Introduction

The OpenEye Python Cookbook is a collection of solutions and practical examples for solving cheminformatics and molecule modeling problems using various OpenEye toolkits.

To install OpenEye’s Python package, please see instructions in the Getting Started with OpenEye Python section of the main OpenEye documentation.

We expect that you are familiar with at least some Python and have used OpenEye toolkits before. The main purpose of this documentation is to illustrate that by combining various OpenEye toolkits you can solve a wide range of cheminformatics and molecular modeling problems.

The OpenEye Toolkit Ecosystem

Outline of Recipes

Each recipe in this documentation is divided into the following sections:

• Problem - brief description of the problem you are trying to solve

• Ingredients - the list of the OpenEye toolkits you need to solve this problem

• Difficulty Level - each recipe is put into one of the following categories:

  novice

  Requires very little prior knowledge.

  

  intermediate

  Requires a fair understanding of the toolkit libraries that are used to solve the problem.

  

  expert

  Requires a deep understanding of the toolkit libraries that are used to solve the problem.

  

• Download - most recipes provide complete python code that you can download.

  Download code

  xlogp2pdf.py

• Solution - code snippet(s) with detailed explanations about how to solve the problem

• Usage - example of utilizing the provided Python script

• Discussion - further discussion and additional code snippet(s) to solve similar problems

• See Also - links and references to other OpenEye toolkit manuals