tab2neo 1.1.1.2

Clinical Linked Data: High-level Python classes to load, model and reshape tabular data imported into Neo4j database

tab2neo- backend classes

High-level Python classes to load, model and reshape tabular data imported into Neo4j database
IMPORTANT NOTE: tested on versions 4.3.6 and 4.4.11 of Neo4j

Installation

pip install tab2neo

Modules

DATA LOADERS - modules allowing to read data from various formats and write it to neo4j

• FileDataLoader - Load data into Neo4j, with support the following input formats: sas7bdat, xpt, rda, xls, xlsx, csv See details

MODEL APPLIERS

• ModelApplier - Class to restructure data in Neo4j database using Class-Relationship model (which as well resides in Neo4j). See details

DATA PROVIDERS

• DataProvider - To fetch the data already in the database (in particular, the way the data after the transformations with ModelApplier in mode='schema_PROPERTY', or any linked data in Neo4j in mode = 'noschema') See details

MODEL MANAGERS

• ModelManager - Class to manage metadata nodes (Class-Relationship model)

QUERY BUILDERS

• QueryBuilder - Class to support creation of cypher queries to work with data in Neo4j

Dependencies:

• https://github.com/GSK-Biostatistics/neointerface