hd2neo4j 0.1.7

yet another tool for transforming heterogeneous data in to knowledge graph

hd2neo4j

hd2neo4j tool to transform heterogeneous data into a knowledge graph stored in Neo4j.

Installation

pip install hd2neo4j

Usage

1. Import Necessary Services

Import RepositoryService and MapperService from hd2neo4j.services, which handle the connection to Neo4j and data mapping, respectively.

from hd2neo4j.services import RepositoryService, MapperService

2. Connect to Neo4j

Stablish a connection to the Neo4j database using RepositoryService.

r_service: RepositoryService = RepositoryService(
    "neo4j://connection-uri:port", "user", "Neo4j_password", "database_name"
)

3. Load Configuration and Data

Two things are needed to start the mapping process:

• The mapping configuration JSON file.
• A data array to transform into a Neo4j graph. For large amounts of data, using a Python iterator is recommended.

4. Execute the Mapping Process

initialize MapperService with the loaded configuration and data, and then the mapping process is executed by calling start_mapping().

m_service: MapperService = MapperService(
    mapping_config=config, 
    repository_service=r_service, 
    data_to_map=data
)

m_service.start_mapping()

5. (Optional) Clean the Database

If you want to clear the database before performing a new mapping, you can use:

r_service.clean_graph_db()