@qeraunos/client NPM

Qeraunos Client Side Caching

Overview

Qeraunos, a lightweight GraphQL caching algorithm to meet your GraphQL caching needs. Qeraunos is a custom built middleware cache based on a mix of LFU and LRU eviction policies that adds the ability to cache GraphQL queries and mutations. With Qeraunos you have the option to either implement it utilizing client side or server side caching.

Note: if you want to cache utilizing your server please download Qeraunos/Server

Features

Client side caching abilities harnessing the power of IndexedDB through localForage
Efficient design with O(1) insertion, deletion, and lookup

For more complete documentation see our website and our GitHub.

Prerequisites Client Side Caching

GraphQL integration: setting up GraphQL schemas and resolvers
Fullstack Application: frontend sending query requests to the backend

Getting Started

Client Side Caching Installation

Install Qeraunos from npm
```
npm install @qeraunos/client
```
Import QeraunosClient from '@qeraunos/client' within a component that will be requiring a cache
```
import qeraunosClient from '@qeraunos/client';
```
Declare a new instance of QeraunosClient passing in the desired size of the cache as a number
```
const qeraunos = new qeraunosClient(size);
```
To initiate the cache and query GraphQL, simply call the qeraunos.query method within an asynchronous function and pass in a query string and /grapphql endpoint as parameters
```
qeraunos.query('queryString', 'GraphQL Endpoint');
```
When the .query method has finished executing, a response with the results returned from GraphQL will be provided. If this is the first time this has been executed, LocalForage will create a new cache within IndexedDB labeled "qeraunos", and the GraphQL query and result will be cached as key value pairs within "qeraunos".
To access the cache, open the console on your browser and navigate to Application -> Storage -> IndexedDB -> localforage -> keyvaluepairs.
You're set to go and you should find your response times drastically reduced for cached queries. Enjoy impressing your fellow software engineers with a cached implementation of GraphQL!