Neo4j Graph Database Fundamentals · Lección

Ejecución programática de operaciones CRUD

Ejecute consultas Cypher desde su aplicación para crear, leer, actualizar y eliminar datos del grafo de forma dinámica.

Ejecución programática de operaciones CRUD es una lección gratuita de Neo4j Graph Database Fundamentals en CoddyKit. Esta es la lección 2 de 4. Puedes leer la lección completa abajo gratuitamente — luego la practicas en el navegador con un editor de código integrado y un tutor de IA 24/7. Forma parte de la ruta de aprendizaje de Neo4j Graph Database Fundamentals, y tu progreso se sincroniza en la web y la app de CoddyKit. El curso de Neo4j Graph Database Fundamentals incluye 4 lecciones en total.

Partes de esta lección aún no han sido traducidas y se muestran en inglés.

CRUD from Your Application

When building applications, you'll often need to interact with your Neo4j database programmatically. This means writing code that sends Cypher queries to create, read, update, and delete data.

These fundamental operations are often referred to as CRUD:

Create: Adding new data (nodes, relationships).
Read: Retrieving existing data.
Update: Modifying existing data.
Delete: Removing data.

Connecting to Neo4j (Review)

Before performing any CRUD operations, your application needs to connect to the Neo4j database. As we learned previously, the official Neo4j Python Driver simplifies this.

You'll use a GraphDatabase.driver object to manage connections and then create a session to execute queries.

from neo4j import GraphDatabase

URI = "bolt://localhost:7687"
AUTH = ("neo4j", "password") # Use your credentials

def main():
    driver = GraphDatabase.driver(URI, auth=AUTH)
    with driver.session() as session:
        # Your Cypher queries will go here
        print("Connected to Neo4j!")
    driver.close()

if __name__ == "__main__":
    main()

Creating New Nodes

To add new entities to your graph, you use the Cypher CREATE clause. Programmatically, you pass your Cypher query string and any parameters to the session.run() method.

Using parameters (like $name, $age) is crucial for security and prevents Cypher injection.

from neo4j import GraphDatabase

URI = "bolt://localhost:7687"
AUTH = ("neo4j", "password")

def main():
    driver = GraphDatabase.driver(URI, auth=AUTH)
    with driver.session() as session:
        query = (
            "CREATE (p:Person {name: $name, age: $age}) "
            "RETURN p.name AS name"
        )
        result = session.run(query, name="Charlie", age=25)
        print(f"Created: {result.single()['name']}")
    driver.close()

if __name__ == "__main__":
    main()

Creating Relationships

Relationships connect nodes and are essential for graph structures. To create a relationship, you first need to identify the nodes you want to connect, usually with MATCH, and then use CREATE.

The example connects 'Charlie' (created above) to 'Alice' (we'll ensure she exists for this demo).

from neo4j import GraphDatabase

URI = "bolt://localhost:7687"
AUTH = ("neo4j", "password")

def main():
    driver = GraphDatabase.driver(URI, auth=AUTH)
    with driver.session() as session:
        # Ensure Alice exists for the demo
        session.run("MERGE (:Person {name: 'Alice', age: 30})")

        query = (
            "MATCH (a:Person {name: $name1}), "
            "(b:Person {name: $name2}) "
            "CREATE (a)-[r:KNOWS]->(b) "
            "RETURN type(r) AS relType"
        )
        result = session.run(query, name1="Charlie", name2="Alice")
        print(f"Relationship created: {result.single()['relType']}")
    driver.close()

if __name__ == "__main__":
    main()

Reading Nodes (MATCH & RETURN)

Retrieving data is done using the MATCH clause to find patterns and RETURN to specify what data you want back. You can fetch entire nodes or specific properties.

The session.run() method returns a result object you can iterate over.

from neo4j import GraphDatabase

URI = "bolt://localhost:7687"
AUTH = ("neo4j", "password")

def main():
    driver = GraphDatabase.driver(URI, auth=AUTH)
    with driver.session() as session:
        query = "MATCH (p:Person) RETURN p.name AS name, p.age AS age"
        print("All People:")
        for record in session.run(query):
            print(f"- {record['name']} ({record['age']} years old)")
    driver.close()

if __name__ == "__main__":
    main()

Reading Connected Patterns

Graph databases excel at querying connected data. You can match complex patterns of nodes and relationships and retrieve specific parts of that pattern.

This example finds people who know 'Alice' and returns their names.

from neo4j import GraphDatabase

URI = "bolt://localhost:7687"
AUTH = ("neo4j", "password")

def main():
    driver = GraphDatabase.driver(URI, auth=AUTH)
    with driver.session() as session:
        query = (
            "MATCH (p:Person)-[:KNOWS]->(a:Person {name: $targetName}) "
            "RETURN p.name AS knowsAlice"
        )
        result = session.run(query, targetName="Alice")
        print("People who know Alice:")
        for record in result:
            print(f"- {record['knowsAlice']}")
    driver.close()

if __name__ == "__main__":
    main()

Updating Node Properties

To modify existing data, you use MATCH to find the node(s) or relationship(s) and then the SET clause to change their properties.

Here, we'll update 'Charlie's age to 26.

from neo4j import GraphDatabase

URI = "bolt://localhost:7687"
AUTH = ("neo4j", "password")

def main():
    driver = GraphDatabase.driver(URI, auth=AUTH)
    with driver.session() as session:
        query = (
            "MATCH (p:Person {name: $name}) "
            "SET p.age = $newAge "
            "RETURN p.name AS name, p.age AS newAge"
        )
        result = session.run(query, name="Charlie", newAge=26)
        record = result.single()
        print(f"Updated {record['name']}'s age to {record['newAge']}")
    driver.close()

if __name__ == "__main__":
    main()

Updating Relationship Properties

Just like nodes, relationships can also have properties. You can update these using MATCH to find the relationship and SET to modify its properties.

Let's add a since property to the KNOWS relationship between Charlie and Alice.

from neo4j import GraphDatabase

URI = "bolt://localhost:7687"
AUTH = ("neo4j", "password")

def main():
    driver = GraphDatabase.driver(URI, auth=AUTH)
    with driver.session() as session:
        query = (
            "MATCH (p1:Person {name: $name1})" 
            "-[r:KNOWS]->" 
            "(p2:Person {name: $name2}) "
            "SET r.since = $year "
            "RETURN p1.name, p2.name, r.since AS sinceYear"
        )
        result = session.run(query, name1="Charlie", name2="Alice", year=2022)
        record = result.single()
        print(f"{record['p1.name']} knows {record['p2.name']} since {record['sinceYear']}")
    driver.close()

if __name__ == "__main__":
    main()

Deleting Graph Data

To remove nodes and relationships, you use the DELETE clause. If a node has relationships, you must use DETACH DELETE to remove both the node and its relationships simultaneously.

Using just DELETE on a node with relationships will result in an error.

from neo4j import GraphDatabase

URI = "bolt://localhost:7687"
AUTH = ("neo4j", "password")

def main():
    driver = GraphDatabase.driver(URI, auth=AUTH)
    with driver.session() as session:
        query = (
            "MATCH (p:Person {name: $name}) "
            "DETACH DELETE p"
        )
        result = session.run(query, name="Charlie")
        print("Charlie and related data deleted.")
    driver.close()

if __name__ == "__main__":
    main()

Quick Check: CRUD Operations

You've learned how to perform all fundamental CRUD operations. Let's test your understanding.

Recap: Programmatic CRUD

Great job! In this lesson, you've learned how to perform essential CRUD operations on your Neo4j graph database directly from a Python application:

Create: Use CREATE to add nodes and relationships.
Read: Use MATCH and RETURN to retrieve data.
Update: Use MATCH and SET to modify properties.
Delete: Use MATCH and DETACH DELETE to remove data.

Mastering these operations is key to building dynamic and interactive graph applications.

Preguntas frecuentes

¿La lección «Ejecución programática de operaciones CRUD» es gratis?

Sí — el texto completo de «Ejecución programática de operaciones CRUD» es gratis para leer aquí en la web. Para practicarla de forma interactiva (editor de código integrado y tutor de IA 24/7) y desbloquear el resto del curso de Neo4j Graph Database Fundamentals, actualiza a CoddyKit PRO. El curso de Neo4j Graph Database Fundamentals incluye 4 lecciones en total.

¿Qué aprenderé en «Ejecución programática de operaciones CRUD»?

Ejecute consultas Cypher desde su aplicación para crear, leer, actualizar y eliminar datos del grafo de forma dinámica. Practicas Neo4j Graph Database Fundamentals con código real que ejecutas directamente en el navegador, y un tutor de IA 24/7 responde tus preguntas mientras trabajas en la lección.

¿Necesito experiencia previa para empezar Neo4j Graph Database Fundamentals?

No se requiere experiencia previa. Neo4j Graph Database Fundamentals en CoddyKit está estructurado para principiantes hasta estudiantes avanzados, así que puedes empezar aquí o desde el inicio y avanzar a tu ritmo. Esta es la lección 2 de 4.

¿Cuánto tiempo toma la lección «Ejecución programática de operaciones CRUD»?

La mayoría de las lecciones de CoddyKit toman alrededor de 5–10 minutos. Cada una es compacta e interactiva, así que avanzas constantemente y retomas exactamente por donde dejaste en la web y la app.

¿Puedo escribir y ejecutar código en esta lección de Neo4j Graph Database Fundamentals?

Sí. Cada lección de Neo4j Graph Database Fundamentals incluye un editor de código integrado, así que escribes y ejecutas código real directamente en tu navegador y obtienes retroalimentación instantánea de IA — sin configuración local necesaria.

Todas las lecciones de este curso

Conexión con el controlador de Python
Ejecución programática de operaciones CRUD
Gestión de transacciones y sesiones
Agrupación de conexiones y gestión de errores

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