Index.load should be used to load previously built and serialized indexes.SEARCHING : LUNR
JSDOC: CLASS: BUILDER lunr.Builder performs indexing on a set of documents and returns instances of lunr.Index ready for querying. All configuration of the index is done via the builder, the fields to index, the document reference, the text processing pipeline and document scoring parameters are all set on the builder before indexing.JSDOC: CLASS: QUERY
A lunr.Query provides a programmatic way of defining queries to be performed against a lunr.Index.. Prefer constructing a lunr.Query using the lunr.Index#query method so the query object is pre-initialized with the right index fields. JSDOC: NAMESPACE: UTILS Convert an object to a string. In the case of null and undefined the function returns the empty string, in all other cases the result of calling toString on the passed object is returned. JSDOC: CLASS: PIPELINE Register a function with the pipeline. Functions that are used in the pipeline should be registered if the pipeline needs to be serialised, or a serialised pipeline needs to be loaded. JSDOC: CLASS: TOKENSET A token set is used to store the unique list of all tokens within an index. Token sets are also used to represent an incoming query to the index, this query token set and index token set are then intersected to find which tokens to look up in the inverted index. LUNR: A BIT LIKE SOLR, BUT MUCH SMALLER AND NOT AS BRIGHTDOCSGUIDES Simple. Designed to be small, yet full featured, Lunr enables you to provide a great search experience without the need for external, server-side, search services. GETTING STARTED : LUNR We will use the above array of documents to build our index. We want to search the text field, and the name field will be our identifier. Let’s define our index and add these documents to it.JSDOC: HOME
JSDOC: CLASS: INDEX
An index contains the built index of all documents and provides a query interface to the index. Usually instances of lunr.Index will not be created using this constructor, instead lunr.Builder should be used to construct new indexes, or lunr.Index.load should be used to load previously built and serialized indexes.SEARCHING : LUNR
JSDOC: CLASS: BUILDER lunr.Builder performs indexing on a set of documents and returns instances of lunr.Index ready for querying. All configuration of the index is done via the builder, the fields to index, the document reference, the text processing pipeline and document scoring parameters are all set on the builder before indexing.JSDOC: CLASS: QUERY
A lunr.Query provides a programmatic way of defining queries to be performed against a lunr.Index.. Prefer constructing a lunr.Query using the lunr.Index#query method so the query object is pre-initialized with the right index fields. JSDOC: NAMESPACE: UTILS Convert an object to a string. In the case of null and undefined the function returns the empty string, in all other cases the result of calling toString on the passed object is returned. JSDOC: CLASS: PIPELINE Register a function with the pipeline. Functions that are used in the pipeline should be registered if the pipeline needs to be serialised, or a serialised pipeline needs to be loaded. JSDOC: CLASS: TOKENSET A token set is used to store the unique list of all tokens within an index. Token sets are also used to represent an incoming query to the index, this query token set and index token set are then intersected to find which tokens to look up in the inverted index.JSDOC: HOME
Home Lunr.js. A bit like Solr, but much smaller and not as bright. Example. A very simple search index can be created using the following: var idx = lunr(functionJSDOC: GLOBAL
A function that is used to extract a field from a document. Lunr expects a field to be at the top level of a document, if however the field is deeply nested within a document an extractor function can be used to extract the right field for indexing. JSDOC: SOURCE: BUILDER.JS Source: builder.js /*! * lunr.Builder * Copyright (C) @YEAR Oliver Nightingale */ /** * lunr.Builder performs indexing on a set of documents and * returns instancesJSDOC: CLASS: SET
a new set that is the intersection of this and the specified set. JSDOC: NAMESPACE: UTILS Convert an object to a string. In the case of null and undefined the function returns the empty string, in all other cases the result of calling toString on the passed object is returned. JSDOC: CLASS: PIPELINE Register a function with the pipeline. Functions that are used in the pipeline should be registered if the pipeline needs to be serialised, or a serialised pipeline needs to be loaded. JSDOC: CLASS: TOKENSET A token set is used to store the unique list of all tokens within an index. Token sets are also used to represent an incoming query to the index, this query token set and index token set are then intersected to find which tokens to look up in the inverted index.JSDOC: CLASS: TOKEN
A token wraps a string representation of a token as it is passed through the text processing pipeline. JSDOC: CLASS: MATCHDATA An instance of lunr.MatchData will be created for every term that matches a document. However only one instance is required in alunr.Index~Result.
JSDOC: SOURCE: TOKEN_SET.JS Source: token_set.js. /*! * within an index. Token sets are also used to represent an. * up in the inverted index. * case of a simple query token set. * Additionally token sets are used to perform wildcard matching. * from this edit distance matching can also be provided. * where both common prefixes and suffixes are shared between tokens. LUNR: A BIT LIKE SOLR, BUT MUCH SMALLER AND NOT AS BRIGHTDOCSGUIDES Simple. Designed to be small, yet full featured, Lunr enables you to provide a great search experience without the need for external, server-side, search services. GETTING STARTED : LUNR We will use the above array of documents to build our index. We want to search the text field, and the name field will be our identifier. Let’s define our index and add these documents to it.JSDOC: HOME
JSDOC: CLASS: INDEX
An index contains the built index of all documents and provides a query interface to the index. Usually instances of lunr.Index will not be created using this constructor, instead lunr.Builder should be used to construct new indexes, or lunr.Index.load should be used to load previously built and serialized indexes.SEARCHING : LUNR
JSDOC: CLASS: BUILDER lunr.Builder performs indexing on a set of documents and returns instances of lunr.Index ready for querying. All configuration of the index is done via the builder, the fields to index, the document reference, the text processing pipeline and document scoring parameters are all set on the builder before indexing.JSDOC: CLASS: QUERY
A lunr.Query provides a programmatic way of defining queries to be performed against a lunr.Index.. Prefer constructing a lunr.Query using the lunr.Index#query method so the query object is pre-initialized with the right index fields. JSDOC: NAMESPACE: UTILS Convert an object to a string. In the case of null and undefined the function returns the empty string, in all other cases the result of calling toString on the passed object is returned. JSDOC: CLASS: PIPELINE Register a function with the pipeline. Functions that are used in the pipeline should be registered if the pipeline needs to be serialised, or a serialised pipeline needs to be loaded. JSDOC: CLASS: TOKENSET A token set is used to store the unique list of all tokens within an index. Token sets are also used to represent an incoming query to the index, this query token set and index token set are then intersected to find which tokens to look up in the inverted index. LUNR: A BIT LIKE SOLR, BUT MUCH SMALLER AND NOT AS BRIGHTDOCSGUIDES Simple. Designed to be small, yet full featured, Lunr enables you to provide a great search experience without the need for external, server-side, search services. GETTING STARTED : LUNR We will use the above array of documents to build our index. We want to search the text field, and the name field will be our identifier. Let’s define our index and add these documents to it.JSDOC: HOME
JSDOC: CLASS: INDEX
An index contains the built index of all documents and provides a query interface to the index. Usually instances of lunr.Index will not be created using this constructor, instead lunr.Builder should be used to construct new indexes, or lunr.Index.load should be used to load previously built and serialized indexes.SEARCHING : LUNR
JSDOC: CLASS: BUILDER lunr.Builder performs indexing on a set of documents and returns instances of lunr.Index ready for querying. All configuration of the index is done via the builder, the fields to index, the document reference, the text processing pipeline and document scoring parameters are all set on the builder before indexing.JSDOC: CLASS: QUERY
A lunr.Query provides a programmatic way of defining queries to be performed against a lunr.Index.. Prefer constructing a lunr.Query using the lunr.Index#query method so the query object is pre-initialized with the right index fields. JSDOC: NAMESPACE: UTILS Convert an object to a string. In the case of null and undefined the function returns the empty string, in all other cases the result of calling toString on the passed object is returned. JSDOC: CLASS: PIPELINE Register a function with the pipeline. Functions that are used in the pipeline should be registered if the pipeline needs to be serialised, or a serialised pipeline needs to be loaded. JSDOC: CLASS: TOKENSET A token set is used to store the unique list of all tokens within an index. Token sets are also used to represent an incoming query to the index, this query token set and index token set are then intersected to find which tokens to look up in the inverted index.JSDOC: HOME
Home Lunr.js. A bit like Solr, but much smaller and not as bright. Example. A very simple search index can be created using the following: var idx = lunr(functionJSDOC: GLOBAL
A function that is used to extract a field from a document. Lunr expects a field to be at the top level of a document, if however the field is deeply nested within a document an extractor function can be used to extract the right field for indexing. JSDOC: SOURCE: BUILDER.JS Source: builder.js /*! * lunr.Builder * Copyright (C) @YEAR Oliver Nightingale */ /** * lunr.Builder performs indexing on a set of documents and * returns instancesJSDOC: CLASS: SET
a new set that is the intersection of this and the specified set. JSDOC: NAMESPACE: UTILS Convert an object to a string. In the case of null and undefined the function returns the empty string, in all other cases the result of calling toString on the passed object is returned. JSDOC: CLASS: PIPELINE Register a function with the pipeline. Functions that are used in the pipeline should be registered if the pipeline needs to be serialised, or a serialised pipeline needs to be loaded. JSDOC: CLASS: TOKENSET A token set is used to store the unique list of all tokens within an index. Token sets are also used to represent an incoming query to the index, this query token set and index token set are then intersected to find which tokens to look up in the inverted index.JSDOC: CLASS: TOKEN
A token wraps a string representation of a token as it is passed through the text processing pipeline. JSDOC: CLASS: MATCHDATA An instance of lunr.MatchData will be created for every term that matches a document. However only one instance is required in alunr.Index~Result.
JSDOC: SOURCE: TOKEN_SET.JS Source: token_set.js. /*! * within an index. Token sets are also used to represent an. * up in the inverted index. * case of a simple query token set. * Additionally token sets are used to perform wildcard matching. * from this edit distance matching can also be provided. * where both common prefixes and suffixes are shared between tokens.* Home
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LUNR
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SIMPLE
Designed to be small, yet full featured, Lunr enables you to provide a great search experience without the need for external, server-side,search services.
EXTENSIBLE
Add powerful language processors to give more accurate results to user queries, or tweak the built-in processors to better fit your content.EVERYWHERE
Lunr has no external dependencies and works in your browser or on theserver with node.js
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