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The initial version of the Socket Python SDK is now on PyPI, enabling developers to more easily interact with the Socket REST API in Python projects.
@redis/search
Advanced tools
This package provides support for the [RediSearch](https://redisearch.io) module, which adds indexing and querying support for data stored in Redis Hashes or as JSON documents with the RedisJSON module. It extends the [Node Redis client](https://github.c
The @redis/search npm package is designed to facilitate full-text search capabilities in Redis. It leverages the RediSearch module to provide powerful search functionalities, including indexing, querying, and full-text search within Redis databases. This package allows developers to efficiently implement search features in their applications by using Redis as the underlying technology.
Creating an Index
This feature allows you to create an index on your Redis data. The example demonstrates creating an index named 'idx:movie' on a JSON document, specifying fields like title, description, and genre with their respective data types.
const { Client } = require('@redis/client');
const { createClient } = require('@redis/search');
async function main() {
const client = createClient();
await client.ft.create('idx:movie', {
'$.title': 'TEXT',
'$.description': 'TEXT',
'$.genre': 'TAG'
}, {
ON: 'JSON'
});
}
main();
Searching an Index
This feature enables searching through the index you've created. The code sample searches the 'idx:movie' index for movies with the title 'Inception' and logs the results.
const { Client } = require('@redis/client');
const { createClient } = require('@redis/search');
async function main() {
const client = createClient();
const results = await client.ft.search('idx:movie', '@title:(Inception)');
console.log(results);
}
main();
Aggregating Search Results
This feature allows for the aggregation of search results based on certain criteria. In this example, it aggregates movies by genre, specifically 'Action', and counts how many movies fall into this category.
const { Client } = require('@redis/client');
const { createClient } = require('@redis/search');
async function main() {
const client = createClient();
const results = await client.ft.aggregate('idx:movie', '@genre:{Action}', {
LOAD: ['$.title'],
GROUPBY: ['@genre'],
REDUCE: ['COUNT', 0, 'AS', 'count']
});
console.log(results);
}
main();
Redis OM provides an object mapping solution for Redis, including support for indexing and searching objects. While it offers similar search capabilities, @redis/search is more focused on leveraging the RediSearch module directly for advanced search features.
Elasticsearch is a distributed, RESTful search and analytics engine capable of solving a broad set of use cases. While not a Redis-based solution, it offers comprehensive full-text search capabilities similar to those of @redis/search but is designed for use cases requiring distributed search capabilities across large datasets.
This package provides support for the RediSearch module, which adds indexing and querying support for data stored in Redis Hashes or as JSON documents with the RedisJSON module. It extends the Node Redis client to include functions for each of the RediSearch commands.
To use these extra commands, your Redis server must have the RediSearch module installed. To index and query JSON documents, you'll also need to add the RedisJSON module.
For complete examples, see search-hashes.js
and search-json.js
in the Node Redis examples folder.
Before we can perform any searches, we need to tell RediSearch how to index our data, and which Redis keys to find that data in. The FT.CREATE command creates a RediSearch index. Here's how to use it to create an index we'll call idx:animals
where we want to index hashes containing name
, species
and age
fields, and whose key names in Redis begin with the prefix noderedis:animals
:
await client.ft.create('idx:animals', {
name: {
type: SchemaFieldTypes.TEXT,
sortable: true
},
species: SchemaFieldTypes.TAG,
age: SchemaFieldTypes.NUMERIC
}, {
ON: 'HASH',
PREFIX: 'noderedis:animals'
}
);
See the FT.CREATE
documentation for information about the different field types and additional options.
Once we've created an index, and added some data to Redis hashes whose keys begin with the prefix noderedis:animals
, we can start writing some search queries. RediSearch supports a rich query syntax for full-text search, faceted search, aggregation and more. Check out the FT.SEARCH
documentation and the query syntax reference for more information.
Let's write a query to find all the animals where the species
field has the value dog
:
const results = await client.ft.search('idx:animals', '@species:{dog}');
results
looks like this:
{
total: 2,
documents: [
{
id: 'noderedis:animals:4',
value: {
name: 'Fido',
species: 'dog',
age: '7'
}
},
{
id: 'noderedis:animals:3',
value: {
name: 'Rover',
species: 'dog',
age: '9'
}
}
]
}
RediSearch can also index and query JSON documents stored in Redis using the RedisJSON module. The approach is similar to that for indexing and searching data in hashes, but we can now use JSON Path like syntax and the data no longer has to be flat name/value pairs - it can contain nested objects and arrays.
As before, we create an index with the FT.CREATE
command, this time specifying we want to index JSON documents that look like this:
{
name: 'Alice',
age: 32,
coins: 100
}
Each document represents a user in some system, and users have name, age and coins properties.
One way we might choose to index these documents is as follows:
await client.ft.create('idx:users', {
'$.name': {
type: SchemaFieldTypes.TEXT,
SORTABLE: 'UNF'
},
'$.age': {
type: SchemaFieldTypes.NUMERIC,
AS: 'age'
},
'$.coins': {
type: SchemaFieldTypes.NUMERIC,
AS: 'coins'
}
}, {
ON: 'JSON',
PREFIX: 'noderedis:users'
});
Note that we're using JSON Path to specify where the fields to index are in our JSON documents, and the AS
clause to define a name/alias for each field. We'll use these when writing queries.
Now we have an index and some data stored as JSON documents in Redis (see the JSON package documentation for examples of how to store JSON), we can write some queries...
We'll use the RediSearch query language and FT.SEARCH
command. Here's a query to find users under the age of 30:
await client.ft.search('idx:users', '@age:[0 30]');
FAQs
This package provides support for the [RediSearch](https://redisearch.io) module, which adds indexing and querying support for data stored in Redis Hashes or as JSON documents with the RedisJSON module. It extends the [Node Redis client](https://github.c
The npm package @redis/search receives a total of 2,086,380 weekly downloads. As such, @redis/search popularity was classified as popular.
We found that @redis/search demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 3 open source maintainers collaborating on the project.
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