Terminal.skills
Skills/neo4j
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neo4j

Neo4j is the leading graph database for connected data. Learn Cypher query language, node and relationship modeling, graph algorithms, and integration with Node.js using the official neo4j-driver.

#neo4j#graph-database#cypher#nodejs#relationships
terminal-skillsv1.0.0
Works with:claude-codeopenai-codexgemini-clicursor
Source

Usage

$
✓ Installed neo4j v1.0.0

Getting Started

  1. Install the skill using the command above
  2. Open your AI coding agent (Claude Code, Codex, Gemini CLI, or Cursor)
  3. Reference the skill in your prompt
  4. The AI will use the skill's capabilities automatically

Example Prompts

  • "Analyze the sales data in revenue.csv and identify trends"
  • "Create a visualization comparing Q1 vs Q2 performance metrics"

Information

Version
1.0.0
Author
terminal-skills
Category
Data & AI
License
Apache-2.0

Documentation

Neo4j stores data as nodes and relationships (edges), making it ideal for social networks, recommendation engines, fraud detection, and knowledge graphs.

Installation

bash
# Docker (recommended)
docker run -d --name neo4j -p 7474:7474 -p 7687:7687 \
  -e NEO4J_AUTH=neo4j/password123 \
  neo4j:5

# Access browser UI at http://localhost:7474
# Bolt protocol at bolt://localhost:7687

# Node.js driver
npm install neo4j-driver

# Python driver
pip install neo4j

Cypher Basics

cypher
// create-nodes.cypher: Create nodes with labels and properties
CREATE (alice:Person {name: 'Alice', email: 'alice@example.com', age: 30})
CREATE (bob:Person {name: 'Bob', email: 'bob@example.com', age: 28})
CREATE (graphDb:Technology {name: 'Neo4j', category: 'Database'})
RETURN alice, bob, graphDb;
cypher
// create-relationships.cypher: Connect nodes with typed relationships
MATCH (a:Person {name: 'Alice'}), (b:Person {name: 'Bob'})
CREATE (a)-[:KNOWS {since: 2024}]->(b)
RETURN a, b;

MATCH (a:Person {name: 'Alice'}), (t:Technology {name: 'Neo4j'})
CREATE (a)-[:USES {skill_level: 'expert'}]->(t)
RETURN a, t;

Querying

cypher
// queries.cypher: Common query patterns
// Find friends of friends
MATCH (p:Person {name: 'Alice'})-[:KNOWS]->()-[:KNOWS]->(fof)
WHERE fof <> p
RETURN DISTINCT fof.name;

// Shortest path between two people
MATCH path = shortestPath(
  (a:Person {name: 'Alice'})-[:KNOWS*..6]-(b:Person {name: 'Charlie'})
)
RETURN path, length(path);

// Pattern matching with filtering
MATCH (p:Person)-[r:USES]->(t:Technology)
WHERE r.skill_level = 'expert'
RETURN p.name, collect(t.name) AS technologies;

// Aggregation
MATCH (p:Person)-[:KNOWS]->(friend)
RETURN p.name, count(friend) AS friend_count
ORDER BY friend_count DESC
LIMIT 10;

Indexes and Constraints

cypher
// indexes.cypher: Create indexes and constraints for performance
CREATE CONSTRAINT person_email IF NOT EXISTS
  FOR (p:Person) REQUIRE p.email IS UNIQUE;

CREATE INDEX person_name IF NOT EXISTS
  FOR (p:Person) ON (p.name);

// Composite index
CREATE INDEX order_status_date IF NOT EXISTS
  FOR (o:Order) ON (o.status, o.created_at);

// Full-text index
CREATE FULLTEXT INDEX person_search IF NOT EXISTS
  FOR (p:Person) ON EACH [p.name, p.bio];

CALL db.index.fulltext.queryNodes('person_search', 'Alice') YIELD node, score
RETURN node.name, score;

Node.js Driver

javascript
// db.js: Neo4j client with official Node.js driver
const neo4j = require('neo4j-driver');

const driver = neo4j.driver(
  'bolt://localhost:7687',
  neo4j.auth.basic('neo4j', 'password123')
);

async function findFriends(name) {
  const session = driver.session({ database: 'neo4j' });
  try {
    const result = await session.executeRead(tx =>
      tx.run(
        'MATCH (p:Person {name: $name})-[:KNOWS]->(friend) RETURN friend.name AS name',
        { name }
      )
    );
    return result.records.map(r => r.get('name'));
  } finally {
    await session.close();
  }
}

async function createFriendship(person1, person2) {
  const session = driver.session({ database: 'neo4j' });
  try {
    await session.executeWrite(tx =>
      tx.run(
        `MERGE (a:Person {name: $p1})
         MERGE (b:Person {name: $p2})
         MERGE (a)-[:KNOWS]->(b)`,
        { p1: person1, p2: person2 }
      )
    );
  } finally {
    await session.close();
  }
}

// Cleanup on exit
process.on('exit', () => driver.close());

module.exports = { findFriends, createFriendship };

Python Driver

python
# app.py: Neo4j with official Python driver
from neo4j import GraphDatabase

driver = GraphDatabase.driver("bolt://localhost:7687", auth=("neo4j", "password123"))

def find_friends(name):
    with driver.session() as session:
        result = session.run(
            "MATCH (p:Person {name: $name})-[:KNOWS]->(f) RETURN f.name AS name",
            name=name,
        )
        return [record["name"] for record in result]

def recommend_friends(name):
    with driver.session() as session:
        result = session.run("""
            MATCH (p:Person {name: $name})-[:KNOWS]->(friend)-[:KNOWS]->(rec)
            WHERE NOT (p)-[:KNOWS]->(rec) AND rec <> p
            RETURN rec.name AS name, count(*) AS mutual
            ORDER BY mutual DESC LIMIT 5
        """, name=name)
        return [dict(r) for r in result]

driver.close()

Graph Data Modeling Tips

Modeling Guidelines:
- Nouns → Node labels (Person, Product, Order)
- Verbs → Relationship types (PURCHASED, KNOWS, REVIEWED)
- Adjectives → Properties on nodes or relationships
- Always direction: (a)-[:KNOWS]->(b), query can ignore direction with -[:KNOWS]-
- Avoid super-nodes (millions of relationships); use intermediate nodes
- Use relationship properties for weight, timestamp, metadata