yet another tool for transforming heterogeneous data in to knowledge graph
Project description
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()
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