Most advanced, well documented and efficient REST client for Neo4j database, with 100% tests coverage. Fibers allows to give a new level experience to developers, no more callback-hell and blocking operations. Speed and low resources consumption is top priority of neo4j-fiber package.
- 100% tests coverage
- Version for Meteor.js - https://atmospherejs.com/ostrio/neo4jdriver
- This this library is heavily depends from Fibers, so you required to wrap all code into Fiber, see example
- This package uses batch operations to perform queries. Batch operations lets you execute multiple API calls through a single HTTP call. This improves performance for large insert and update operations significantly
- This package was tested and works like a charm with GrapheneDB
- To find more about how to use Cypher read Neo4j cheat sheet
npm install --save neo4j-fiber
- Hosted at Heroku (GrapheneDB Add-on)
- Check out it's source code
Please see full API with examples in our wiki
const Neo4jDB = require('neo4j-fiber').Neo4jDB;
const db = new Neo4jDB('http://localhost:7474', {
username: 'neo4j',
password: '1234'
});
Set NEO4J_URL
or GRAPHENEDB_URL
to as connection URL to Neo4j Database
NEO4J_URL="http://neo4j:1234@localhost:7474" node index.js
If environment variable is set, no need to pass url
argument into Neo4jDB
constructor
const Neo4jDB = require('neo4j-fiber').Neo4jDB;
const db = new Neo4jDB();
const cursor = db.query('CREATE (n:City {props}) RETURN n', {
props: {
title: 'Ottawa',
lat: 45.416667,
long: -75.683333
}
});
console.log(cursor.fetch());
// Returns array of nodes:
// [{
// n: {
// long: -75.683333,
// lat: 45.416667,
// title: "Ottawa",
// id: 8421,
// labels": ["City"],
// metadata: {
// id: 8421,
// labels": ["City"]
// }
// }
// }]
// Iterate through results as plain objects:
cursor.forEach((node) => {
console.log(node)
// Returns node as Object:
// {
// n: {
// long: -75.683333,
// lat: 45.416667,
// title: "Ottawa",
// id: 8421,
// labels": ["City"],
// metadata: {
// id: 8421,
// labels": ["City"]
// }
// }
// }
});
// Iterate through cursor as `Neo4jNode` instances:
cursor.each((node) => {
console.log(node.n.get());
// {
// long: -75.683333,
// lat: 45.416667,
// title: "Ottawa",
// id: 8421,
// labels": ["City"],
// metadata: {
// id: 8421,
// labels": ["City"]
// }
// }
});
const node = db.nodes();
const node2 = db.nodes({property: 'value', property2: ['val', 'val2', 'val3']});
const node = db.nodes(123);
node.delete();
const n1 = db.nodes();
const relationship = db.nodes().to(n1, "KNOWS", {property: 'value'});
relationship.delete();
// Create some data:
const cities = {};
cities['Zürich'] = db.nodes({
title: 'Zürich',
lat: 47.27,
long: 8.31
}).label(['City']);
cities['Tokyo'] = db.nodes({
title: 'Tokyo',
lat: 35.40,
long: 139.45
}).label(['City']);
cities['Athens'] = db.nodes({
title: 'Athens',
lat: 37.58,
long: 23.43
}).label(['City']);
cities['Cape Town'] = db.nodes({
title: 'Cape Town',
lat: 33.55,
long: 18.22
}).label(['City']);
// Add relationship between cities
// At this example we set distance
cities['Zürich'].to(cities['Tokyo'], "DISTANCE", {m: 9576670, km: 9576.67, mi: 5950.67});
cities['Tokyo'].to(cities['Zürich'], "DISTANCE", {m: 9576670, km: 9576.67, mi: 5950.67});
// Create route 1 (Zürich -> Athens -> Cape Town -> Tokyo)
cities['Zürich'].to(cities['Athens'], "ROUTE", {m: 1617270, km: 1617.27, mi: 1004.93, price: 50});
cities['Athens'].to(cities['Cape Town'], "ROUTE", {m: 8015080, km: 8015.08, mi: 4980.34, price: 500});
cities['Cape Town'].to(cities['Tokyo'], "ROUTE", {m: 9505550, km: 9505.55, mi: 5906.48, price: 850});
// Create route 2 (Zürich -> Cape Town -> Tokyo)
cities['Zürich'].to(cities['Cape Town'], "ROUTE", {m: 1617270, km: 1617.27, mi: 1004.93, price: 550});
cities['Cape Town'].to(cities['Tokyo'], "ROUTE", {m: 9576670, km: 9576.67, mi: 5950.67, price: 850});
// Create route 3 (Zürich -> Athens -> Tokyo)
cities['Zürich'].to(cities['Athens'], "ROUTE", {m: 1617270, km: 1617.27, mi: 1004.93, price: 50});
cities['Athens'].to(cities['Tokyo'], "ROUTE", {m: 9576670, km: 9576.67, mi: 5950.67, price: 850});
// Get Shortest Route (in km) between two Cities:
const shortest = cities['Zürich'].path(cities['Tokyo'], "ROUTE", {cost_property: 'km', algorithm: 'dijkstra'})[0];
let shortestStr = 'Shortest from Zürich to Tokyo, via: ';
shortest.nodes.forEach((id) => {
shortestStr += db.nodes(id).property('title') + ', ';
});
shortestStr += '| Distance: ' + shortest.weight + ' km';
console.info(shortestStr); // <-- Shortest from Zürich to Tokyo, via: Zürich, Cape Town, Tokyo, | Distance: 11122.82 km
// Get Cheapest Route (in notional currency) between two Cities:
const cheapest = cities['Zürich'].path(cities['Tokyo'], "ROUTE", {cost_property: 'price', algorithm: 'dijkstra'})[0];
let cheapestStr = 'Cheapest from Zürich to Tokyo, via: ';
cheapest.nodes.forEach((id) => {
cheapestStr += db.nodes(id).property('title') + ', ';
});
cheapestStr += '| Price: ' + cheapest.weight + ' nc';
console.info(cheapestStr); // <-- Cheapest from Zürich to Tokyo, via: Zürich, Athens, Tokyo, | Price: 900 nc
For more complex examples and docs, please see our wiki