Elsevier Knowledge Platform Python SDK

A comprehensive Python SDK for programmatically accessing and integrating data from Elsevier’s premier knowledgebases, including Resnet, Reaxys, Embase, Pharmapendium, and more.

Overview

This repository serves as a centralized hub for Elsevier data integration. It is designed to bridge various knowledgebases into a unified workflow, with a primary focus on the ResnetAPI, which provides programmatic access to the world’s largest molecular biology knowledge graph.

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The ResnetAPI

The ResnetAPI interfaces with the Pathway Studio relational database. It leverages the Zeep package for SOAP API communication and transforms relational data into high-performance graph representations using NetworkX.

Core Components

• Graph Object Query Language (GOQL): All requests to the relational database are made via GOQL. You can build these queries using the PathwayStudioGOQL.py module or pass raw GOQL strings.
• APISession Class: This is the primary entry point for data retrieval. It handles iterative data fetching to ensure optimal network performance and stability for large datasets.
• ResnetGraph Object: Query results are loaded into an APISession.Graph object, which is a ResnetGraph class derived from networkx.MultiDiGraph.

Customizing Data Retrieval

You can specify which entity and relation properties to load by modifying the session attributes:

• APISession.relProps: (Default: ['Name', 'RelationNumberOfReferences'])
• APISession.entProps: (Default: ['Name'])

Detailed documentation on property names and object types is available in the Documentation folder.

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Getting Started

Prerequisites

To use these APIs, you must obtain credentials for the respective Elsevier services:

• Pathway Studio (Resnet): Professional Services
• Reaxys: Contact Sales
• Embase & Pharmapendium: Visit the Elsevier Developer Portal. Swagger documentation is available here.
• Text-Mining API: Elsevier Text Mining

Configuration

1. Locate the APIconfig.json template in the ElsevierAPI folder.
2. Input your login credentials for each respective service.

Installation

All SDK requirements are listed in requirements.txt file

pip install -r requirements.txt

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Integration Tools

• Neo4j support Use the PSnx2Neo4j.py module to import Resnet data retrieved via the API directly into a local Neo4j server instance for advanced graph visualization and querying. APISession parameters now support Resnet graph retreival from Neo4j database with references stored in Postgres database. Set parameter useNeo4j to True to envoke this option.