Scientific software is often dependent on many disparate libraries of code written by multiple people over the course of decades. Legacy code is often not updated for fear of breaking already working code, which often drives the choice of programming language. This forces future developers to rely upon and utilize outdated and/or proprietary programming languages which can hinder scientific development and prevent the use of more advanced software techniques or tools. This tutorial will focus on utilizing Python to incorporate and tie together your existing IDL and/or Matlab code. You will learn techniques to build processing pipelines that can seamlessly tie together these three languages, allowing you to work with legacy code as well as code from other team members. Each individual unit of code can be encapsulated into a generic Python wrapper which will enable you to gradually replace or update portions of your pipeline without disrupting other components. For example, a Matlab unit may be swapped out for an IDL or Python unit, etc.